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                  Thursday, April 25, 1996

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              The    Committee        convened     in   the   Clark

Room,   Holiday     Inn   Capitol,       550   C   Street,    S.W.,

Washington,    D.C.,      at   9:00    a.m.,     Dr.    Timothy   D.

Mount, Chairman, presiding.


              TIMOTHY D. MOUNT, Chairman


              BRENDA G. COX

              JOHN D. GRACE

              CALVIN KENT

              GRETA M. LJUNG

              RICHARD A. LOCKHART

              DANIEL A. RELLES

PRESENT (Continued):




            RENEE MILLER

            YVONNE BISHOP

            MARY HUTZLER

            JAY HAKES

            DOUGLAS HALE

            ART HOLLAND


            LOUISE GUEY-LEE

            JOHN CYMBALSKY

            ERIN BOEDECKER

            JERRY COFFEY

            INDER KUNDRA

                  C O N T E N T S


Presentation by Jay Hakes               6

Presentation by Yvonne Bishop          34

Presentation by Art Rypinski           43

Presentation by Richard A. Lockhart    61

Presentation by Douglas Hale           84

Presentation by Art Holland            97

Presentation By Timothy D. Mount      112

Presentation by John Cymbalsky        148

Presentation by Erin Boedecker        159

Presentation by Campbell Watkins      168

Presentation by Jerry Coffey          194

Presentation by Inder Kundra          240

Presentation by Greta Ljung           245

1                            P R O C E E D I N G S

2                                                                 (9:07 a.m.)

3                      CHAIRMAN        MOUNT:         Let's         begin      this

4    meeting.

5                      My     name     is    Tim     Mount       from   Cornell

6    University.

7                      This       meeting    is    being     held    under     the

8    provision     of       the    Federal       Advisory     Committee        Act.

9    This   is    an    American       Statistical          Association,       not

10   Energy Information              Administration Commission, which

11   periodically provides advice to the EIA.

12                     The    meeting        is    open     to    the   public.

13   Public comments are welcome.                  Time will be set aside

14   for comments at the end of each session.                           Written

15   comments are welcome and can be sent to either ASA

16   or EIA.

17                     Non-EIA        attendees        should        sign       the

18   register     if    they       wish     to    receive    a   copy     of   the

19   meeting highlights.

20                     In commenting, each member of the public

21   is asked to stand, state his or her name, and speak

22   into   the    microphone          at    the     podium      there.        The

23   transcriber will appreciate it.                       Also, members at

1    the table need to speak loudly, Committee members.

2                  We did change the schedule originally,

3    but I think we can go back to the standard beginning

4    where we introduce members of the Committee, and

5    hopefully by the time we've done that, our first

6    presenter will be here.

7                  So let's start going around.

8                  MR. HAKES:    Jay Hakes, EIA.

9                  MS. BISHOP:    Yvonne Bishop, EIA.

10                 MS. MILLER:    Renee Miller, EIA.

11                 MS. LJUNG:    Greta Ljung, MIT.

12                 MR. RELLES:    Dan Relles, RAND.

13                 MR. GRACE:      John Grace, Earth Science

14   Associates.

15                 MR. LOCKHART:      Richard Lockhart, Simon

16   Fraser University.

17                 MR. WATKINS:    Campbell Watkins, LECG.

18                 MS.   COX:      Brenda    Cox,     Mathematical

19   Policy Research.

20                 MR.   SKARPNESS:         Bradley    Skarpness,

21   Battelle.

22                 MR. CHATTERJEE:    Samprit Chatterjee, the

23   New York University.

1                 CHAIRMAN      MOUNT:        And    members      in    the

2    public there?

3                 MR. GROSS:         John Gross, EIA.

4                 PARTICIPANT:        (Inaudible) EIA.

5                 MR. WEINIG:        Bill Weinig, EIA.

6                 MR. WOOD:      John Wood, EIA.

7                 MR. CRONE:         Tom Crone, EIA.

8                 CHAIRMAN MOUNT:           Thank you.

9                 What else have I got here?                 There will

10   be a luncheon for the Committee and invited guests

11   at 12:15 in the Lewis Room, and breakfast tomorrow

12   will be in the Lewis Room, Committee members.

13                So    I    think    that    we    now    turn    to   an

14   important address from the boss of EIA, Jay Hakes.

15                MR. HAKES:          Well, first I thought I'd

16   deal with a question that most of you are probably

17   most   interest   in,    and    that    is    why    your   gasoline

18   price is so high.

19                (Laughter.)

20                MR. HAKES:         The reason is we have a very

21   cold winter.      That put a lot of pressure on heating

22   oil stocks, which were low anyway.              There's a lot of

23   uncertainty in the world market because of Iraq.

1    It's not that the Iraq capacity is needed to create

2    adequate supplies.                  It's that people are reluctant

3    to bring on supplies if they think Iraq is going to

4    come out and the price might go way down.

5                        Also there are some refinery problems in

6    California now which are really having a big impact

7    out there, and also demand is rising very rapidly to

8    record levels, partly because as people continue to

9    drive       more    and    more,       it's     not      being   offset   by

10   vehicle efficiency like it had been in the past.

11                       So the combination of all those things,

12   plus    the    usual       spring      run-up      you    get    every   year

13   anyway, has created a pretty volatile situation that

14   will probably continue for another month or two, but

15   when you average out the whole year, probably we'll

16   still be fairly low by historic standards.

17                       Fortunately I did not write a detailed

18   speech out yesterday because if I had, I would have

19   had    to    change       it    last    night      with    regard   to    our

20   budget,       but    let       me    start    by    talking      about    the

21   electronic revolution, and this is something we've

22   talked about before.

23                       It is hard to remember that only two

1    years ago this was sort of an idea in a few people's

2    minds.     We did not have a real electronic presence

3    out there, and we now have a Web site that is not

4    fully    completed    yet,    but    is   a    very    usable,   user

5    friendly vehicle, and it's interesting to watch the

6    usage trends.

7                    When we started off last summer, we were

8    getting about 100 people per day coming out of the

9    system.        We   don't    measure      it   by     hits,   but   we

10   basically measure the number of people, subtract our

11   own employees, and use that as our metric, and we're

12   now up to 800 people a day using and visiting the

13   Web site.      That's been a very steady increase month

14   by month, except for December when the holidays, the

15   weather, government shutdowns caused the numbers to

16   go down.

17                   But if that trend continues, we see, you

18   know, tremendous usage.

19                   Another metric that's a good one for us,

20   I think, is the number of files that are downloaded

21   off of our system.           Last summer that was running

22   about three to 4,000 files being downloaded a month.

23   It's     now   up    to   about     14,000     data    files     being

1    downloaded a month.

2                   Some       of     these     are     people    who        are

3    converting from hard copy usage to electronic, but

4    many of them seem to be new customers.                      There's a

5    very    good   cross-section        of   people      from    industry,

6    government, academia, the general public.                    A lot of

7    users    still      are    not     ready     yet     to     do    things

8    electronically, but I keep repeating this.                        A high

9    school student in Boulder, Colorado, who's got a

10   modem has better access to energy information than

11   any individual in the Forrestal Building had two

12   years ago.     That's a major revolution.

13                  In     fact,      that    student     can     be    in    a

14   foreign country, as well, because we do have a fair

15   amount of usage.

16                  Our latest product is a CD-ROM that has

17   now gone through data testing, and it's generally

18   available to the public.            It sort of duplicates what

19   is on the Internet, but the difference is it's just

20   a lot faster and has more features.                 It has a search

21   feature on it where you can type in any word or

22   phase, and in 15 seconds it will take you to every

23   page in our current publications where that word or

1    phrase is mentioned with that word highlighted.

2                     It's   really    a   tremendous       asset    for    a

3    non-energy specialist.            For instance, if you're a

4    staffer on the Hill and you deal with energy in

5    several other substantive areas and your boss asks

6    you to write a speech or find some information on a

7    specialized energy topic, you can now do that in a

8    couple of minutes, and there's really not too much

9    that you couldn't do using that.

10                    I've   often    said,     too,    that    this       is

11   tremendous.       It saves us all of the embarrassment

12   because I don't care who you are.                 There's no one

13   that   knows     all    the   acronyms     and    the     jargon      in

14   energy, but who wants to admit it, you know?                   So now

15   you've got this CD-ROM, and you whip right through

16   there, and you can find the definition to anything.

17                    So this electronic revolution has had a

18   major impact.       It is a tribute to a lot of employees

19   at   EIA   who    spent   a     lot   of   time   on    this.         It

20   ultimately has very little incremental cost because

21   you can start to prepare your documents digitally to

22   begin with, and so having them available to transfer

23   into this electronic form is important.

1                    And also particularly with the Web, for

2    you   economists,       it's      about      the      only    thing        I   can

3    think   of    the     government         can    give     to    people          that

4    doesn't have a marginal cost.                      Once we provide it

5    100 people off of our server, we can provide it to

6    100 million people and the cost to us is the same.

7                    That's       a    new    way    of      thinking         because

8    everyone wants us to cost out everything these days,

9    and I'm trying to convince people that information

10   is a free good, ought to be treated as such.                               After

11   all, the Census Bureau was in the Constitution.                                 So

12   I think the electronic revolution will help us, and

13   frankly, it's a good selling point to members of

14   Congress      because       it    sort    of     shows        if    usage       is

15   getting      that    high,       it   starts       to    show       them       that

16   people in their district, in their state will use

17   it.

18                   I     can    also     take      the     CD-ROM       when       I'm

19   showing      them      and       type      in      cities           in     their

20   congressional district, and, boom, they get all of

21   the   energy        information         about    that        city    if        it's

22   mentioned, which it usually is if it's a large city.

23                   The second item is quality management.

1    Let me get one prop here.                I don't know if Renee put

2    this in the package, but for those of you who are

3    interested, we can certainly get you one by request.

4                    This       is   our     application          for   the   1996

5    energy   quality       award,      and        we    just     finished    this

6    document this week.             So it's very fresh information,

7    and basically what it talks about is the things that

8    we've    done    in    terms       of    quality        management,      the

9    development of performance measures, and the use of

10   cross-cutting         teams,       how        we've        addressed     the

11   electronic       revolution,            the        process     we've     gone

12   through on business reengineering, and I think that

13   is information you will find useful.

14                   Last year we did such an application.

15   This was the first time the department had had such

16   an award.       They brought in external reviewers, and

17   we   were      one    of    only      two      organizations        in   the

18   headquarters of DOE to receive a quality award.                           In

19   fact, of the various awards that have been given on

20   various quality topics at DOE, we have certainly won

21   more than any other organization in headquarters.

22                   So I think there is a lot of change

23   going    on.         Part   of     it    has        helped    produce    the

1    electronic     changes     that   we've    seen,      and    I     think

2    there will be more.

3                   I mean we are in the process of deciding

4    what parts of the business reengineering proposals

5    will be implemented, and there are a lot of changes

6    that are coming at EIA.           We expect lower resources

7    in the future.        We're under mandates to reduce the

8    number of employees, both contractor and federal.

9    So we're having to change the way we do business.

10                  On    the   personnel      front,      we    are     just

11   about meeting our personnel reductions.                    We're very

12   close.      Any week here now we'll meet our personnel

13   reductions     for    this   fiscal    year.          So     all    the

14   reductions will be voluntary this year, which is a

15   much better way to do it.

16                  Now, on the budget front, there are very

17   recent developments that seem to be positive, but

18   let me see if I can go through the complexity of the

19   federal budget system.

20                  We are now in fiscal year 1996, which

21   started on October 1 of 1995, and we still don't

22   have   an   appropriation     yet.        We   have    been      funded

23   through this fiscal year by a series of continuing

1    resolutions that provide temporary funding at lower

2    levels than the appropriated amount.

3                       We do believe, however, that within the

4    next day or two we will receive an appropriation of

5    approximately $72 million.                     This now seems somewhat

6    high   to     us    because          we've    been     operating        under   a

7    continuing resolution at the level of $65 million.

8    So we will be back up to the $72 million level, and

9    life will continue a little bit.                       People can travel.

10   We've had some promotions frozen and other things.

11                      But        the     $72    million       level,   we     must

12   remember, is a $13 million cut from the $85 million

13   appropriation            in     1995.          So     we   have     basically

14   undergone a 15 percent cut in our resources.

15                      Well,       you     say:         what   difference      does

16   that make?         The Congress directed that half of that

17   cut come out of our forecasting operations.                                This

18   was    done    at        the        very    last     minute    in   a     small

19   conference committee with no consultation with us or

20   anyone else that I'm aware of, and the argument the

21   committee      gave       was        that     they    wanted      to,    quote,

22   protect the data.

23                      So this resulted in a 35 percent cut in

1    the amount of resources available in the forecasting

2    area and sort of sent some alarm bells out that we

3    have a job to explain to the Congress what the role

4    of forecasting and modeling is.

5                     The Congress itself is a heavy user of

6    our    models,    but   what    the    difficulty   is     that   the

7    staffers in the Congress understand pretty well how

8    these models are used, how our data are used, but

9    the actual members by the time it's filtered to them

10   may not realize where it comes from or how these

11   calculations are made.

12                    And    the     appropriations      process       has

13   really changed in the last year or two.                     EIA has

14   been very popular with the staff on the Hill, and

15   they have sort of looked after our budget, but in

16   last    year's     budget      cutting    frenzy,    the    members

17   themselves got more involved in the small budgets,

18   which    they     had   not     done     before,    and    we     were

19   competing    against     the    National     Endowment     for    the

20   Arts, Indian education, other items that seemed to

21   be more visible in some ways politically, and so we

22   did not fare well.

23                    But we are also going to be cutting out

1    some data series.            We're going to be collecting less

2    detail on electric utilities.                   We'll be collecting a

3    little     more       information          on        independent         power

4    producers.           Some     of    our    technical         publications,

5    things    that       are    highly    technical,           appendices     and

6    things     like            that     will        be        available       only

7    electronically.            They will not be available in hard

8    copy.

9                     We are trying to make these cuts in as

10   painless a way as possible, but it's not an easy

11   situation.       We are having to cut.                We, for instance,

12   had to cut out our support of the Stanford Energy

13   Modeling Forum, which we've provided some support to

14   for a number of years, and we will be publishing

15   probably in the next few weeks a Federal Register

16   notice listing the cuts that have been made and ones

17   that     are     being       contemplated            to    invite      public

18   comment,       and    we    urge    full    participation           in    that

19   because we do want to consult with our users to make

20   sure    that    the    cuts        that    we    make      are   the     least

21   damaging to the work that people need to do.

22                    We are consulting closely with Capitol

23   Hill on this budget, and that's one of the reasons

1    I'm going to be slipping in and out during the next

2    couple of days, is I do have some meetings over

3    there talking with people about our 1997 request.

4                       EIA's 1997 request is for $71 million,

5    which would be pretty close to a continuation of the

6    $72 million that we apparently now are going to get

7    for fiscal year '96.           However, we don't know whether

8    we're     going          to    actually         get        that    amount

9    appropriated.         Sixty-six million of it is listed as

10   our    budget;      approximately        five    million      of    it   is

11   listed in the efficiency and renewables budget.                          I

12   think there was an attempt to show as much support

13   for energy efficiency and renewables as possible.

14   It's    the    same      money.    It     comes       directly     passed

15   through       to   us,    so   there's    no     ability      of    EE   to

16   influence this in any way.

17                      But that's where we stand.               We could get

18   a continuation budget if we're successful.                        However,

19   looking       at   the    steps   that     will       be    required     to

20   balance the federal budget over the next five years

21   and the pressures on the discretionary spending, in

22   other words, the nonentitlement part of the budget,

23   there's virtually no way that that number can be

1    held for very long, and we do expect further cuts,

2    and we're planning to be able to deal with those

3    cuts,   while       at    the    same     time    trying       to   persuade

4    people of the value of the programs to the economy

5    and to try to minimize those cuts.

6                    Certainly we do have some opportunities

7    for efficiency, but not enough to offset the levels

8    of cuts that are being discussed.                        We're basically

9    looking     ahead        to    1998    and    '99.       On    Monday     and

10   Tuesday we are spending two full days in strategic

11   planning basically to try to look ahead to what kind

12   of   organization         EIA    will     be,    what    should      be   the

13   appropriate         analysis          between     data     analysis       and

14   forecasting.          All of those things are important.

15   Should the balance in the future be more or less

16   what it is now?           Does it need to change in some way?

17                   I    think       on     the     data    side    there     are

18   opportunities for automation there where I think the

19   efficiency can be increased, and even with cuts we

20   can maintain a lot of the data.                   Analysis is sort of

21   a    very    human            activity,       less      susceptible       to

22   automation, and that's more difficult.

23                   I do think the model needs to certainly

1    be maintained in a strong way.                It will be a simpler

2    model than we might have contemplated a year or two

3    ago.        We've    had    to    pull   back       on    some    of     the

4    development work on the model.                     We've also pulled

5    back on the PC version of the NEMS, but we are doing

6    some limited work in that area, but so far at least

7    the model is still a strong analytic tool and still

8    more used than ever before.

9                      I think the best thing at this point may

10   be, Tim, if it's all right, to take questions.

11                     CHAIRMAN MOUNT:        Sure.

12                     MR. HAKES:         And see what comments and

13   questions people have.

14                     CHAIRMAN MOUNT:        Sure.

15                     MR. GRACE:      What do you need to protect

16   the data?         You made the comment that part of the

17   modeling     was    to     protect    the    data    or    protect       the

18   figures      or      something       like      that.             Maybe    I

19   misunderstood.

20                     MR. HAKES:      Well, so that the cuts would

21   not    be    as     great    in    the      data    area,    the       data

22   collection area.

23                     MR. GRACE:      Oh, I see.        Okay.

1                      MR. HAKES:        I think some of you may be

2    aware    the      Washington        Post      actually       wrote    two

3    editorials last summer about EIA because they were

4    concerned that the nation might lose some of its

5    ability to deal with shortages of supply of fuels,

6    and those editorials particularly emphasized data,

7    and I think some of the people got a little worried

8    about that.

9                      I    would   hope    that    the    next     editorial

10   from the Washington Post might mention forecasting,

11   as well.     You know, obviously there's a whole set of

12   issues   like         the   restructuring      of    the     electricity

13   area,    how      you       might   deal   with       greenhouse      gas

14   policies, all of which will rely very heavily on the

15   NEMS model.

16                     MR. WATKINS:         I was interested in your

17   comments     on       the   gasoline    price       issue,    and    if   I

18   understood that correctly, one of the problems is

19   the use of No. 2 fuel oil, and higher requirements

20   for   that     reduced        the   build-up    of     the     inventory

21   because you have all of the requirement slate on the

22   use of No. 2 fuel oils.             Have I got that right?

23                     MR. HAKES:        Yes, and secondly, I think,

1    as   I   understand      it,   the       refineries    undergo      some

2    maintenance usually when they're switching over from

3    heating oil to the spring gasoline system, and that

4    maintenance      was    delayed      a    little    bit     this    year

5    because of the colder winter, and so it's the slate

6    within refinery and the maintenance schedule.

7                    MR.     WATKINS:           The     inventory       would

8    normally be --

9                    MR. HAKES:      Right.       This is a good topic

10   for somebody to do some very good research on, and

11   we're trying to do some.             We went through the whole

12   winter with the inventories for heating oil being

13   below the low point of the historical range.                        Now,

14   that's    an    interesting     question         because    a   lot     of

15   people in industry will tell you we've gotten more

16   efficient handling inventories, and they certainly

17   have.

18                   So     maybe   it's       healthy      to   have        low

19   inventories because it reduces your cost.

20                   They    also   feel       they   can   move     product

21   around the world a lot easier.                To some extent they

22   can,     but,   for    instance,      California,       which      is    a

23   fairly    isolated      market,      takes    three    weeks       to   go

1    through the Panama Canal.

2                 So what would happen if the whole world

3    had a cold winter?     You know, it's not statistically

4    probably that likely, but there's an issue there of

5    whether we're going to get back into a more volatile

6    situation because of the much lower inventories than

7    we have seen historically.

8                 Yes.

9                 MR.    CHATTERJEE:       You    spoke    a   little

10   about using a simplified forecasting model.                    That

11   may not be a bad idea.        Sometimes forecasting models

12   do as effectively as the more complex models.

13                MR. HAKES:    Well, I guess we're a little

14   bit   conflicting   because    one   thing   you     do   is   you

15   forecast, but you're also doing "what if" scenarios

16   for purposes of legislation and other purposes.                  So

17   the ability to do "what if" scenarios is somewhat

18   diminished   with   less   detail    even    if    the    detail

19   doesn't add to or maybe even detracts a little bit

20   from your accuracy.

21                We did go through a lot of machinations

22   this year on prices of fuels.           We found over the

23   years that a lot of the projections seemed to hold

1    up pretty well in terms of patterns of consumption

2    and production, but price has been a variable, and

3    we, like many forecasters, have been on the high

4    side compared to what's happened in actuality, and

5    we've    lowered      very   substantially    this    year       our

6    projections for natural gas, and I think that was a

7    good thing to do.

8                   Yes.

9                   MR. GRACE:       Along the same lines, with

10   the increasing support you've received by use of

11   your Web site, and I've been one of the people who's

12   been on there --

13                  MR. HAKES:      Good.

14                  MR. GRACE:       -- is the decision to pull

15   back on the PC NEMS perhaps kind of contrary to that

16   philosophy, that if you had greater accessibility to

17   the models via a platform that was more popularly

18   available, that you might be able to build the same

19   sort of support on the modeling side that you're now

20   building on the data side through the electronic

21   access afforded through your Web site?

22                  MR. HAKES:      Yeah, I mean, that's a good

23   point.     I   think,    you   know,   when   you    talk    a    35

1    percent cut, you sort of get a little desperate, and

2    you sort of cut what you can.

3                    You know, ultimately, too, to the extent

4    that    our    biggest    customer    is     the   Congress,       they

5    probably are many years away from having the ability

6    to operate even a PC NEMS.            We'll have to run it for

7    them.    So in terms of our key customer that's going

8    to    make    the    appropriations    decision,       it   probably

9    wouldn't make a huge difference.

10                   I hope we can get that back on track

11   because I think it is part of the vision we have of

12   really sort of allowing people to get in there and

13   use    the    stuff    themselves,     you    know.         With   the

14   smaller number of people that we have that's almost

15   a necessity.

16                   Now, you know, two years ago we were on

17   a mainframe.         We're now down to RISC work stations,

18   and the PC thing would be nice.

19                   Yeah, Dan.

20                   MR. RELLES:     Fifteen percent is a lot,

21   and presumably there should be a lot more pain to

22   describe      than    you've   described       here,    especially

23   since I think any staffer or any Congressman, if he

1    doesn't hear that there's a lot of difficulty this

2    has    caused,    will      say,     "Well,      okay.         I'll    do   15

3    percent next year until we hear about it."

4                     (Laughter.)

5                     MR.       RELLES:         Now,        presumably           the

6    voluntary retirements are not going to be able to

7    absorb another 15 percent, but what about the users?

8    Are     many   of      them   complaining         about    the        reduced

9    volume or quality or availability of data?

10                    MR. HAKES:        We don't play the Washington

11   Monument game like many people do in town, that the

12   first thing we'll cut is the most valuable thing we

13   do, and I think we've done a good job of becoming

14   more efficient.

15                    I think there has been a lot of pain

16   internally, but I think we've shielded a lot of our

17   customers      from    it.     You       know,    in     the    government

18   shutdown, we did not shut down at any point because

19   we had carryover money.

20                    The next set of things are going to be

21   very    tough.         I    mean     I   think     things        like       the

22   voluntary reporting on greenhouse gas, which is one

23   of Art's programs, is going to be tough.                                We're

1    going   to    do    like     oil    reserves    every         other    year

2    instead      of    each    year    in   terms       of    the     detailed

3    analysis.         Our     consumption     studies         are    going   to

4    probably be in four-year cycles rather than three-

5    year cycles.        That in and of itself saves sort of a

6    bit of money.           Now, is that enough to get people

7    jumping up and down and screaming?                   Probably not at

8    this point, but, you know, if you, say, reduce your

9    sample size so you can't do regional analysis, you

10   know, again, is the average person in the street

11   going to jump up and down and say, "I want regional

12   analysis"?         Probably not.          People like you might

13   yell and scream, and that might be a good thing.

14                     I guess my preference would be on like,

15   say,    consumption         studies      is    to        do     them   less

16   frequently        to      preserve      some    detail          and    some

17   regionality, you know.             So that's one way to save.

18                     In a sense, the next five million is

19   almost tougher than the first 15 million because

20   it's just the nature of things and how rapidly you

21   have to change, but it's certainly tough.

22                     I mean, in the modeling area we had some

23   projects going, say, on the international natural

1    gas model, refinery model that we had spent some

2    money on over the years that we had to stop in the

3    middle   of   the    work       and   suspend       the   project,       and

4    that's very irrational because you're wasting money

5    you've already spent.

6                  But when the Congress sort of targets

7    the cuts that way, you know, we don't really have

8    any choice at that point.

9                  MR.        RELLES:           Yeah.      Do     you    think

10   electronic media are going to be a big money saver

11   for you in the future by not having it published in

12   paper?   You'll be able to save a fair amount?

13                 MR.        HAKES:       Well,    we    spend    about       $1

14   million a year on paper.                   So there is definitely

15   some money to be saved there.                In a budget our size,

16   that's significant, but I think what it allows us to

17   do is talk about expanding our customer base without

18   increasing cost, and so it saves some money.

19                 Now, of course, automation is not just

20   dissemination.           It   may     be   collection;       it    may   be

21   processing.      There's a lot of things that can be

22   automated.          So    the     savings      of     automation         and

23   computers, in general, probably is much greater than

1    just the cost of saving paper and dissemination.

2                       But, you know, to the extent we can do

3    that, we can absorb some cuts.            What we're trying to

4    do is set aside money each year, too, for investing

5    in   this    technology.        You    know,    we're      trying   to

6    think, well, where do we need to be in three years.

7    What kind of training do we need to get to that

8    point?      What kind of technologies do we need?

9                       We're going to try to standardize a lot

10   more   the    software     that's     being    used   so    that    our

11   offices      communicate     more   easily     with   each    other.

12   Maintenance costs go down.             We project that getting

13   totally      off    the   mainframe    will    probably      save   us

14   about $2 million, net savings.

15                      So, you know, there are a lot of things

16   that can be done, and you know, we plan to do those

17   anyway.      So if we can keep continuation for a year

18   or two to sort of catch up from last year, I think

19   we can maintain a very high level of service.

20                      MR. GRACE:   I do a lot of work with the

21   U.S. Geological Survey, and in the last few years

22   they have started to go a direction -- and I don't

23   even know what the acronym stands for -- creating

1    CRADAs.     CRADAs are essentially allowing the Survey

2    to take private sector money as income and provide

3    something      like     proprietary        services,     but   not

4    exactly.      It's somewhere in between, but it's a new

5    source of income for them.

6                   And especially when I think about, for

7    instance, the reduction in the rate from one year to

8    two of collecting data on oil and gas reserves, is

9    there a possibility within the legislative confines

10   of the EIA to set up partnerships with the private

11   sector to augment your budget in a way that would

12   allow the provision of services that might have a

13   specific client base out there that's willing to

14   pay?

15                  MR. HAKES:           Well, I think it's worth

16   discussing.     I mean we have CRADAs at the Department

17   of   Energy    in   a   lot   of    our   technical    development

18   areas where there are partnerships with industry.

19   It's very interesting.         Those CRADAs are under great

20   attack in the Congress right now.

21                  MR. GRACE:      Are they really?

22                  MR. HAKES:          They're viewed as, quote, a

23   subsidy to business.          You know, the current rhetoric

1    and ideology is very interesting and how things get

2    interpreted.

3                   I must say that there's a side of me

4    that's much more comfortable making the public good

5    argument and continuing to ask for taxpayer dollars

6    than    to   get     into     the   issue     of     proprietary

7    information.       You      know,   Statistics      Canada,    for

8    instance, copyrights their information.               That does

9    create a different ball game.

10                  I personally would not like to do that

11   because if you look at the history of energy in this

12   country, one of the big issues in the '70s was the

13   public didn't trust industry data.              It's been very

14   beneficial   to    the   industry,      as   well    as   to   the

15   environmental      community,        consumers,       and      the

16   government to now have some data that's viewed as

17   being   objective.       I   mean   I   don't    think    anybody

18   really questions our objectivity, and it's now so

19   assumed that people don't talk about it anymore.

20                  But there is in this country a suspicion

21   of the oil industry, for instance, which, you know,

22   whether it's justified or not, it's sort of there.

23   So if you start saying, "Okay.               Well, we've got

1    these    partnerships       and     they're     giving      us     some

2    money," and all of that, I'm not saying we couldn't

3    handle it and I'm not sort of taking it off the

4    table, but I feel more comfortable arguing for --

5    you know, the government has something.                I think the

6    government    has     the   responsibility       to   provide       the

7    base information, and it's very interesting because

8    when    the   World     Bank      goes   into    a    lot    of    the

9    developing nations, they are urging them to set up

10   and EIA type organization, and so we are visited

11   frequently by people from other governments around

12   the world saying, well, how do we do this.

13                    The reason is, one, the investors will

14   invest more in a high information system.                   You know,

15   low information equates to risk.                Risk relates to

16   higher rates of return, more reluctance to invest.

17                    The other thing the World Bank feels is

18   that    public    officials    will      make   better      decisions

19   about energy if they have data to deal with.                      Those

20   are all public reasons to have this kind of data.

21   It would be sort of ironic if in spreading our data

22   out, helping other countries set up this system that

23   we ourselves sort of lost it.

1                   But that's a question I get a lot.               The

2    Paper Work Reduction Act, of course, which is part

3    of the framework under which all of the statistical

4    agencies operate, says that our basic system is to

5    charge      only     for        the   dissemination       of    the

6    information.       It costs so much to print a document.

7    That's what the cost of the publication is, not our

8    collection cost.

9                   And so to move away from that would be a

10   pretty major change, and I have done some fairly

11   superficial        look    at    Canada,     New    Zealand,    and

12   Australia, and some other countries that have tried

13   to move more into the cost recovery phase, and I'm

14   not sure that they really recover costs at the level

15   that it's perceived that they do.                   I think, you

16   know, we have several hundred thousand dollars a

17   year that goes into the federal treasury from the

18   sale   of   our    publications.        So   we    at   that   point

19   recover some cost, but I think information because

20   it has such low marginal cost, it's very difficult

21   to get it to pay for itself.

22                  Well, we thank you all.             This year is a

23   strange year because I think we have stability on

1    the Committee.           I don't think there are any new

2    members to announce, but it's good to see you all

3    back again, and I'm looking forward to the exchanges

4    on this.

5                   These critiques that you have done have

6    been very helpful to us, and we really appreciate

7    the help that you're giving us.

8                   CHAIRMAN MOUNT:          Thank you, Jay.

9                   I certainly am glad to hear you saying

10   that   this    is   an    important      public    good    that   you

11   provide.      You know, I really do agree with that, and

12   I think it's truly impressive to see the number of

13   people and the new types of people that are being

14   able to get access to data on energy now through the

15   Internet.

16                  So   I     think   the    next     item    is   Yvonne

17   Bishop to tell us how the EIA responded to the last

18   meeting.

19                  MS. BISHOP:        Well, he said a lot of the

20   things I was going to say.

21                  (Laughter.)

22                  MS. BISHOP:        On the last meeting Perry

23   Lindstrom spoke about the renewables in the AEO.                   I

1    had a great big package from him responding to the

2    comments.     I think I'll give it to the persons who

3    made the comments rather than repeat them all here.

4                      The     difference   in     the   forecasts      for

5    renewables in '93, '94, and '95 was queried, and he

6    points out that although the differences are large

7    relative     to     the     specific   market,      they're       small

8    relative     to     the     total   energy     picture,     and    the

9    reasons    for     the     differences      include   not     only   a

10   dynamic industry, but changes in the model as well.

11                     And ethanol and biomass are not really

12   renewable.        They are agreed that, say, they would

13   like to use this broad definition because these are

14   treated the same way in a policy perspective.

15                     The side cases taken as a whole give a

16   likely range of renewable penetration rather than a

17   one point estimate.               They feel that what they're

18   really trying to do is give plausible ranges for

19   what might happen in the future.

20                     Doman     and     Peabody     spoke       on     the

21   international energy outlook.               They much appreciated

22   Campbell Watkins' comments.              They tried to include

23   as many of them as they can.                 They've discontinued

1    the use of sensitivity ranges and replaced them with

2    two    economic         group     scenarios,       and        they    have

3    described the method by which the scenarios were

4    developed.

5                     The 1996 outlook, which will be here any

6    moment,       includes     comparisons          with    the       previous

7    year's    projections       and    has    --    which    is    what     was

8    suggested -- and has added a lot of new features.

9    They    now     include    exports       from    the    former       Soviet

10   Union, China's nuclear expansion, improved estimates

11   of     energy     intensities,       and        there's       a      better

12   electricity demand model, and they're planning on

13   including India in the whole story.

14                    The other issues concerned largely data

15   collection        and      dissemination          in      a       changing

16   environment.       As Jay mentioned, we will address some

17   of the issues raised in the strategic planning next

18   week, and it was suggested a new mission statement.

19   We may get around to that.

20                    We need to define what is the core data,

21   and we need to consider the issues of integrating

22   service.

23                    In terms of how much we learn from our

1    customers,   we've     again    had     a    small    survey      of

2    telephone customers with much the same results as

3    last time.   We've mailed questionnaires and included

4    cards in publications for various groups of readers.

5                 For   the   Weekly    Petroleum        Status      Group

6    report, of the 200 who responded, 70 percent have

7    computer   capability,    and     nearly      all    of   that    70

8    percent said they don't want paper anymore.                  So we

9    took them off the mailing list.

10                (Laughter.)

11                MS. BISHOP:       We have had many favorable

12   comments spontaneously on the Web site, and we are

13   currently discussing development of a questionnaire

14   for electronic users to get their opinions of the

15   strengths and weaknesses of the current offerings.

16                The   Information        Products      and   Services

17   Committee has begun to analyze Internet accession.

18   I got a different number than you.             I've got 90,000

19   a month, but anyhow, it's growing very rapidly, and

20   --

21                MR. HAKES:    That's probably kids.

22                MS.     BISHOP:      No,       sessions,     and    now

23   totals 400,000.      Anyway, whichever number is right,

1    it's getting bigger.

2                   They can determine by looking at these

3    the type of user, which files were accessed, the

4    number   and   order     of    the     files      accessed,     and   the

5    number of return visits.                So this will give some

6    indication of what's popular.

7                   We      were     planning          to      present     this

8    analysis in Chicago, but have not been able to make

9    any firm travel plans.

10                  (Laughter.)

11                  MS. BISHOP:           On business reengineering,

12   the executive sponsors reviewed the team's plans and

13   implementation        suggestions.           As    of     Tuesday,    they

14   came out with a summary of their decisions, and they

15   proposed some pilot efforts and some reallocation of

16   resources.       No     doubt    details          will    be   available

17   later.

18                  Meanwhile         some         of         the    business

19   reengineering enthusiasts have been thinking about

20   the issues, and two of them will be talking about

21   the more statistical issues today.                     Nancy Leach will

22   be   talking     on     performance       statistics           for    data

23   process,   and      Renee     Miller    on     the       important,   but

1    unresolved, issue of how we measure quality.

2                     The      issues   arose    because         we   recognize

3    that if you're trying to improve the efficiency of

4    data    processing,        you'd    better      have     some      measures

5    about how efficient you are, and the question of

6    quality arose because we had                    goal of speeding up

7    how quickly we got the information out, and we were

8    anxious that this would not be a cost of the quality

9    of the data.

10                    In general, many staff recognized that

11   reduced resources implies a need for training for

12   those      who         take        on      more        or        different

13   responsibilities.           Howard Magnus has been around to

14   all of the offices and collected the perceived needs

15   for training and is now trying to arrange seminars

16   and workshops on these topics.

17                    I   have      a   list   of    the    topics,       and   I

18   thought    that      if    I   handed     out     this      list    of   the

19   topics, maybe the Committee would help by suggesting

20   persons who might help us by leading a seminar or

21   workshop in these areas.

22                    We've been doing some of it in house.

23   Doug Hale has been organizing a training seminar on

1    electricity   pricing     based    on     Schweppe's      book   on

2    electricity spot prices, and Ruey-Pyng Lu has been

3    conducting introductory statistics courses for those

4    who felt they needed that.

5                  And   I   think    that's    all    that    we   have

6    today in terms of follow-up.         I'll hand those things

7    out now.

8                  MR.   RELLES:       You     mentioned      telephone

9    surveys and the Internet in the same sentence, and

10   it actually made me think of an experience that I

11   had recently, which I must say was rather annoying,

12   but it might be of use to discuss it.              I was on the

13   Internet trying to get some stock market information

14   from Scudder, and before it would let me get into

15   some of the more interesting stuff beyond its home

16   page, it asked me a whole bunch of questions, and I

17   couldn't   get   any    further    without       answering     some

18   questions.

19                 (Laughter.)

20                 MR. RELLES:       Now, I mean --

21                 MS. BISHOP:       That's pretty annoying.

22                 MR. RELLES:       But actually --

23                 PARTICIPANT:      Did a broker call?

1                     MR. RELLES:        But actually I didn't mind

2    it all that much because I really did want to get

3    it,    and   I   figured,      well,   that's    the   cost    of   my

4    getting information, and it was phrased in a neutral

5    way.     You need a password to get in there.                       So,

6    okay, so I'm going to make up a password, and then

7    it asks you your name and where you live and a few

8    things like that, but that might be a device that

9    the EIA could consider using to try to survey some

10   of its customers, especially looking for ways to cut

11   costs.       Instead    of   making     phone    surveys    all     the

12   time, you've got 14,000 accesses.                 If I'm asked to

13   answer some questions once and that registers me

14   with you and you know a lot about me, that could

15   very well be a useful device for collecting that

16   kind of data.

17                    I know it goes against the grain that

18   information should be free because I now have to

19   spend some of my time answering your questions, but

20   on     the   other     hand,     given     the     value      of    the

21   information,      I    think    a    lot   of    people    would    be

22   willing to do it.

23                    MS. BISHOP:        The telephones -- sorry.

1                   MR.    HAKES:        I     think     I    can   respond

2    specifically to that.          On the Web site there is an

3    icon called "feedback," where we encourage people to

4    do it, and we do get some data.

5                   Now, the Department of Agriculture has a

6    system   that's      similar   to   what        you're    describing,

7    that you basically are giving it, and it sort of

8    hits you up front when you're identified as a first-

9    time user, and we're going to take a look at that.

10                  I do think that you have to have a very

11   easy bypass for it because a citizen does have the

12   right to come into that anonymously, I believe, and

13   I   think     you    would   have       legal     problems     if   you

14   required them to fill out a form, but I think we

15   could    do     a     better    job        of      capturing        that

16   automatically and maybe purging people more than the

17   current system does.

18                  MR. RELLES:       Yeah, I actually saw your

19   attempt to request information, and I bypassed that

20   very quickly.

21                  (Laughter.)

22                  MR. HAKES:       We appreciate your concern

23   about respondent's burden.

1                   (Laughter.)

2                   MR. HAKES:    You of all people.

3                   MR. RELLES:     Hey, I'm counted as one of

4    your users.

5                   MS. BISHOP:     Still the telephone service

6    is for the people who call in on the telephone.                  I

7    should have made that clear.           We still get thousands

8    of phone calls asking for information, and at the

9    time   they   apparently     say,    "Would   you   mind    if   we

10   phone you back?"

11                  MR. HAKES:     The problem is a lot of our

12   phone users are playing the commodities market, and

13   you    can   tell   when   you're    interviewing    them    that

14   their mind is elsewhere, and they don't want to be

15   distracted for too long.

16                  CHAIRMAN MOUNT:       So we move to the first

17   presentation of the results of the greenhouse gas

18   voluntary reporting program by Art Rypinski, Office

19   of Integrated Analysis and Forecasting.

20                  MR. RYPINSKI:        Okay.   Good.   We have the

21   opening slide.

22                  The greenhouse gases voluntary reporting

23   survey is regrettably not a household word.                  So I

1    thought that it would be useful to provide you with

2    some   background      so     you     can     figure      out      what       this

3    curious animal is.

4                    Can I have the next slide, please?

5                    We    made    a     presentation          to       the    ASA   a

6    couple of years ago when we were first developing

7    this    program        that       stimulated         a        very        lively

8    conversation, including Mr. Coffey of the Office of

9    Management      and    Budget,        who     argued,         if    I     recall

10   correctly,      that    if     this     was        not    a     statistical

11   survey, that OMB if presented with it was under, of

12   course, no obligation to approve it.

13                   So I just thought I would come back now

14   and talk a little bit about now that we've completed

15   our first reporting cycle what this program is, what

16   we think we've learned, and you know, where we're

17   going from here.

18                   The    first        thing     to     note       about         this

19   program    is   that    it's      a    statutory         program.             It's

20   specifically      required        by    Section          1605(b)         of   the

21   Energy Policy Act, which, no, I don't expect you to

22   remember that particular section of what is, after

23   all,   a   telephone         book      size    document,            but       what

1    Section     1605(b)      does       is     it     requires       that        the

2    Department of Energy will, in cooperation with the

3    Environmental Protection Agency, provide a mechanism

4    by which entities -- and that's the word in the law,

5    "entities"    --       may    report,      and     this    is     a    quote,

6    "annual reductions of greenhouse gas emissions and

7    carbon    fixation           achieved      through        any    measures,

8    including      fuel           switching,          forest        management

9    practices, tree planting, use of renewable energy,

10   manufacture       or     use        of    vehicles        with        reduced

11   greenhouse     gas       emissions,         appliance           efficiency,

12   methane     recovery,         cogeneration,            chloroflurocarbon

13   capture and replacement, and power plant heat rate

14   improvement,"      and       so   other     things,       too,     "and      an

15   aggregate calculation of greenhouse gas emissions by

16   each reporting entity."

17                 The Energy Information Administration is

18   required to develop forms for voluntary reporting

19   under these guidelines developed by the Department

20   of Energy, make the forms available to anyone who

21   wishes    them,    and        put    the        data    received        in    a

22   database.    So that's what we've been doing.

23                 The law was passed in October of 1992.

1    The Department of Energy issued its guidelines in

2    October of 1994.             In November of 1994, we submitted

3    draft forms for public comment.                     We submitted final

4    forms to the Office of Management and Budget for

5    review     under       the     Paper     Work       Reduction     Act        in

6    February '95.          They were cleared in May, the end of

7    May.      We    spent       six    weeks     with    the      printer    and

8    putzing around with necessary changes, and released

9    them to the public in July of 1995.

10                    The       first     reporting      cycle      purportedly

11   closed on October 31st, but in practice, the actual

12   reports drifted in mostly after the deadline.

13                    The forms development process was quite

14   lengthy, as you would expect from something that

15   involved       all    of     these    items     that     I    listed,    and

16   essentially          the    problem     we    faced      was    that     the

17   Department of Energy, faced with the question of

18   building a structure for this program, answered the

19   question:       who can report?              Anyone.         And what can

20   they report?         Anything.

21                    So    whenever       the     department       came     to   a

22   binary choice, "we can do it either this way or that

23   way,"    they    always       said,    "Let's       do   it    both    ways.

1    Make it possible to do it both ways."

2                   And given this range of activities, we

3    wound up with a fairly complicated form.                  We worked

4    closely with potential reporters.                We worked with

5    the   Policy    Office      of   DOE.    We    worked     with   the

6    Environmental Protection Agency.               We went out, and

7    we developed the forms.            We pre-tested them with a

8    number   of     companies,       including      Niagara     Mohawk,

9    Houston Light and Power, General Motors, New England

10   Electric System, and that was extremely helpful.

11                  We wound up with two kinds of forms.

12   There's a long form, which is on the order of 40

13   pages.      It's     like    a   1040.      It's   divided       into

14   sections.      So no one reporter has to report all of

15   it.    You report the pieces you need to report to

16   cover your particular problem.

17                  It comes in four schedules.              The first

18   schedule asks you what you want, who you are, what's

19   your name, what's your address, what is your quest.

20                  The   second      schedule     covers   people     who

21   would like to report projects, which are actions

22   which we define following the law as actions causing

23   reductions of emissions of greenhouse gases, and we

1    have    ten     project        types     of     capture     specific

2    information     for     each    project       type.     Most    people

3    don't use very many project types.

4                    And then we have a Schedule 3, which is

5    the    aggregate       emissions       and    reductions       of    the

6    reporting entity.

7                    As we were developing the forms, and as

8    the guidelines were being developed, in April 1993,

9    President Clinton announced that he was committing

10   the    United    States        to   reduce     its     emissions      of

11   greenhouse gases to the 1990 level by the year 2000,

12   and he prepared, "he," the administration, prepared

13   a     climate    action        plan,     which        describes      the

14   mechanisms by which the administration expects to

15   use to get to that objective.

16                   Many of those mechanisms are voluntary

17   programs which encourage firms and individuals in

18   the private sector to do things that reduce their

19   emissions of greenhouse gases.

20                   We have, since this program was already

21   in train in the statutory program, we've reached

22   arrangements with many of these voluntary programs

23   that    they    will    use     the    1605     program    as       their

1    reporting mechanism.       So it becomes a means by which

2    third    parties    can    assess    the   success       of    these

3    voluntary reporting programs.

4                  We also have two kinds of forms, a long

5    form and a short form.         The short form we thought of

6    as being for individuals and households.                 It's two

7    pages, front and back, and then we have the 40-page

8    long form.

9                  We developed an electronic form, which

10   is   a   visual    Basic   application,    which     was       widely

11   used.

12                 Next slide, please.

13                 This is a list of our 108 reporters.

14                 MR. WATKINS:       Including you?

15                 MR. RYPINSKI:         Including my name.          I am

16   a reporter, and I can assure you that nothing was

17   more educational about the form than having to fill

18   it out myself.

19                 (Laughter.)

20                 MR. HAKES:       How much did you save?

21                 MR.    RYPINSKI:       How   much    did     I    save?

22   Five tons.        I'm sorry.     I admitted five tons.             I

23   saved about -- no, I saved five tons.             That's right.

1    Sorry.

2                   Next    slide.       I'll     characterize      those.

3    Yeah, good.

4                   As I said, we had 108 entities.                Most of

5    them, 96 of them, were electric utilities.                         Most

6    utilities     were     participants        in    a   DOE    voluntary

7    program for reducing emissions of greenhouse gases

8    called Climate Challenge.              Even the 96 utilities is

9    kind of an understatement of our coverage in the

10   electric    utility         industry    because      many     of    the

11   utility    reporters        reported    as      holding    companies.

12   For   example,      Southern     Company,       Cinergy,    flipping

13   back, all of those guys with the "ergy" names turn

14   out to own multiple regulated utilities.

15                  We     had    many   investor-owned         utilities.

16   We had municipal utilities.              We had G&T co-ops.          I

17   think that the evidence is that we got somewhere

18   between a half and a third of the emissions of the

19   electric utility sector.

20                  At     the     project      level,     we     received

21   information      on    645     individual         projects.        One

22   submission from GPU, which is a big utility up in

23   Pennsylvania, was 500 pages.                 So when we say 108

1    reporters, that doesn't really do justice to the

2    volume of stuff we got.

3                  Non-utility      participation        was      rather

4    modest.     There     were   three    manufacturers,      General

5    Motors,    IBM,   and    Johnson      &     Johnson;   two    coal

6    companies, including Peabody Holding, which is the

7    largest    coal   company    in     the    United   States;    two

8    aluminum     companies       that         were   reporting      on

9    perfluorocarbon reductions, a landfill methane form;

10   two forestry groups, and two households, including

11   as Dr. Watkins pointed out myself.

12                 Next slide, please.

13                 Okay.     How did they report?           Basically

14   about two-thirds of them used the long form.                 About

15   one-third used the EZ form.

16                 What we discovered is that we thought of

17   the short form as being a mechanism for households

18   and voluntary groups.        It turned out that it sorted

19   out that it actually was a mechanism for voluntary

20   burden reduction for people who wanted to report,

21   but didn't want to put in a lot of efforts.

22                 So one of our short form reporters, for

23   example, was Pacific Gas and Electric, which is a

1    large firm, and one of our long form reporters was

2    yours truly, who's a household.

3                     (Laughter.)

4                     MR. RYPINSKI:              So among the long form

5    reporters, most of them -- it actually divides up a

6    little   more        than     half     --    some        half,    two-thirds

7    reported        on      the      missions           of      their      entire

8    corporation, and about one-third reported just on

9    project, which are individual actions.

10                    Nearly everybody who filed the long or

11   actually not nearly everybody; about two-thirds or

12   three-quarters of the people who filed the long form

13   used the electronic form.                   Most people who used the

14   short    form        used     paper.         It's        like    the   burden

15   associated with flipping through those diskettes and

16   firing up the software approximated the burden of

17   filling out the form itself.

18                    Next slide, please.

19                    As you would expect, for a process that

20   turned   out     to     be     dominated       by    utilities         on   the

21   project side, most of the projects were -- that's

22   interesting.          That's a different graph than I had

23   with my -- never mind.                 Don't worry about it.                No,

1    no, no, it's right.        It's just earlier data.            That's

2    embarrassing.      The results kind of changed.

3                  Most of the projects were energy end use

4    and power generation and transmission.                  We got a lot

5    of forestry projects, carbon sequestration projects,

6    76 on that slide, and then there was what for me

7    were the most interesting projects, though not the

8    most frequent, is distribution of other activities,

9    including    particularly        a    lot    of   landfill    methane

10   capture     projects,      gas       pipeline     methane     capture

11   transport     projects,          and        halocarbon      reduction

12   projects.

13                 We    also    had      a   tenth    category    in   our

14   forms for "other," which was for projects we hadn't

15   thought of, and it turned out we got quite a few

16   "other" projects.       The most frequent "other" project

17   was coal ash recycling by electric utilities, which

18   was something I didn't know about, and basically

19   coal   ash    substitutes         for       limestone    in   cement

20   manufacture, but doesn't need to be calcite.                   So it

21   reduces the CFC emissions.

22                 By    gas,    the        number     of   projects    and

23   reductions reported were dominated by carbon dioxide

1    and carbon sequestration, but we got a fair number

2    of other gases.

3                   Let's see.       Next slide please.

4                   MR. WATKINS:      I have one question.

5                   MR. RYPINSKI:      Yes, sir.

6                   MR. WATKINS:        Gen. tran. is generation

7    and transmission --

8                   MR. RYPINSKI:      Yes.

9                   MR. WATKINS: -- of electricity?

10                  MR. RYPINSKI:      Of electricity, yes.

11                  MR. WATKINS:        Okay.     But the transport

12   is the transportation of natural gas mainly or --

13                  MR. RYPINSKI:        No, it's motor vehicles

14   essentially.        Motor vehicles, yeah.         The pipeline

15   projects fall under coal gas CH4.

16                  As you can see, I did not submit this

17   slide to OSS for approval, and I was regrettably

18   constrained     on     space      or      ingenuity   or      some

19   combination thereof.

20                  We    had   40    entity    reports,   which    is

21   people reporting the emissions of their entire firm.

22    Those emissions covered about 1.2 billion tons of

23   carbon dioxide.       That's about 20 percent of the U.S.

1    total, and included most of the largest emitting

2    firms in the United States.

3                   The biggest single emitter turned out to

4    be   General   Motors.        We   will    come   to    this     in   a

5    minute.        They     claimed    responsibility          for    the

6    emissions of their entire fleet of vehicles on the

7    road.

8                   (Laughter.)

9                   MR. RYPINSKI:        Which came to some 350

10   million   tons,       and   they   noted     that      because    the

11   average MPG of the vehicles they're putting out on

12   the road is steadily improving, that this number has

13   come way down from 1990.

14                  Interestingly,         they        didn't         claim

15   formally a reduction.         They just wanted to make this

16   point, which they did.

17                  Most of the other --

18                  MR. WATKINS:         They didn't take people

19   who drive?

20                  MR.     RYPINSKI:        Well,     General      Motors

21   claims that if you're driving a GM car, even if

22   you're    driving     more,    you're     emitting      less.         I

23   shouldn't comment on that.

1                        Most of the entities who reported used

2    what we called in 1605 speak a modified reference

3    case.       It means that emissions were higher than they

4    were in 1990, but lower than they would have been

5    had they not undertaken a number of good deeds.                          The

6    most common good deed, the big number good deed was

7    improving the availability of nuclear power plants.

8                        Twelve companies reported reductions on

9    what we call, once again in 1605 speak, a basic

10   reference case, which says that emissions were lower

11   than        1990,     and        these        firms      were     actually

12   concentrated         in    New    England,      Niagara       Mohawk,   New

13   England Electric System, Public Service Electricity

14   and    Gas,    which       is    in    New    Jersey,     and    Northeast

15   Utilities.

16                       Most projects were associated and most

17   of    the    reports       were   associated          with    these   firms

18   participating         in    various          voluntary       action   plans

19   associated          with    the       President's       Climate       Change

20   Action Plan.          I noticed the largest ton reductions,

21   and at the entity level I think we got about 60

22   million tons of carbon dioxide in aggregate claimed

23   reduction, though I would be most loath to add those

1    numbers up because of the differences in definition

2    -- yes, I see.         I'll move along swiftly.

3                     From TVA, Duke Power, and Niagara Mohawk

4    improving availability of their nukes.

5                     Next slide, please.              That's been there

6    before.

7                     We learned an awful lot.                  The biggest

8    single    accounting        issue        was    how   do    you    treat

9    wholesale       electricity           transactions.              Electric

10   utilities   tended        to     claim      emissions.      It's    very

11   interesting.           Consumers      of    electricity     tended    to

12   feel     that     they         were      responsible       for     their

13   electricity       consumption,           and    electric     utilities

14   tended to feel that they were responsible for the

15   emissions       arising     from       providing      electricity     to

16   their customers.

17                    But      then        the      question     of      who's

18   responsible for wholesale electricity transactions.

19   Different reporters came down all over the map on

20   that one.        Some said, "We're responsible only for

21   our plants, period."             Some said, "We're responsible

22   for our plants, plus our purchases."                       Some said,

23   "We're    responsible           for      our    plants,     plus     our

1    purchases net of sales," and there are all of these

2    various arguments.

3                    There was a lot of discussion during the

4    design of this program about would people gain in

5    the   system,      and    what    we   learned       is     that    these

6    reports were so complicated that with a couple of

7    exceptions, people didn't gain the system.                              They

8    worked     hard.      They     had   enough     trouble      doing      the

9    first report without doing five to figure out which

10   one made them look best.

11                   Also,     reporters         tended     to     be        very

12   conservative         in   their        claims     and        in     their

13   accounting.        They tended to follow the view "if in

14   doubt, leave it out."            If we're not sure about our

15   claim, we won't make it.               So for the most part, a

16   lot   of    the      gaining     problems     turned      out      to    be

17   nonexistent.       They turned out to be self-enforcing.

18                   There was a lot of discussion during the

19   design about fuel cycle effects.                     Reporters that

20   they didn't know about fuel cycle effects.

21                   We    discovered       that     reporters       required

22   substantial        assistance        with     calculating           their

23   emissions of greenhouse gases, even if they were

1    very sophisticated reporters.                It turns out that

2    operationally, when we were designing the system, we

3    had this notion that these reports would be filed by

4    electric utility planning offices which would have

5    sophisticated      generation         planning     models   to     run.

6    What we found out was for the most part they were

7    filed by environmental or environmental compliance

8    offices,    and    one    of    the    problems       internally   was

9    getting the data out of their operating arms and

10   understanding it before they could report it to us.

11                    The concept of emissions for individual

12   projects turned out to be very problematic in the

13   database.       If you have a power plant whose heat rate

14   you improve so that it emits less, in effect, it

15   affects the emissions of every plant on your system

16   because the improved heat rate means that it jumps

17   up in the merit order, and other plants go down.

18   People    did     all    sort   of    things     to    capture     this

19   concept     of     emissions,         and   they       weren't     very

20   comparable across companies or projects.

21                    I have a couple more slides, but I think

22   I'll just do one more.           What we were planning to do

23   next were the dates here, which are already out of

1    date as we spiral out of control here.

2                  Data validation took far longer than we

3    anticipated    in    large    part    --   partly    because       the

4    reports   straggled     in,    partly      because   the    reports

5    were far more complicated than we had imagined in

6    our   worst   nightmares,       and   partly      because,    as    I

7    alluded to earlier, the people needed a lot more

8    help than we anticipated.

9                  We're working on a database, including a

10   public use database, so that we can distribute this

11   information to the public.            This slide says April.

12   That was what I thought in March.            Now I think May.

13                 We're in the throes of writing, which is

14   what I have to go back to when I finish here, a

15   report on the data.           I think that was due to the

16   administrator a couple of days ago.                  We're still

17   struggling with it, and that will probably be out in

18   June now.

19                 We'll    be     releasing     the   1995     forms   in

20   June,   and   then    the    second   reporting      season    will

21   close in October.

22                 I guess that's where I'll end, and let

23   my discussant, whom I terribly skipped in sending

1    him materials in advance, for which I apologize,

2    have a shot.

3                     Dr. Lockhart.

4                     MR. LOCKHART:      I'm being introduced now,

5    right?

6                     I have only two transparencies and only

7    a very few remarks.            I have been struggling since

8    1993, when Art Andersen made a presentation to this

9    Committee, to understand what this survey is for,

10   and I was pretty critical of the idea in 1993, and

11   I'm still critical of the basic concept.

12                    So I put up some questions and answers.

13                    Is a voluntary survey a good idea?               I

14   don't    think    so,    and   I   haven't    changed    my   mind,

15   except that I was impressed on this slide.                    I put

16   this caveat at the bottom:           "except when the outcome

17   is nearly a census."           So if everyone fills it out,

18   then the fact that it's voluntary, the non-response

19   bias is presumably negligible, and I gather that we

20   have a very high rate of return from the utilities.

21   So   at    least    in    some     sections   we're     getting   a

22   reasonable supply of information.

23                    Is EIA doing a good job of analyzing the

1    pitfalls of a voluntary survey?         I think the answer

2    seems to be yes.      That last question, there were two

3    households     that   reported.        That's    the      other

4    household.

5                   MR. RYPINSKI:      No, the other household

6    was Carter Lewis.

7                   MR. LOCKHART:   Oh, was it?

8                   MR. RYPINSKI:   Yes, Moorhead P.S. is --

9    I'm   sorry.     Moorhead   Public    Service   is   a   little

10   muni. utility.

11                  MR. LOCKHART:      All right.         I got it

12   wrong.     I was looking to try to figure out who the

13   other household one was.

14                  In 1993, we were warned in advance there

15   would be baseline problems, that is, they couldn't

16   decide whether to do this modified reference case or

17   basic reference case kind of baseline, and I see

18   both have been done, and that does seem to be a

19   problem.

20                  Government    budget     cuts,    which      are

21   relative to imaginary future budget increases, are

22   not entirely -- not universally seen as credible,

23   and that may be -- I just don't know whether it will

1    be seen as credible here either.

2                    We were warned about other problems with

3    few   graphic        scope,        that    is,    people    reporting

4    emission reductions that didn't really occur inside

5    the country because they were forestry projects that

6    were happening outside the country.

7                    We        were   warned     about     problems      with

8    forestry and land use baselines, and we were warned

9    about this problem of many people taking credit, and

10   the example of GM taking the blame but also the

11   credit for all of the improvement in their fleet

12   mileage       performance          so     that    we'd     get      from

13   individuals         the     same    claim     that    they've       made

14   reductions if they bought more fuel efficient cars.

15   You can't count that kind of thing twice.

16                   My last two questions on the slide are

17   connected with the "is a voluntary survey a good

18   idea."    I don't think that they're generally a good

19   idea because I don't see how to make use of the data

20   in any further activity.                You don't want to add it

21   up.      So   I'm    wondering       who    the   users    of    such   a

22   database will be.

23                   I'm        concerned       that     the    answer       is

1    politicians with an ax to grind and a point to make.

2    I'm wondering what possible use can be made of the

3    data.

4                     That's really all I have to say, but I

5    do want to congratulate you on what I think is a

6    very good job of looking at the pitfalls.                        I have

7    the   idea   of     reading    or     hearing       the   speech       and

8    reading the documentation that, in fact, the EIA's

9    job here is to certify individuals as having, yes,

10   achieved     a    reduction     rather       than     maintaining       a

11   database,        which    is   sort     of     what       I'm,    as    a

12   statistician, used to commenting on.

13                    CHAIRMAN MOUNT:        Some comments from the

14   Committee?       Bradley.

15                    MR.     SKARPNESS:       It    would      have    been

16   useful if we could have had one of these long forms

17   or short forms just to see exactly, you know.

18                    MR. RYPINSKI:        I'm sorry.      I didn't know

19   to even bring them.

20                    MR. SKARPNESS:        Yeah, I know, but if I

21   could have seen them.

22                    MR. RYPINSKI:         I can get you one by

23   lunchtime.

1                    MR. SKARPNESS:       I may fill it out or

2    look at it.

3                    (Laughter.)

4                    MR. SKARPNESS:      The other thing is that

5    I used to work for TVA, and I see that they have

6    this largest tonnage reduction claim when they get

7    their    nuclear   reactors   running,       and   when   I    was

8    there, there was the potential for that, but of the

9    four reactors, none of them were running most of the

10   time, and so I'm wondering.         There is a claim there,

11   but what is actually happening?

12                   In other words, when you have one of

13   these humongous reactors on line, you can really

14   shut down a lot of the coal facilities, but when

15   they aren't on line, they're running gung-ho, and

16   you're not getting the savings that you potentially

17   could.     So it's sort of like a disconnect of what

18   actually   is    the   reductions    compared      to   what   the

19   claims are.      So that's where I think there is maybe

20   a little bit of a disconnect that's related to, you

21   know, what is actually the data telling us.

22                   Thank you.

23                   CHAIRMAN MOUNT:     Greta.

1                   MS. LJUNG:        Yeah, I think that it's a

2    good idea if you gave everybody on the Committee a

3    form and we all filled it out.                    It would increase

4    your response rate by 1,000 percent.

5                   (Laughter.)

6                   MS.    LJUNG:         You     said     you    have    two

7    individuals reporting?

8                   MR. RYPINSKI:         Yes, that's right.

9                   MS. LJUNG:       That would increase it 1,000

10   percent.

11                  CHAIRMAN MOUNT:         Brenda.

12                  MS. COX:         Oh, in Arthur's defense, I

13   have to say we have seen a form before, but I don't

14   remember what it was.            I thought it was just last

15   year.    Yeah, the program was presented before.

16                  I     really    think       that     this    issue    was

17   bagged last time, and it was bagged this time, and I

18   kind    of   understand       why,   but    I     really    think    you

19   should grapple with the difficult issue of why in

20   the world is this study being done.                 I mean it's not

21   to accomplish a statistical objective.                      I hope it

22   isn't    because     as   a     statistical         objective       goes,

23   you're going to have trouble defending it, other

1    than maybe just to gain some information that might

2    allow you to do a valid study later.

3                    In        other     words,     you        are    gaining

4    information,       et     cetera.      The    last    time       that   we

5    spoke, I just assumed that Congress was trying to

6    encourage    widespread           voluntary    efforts      to    reduce

7    emissions, and maybe that's the purpose, but I think

8    you    really   need       to     grapple    with    it    because      it

9    certainly in these days of budget cutting and not

10   being able to do things that we know are valuable

11   and important, you need to say why is this being

12   done.

13                   The data deficiencies are obvious, not

14   just the voluntary ones.               You really don't have a

15   target   population         definition,       and    you    don't   have

16   definitions for the units that report, and they're

17   vastly different.           So as a statistical database, you

18   just can't do anything with it other than kind of

19   discuss its attributes the way you did.

20                   I'm actually impressed, by the way.                     You

21   did a good job of a difficult task, but you come

22   back    to   why     is    this     being    done    and    should      it

23   continue being done.

1                   CHAIRMAN MOUNT:           Samprit.

2                   MR. CHATTERJEE:            I think one reason, I

3    think, which Brenda said, is probably right.                   It's a

4    consciousness      raising     act,      you    know,     across    the

5    industries   as      a    whole.     I    think    the    information

6    gathered may not be just applicable directly to get

7    an estimate, but I think it gives you the gross

8    aggregate figure in which we might be able to see

9    the direction and trend in which this is going and

10   also to get some kind of very broad estimate.                       You

11   know, we're not talking about standard errors or

12   anything of that, but at least a ball park figure.

13                  I   think     that's      one    thing     which     this

14   particular form might be useful.                  Another thing is

15   basically, as you say, making people more aware of

16   generating   greenhouse        gases      and    some    attempts    to

17   reduce them.

18                  MR.       LOCKHART:       I     would    like   to    ask

19   Arthur explicitly whether you think that the EIA's

20   role is principally asserted by that reductions have

21   been made.

22                  MR. RYPINSKI:         I do not.          In fact, I go

23   back to the language of the statute which mercifully

1    I    didn't    quote    in     full,      but    it     says   persons

2    reporting under this subsection shall certify the

3    accuracy of the information reported.                    EIA does not

4    certify the accuracy of the information reported,

5    and you'll notice that some of my apparently casual

6    language was, in fact, exquisitely phrased.                     I said

7    "claims,"        that          General          Motors         "claims"

8    responsibility       for     most    of   the     vehicles      in   the

9    United States.

10                   Read my lips.

11                   (Laughter.)

12                   MR. LOCKHART:          But let me turn to the

13   your     function,     the     function     of     the     agency     in

14   collecting the data.           Let me try it a different way.

15   Is the establishment of guidelines which will make,

16   provided they are followed, the individual claims

17   more credible, that is, your guidelines carefully

18   prepared enable the companies that report to assert

19   that they have made calculations in a sensible way

20   so   that     they   can     claim   more       credibility     having

21   received reductions?

22                   MR. RYPINSKI:          It is my hope that the

23   design    of   the     forms    enhances,        does    things      that

1    enhance    the     credibility      or,    at    the   minimum,   the

2    transparency of the information reported.                    That was

3    one of our objectives, to make it clear, as clear as

4    possible, what was reported and what people were

5    claiming.

6                      We do not assert that these claims, as

7    an agency, that these claims are accurate, and with

8    the various accounting definitional issues, I don't

9    think the problem is people are claiming things that

10   are not true.          I mean, you know, there's a statute

11   that says, "You shalt not make false statements on a

12   government form," and it has criminal penalties.                   It

13   doesn't matter what the government form is, and that

14   was never my sense that the reporters were making

15   statements that were not true.

16                     What does happen is that there is no

17   definition        of   who   owns       emissions,     and    there's

18   nothing     resembling       a    set     of    generally    accepted

19   emissions accounting principles that firms can adopt

20   and produce reports that are consistent even to the

21   degree of, say, financial statements, and we, in

22   fact,     know,    those     of    us     who   have   worked     with

23   financial statements, know that the comparability of

1    financial statements in detail is a little tricky

2    despite all of the effort expended on it.

3                    So the real problems are not that the

4    claims   aren't    true.    It's    that   what    one    company

5    claims, another observer might not -- one observer

6    might    find     it   credible    under     one    theory      of

7    accounting,     and    another    observer   might       find   it

8    unbelievable under a different theory of accounting.

9                    Our mission is to make it clear what it

10   is they claim so that people can form judgments on

11   those questions.

12                   CHAIRMAN MOUNT:    Cal, welcome.

13                   MR. KENT:   Thank you.

14                   CHAIRMAN MOUNT:    So if you want to joint

15   in?

16                   MR. KENT:    Just to make a comment, and

17   that is I find this discussion amusing in that it

18   almost takes me back four years ago when we were

19   talking about this particular piece of legislation,

20   and I think if we weren't on tape I could be more

21   explicit about the discussions that went on about

22   this particular "why are we doing it," and basically

23   this is one of the things that the "why are we doing

1    it" is because this was a compromise between the

2    people who wanted a certification program so that we

3    could give out gold stars or green trees or whatever

4    the badge was going to be; those that wanted to use

5    it for regulatory purposes to say, "You've got to do

6    it by so much"; and those that wanted to be able to

7    claim     that      there     were     certain       reductions        as    a

8    fallout    of       this    particular       piece    and    be   able      to

9    point that this particular piece of legislation had

10   had so much positive impact on the environment so

11   that in international conferences, and so forth, we

12   could, rather than lying directly like the Europeans

13   do, that we would be able to have a statistical

14   shroud that we could drape ourselves in when we made

15   our    outrageous          claims    for    how     effective     we    were

16   becoming.

17                       So that was basically why it came into

18   being.     The problem is that every one of the issues

19   that    you    guys    have     just       raised    was    discussed       in

20   detail,       and    basically       what     the    writers      and       the

21   promoters and the pushers on both sides of the aisle

22   of this legislation said is, "We don't care.                            This

23   is at least something we can point to," and the

1    result is it will be used for mischief.                  I can

2    assure you it will be used for mischief.

3                 And when it is used for mischief, I can

4    assure you as in the past EIA will be blamed.

5                 CHAIRMAN MOUNT:         Campbell.

6                 MR. WATKINS:      It seems to me a key here

7    is going to be how are you going to write up and

8    present this material.         I saw on the issue paper

9    that you have, in fact, a report.             Have you given

10   any thought to how you're going to or do you have

11   any   insights   on   how   you're    going   to   present   the

12   data?

13                MR. RYPINSKI:       Yeah, actually there are

14   a number of people here who are anxiously awaiting

15   that report: my bosses.

16                We propose to in the report -- basically

17   the report will probably follow the tone and the

18   spirit that will follow very much the way that I

19   have presented it, which is to play it straight and

20   say this is what people are claiming, and to discuss

21   the problems as fully as we can.

22                MR. WATKINS:       But wouldn't you want to

23   go a bit beyond that and make some kind of at least

1    qualitative comments on what it all means.

2                   MR. RYPINSKI:   Well --

3                   MR. WATKINS:    Otherwise I think it will

4    be a bit misleading to say, "Well, here is what

5    people claim."       I think you would have to alert the

6    public to what the problems are with this sort of

7    exercise.

8                   MR. RYPINSKI:     Well, I expect that we

9    will, that that is one of the things that is an

10   objective in the report.       As always, preparing these

11   documents requires a bit of art.

12                  MS. LJUNG:    I like Samprit's idea of the

13   awareness, or making people aware, but the problem

14   seems to be that nobody is aware of the survey.        Two

15   households responding, obviously the people probably

16   don't know about it.

17                  CHAIRMAN MOUNT:   Jay?

18                  MR. HAKES:    I'd like to make a couple of


20                  One is to put this in context, I think

21   you'd have to go back to the Clean Air Amendments of

22   1990   where    we    have   regulated   sulfur   emissions

23   seemingly quite successfully at much less cost than

1    was anticipated and pretty sizable reductions.

2                  The system that they used was a capping

3    system where you say there's such-and-such limit on

4    sulfur emissions, and people trade emissions.           That

5    has worked well enough that it's likely to be the

6    model for any further emissions.          So you would have

7    a system where carbon emissions are capped and then

8    traded back and forth.

9                  One of the problems with that system is

10   the issue if the baseline is the point at which the

11   legislation   is   passed,   there   is   no   incentive   to

12   reduce emissions before that point because you don't

13   get credit.     In fact, the people who voluntarily

14   reduce emissions are disadvantaged because they've

15   already taken the easy steps.

16                 So contemplating that there is a chance

17   that the Sulfur Act would be a model for greenhouse

18   gas reductions, the major emitters would like some

19   system to allow them to claim credit, and while the

20   methodology   is   a   little   "loosey-goosey"    at   this

21   point, it is transparent as could possibly be made

22   so that if one decided how one was going to do this,

23   you could make adjustments within the systems.

1                       I think the value of this system -- it's

2    an uncomfortable situation for EIA to do this in

3    some ways because it's not statistics work as we

4    know it.      On the other hand, I think it's work that

5    EIA is probably better prepared to do than anybody

6    else is.

7                       One of the things I would urge you to

8    look at this as is a definitional effort.                      I mean

9    before you measure something, you have to define it,

10   and    if    you    look   at    the    last   two   years   and   our

11   knowledge of what greenhouse emissions are, how the

12   rank    of    one    emittant      compares     to   another,      what

13   measures are used to mitigate them, we know a lot

14   more now than we did two years ago.

15                      So that if you're going to measure it in

16   the future in a way that is statistical, at least we

17   have some definitions on which to base those, and

18   Congress, if they're going to pass a law, would have

19   at least some definitions and some information on

20   which to base that law.                 Most of the environmental

21   regulation in this country has been based on pretty

22   good    guesses,       you      know,    educated    guesses    about

23   things and hoping that it would work out if there is

1    some chance that there is legislation in this area,

2    that that would be worked out.

3                 I     would    also       say   that    the   nuclear

4    capacity is going up very rapidly.               We just issued a

5    report within the last two weeks, and it's gone up

6    very year in recent years and is a fairly major

7    driver in the electric system.

8                 The    other   is     I    think    this   electronic

9    reporting system that Art has developed can be a

10   model for us of how we ought to be user friendly in

11   data collection and other areas, but it is not true

12   that Art is being considered to head the IRS.

13                (Laughter.)

14                CHAIRMAN MOUNT:           Well, thank you.

15                So I think that that -- have you got one

16   more?   Sorry.     I didn't see.         You wanted to address

17   --

18                MR. RYPINSKI:         I wanted to address very

19   briefly --

20                CHAIRMAN MOUNT:           We are running a little

21   bit over time.     So --

22                MR. RYPINSKI:         Okay.        I'll bang through

23   this.

1                 Some     of   the    comments.        First,    on

2    geographic scope, we got a small number of overseas

3    forestry   projects.       Nearly     everything    that    was

4    reported   was    domestic.       The   overseas     forestry

5    projects actually were quite interesting, but by no

6    means did they dominate the landscape.

7                 Forestry and land use turned out to be

8    for the most part that we saw in the forms through

9    careful forms, and the forestry numbers turned out

10   not to be that large, in part, because the forms

11   were   designed     carefully    to   prevent   people      from

12   summing 150 years of savings into the first year.

13                The next question is what is this for.

14   There are a couple of useful purposes that I would

15   suggest to you that I think are important.                  The

16   first one is that we have today a situation in which

17   the President has made a major national commitment,

18   which is to stabilize emissions of greenhouse gases,

19   and he has defined a mechanism, which is a set of

20   voluntary programs.        If people are interested in

21   assessing the effectiveness of that mechanism and

22   linking back the claims made for voluntary programs

23   to what companies are actually doing, this database

1    is   an    extraordinary,      even    a    unique    way    of   doing

2    that.

3                    So   I   think    that      this   will     ultimately

4    make it possible to assess the voluntary programs

5    and point a realistic way.

6                    And the second thing is that in it there

7    is an array of all sorts of interesting information

8    about what I would characterize as unusual projects:

9    landfill        methane          reduction,          perfluorocarbon

10   emission reduction, fly ash recycling.                    And I think

11   there's a lot for us to learn.                Certainly there are

12   things to be learned for the national inventory in

13   the database.         There are things to be learned in

14   there, in fact, about very low cost approaches to

15   controlling emissions of greenhouse gases in areas

16   where     emissions      are   uncontrolled        because    there's

17   never been a reason to do it.

18                   So I think there's a significant social

19   interest in that now.          With that I'll shut up.

20                   CHAIRMAN MOUNT:        So some of us are going

21   into      caffeine   deficit.         One    brief     comment    from

22   Bradley.

23                   MR. SKARPNESS:        Brief.       You do aggregate

1    these numbers, okay, and as a consequence, I think

2    that's where we have a problem because there's no

3    definitions       or     there's        no      standard       way     of

4    calculating these reductions.

5                  MR. RYPINSKI:           That chart is pretty good

6    because it's number of projects.

7                  MR. SKARPNESS:             Yeah, but this is what

8    people are going to use.              Once you aggregate them,

9    then they're going to start using these.

10                 Is        there     a     way      --     I     mean     in

11   nonattainment areas, there are air monitoring data

12   being collected.          Maybe if you could compare, you

13   know, aggregate some of those numbers where it's

14   done somewhat independently, you know, with using

15   air monitors, compare trends there that have gone

16   over the years with what's going on, what's being

17   claimed   here.         That    might    give    some       credence   to

18   these numbers.         I don't know.

19                 MR. RYPINSKI:             Well, I don't think the

20   problem is the numbers that are claimed are untrue.

21                 MR. SKARPNESS:            No.

22                 MR. RYPINSKI:           If there's an issue, it's

23   not going to be that the monitor says X and the

1    reporter claims Y.           The problem is going to be that

2    the circle the reporter draws around his project

3    will   include    things      that    some    people    will        think

4    should have been out or in.

5                 MS. GUEY-LEE:           Can I ask --

6                 CHAIRMAN MOUNT:               Can you speak at the

7    microphone, please?

8                 MS. GUEY-LEE:           I'm sorry.

9                 CHAIRMAN MOUNT:           And state your name.

10                MS. GUEY-LEE:           My name is Louise Lee.            I

11   worked with Arthur on the project.

12                I       think    that    when    you     look     at    the

13   reporting, what you saw, we know what the aggregate

14   statistics in the U.S. is, and it supports what was

15   reported.        A    lot     of     our    reports     were        about

16   improvements in nuclear availability.                  We know from

17   the national data that that was a trend in that

18   period.

19                So I guess if I characterized this, the

20   reports, you know, you shouldn't think that they

21   were not credible.            They were reported within the

22   rules.      For       example,       General       Motors      was     a

23   manufacturer.          They     invested      in    improving         the

1    process of developing cars that were more efficient,

2    and within the rules of the game, they claim they

3    reduced indirect emissions.          So now that sounds a

4    little better when you look at it that way.                     They

5    were within the rules.

6                    Does that help?

7                    MR. SKARPNESS:      Well, nobody's claiming

8    that they're not doing it in a legal, you know, way,

9    but     there   is    a   truth   out     there        that    as   a

10   statistician we're after that truth.

11                   MS. GUEY-LEE:     Okay.

12                   MR. SKARPNESS:     Okay?    And so that's --

13   well, we don't see the disconnect between what the

14   numbers are and maybe how they relate to, quote,

15   unquote, the truth, and that's --

16                   MS. GUEY-LEE:       Well, one of the ways

17   that    we   know    we   can   improve    is     to    make    more

18   efficient appliances, more efficient cars.                    GM did

19   that.

20                   MR. SKARPNESS:    I agree with you.

21                   MS. GUEY-LEE:     And they reported it.

22                   MR. SKARPNESS:    Okay.

23                   CHAIRMAN MOUNT:      So I think that this

1    discussion should continue over coffee.

2                   (Laughter.)

3                   CHAIRMAN      MOUNT:           Let's    try      and

4    compromise and have a ten-minute break because we've

5    got an important topic on restructuring the electric

6    utility industry after the break.

7                   (Whereupon, a short recess was taken.)

8                   CHAIRMAN   MOUNT:        So    this    session   on

9    restructuring of the electric power industry has two

10   papers.   The first one, "An Analysis Agenda for a

11   Restructured    Industry,"     by     Doug    Hale,   Office    of

12   Statistical Standards.

13                  MR. GRACE:     Tim, I understand there's a

14   little problem of hearing in the back from people

15   making comments at the table.

16                  CHAIRMAN   MOUNT:        So,    members   of     the

17   Committee, you have to speak into the microphones.

18   You're not doing a good job, and you will be graded

19   on the second session.

20                  (Laughter.)

21                  CHAIRMAN MOUNT:        Those that pass will be

22   allowed to go to dinner, which is the other things

23   that I should have announced, that we plan to have a

1    dinner for the Committee at Le Rivage, the usual

2    location, at 6:30, but we need to have a number

3    count of how many people will be able to go, and I

4    think the best thing is to decide by the lunchtime

5    and make sure you tell Tracy.

6                Okay.   So now you're on, Doug.

7                MR. HALE:     All right.    Thanks, Tim.

8                My name is Doug Hale.         I'm the author of

9    the paper on electric power industry restructuring.

10               The   world   is   changing    all   around     us.

11   Last week they started dancing at Baylor University.

12               (Laughter.)

13               PARTICIPANT:       They    didn't    when   I   was

14   there.

15               MR. HALE:     Yesterday the FERC announced

16   new open access rules for the entire U.S. domestic

17   or U.S. electricity industry.          Unless things have

18   changed for the worse, the far worse, we all know

19   where the dancing is going to lead up.              We don't

20   know where the electric pricing is going to end up,

21   and so the Administrator has given me an opportunity

22   to think about this for a while with some of my

23   colleagues at EIA, and I want to present kind of

1    where we are in our thinking.

2                   I must say that there is a huge debate

3    about how this is all going to shake out.                       On the

4    one hand, you have people like Paul Joskow claiming

5    in   different        ways       that    the     benefits         from

6    restructuring and price competition may, in fact, be

7    minimal.

8                   Joseph        Stiglitz     yesterday        at      the

9    announcement      said    that    we    got    enormous     economic

10   benefits       from       the       deregulation           of      the

11   telecommunications and natural gas industries.                    This

12   is   the    first     comprehensive       step    in   a        similar

13   transformation of the electric industry.

14                  First slide.

15                  What I've tried to do in this paper is

16   present a conceptual framework for thinking about

17   the restructuring of the industry.                I've described

18   EIA's current projects that relate to electric power

19   restructuring, and I've made some suggestions about

20   a prospective analysis agenda.

21                  This paper has been widely circulated,

22   including    to     the   Department     of    Justice,         Federal

23   Trade Commission, and others, for the purpose of

1    getting suggestions about alternative approaches and

2    different    suggestions           for   projects.              I    would

3    certainly like your ideas in that area, but more to

4    the   Committee,    I'm    concerned          with   learning        about

5    ongoing work in the area.

6                 I     was    at   a    Department       of   Justice-FTC

7    closed   seminar    Tuesday        dealing      with      the       merger-

8    acquisition guidelines and their application, and in

9    the course of that, they had invited people from

10   Enron, Berkeley, several of the private consulting

11   firms to present research that's not been published,

12   and it's very clear to me that there's a lot of work

13   going on that we will have to take advantage of if

14   we're going to have an effective analysis program in

15   this area.

16                I'm     particularly             interested        if     the

17   Committee    has    access         or    knowledge        of        ongoing

18   empirical work dealing with such things as nodal

19   pricing,      distribution               of      nodal              prices,

20   approximations to nodal pricing, elasticities under

21   demand -- of demand under spot pricing, anything you

22   may have on transmission economics, and the metering

23   controlled costs associated with something closer to

1    real time or closer to nodal pricing.

2                   Most of the economic analysis of this

3    industry is based upon network models, and we at EIA

4    have not had much experience with them.                 So we're

5    very interested in any information you have about

6    small   scale     network     models     applicable         to   the

7    electric   power       industry   that   we    might    use,      if

8    nothing else, as learning devices at this stage.

9                   The      Justice     Department         is        also

10   extraordinarily interested in them, and they have

11   already suggested informally joint projects with us.

12                  Finally, any information you might have

13   on   ongoing    work    to   quantify    the   price    quantity

14   impacts of restructuring in the U.S. markets would

15   be very much appreciated.          We're learning more and

16   more about what went right and what went wrong in

17   the U.K., excellent empirical papers in the Journal

18   of Political Economy and other places talking about

19   the number of competitors, that there are too few.

20   There isn't anything quite ready yet in the U.K.,

21   even though there have been a lot of preliminary

22   pricing experiments in the last few years.

23                  The next slide presents the organization

1    of the paper.    The paper is kind of long, so let me

2    just run you through it.

3                The first four sections basically deal

4    with the conceptual framework, the first question

5    being:   why do we regulate?      Why are we stopping

6    regulation of the usual sort?

7                The second deals with the benefits of

8    restructuring.     What is there?     Are the benefits

9    real or are they not?

10               We   then   look   very   briefly   at   three

11   archetypical restructuring proposals.     How do we get

12   from here to there is the issue.      Even if there are

13   benefits from competition, how do we move from the

14   state we're in to this better world?

15               Finally, an analysis issue is:       is there

16   a there there?     Again, it's not at all clear.      How

17   much of a change there's going to be depends upon

18   empirical facts.     It depends upon the equilibrium

19   outcome of this evolution, and also our ability to

20   quantify it is very much limited by the data we

21   have.

22               The final part of the paper deals with

23   the analysis agenda, again, the first phase being

1    what we're doing now and the latter phases of a

2    prospective nature.

3                   I     want    to    speak    just      a    second    about

4    benefits   because         it's    the   benefits         that     set    the

5    parameters on how big the changes might be.

6                   Do you want to put that up?

7                   If you look at the literature, most of

8    the   benefits     are      said   to    come     from      five    areas.

9    First are improvements in operating efficiency and

10   the allocation of system-wide resources, including

11   the closing of uneconomic facilities.

12                  The second thing, which can't be over-

13   emphasized,     in    my    opinion,       is   that      by     moving   to

14   something closer to nodal pricing or marginal cost

15   pricing or flexible pricing, you are now able to

16   make beneficial trades that simply were not possible

17   under     average        cost      pricing.               That     changes

18   everything.        Okay.      That changes when and how the

19   plants -- you know, when demands appear, how plants

20   are run, what emissions are like.

21                  The third thing is an asset reevaluation

22   at    market   values.          Utilities       are    valued      by     the

23   market,    those     publicly       owned       utilities,        but     you

1    cannot get a value for individual facilities apart

2    from book values.            The market will make it very

3    clear as to the values attributable to transmission

4    versus   generation        versus    better     control,       better

5    coordination, all sorts of information features that

6    are simply lost now.           It may lead to new products,

7    new    ways    of      delivering       and     contracting        for

8    electricity.

9                   And finally, the restructuring is said

10   to    lead    to     appropriate     signals      for        long-term

11   investment,        perhaps    more   investment         in     storage

12   capacity,     perhaps      more   investment     in     incremental

13   changes to upgrade our ability to transmit power.

14                  I don't want to go into the analysis

15   issues as such.        They're long; they're tedious; and

16   they're written in "economese," I guess, but I do

17   want to mention a couple of things on the empirical

18   analysis issues.

19                  What I'm talking about here is how big

20   are the potential benefits.             How much might we get

21   out of restructuring?             And that's why we look at

22   these sets of questions.

23                  So    the     question    then    is:         are   the

1    utilities       actually       minimizing          the     cost       of    the

2    services       they    provide?         Are       they    operating         the

3    proper facilities in the proper sorts of ways?

4                     If,    in     fact,    the       great    benefit         from

5    competition       is    prices       will    get    closer       to    either

6    nodal    or    marginal      costs,     then       how    much    do       those

7    prices     vary       during     the        day    over     seasons,         by

8    location?        If they don't vary, then there's less

9    payoff.

10                    Is     demand       really        elastic        over      the

11   distribution of nodal prices?                  Can you really reduce

12   demands 15, 20, 30, 40 percent for a few hours and

13   then    have    them    met     at     other      times    when       there's

14   plenty of capacity?            If you can't, the restructuring

15   benefits are lessened.

16                    Even if there are large benefits, and

17   most people, I think, believe there are, what are

18   the     actual        magnitudes        of        the     metering,          the

19   communication,          control,        and        contracting             costs

20   associated with moving to the new world?                           Are they

21   large enough to swamp the potential benefits?

22                    And finally, what are the opportunities

23   and costs of changing transmission capability?                              The

1    FERC strategy for making the industry competitive is

2    based     upon       transportation,         getting   competition

3    through transportation.            Whether or not and how or

4    under what terms you can improve your transportation

5    system is key to how effective this is going to be.

6                      Right now, EIA is running four projects,

7    three of which made it on this graph, one of which

8    didn't.       So let me start with the important project

9    that was inadvertently left out.

10                     The first one deals with the status of

11   FERC    and    PUC   regulations    with      the   status   of   new

12   entrants into the industry and takes a preliminary

13   look         at      transportation           capabilities,        of

14   opportunities           for       expanding         transportation

15   capabilities.        This is ongoing now in the CNEAF.

16                     The second project, which is prospective

17   and    has    just   been     started   in    a   preliminary     way,

18   deals with the efficiency of individual generating

19   stations.         This is an attempt to use NERC data to

20   look at what used to be called the X efficiency of

21   the operations of plants.               How well that project

22   succeeds depends upon the data.                Right now we don't

23   know.

1                    And     finally,         there     are     two     modeling

2    projects.       The first, which Art is going to talk to

3    you    about    a    lot,   deals    with        simulating       marginal

4    costs, pricing, plus adjustments to marginal costs

5    under a regime where you're assuming elasticities

6    and a lot of other things you would like to know

7    instead of having to just assume.

8                    And     another      project        deals        with   the

9    effect of removing regulatory constraints on how our

10   models would view investment over time.

11                   I think these projects, on the whole,

12   are going to be very informative and successful.

13   I'm quite excited about Art's in particular, but I

14   think what we're going to realize after they're done

15   is that our database is still a bit thin, and so I

16   think for prospective projects the first thing we're

17   going to want to do is get a better handle on how

18   much    the     prices      vary    and     how     much         transition

19   metering costs might really amount to.

20                   I think we're going to find out that

21   with    these       networks,      the     costs     and    effects     of

22   alternative ways to increase transmission capacity

23   is at least as important, if not far more important,

1    than generation capacity at least for the next ten

2    or 15 years.

3                     I think also we're going to discover in

4    a very profound way how difficult it is to estimate

5    demands    with       the   information      we    have    available.

6    There's never been anything like the spot market or

7    see     anything       approaching       a    spot        market        for

8    electricity      in    this   country.       Ergo,    there        is   no

9    data, at least local data, or very little.

10                    The other thing we're going to have to

11   start worrying about is scenario construction.                          By

12   the time these projects are done, we will have had

13   basically three years under a slowly moving, perhaps

14   slowly moving change to a restructured environment.

15   We should be in a better position to talk about

16   where     this    is    all   going   to     end     up,    what        the

17   equilibrium outcomes might be like, but right now

18   it's too early, but maybe then.               In order to do our

19   analysis, we're going to have to make some guesses.

20                    I think finally we'll have to do what

21   we're going to have to do at every juncture in this

22   project, and that is to reassess where we are.                      This

23   is clearly a one step at a time learning process.

1                       I just want to speculate a little bit as

2    to what would come next, and I think in this Phase 3

3    we    would    start       emphasizing      doing     serious       demand

4    estimates.          Right now, as I say, we are just making

5    up elasticities.            In the foreseeable future I think

6    we will be able to sort through which assumptions

7    are sensible and which are not, but we're still far,

8    far    from        making       serious    attempts        to     estimate

9    elasticities         in    the   context      of   this    sort    of   new

10   market.

11                      I think we're also going to have to face

12   the network issues head on.                 I am proposing that we

13   build three, a couple perhaps toy network models

14   maybe representing California, the Northeast and the

15   Midwest       to    try    to    get   some    feel       for    how    much

16   difference          the     network       effects     make       for     the

17   forecasts          and    the    analysis      and    the       analytical

18   results we get using our standard tools.

19                      If those effects are large, I suggest

20   then we adjust our models for these network effects

21   or    try   to.          That may not be possible.                 In the

22   distant future, perhaps we will, you know, replace

23   what we have now with a more network based approach

1    to electric prices.            I don't know.               My guess is I

2    will have retired by the time we get to that.                         So we

3    will find out.

4                   I'd like to return to my questions one

5    more time.         This is an incredible area of analysis

6    and activity.         EIA cannot do it all, should not do

7    it all.       We have to find targets of opportunity

8    where we can add particular value to the ongoing

9    debates,     and    one     place       to    start   in    making    those

10   sortings out is to get a better idea of the work

11   that's going on.

12                  So once again, anything you all can do

13   in    your   own    particular          knowledge     working    in     the

14   research organizations to inform us of what's going

15   on would be a great help.

16                  And with that, thank you very much.

17                  CHAIRMAN MOUNT:               Thanks a lot, Doug.

18                  We go to the second paper, "Forecasting

19   Electricity        Prices    in     a    Competitive       Environment,"

20   Art    Holland,      Office       of     Integrated        Analysis     and

21   Forecasting.

22                  MR. HOLLAND:                  Good morning.       I'm Art

23   Holland.     I appreciate the opportunity to speak with

1    you this morning.

2                     I'll be describing the method that we're

3    developing in the Office of Integrated Analysis and

4    Forecasting       to     model    the     price        of     electricity

5    generation services under competition.

6                     We're up to Number 2, Doug.

7                     I've been asked to review the questions

8    for the reviewers, and they are:                       what analysis,

9    data   or   modeling       products       do      decision-makers         in

10   industry    and        government     need      as     they       face   the

11   uncertainty of the future electric power industry?

12   How can we best use the integrated nature of NEMS to

13   serve them?

14                    We are in the process of developing a

15   model of a quasi-spot market pricing mechanism.                          Are

16   108    pricing     periods       enough      to      simulate      a     spot

17   market?

18                    And     the   next     step      is    to    develop      a

19   contract pricing mechanism, or maybe to develop a

20   contract    pricing       mechanism.           Should       the    contract

21   price be the average spot market price plus some

22   insurance premium?             Should this premium be based

23   upon the volatility of the spot prices, assumptions

1    regarding   risk      aversion       and    the   avoidance    of

2    transaction costs?         Are there other factors that we

3    should consider?

4                    Now, the restructuring of the electric

5    power industry is not just an electricity issue.

6    Fortunately the Office of Integrated Analysis and

7    Forecasting is able to use NEMS for this analysis

8    effort, and the strength of NEMS is in its unique

9    systems integration feature.

10                   Now, let me point out before I go any

11   further that what I'm going to describe to you today

12   is not integrated into NEMS yet.              It's in the test

13   phase.   We're doing it off line, and the purpose of

14   this phase is to determine how to integrate it into

15   the NEMS framework, what pieces to use, and how to

16   hook up all the wires.

17                   On the left in this diagram of NEMS,

18   you'll see the supply components; on the right, the

19   demand components; and in the center, the conversion

20   components and the system integration piece.                  What

21   NEMS   allows    us   to   do   is   gain   insights   into   how

22   changes in the electric power industry will affect

23   other U.S. energy markets, like coal and natural

1    gas.

2                     So     with     that,    I'll       try    to     describe

3    something       about     what    we're     doing      and       how     we're

4    calculating these competitive prices.

5                     Now, there are at least two, and maybe

6    three, components.             Again, this is the test phase,

7    and keep in mind that this is generation services

8    only.          Transmission       and     distribution           are      very

9    important, but we're going to save those for later.

10                    The     first     component          is     the       energy

11   component.        Now, the energy component is based on

12   the    short     run    operating       cost    of    the     last       plant

13   dispatched.        There are 108 dispatching periods per

14   year in each region in NEMS.

15                    Now,     some    people       believe       that      in    an

16   over-capacity situation like we are in right now,

17   this is the only determinant of prices.                             Now, we

18   anticipate that most of the times that will be true,

19   but     what    that     means     in     our    algorithm          is      the

20   reliability component, which is next, and that may

21   not be the best name for it, and I'll talk a little

22   more    about     that,    will     be    small      at    least       on    an

23   average        annual     basis     until       this       over-capacity

1    situation is relieved.

2                   Now,   the     reliability    component        may

3    better be called the market clearing component.                I

4    have to give Doug credit for that name, and it's

5    based on two general calculations or values.             First

6    is the value that consumers place on reliability,

7    reliability specifically of generating supply, and

8    the second thing is the reduction in unserved energy

9    that's contributed by each kilowatt of generating

10   capacity in the region.

11                  Let me repeat that and talk about it a

12   little bit because it's a slippery concept if you're

13   new to it.     That's the reduction in unserved energy

14   contributed by each kilowatt of generating capacity.

15   Now, unserved energy, think of that as a bad thing.

16   That is the extent to which demand exceeds supply,

17   and anyone that knows anything about electric power

18   knows   that   that   can't    happen.      So    this   is   an

19   expected value that we're calculating in the model.

20                  Now, one of the questions that I'm asked

21   about this component is:        how will it be integrated

22   into the prices that consumers see?              There are two

23   possibilities that I can envision.

1                        First    would    be       an    independent        system

2    operator       in    that     type   of    a    world       enforcing        some

3    system reserve requirements.

4                        Another way that it may get in there

5    would     be        through     contracting              mechanisms      where

6    consumers       purchase       greater         levels       of    reliability

7    and, therefore, pay a higher price for their power

8    on a per kilowatt hour basis.

9                        The third component -- I'm going to talk

10   more     about       the     reliability            or    market       clearing

11   component before we're done -- the insurance and

12   convenient component, if that's used, will be for

13   end use consumers who enter into service contracts

14   to avoid the risks and transaction costs at the spot

15   market.        Now, I don't know that we're going to do

16   this.

17                       One of the purposes of the current test

18   phase is we're going to look at the results we get

19   and then make a determination of this convenience

20   insurance component.

21                       Now, the first component that I talked

22   about,    the       energy    component         of       price,   is    on    the

23   overhead.           Now, I know you can't see the numbers,

1    but I wanted to show you this to give you an idea of

2    the range of costs that we're looking at that are

3    translating into prices, and the costs are color

4    coded.

5                   Now, there are 108 rows in this graph.

6    Those are the 108 dispatching periods per year in

7    NEMS.      Now, each of those dispatching periods is

8    characterized so that we're trying to capture the

9    entire year in load characteristics that exist on a

10   time basis throughout the year.

11                  The     columns,     there   are    13     columns.

12   These are the 13 regions that the model uses for its

13   solutions.

14                  Wherever you see white on the chart is

15   where the cost or the short-run operating costs of

16   the     last   plant   dispatched,     which      is    the   price

17   setting plant for this component, is less than two

18   cents per kilowatt hour.          Where you see yellow, the

19   short-run      operating     cost     of    the        last   plant

20   dispatched is between two and four cents a kilowatt

21   hour, and everywhere you see red, it's greater than

22   four cents a kilowatt hour.

23                  This tells us that we're in the ball

1    park    of   expectations.        These   are   the    kinds    of

2    numbers that we expected to see for the last plant

3    dispatched to meet load throughout the year.

4                   Doug.

5                   Now, the more contentious piece.                The

6    reliability or market clearing component has three

7    steps basically.       There are four up here, but one or

8    two are done in the model simultaneously.

9                   The first step is to calculate unserved

10   energy for the region for each of those 108 time

11   slices for which plants are dispatched in the model.

12   Now, again, unserved energy is not a good thing.

13   That's the difference between supply and demand when

14   demand exceeds supply.

15                  I've been asked why would demand ever

16   exceed supply, and of course, it can't.            The idea is

17   that it will not exceed supply if it's priced to

18   reflect shortages properly, and that's what we're

19   endeavoring to do with this component of price, and

20   that's   why   market    clearing    component     might   be   a

21   better term.      It raises the price of electricity

22   when demand approaches the capacity limits in order

23   to     communicate      through     prices      that   capacity

1    shortage.

2                     The unserved energy is calculated based

3    on   the     capacity     of   each     generating   plant      in   the

4    region, expected planned enforced outage rates for

5    each generating plant, and the hourly loads for the

6    region.

7                     Then what we do is we increment capacity

8    a    small    amount,     maybe       ten   megawatts,    and   do   it

9    again.       This shows us the change in unserved energy

10   for a change in generating capacity, and the result

11   of those two calculations gives you the reduction in

12   unserved energy that you get for each megawatt of

13   capacity in the region, and the assumption is that

14   every        megawatt     of      capacity      that's     available

15   contributes to the same degree in that reduction of

16   unserved energy.

17                    If     you    take    those   numbers,    take      the

18   total capacity in the region and an assumed value of

19   unserved energy or, on the other side, the cost of

20   unserved energy, multiply those together, and divide

21   by sales, it gives you the reliability or market

22   clearing component of price.

23                    I think some sensitivities, and to show

1    you some preliminary results, might help to clear

2    that up a little bit.             Now, this was in the early

3    stages of the model.             We didn't have the 108 time

4    pieces.     All we had is an average annual number, and

5    as   I    said,    in    the     current     situation     of    over-

6    capacity,      we're      going       in    assuming      that    that

7    reliability or market clearing component will be low

8    because    demand       should    very     infrequently     approach

9    your capacity limits in the region.

10                    Now, this is New England, and I selected

11   New England because if you look in the far right-

12   hand column, you'll see that with the original data

13   on   an     average      annual        basis,    the     reliability

14   component of price we were getting was three and a

15   half cents per kilowatt hour, which is way too high.

16   That's     out    of    the    ball    park,    and   something    was

17   wrong with that.

18                    So we did some sensitivities.             The first

19   thing we did is we doubled the number of generating

20   plants    in   the     region    and    halved   the   capacity    of

21   each, which means you have the same capacity, but

22   it's broken up more finely.                That should lower your

23   calculations      of    unserved       energy,    which    means   an

1    increase in capacity will have a smaller effect on

2    that   unserved       energy         number,    which     means       your

3    reliability        component      of    price     or      your    market

4    clearing component of price should be lower when you

5    do that, and sure enough, it dropped from three and

6    a half to 2.2 cents a kilowatt hour, but that's

7    still too high.

8                   Then we started looking at some of the

9    data that was feeding into the model, and we saw

10   that in the original data, the availability rates

11   that were assumed for nuclear power plants were 65

12   percent.     That's way too low.               It's more reasonable

13   to plug in a number like 80 percent.                   So that's what

14   we did, and bang, that number dropped from three and

15   a   half    cents    to   .7    cents     a    kilowatt    hour.        So

16   clearly     the     model       is     very     sensitive        to   the

17   availability of your large base load plants, which

18   it should be.

19                  Oh, let's skip the next one, Doug.

20                  Now, what I'd like to do is show you

21   some   of    the    early      results.        We've    just     started

22   getting some what I think are credible results out

23   of this model this week.                So this is very early.

1    We've got a lot more analysis of the results to do.

2    So please don't run out and quote me on these, and

3    that's why I'm using 1995, so that we can't call

4    them forecasts, and we also know something about the

5    industry in 1995, and we don't know what's going to

6    happen later.

7                   Now,   the   assumptions    in   these    results

8    you're seeing are the value of unserved energy is

9    $12 a kilowatt hour, and assumed elasticities of

10   demand are minus .15.

11                  Now, I have two graphs which are lined

12   up    here.    The    top   graph   --   and   the    reason    why

13   they're lined up is so you can see how supply and

14   demand    relationships,       which     are    on     the     top,

15   translate to prices, which are in the bottom graph.

16                  The top line, the dark blue line, are

17   your seasonal capacity numbers.           Those are adjusted

18   for    your   maintenance    schedule    and    for   your     firm

19   trades.       Under that, the lighter kelly green are

20   your hourly demands.          Now, keep in mind that the

21   peaks that you see in demand -- and those are broken

22   up, as you can see, under that by season -- we don't

23   know when those peaks are going to occur.                      They

1    could occur any time during the month, but we want

2    to get them in there so that they're represented in

3    the model.

4                  Under that, you'll see the red line or

5    the   red    spikes   are   the   reliability   or   market

6    clearing component of price.          You'll notice that

7    those line up whenever your green demand lines start

8    getting very close to your blue capacity lines.

9                  Under that -- and these, by the way, the

10   three lines on the bottom are stacked.          So the top

11   red line shows you the spot price of electricity at

12   that point or what we're calculating.

13                 The green line is the energy component

14   of price based on the short-run operating costs of

15   the last plant dispatched, and you'll see that's

16   fairly flat in ERCOT.       I should have mentioned this

17   is Texas, for those of you who don't know the North

18   American Electric Reliability Council Regions.

19                 The bottom line is your transmission and

20   distribution component of price, blue.          Now, as I

21   mentioned earlier, we're just using the NEMS numbers

22   for that, which for distribution and transmission

23   means that that's the average imbedded cost.            So

1    it's going to be flat throughout the year.

2                   Now, if you take those green, red, and

3    blue   lines   and    you     average       them    out   through    the

4    year, your T&D component, which is the same as in

5    the regulated cases, 1.2 cents a kilowatt hour; your

6    energy component is two cents a kilowatt hour; and

7    the    reliability       or     market        clearing        component

8    averaged   throughout        the     year    is    .1    cents.      That

9    comes out to 3.4 cents per kilowatt hour.                     This is a

10   very early number, and there are still some things

11   that we need to figure out how to get in there, but

12   that does compare to a 1995 price of six cents a

13   kilowatt hour for this same region coming out of the

14   cost of service regulation method that's in NEMS

15   now.   So we are getting big drops in the price of

16   electricity using this method.

17                  Another       reason    I    wanted       to   show   you,

18   again, very early, preliminary results that probably

19   still have some problems with them, this is for the

20   MAAC region.      Now, MAAC, for those of you who aren't

21   familiar   with      NERC,    is     Pennsylvania,        New     Jersey,

22   Delaware, Maryland region.             The lines are the same,

23   seasonal   capacity,         under    that    the       demands.     But

1    you'll    notice    the     difference           here    is   that     we're

2    getting    a   rougher,          a    higher          volatility     energy

3    component of price.              So the reliability or market

4    clearing    component       of       price      isn't    kicking     in   as

5    much.     That energy component is enough to drive the

6    demands down away from the capacity limit.                         So we're

7    not getting that red piece in there as strongly.

8                   And,        again,           a        price    comparison,

9    regulated cost of service was eight cents in NEMS in

10   '95.    This totals to 4.6 cents.

11                  And,        finally,             no       discussion        of

12   electricity restructuring would be complete without

13   looking at California, and I don't know if we should

14   get any insights from this or not, but I was struck

15   with how flat and how low the price of electricity

16   in   California     is     from      this       graph.       There's   very

17   little volatility in the price, which suggests they

18   have    certainly     in    excess      of       capacity     there,      and

19   they're able to use their cheaper generating plants

20   to meet their demands.

21                  Again, a comparison.                   I was able to pull

22   nine cents per kilowatt hour out of the Electric

23   Power    Monthly.        That's       all       of   California.        This

1    region isn't exactly California.                     There are some

2    slight geographic differences, and there may be some

3    modeling inconsistencies, but 9.6 is what came out

4    of NEMS.        So you've got nine to nine and a half

5    cents as a regulated price, and these totaled to 4.7

6    cents per kilowatt hour.

7                     Doug,    you        might    want    to     put    the

8    questions back up.

9                     Again,    thank      you     very    much   for    the

10   opportunity to speak with you this morning, and I

11   look forward to your comments.

12                    CHAIRMAN MOUNT:             Well, there wasn't a

13   rush from the Committee to be a discussant for these

14   papers.     So I hope there are going to be some very

15   insightful comments after my rather bland remarks

16   are over.

17                    I think it's fair to say that it's much

18   too early to be able to answer the questions that

19   have been posed.          However, I think that the overall

20   approach    to    this    problem      is     correct.       Basically

21   people    are    going    to    be    interested     in    prices   and

22   demand.     Are prices really going to go down?                     Who

23   benefits?       What's going to happen to sales?

1                        In many parts of the country with high

2    reserve margins, the need for new capacity is not

3    immediate,          and        the       problems     about       investment

4    incentives then can be looked up as a sort of next

5    issue that ought to be addressed.

6                        So     I     have       four     issues        that     are

7    mentioned, but I think are more important maybe than

8    they are in the paper.                   The first one is regulatory

9    burden.        I don't think it's a surprise that the

10   areas     of    the        country         that     are     interested      in

11   competition          are       the       Northeast        and    California.

12   There's an awful lot to regulatory burden.                           Some of

13   it is very positive, shall we say doing things about

14   the environment, but some of it really, certainly in

15   New   York,     has       been       a   way   of    essentially      taxing

16   people indirectly using utility companies, and this

17   has   led      to    frustration           from     major       customers   of

18   electricity who think that they ought to be able to

19   get power a lot cheaper, and I think that the answer

20   is that they probably can.

21                       But there's one small component of the

22   regulatory burden, and that's the collection of data

23   that also is very important for this.                              So that I

1    think that EIA needs to make a major review of the

2    types of data that are being collected to answer the

3    most obvious question that one's going to get from

4    the Hill about what is actually happening and are

5    prices going down.

6                   So    I   think     that   given    the     financial

7    pressure that the utility industry is facing, having

8    a   serious    review    of   data    collection      is    sort   of

9    politically sensible.          I think that given the fact

10   that   we're   going     to   be   looking    at     new   forms   of

11   financial markets, being able to gather this type of

12   information     electronically       is   a   real    possibility.

13   So the burden will not be as great as it might be

14   without that sort of mechanism.

15                  But   I   think     that   the      most    important

16   thing is that EIA is going to need new types of

17   information on prices that are not being gathered at

18   the moment, and I think that what we have to do is

19   to try to avoid getting into the predicament that

20   there was with natural gas prices that a lot of the

21   market was missed, not covered.

22                  So I really congratulate EIA for sort of

23   looking at these issues and trying to grapple with

1    them early at a time when it is not obvious what

2    exactly is going to happen.

3                    So the second issue that I want to talk

4    about is restructuring rates that customers pay, and

5    I suppose here one might look at a parallel with

6    what happened in the airline industry.                It costs me

7    about as much to go and visit my mom in England as

8    it does to make a business trip to come and visit

9    you folks down here.           I also have a vast array of

10   different pricing systems and different "thises" and

11   "thats"   and    I   contract    with   a   broker,    my    travel

12   agent, to figure out what in the heck is going on

13   and tell me what to do.

14                   But I think that the bottom line is that

15   the reason that I pay a high price to come to visit

16   Washington      is   because    I   live    in   a   small   town,

17   Ithica, and the reason that I don't pay much to

18   visit my mom is that I'm going on a big trunk line,

19   the Atlantic run, and I'm paying very competitive

20   rates, and I think that's basically what it's going

21   to be, that large industrial customers are going to

22   do pretty well or better than they are now, but I'm

23   not too optimistic how I'm going to come out of this

1    as a residential customer.

2                   So the something that's very important

3    about the electric industry and that the nature of

4    the   product      makes        it    possible       to     use    price

5    discrimination       in     a        way    that     is     completely

6    unrealistic for other types of products, so that we

7    can have prices that vary by day.                         We can have

8    prices for individual customers.                   We can price the

9    demand from individual customers so that you pay

10   different       amounts         for        different        quantities

11   purchased,   and     so    essentially         multi-part         tariffs

12   that can be approximated by two-part tariffs.

13                  But the ability to come up with a very

14   new, innovative way of pricing electricity is really

15   substantial,       and    therefore,          just    assuming      that

16   getting information about the average price paid is

17   really inadequate for understanding how these types

18   of price changes are likely to affect demand.

19                  I   think    that       it's    important      to    talk

20   about the sort of vision of what the institutional

21   structure of pricing is likely to be.                      Most of the

22   discussion   about       competition        focuses       currently   on

23   generation, and the general view is that some sort

1    of real time spot market will emerge for generation.

2                     It    seems     to    me    that   packaged     around

3    that, the same way that my travel agent protects me

4    from all of this stuff, there are going to be a vast

5    number     of     brokers        representing         suppliers     and

6    purchasers.      There are going to be many new forms of

7    financial derivatives, forward markets, et cetera,

8    et cetera, that are going to be important, and it is

9    the prices that customers pay that determine their

10   demand and the way that they pay those prices so

11   that    customer       charges    are       different     form   energy

12   charges.

13                    With regard to the actual structure of

14   the industry itself, it seems to me that we're going

15   to have a competitive generation system, and then

16   we're    going    to    add    what     I've   called     a   regulated

17   wedge,     which        maybe         covers    transmission        and

18   distribution, but clearly the utility industry is

19   very     interested      in     maintaining         the   ability    to

20   recover    money       for    stranded      assets,     and   how   much

21   they're going to be able to do that is really the

22   political issue that hasn't been determined.

23                    But I think that that ability, if it

1    exists,       to       be     able        to     extract     more     than       a

2    competitive price for electricity will depend on a

3    sort    of    quasi-regulated              system     existing       for    some

4    part of the industry, and the most obvious one is

5    for transmission, and I think we're going to end up

6    with      the          sort      of        bizarre     situation           where

7    transmission charges cover the cost of nuclear power

8    plants.

9                       So I think that this really says that

10   trying to figure out what's going on is going to be

11   extremely difficult, and I don't think that there's

12   any easy way to say what type of data are required.

13                      However,           I    think     that     there        is    a

14   difference between the sort of analysis that we're

15   doing    at     the     moment        at    Cornell    and     the    sort      of

16   analysis that's being done at EIA.

17                      A     lot     of        the    complication        in        the

18   presentation this morning is trying to come up with

19   the    equivalent           of   a    capacity       charge.         Everybody

20   knows what the energy charge is, the spot market

21   price.        I think that there's a good argument that

22   maybe if there is an effective competitive market,

23   that capacity charges are not going to be needed as

1    a separate item.       The system that the U.K. used, I

2    think -- I don't know what the polite word is, but

3    "hokey" would be a good one --

4                  (Laughter.)

5                  CHAIRMAN      MOUNT:         So    the    bottom      line,

6    it's not clear to me that worry about how one ought

7    to measure capacity charges is important at this

8    time.     I think that something that could be done now

9    with NEMS is to just assume that somebody is going

10   to get a hit somewhere.             There's going to be some

11   stranded assets, and you're not going to have to

12   recover as much revenue.

13                 My guess is the big advantage of that is

14   going to go to the industrial sector, and therefore,

15   an interesting question is if, in fact, rates get

16   lower   in   the    industrial      sector,         what   happens    to

17   demand.      Does    this    deal    with       some    of    the    high

18   reserve margin problems that we have?

19                 You    know,     this    is       a      very   sort    of

20   straightforward      analysis       with    the      existing       model

21   structure.

22                 Then I have one technical argument with

23   Doug over his use of nodal pricing, point-to-point

1    pricing.      Certainly the people that we've talked to

2    who are trying to set up a market in California for

3    the Mercantile Exchange think that zonal pricing is

4    the best that we'll be able to get to, but I think

5    that the distinctions of these two are technical.

6                       Clearly    one       has   to    take    into   account

7    capacity      constraints         in     some      form    to   avoid   the

8    problems that the U.K. had.

9                       Given    all    of    these      complications       with

10   rates, my guess is that the best data that exist are

11   currently at EIA, and I really hope that that stays

12   the way, that EIA is able to get the data that they

13   need    in    order    to    be     able      to    monitor     this    very

14   complicated situation that we're getting into.

15                      So the third point deals with customers

16   with large loads, and this is somewhat of a side

17   issue    in    a    way,     but    I     think     that    the    utility

18   industry got into a problem rather like computing

19   groups that hung onto the mainframe and didn't get

20   into    distributed          computing;            that     the    utility

21   industry did not realize that there were very real

22   efficiency gains from using combined cycle turbines

23   and, therefore, having a small distributed system

1    rather than large plants.

2                      There     are    probably   a     few   people    that

3    still believe that we ought to be running an energy

4    system based on plutonium, but my guess is that that

5    view is dying out and that the potential advantage

6    of having this distributed system is that it makes

7    things like cogeneration a lot more feasible, and so

8    that the hope that existed under PURPA really can

9    manifest itself with new technology.

10                     However,        the   customers    that     are   most

11   likely to be able to do this are the ones that are

12   going to get all the breaks with competitive prices,

13   and   so     I    personally       think   that     there's    a    real

14   tension between trying to do things more efficiently

15   and   worry       about    greenhouse      gases,    et     cetera,   et

16   cetera, and the fact that the large customers are

17   the ones that are going to be able to negotiate

18   lower rates in the systems that are being considered

19   at the moment.

20                     And the final point I have is nuclear

21   power.           Clearly    the     nuclear   industry       has    made

22   tremendous improvements in the last couple of years

23   so    that    the    many    nuclear       power    plants    are     now

1    competitive in an operating sense, but there are

2    still large amounts of debt in the rate base of many

3    utilities, and this is a major stranded asset or

4    strandable asset, if you're working for the utility

5    companies.

6                  So there's an awful lot of restructuring

7    of the industry going on, and it seems to me that

8    it's very important that EIA keep track of what's

9    going on to the nuclear industry.            I think that the

10   important thing about the nuclear industry is that

11   this is not a question of just paying off what's in

12   the rate base.

13                 I tried to think of an analogy for it,

14   and the best I could come up with was alimony, that

15   basically there's a real commitment to pay money to

16   these plants into the future and decommissioning and

17   the monitoring of those plants is something that

18   will   make   companies    that     have   those       liabilities

19   uncompetitive compared to companies that don't have

20   those liabilities.

21                 So   the    ability    to    keep    a    regulatory

22   wedge so that you're able to recover costs for that

23   is one way of dealing with it, but the bottom line

1    is that I think it's very important that we don't

2    see a restructuring of the industry so all of the

3    nuclear pieces go bankrupt, and then I'm not too

4    certain who owns them.

5                    But I think that the importance here is

6    that in my view the federal government cannot cease

7    to be heavily involved in dealing with the nuclear

8    industry, and that includes paying for a lot of the

9    costs that are going to come in the future.

10                   Thank you.

11                   So    now    we    open    it    up    to    the   floor.

12   Campbell.

13                   MR. WATKINS:          I have several comments.

14   So maybe I'll come up to the podium.

15                   CHAIRMAN MOUNT:           That's fine.

16                   MR.    WATKINS:           First       of    all,   a    few

17   comments on Doug's paper and then one or two on

18   Art's.

19                   This is a very difficult exercise, of

20   course,   but    few    in    Doug's       paper      --    one    of   you

21   mentioned   about      Paul       Joskow's      estimates      that,    in

22   fact, electricity deregulation would not generate a

23   lot of benefits.            I'm not quite familiar with the

1    paper of his that you're referring to, but it seems

2    that I'm more with your kind of results, that, in

3    fact, there would be substantial benefits.

4                     I say that because the mere fact that

5    we're talking at all about a stranded asset problem

6    or perception of it is an indication that there are

7    a lot of assets out there that are uneconomic.                     If

8    they're uneconomic, then with a competitive system

9    they're not going to be built in the first place.

10   If they're not going to be built in the first place,

11   they don't get in the rate base or whatever, and so

12   your    prices        should   be    lower,   and    significantly

13   lower, other things equal.

14                    It     may    be,    however,      that     Joskow's

15   comments are more directed about what may happen

16   under regulation when, in fact, you have incentive

17   regulation and things like that.              So if you do that

18   and if you take account of the fact that maybe some

19   of these stranded assets have reached the point in

20   their    life     in     the   regulated      system       where   the

21   depreciation schedule is such that the contribution

22   of those, the cost of services diminishing, perhaps

23   that's how he gets this kind of result.

1                   Doug, you mentioned the point about spot

2    elasticities and the fact that you're really data

3    short on that.       Two suggestions there.

4                   What we're really talking about is peak

5    shifting      in     that     context,           is   to       look     at

6    international data where, in fact -- and, of course,

7    the U.K. would be the prime one -- where you do have

8    some data that may be useful.

9                   And,        secondly,        there     is       quite     a

10   literature     on     time     of     day    pricing        even       with

11   regulation, and you may be able to use that.

12                  A third point, I had a question for you

13   on this question of how pool delineation.                        How are

14   you   going   to     handle    that?         I    mean     how    do   you

15   delineate     what    is    the     power    pool     in   a     regional

16   locational sense?

17                  On your steps where you talked about --

18   on the latter part of your paper, pages 11 and 12,

19   the various step, when I read those steps I thought

20   that you have to or my guess would be that what you

21   had as a portion of Step 2, which has to do with

22   data collection, was more important than Step 1 that

23   had to do with the NEMS model in that I think if

1    you're    going     to    grapple    with    this     problem,   your

2    collection of the actual data that will be emerging

3    or the mechanisms you have to collect those data --

4    I would put that as Step 1, not as part of Step 2.

5                    A     comment     Tim     made      about   capacity

6    allocation and the regulated wedge for transmission,

7    and it's frequent to think of that as being in the

8    kind of natural monopoly category, which is why you

9    may want to have regulation.

10                   I think you can go a step further than

11   that,     however.           If     you      really      had     total

12   deregulation, and it's a step that natural gas is

13   yet to go to, that is, where rather than just, in

14   effect, renting capacity rights on the pipeline and

15   in this case an electric transmission facilities,

16   you, in fact, acquire property rights on the system,

17   and you had a capacity release market.                  You wouldn't

18   need     to    have      regulation       even   of     transmission

19   facilities.

20                   My final comment on Doug's paper is that

21   my     guess   is     that   if     you     do   have    electricity

22   deregulation, we're going to be surprised about how

23   pervasive it is and how quickly it takes place in

1    that you do have the natural gas industry to look

2    at, and everybody has been surprised at the extent

3    to which a competitive market has emerged in a way

4    and to a degree that hadn't been anticipated.

5                    If you look at the recent studies or

6    papers, say, by DeVany and Walls on the way in which

7    all the prices, the natural gas prices across the

8    system from one end of it to the other, from Canada

9    right through to Louisiana, are linked and he degree

10   to which they're linked, that has been a surprise

11   that that has happened that quickly.

12                   Now, dealing with Art's paper, I had one

13   question, and I will, notwithstanding our Chairman's

14   caveats   have    a   stab   at   answering   some   of   your

15   questions here, but these 108 pricing periods.            Were

16   you   talking    about   are   they   different   prices   at

17   different times of the day over different days or

18   the year or they're just different days in the year?

19   It wasn't clear from your paper just what these

20   time slots represented, the 108.

21                   MR. HOLLAND:      They were selected to try

22   to capture the full range of load characteristics

23   throughout the year.

1                       MR. WATKINS:         Okay.     So they vary by

2    time of day.

3                       MR. HOLLAND:     They vary by time of --

4                       MR. WATKINS:         That's seasonal and time

5    of day.

6                       MR. HOLLAND:     Correct.

7                       MR. WATKINS:     Within the seasons.              Okay.

8                       MR. HOLLAND:     Seasonal and time of day.

9                       MR. WATKINS:     Okay.       I understand.

10                      MR.   HOLLAND:        And    they    vary    in     the

11   number of hours, as well.

12                      MR.   WATKINS:        Right.        Well,    on    your

13   Question 1 about what analysis stage while modeling

14   products, I jotted down three things here.                       One is

15   price formation.            The second one, I would suggest,

16   is   plant    utilization,        and    I'm     including      in    that

17   investment in new plants, and the other one I jotted

18   down was this question of inter-regional trade that

19   may emerge, as you rightly pointed out, to a much

20   greater degree with deregulation, that aspect.

21                      On your Item 4, I think there's too much

22   focus here on the spot price.                   With a deregulated

23   market,      you    could    have   a    much     greater      array    of

1    contracts, of different terms and conditions.

2                 Tim    was     talking     about   the     airline

3    industry   and,    you    know,   the   great   array    there.

4    You're going to have that probably happen.

5                 Also, if you have futures markets that

6    do develop, you may be able to sign up equivalently

7    for prices one, two, three, four years in advance

8    using those kinds of mechanisms.           So I think your

9    concern with the spot price is too great.               I think

10   you're going to have a greater range.

11                The discussion of the energy prices and

12   your market clearing mechanism, I wondered why that

13   wasn't simpler to think of in terms of just the

14   distinction between short run and long run marginal

15   costs, but I'm not sure I really understood your

16   simulations in terms of your methodology.

17                Could you put up the first graph again?

18   Was it New England?         I mean your reactor results.

19   You know, you had the ones you had just done this

20   week.

21                MR. HOLLAND:         The ones with the spot

22   prices?

23                MR. WATKINS:         Yeah, and the components

1    of the price.

2                     MR. HOLLAND:     The first one was ERCOT.

3                     MR. WATKINS:     Now, I mean, I'm not sure

4    I understand your methodology.             The way I saw it

5    described in the paper because there's a gap between

6    the capacity and the peak demands, ostensibly both

7    the ex ante and ex post demand is satisfied.               So why

8    is there a red component to the charge at all in the

9    context of your methodology?

10                    And then if there is a red component in

11   there,     I    don't     quite   understand     some     of   the

12   relationships.          For example -- I'll have to point

13   here -- this one is almost past here.                So why isn't

14   this --

15                    MR. HOLLAND:     Actually you should go to

16   the second season.            That's the first price in the

17   second season.          So you should look at the second

18   position of the top blue line.

19                    MR. WATKINS:      Oh, all right.         So it's

20   not -- what I was going to say is suppose they were

21   aligned.        You   would    expect   this   one   to   be   much

22   higher.        The gap here is squeezed.         So maybe when

23   you align it, perhaps you get that pattern when you

1    align it, but my main question was I don't quite

2    understand    how     the    calculations      emerge        if    I

3    understand your methodology properly.

4                  I think that's it.

5                  CHAIRMAN MOUNT:     Cal?

6                  MR. KENT:      Most of the things that I was

7    going to say have already been covered, but let me

8    just stress a few things that I think need to be re-

9    emphasized.

10                 The first one is to thank Doug for a

11   very   insightful     paper.       As    an    economist,          I

12   appreciated reading it very much, and what you're

13   attempting to do with that, I think, is extremely

14   useful.

15                 I did come away though with the feeling

16   that it's going to be very difficult for EIA to

17   respond   even   to   your    paper,    much   less     to    this

18   environment, because we don't know yet what it is

19   that we need to know, and that's very hard to plan

20   or to model or to even figure out what data it is

21   until we know what it is that we need to know, and I

22   didn't get the feeling that we were certain enough

23   in our knowledge of what was going to be expected,

1    what    questions    were    going      to    be       asked,    that   we

2    really knew what it was that we ought to be out

3    there looking for.

4                     The second thing is I would reemphasize

5    what Campbell just said, and that was I think there

6    was an overemphasis in Art's paper on spot markets.

7    I think that the interesting play is going to get

8    to be the futures markets, which I think are going

9    to develop very, very quickly in this area, and that

10   that may alleviate some of the problems, Art, that

11   you     talked    about    as    soon    as        a    future    market

12   develops, and I certainly think that they are going

13   to be more important, as they have proven to be in

14   other      energy     sources,        particularly              petroleum

15   markets.

16                    The next thing is just to make a general

17   comment.       In one sense natural gas has kind of led

18   the way, and as I was reading between about four

19   o'clock this morning as I was flying in from Los

20   Angeles the paper on natural gas, it surprised me

21   that some of the questions that were being asked

22   there    about    what    sort   of   data     issues      were    being

23   raised    by     deregulation    I    think    are       going     to   be

1    exactly some of the same issues that you all are

2    going to be facing, and there may be quite a bit

3    more out of the natural gas deregulation that you

4    can mind for indicating to you or indicating what

5    direction you should go, certainly not to the degree

6    that took place in natural gas.

7                The    stranded    costs     have   occurred   in

8    natural gas, and I'm babbling now.        So let me see if

9    I can clarify that point.

10               The deregulation of natural gas has led

11   to stranded costs.      They are certainly not of the

12   magnitude of the major nuclear power plants, but

13   particularly into East Coast or eastern area gas

14   producers, such as those in West Virginia, have had

15   terrible losses due to stranded costs that they have

16   not been able to recover because of the distribution

17   system that exists in the East as opposed to that

18   that is now in the South and certainly to the West.

19               And so I think that what you're going to

20   have is that since historically any time an industry

21   has become more competitive, whether it's through

22   the   natural     entrance    of   new     competitors     or

23   deregulation, there are always going to be stranded

1    costs that were there and that were only justified

2    because of a monopoly position, either a natural

3    monopoly position or a regulated monopoly position.

4                      And I think that the other remark that

5    was made is that we are going to be surprised at how

6    fast    we're     going        to    see    competition;     that     this

7    stranded cost issue may very, very quickly almost

8    get itself solved just because of the fact that the

9    market is going to force the issue much more quickly

10   than we may even be able to comprehend it, and my

11   suspicion is that the end result is going to be as

12   historically it has almost always been, and that is

13   to say to the people who are stuck with the stranded

14   costs, "You get to eat them."

15                     And I think if you take a look at the

16   prices of shares of certain utilities today, you can

17   begin   to    see       that    to    an    extent   the     market   has

18   already anticipated that result, and so I may be

19   saying that this whole issue of stranded costs may

20   be one that you're not going to have to worry about

21   modeling     as    much    as       you    think   because    it's    just

22   going to happen.          There are going to be some losers.

23   It's    going      to    be     quick      and   merciless    for    their

1    stockholders, and then after that the market will

2    sort its way out.

3                 And I may be wrong on that, but that's

4    just my suspicion of the way things are going to

5    happen.

6                 Then the last comment, and I'll shut up,

7    is I think as Doug's point as made in his paper.           I

8    think there's going to be a tremendous amount of

9    interest in what us economists call the transactions

10   costs, and I think this gets back to what Joskow was

11   talking   about   in   his   paper,   if   I   remember   it.

12   There's going to be phenomenal transactions costs

13   involved here, particularly in the rather extended

14   transition period we're going to go through, and

15   those transactions costs are going to be much more

16   interesting than the generating costs that we talked

17   about in the past, and that may very well be where

18   some of the efficiencies are lost, is just through

19   these transactions costs.

20                And you can go back to Coase's original

21   work in the area and everything like this, and I

22   think that a lot of the anomalies that you may see

23   developing in this market and are probably already

1    developing in the natural gas markets are due to

2    these transaction costs that we tend to overlook and

3    we tend not to model.

4                   So that's my whole comment.

5                   CHAIRMAN MOUNT:           Thank you.

6                   The rest of the Committee is silent.                  I

7    am amazed.

8                   So how about members of the public back

9    there?     Anybody would like to comment?                    Would you

10   like to respond?

11                  MR. HALE:       Oh, yeah, sure.           Just first

12   thank you all very much for your comments.

13                  First,     just       a     couple       of     things.

14   Campbell    and   I   will     be    talking     some    more     this

15   afternoon, I'm sure, but there are a couple that are

16   worth talking about now.

17                  First,    the    emphasis        on    spot    markets,

18   spot pricing, I agree with Campbell that what the

19   consumers are going to see are not the spot prices,

20   okay, but the spot prices to the extent that you get

21   something like that happening is the grist for the

22   mill.      I   mean     that    is       what   all    the     futures

23   contracts, all the deals, all the packages are based

1    upon.

2                   If you don't get the spot market prices

3    right, you should go home now because the rest of it

4    is just -- you've got nothing to work with.                              So

5    that's the emphasis on spot.

6                   We're not all that optimistic.                   Well, we

7    find that real hard right now to even think about

8    getting the spot market prices right without going

9    to    the   next     level    of      the    packaging         that     the

10   entrepreneurs are doing right now.

11                  Second, I think everybody has a lot of

12   priors about how this restructuring is going to go.

13   You know, as a personal opinion, I believe that

14   we're going to see a huge amount of efficiency gain.

15   I think we're going to see de facto deregulation

16   very, very quickly for industrials and commercial

17   and   people   who    are     lucky      enough     to    be    close    to

18   borders between utility districts.

19                  I     think        you're    going        to    see    more

20   attempts on the parts of utilities to insure their

21   monopoly    position     as       best     they   possibly        can   be

22   mergers, acquisitions, joining up with natural gas

23   companies,     joining       up    with     the   cable        companies,

1    anything they can to control various aspects.

2                  And I also think that what you're going

3    to see is, in fact, you won't see nodal prices.

4    You'll see something zonal, but we'll get to that in

5    a second.

6                  I believe all this stuff, but when I

7    look at the data I got and I look at my models and

8    my analytical capability, I'm not really persuaded

9    that I've got other than a religious case to make at

10   this stage.    I believe that the answer I've given is

11   the right one.    I haven't seen it yet.

12                 MR. WATKINS:     Religious must be perfect

13   foresight.

14                 MR. HALE:    Once again, I started out by

15   saying I know where dancing leads.           I don't know

16   where this leads for sure.

17                 Okay.     I really don't see any conflict

18   whatsoever    between     environmental    protection    and

19   restructuring.    I think that there's a real chance

20   that   by   pricing   electricity   much   closer   to   its

21   social cost you're going to see much better resource

22   use, and I think you're going to see the old, ill

23   controlled facilities shutting down much quicker.          I

1    think you're going to see electricity used the way

2    it should be, and I think the environmental benefits

3    could be substantial.

4                  I     think     this     is        one    where     the

5    environmentalists are very, very wrong, and I hope

6    that I'm right on this one.

7                  The issue of power pool delineation is

8    critical.    It's the name of the game.                I don't know

9    what   to   say.     I    mean   the      size    of    the    market

10   determines how well this is going to work, and if

11   the market is expanding, the larger it is, you know,

12   the better for all of us.

13                 There was a point made that perhaps in

14   the analysis agenda Step 2 should actually be Step

15   1, and I think the argument I'm making or the fact

16   is Step 1 is already underway, and what I was trying

17   to do in Step 2 is argue that we should return to

18   some of these data issues just as quickly as we

19   possibly can.

20                 I'm   not     saying   we     shouldn't     be    doing

21   what we're doing, but the data issues are not going

22   to go away, and they are basic material for coming

23   to any conclusion at all or contributing to this

1    debate at all.

2                       Joskow,       I'll     either             get    the        proper

3    citation       and       quote     or    I'll           send       you     a        note

4    recanting.         How's that?

5                       So I really appreciate your comments and

6    suggestions on the paper, and I'm looking forward to

7    talking       to   you     all     privately            on     more      technical

8    matters.

9                       Oh,    one     other       thing          I     do     want       to

10   mention.           In    looking        at    how        spot       prices          are

11   calculated, it becomes very, very clear to you that

12   a lot of the pricing algorithms and a lot of the

13   dispatch operations that are done now by engineers

14   are    done    based      on     rules       of    thumb,          and     computer

15   software and control software that's good enough.

16   Why?    Because making the software better, making the

17   calculations         better,         getting        your         approximations

18   more   accurate          doesn't      make        you    any       money       in    an

19   average cost pricing world.                  It's a wash.

20                      Now    I    think     there          are        going       to    be

21   substantial              incentives               for          much            better

22   approximations           of    the      physical         constraints,                the

23   flows throughout the system, substantial incentives

1    to go from zonal, you know, to finer and finer and

2    finer zones because if you have a difference between

3    the accounting cost and the economic values, that's

4    a license to steal, and they're going to do it.

5                    So that's my last pitch on that.

6                    MR.   CHATTERJEE:         Can     I     ask?      This

7    question is for Doug.

8                    MR. HALE:   Yeah.

9                    MR.   CHATTERJEE:         Do    you   envisage     the

10   effect of deregulation to be many small, efficiently

11   run   utility    companies,     or   do    you    see    large    mega

12   utility companies?

13                   MR. HALE:      I think you're going to see a

14   lot   of   gorillas,     you     know,     fighting       over    each

15   other's territory a lot at the fringes.                        I don't

16   think you're going to see atomistic competition.                     I

17   just don't.

18                   But, you know, the key elements to me,

19   at least, are what do they do with the transmission

20   systems, you know, and control.                It has very little

21   -- and control has to do with what gets dispatched,

22   who gets turned on and off, and what conditions,

23   that sort of thing.

1                           I think at least the control part is

2    inherently monopolistic and will remain that way and

3    will be regulated.                 Transmission I'm not so sure of,

4    at least long distance, you know, the high power

5    transmission.               I'm not so sure what that is.

6                           So I would imagine you're going to have

7    fairly large firms.

8                           MR. CHATTERJEE:            The difference in spot

9    pricing, of course, was diminished at the efficiency

10   of the transmission.

11                          MR. HALE:          Absolutely, absolutely.            So

12   that's our best bet, I think.                       I think you're going

13   to have a lot of gorillas, you know, big firms, but

14   if     we       can     get       the     transmission       system    working

15   properly, I think there's going to be very effective

16   competition amongst large firms.                          I just don't see

17   small firms being able to complete.                             I mean they

18   can't           even        afford      the     software       to      do   the

19   calculations I don't think.

20                          MR. WATKINS:           I think, Doug, you should

21   draw        a    distinction            between     the     generation      and

22   distribution                and   transmission.             There's     greater

23   likelihood             of    a    small    firm    or   a    more     atomistic

1    competition in generation.

2                      MR. HALE:      Oh, absolutely.              Yeah, I'm

3    sorry.       See, I think the real question has to do

4    with    transmission     and    control      of    the    system.     I

5    think control of the system is probably going to --

6    you know, the ISO or whatever you call it is going

7    to     end   up     viewed     as     some   sort        of    natural,

8    indivisible, you know, kind of monopoly that you're

9    going to have to have regulation.                  Transmission to

10   me is an open game still.            I just don't know.

11                     MR. WATKINS:        I mean in generation the

12   efficiency        of   small     turbines         and    the     change

13   associated with that is very strong.

14                     MR. HALE:         No, I agree.          I think in

15   generation you're going to have opportunities for

16   small firms, but I don't think generation is where

17   the action is going to be in this market.                       I think

18   you're right, but that's not where you're going to

19   make your money, in my opinion.              We'll see.

20                     MR. HOLLAND:        I had just a couple of

21   comments I wanted to make about some of the things

22   that were said.

23                     This issue about the emphasis on spot

1    prices, there are a couple of reasons for that.                      I

2    agree completely that most consumers are probably

3    not going to see those spot prices.                     They're going

4    to see contracts, and one of the things that we're

5    doing with the spot pricing mechanism or the spot

6    pricing algorithm is to try to calculate what those

7    contract prices are going to be.

8                    There's a possibility we may even use

9    the spot pricing algorithm to develop a range of

10   prices over which contracts could exist.                    Given what

11   assumptions are done in the particular modeling run,

12   you    may   even       think    of    the   energy     component   as

13   defining the floor of the contract prices and the

14   reliability        or     market       clearing       component     and

15   possibly     the    insurance         component    as   defining    the

16   ceiling of those contract prices, depending on how

17   much    reliability           different      consumers       want   to

18   purchase from their generation suppliers.

19                   A second thing or point for the spot

20   pricing is if you reduce the price of electricity by

21   restructuring       the         electric     power      industry    and

22   nothing      happens     to     your    demands,     what    have   you

23   accomplished?        Possibly some of your big bangs are

1    going to come from load leveling that will change

2    your   capacity    planning    decisions     and      also   could

3    change the way you operate your system.

4                 When    Larry     Ruff     spoke    at    the     NEMS

5    conference, he talked about a system where as the

6    limits of your capacity start to be reached, you

7    need some mechanism to jack the price up so that you

8    start getting people who don't value electricity as

9    much off of your system.           That keeps you from having

10   to decide where you shed your loads.

11                It also is a good load management -- I

12   think pricing is possibly the best load management

13   system, but the energy component doesn't give you

14   enough of that.     You have to have some other way to

15   calculate how much you increase your prices.                    So

16   this algorithm is trying to do that.

17                We talked about that it was mentioned

18   that there was no capacity.          Some people are using a

19   capacity   chart    which     is    based   on   the    cost    of

20   building the capacity, but that's doesn't get at

21   what the demand -- what your consumers' value is,

22   how much they're willing to pay, what the market

23   will bear is, and that value of unserved energy is a

1    way to estimate or guess what the consumer or what

2    the market will bear.

3                   That   has     to     be    a   varying     input

4    assumption because everyone has a different value

5    that they place on electricity during a blackout.               A

6    good example might be to look at what a restaurant

7    owner    in   Georgetown    might   be    willing   to   pay   for

8    electricity on Friday night if he's got a dining

9    room full of customers and the lights go out, and

10   then you might look at a college student with their

11   boyfriend or girlfriend on Friday night sitting on

12   the sofa in front of the television and the lights

13   go out.

14                  (Laughter.)

15                  MR. HOLLAND:         They are very different

16   amounts that they would pay to bring the lights back

17   on.     So that's what that value of unserved energy is

18   trying to get at.

19                  So what's all that I wanted to say about

20   that.

21                  CHAIRMAN MOUNT:        Anymore comments from

22   the Committee?     From the public?

23                  So I thank you both very much, and we

1   are adjourned and we will meet back here at two

2   o'clock.

3               (Whereupon, at 12:22 p.m., the meeting

4   was recessed for lunch, to reconvene at 2:00 p.m.,

5   the same day.)


1                           AFTERNOON SESSION

2                                                             (2:05 p.m.)

3                   CHAIRMAN MOUNT:            I'd like to reconvene

4    the meeting of the ASA Committee, and there will be

5    two presentations on the residential and commercial

6    demand models in NEMS.

7                   The    first      one     is     going    to      be    John

8    Cymbalsky,     Office       of     Integrated           Analysis        and

9    Forecasting.

10                  MR. CYMBALSKY:           Okay.    Thank you, Tim.

11                  Is it okay if I talk like this for the

12   transcript?    Okay.

13                  As Tim said, my name is John Cymbalsky

14   with    the    Office       of     Integrated           Analysis        and

15   Forecasting.        I've been with EIA doing residential

16   demand modeling for almost seven years now.                            That

17   covers, I think, seven AEOs I've done since I've

18   been here.

19                  Today's presentation, I'm going to talk

20   about   the   NEMS     residential        model       and     especially

21   focus on the projections from AEO '96.

22                  To    give       those    of     you     who      are    not

23   familiar   with      NEMS   a    little       overview      of   what   it

1    does, okay, the NEMS energy model has 11 supply and

2    demand models, a macroeconomic activity model, and

3    an emissions model.         This is a general equilibrium

4    model, and it iterates over the years to come to a

5    partial equilibrium for the energy supplies/demand

6    market.

7                  Now, talking about the residential model

8    in particular, it's not an econometric model.                 It's

9    an energy engineering economic modeling structure.

10   It's very data intensive.          It has information about

11   the housing stock, the equipment stock, appliance

12   efficiencies.        We have technology choices.           We have

13   building     shell     efficiencies,      and   all   of     these

14   numbers vary by the nine Census divisions and three

15   building types.

16                 We also model at the end use level, and

17   we have about seven end uses, including lighting,

18   heating, cooling, water heating, and the like.

19                 Now, for AEO '96 and all AEOs that I've

20   been involved with, we run generally three cases for

21   the AEO.      We have the reference case, which I'm

22   going to call the business as usual, and what that

23   means   is   that    we   assume   that   policy   will     remain

1    unchanged as it exists today for the next 20 years.

2                    We also have the low and high world oil

3    price    cases       where    we     perturb       the     oil     price

4    projections and see what the response in the energy

5    markets are.

6                    We also do low and high economic growth

7    cases,    and   we    perturb      GDP    and    see   what     happens,

8    again, with the energy markets in these scenarios,

9    and for the last two AEOs, we've also used stand

10   alone technology cases for both the residential and

11   commercial models.           In these cases, what we did is

12   we made assumptions about technology, whether it's

13   going to be a high technology case, which is the

14   best technology available, or frozen technology case

15   where we freeze technology at its 1995 levels and

16   then we want to see what happens, you know, when you

17   make     different      assumptions         about        technological

18   progress in the future.

19                   Okay.        My first graphic here is just

20   showing historical and projected residential primary

21   and    delivered     energy.        You    can    see     the    primary

22   energy line versus the delivered energy line has

23   been diverging over the past, say, ten years, and we

1    project     this   to     continue,       and     this        is   just

2    increasing    electricity       penetration       in     residential

3    market, and when you convert that to primary, you

4    can see that the lines diverge even more.

5                  Okay.       This    graph     now       shows    primary

6    energy    intensity       for    historical        and        projected

7    residential energy demand.            You can see that on a

8    per   household        basis,     energy        consumption           per

9    household    has   been    coming    down       for     the    past   20

10   years, and also -- and this is due to efficiency

11   standards and the like -- and our forecast you can

12   see also has it slightly declining, but the thing to

13   note here is if you look on the square foot basis

14   and the per household basis, you can see the square

15   foot basis, it's declining more in the forecast, and

16   that's due to the fact that we're projecting bigger

17   households in the future in terms of the physical

18   square footage.

19                 Okay.     This graphic shows historical and

20   projected    primary    fuel     shares    in     the    residential

21   sector.     From the graph you can see that in 1970

22   electricity and gas almost had the same share in the

23   residential sector, and in 1994 you can notice how

1    different the fuel shares have changed.                  We have an

2    increasing      electrification,         and    again,    this     is

3    primary     energy.        So   electricity     has,     you   know,

4    dominated the market in terms of market penetration

5    in    the   last    24    years,   and    we   project     this   to

6    continue for the next 20 years or so.

7                    Now, if we look at the end use energy

8    for the residential sector, you can see that space

9    conditioning, which is heating and cooling, is the

10   largest end use in the sector, has been and will

11   continue to be in the projection period.

12                   You can see that the other category is

13   all of the other categories that aren't listed, and

14   this   is     mostly     miscellaneous    electric     appliances.

15   You can see that grows enormously in the projection,

16   and    this    is   due    to   the   fact     that   they're     all

17   electric, and there's no efficiency standards for

18   most of these appliances.             So as they penetrate the

19   market, they just increase over time.

20                   And      another   important      fact     here    is

21   refrigeration as an end use, even with the addition

22   of the number of refrigerators in the stock in the

23   past up till now, you can see the actual consumption

1    by refrigerators has declined, and this is due to

2    the   federal       energy         efficiency       standards      for

3    refrigerators in both 1990 and 1993.

4                  Okay.         This    next    slide    shows   housing

5    growth in the pie, in the projection period from

6    1994 to 2015, and what we did with the pie is we

7    wanted   to   break    out    and     show   you     where   in    the

8    country the housing growth is projected to be in the

9    next 20 years.

10                 You     can    see     that    the     South   has    47

11   percent of the growth in housing in the projection

12   period, and to show you, you know, what's going to

13   happen with fuel use for the next 20 years, it's

14   important to know regionally what fuels are being

15   used, for space heating especially since it's the

16   biggest end use, and you can see that in the South,

17   which has 47 percent of the builds, it also has 56

18   percent space heating for electricity and only 43

19   percent for gas.

20                 Now, nationally -- well, for the rest of

21   the nation the trend is different.                  It's 68 percent

22   for gas and only 24 percent for electricity.                       So

23   this is very important in the modeling to know that

1    the region in the country where the houses are being

2    built is very important in terms of which fuels will

3    be used in the future.

4                   MR.   LOCKHART:      Is   that   primarily    the

5    heat pumps?

6                   MR. CYMBALSKY:      Yeah, heat pumps mostly

7    are in the South.      That's right.      So most of the new

8    construction    in   the   South   are   using   heat    pumps.

9    Whereas the rest of the country tends to go with gas

10   furnaces.

11                  MR. LOCKHART:     Okay.

12                  MR. KENT:   Is that the delta that you're

13   talking about there or is that the stock that you're

14   looking at?

15                  MR.   CYMBALSKY:      Right.       It    is   the

16   accumulation of all the new stock from 1994 to 2015.

17                  MR. KENT:     But it isn't anything -- I

18   mean what you're saying is 2015, this is where we're

19   going to be.     It's not just talking about what the

20   change is?

21                  MR. CYMBALSKY:      It says that between '94

22   and 2015 if you build 20 million homes, of those 20

23   million that's the percentages.

1                   MR. KENT:    Okay.         So it is the change.

2                   MR. CYMBALSKY:         Right, correct.

3                   Yeah, and in the South the reason they

4    use heat pumps obviously, they have lower heating

5    loads than in the North.              The fuel price is less

6    important.        So,      you       know,       they'll      go   for

7    electricity.

8                   Okay.    Again, here this is just going to

9    reestablish    the     growth    in       the    households    that   I

10   mentioned in the last slide, and you can see that in

11   the middle, the south Atlantic, east south central,

12   and the west south central are the three big growers

13   out of the nine Census divisions, the south Atlantic

14   especially because that's already the biggest Census

15   division in terms of households and energy use, and

16   you can see that's going to grow the biggest, and it

17   already has the most houses.                    So that's a major

18   impact in the forecast.

19                  Okay.      This       is    the    energy   intensity

20   change from '94 to 2015 as a growth rate:                     primary

21   fuel consumption per household, and again, you can

22   see   refrigeration        on    a        per     household    basis,

23   refrigeration as an end use we project to decline

1    over three percent per year in intensity, and again,

2    "other" is all of the miscellaneous electricity end

3    uses which do not have federal efficiency standards

4    associated with them.                So they basically will grow

5    as they penetrate into the housing market.

6                      This graph just shows to give you an

7    idea of the intensity for each of the three housing

8    types that we have in the model in 1994.                         There's

9    really no surprise here.                  Single family, you know,

10   they're     the     biggest      houses;      they      use    the   most

11   energy.     Multi-family, they, you know, tend to be

12   apartments and smaller.              So they use the least.

13                     Okay.        As I mentioned before, we had

14   three side cases that we ran or two side cases that

15   we ran relative to the reference case in this year's

16   AEO, and this graph is just going to show over time

17   the    difference         from       the     reference        case   that

18   different technology assumptions -- what impact they

19   have on consumption in the sector, and you can see

20   that   if    there        were       on    efficiency       improvements

21   relative to 1995, we would use about one and a half

22   quads more by 2015 relative to the reference case.

23                     But     if    we    employed       best     technology

1    choice in the next 20 years, there's a potential for

2    over three quads of savings in the sector by 2015.

3                   And when we run these cases, basically

4    the cases are run such that economics are not a

5    factor in the decision making for the technologies

6    for the side cases, but what I've found interesting

7    and people always ask is, "Well, what if you looked

8    at the investment costs for these technologies?              How

9    much   would    they     cost   and   what      would   be   the

10   incremental investment needed for the savings?"

11                  So what this graph does is try to show

12   you what level of investment in certain appliances

13   is in the AEO reference case and then how much more

14   it   would   cost   to   get    the   savings    that   I    just

15   mentioned in the previous slide.

16                  The top line shows in the AEO reference

17   case what Americans are paying for the fuel costs

18   for these appliances, and you can see it's around

19   $80 billion in 1991 dollars, and then the next line

20   down is the capital investment associated with the

21   AEO reference case.       So you could see that Americans

22   are paying somewhere around $30 billion for this

23   equipment.

1                  And then relative to the base case, we

2    want to look at the best technology case and ask

3    ourselves, well, how much incremental investment and

4    how   much   incremental   savings   we   would   get   from

5    running the case, and you can see the red line.          In

6    the first years you need a lot more investment to

7    get the fuel cost savings, and then around 2005 you

8    can see that the lines intersect, and by the end you

9    have more fuel cost savings than you do investment.

10                 Now, there is no discounting of the cash

11   flows here.    So this is just undiscounted money.

12                 And the last slide is to look at this

13   same thing, but on an end use level for electricity

14   and gas.     So you could see that the important thing

15   to note on this is the bottom graph -- excuse me --

16   the top graph shows that in electric water heating

17   it's the only end use where the savings is greater

18   than the investment, and this basically is because

19   of the heat pump water heater that is out there and

20   is a viable technology.      It's not be purchased much

21   now, but the fuel cost savings associated with using

22   this electric heat pump water heater far outweigh

23   the investment needed.

1                     So you can see by all of the end uses

2    sort of what would be needed in terms of investment

3    to get the savings.

4                     Okay, and I think I'm out of time.                     I'll

5    turn it over to Erin.

6                     CHAIRMAN MOUNT:            The next presentation

7    is     going    to     be    by     Erin    Boedecker,         Office     of

8    Integrated Analysis and Forecasting.

9                     MS. BOEDECKER:            I'm John's counterpart

10   on   the   commercial        side     of    the    house,      and   so   I

11   project       energy    demand      in     the    commercial      sector,

12   mainly dealing with building energy.

13                    Today I'd like to look at the trends

14   that    are    shown    in    AEO    '96    as    far    as    commercial

15   energy use and intensity, looking at both primary

16   energy, which includes the electricity losses from

17   production       and    distribution,            and    also    delivered

18   energy; look at what types of fuels are used and how

19   those fuels are used.             then I'd like to look at some

20   of the factors that contribute to the trends, look

21   at the end uses in more detail, look at different

22   areas of the country, and also look at the different

23   types of businesses that are portrayed in the model.

1                   And    finally,      I'd    like     to    present    the

2    future energy savings that are projected in AEO '96

3    in the reference case, and also show the potential

4    for additional savings if the commercial sector were

5    to change the way that they make their investment

6    decisions.

7                   In the commercial sector, we're mainly

8    talking   about       building      energy,       and    so    for   our

9    intensity measure we typically use BTUs per square

10   foot instead of per capita or some other measure.

11                  Over    the     forecast,      you       can    see   that

12   energy intensity is projected to decline, and as far

13   as   primary   energy,       this      reverses     the       historical

14   trend for the last 20 years.                  In the model, this

15   decline   is    due     to     efficiency      gains      represented

16   through standards, such as the Energy Policy Act;

17   voluntary programs, such as EPA's Green Lights and

18   Energy Star Programs; and also efficiency gains in

19   electricity generation.

20                  This     year     the      shift     in    focus      from

21   delivered energy to primary energy has emphasized

22   the commercial sector's reliance on electricity, and

23   this dependence is expected to continue just like it

1    is in the residential sector.

2                  I'll     explain    a    little       bit    about       this

3    slide before I talk about it.                The numbers far to

4    the left are total commercial energy consumption.

5    The top of the slide is for 1994 and the bottom is

6    for 2015.    The pie charts show us energy consumption

7    by fuel, and here you can see that electricity is

8    expected to maintain its share at 73 percent.                          The

9    right-hand     side     columns       show      you       the     energy

10   consumption by end use.

11                 Now, the fuel shares are projected to be

12   stable, but the composition of end uses is projected

13   to change slightly.

14                 As you can see, office equipment, which

15   includes     PCs,     copiers,        faxes,        that        type    of

16   equipment, and also the other use category, which

17   includes     such     emerging     technologies            as    medical

18   imaging technology and telecommunications equipment,

19   are   both   expected     to     continue      to     penetrate        the

20   commercial market.

21                 We made more changes to the model this

22   year to more accurately reflect the popularity and

23   advances in these areas.

1                   On the other hand, the percent of total

2    energy consumption and also energy use per square

3    foot, as is shown on this slide, both decrease for

4    uses that have reached market saturation, such as

5    space conditioning, water heating, and lighting.

6                   These    declines    reflect   the    efficiency

7    gains that I spoke of earlier, and also in water

8    heating, they reflect the shift from electricity to

9    natural gas.

10                  The efficiency gains are also expected

11   in   office      equipment,        but   these      gains   are

12   overshadowed by the project growth.

13                  This slide shows fuel shares by end use,

14   and this more clearly reflects the shift in water

15   heating from electricity to natural gas as a fuel.

16   Again,   it     shows    the   sector's       reliability   on

17   electricity, and it shows that the changing end use

18   composition does play an important role in trends,

19   but there are also other factors that affect energy

20   consumption, and we'll see whether they reinforce

21   the national trend or counteract each other.

22                  Just as John looked at different areas

23   of the country, we will for the commercial sector,

1    too,    and    energy       use     in   different       areas       of    the

2    country       is         affected        by     both        climate        and

3    demographics.            The commercial sector does operate at

4    the Census division level, which there are nine of,

5    and    the    south       Atlantic       division      is     the   largest

6    sector.       It covers the East Coast from Maryland to

7    Florida,      and        it's     also    projected         to   grow      the

8    fastest.

9                       The     only    division       in    the      commercial

10   sector that is not expected to grow is New England.

11                      Looking at energy intensity by area of

12   the country, it's expected to decline in all areas.

13   However, there are two areas of interest on this

14   graph.        If    you     look    at    the   east        south    central

15   division,      which         includes         Mississippi,          Alabama,

16   Tennessee, and Kentucky, it shows very little change

17   in    intensity      relative       to    the   other       areas    of    the

18   country,      and    New     England      shows     declining        use   in

19   energy per square foot even though there's no growth

20   in commercial floor space.

21                      This can be explained at least in part

22   by trends exhibited by another contributing factor,

23   which is building or business type.                    In NEMS we have

1    11 commercial building types, and energy use per

2    square foot does vary by business category.                              Food

3    sales, service, and health care have the highest

4    intensities, while warehouse space has the lowest.

5                    Remember in the last slide that energy

6    intensity decreased very little in the east south

7    central division.             It turns out that health care

8    related space in this division is expected to grow

9    at twice the national rate, and it happens to be one

10   of     the    higher    intensity           end   uses    and     also    is

11   projected to decline in intensity the least.

12                   At      the     same        time,       revisiting       New

13   England,       while     no    growth        is     expected      overall,

14   warehouse       space,        which     has       the    lowest     energy

15   intensity, is projected to increase close to one

16   percent per year over the forecast period.

17                   This slide just projects floor space by

18   building      type     kind    of     for    completeness       since     we

19   showed it for the Census divisions.                        You can see

20   that    the    mercantile       and     service         category,    which

21   contains everything from retail businesses to auto

22   repair, starts with the largest share of floor space

23   and is also expected to show the highest rate of

1    growth.     It retains a much greater share of floor

2    space than most of the energy intensive businesses

3    portrayed.

4                     The next slide shows the considerations

5    that go into choosing equipment in the commercial

6    sector, which in turn affects the energy use.                 We've

7    already looked at the AEO '96 results by end use,

8    Census division, and building type.                Another factor

9    that certainly affects energy use is the payback

10   period consumers require to cover their investment.

11                    In NEMS we have a distribution of six

12   implicit    or    observed   discount      rates    ranging    from

13   just under 20 percent, which is roughly a five-year

14   payback period, to a rate representing those who

15   only     consider      capital    costs    in   their    purchase

16   decisions.

17                    The    effects     of     commercial       sector

18   discount rates can be observed in the technology

19   scenarios for AEO '96.            Just as in the residential

20   sector, for the commercial sector we ran two stand-

21   alone cases with the 1995 technology case assuming

22   no     efficiency      advances    after   that     year.      The

23   efficiency gains represented in the reference case

1    compared     to    that     case     represent         2.4    percent      of

2    energy savings by the year 2015.

3                      However, the potential for much greater

4    savings exists in the high technology case where

5    commercial       consumers        would     choose      only       the    most

6    efficient       technology        available,      regardless         of    the

7    cost.      If     the    commercial       sector       started      to    base

8    investment decisions more on energy use than the

9    cost of equipment, an additional 12 percent savings

10   could be expected by 2015.

11                     However, the price paid for energy by

12   the commercial sector is only expected to rise one

13   tenth   of   one        percent    per    year    over       the   forecast

14   horizon.     So many changes would have to occur before

15   that potential could be realized.

16                     Okay.            That's        the     end        of     my

17   presentation.       It was requested that we come up with

18   a few questions to focus discussion.                     Since this was

19   an informational briefing, we had a tough time.                             I

20   did pull a few out.

21                     The     first     is    more       specific.             The

22   presentation focused on energy use per square foot

23   as the measure of intensity in commercial buildings.

1    What     additional       measures      of   intensity          should   be

2    investigated and would add some type of insights or

3    give a better picture of energy use, if there is a

4    better picture?

5                   And the second question is up for grabs.

6    Is     there   a    statistical      method       of    any     type   that

7    would reconcile the inherent differences between a

8    short-term, econometric type model and a long-term

9    engineering        economic     simulation        model        when    your

10   forecasting years overlap?

11                  This is something that we keep grappling

12   with and would like help with if there's any help

13   out there.

14                  Thank you very much.

15                  CHAIRMAN        MOUNT:        So        the     discussant,

16   Campbell Watkins.

17                  Thank you very much, both of you.

18                  MS. BOEDECKER:         Thank you.

19                  MR.     WATKINS:          I   don't           know    whether

20   there's any help out there, but you'll be pleased to

21   know    that   I    did   at   least     anticipate            the    second

22   question in some of the remarks I want to make.

23                  Both these models are very comprehensive

1    and complex and contain a lot of fine detail, and to

2    my mind or at least to my knowledge are the best

3    models available to capture a lot of the things that

4    you're trying to capture at this time.

5                  As you just indicated in one of your

6    questions there, there are a mix of what I'd call

7    the engineering and econometric approaches, and one

8    can but hope that the outcome of this marriage is

9    fruitful.

10                 It reminds me a little bit of a story

11   about an Irish playwright of the first half of this

12   century, George Bernard Shaw, and he was popular on

13   the circuit at that time.            They used to invite all

14   of   the    famous      and    the     literati     to        weekend

15   gatherings, and one of the persons who used to host

16   these   events    was   a     person   called     Lady    Ottiline

17   Morrell,    and   she   became    very   enamored        of   George

18   Bernard Shaw and said, "Well, you know, really we

19   should get married because look at what talented

20   children we would have.           They'd have my looks and

21   your brains."

22                 And he said, "Well, madame, what if the

23   child had your brains and my looks?"

1                     So I can but hope that the outcome here

2    is useful to us.            I cannot delve into all the fine

3    details of the model.            So what I'm going to do is

4    focus on several design aspects.

5                     Concerning particularly the interaction

6    between the engineering and econometric approaches,

7    I'm going to focus on the models themselves rather

8    than     your    projections        because,    after     all,    the

9    projections flow from the models, and if I focus my

10   attention on the models, that is more valuable, I

11   think.

12                    I'm   going    to    talk     mainly     about   the

13   residential model.           However, several of the comments

14   I have with respect to that carry equally over onto

15   the commercial mode, and I will, however, finish

16   with one or two comments on the commercial model

17   itself.

18                    Let   me    deal    first     of   all    with   the

19   consistency between the econometric and engineering

20   aspects, and I want to discuss just briefly three

21   aspects.        One is the price elasticities; secondly,

22   the issue of technological change; and, thirdly, the

23   issue of reversibility.

1                  As I read the description that I have of

2    the models dealing first with price elasticities,

3    the space heating and cooling energy consumption are

4    assumed to be the components that are affected by

5    prices in the short run, and the short run price

6    elasticity of minus 0.15 is currently employed.

7                  That     to   my   mind        raises    five    issues:

8    firstly,   whether     other     end       users,     such    as   water

9    heaters, dryers, and washers, would not be affected

10   as well; whether the impacts are confined to just

11   own price effects or whether they include cross-

12   price effects; whether the short run elasticity is

13   very strictly speaking short run in being restricted

14   to    intensitive    (phonetic)            use   of    the     existing

15   stocks; how the longer run dynamic impacts of price

16   changes are accommodated; and also the origin and

17   nature of the short-run price elasticity used.

18                 Now,   typically         a    short     run    elasticity

19   picks up not just changes in intensity of use in the

20   short run and whether it's one year or whatever, but

21   we'll talk about one year, but also it does pick up

22   the   first   period    impact     on       replacement        and   new

23   appliance stocks.

1                   Let me just by illustration put up --

2    Richard, if you could just put up a simple model

3    here, this is just purely for illustrative purposes.

4    I'm not suggesting this is the kind of model you

5    would want to use, but it's just to illustrate a

6    point I want to make.

7                   This     is    a      simple    dynamic,   double

8    logarithmic model where the variables are expressed

9    in logarithmic terms, and that being the case, the

10   coefficients    of    the    model    represent   elasticities.

11   So the short-run elasticity that you see there for

12   price would be the coefficient B.             You can show that

13   the long-run elasticity will be given by the ratio

14   of B divided by one minus C.

15                  C is analogous to the retention effect

16   or maybe in certain models it can actually be one

17   minus the rate of depreciation.               So that if C were

18   zero, that means all of the adjustment is in the

19   first   period,   and    so    the    long-run    and   short-run

20   elasticities are the same.

21                  The larger C is, the longer the period

22   of adjustment to a given price change.

23                  Now, the point I want to make is that

1    you have a short-run elasticity which for the sake

2    of argument we'll assume is B, is minus 0.15.                         You

3    have a price change either up or down.                         You plug

4    that   into     your    model    for   the    given      category     of

5    consumption.

6                    Now, suppose that higher price or lower

7    price is sustained in the next period.                        If I read

8    the    model     description       correctly,           you    wouldn't

9    register any change induced by price because there's

10   been no change in the price between Period 1 and 2.

11   However, if you think of the dynamics of the model,

12   what you do is you have another impact from the

13   first period price change, which is how you get all

14   of these dynamic impacts to asymptotically become B

15   over   one     minus    C   eventually    as      the    thing    works

16   through, if the price is maintained at that level

17   throughout.

18                   Now, what is not clear to me is whether

19   that     kind   of     dynamic   impact      is   imbedded       in   the

20   model.    If so, it's not clear from the descriptions

21   that I have read as to just how it does emerge.

22                   The direction of the impact, of omitting

23   the dynamic impacts, if, in fact, they are omitted,

1    is in the direction of reducing the impact of price

2    changes either up or down, but we'll see in a moment

3    another       comment      I      have     is     maybe       an   offsetting

4    element to that.

5                     The short-run elasticity reference that

6    I have for how do you get the minus 0.15 was taken

7    from a report done by Carol Dahl for EIA about a

8    couple of years ago.               I checked the reference there,

9    and it said that that was the elasticity for natural

10   gas    across    all       sectors.         So    if    my     reference    is

11   correct, the question that arises is to what extent

12   is     that    appropriate          for     the     residential          sector

13   rather    than       the    average       across       all     sectors,     and

14   secondly,       the     extent      to      which       the     natural     gas

15   elasticity is appropriate for other fuels.

16                    As an order of magnitude, when I see

17   that    kind    of     number,      it     doesn't      kind       of   trigger

18   something in my mind that says, "Hey, that's too

19   high,"    or     too       low.          It's    just     I'm      trying   to

20   reconcile your source, apparently source, cited for

21   that elasticity and the component of consumption to

22   which you're applying it.

23                    Technological change.                    As I understand

1    the model, these are largely treated autonomously.

2    An example here would be how he treated the building

3    shell efficiencies that gradually improve over time.

4    The      concern      I    would        raise      is     the      interaction

5    between that and any econometric elements of the

6    models,       and     that      is      because         if    you're         using

7    econometric estimates of, say, price elasticities,

8    they themselves are influenced by changes in energy

9    efficiency over time.

10                    I mean it's no surprise that interest in

11   energy        efficiency             became     stimulated             by     the

12   substantial increases in prices in the 1970s and

13   early     1980s.          So     to     the     extent       to    which      any

14   econometric elasticities are affected by changes in

15   energy efficiency and, therefore, embody them, and

16   then    you    have       an   autonomous          technological            change

17   that also is depicting improved efficiency, there

18   could be some form of double counting there.

19                    And if that were the case, that would

20   tend to over-estimate impact.                       So it would be the

21   opposite      side    of       the    coin    to    the      way      that   I've

22   suggested,      a     lack      of     attention        to      the    long-run

23   dynamic aspects may underestimate.

1                       Reversibility.       That issue arises if you

2    have    an    increase      in   energy      prices     followed          by   a

3    decline in energy prices or the other way around.

4    Are these responses reversible?                 In other words, if,

5    say,    the    price    goes     up    and     then    returns       to    its

6    original value and nothing else changes, do you get

7    back to consumption at the original value?

8                       There are various reasons why that would

9    not be so.          Irreversible technology, and maybe you

10   capture       that     in    model      specification;           mandated

11   efficiency         standards     that    don't        revert,    are       not

12   responsive to changes in the conditions.                        There are

13   new    operational       modes,       become    imbedded.         There's

14   changes       in     what   is    terms        bounded    rationality,

15   whereby, say, in the 1960s nobody cared too much

16   about energy budgets, and in the 1970s they became

17   very concerned about those, and when prices went

18   back down in real terms to figures that are not far

19   off what they were in the late '60s, early '70s,

20   nevertheless, people are still very aware of energy

21   costs    and,      therefore,     would      not      revert    to    their

22   original behavior.

23                      The other aspect is that just because

1    prices have switched direction in terms of price

2    expectations, people don't necessarily think that's

3    going to be the case throughout.                     So expectations

4    may affect things as well.

5                     These      are   all     reasons    why   you're    not

6    going to necessarily get reversibility.                        I don't

7    know    what    sort       of   dynamics      are   imbedded    in   the

8    models, but maybe by experimentation you can see

9    whether, in fact, this imbedded assumption in the

10   model that assumes reversibility.                    If so, I think

11   it's something that should be adjusted.

12                    Let me make some other comments.               On the

13   residential          model,     there's    two      housing    vintages

14   where you kick off from.               There's pre-1991 and post-

15   1990.    For the future you keep track of the start by

16   vintage,       but    as    I   read    the    description      in   the

17   residential model -- there's a different aspect in

18   the commercial model which I'll come back to -- you

19   seem to treat the 1990 stock on a kind of average

20   basis.

21                    If that is the case, it seems to me you

22   could by a process -- as long as you have data on

23   housing starts, you could kind of backtrack and get

1    the historical vintages of the housing start.

2                     You        mentioned         that      the        equipment

3    retirement rate in your model depends on a linear

4    decay function.            I assume that the way that function

5    operated    is    it       operated      between      the     minimum   and

6    maximum     lives      that        you   have,       and     you     weren't

7    implying that you'd have an attrition from the first

8    year.     That would be like a flat function and then a

9    reduction.

10                    All equipment in the residential sector,

11   except that for space heating, seemed to be replaced

12   by the same equipment types, although that may well

13   have    improved           efficiency,        but      I      think     that

14   assumption       is    a     bit    restrictive         in    that     water

15   heaters,     washers,        dryers,         and     ranges    could     all

16   switch as well.

17                    The real discount rate that you used of

18   20 percent in life cycle costing for choosing among

19   technologies to my mind appears a bit high, but that

20   may have been picked based on observations about

21   consumer behavior, and I'd be interested in your

22   comment on that.

23                    I'm   not     sure      I    fully     understood       the

1    relationship           between        the       macro     model       and     these

2    components,            both    the        residential          and    commercial

3    sector in that as I understand it energy prices are

4    exogenous         to    the     two       residential          and    commercial

5    models.      What I'm not clear on is                      the way in which

6    changes      in    the        residential           and   commercial        energy

7    demand aggregates, which of course are a sizable

8    proportion        of     the     total         aggregate,       react       on     the

9    price projections.

10                      You've got around very neatly in the way

11   the     problem         of      what       I     call      simultaneity            in

12   identification,               but      I       wasn't      clear        on         the

13   relationship between aggregate price formation and

14   the demand in the individual sectors.

15                      I also think there's a hidden assumption

16   in    the    model,       and       you     touched       on    this    in       your

17   presentation,            John,        that          changes      in     mandated

18   efficiency        standards          always         act   to    reduce      energy

19   demand.       That's kind of intuitively appealing, but

20   there       are    quite        a     lot       of    references         in        the

21   literature to why the impact of mandated efficiency

22   standards may be muted, and that is because if you

23   increase      the        efficiency            of    an    appliance          in    a

1    mandated way, what you do is make the output BTUs

2    cheaper for the user because he doesn't need to buy

3    as many input BTUs to get the same level of service.

4                    So you have reduced the price of output

5    BTUs.     That being the case, some of the efficiency

6    impacts on energy consumption can be muted and even

7    conceivably exceeded by the fact that people will

8    use the appliance more intensively or they may buy a

9    bigger appliance.

10                   So I think that indicates there's some

11   caution    to   be     used   in   assessing     the   impact   of

12   changes in efficiency standards.            It depends on how

13   your model operates.

14                   Now,    let   me   finish   by    making   a    few

15   comments about the commercial sector that are solely

16   related to it.         A lot of the comments I've made on

17   pricing    dynamics,     elasticities,      et   cetera,      carry

18   over equally to the commercial model.

19                   The first one that's really commercial

20   specific is cogen electricity.          That is included, at

21   least     for    commercial        establishments,       in     the

22   commercial aggregate data.           My suggestion would be

23   it would be preferable for you to exclude that and

1    put it in the power generation sector.

2                     Discount rates, I see those as treated

3    in a much more elaborate way than in the residential

4    sector.      You've         got     11    consumer     time    preference

5    premia    over    risk       free    rates.        The     question     that

6    brings to my mind is why that sort of or why several

7    premia    might       not    also        apply   in    the    residential

8    sector, and there is some literature on that.

9                     Floor space vintaging.                    As I read the

10   description,          your        pre-1989         floor      space      are

11   calculated       by   what     you       call    back-casting,        and    I

12   think maybe that is the kind of technique that could

13   be applied to the residential sector if it hasn't,

14   in fact, been done because what you've done is back

15   off from 1989, your earlier vintages, by using the

16   floor space data that you have for earlier years as

17   additions to floor space.

18                    Energy price projections.                   I saw in the

19   description where you're doing the full life cycle

20   analysis that you depend on what you call foresight

21   routines,    that       kind        of    myopic      or    reductive       or

22   perfect foresight.                What I didn't understand was

23   that you already have price projections from the

1    macro model, and there seems to be a distinction

2    between the price projections that you're using for

3    the life cycle analysis and the price projections

4    that may flow from the macro model.               I would have

5    thought you were going to make them consistent.

6                  A final comment is on DSM links.              I see

7    that the commercial sector model does make specific

8    reference    to   DSM   linkage.     No   such    treatment    is

9    advertised for the residential sector, although I

10   may have missed it in the description, but if, in

11   fact, it is not included, then I think it should be

12   because      particularly     in,     for        example,     the

13   electricity sector, the impact of DSM programs is

14   certainly noticeable.

15                 CHAIRMAN MOUNT:       Thank you, Campbell.

16                 So anybody from the Committee who wants

17   to add to Campbell's comments?        Dan.

18                 MR. RELLES:     These aren't exactly adding

19   to Campbell's comments.       They're taking a different

20   dimension.

21                 There's a lot of statisticians here, and

22   we'd be guilty of malpractice if we let you talk

23   about the year 2015 and we just sat here and didn't

1    raise the specter of uncertainty.                   I want to say a

2    little bit about that.

3                   I know, on the one hand, you do deal

4    with uncertainty by varying your base cases, and you

5    said that up front, oil prices, GDP, and so forth,

6    and in fact, the one time I tried to run NEMS on the

7    Web, I was also given some choices.                  Do I like these

8    data values?       Do I want to change them?

9                   So     I    appreciate       that,    but    there   are

10   other      sources        of     uncertainty       that    don't    get

11   reflected in these projections.                    Coefficients have

12   gotten estimated.              Surveys have gotten compiled and

13   models estimated based on those, and I guess I'd

14   like to see some discussion in these things about

15   uncertainty or even see NEMS provide the capability

16   of providing some kind of uncertainty measures.

17                  I     don't      think     it's   feasible    to    think

18   about reprogramming NEMS to do that.                      I appreciate

19   that it's awfully hard to communicate uncertainty in

20   a bar chart, but the kind of uncertainty I'd be

21   willing to live with would be if I could run NEMS;

22   if I could plug my assumptions in and rum NEMS five

23   or   ten     times,       having     it     each    time    vary    the

1    parameters a bit and letting me, you know, select my

2    output and just try to see how it varies over those

3    different ten iterations.

4                  That idea of varying things ten times

5    and looking at it has gotten well accepted into the

6    statistical     literature.          Concepts   like    multiple

7    imputation in the end basically say, "Go ahead and

8    re-impute this database five or ten times and see if

9    there are major changes."

10                 So it's a fairly well accepted notion,

11   and I guess I'd like to put a plug in for instead of

12   having it ask me do I want to change this data

13   value, put a plug in to have it ask do you want me

14   to change all of my parameters by amounts suggested

15   by random variation, and I would most certainly say

16   yes to that because I really have no idea of what

17   the uncertainty is when it comes out, when out comes

18   a projection.

19                 MS. COX:       Just to remark on his remark,

20   and that is in terms of what he was saying about or

21   what was said about modeling uncertainty, it is a

22   good point for some of the things that I do when I'm

23   just   guessing   on   the    size    of   parameters   or   what

1    effects might be, et cetera.          I'll go in sometimes

2    and say, "Well, okay.       I thought the cost ratio was

3    going to be this, but suppose it's ten percent more

4    or 25 percent more."

5                  If    you    don't    see     a    whole      lot    of

6    reaction, you feel pretty good, but if it's bouncing

7    all over the place, then you start wondering and not

8    feeling a lot of confidence in the results.

9                  CHAIRMAN MOUNT:       Well, I think it's very

10   important    that    you   both     raised       this     issue    of

11   uncertainty since this is a favorite topic of this

12   Committee, and I think it has got lost.

13                 (Laughter.)

14                 CHAIRMAN     MOUNT:         And     I     think     it's

15   important to bring it back again to the forefront.

16                 PARTICIPANT:     I'm a little surprised it

17   wasn't on the agenda.

18                 (Laughter.)

19                 CHAIRMAN     MOUNT:     But       there's    a    point

20   that I would like to raise about the use of end use

21   models.     In particular, the fact that you are using

22   a   relatively      high   discount       rate    in      order    to

23   approximate what is actually going on suggests that

1    people   are   not   making   energy   efficient   decisions

2    when they make appliance choices, and I wondered

3    whether you could say a little bit more about this

4    particularly for new construction.

5                   Is it because, for example, the people

6    who are making the decisions are not the people who

7    are actually going to use the buildings or are there

8    other reasons?

9                   I think that with a model like this, the

10   possibility exists unlike many econometric models to

11   actually address this type of issue and to say how

12   well are we making energy appliance and equipment

13   choices now, and in particular, it's surprising how

14   much penetration is being -- of electricity into

15   space heating and things like that, given the prices

16   that we pay for it in the Northeast particularly,

17   where heat pumps don't work very well.

18                  So ny other Committee members want to

19   comment?

20                  Anybody from the public want to make a

21   comment?   Would you like to respond?

22                  MR. CYMBALSKY:     I don't know where to

23   begin with all of those comments.          I'll begin with

1    the one I can answer.

2                       (Laughter.)

3                       MR.     CYMBALSKY:           The    discount       rate

4    question has been around forever.                     So why don't we

5    go for that one first?

6                       As     Campbell      mentioned,      he     said    the

7    commercial         model    segments     its    population      into   11

8    different discount rates.                 Six?        And his comment

9    was:     why doesn't the residential sector do the same

10   thing?

11                      And tying into what Tim said, why do we

12   have these high discount rates?                  Well, what we do in

13   the residential model is we have one segment of the

14   population.             That's it.       We don't segment it by

15   owners or leasers or builders.                    We have one, but

16   what   we     do    have    is   good    shipment      data    from    the

17   appliance manufacturer.              So we actually know what's

18   being purchased on the market.

19                      I'm going to agree with Tim and say,

20   well, if you have the new construction, they tend to

21   do things differently than someone who is going to

22   live     in    the       house   and     they     stock       their    own

23   appliances.         They purchase higher efficiency goods.

1    That's definitely true.

2                  I     think     the     problem     we    have     is

3    estimating     different       discount       rates     in     these

4    different classes.      So we used one discount rate per

5    appliance and said, well, the average of the whole

6    residential sector is, for instance, 69 percent for

7    refrigerators.

8                  Does that mean everyone has a discount

9    rate of 69 percent?         No, but when a builder builds a

10   house, he doesn't care what the efficiency level is.

11   So he throws in a bad one.                A consumer going out

12   may buy a better one, but on average, you get the 69

13   percent.    So that's what we do there.

14                 Uncertainty?           I'm     certain    that    I'm

15   uncertain    about   pretty        much    everything   you    said

16   there.     We did have a project on uncertainty, and I

17   think with budget considerations that actually did

18   not go through in our plans.

19                 You    know,    to    address    his    point    about

20   uncertainty, you can take the residential PC models

21   and perturb a lot of different things, not just this

22   data input set.        I think you're referring to the

23   spread sheet where you have different housing levels

1    maybe or different prices.

2                   You can change a whole lot of things.

3    It doesn't have a switch to just say, "Change them

4    all by ten percent."      You know, that capability may

5    be a little bit tough to do, and I'm not sure how

6    the model would respond to something like that.               It

7    may blow up; it may work.        I've just never done it,

8    so I don't know.

9                  Let's address the housing stock issue in

10   terms of the vintages.          There are data that are

11   available    through   RECs    that   segment   the   existing

12   housing stock into different vintage levels.                 When

13   we were developing the model, we decided to only use

14   the two vintages, basically what existed the year of

15   the last survey and whatever else is going to be

16   built   in   the   forecast    period.     So   we    have   two

17   vintages and we keep those separate over time.

18                 We can segment the '90 stock, you know,

19   by different vintages.        I don't know what that would

20   really buy us in terms of our projections.                   That

21   would be very data intensive.            You could see how

22   many pieces of data we already had, and then you

23   would just segment all of those numbers again by how

1    many     vintages    you   would   want   in   the   existing

2    housing.

3                  The things that would come to mind, you

4    could probably track age of equipment a little bit

5    better.     You can track how efficient the building

6    shell is for different vintages of housing a little

7    bit better.         Yeah, it's a fair concern.       I'm not

8    sure in terms of the amount of data needed in the

9    model.     It would just expand the dimensions by, you

10   know, probably four or five.

11                 The reversibility issue, I think this is

12   the last one I'll talk about.         Maybe Erin wants to

13   address.

14                 The reversibility of all the equipment

15   purchases, they are irreversible, and you know, once

16   you make a decision to improve your housing shell,

17   for instance, you don't make the decision to take it

18   back out.     So once there's a price response, say, to

19   increased insulation in your home, once you do that,

20   it's done forever no matter what else happens to

21   price after that time period.

22                 And I guess I'll end up with my comments

23   on talking about what we call the rebound effect,

1    and you mentioned, Campbell, that, well, if you do

2    these efficiency gains, your outputs go down, so you

3    should have some sort of rebound effect.                       That is

4    captured in the model now, in fact.                   So I think the

5    version of the documentation maybe didn't include

6    that,    but   we     do    have    the     rebound   effect   in   the

7    model.

8                    MS. BOEDECKER:              I'll be very brief, but

9    to continue what John was just talking about, the

10   commercial      model,       too,       did    just   incorporate    a

11   rebound effect for this year.                   So we do take that

12   into account to a certain extent.

13                   And    as    far       as   reversibility   goes,    as

14   long as a piece of equipment meets a standard, the

15   next time that person goes out to buy equipment,

16   they    can    go   back     to    a    less    efficient   piece   of

17   equipment.

18                   Also, as in the residential sector, if

19   they make shell improvements, those improvements are

20   there to stay, and they won't rip the house back

21   out.

22                   I'll just address one more thing since

23   John touched on most of the other things.                      On the

1    price projections, noticing that the forecast prices

2    used     in    the    life     cycle     cost       calculation       were

3    different      than    those    that     we   get    from     the     macro

4    model for our consumption calculations, the forecast

5    prices used in the life cycle cost are supposed to

6    represent the consumer trying to make a forecast

7    into the future, what they expect the prices will

8    do.

9                      The prices we get from the macro model

10   we    get     every    year.        So   if    we    are    running      an

11   integrated run of NEMS, those fuel prices that we

12   get from the macro model may change from one year to

13   the next, depending on how demand and supply does

14   change.        So     they   will    not      be,    quote,      unquote,

15   foresight prices until the year of the model run.

16                     CHAIRMAN MOUNT:          You've got one follow-

17   up here?

18                     MR. GRACE:         One simple comment, maybe

19   not simply; simple in theory, perhaps more difficult

20   to implement.          We've had a lot of success in the

21   uncertainty area in dealing with these deterministic

22   models to build -- I'll say simply build -- a shell

23   around      the   model      that   allows      either      in    a   more

1    sophisticated sense drawing in a Monte Carlo from

2    distributions or simple up ten, down ten, up five,

3    down five, but you don't end up having to screw

4    around with the model guts.              You're just building a

5    big shell around it that says:                   go to this array.

6    Draw from some values.            Maybe it's a distributional

7    array or maybe it's just some nominated array, but

8    the mechanics of doing it aren't as daunting as they

9    might seem if you're thinking, "Oh, gosh, now I've

10   got to make this whole general equilibrium model

11   stochastic."

12                  And    you       get     pretty     much       the   same

13   effects, at least in stability and some sort of idea

14   about   the    uncertainty        surrounding          it,    and   they

15   should propagate forward in time.

16                  CHAIRMAN MOUNT:          So we've had a proposal

17   to change the plan slightly and have a break now

18   before Jerry's presentation.               So let's have a 15-

19   minute caffeine shot and be ready for Jerry.

20                  (Whereupon, a short recess was taken.)

21                  So first I've got an announcement for

22   Committee     members     who    are     going     to    dinner     this

23   evening,    that     we   were    not    able     to    get    into   Le

1    Rivage,    and    we're      now      going      to   go     to    701

2    Pennsylvania Avenue.          This is not the same place.

3    It's 701 Pennsylvania Avenue.              We have the private

4    dining    room,   and   we    have    to    order     before      seven

5    o'clock to get the theater meal.                  So be there on

6    time, please.

7                  MS. COX:       To get what?

8                  MR. HAKES:       The cheap prices.

9                  MS. COX:       Oh.

10                 CHAIRMAN       MOUNT:        The   cheaper     prices,

11   less expensive prices, and there's a very important

12   announcement for your TV pleasure this evening, that

13   Jay Hakes is going to be live on CNN at ten o'clock

14   to tell us why gasoline prices are going up.

15                 MR. HAKES:       Any help would be welcome.

16                 (Laughter.)

17                 CHAIRMAN MOUNT:           He will be soliciting

18   comments at dinner.

19                 MR. LOCKHART:        Will it be the same story

20   as this morning or a different story?

21                 (Laughter.)

22                 CHAIRMAN        MOUNT:             So    the        first

23   presentation now is an update on confidentiality by

1    Jerry   Coffey    from   the     Office     of    Management        and

2    Budget.

3                 MR. COFFEY:       Thank you.

4                 As some of you know, I've been working

5    on   bits   and    pieces      of    this    for    most       of   my

6    professional career.        So sometimes I give quite a

7    long speech, but I'll avoid that today and give you

8    the quick version, which is the version that focuses

9    on the successes.

10                I'm    going   to      talk    about   three      things

11   today, two of which are now public, one of which

12   should be public some time in the next 48 hours, I

13   hope.

14                On Wednesday of last week, Alice Rivlin,

15   the Director of OMB, transmitted to Congress a bill

16   called the Statistical Confidentiality Act, which I

17   personally have been working on off and on for about

18   18 years.    This bill does a number of things, and

19   I'll be happy to go through some of them.

20                Really,     you    all   have       copies   of    this.

21   Rest assured that this is the result of many, many

22   person-months of haggling with our attorneys, and

23   there are lots of subtleties in the language of both

1    the bill and the administrative order which bears

2    some thinking about, and I'm sure as you look at

3    these things and read them closely, there may be

4    questions that will occur to you.

5                    What I would like to highlight are some

6    of the issues that are already being bobbled by some

7    of the pundits.         The bill itself has a statement of

8    findings      and    purposes,      which   hasn't      changed    that

9    much over most of the time I've worked on it.                       We

10   really   are    after       the   same   things,     and   in     fact,

11   recently I pulled out some very old documents and

12   made copies of them for Cathy Waldman, the Chief

13   Statistician, to remind her just how long some of

14   these concepts have been around.

15                   I had a page from the 1971 report of the

16   Commission on Federal Statistics, another page from

17   the   -- actually pages from two different reports

18   issued in, I think, '78 and '79, one by the Privacy

19   Protection Study Commission and the other by the

20   Paper Work Commission, where you could find language

21   that looked like we had copied it verbatim, and in

22   fact,    we    did     in    some    sections      of    this     bill,

23   particularly the piece that was written by the Paper

1    Work Commission, which was the last of those three.

2                  The     privacy       issue         dealt     with      both

3    statistics and research and had some complexities in

4    it that we don't have to worry about when we're

5    dealing strictly with statistical agencies.

6                  There are a series of definitions.                      Most

7    of them are fairly straightforward.                       A couple of

8    them I would note.         We do use an unusual definition

9    of "agency."        It includes most of the things that

10   most laws treat as agencies, but in addition, covers

11   some unusual agencies, like some of the groups in

12   the national laboratories are included in this, and

13   there's an explanation of why we did that in the

14   analysis of the bill.

15                 The    other    concept        over    which      we    have

16   haggled endlessly for several years now is the idea

17   of an agent.        What this really means, there are a

18   lot of words here.           There are other words in the

19   administrative      order.         There   are      explanations       in

20   both   places.      What     an    agent     is    in     the   simplest

21   terms, it's anybody who does anything helpful for a

22   statistical      agency      and     whose        behavior      can     be

23   controlled    at    least     to     the     extent       of    assuring

1    information security.

2                    The     reason       we        have    such        a    broad

3    definition is that statistical agencies have come up

4    with   ways    of     solving     this       problem    of    how       do       we

5    handle   contractors         or   how     do    we    get    people         with

6    specific      skills    in    that      may     help    us    work          on   a

7    particular project in so many different ways that we

8    needed a very broad definition in order to capture

9    them all.

10                   Why do we want to capture them all?                              We

11   are proposing in this bill to make agents with this

12   broad definition subject to the penalties of the

13   Trade Secrets Act.           For those of you who may not be

14   familiar with the Trade Secrets Act, it was actually

15   derived from a piece of tax law, an old BEA statute,

16   and one other which I'm not quite sure of many, many

17   years ago, and essentially it establishes criminal

18   penalties      for     employees        or     officers       of       federal

19   agencies who make unauthorized disclosures.                             It is

20   probably the one most general piece of the criminal

21   code dealing with disclosures and the penalties for

22   making inappropriate disclosures.

23                   There    are      some       other     changes         we    are

1    going to make in that statute which I'll get to in a

2    moment.

3                  But the concept of agent didn't really

4    authorize anything new.             In the case of the Census

5    Bureau, they have a section in Title 13 that allows

6    them to sort of swear in people as if they were

7    employees.        They use it to bring people in from

8    universities and lots of other folks and essentially

9    impose employee discipline on those people.

10                 There     are    other       statistical        agencies

11   that are dealt with in this bill who have many other

12   different     strategies.                There    are     licensing

13   strategies.       Certain kinds of contracts are written,

14   and the flavors of contracts are quite wide in their

15   variety.

16                 There     are    in    a    few    cases   situations

17   where a federal agency actually pays the salary of

18   someone operating out in the state and supervising

19   employees    of    a   state   agency.           This    is    a   NASS

20   agriculture invention which they've had a long time

21   to think that one up, but it works very well.                        I

22   don't know if anybody else could come up with a

23   scheme like that any time in this century, but is

1    has worked very well for NASS.

2                     The responsibilities of the statistical

3    data     setters,       which    are       the     agencies       that    are

4    defined in this act who have special authorities to

5    get data for exclusively statistical purposes from

6    almost anyone.          Their responsibilities are laid out

7    there.      They're pretty straightforward.

8                     The    agencies       themselves       are       named    in

9    Section 4 of the bill.                There's Bureau of Economic

10   Analysis,     Bureau      of    the    Census,       Bureau       of     Labor

11   Statistics,       the     National         Agricultural       Statistics

12   Service,     Department         of    Agriculture,          the    National

13   Center for Education Statistics, National Center for

14   Health Statistics, the Energy End Use and Integrated

15   Statistics       Division        of        the     Energy     Information

16   Administration, and a very late-comer, the Division

17   of     Science    Resources           of     the     National       Science

18   Foundation.                           This was one of the very

19   late changes that we made to the bill in the last

20   couple of weeks.          We've had a very interesting time

21   in the month of April.

22                    The agencies that are named here are, as

23   I    say,    authorized         to     acquire        information         for

1    exclusively statistical purposes from almost anyone

2    else    in    government.      There      are   a   few    exceptions

3    which    are    in   the     bill.        Particularly      national

4    security information is out of bounds.                    Information

5    which is controlled by a statute that itself sets

6    specific limits on how statistical information may

7    be used also have to be observed in any kind of

8    arrangement for sharing data.

9                    The main body, the main policy of the

10   bill     is     in    Section        6,     confidentiality         of

11   information, and this is where we have some of the

12   phrases that go back for decades.               The basic policy:

13   "data or information acquired by a statistical data

14   center for exclusively statistical purposes shall be

15   used only for statistical purposes.                  Such data or

16   information shall not be disclosed in identifiable

17   form    for    any   other   purpose      without    the    informed

18   consent of the respondent."

19                   There are some slight changes in wording

20   that came along very recently in there.                    There are

21   provisions      in   here    for   situations       that    arise   in

22   almost all of these agencies where information is

23   collected for both statistical and other purposes.

1    In those cases what we want the agencies to do, the

2    policy that we're establishing is that distinctions

3    of that type have to be made on the record by rule

4    before the data is collected.             You can't collect the

5    data for exclusively statistical purposes and tell

6    all of the respondents that's what you're doing and

7    then change your mind later.             You've got to do it on

8    the record before the data is collected.

9                    This     also      contains         some     of     the

10   exceptions,      kinds   of     information         that   cannot   be

11   disclosed.      It also has a fairly elaborate procedure

12   for data sharing agreements, and this has a long

13   history, and every word has been fought over at one

14   time or another.         I encourage you to read it.                 I

15   doubt if I could explain it in less than an hour.

16                   One of the pieces of sub-text that you

17   should understand and which you don't always see

18   explicitly in the language of this bill, there are a

19   number of areas where this bill has been written to

20   dovetail with provisions of the Paper Work Reduction

21   Act.    In some cases, we actually restate policies of

22   the    Paper    Work   Reduction       Act,   one    of    them   being

23   Section    6,     Subsection       F    of    Section       6,    which

1    guarantees that any restrictions on the use of data

2    in law travel with the data to any other agency.

3                       An interesting sidelight here is when we

4    originally picked up the language from the Paper

5    Work Reduction Act, I discovered that there was a

6    glitch in it.            It didn't really work.                         So we fixed

7    our    version,          and     in        the        last        stages      of    the

8    reauthorization or the 1995 amendments to the Paper

9    Work Reduction Act, the House and the Senate decided

10   we    were    right,       and      they     changed              the    Paper     Work

11   Reduction Act to match this bill, though they didn't

12   even know this bill existed.

13                      There       is      a    section             on      coordination

14   oversight.          Because         a      lot        of     this       approach     is

15   procedural,         we're        setting          up         ways       of    sharing

16   information, ground rules for sharing information,

17   permitting agencies to find the best answers for how

18   they     manage         information              in        this      kind     of     an

19   environment.         A lot of this we're going to have to

20   invent as we go along.

21                      One    of     the       things          we     learned     over    a

22   decade       and    a      half        is    that            we      cannot        write

23   prescriptions that solve all of the problems and

1    remain consistent with all of the statutes that are

2    on the books already.      We tried that in 1983, and we

3    had a bill about this thick, and nobody could read

4    it; nobody could understand it; and certainly nobody

5    supported it.

6                  So   there   is    a     process      in    here    for

7    coordination of oversight.           The main engine of this

8    will be the Director of OMB.            There are a number of

9    tasks there, including the task of reviewing and

10   approving any rules adopted by any of the agencies

11   that are affected by this bill.

12                 Any agency that donates information for

13   exclusively statistical purpose to one of the named

14   statistical     data   center,         and     of   course,       the

15   statistical data centers themselves, may, in fact,

16   be writing policies as regulations for how they are

17   going to manage this.         OMB has the task of looking

18   at   these   and   assuring     that    they    are      done    in   a

19   consistent fashion.

20                 What this gives us is the opportunity to

21   look for the kinds of problems that have gotten in

22   the way for a long time when an agency that has a

23   solution that works reasonably well for them, but it

1    prevents you from doing something that's very useful

2    somewhere       else,    and    we     felt    this      was     absolutely

3    necessary.

4                        Another important principle is generally

5    rules    discovering       disclosures         of       information         that

6    are authorized by this act are promulgated by the

7    agency       that    originally       collected         the    information.

8    The    presumption       here    is    the    agency          that    had   the

9    mandate to get the information in the first place

10   probably best understands what the problems are with

11   the data, what the sensitivities of the respondents

12   may be, what problems they would have if somebody

13   made     a     mistake     and        disclosed          something          that

14   shouldn't       be    disclosed.         So       they    are        the    ones

15   responsible.          They have the primary responsibility

16   for drafting these regulations.

17                       Each agency writes rules for the data

18   that     it    collects.         This       was     a    very        important

19   principle for winning over the Treasury Department,

20   who had always looked at this as this is a way for

21   OMB    to     rewrite    all    of    the     Treasury         Department's

22   rules, but that's not what we intended ever.

23                       A good bit of the text of the bill is

1    then    in    the       series    of    conforming           amendments     in

2    Section 9.          There are a couple of real short ones

3    for the Department of Commerce covering the Census

4    Bureau and BEA, one very long one for the Department

5    of Energy, beautifully drafted.                      I was told before I

6    ever got started in this that there were some people

7    in the General Counsel's Office of Department of

8    Energy       who    were    probably          the     government's         best

9    drafts-persons for legislation, and I was certainly

10   impressed with the job that they did.                            We only made

11   really one change in what they sent us, except for

12   adjusting the indentations and things of that sort,

13   and that was another one of these fire fights that

14   occurred      actually          after   the     bill        had    been    sent

15   forward for Alice to sign off on.                                We made one

16   slight    change         affecting      the     Department         of   Energy

17   piece.

18                      We     then     have        some     new        conforming

19   amendments.             These    weren't       in    there    a    couple   of

20   years ago, weren't in the version that we circulated

21   last    year,      one    for    the    Department          of    Health    and

22   Human    Services          and    a     very        short    one     for    the

23   Department of Labor.

1                    Any    of     you     who        have     seen     earlier

2    versions of this, the conforming amendment for the

3    Department of Labor has gone up and down and up and

4    down    several    times.        We    had       a   three       paragraph

5    version that we wrote with some members of Janet

6    Norwood's staff years ago.                 Shortly before we went

7    out for review on the previous iteration of this,

8    which was about a year and a half ago, Labor said,

9    "We want to change it," and they took the three

10   paragraphs out to about three pages.

11                   They   came     in    again       shortly     before    we

12   were going to circulate it this time and they wanted

13   to restore some of the stuff we had taken out last

14   time.     This    went      round     and    round.          Finally    we

15   reminded Labor subtly that, in fact, no conforming

16   amendment was needed for the Department of Labor and

17   that if necessary we could go forward without one,

18   and    after    some   discussions          of     some    very    subtle

19   changes   in    the    main    language       of     the   bill,     which

20   solved some problems their solicitor was concerned

21   with,   we     ended   up     with    an    amendment        that's    one

22   sentence long.

23                   The other new feature here, and this was

1    another       late     riser,    was     the     amendment        for     the

2    National Science Foundation.                   A year ago, when we

3    talked    to    NSF,     they    really        weren't      prepared      to

4    become part of this policy effort.                         However, they

5    went back and started thinking about it.                           We told

6    them, well, maybe the first round of amendments a

7    couple of years from now we can do something.

8                     They    went    through       the    process.           They

9    spent a lot of time with their General Counsel.                           As

10   a result, when we went out for comment on the bill

11   about     a    month     ago,    their        comment      came    back    a

12   completely coordinated, conforming amendment to the

13   section of Title 42 that deals with the National

14   Science       Foundation,       very    well     written,         well    put

15   together,      completely       coordinated         with    the    General

16   Counsel,      and    a   request       that    we    add    the    Science

17   Resources Division to the list of statistical data

18   centers, and they had done such a beautiful job that

19   we said, "Fine.          That looks great to us."

20                    There is one other important conforming

21   amendment that's in Section F disclosure penalties

22   on page 14 of the handout.                    Section 1905 of Title

23   18, this is the Trade Secrets Act.                         What we have

1    done there, and this looks a little different from -

2    -   oh,   my    goodness,       this   is    not   even     the    right

3    version.       Oh, no, that's all right.             Okay.        I have

4    to be careful with this one because we changed the

5    language on the recommendation to the Department of

6    Justice    in    the     last    three      days   before    we     went

7    forward.       Ah, yes, okay.      This is the correct one.

8                     Initially what this law said, it imposes

9    penalties       on     officers        or     employees      of      the

10   government, and there's also a special category in

11   there which are agents of the government, which I

12   think it was put in there by a unit of the Justice

13   Department for certain kinds of agents that they

14   have that they wanted added to this.

15                    And what we are doing is simply adding

16   this   broad     agent    concept      that    we've   defined       for

17   these statistical data centers as another form of

18   agent who can be punished as if they were officers

19   or employees, and then the other thought we had was,

20   well, this is really old law.                It says you can only

21   be fined $1,000 for something like this, which isn't

22   very much these days.             So we sort of poked around

23   and originally proposed, well, we ought to increase

1    it to 10,000.

2                      When     Justice        came   back,      they      said,

3    "Well, why don't you just make it conform to the

4    current sentencing standard for what this is, which

5    is a Type A misdemeanor?"

6                      I said, "Well, okay.                What do you want

7    to do?"

8                      They     said,    "Well,       you      look   in    this

9    section   and      look     in     this    other      section,     and     by

10   simply tying the fine to the title in which this is

11   placed,     you     have     the     effect      of    tying     it    into

12   whatever gets done with the sentencing standard."

13                     I said, "Well, what is the sentencing

14   standard?"

15                     Well,     it's     $100,000,         which     probably

16   makes a lot of sense considering what we're actually

17   talking about here, but it kind of made a lot of our

18   agonizing    debates        over     whether       it's    going      to   be

19   10,000 or 15,000 look kind of silly in hindsight,

20   and this was, in fact, the issue we came back to EIA

21   with.

22                     I called Larry Klerr after the bill had

23   been sent forward through coordination in OMB.                             It

1    was halfway to the Director's office, and I got a

2    call from LRD and said, "Hey, there are two of these

3    conforming amendments which still have this $10,000

4    in there.    Do you want to keep them or not?"

5                  And I said, "Well, I don't know."                    In

6    the case of the National Science Foundation, they

7    had    different     reasons    for    establishing     a   $10,000

8    fine.    In the case of the EIA amendment, they had

9    basically    just     lifted    the    language      that   we   were

10   using at the time that they wrote the amendment, and

11   I   called   Larry    and   said,      "Hey,   go    talk   to   your

12   General Counsel and see if you want to take this

13   ride with us up to 100,000 on the fines."

14                 And 20 minutes later Larry had it all

15   coordinated and came back and said yes, and we sat

16   there on the phone and I got the LRD guide and wrote

17   in the new language.          I then made replacement pages,

18   went    up   and     caught     the     package      over   in    the

19   Director's suite, and put the new language.                    It was

20   that kind of week.

21                 Finally,         there    was    one     other     very

22   important    contribution        that     of   all     people     the

23   Department of Defense made.              In Section 10, effect

1    on other laws, we have always had a section in here

2    which acknowledged the relationship of this law to

3    the Paper Work Reduction Act, particularly Section

4    3510, which is the basic piece of law in the federal

5    government       that       controls    exchanges           of    information

6    between agencies.                 It sets the general rule, and

7    this reinforces the fact that this still applies,

8    though the way this new law is written, it sets some

9    new boundaries.            It's drafted so as to work with the

10   language of the PRA.

11                    The       suggestion       that       we     got   from      the

12   Department       of    Defense       was     that      it     may   still     be

13   useful.     It's sort of "belt and suspenders" type of

14   stuff, but it may be useful to reiterate the fact

15   that      what        we      have     written           as       policy      on

16   confidentiality             in     Section        6    is        intended      to

17   constitute a (b)(3) exemption under the Freedom of

18   Information Act.

19                    We        went    around     a       little      bit   as    to

20   exactly how to word it, but everybody agreed.                                Even

21   Justice agreed that this was okay to do.                                What's

22   happened and the reason this is put in there is that

23   there are a number of courts when they look at FOIA

1    cases who believe because the way FOIA is written

2    they do not have to look at the legislative history

3    of an act in making a determination as to whether

4    the (b)(3) exemption applies, which is why you have

5    sometimes very elegant language which clearly states

6    restrictions that would qualify a law for the (b)(3)

7    exemption,   and    then   somewhere     down    there    there's

8    another little piece of verbiage that says, "This is

9    a (b)(3) exemption in case you didn't notice."                  So

10   that's basically what was added here.

11                   The analysis probably does a better job

12   than I've done in the last few minutes of explaining

13   what all this stuff is about.          There is a companion

14   piece that has not yet gotten out of the agencies.

15   One of the things you will notice if you are a

16   follower of the various iterations of this bill over

17   the years is there is no amendment to the tax code

18   in the main bill.

19                   What happened here -- well, let me back

20   up a little bit.        Over the years, the Census Bureau

21   and   Internal     Revenue   Service      have    taken    turns

22   blocking   us    from   getting   this    thing    out    of   the

23   administration.      During the Bush administration, we

1    came up with a version of the bill that essentially

2    took all of the chips away from the Census Bureau.

3    It didn't get out of the administration, but the

4    Census Bureau has been very cooperative in helping

5    us do a reasonable version of this bill ever since.

6                    On    the       recommendation          of     a    lot    of

7    people, we were encouraged to make the bill more

8    ambitious than the one in the Bush administration,

9    and as a result, we tried to come up with a new

10   version of the amendment to the tax code in the bill

11   that   we   circulated          a    year     ago.      Treasury        still

12   didn't   like    it,      but       shortly    after    that       bill   was

13   circulated, there was a high level meeting involving

14   the    Commissioner         of        Internal        Revenue,          Deputy

15   Secretary of Treasury, and Sally Katzen, my boss'

16   boss' boss, where we came to an agreement on some

17   principles for what might constitute an agreement on

18   an amendment to the tax code.

19                   What we were offering them was basically

20   some   changes       in   language          that     reduced       at   least

21   theoretically the amount of information that would

22   be disclosed for statistical purposes, but disclosed

23   kinds of information that were much more useful than

1    under the current language of the tax code.

2                   After          seven     or     eight      months    of

3    negotiation back and forth, IRS came up with a form

4    of this that we could all live with, and this is now

5    -- this was also circulated the same week as our

6    bill   and    has,       to     my     understanding,      now     been

7    completely revised to reflect all comments from all

8    agencies     and    is   back     at    the   Treasury     Department

9    awaiting signature by their General Counsel before

10   it goes to Congress, but I can't really show you

11   copies of that until it becomes official.

12                  If    anybody         wants    to   talk   about,   you

13   know, what the changes are, I'll be happy to talk to

14   you after, but I do want to mention one more piece

15   of this strategy which started later, but finished

16   earlier than either of the others, and that was our

17   administrative order which really deals with a lot

18   of the same concepts that are in the bill.

19                  One of the things that we decided to do

20   when we were having difficulties many years ago with

21   getting agencies to agree on a strategy for changing

22   the law was we decided to look at how much we could

23   do without changing the law, and EIA was, in fact,

1    an important player in determining how far we could

2    go.

3                  There were some events that some of you

4    in this room will recall in which there were some

5    disclosures that were being requested.              There was a

6    lot   of   pushing   and   shoving    going   on    within    the

7    executive branch that was causing us all kinds of

8    problems, and they really put a fine point on the

9    extent to which in some cases Congress and the law

10   is not the problem; it's the agencies and the way

11   they behave to each other that is the problem, and

12   that's something we ought to be able to get a handle

13   on.

14                 As a result of the case that was made

15   all the way up to the White House by EIA, some of

16   the President's key advisors suggested that maybe we

17   should have an executive order that tells all of the

18   executive agencies to behave with respect to this

19   particular problem in the future.             We couldn't do

20   anything about that immediately.            Well, this was in

21   the   Bush   administration,    and    we    only   had   a   few

22   months after that before the Bush administration was

23   no more.

1                     But the idea was planted, and we started

2    drafting little things and looking at things.                    What

3    could we do that would work with the strategy that

4    we were pursuing with the bill?

5                     On January 29th of this year, we put out

6    for comment an order, not an executive order, but an

7    order      providing        for    the     confidentiality        of

8    statistical information.            Some of you may be aware

9    that last year we circulated a proposed executive

10   order.     After a lot of discussion with our General

11   Counsel, we determined that we could actually do

12   more under our existing authority, which goes back

13   to the Budget and Accounting Procedures Act of 1950

14   and has been since buttressed by an executive order,

15   a     congressional        requirement       to    delegate       the

16   authority        granted    to     the   President       which    is

17   reflected in an amendment to that executive order.

18                    What it all boils down to is we have a

19   strong     case      that     orders       adopted      under    the

20   authorities that exist have the force of law.                     If

21   any   of   you    doubt    this,   there    is    one   spectacular

22   case, which is Statistical Policy Directive No. 3.

23   Most of the statistical policy directives sound like

1    advice and are taken as advice.                    This one is not.

2    This is the directive that controls the release of

3    principal economic indicators.                   It has been treated

4    as law by six Presidents.              It is one of these really

5    strange situations where lowly working stiffs like

6    me   write     something,       go    out    and   talk    to   agencies

7    about    it,    come      up   with    a    policy,      and    even   the

8    President feels bound by it.

9                     Even     though      it    is   based    on    authority

10   assigned to the President, because of the way it's

11   operated over the years and also because of the good

12   sense    of     a   lot        of    presidential         advisors     who

13   understood why things need to be done this way, we

14   have a perfect record of compliance all the way up

15   to the President, and as our General Counsel pointed

16   out, you don't get that with a lot of laws.

17                    So the point he made, one of the other

18   points    that      was    made      is     that   executive      orders

19   frequently change with administrations, which is not

20   the sort of stability that we were seeking.                            We

21   really want, after all these years of living with

22   informal versions of this policy, we really want to

23   make something permanent happen, and that's what the

1    order is all about.

2                     Tactically also, the order gave us an

3    opportunity to put some of these principles out on

4    display    for     the   public,    out    where    Congress   and

5    congressional staff would see them, would have a

6    chance to think about them, to talk about them, to

7    debate them before we go to Congress with a very

8    similar strategy that requires them to take action

9    and to pass legislation, and this has generally been

10   very effective.

11                    A number of statistical agency heads and

12   people who have a great deal of concern with the way

13   the government does its statistical work testified

14   as   a   hearing    in   March,    along   with    Sally   Katzen.

15   Cathy Waldman was there, but she was basically a

16   resource for Sally, and that was one of the things

17   that clearly had made an impression on Congress.

18                    They had looked at what we were trying

19   to do in the confidentiality order.               There was broad

20   agreement with the principles that we were trying to

21   pursue there.

22                    Some important differences between what

23   we do in the bill and what we do in the order.                  I

1    mentioned before that the bill is a (b)(3) statute.

2    the reason that the order has a lot more verbiage

3    in it about how you get things done and a lot of

4    required reviews on the part of the agency as to

5    what   statutes    require       you    to   do    and      what    policy

6    options are open to you is because the order does

7    not assume that you have a (b)(3) FOIA exemption.

8    What it is doing is, among other things, making a

9    significant change in the way FOIA policy operates

10   in the case of some designated agencies.

11                  If any of you are followers of the way

12   Freedom of Information Act law has developed over

13   decades now, one of the principles had been that

14   determinations       as    to    what    may      be   disclosed      are

15   almost    always      deferred          until      a     request      for

16   disclosure is made.             If you think about it for a

17   minute, you can see this really makes a hash of a

18   confidentiality pledge.           How can you go out and tell

19   a respondent that this is not going to be disclosed

20   because   it    is    very       important.            We    know    it's

21   important to you and we want you to feel confident

22   the    government         is    not     going     to     splash       this

23   information all over the place.                 It's going to treat

1    you      with        respect         and     respect           both        your

2    confidentiality privilege and your privacy rights,

3    and yet at the same time, try to observe a policy

4    that says we're not going to decide until somebody

5    asks us for it.

6                        So part of what we have crafted in the

7    order    is     a    required      change    on    the       part   of     some

8    designated agencies in the way they deal with FOIA

9    policy.       We require these agencies to make these

10   determinations in advance, which flies in the face

11   of most FOIA regulations, flies in the face of a

12   couple of executive orders if you get right down to

13   it, because FOIA regulations and executive orders

14   have    all     predominantly         dealt       with       the    case    of

15   administrative information.                 Neither the Privacy Act

16   nor FOIA have ever really dealt adequately with the

17   problems      of     statistical      agencies         and    particularly

18   the     concept          of   statistical        confidentiality,           and

19   we're trying to carve out some area where we can

20   make sense of this and make it work.

21                       So    this     went    out    in     January.           The

22   comment period ended the end of March.                         I have some

23   extra copies here.               If any of you want to see it and

1    you don't get a copy, I can give you the Federal

2    Register citation.

3                   The comment period is over, but since

4    I've been busy writing the last minute changes to

5    the bill, we're going to be working on the comments

6    for    a   while    yet,   and     if   any    of   you    get    some

7    inspirations, my E-mail address is in the notice.

8    It's    probably     easier   if    I   tell    you   what       it   is

9    because the particular font I use here, the lower

10   case Ls and the ones are identical.                       The E-mail

11   address if you have any comments on any of this, and

12   I'd be happy to see them, is Coffeyjay, C-o-f-f-e-y,

13   underscored Jay, at sign, A1.dop.gov.

14                  As I say, the formal comment process is

15   over.      We are still, however, talking with people

16   who submitted formal comments, and if any of you

17   have real inspirations, I'd be happy to look at them

18   because there are many, many issues that I'm going

19   to be writing up papers on that came in in the

20   course of the comment period, and any insight you

21   can provide me as a personal favor I would greatly

22   appreciate.        We can't treat them as formal comments,

23   but I'd be glad to have them.

1                    That's about it.        How well did I do?

2    Probably behind time.           How much time do you have

3    left for questions?

4                    CHAIRMAN MOUNT:        Does anybody want to?

5    Yes, Cal.

6                    MR. KENT:       Is the idea that the order

7    and the law go together or is the order seen as a

8    separate act that will not require the law to be

9    affected?

10                   MR.   COFFEY:      Both.     We   designed    the

11   order so that we could get substantial benefit from

12   it whether or not Congress passes the bill.

13                   MR.   KENT:       Whether    or   not   the   law

14   passes.      Okay.

15                   MR. COFFEY:       We also designed it to be

16   consistent and to work effectively with the bill if

17   Congress chooses to pass it in the way it's been

18   proposed.      Some of the things you see in the bill

19   you   will    eventually    see   in   the   guidance   for   the

20   order.    I don't have as big a writing job as it may

21   appear because I'm just going to lift whole chunks

22   of definitions and other things from one straight

23   across to the other.

1                  If you do get a copy of the order, by

2    the way, there's one glitch.            There's one thing we

3    missed in all of our interminable debates with our

4    General Counsel.      Somewhere in here there's a phrase

5    that says about agents something about "supervision

6    and control."       It should have been "supervision or

7    control," which makes a big difference.

8                  MR. KENT:        And can I just ask one more

9    question as a follow-up?         Why is this not applied to

10   all of EIA?

11                 MR. COFFEY:        Good question.      It was a

12   tactical decision made some time ago.               The first

13   question was could we apply it to any part of EIA.

14                 The choices that we made in this bill

15   were often influenced by what was perceived to be on

16   the edge of controversy or over the edge.              In the

17   case   of    EIA,   as   you     well    know,   changing    the

18   disclosure rules that apply generally to EIA has

19   been a meat grinder since the 1970s.

20                 It appeared to us, at least, that even

21   among the people who were dead opposed to changing

22   the    way   information       about    energy   producers    is

23   handled, it's to get the big boys, you know, the

1    anti-oil company mentality, which everybody is aware

2    of, but that has clearly -- in some of the actions

3    of Congress that has not applied to small fry, to

4    households, to small businesses when you're talking

5    about retail gasoline franchises.             Congress has from

6    time to time written in special protections for the

7    interest of these not so big boys.

8                    We basically seized on that and tried to

9    look at the largest chunk we could define that would

10   avoid    that   other       controversy     which    had   been   so

11   intractable.

12                   The other issue was, and what we have

13   looked   for    in    the     designation    of     each   of   these

14   agencies, we are looking for units who, in fact, can

15   do   something       useful    with   data   sharing,      and    the

16   Energy End Use Consumption division clearly in their

17   work with several other agencies has laid the ground

18   work for doing some very effective data sharing.

19   They've had to be very imaginative in many cases in

20   how they did things, but clearly there was a very

21   real potential there which we could easily explain

22   to Congress if anybody asked us, and that was the

23   other practical consideration.

1                    MR. KENT:           Right, but this particular

2    bill then would not deal with the issue that we had

3    in the famous White House meeting?

4                    MR. COFFEY:         No, there are other ways to

5    deal with that, particularly once we get everyone's

6    attention with this order.                The way disputes over

7    data    sharing    are    supposed       to   be    managed      in    the

8    government, most of the time agencies talk to each

9    other    and    decide        either     you're     going      to     give

10   somebody    some    data       or    you're    not,      and    agencies

11   actually have quite a lot of latitude in how they

12   make these choices.

13                   The law that applies in these cases is

14   Section 3510 of the Paper Work Reduction Act, which

15   authorizes agencies to make disclosures that are not

16   inconsistent       with       existing    law.        The      way    that

17   language   is     written,      each     of   the   people      in    this

18   discussion      makes     a    determination        as    to    what   is

19   inconsistent with law.              If they can't agree, there's

20   no agreement.

21                   Congress then provided for another step

22   to   resolve      such    differences,        which      is    that    the

23   Director of OMB may order exchanges of information

1    if he or she determines that it is no inconsistent

2    with the law.          Once again, this is an independent

3    determination.         This is the way we've interpreted it

4    anyway, along with our General Counsel.                 If OMB can

5    sit down, they don't have to listen to what anybody

6    else has said in their regulations or what their

7    policies are.           They look at the law and make a

8    determination         as   to     whether    or   not     this     is

9    inconsistent.

10                   Now, one of the dilemmas we've had in

11   this    is    that    without     either    the   confidentiality

12   order    or     the     confidentiality       law,    there's     no

13   distinction     in     many     instances   between     statistical

14   uses and non-statistical uses.              So if you read 3510,

15   it seems to say, well, OMB should be deciding that

16   statistical          agencies     should     be    central       data

17   collection agencies for the Federal Trade Commission

18   or, you know, anybody else who has an interest in

19   similar information.

20                   One of the things we do in both                   the

21   order and the statute that we're proposing is we

22   finally build into law the concept of functional

23   separation that's been pushed for 25 years now so

1    that when OMB looks at these determinations under

2    Section     3510,      we       can     legally          and     rationally

3    determine    that     we    may       have   a    central        collection

4    agency    for    statistical          uses    and    another          central

5    collection agency for administrative uses of very

6    similar   data,       and   it     would      not    be        inconsistent

7    because here we would have provided for the basis

8    for   making     such       a    distinction,            the     functional

9    separation policy.

10                   MR. KENT:         So the order would take care

11   --

12                   MR. COFFEY:            You can do it under the

13   order.    You can do it even more explicitly under the

14   bill for any agencies covered in the bill.

15                   MR.     SKARPNESS:                I've     got        a    sort

16   question, a point of information.                    So you're saying

17   there's even parts of EIA that aren't going to be

18   covered by this?

19                   MR. COFFEY:            Right now all of EIA has

20   very little legal back-up for its confidentiality

21   policies.       Yeah, I tried very hard with some very

22   ingenious regulations some --

23                   MR.    SKARPNESS:            So    across       the       street

1    here is DOT.

2                   MR. COFFEY:   Okay.

3                   MR. SKARPNESS:     You know, were they part

4    of or did they decline getting involved?

5                   MR. COFFEY:      DOT also got into the game

6    late, in part because DOT has doubled in size and

7    substantially changed its functions in the last six

8    or eight months.

9                   MR. SKARPNESS:     Oh, yeah.

10                  MR. COFFEY:      We have been in constant

11   communication with the people in the BTS, Bureau of

12   Transportation Statistics.        If they had been farther

13   along --

14                  MR. SKARPNESS:     They might have.

15                  MR. COFFEY:      -- this would have been an

16   opportunity to do this.         At best now we hope things

17   will settle out, and maybe the first time we get a

18   chance to go back and amend this and add another

19   statistical     data   center     and   show   Congress   how

20   wonderful this whole strategy is working, BTS is

21   high on the list of the next set of agencies to be

22   added.

23                  MR. SKARPNESS:     One last thing.

1                 MR. COFFEY:    Yes.

2                 MR. SKARPNESS:    There's been talk about

3    a statistical clearinghouse concept, you know, sort

4    of a central location where, you know, this data is

5    cleared.    Does that fit into this in any way?            I

6    know that each agency --

7                 MR. COFFEY:    Well, are you talking about

8    a consolidation of agencies?

9                 MR. SKARPNESS:        Well, no, of just data

10   more or less.

11                MR. COFFEY:    I'm not familiar with that

12   strategy.

13                MR. SKARPNESS:    Okay.

14                MR. COFFEY:     I am familiar with a bill

15   that's been discussed on the Hill.

16                MR.   HAKES:     You're    talking   about    a

17   central place where you can go for data?

18                MR. SKARPNESS:    Yeah.

19                MR. COFFEY:    Oh, oh, that's a different

20   story.

21                MR. HAKES:     We can create that create

22   that electronically.

23                MR. SKARPNESS:    Right.

1                   CHAIRMAN MOUNT:         A virtual one.

2                   MR.     SKARPNESS:           Yes,     where      it   fits

3    these--

4                   MR. COFFEY:        That's happening.

5                   MR. SKARPNESS:         Okay.

6                   MR.     COFFEY:         Yeah,       that's    happening

7    right now.

8                   MR.       SKARPNESS:           I     mean        is   this

9    facilitated or you know?

10                  MR.    COFFEY:         It    should    have      happened

11   already, but you know, there's been a lot of back-

12   and-forth     in   the    White    House     about       when    they're

13   going to roll it out and who's going to be there.

14                  MR.    HAKES:       It's      kind    of     encouraging

15   because it's going to be a fairly prominent part of

16   the White House Home Page.             So a person coming into

17   the    federal       system    will        see     the      statistical

18   resources early in the process without getting much

19   into    the    system,        which        should     increase       the

20   visibility of federal statistics.

21                  MR. COFFEY:         Right.         Our staff and the

22   statistical agencies have all been working on this

23   one for a while.         As I say, we sort of expected that

1    it was going to happen before now, but for a number

2    of reasons it hasn't quite been scheduled yet, but

3    it's about ready.    It's going to happen soon.

4                Any other questions?

5                MS. COX:       I as invisible.

6                (Laughter.)

7                MS. COX:       I think this might come -- as

8    I understand it, what you've handed out here only

9    affects the named agencies.

10               MR.     COFFEY:         The    act   itself    names

11   statistical data centers, yes.

12               MS. COX:       Right.     Now, for the order, is

13   that -- I haven't seen the order.              Can that impact

14   on -- yes, I would like a copy of it.

15               MR. KENT:         Have you got another copy?

16   I'd like one.

17               MR. COFFEY:        I have a few more.          If I

18   don't have enough I can also give you the --

19               MS.     COX:       Such       as   the   Bureau   of

20   Transportation    Statistics    or     maybe     another   group

21   that's concerned about the confidentiality for their

22   survey participants.

23               MR. COFFEY:       Right.

1                  MS. COX:       I did work on a survey once

2    where survey data that had been -- they had said

3    they were going to preserve their confidentiality,

4    but they had no legal right to do so, and it was

5    subpoenaed under -- I can't remember.               I think this

6    was under EPA.

7                  MR. COFFEY:     Which agency?

8                  MS. COX:      They had a subpoena and had to

9    release data.

10                 MR. COFFEY:     This was EPA?

11                 MS. COX:      I think it was EPA.

12                 MR.   COFFEY:        Yeah,   I'm     familiar        with

13   that situation.

14                 MS.    COX:      And    it     was    a     very     sad

15   situation.

16                 MR. COFFEY:     Yeah.

17                 MS.    COX:      But    they    had       no   way    of

18   preventing it.

19                 MR. COFFEY:          We went through this in

20   great    detail     with    both     EPA     and    the      Justice

21   Department when there were proposals to create a

22   Bureau   of   Environmental     Statistics.          One     of    the

23   issues, and it is also an issue at BTS, is whether

1    this    agency    has    a   mandate        to     collect    data      for

2    statistical purposes, and we asked both EPA and the

3    Justice      Department      to    consider        whether       this    is

4    something that should be added because all of EPA's

5    current data collection authorities all derive from

6    regulatory statutes.

7                     The issue we put to EPA and Justice was:

8    does    it    make     sense?         And    we     cited    some       very

9    important      examples      where,         in    fact,     there       were

10   pitched battles within EPA because they had to, in

11   fact,     guarantee      very     strict         confidentiality        and

12   guarantee that certain things were going to be used

13   only for statistical purposes in order to get some

14   things done.

15                    There    were    a   couple       of   surveys     where

16   clearly they would not have happened, would not have

17   had good results unless they had done that.                         Every

18   one of them was a bloody battle with the General

19   Counsel at EPA because the general principle that

20   they    wanted    to     observe      was    anything       we    get    is

21   available for enforcement purposes, and the point we

22   made was that if you say that, you're not going to

23   get anything from these kinds of surveys.

1                    So    we   won       the    little    battles.          What

2    happened ultimately though when we talked to Justice

3    about this was they raised a number of important

4    questions.      Since Justice has a fair chunk of their

5    resources    invested           in    prosecuting         environmental

6    violations, they've got a division over there that

7    spends all of their time doing this.

8                    The question that arises in that kind of

9    an   environment        is:          how     can     we     assure     that

10   information that needs to be used to prosecute an

11   offense is not tainted by the terms under which it

12   was collected?        And it's purely a pragmatic kind of

13   problem.     It's can someone who doesn't like what

14   we're   doing    come      in    and       say,    "Well,      you    didn't

15   collect this correctly because I thought it should

16   have been used for only statistical purposes," and

17   even though the agency may have said otherwise, it's

18   a real hassle.        It is something that attorneys have

19   nightmares over, and basically we just didn't want

20   to      fight    with      Justice         any     further      on    that,

21   particularly since the bill wasn't going anywhere.

22                   Transportation             has    some    of    the     same

23   problems.            They've         inherited       two       regulatory

1    mandates, along with staff.                If you look at what

2    they're     doing,     a     lot    of     the    reason     for     the

3    regulatory collection has disappeared.                  They haven't

4    done nearly the kind of job that EIA did in the

5    early '80s to sort out what we need for statistical

6    purposes     from     the      legacy      of     regulatory        data

7    collections.         There's       still   a     lot   of   people   in

8    transportation who still think the same way about

9    what their information requirements are.

10                  They don't quite know how they're going

11   to handle that.       Clearly they've got some staff work

12   to do.     There is some additional refinement they're

13   going to have to do to their organization.                         Right

14   now it's an agency that's in flux, and the one thing

15   we cannot do is go to Congress with promises.                      We're

16   going to raise enough controversies as it is.                      We've

17   got to go to Congress with agencies who are entirely

18   credible as statistical agencies.

19                  CHAIRMAN MOUNT:           When is the order going

20   to be sent out?

21                  MR. COFFEY:           The order?         When I have

22   time.     I'm basically the resource for both of these.

23   We   have    two     other    permanent        staff   and   a     chief

1    statistician in our shop, but this is my baby, both

2    of these.

3                    CHAIRMAN MOUNT:              Like a month are we

4    talking about?

5                    MR. COFFEY:           A month, possibly longer.

6    I have promised the agency heads some issue papers

7    on some of the extremely interesting comments that

8    we got.     We don't anticipate a lot of changes in the

9    order.     You can see that one of the reasons is we

10   have to have certain relationships between the order

11   and the statute in order to make this whole strategy

12   work,    and    those        things   we're      going       to     be   very

13   reluctant to change unless there's somebody on the

14   Hill who wants to make a similar change.

15                   What we anticipate is going to happen on

16   the   order,     we     have    gotten       comments        now.        We're

17   probably       going     to    go     back      to     the    statistical

18   agencies with some issue papers on a number of the

19   comments, a number of the issues raised, hash these

20   out     further,       and     then    basically        make        whatever

21   hopefully small changes will need to be made to the

22   order    itself,       and    then    go   to    the    next      important

23   step, which is going to be to write the guidance

1    that implements the order.

2                   The order is written in fairly general

3    terms.    There are a lot of things in here that we

4    flesh out in the next stage of things, which is how

5    we're going to do this.          This says what we're going

6    to do.    The next step is how we're going to do it.

7                   MS. COX:       But who's affected?       Would EPA

8    come under this order?

9                   MR. COFFEY:       They could within 60 days,

10   any time we can to do it.              Once this order is in

11   place, we can amend that list at the end with a 60-

12   day public comment period.            We've got to have reason

13   to do it.   We've got to have whatever.

14                  What was really needed in this case and

15   what we asked the agencies to do is look at several

16   things.        Do     you     have    authority    to     collect

17   information for statistical purposes?              No point in

18   being on the list if you don't.

19                  Second, do you have the wherewithal to

20   provide security for this information, to make sure

21   it   doesn't    get    used     for    other   purposes    unless

22   there's some statutory reason for doing that?                 And

23   in that case, you've got to go through some other

1    steps to make sure that the public knows exactly

2    what you're doing.

3                   And all of these agencies, we believe,

4    passed these tests.      There's still a bit of question

5    about -- we don't have a final opinion from Chief

6    Counsel at IRS over some questions on the authority

7    of SOI Division, but we're pretty sure that BTS will

8    pass muster.     All these other agencies are going to

9    pass muster.

10                  Under the order it is very easy for us

11   to extend the scope of this, the effect of this

12   order   to   other   agencies   by   simply   adding   to    the

13   list.      If you look at the general terms of the

14   order, it doesn't even say it has to be just a

15   particular set of agencies.          We've grafted that on

16   to say, well, the following agencies are the ones we

17   intend for this to apply to at this point in time.

18                  CHAIRMAN MOUNT:       Are you going to be

19   here afterwards?

20                  MR. COFFEY:      Unfortunately I've got a

21   command performance back at the office in about 40

22   minutes.     I wish I could stay around longer.             I am

23   likely to be back.        Because I've got to go this

1    afternoon, I'm likely to get back tomorrow morning.

2    It was a choice of one or the other.                So if you

3    have some more questions you want to think about

4    tonight and talk tomorrow, maybe at the break we can

5    discuss any other things you're interested in.

6                  CHAIRMAN MOUNT:         Thank you very much,

7    Jerry.      That   was   a   very   important   topic,   and   I

8    remember it was one of the first topics that was

9    discussed when I joined the Committee a number of

10   years ago.

11                 So we should move on now to the last

12   subject for the afternoon -- I can't even say it --

13   pollution control experiments.          I've obviously been

14   here too long this afternoon.          Inder Kundra from the

15   Office of Statistical Standards.

16                 Sorry for squeezing your time.

17                 MR. KUNDRA:       I'm Inder Kundra.        It's a

18   pleasure to talk to you.

19                 The purpose of my talk is to update the

20   Committee     concerning      the    experimental    economic

21   project undertaken by EIA to analyze the effects of

22   environmental regulations of energy industries.

23                 In 1993 we informed the Committee that

1    we were in the process of replicating the results

2    using    a    software        built      by       Arizona    and    using   a

3    uniform set of parameters.                That's what I'm going to

4    report here.

5                       The   Clear     Air    Act       of    1990    instituted

6    variable emission permits for sulfur dioxide.                             Each

7    permit with the industry was given to emit one ton

8    of sulfur dioxide.            These permits were the industry

9    could purchase or sell or even keep these permits

10   for future use.          That's called banking.

11                      And   by    1993,          a    central       market    was

12   established        for    trading        these       permits       with   the

13   provision that to auction about 2.8 percent of the

14   annual       allocation       by      revenue        to     discrimination

15   auction (phonetic), this kind of auction does not

16   generate any money for the central authority.

17                      The    Energy      Information           Administration

18   contracted the University of Colorado and Arizona

19   for two experimental institutions that mimics the

20   salient features of the sulfur dioxide market to

21   develop      and    document       transportable            software      that

22   implements the experimental institution and propose

23   to replicate by pots and pots (phonetic), propose to

1    replicate high pluses (phonetic) of possible future

2    testing with additional experimental and field data.

3                        The    results      were         presented      to    the

4    Committee in 1990 and 1991.                   In '91, following the

5    recommendation of the Committee that EIA should pay

6    attention to the statistical details, we analyzed

7    the     Colorado          experiment      and        presented      to    the

8    Committee with a finding that there was no crossover

9    between        the        replications,         and        the     Colorado

10   experiment was not subject to any experimental bias.

11                       At that time the Committee stressed the

12   need          for         replicating          these          experiments.

13   Subsequently we funded the Universities of Southern

14   California          and     Mississippi         to     replicate         these

15   experiments by using Arizona software and design and

16   by using a statistical experimental design Arizona

17   software.

18                       To test the applicability we adopted an

19   experiment, a two-by-two pictorial design with two

20   supplix (phonetic) within each cell.                          This design

21   consisted       of    two     forms,    high         and   low,    and    two

22   technologies,         old    and   new.         The    high      forms,   the

23   forms     I    have       indicated     the     amount        of   the    BTU

1    produced and the technologies, I have indicated the

2    amount of sulfur dioxide emission per BTU, and with

3    the    condition       that   each      from      the     high    forms    we

4    allocated about eight -- there were two figures.                           I

5    mean    six    --   12   figures     for       the      experiment,       one

6    through six and seven to 12.                   One to six would be

7    allocated eight permits, and we have seen that eight

8    permits for the high forms and four from seven to

9    12, and for the low firms, in those two -- as is

10   obviously       from     here,    that       we      did     deliberately

11   introduce       variations       taking        the        firms   and     the

12   technologies.

13                   And to start the experiment, we started

14   in the beginning with about $20 for each student,

15   and    those    students      then       made      their      profits     by

16   selling the permits.             They were the subjects within

17   the    firms,    made    profits     either          by    redeeming      the

18   permits at the pre-assigned redemption values or by

19   selling the permits to other firms in each of the

20   transaction periods.             The -- either in a revenue

21   neutral, sealed, bid discriminatable auction or in a

22   double   auction.         That     is    a     centralized        exchange

23   where a public bids us and gets prices.

1                    The experiment was done, repeated about

2    eight        times        in      each         of        the     universities

3    independently, and in each of the replications, we

4    had different students.

5                    The       total        profits       which      was     made   by

6    these students in each of the experiments at the end

7    of the 12 periods were used to determine if the

8    observed      differences          in     estimated             profits         in

9    universities         and       application          to     other       subjects,

10   simply things were obtained for determining as the

11   basic   parameters         to     use    for        making      some    sort   of

12   distinction whether the relation was -- whether we

13   would replicate experiments or not.

14                   Next slide.

15                   As        is     obvious            from       here,     at    18

16   universities         we        could     see        that       there    was    no

17   difference.          Most independent poll, even -- within

18   applications,         within           universities             of     different

19   technologies, of different subjects within the given

20   percents.

21                   What we concluded from here that we were

22   able    to    replicate          those    experiments            without       any

23   problem, without any bias in here left.

1                     I just want to add another slide where I

2    have to thank Dr. David Bellhause from Canada.                    He

3    suggested an experiment like this, that we should

4    have done the analysis with different firms if we

5    see   an    obvious     infraction     between   the    firms    and

6    these, but my main problem was that we were taking -

7    - test the only applicability, and the firms were

8    taken      within    the   universities    and   all     of     those

9    things.      We did it.

10                    It is not something you say whether you

11   do this or that way.                Still we can come to the

12   conclusions that we can replicate those experiments

13   and maximum variations which was formed was between

14   the     forms,      between   the    technologies      within    the

15   universities.

16                    And I am very thankful to him because I

17   did talk to him once or twice on the phone.

18                    That's all I can say about this.

19                    CHAIRMAN MOUNT:       Thank you.

20                    The discussant is Greta Ljung.

21                    MS. LJUNG:         So I'll be just making a

22   couple of comments on the experiment, and then I'll

23   discuss the analysis, and the last transparency that

1    David had provided covers some of the topics that I

2    was going to mention with regard to the analysis.

3                    And    the    first   transparency        is    just    a

4    summary of the experiment.                 We have a two-factor

5    experiment.         The factors are per type and technology

6    type.       We have a two-level design.            Each factor has

7    two levels.         We are running the experiments in two

8    locations, and the experiment is replicated eight

9    times in each location.

10                   And the output variable we're interested

11   in     is     the     total    profits      realized       by         each

12   participant.

13                   The    objective      of   the   experiment       as    I

14   read it is to study the effects of the two factors

15   and also to test the hypothesis that the results can

16   be     replicated,      that    the    results      are        sort    of

17   insensitive to the location and also to the subject

18   who was used in the experiment.

19                   Now,    the    two-level     design   that's          used

20   here is, of course, very economical.                     It includes

21   the fewest factors possible, possible to study the

22   factor effects.          The disadvantage is that we can

23   only    study       linear    effects,     while    if     there       be

1    nonlinear relationships between our output variable

2    and the factors, we would not get information on

3    those nonlinearities.

4                    And in the present setting, a potential

5    concern is that we have only four combinations of

6    the two factors.         We have very small experiments.

7    Within each cell there are only two subjects.                 So we

8    have a total number of participants in each trial

9    here is only eight, and so a question arises:                   are

10   the results that we get with only eight subjects

11   really   representative     of    the    market     where     there

12   would be many more players?

13                   Now, as far as the replications, we have

14   a fairly large number of replications.               Eight is a

15   fairly good number.       Different students are used in

16   different   replications.        I   think    slightly      better

17   design   here    might   have    been    to   use   --   in    each

18   location only use like four sets of students and

19   replicate the trials for those.               That would have

20   given us a slightly better estimate of experimental

21   error    perhaps   and   might    have    given     us   slightly

22   different information.

23                   Now, the tests that are performed show

1    no differences between replications, and that to me

2    says that the experiments if tightly controlled, the

3    same instructions given, somehow those results are

4    not all that exciting.              I mean it would have seemed

5    it would have been a little more interesting to try

6    to introduce a little more noise into the system

7    here and to see how sensitive or if the results are

8    sensitive       to   changes      like    changes       in       parameters,

9    maybe     use        different       types        of        --     different

10   instructions or different training or different sort

11   of subjects, not just these who were all business

12   majors, which are fairly uniform, just introducing

13   some changes instead of just replicating everything

14   under    constant       conditions        could    have          given   us   a

15   little more information.

16                    Now, when we talk about replicability,

17   the tests that are done in the paper basically focus

18   on the average if you compared the two locations.

19   The     tests    that      are     done    focus       on    the     average

20   shortage realized at each location.                    So there's just

21   a     comparison      of     mean     values.           One        might      be

22   interested      also    in       comparing   the       factor       effects.

23   Are the factor effects the same when we replicate

1    the experiment or did we get different results?                      So

2    we might want to compare just the -- we can do the

3    analysis or we can think in terms of a mean.                       The

4    observed -- for each location is the mean plus the

5    firm effect, plus the technology effect, and then we

6    had possible interaction between the two factors,

7    the replication effect, and then error.

8                  I've       calculated           those         parameters

9    separately for the two locations and compare not

10   just the overall means for the two locations as done

11   in the paper here, but we would also be interested

12   in   are   the    firm   effects        the   same     in    the    two

13   locations and are the technology effects the same,

14   and we are also comparing two-factor interactions

15   for the two locations.

16                 Now, if we compare the firm effects for

17   the two locations, what we are really looking at is

18   the university by firm interaction.                   So it becomes

19   an interaction effect with the university.                    And the

20   same, we have an interaction effect with technology

21   if   we    compare    the    138,       actually      half    of   the

22   difference    between       138   and    151.        Half     of   that

23   difference       is   the     university        and         technology

1    interaction.         Half    of    the       difference          of    the   two

2    factor       interaction       becomes             the     three           factor

3    interaction, the interaction between the two factors

4    and    the    university,         and    I     think       all        of   those

5    quantities are of interest.

6                    Now, if we wanted to write out a model

7    that   includes      location,          we    would       then    --       that's

8    written down on the bottom part there.                           We have an

9    overall mean.

10                   Three      main    effects,          if    we     treat      the

11   university effect as a fixed effect, we have three

12   main     effects.       We     have          now    three        interaction

13   effects,     three    two-factor         interaction            effects      and

14   one and then the three-factor interaction effect,

15   replication effect, and the random error.

16                   And the replication effect here, we are

17   not    interested     in     making          inferences      about         those

18   specific student groups that we used, but rather we

19   would treat those as a random sample from a much

20   larger population of students.                      So the interaction

21   effect should be treated as a random effect rather

22   than a fixed effect.

23                   Now, the analysis that we do would then

1    include     sums        of    squares       corresponding         to     those

2    terms, and that was done at the last transparency or

3    table that David had provided.                     David also included

4    interactions       between          the    factors       and    replicates.

5    That was the last one that we showed.

6                      This is then the table that was included

7    in the paper, and when I first looked at that, a

8    sort   of   striking          feature,      I     thought,      was    the   16

9    degrees     of    freedom          for    firms    and    16    degrees      of

10   freedom     for     technology,            and     this    is     a    little

11   strange, given that we only had two levels of each

12   factors.         There       should       really    be    one    degree      of

13   freedom instead of 16, and the reason we have 16

14   here   is        that        the    analysis        assumed      a     nested

15   structure.         So we assume that the replicates are

16   nested within universities, and then the treatments

17   are nested within replications.

18                     But    that       is     sort    of     not    quite       the

19   correct assumption because if we assume firms nested

20   really in replications, we would actually have 16

21   different    firms.            That's      what     the    nesting       would

22   imply, and the same for technologies, 16 different

23   technologies.           Each replicate would basically use a

1    different level of the factor.

2                      I     would       note      that        the     levels        stay

3    constant      across          the    experiment.                 There     is    no

4    nesting.      Those factors are crossed.                           So that is

5    something that needs to be changed here.

6                      And       then    I    think       we     have     degree      of

7    subjects within cells, and we have an F ratio.                                    F

8    ratio for that particular component, and then we

9    have an error term.                  Now, the error term in this

10   particular case, since we are already subtracting

11   out    the    cell          variability,            typically        the        cell

12   variability       would        provide        the    error,        and    sum    of

13   squares      --       the    error,       sum       of    squares        in     this

14   particular            table         probably             comes      from        the

15   interaction,           from     omitted         interactions             and    the

16   interactions           probably          in     this        case      are       the

17   interactions          between       firms     and        technology.            That

18   would give us 16 interactions, 16 degrees of freedom

19   there.

20                     Now,        for       testing          main     effects        and

21   interactions, my preference would have -- no, no,

22   for the analysis down here -- if you are interested

23   in    comparisons           between      firms       and        technology,      my

1    preference would have been to combine and not break

2    out within cell variability from the error, combine

3    those two into a single error estimate.

4                      Now, David's analysis looked quite good.

5    So basically what we need to do is include main

6    effects and interactions, and that was all done.                  So

7    I   think    his     suggestions    there    were    very,    very

8    useful,     and    that's   probably   the   right   way     to   go

9    about the analysis.

10                     Because in the analysis that's done on

11   this particular page, the F ratios all have the same

12   error mean squared, but because the very experiment

13   was done, it's not quite clear that we'll have the

14   same error mean squared for all F statistics, and

15   that's something that one should pay attention to,

16   as well, in the analysis.

17                     But it's true of course that although

18   it's said the results don't really change, but we

19   still like to have, even if the results are not

20   affected, we still like to have sort of a sound

21   system.

22                     CHAIRMAN MOUNT:   Thank you.

23                     From the Committee?    Bradley.

1                   MR. SKARPNESS:           I think this brings up a

2    good point in that when you're doing these kinds of

3    analyses that you include a model, and then things

4    are clarified a little more, exactly what's going on

5    and how you're going to do the analysis, and that

6    would help here.

7                   And the other thing is that I was also

8    struck a little bit by the way he broke up the sums

9    of squares here, and in David's approach, I don't

10   think   he   has     a   nested    effect      in   there,   what     he

11   showed.      Okay.       You do, but this is still not sort

12   of the standard way that we sort of -- you know,

13   from the model you would break up your different

14   components of variability here.

15                  And       then     the     other     thing       I    was

16   wondering,     you       know,    you     do    have     this       fixed

17   university effect.          You know, it could be a random

18   effect,      too.         You     know,     you're      really       not

19   generalizing this.         I know it's not, but --

20                  MR. KUNDRA:        It's not.

21                  MR. SKARPNESS:           It would be nice to sort

22   of say, well, we did this across universities or

23   something, but that's just an aside.                   It is a fixed

1    effect.

2                      CHAIRMAN MOUNT:          Richard.

3                      MR. LOCKHART:           Well, I'd like to put in

4    a   word    for    multivariate       analysis     in        the       form   at

5    least of asking a question to reveal that which I

6    don't   understand.           The    eight    students        are       in    an

7    experiment together.             When you take instead of eight

8    students     two    in    a   high    tech.,      in     a    large,          old

9    technology firm, and two in a large new technology

10   firm, they're all in one.             They're run together.

11                     MR. KUNDRA:       Right.

12                     MR.    LOCKHART:          And   they       buy       permits

13   effectively from each other.

14                     MR. KUNDRA:       That's true.

15                     MR. LOCKHART:            So that there are the

16   eight      responses      that      are    obtained      in        a    single

17   replicate of the experiment.                It would seem to me to

18   be at least potentially correlated.

19                     I mean the analysis of variance that's

20   been discussed by David and Greta is one of the

21   univariate ways of -- there are univariate versions

22   of MANOVA and then there are multivariate versions

23   of MANOVA, and the data don't actually show much

1    sign of correlation --

2                   MR. KUNDRA:    No, they don't.

3                   MR. LOCKHART:        -- between the students

4    within a cell, if you know what I mean.

5                   MR. KUNDRA:     That was the reason that I

6    did it that way, because we wanted to test whether

7    the students in the cell or not, as well as reasons

8    because we had -- but this was the reason.            That's

9    one of the reasons we wanted to test whether there's

10   a change between students or not, and that was the

11   first problem that was raised by Dr. Bishop, to see

12   whether   we    can   test    whether   there's    publishing

13   (phonetic) for students or not.           That's the way it

14   was designed to test the students.

15                  I understand what she's saying, that we

16   should have not nested, but the question here was

17   that nested or not nested, the main things was we

18   wanted to test where the replications are.            We can

19   repeat the experiments and all that.            We have them

20   or not.

21                  And then one of the other factors is

22   also the error -- to test the question that she

23   raised,   whether     there    is    interaction   with   the

1    squares or not. That's why we did that way, but I

2    mean, they would have suggested the same thing for

3    both of these interactions between the firms and --

4    I   mean   the    firms   as    the   --   and   the    interaction

5    between    the     firm   and    technology       and    all    those

6    things.

7                     I had a discussion with him.              First he

8    was   taking     the   university,     and   he    was    not    even

9    taking the replication test, not nested.                       Then I

10   discussed with him, and he changed it.                  So it was a

11   good discussion with him.

12                    But I do realize what you are saying,

13   that we should have not used nested because nested -

14   - the purpose was to see whether we can really get

15   what we're getting.

16                    CHAIRMAN MOUNT:      I do have one question.

17   Bill Schulze at COLNOW (phonetic) has recently set

18   up an experimental lab and has just introduced the

19   Arizona software.         So I'm sort of interested if you

20   have evidence about the form of auction in terms of

21   which auctions work best in terms of coming up with

22   efficient prices in this kind of situation.

23                    PARTICIPANT:     Double.

1                  CHAIRMAN MOUNT:       Double election.

2                  MR. KUNDRA:     We did that.

3                  CHAIRMAN     MOUNT:       I    mean        it's    pretty

4    clear, right?      Yeah.

5                  So     are   there     any       more        comments?

6    Campbell.

7                  MR.    WATKINS:       Just      so     I    understand

8    Greta's comments, on the nesting if you had eight

9    different technologies within the nest -- what was

10   the other factor you mentioned that also should be

11   broken out?

12                 MS.    LJUNG:         You       have        firms    and

13   technologies.

14                 MR.     WATKINS:              Yeah,        firms     and

15   technology.     So that then if you did that, then your

16   interaction effects would proliferate, if you do all

17   of those combinations, right?

18                 MS. LJUNG:      Well --

19                 MS. BISHOP:       Basically we wanted to know

20   whether the change of university affected any of the

21   conclusions that you would have drawn had you only

22   done it in one university, and that was the basic

23   purpose of doing it.

1                 CHAIRMAN       MOUNT:      So   have   you    got   a

2    comment, Samprit?

3                 MR. CHATTERJEE:          Yeah, I think the same

4    kind of thing.          Since other factors were balanced

5    with   regard      to    the      universities,     that's    the

6    breakdown.      So it is a perfectly balanced layout.

7    So the university is one replication and --

8                 MS.        BISHOP:       Except      that    they're

9    different students.

10                MR. CHATTERJEE:         Yes.

11                CHAIRMAN MOUNT:           Any comments from the

12   public?

13                MR. KUNDRA:          I just want to stress the

14   point again we were not suggesting -- that was not

15   our purpose because we had deliberately introduced

16   the variations into those firms and technologies.

17   That's how we started.

18                CHAIRMAN MOUNT:           So before we formally

19   close, I just want to ask the Committee:                  are you

20   going to be here for lunch tomorrow?                We do have

21   some Committee business, and who's not going to be

22   here for lunch?

23                MR. RELLES:          I have to leave right after

1    I give my discussion.

2                MS. COX:     I'll be here, but we can't

3    talk on and on.

4                CHAIRMAN MOUNT:    I thought that it would

5    be nice if we could break now.     Right?   That's what

6    I was assuming.   Maybe we could meet -- could we

7    meet at 8:30 tomorrow morning for breakfast and you

8    try and be there a little bit earlier so we're ready

9    to talk at 8:30 so we can get Dan's input?

10               MS. COX:    I have to leave at 2:30.

11               CHAIRMAN MOUNT:    Yeah, so let's do that

12   then.   The Committee try to get down about 8:15 so

13   you have time to eat, and we'll just talk for a

14   while at 8:30 before the meeting at nine, and I

15   think it's next door, I assume, in the Lewis Room.

16               And to remind you that we're going to go

17   to 701 Pennsylvania Avenue for dinner.      We can't get

18   in at Le Rivage, and for people who want to walk,

19   we'll meet in the lobby about five past six.        Five

20   past six in the lobby.    Who's going to walk?     You're

21   going to walk?

22               Who's walking?    Greta, are you going to

23   walk?   I just want to know how many people to look

1    for.   Right, you're walking.

2                  MS. BISHOP:    Where to?

3                  CHAIRMAN    MOUNT:     To    701     Pennsylvania

4    Avenue.

5                  MS. BISHOP:    Well, I have a car in this

6    building.   How far is it?

7                  MR. KENT:    It's right across the Mall.

8                  CHAIRMAN    MOUNT:    I     assume    it's   right

9    across the Mall.

10                 MR. KENT:    It's right across the Mall.

11                 MS. BISHOP:     Well, I think I'll drive

12   over if anybody wants a ride.

13                 CHAIRMAN MOUNT:       Would the offer of a

14   ride make you change your mind?

15                 Five past six.       That will give us time

16   to make it.

17                 (Whereupon, at 4:51 p.m., the Committee

18   meeting was adjourned.)

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