Environmental Economics II

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Environmental Economics II Powered By Docstoc
					Environmental Economics II

      Dr. Anil Markandya
hssam@bath.ac.uk – 01225 386954 –
        Room 3E 4.31b
     Valuing the Environment
• Environmental Valuation
• Enable environmental impacts to be
  included in Cost-Benefit-Analysis (CBA)
• To take account of environmental damage
  in measuring economic performance
• To take account of environmental benefits
  of public programs

                                              2
     Categories of environmental
              benefits
• Use Value (UV)
• Existence Value (EV)
• Option Value (OV)(Option Price = Expected Use
  Value + OV.
• Quasi Option Value (QOV)
• Bequest Value (BV)
• Total Economic Value (TEV)
• TEV = UV+EV+OV+QOV+BV


                                                  3
 Non-market valuation techniques
• Stated Preferences
  – Contingent Valuation
  – Choice Modelling
• Revealed Preferences
  – Travel Cost Model
  – Hedonic Pricing




                                   4
    The Contingent Valuation Method
• Stated preference technique
• Questionnaire based
• Direct method
• Valuation of a hypothetical scenario
- It is called ―contingent valuation‖ because the
  valuation is contingent on the hypothetical
  scenario put to respondents
• Non Use Values + Use Values
• Willingness To Pay (WTP) question
                                                    5
                    Stated Preference Techniques: CVM
An interview is used to create the hypothetical market within these questions are
asked. The hypothetical market comprises two key parts:
         a statement of the proposed change; and
         an institutional mechanism through which the proposed change is to be
         provided/avoided and financed.
The challenge in conducting a CV is to make the market as realistic as possible.
The process of directly questioning a sample group to ascertain their valuation of a
change can be divided into six stages. These are (each with a number of steps):
         definition of survey objectives;
         design of the questionnaire;
         surveying the sample population;
         creating a database and performing an exploratory data analysis;
         estimating WTP values; and
         reporting the survey results.                                             6
       CVM: Stage 1 - Project Definition - Theoretical Model

CV study should begin with a basic theoretical model: two purposes:
       Identifies the information required from questionnaire
       Generates predictions allowing results to be checked
Number of sources of information that can be used to construct the
model, including:
       predictions of economic theory and existing literature,
       discussion/meetings with focus groups/affected parties.
Participants discuss understanding of the context of the good/service in
question, the good/service itself, its “value”, who should provide it,
how it should be paid for, whether they would contribute, etc.
The information from the focus groups is particularly valuable in
designing the CV survey.
                                                                     7
        CVM: Stage 1 - Project Definition - Sample Design

For a site-specific resource, the sample may be drawn from:
Visitors to the site („on-site‟ sample)
       • does not elicit information on the WTP of „non-users‟; •
       interviews must be kept short; • procedure is needed to select
       among visitors to a site
Households within a certain radius of the site („off-site‟ sample)
        • geographical boundaries need to be defined; • a larger
       sample required, many households may not visit the
       site
It is also important to carefully select the size of the sample:
       A larger means more confidence that the sample mean
       WTP/WTA is a reliable estimate of the „true‟ mean
       WTP/WTA. (Balance precision and cost)                         8
  CVM: Stage 2 - Questionnaire Design - Background Questions

General background: Questions on general characteristics of the
respondents – information for checking the validity of the valuation
results
Respondents’ tastes and socio-economic characteristics (is the
sample representative?). Personal details - should , come at the end of
the questionnaire
Respondent’s knowledge of the commodity in question, e.g.
background questions concerning the respondent‟s visits to a recreation
site should cover such issues as:
       • attitudes towards environmental issues; • proximity of their
       home to the site; • frequency of visits; • duration of trip; •
       reason for visit, etc.
These questions should be asked at the beginning of the interview as
they are relatively straightforward to answer, and will help to build-up
                                                                       9

the respondent‟s confidence.
  CVM: Stage 2 - Questionnaire Design - Preparation Questions

To avoid bias, interviewer must make sure the respondent is aware of:
       budget constraints (you cannot spend more than you have!)
       their right to refuse to pay for the good
If the event of a negative response, the reason must be recorded
a „zero valuation‟ is implied if:
       the respondent may not be able to pay anything; or
       the respondent may not be willing to pay anything.
a „protest bid‟ is implied if:
        the respondent may find it too difficult to establish a monetary
valuation;
       the respondent may disapprove of the concept of expressing
       environmental resources in monetary terms; or may be hostile
                                                                  10
                  Format of WTP question
• Open Ended:
   – ―How much are you willing to pay for public good A?‖

• Bidding Game:
   – 1) ―Are you willing to pay X for public good A?‖
   – 2a) If Yes to (1), ―Are you willing to pay Y for public good A?‖ (Y>X)
   – 3a) If Yes (2a), ―Are you willing to pay Z for public good A?‖ (Z>Y).
   – 4a) if Yes to (3a) …
   – If No to (Na), WTP questions stop.
   – 2b) If No to (1), ―Are you willing to pay T for public good A?‖ (T<X)
   – …

• Payment Cards:
   – choose a WTP point estimate from a list of values




                                                                         11
• Dichotomous or Discrete Choice CV (Referendum format):
   – ―Are you willing to pay X for public good A?‖ => STOP

• Dichotomous or Discrete Choice CV with follow-up:
  1) ―Are you willing to pay X for public good A?‖
  2a) If Yes to 1, ―Are you willing to pay Y for public good A?‖   (Y>X)
  => STOP
  2b) If No to 1, ―Are you willing to pay Z for public good A?‖    (Z<X)
  => STOP




                                                                       12
CVM: Stage 2 - Survey Design - “Open-ended” Elicitation Format

Respondent simply asked to state maximum WTP for a specific
environmental change
The advantages of the open ended:
     Quick and easy to administer and analyse;
     Can be performed with a smaller sample size;

     Avoids „anchoring‟ effects - respondents influenced by
      suggested starting value.
Main drawbacks:
     Makes strategic bias, more likely

     The respondent may need a reference point to bound value
      judgement
     Respondent must be familiar with the affected commodity in
                                                               13
CVM: Stage 2 - Questionnaire Design - “Dichotomous Choice” or
              “Referendum” Elicitation Format
       range of values for the max WTP of individuals pre-set.
       sample of respondents is divided into sub-samples.
       value within the pre-set range is assigned to each sub-sample (the
       source of he so-called „anchoring effect’).
       Each respondent asked whether WTP assigned value for proposed
       change
Answer not the max WTP – only consent or refusal to pay a given amount
     Random utility theory (logit model) are required to estimate the
       respondent‟s mean and median WTP values. Requires large sample.
     No Incentive to engage in strategic behaviour.
    Easier to convey decision rule - >50% say “yes”  change provided.
     Realistic – individuals typically make decisions faced with fixed 14
       prices.
  CVM: Stage 2 - Survey Design - “DC” Format: An Example

After describing their illness, the respondent was given the following valuation
question:
We are now going to ask you a hypothetical question. Suppose you were told that,
within the next few days, you would experience a recurrence of the illness episode
that you have just described for us. What would it be worth to you – that is, how
much would you pay – to avoid the illness episode entirely?
Remember that you are paying to eliminate all of your pain and suffering, your
medical expenditure, the time you spent visiting the doctor or clinic, your missed
work, leisure or daily activities.
Bear in mind if you pay to completely avoid being ill this time, you have to give up
some other use of this money. For example, you may reduce your expenditures for
entertainment or education.
Would you pay      300     dollars to avoid being sick at all?
[If NO] Would you pay       100     dollars to avoid being sick at all?
[If YES] Would you pay     1,000    dollars to avoid being sick at all?         15
    CVM: Stage 2 - Questionnaire Design - “Iterative Bidding”
                      Elicitation Format
“suppose you were told that within the next few days you would have a
recurrence of the respiratory condition that you have just described.
Would you be willing-to-pay $10 to avoid the illness episode entirely?”
       1.         “NO”, I would not be willing-to-pay $10.
       2.         “YES”, I would be willing-to-pay $10.
    If “NO”, would you be willing-to-pay $…
      1.a    $9   If “YES”, then stop; if “NO”, then go to 1.b
      1.b    $8   If “YES”, then stop; if “NO”, then go to 1.c
      1.c    $7   If “YES”, then stop; if “NO”, then go to 1.d
                                       


      1.k $0.25   If “YES”, then stop; if “NO”, then explain why
                                                                   16
                NOAA Panel Guidelines

•   Conservative design => better to underestimate WTP
•   WTP, rather than Willingness to Accept (WTA)
•   Referendum format (i.e. Yes/No Questions)
•   Accurate description of the good/scenario => use of focus groups
    and pretest of the survey instrument
•   Reminder of substitute commodities
•   Yes/No follow ups
•   Checks on understanding and acceptance
•   Cross tabulations
•   Sample size circa 500 is a minimum.




                                                                       17
  Other important aspects for questionnaire
              development (1)
• Mail / In Person / On the Phone interview
• In person => costly, interviewer bias, time consuming,
  more accurate, better option if it is difficult to explain the
  scenario (need pictures), only users if on site
• Mail => low response rate, sampling bias => who takes
  the survey? Those who are interested in the topic?,
  limited information, relatively inexpensive
• Telephone => relatively inexpensive, limited information,
  not accurate, response rate, developing countries?
• Mail + Telephone
• Internet
• Computer based instruments
                                                               18
  Other important aspects for questionnaire
              development (2)
• Introduction
• Warm-up questions
• Questions on the knowledge of the problem / experience with the
  environmental good => USE values, etc
• Description of the scenario
• WTP question(s)
• Debriefing questions => why did you vote in favour or against the
  program
  - Use and Non-Use values investigation => did you vote yes,
  because (a) you will visit the national park, (b) even if you will never
  visit the national park, you want future generations to visit the park,
  etc.
• Attitudinal questions
• Socio – demographic questions. Ask questions on Income at the
  end of the questionnaire!!! => we don’t want to irritate the
  respondent
                                                                         19
  Other important aspects for questionnaire
              development (3)
• Identify protest respondents after the WTP questions (ask why the
  respondent voted YY, NN, NY, YN)
• Analyze the data for the full sample of respondents, then delete
  those respondents that show protest behaviours
• Income. Try to get an answer to the income question. In developing
  countries, sometimes researchers (Cropper, Alberini) ask a list of
  expenditures. If you have no information on income from some
  respondents, don’t loose those observations. Add a dummy equal to
  1 for those that did not answer the income question, and 0
  otherwise. Set equal to 0 the income of those respondents that did
  not answer the income question. In your regression the coefficient of
  the dummy for those that did not answer the income question tells if
  they are statistically different from those that reported income. In this
  way you don’t loose the observations!
• Clearly define the population of interest
• Consider your budget constraint
• Make sure that your referendum question avoids free rider
                                                                         20
  behaviours!
                     Payment vehicle
  • Whose welfare are we interested in?
    => Important for sampling plan
  • TAX => One time Tax is incentive compatible
  • How do we choose the tax level? Focus groups, previous
    research, pretest, optimal bidding design literature, cost of the
    public program
                                             Percentage of YES responses to the bid

                                            100
                        Percentage of YES




If Data are not as                          80
Shown, use Non-                             60
   Parameteric
                                            40
     Methods
                                            20

                                             0
                                                  5   15   20   40   60   80   100    150
                                                                  TAX
                                                                                            21
      CVM: Stage 2 - Questionnaire Design - Payment Vehicle

Valuation question needs a realistic institutional context - usually an
appropriate payment (or bid) vehicle (instrument). The payment vehicle is
the mechanism through which the WTP/WTA values are to be
raised/distributed.
Key considerations when selecting a payment vehicle are:
       familiarity – does the respondent understand the payment vehicle?
       credibility – does the payment vehicle represent a realistic situation?
       empathy – is the respondent favourably or unfavourably disposed
             towards the recipient of the funds?
       feasibility – is the recipient of the funds capable of delivering the
                improvement?
       universality – would all the respondents be affected by the payment
              vehicle?
                                                                           22
                                 WTP and WTA
• The goal of contingent valuation is to measure the compensating or
  equivalent variation for the good in question. Both compensating
  and equivalent variation can be elicited by asking a person to report
  a willingness to pay amount. For instance, the person may be asked
  to report his WTP to obtain the good, or to avoid the loss of the
  good. Formally, WTP is defined as the amount that must be taken
  away from the person’s income while keeping his utility constant:
1)   V ( y  WTP , p, q1 ; Z)  V ( y, p, q0 ; Z)

     where V denotes the indirect utility function, y is income, p is a
     vector of prices faced by the individual, and q0 and q1 are the
     alternative levels of the good or quality indexes (with q1>q0,
     indicating that q1 refers to improved environmental quality). Z is a
     vector of individual characteristics.

• (Compensating variation is the appropriate measure when the
  person must purchase the good, such as an improvement in
  environmental quality. Equivalent variation is appropriate if the
  person faces a potential loss of the good, as he would if a proposed
  policy results in the deterioration of environmental quality.)
                                                                            23
 • Willingness to accept (WTA) is defined as the amount of money
   that must be given to an individual experiencing a deterioration in
   environmental quality to keep his utility constant:
2)   V ( y  WTA , p, q 2 ; Z)  V ( y, p, q0 ; Z)

 • Where q2 indicates a deterioration in quality compared to the status
   quo, q0.
 • In equations (1) and (2), utility is allowed to depend on a vector of
   individual characteristics influencing the tradeoff that the individual is
   prepared to make between income and environmental quality. An
   important consequence of equations (1) and (2) is that WTP or WTA
   should, therefore, depend on (i) the initial and final level of the good
   in question; (ii) respondent income; (iii) all prices faced by the
   respondent, including those of substitute goods or activities; and (iv)
   other respondent characteristics.
 • Internal validity of the WTP responses can be checked by
   regressing WTP on variables (i)-(iv), and showing that WTP
   correlates in predictable ways with socio-economic variables.


                                                                           24
     Dichotomous-Choice Contingent Valuation
• When dichotomous choice questions are used, the researcher does
  not observe WTP directly: at best, he can infer that the respondent’s
  WTP amount is greater than the bid value (if the respondent is in
  favor of the program) or less than the bid amount (if the respondent
  votes against the plan), and form broad intervals around the
  respondent’s WTP. To estimate the usual welfare statistics, it is
  necessary to fit binary data models.
• The simplest such models assume that an individual’s response to
  the WTP question is motivated by an underlying, and unobserved,
  WTP amount, which is normally (logistically) distributed. Formally,
  let WTP* be the unobserved WTP:
3)    WTPi *     i
• Where  is both mean and median WTP,  is a zero-mean normal
   (logistic) error with mean zero. The model is completed by
   specifying the mapping from the latent variable to the observables:
4) WTPi=1 iff WTPi*>B             and    WTPi=0 iff WTPi*≤B
• where B is the bid that was assigned to respondent i, WTP = 1
   means that the response is a ―yes,‖ and WTP = 0 means that the
   response to the payment question is a ―no.‖                         25
  • Because we observe discrete outcomes, we must derive the
     probabilities of ―yes‖ and ―no‖ responses. When attention is
     restricted to a normal latent WTP, the probability of a ―yes‖ response
     is, therefore:
                                                                                     B 
5) Pr( yes | Bi )  Pr( WTPi  1 | Bi )  Pr( WTPi  Bi ) = Pr( i  Bi   )  Pr i  i  
                                                  *

                                                                                     
  • Because / is a standard normal variate,
            B       B 
      1   i      i  
                    

  • where () is the standard normal cdf. If we define α=μ/σ and
    β=-1/σ, the probability of a yes response can be rewritten as:
  6) Pr( yes | Bi )   (    Bi )
    Equation (6) is the contribution to the likelihood by a ―yes‖
    observation (or a one) in a probit model with the intercept and one
    regressor—the bid. As long as  is identified and estimable—which
    requires that the bid amount be varied to the respondents in the
    survey, so that it becomes a legitimate regressor in the probit
    model—mean/median WTP is estimated as:
            ˆ ˆ
  7)    / 
      ˆ                                                                 26
• while the standard deviation of WTP is estimated as:
             ˆ
8)   1 / 
    ˆ

• The same formulae produce estimates of mean/median WTP and of
  the scale parameter of WTP from the logit coefficient if WTP is
  assumed to be a logistic variate.
• A standard probit routine will automatically produce standard errors
  for  and  , but not for  and  .
                                  
• To obtain the covariance matrix of  and  , you can use the delta
                                             
  method (Cameron, 1991).
• First calculate the covariance matrix of  and  produced by the
                                            
  probit routine V:
                            1
        n
9) V   w( z )  1 Bi  
                        B
            i 1
                    i
                         i   Bi2  
                                  
             
where zi      Bi , and w( zi )   ( zi ) {( zi )[1  ( zi )]} , with () the
                                       2


   standard normal probability density function (pdf).
Next, compute the matrix G :
10) G =   1 /  0 
                     
              / 2        
                         1/  2 
                              
                                                                                    27
• Finally calculate the matrix product V1=G’VG, with V1 the covariance
  matrix of  and  . Nb This can be done in LIMDEP.
                    
• If WTP is assumed to be a logistic variate, the steps required for the
  delta method are the same, except that w(z) in expression (9) is
  equal to exp(zi) / [1 + exp(zi)].
• in some studies, depending on the frequencies of the ―yes‖ and ―no‖
  responses to the payment questions, formula (7) produces a
  negative mean/median WTP figure.
• Perhaps a better way to avoid this problem is to work with a WTP
  distribution that is defined only over the positive semi-axis. The
  Weibull and the lognormal are examples of such distributions.
                                                                                
• The cdf for a Weibull with parameters  (>0) and  is F ( y)  1  e ( y / )
• Mean WTP is     1
                         1
                                where () is the gamma function
                                      
                                              1/
• Median WTP is   [ ln( 0.5)]
• The log likelihood function becomes:
      n

11)  WTPi  log(1  F ( Bi ; ,  ))  (1  WTPi )  log F ( Bi ; ,  )
    i 1
• where F is the cdf of the Weibull                                            28
• median WTP is generally regarded as a robust, and conservative,
  welfare statistic associated with the good or proposed policy. It is
  usually estimated more precisely than mean WTP, and is interpreted
  as the value at which 50% of the respondents would vote in support
  of the program, and hence the cost at which the majority of the
  population would be in support of it.




                                                                    29
         The Double Bounded Dichotomous Choice model
•    Double bounded models increase efficiency in three ways:
•    YN and NY answers bound WTP
•    NN and YY answers further constrain WTP
•    The number of observation is increased
     The log likelihood function becomes:
                 n
        log L   log F (WTP H ; )  F (WTP L ; )
                i 1




where WTPH and WTPL are the lower and upper bound of the interval
    around WTP defined above, F() is the cdf of WTP, and θ denotes
    the vector of parameters that index the distribution of WTP. (Notice
    that for respondents who give two ―yes‖ responses, the upper bound
    of WTP may be infinity, or the respondent’s income; for respondents
    who give two ―no‖ responses, the lower bound is either zero (if the
    distribution of WTP admits only non-negative values) or negative
    infinity (if the distribution of WTP is a normal or a logistic.))
                                                                      30
     Non parametric models for contingent
       valuation: the Turnbull estimator
1.   Consider only the first bid answer
2.   For bids indexed j=1,…,M, calculate Fj=Nj/(Nj+Yj) where Nj is the
     number of No responses to tj and Yj is the number of Yes
     responses to the same bid, Tj= Nj+Yj
3.   Beginning with j=1, compare Fj and Fj+1. Intuitively, % of No’s
     should increase with the increase in the bid
4.   If Fj+1>Fj then continue
5.   If Fj+1≤Fj then pool cells j and j+1 into one cell with boundaries
     (tj,tj+2], and calculate Fj*=(Nj+Nj+1)/(Tj+Tj+1)=Nj*/Tj*. That is,
     eliminate bid tj+1 and pool responses to bid tj+1 with responses to
     bid tj.
6.   Continue until cells are pooled sufficiently to allow for a
     monotonically increasing CDF
7.   Set FM+1*=1, F0*=0
8.   Calculate the PDF as the step difference in the final CDF:
     fj+1*=Fj+1*-FJ* for each offered price. These represent consistent
     estimates of the probability that WTP falls between price j and 31
     price j+1.
9.    Multiply each offered price (tj) by the probability that WTP falls
      between it and the next highest price (tj+1)
10.   Sum the quantities from step (9) over all prices to get an estimate
      of the lower bound on WTP:
                       M
      E LB (WTP )   t j ( F j*1 F j* )
                       j 0


11.   Calculate the variance of the lower bound as:
                              M*     F j* (1  F j* )
      V ( E LB (WTP))                       *
                                                        (t j  t j 1 ) 2
                              j 1        T   j




                                                                            32
                             Unrestricted              Turnbull
           tj    Nj    Tj         Fj            Fj*                fj*

           5     20    54       0.370          0.343              0.343
           10    15    48       0.313       Pooled back     Pooled back

           25    46    81       0.568          0.568              0.225

           50    55    95       0.579          0.579              0.011
          100    106   133      0.797          0.797              0.218
          200    82    94       0.872          0.872              0.075
          300    72    81       0.889          0.889              0.017
          300+    -     -         1             1                 0.111



ELB(WTP)=0*0.343+5*0.225+25*0.011+50*0.218+100*0.075+
+200*0.017+300*0.111=$56.50
V(ELB(WTP))=(0.343*0.657/102)*(5-0)2+(0.568*0.432/81)*(25-5)2+
+(0.579*0.421/95)*(50-25)2+(0.797-0.203/133)*(100-50)2+
+(0.872*0.128/94)*(200-100)2+(0.889*0.111/81)*(300-200)2=$29.52

                                                                          33
        Literature for this lecture
• Haab-McConnell ―Valuing environmental and natural resources‖
  chapters 1-5
• Perman et al. Chapter 12
• A good book for the CV: Mitchell-Carson ―Using surveys to value
  public goods: the contingent valuation method‖ Resources for the
  Future, Washington, DC, 1989.
• Read the paper Alberini, Rosato, Longo, Zanatta ―Information and
  Willingness to Pay in a Contingent Valuation Study: The Value of S.
  Erasmo in the Lagoon of Venice.‖
• I’ll post the slides and the paper on my website:
  http://people.bath.ac.uk/al224/




                                                                    34