Unemployment

Document Sample
Unemployment Powered By Docstoc
					Unemployment
Some Questions to think about

How many people here are in their last year of school? How many are looking for full
time work? For those who are, do you care what the unemployment rate is right now?
Why?


How many people think low unemployment is correlated with low wages in the
economy? How many people think low unemployment is correlated with high wages?


What in the long-term? If you graduate in a recession (when unemployment is high) or
a boom (when unemployment is low), would that affect your career 10 years down the
road? What does economic theory suggest? What does the data suggest?


Say you are working full time and your firm goes bankrupt and you are displaced.
Clearly you will be unemployed, at least for a little while you look for another job at
another firm. But would you expect your displacement to affect your career 5 years
later? Ten years later?


Stick around and I will tell you why know is a pretty good time to be looking for work.


On Friday, the latest unemployment figures were released by Statistics Canada. Does
anyone know what the current unemployment rate is? Statistics Canada announced
that the unemployment rate had reached a 30-year low of 6.4%.
Recent Unemployment Statistics
The unemployment rate differs markedly by province too:


UR by province for February 2006:


Canada     6.4%


Newfoundland and Labrador 15.1%
Prince Edward Island          10.9%
Noval Scotial                         8.4%
New Brunswick                 9.4%
Quebec                        8.2%
Ontario                       6.2%
Manitoba                      4.4%
Saskatchewan                  5.3%
Alberta                       3.1%
British Columbia              4.8%


Alberta’s unemployment is 3.1%!


Different ways that Statistics Canada Measures Unemployment (and Employment)


Unemployment is obviously a huge topic in labour economics. What it means to be
unemployed is not easy to define. But it is a situation for which most of us do not want
to find ourselves in. The amount of unemployed is often used to measure the pulse of
the economy and as an indicator of hardship in society.


Let’s first examine the official way to measure unemployment. The labour force (LF) is
defined as the set of people who are either employed (E) or are unemployed but would
like to be employed (U):


LF = E + U
Statistics Canada classifies someone as unemployed if he or she is on a temporary
layoff waiting to be recalled by their previous employer or he or she is without a job and
actively searched for work in the previous month. So most people who are unemployed
are not working but looking for work.


Each month, Statistics Canada conducts the Labour Force Survey, which is used
primarily for calculating the extent of unemployment in Canada. The agency randomly
selects and visits or calls about 35,000 households across Canada. Among the many
responses they collect from each household member is whether or not they are working
and if not, whether they are looking for work.


The unemployment rate is simply calculated as the fraction of people in the labour force
unemployed:


Unemployment rate = U / LF


One of the need things with statistics is that you only need a random sample of all
Canadians to get an unbiased estimate of the unemployment rate in all of Canada (you
don’t have to check with everyone all the time). With 35,000 households and more than
100,000 individuals surveyed each month, we get a pretty accurate estimate of the true
population level of unemployment that month.


There are multiple measure of unemployment, and it is not obvious which one provides
the best description of the state of the economy or the degree of hardship in the labour
market.


The unemployment rate reflects the proportion of a group that, at a point in time,
actively want to work but are not employed. However, it does not necessarily provide
an accurate reflection of the economic hardship that members of a group are suffering.
Why?
First, individuals who are not actively searching for work, including those who searched
unsuccessfully and then gave up, are not counted among the unemployed. Individuals
who were looking for work but stopped actively looking because they figured there’s
nothing out there are not classified as unemployed by Statistics Canada, and are known
as discouraged workers. It is difficult to identify discouraged workers. For this reason,
some economists prefer to focus on the employment rate, which is the fraction of
people         in        the        population         (P)         employed          (E):


Employment Rate = E / P


One minus the employment rate will give the fraction of people either 1) unemployed, 2)
discouraged workers, or 3) not working, not looking for work, and not discouraged (e.g.
people who at a point in time do not want to work).


Second, the unemployment rate does not tell us anything about the earnings levels of
those who are employed, and does not distinguish between part time and full time work.
An individual who is working part-time but looking for full-time work is not counted as
unemployed (Why? – look at the definition again).            To account for this, some
economists pay closer attention to the labour force statistics that come out each month
and differentiate between part time and full time work. Journalists will often note what
fraction of the employment growth that occurred over the last month was due to full-time
employment or part-time.


For example, from the CBC on Friday, March 10, 2006:


“Canada's unemployment rate fell two-tenths of a percentage point to 6.4 per cent in
February, matching the 30-year low set last November, Statistics Canada said Friday.


The country churned out 24,700 new jobs last month, matching analysts' expectations.
    The job creation was due entirely to growth in part-time work. More than 56,000 part-
    time jobs were added, while more than 31,000 full-time positions disappeared.”


    Sometimes journalists will view individual’s unemployed taking on part-time work as
    having to ‘settle’.   Like discouraged workers, they are no longer classified as
    unemployed, but the outcome may not be reason to celebrate entirely.         However,
    whether it is appropriate to view part-time employment like this depends obviously on
    each individual’s circumstances. My sense is that most part-time employment is likely
    driven by people who want to work part-time and not full time.


    Third, a substantial fraction of the unemployed come from families in which other
    earners are present – for example, many unemployed are teenagers who are not the
    primary source of their family’s support. Another case is if one spouse is unemployed
    while another is not. The unemployed spouse is not the single source of income for the
    family.


    Fourth, length of unemployment matters a great deal in determining the extent of an
    individual’s economic hardship. You would probably consider the circumstances of an
    individual who is unemployed for 1 month differently than for an individual who is
    unemployed for more than 1 year. Note that unemployment is measured at one point in
    time (with cross-section data). The unemployment rate does not distinguish someone
    just starting to look for work from someone who has been looking for work for a long
    time.


    However, the Labour Force Survey does ask people how long they have been looking,
    and we can use that information to construct alternative measures of unemployment.
    For example, some additional measure of unemployment measured by statistics
    Canada are:


             R1 unemployment rate for those unemployed one year or more
             R2 unemployment rate for those unemployed 3 months or more


             R5 Official Rate plus official discouraged workers


             R5 Official Rate plus official discouraged workers


             R7 official rate plus those working part time who say they want to work full
    time


    R4 is the official rate. R1 and R2 focus on groups for whom unemployment may
    represent particular economic hardship. Discouraged workers in R5 are measured in
    the labour force survey by identifying persons who want work, are available for work,
    but are not seeking work for ‘personal’ or ‘economic’ reasons.


    In 2004 (free access data is only available up to this year), the official unemployment
    rate including all 15 year olds and older not working but looking for work was 7.2%. R1
    was 0.7%, and R2 was 2.2%.R5 was 7.3%


    Most respondents are unemployed for less than 3 months (however, this may mask
    people who would work but feel they have no chance at finding a job so do not look for
    work). This is also deceiving because we do not yet know how long these people will
    be unemployed: the question only asks how long have you been unemployed SO FAR.
    (see below).


    Changes in these measures are highly correlated. This suggests that, while no one
    measure of unemployment can accurately describe the degree of economic hardship in
    the economy, changes or trends in the unemployment rate can adequately capture
    whether hardship is increasing or decreasing.


    You can easily look up these rates, for any year, for different age groups, by gender, by
    province at:
http://www.chass.utoronto.ca/datalib/codebooks/cstdli/cansim.htm
Click on E-stat
And make your way to CANSIM Table 282-0086
Or try using this url:
http://estat.statcan.ca/cgi-
win/CNSMCGI.EXE?regtkt=&C2Sub=&ARRAYID=2820086&C2DB=&VEC=&LANG=E&
SDDSLOC=http%3A%2F%2Fdissemination.statcan.ca%2Fenglish%2Fsdds%2F*.htm&
ROOTDIR=ESTAT%2F&RESULTTEMPLATE=ESTAT%2FCII_PICK&ARRAY_PICK=1
&SDDSID=&SDDSDESC=


Stocks and Flows of Unemployment and the Labour Market


Although net monthly changes in unemployment and employment tend to be relatively
small, so that the overall totals of the employed and unemployed are quite stable, these
net figurers mask the important fact that Canadian labour markets are very dynamic.
Even in stable economic times, there are large monthly flows into and out of
employment. For example, flows which roughly cancel in net terms but which in gross
terms amount to a high degree of labour market mobility.


The Labour Force Survey asks every surveyed individual questions on whether they are
in the labour force, whether they are working, no working, looking for work, and also
what they were doing the month before. Steve Jones from McMaster calculated the
average flows into and out of 1) Being not in the Labour Force, 2) Being Employed, and
3) Being Unemployed.
(The textbook on page 515 shows the same information).


E stands for employment, U employment and N not in the labour force.
EU stands for going from Employed to Unemployed in one month, etc…
PEU stands for the conditional probability of going from Employed to Unemployed
(conditional on being Employed) in one month, etc…


The most striking aspect of the economy-wide figures is the size of the flows, with about
200,000 individuals moving from any one state to any other in each month (over this
period). On a mean base on 11.1 million employed, this results in a monthly probability
of moving from employed to unemployed of 2 percent. On average, 20 percent of
people who are unemployed find employment in the next month.


Young are much more likely to be unemployed. Women are much more likely to leave
unemployment from leaving the labour force.


Somewhat more formally, we can show that if labour markets are roughly in balance,
with the flows into and out of unemployment and the labour force equal, the
unemployment rate for any group depends upon the various labour market flows in the
following manner:


                                  
UR F ( PEN , PNE , PUN , PNU , PEU , PUE )


In this equation,


F means “a function of”
PEN is the fraction of Employed who move to ‘Not in the Labour Force’ (who leave the

labour force).
PNE is the fraction of those not in the labour force who become employed

PUN is the fraction of unemployed who move to ‘Not in the Labour Force’ (who leave the

labour force).
Etc…


A plus sign over a variable in the equation means that an increase in that variable will
increase the unemployment rate, while a minus sign means that an increase in the
variable will decrease the unemployment rate.         You should think carefully why a
variable is listed here as a plus or a minus. The equation thus asserts, for example,
that, other things being equal, increases in the proportions of individuals who voluntarily
or involuntarily leave their jobs and become unemployed or leave the labour force will
increase a group’s unemployment rate.
The equation and an appreciation of labour market stocks and flows make clear that
social concern over any given level of unemployment should focus on both the
INCIDENCE of unemployment (the fraction of people in a group who become
unemployed) and the DURATION of unemployment.               Society is probably more
concerned if small groups of individuals are unemployed for long periods of time than if
many individuals rapidly pass through unemployment status.


When the proportions of people flowing in and out of each state are constant, the
unemployment rate can also be expressed exactly as the product of the average
incidence rate and average duration rate:


Unemployment rate = Average Incidence Rate * Average Duration Rate For example,
in this case of a steady state labour market, when 2 percent of people each month
become unemployed and the average duration spent unemployed is 5 months, the
unemployment rate will be 10%. To see this more clearly, if 5 percent of the population
each month become unemployed for only one month, in steady state, the
unemployment rate will be 5%. We can also go backwards: If the unemployment rate is
10% and 2 percent of the population each month become unemployed, then the
average duration rate, in steady state, must be 5 months.


Our data suggests that while many people do flow quickly through the unemployed
state, at any given time, a number of individuals experiencing prolonged spells of
unemployment characterize those found in the stock of the unemployed.


How do Labour Economists View Unemployment?: the distinction between
voluntary and involuntary unemployment


Think back to when we were studying the theory of labour supply. Individuals were
maximizing utility by choosing between how much to work and how much not to work,
given the wage offer. In a perfectly competitive labour market, what is the wage equal
    to? It is equal to a worker’s marginal product. Our theory predicts that any individual
    who is equally productive to a firm than another individual could offer to work for one
    penny less than the wage that other individual is working for. The two would get into a
    bidding war until the wage is lowered to a level that one of them prefers to look
    elsewhere, or not to work at all.


    So in a perfectly competitive labour market, unemployment is, for the most part,
    voluntary.


•                If there is always someone out there willing to pay 50 cents if you shine their
    shoes, can you ever be involuntarily unemployed?


•                Orley Ashenfelter’s view:


        “A worker is involuntarily unemployed if he or she has identical preferences and
    skills as other workers and yet is unable to find the number of hours work that others
    have both chosen and managed to find”.


    Ashenfelter, 1978. This is required reading and I’m going to put it up on the web page.
    You’ll like it.
      Involuntary unemployment

        Other workers with same                    You are offered w2 : your
        preferences and skills                     utility would be higher if
        offered w1                                 you were offered w 1




40w 1




                                           40w 2
        0        40                 0                                        0
                                                   0        40


Or, an individual accepts a job (e.g. paying w2) while there exists another job where
another equally productive worker is being paid w1. Although both are employed, one
worker is paid more than another.


Why is unemployment viewed as a social concern?


Outcomes unequal: some able to choose optimal leisure/consumption bundle, others
not


“Why don’t you accept the work available at lower wage rates?”


Response 1: “Why don’t all other similarly situated workers have to do the same?”
Response 2: I would work for a lower wage, but now employer seems to be willing to
lower the wage, even though I would do just as good of a job as the person currently
working.


These 2 responses portray the involuntary unemployed.


The big question here is why would these situations arise in the first place? Why would
some workers with the same skills be offered one wage, and others a different wage?
Why don’t employers lower the wage when similar workers are willing to work for less?




First, let me just say briefly, there is empirical evidence that wages DO differ across
industries and firms, in which similarly skilled individuals are paid different wages.


There is also empirical evidence that employers DO NOT tend to lower nominal wages.
The rate at which wages increase may differ over time, but very few firms actually lower
(nominal) wages.


Economists have thought about this long and hard to explain reasons for involuntary
unemployment. There are many theories. I will present three of the main theories here
(my favourites and probably the three most popular ones):


Efficiency Wages


Efficiency wage theory focuses on the effect that wages have on incentives, motivation,
and worker productivity. Suppose, for example, I hire one of you for $20 an hour to
enter data in for me. I don’t really know how hard you’re working, because I cannot look
over your shoulder to see how fast you’re typing.       But $20 is a pretty good rate, and
you may feel happy with that – happy enough that you are willing to work at a good
pace because if I ever thought you were slacking off, you would be out of a good paying
job. But now suppose another one of you comes up to me and says you’d be willing to
work for $10 an hour. That would save me a lot of money if you work as hard as the
other guy. But at $10, you have less at stake if I catch you slacking off. At $10 you
may work less.        So I may be willing to pay someone $20 an hour as a way of
encouraging effort, even though other people are willing to work for less but I will not
hire them (and so they are involuntarily unemployed).


Let’s look at this more formally.


A firm is trying to choose how much labour to hire to maximize profits. The production
function that determines how much output, Q is produced, is a function of labour hired
(L)     and     the       amount   of   effort   labour   puts   into   their   work   (e):


Q F (eL )


Now, before, the production function was just a function of how much labour is hired.
The wage paid to workers only affected the cost of hiring. But support the wage you
offer also affects the level of effort each worker decides to commit. So effort is a
function of the wage:


e  (w)
   e


Profit for the firm is:


      profit F ( eL) wL
(1)
      profit F ( e( w) L) wL


Before, the firm would just choose how much labour to hire, given the wage. The wage
was taken as given because, in a perfectly competitive labour market, firms would offer
the lowest wage possible and workers would accept the highest wage possible and the
equilibrium wage was what the amount that reflected the worker’s marginal product: if
profit is G ( L)  , and the equilibrium wage is w  ' ( L) .
                  wL                                G
Now, a firm has to take into account the impact of the wage on effort, and its
implications for profit.   A firm may want to offer a higher wage.       The first order
conditions from equation (1) above are:


eF ' (eL)  
           w 0


e ' ( w) LF ' (eL)  0
                    L


We can rearrange these two equations to imply that:


w    e 1
  
L e' ( w) L


or


w
     e' ( w) 1
e


So, when profits are maximized, the elasticity of effort with respect to the wage, should
be one. The intuition (as discussed more in the text) is straightforward. An increase in
the wage by 1 percent will increase labour costs by 1 percent, no matter what happens
to output.


So the firm should increase the wage as long as the gain from extra effort per worker is
greater than the extra cost per worker. At some point, the extra cost is not worth it.
This occurs when the condition above holds.


Some economists believe the persistence of unemployment is the result from the
widespread payment of above-market wages. Further, persistently different wage rates
paid to quanlitatively similar workers in different industries are the hypothesized result of
efficiency wage considerations.


One of the most important implications of efficiency wages relates to their effects on
productivity. Those firms that raise wages above what other firms are willing to pay for
similar workers should be the ones that 1) stand to gain the most from enhancing
worker reliability, or 2) find it most difficult to properly motivate their workers through
output based pay or supervision.


Social Norms on the Worker Side


Even if some firms pay higher than market wages, why can’t individuals who would like
to work for these better paying firms not settle for jobs at other paying firms that pay
only market wages (where wages can adjust)?           Some economists believe that the
failure of unemployed workers to flock to low-wage jobs derives from their sense of
status (their relative standing in society). Individuals may prefer unemployment in a
good job to employment in an inferior one, at least for a while. This is not involuntary
unemployment.


Social Norms on the Worker Side


Unemployed workers may not be able to undercut wages of employed (bid the wage
down). Worker moral and motivation of existing workers when the wage is reduced
would drop dramatically. The disruption cost of having to encourage motivation, or hire
new workers at a lower wage is too high to be willing to lower wages.                 Some
economists have suggested that inflation helps ‘grease the wheels’ of the economy by
allowing for real wage decreases even though firms are reluctant to lower nominal
wages. Thus, inflation may actually help reduce unemployment not because of the
traditional Phillips Curve relationship (through an increase in money demand) but
because it gives firms more flexibility to lower real wages.
    Job Search


    Search models relax the assumption that workers always know wages offered at all
    other firms.   Frictional unemployment is when jobs are available and unemployed
    individuals want them, but a match hasn’t occurred yet. Finding a job involves search.


    Allowing for the more realistic assumption that it takes time for workers to find a job and
    for firms to find someone who wants to work alters the perfectly competitive model in
    dramatic ways.




    Set-up of Search Model:


    Workers:


•              Many workers, equally productive


•              New job offers come about to both unemployed and employed workers at a
    constant rate (e.g. every 2 months)


•              A worker accepts another job if the wage offer from the new one is above her
    current wage and stays otherwise


    Firms:


•              Many firms that want to maximize profits


•              all workers in the firm are paid the same wage


•              In this set-up where it takes time for workers to find another job, firm can
    change it’s wage without losing all workers
•             An unemployed individual accepts a job if the wage offer is above her
    reservation wage


    Why is perfectly competitive wage not the equilibrium wage for all firms in this model?


•             With all firms charging competitive wage and making zero profit, one firm
    could lower its wage


•             Workers currently at that firm will move if they get another offer, but this takes
    time


•             Unemployed workers receiving an offer at this firm but not at another firm will
    prefer to work there if wage above reservation w.


•             This firm then can make a profit!


    If one firm can make a profit, the other firms will want to as well. What can they do?


•             Firms face a trade-off:


•             The lower the wage offered, the bigger the difference between productivity
    and wage paid, but the higher the quit rate


•             What is the highest wage offered? The lowest?


    In equilibrium, all firms making same profit, but charging different wages


    Distribution of workers by wages paid by firm
                                                                     P = VMP
    Reservation
    wage



                                                                       w
                    r                                            p



    Note how a slight change in assumptions leads to very different result


•             Firms offer different wages to workers of equal productivity


•             Because workers take time to find alternative jobs, firms can pay less than a
    worker’s marginal product, make a profit, and retain the worker until that worker finds a
    firm willing to pay them more.


•             The distribution of wages varies between the reservation wage and the
    perfectly competitive wage (w = VMP)


•             As the rate of obtaining a new offer gets smaller and smaller, the equilibrium
    approaches the competitive one (once all firms offering a job at the same time to
    workers, firm profit goes to zero)


    Summary of Search Model


•             With market friction, workers must search employers for a job and don’t get
    offers from everyone at once


•             This causes workers to stay at a firm while searching for a job that pays a
    higher wage
•             Each employer chooses a wage given this search behavior


•             The labour force available to an employer is constantly changing


•             Trade-off between offering a higher wage and having a more stable labour
    force (fewer quits) and lower profit


    Some Important Implications of the Search Model


•             Good jobs and bad jobs out there (for similar workers)
    Otherwise identical individuals will wind up receiving different wages. Two unemployed
    individuals with the same skill level could choose the same reservation wage and have
    the expected post-unemployment wage. However, the wages they actually wind up
    with will depend upon pure luck.


•             Because workers only switch firms for higher wages, the longer workers are
    employed the more likely they are at a higher paying firm


•             There may be ways of jumping the que (connections)


•             Discrimination may lead to certain groups more likely to end up in lower
    paying jobs


    If the cost to an individual being unemployed were to fall, the person should be led to
    increase his or her reservation wage (that is, the person would become more choosy
    about the offers deemed to be acceptable). A higher reservation wage, of course, would
    increase both the expected duration of unemployment and the expected post-
    unemployment wage. One important influence on the cost of being unemployed, and
    hence on the reservation wages of unemployed workers is the presence and generosity
    of governmental unemployment insurance programs.
    Unemployment and Search


•               To switch jobs, workers must ‘search’ by definition: those not working do not
    find jobs immediately.


•               Costs to switching jobs may lead to unemployed waiting longer before
    accepting offer (trying to find best job)




    Two predictions of the search model, in contrast to the perfectly competitive model of
    the labour market.


    1) You are displaced (lose your job from a firm going bankrupt or having to layoff
    workers because of slower demand for its product). What are the long-run (say, 5 or 10
    years out) implications to your wages under the perfectly competitive model? Under the
    search model?


    In the search model, workers are moving from one job (or firm) to the next in search of a
    higher paying wage. Workers that lose their high paying job must start over, searching
    while unemployed and willing to work at any firm that offers higher than the reservation
    wage. If you had a top paying job (compared to other similar workers) and were laid off
    because of bad luck, you may experience prolonged lower wages than if you were not
    laid off.


    Let’s look at the evidence.


    Jacobson Lalonde, and Sullivan (AER 93) exploit employer-employee data to examine
    the wage dynamics from unexpected job loss. The Burdett-Moretensen model predicts
    job loss lower wages for those that lose their jobs, as they end up trying to climb the
wage ladder again from the bottom. In a perfectly competitive setting, workers should
be able to obtain similar paying jobs at other firms, and we shouldn’t observe a long run
impact. There are other reasons to expect a prolonged impact from job loss, especially
in the presence of specific firm capital. But the analysis is informative in that mild and
temporary impact from job loss shocks would be evidence against the Burdett-
Moretensen model.


JLS have quarterly data over 15 years from government administrative records in
Pennsylvania.


Sample is: workers at same firm for 6 years between 1974-80.


‘Treated’ Group: workers that left firm in quarter where at least 30% of firm’s labor force
left (e.g. mass layoff or firm closure). This is an attempt to identify exogenous job loss.


‘Control’ Group: The rest of the sample
•              In recession, more individuals searching (e.g. from lower output demand)


•              This may lead to longer search times and makes individuals more likely to
    ‘settle’ for lower paid jobs




    Could there be long-run effects from graduating during a recession or boom?


•              In a competitive market, shouldn’t matter


•              Initial conditions (e.g. lower labour demand) may increase search time and
    lower initial reservation wage


•              But once recession over, should ‘bounce-back’


•              Workers with equal productivity should be paid same


    Possible reasons why graduating in recession might matter


•              Jobs harder to get during recessions may offer more opportunities for human
    capital accumulation – productivity grows faster


•              Jobs harder to get during recessions may make search for higher paying jobs
    easier


•              Firms may use initial job as ‘signal’ for a workers’ productivity (stigma model)
    Let’s                 look                 at                 the                 data
    what happens, on average, when university students graduate during a recession?


•             University Student Information System (USIS) tracks university enrollment
    status and graduate status for universities in Canada (1976 – 2000)


•             USIS data matched to administrative records tracking earnings data from
    1982 - 2000


    Data matched to youth unemployment rate conditions by province




    Regression Set-up:
                   
log w p ,c,exp  p  c  exp  exp unemp _ 1524 p ,c
              
              unemp _ current p ,c,exp  p ,c,exp
                                         e


log w p ,c,exp average log wages for workers from province p
             grad. year c, and with years since grad. exp

unemp _ 1524 p ,c youth unemployment rate at time of
                    graduating, g, from prov. p,


unemp _ current p ,c ,exp current unemployment rate
                         (set to zero when exp 0)
The Effects of Unemployment Insurance Benefits


Virtually every advanced economy offers its workers who have lost jobs some form of
unemployment compensation, although these systems vary widely in their structure and
generosity. In Canada, the system is operated by the federal government and, since
1996, has been called Employment Insurance instead of Unemployment Insurance. In
contrast, in the United States the unemployment insurance system is actually
composed of individual state systems.


You can go up on Human Resource and Development Canada (HRDC)’s website and
discover how it works: To qualify for EI, generally you must have worked about 12 to 20
consecutive weeks in the same job, which translates to roughly 12 to 20 weeks at 35
hours per week. Someone on EI can receive transfers from ranging from 14 to 45
weeks, depending on the unemployment rate in the region: if the unemployment is high,
you are eligible for EI for longer. The basic payment is 55% of your previous earnings,
although this amount is capped at $413 per week ($21,476).              So if you have an
annualized salary more than about $40,000, you will get less than 55%.


The way it works is when an individual is laid off or dismissed, he obtains a copy of the
Record of Employment (ROE) which shows evidence of the length of time working, and
the reason that the individual left the firm.       With this, the individual fills out the
application, including SIN, bank information, details of dismissal, and salary, and sends
it off to HRDC. If everything is in order, HRDC starts sending checks within about a
month.


You can’t just go on EI if you stop work. You have to convince HRDC that you were laid
off or dismissed. If you voluntarily quit or you are fired, generally you are not eligible for
EI. Also, while on EI, if you do find work, you’re supposed to let HRDC know, otherwise
they might send you a check you’re not supposed to have. Payments generally stop
after the number of weeks you’re eligible for. If you still haven’t found a job by then,
you’re in trouble, because welfare might be the only remaining option for non-labor
income.
                                 We can go through the effects of EI using our
                                 standard labor supply model. Suppose the
                                 wage rate is $500 per week. Suppose EI pays
                                 out 55% of annualized earning, so that’s $275
                                 per week. To qualify for the program, an
                                 individual must work at least 10 weeks, and
                                 wait for 2 weeks. This was a similar set up to
                                 the UI program before 1994.

                                 Assume an individual can receive UI for up to
                                 40 weeks. In analyzing EI over just 52 weeks,
                                 for every hour worked more than 10, that’s one
                                 less hour available to be on EI. This is a
                                 awkward assumption that the textbook makes
                                 also. It does work well for seasonal workers
                                 that have steady employment for at least part
                                 of the year. But in general, perhaps a more
                                 realistic assumption is to assume the benefit
                                 amount (annualized), stays the same.

                                 Note that in this graphical analysis, we set it up
                                 as though an individual automatically qualifies
                                 for EI if they work more than 10 weeks. This is
                                 not a realistic assumption. Also note this initial
                                 analysis ignores the fact that EI is paid for may
                                 employer and employee contributions. The
                                 textbook generally does not discuss how
                                 contributions alter this discussion, but we will
                                 look at that in just a bit.

An individual maximizes utility by choosing the number of weeks to work. After
working 10 weeks, and waiting 2 weeks, an individual is eligible to receive EI.
The wage rate is 500. For every hour worked after 10, the individual gives up 1
hour of unemployment at .55(500) = 275 per hour.

For someone working, what do you suppose this program will do to labor supply?
The way we’ve specified the program here, the
implicit wage after introducing the EI program is
lower than before for those already working
more than 10 hours. So what direction is the
substitution effect? It leads to decreasing the
number of weeks worked because the relative
price of leisure has fallen. What about the
income effect for those already working more
than 10 hours? EI provides more income, and
so the income effect is to reduce work if leisure
is a normal good. Thus, BOTH the income and
substitution effects lead to reducing work
among those already working. Here is an
example where we can predict the response in
labor supply from a change in the budget
constraint, but note that this is only because of
our assumption that the individual is limited to
looking at just these 52 weeks.

For someone not working, the EI program could
actually increase the number of hours worked.
The logic is simple: someone not working would
be able to receive a lot more income if they just
work 10 hour more, because not only do they
gain from the additional income, they also then
qualify for EI. But this need not be the case for
everyone. We could easily draw the
indifference curves for individuals not working
still being better off not working after the
program.

This analysis supposes the individual
automatically qualifies for EI if they stop
working which, of course, is incorrect, unless an
individual is able to co-ordinate the reason for
dismissal with the employer. One reason for
lowering the limit of EI in 1994 was that many
seasonal workers (e.g. fisherman, tree planters,
…) were using EI to prop up their salaries while
not really looking for work in between periods.
But most people are able to receive UI only if
they lose their job from unpredictable reasons.
EI can’t make anyone worse off unless we take
into the costs of the program because the same
budget constraint as before is available, plus
more if the new portion of the budget constraint,
that requires going on EI, is considered.
In ECO200 you examined how insurance can make
risk averse individuals better off because a loss in
income generates a larger fall in utility relative to
the gain from the same increase in income. EI is
like other insurance plans, except everyone must
participate in EI when they work, whether they are
better or worse off from doing so. Let’s compare
the gain or loss in EXPECTED utility from the
program for a particular individual. Suppose the
probability of Katie losing her job is 2% over a 52
week period. If Katie loses her job, she is paid
$6,425 for that year. I’m keeping things simple
here by assuming a lump sum payment that does
not depend on how much Katie works, and that
Katie either works or loses her job for the whole
year. Katie’s utility is C*L, and her wage rate if 500
per week, so her budget constraint is C+500L =
500*52. Assume she has no control over whether
she loses her job. Things would be way more
complicated if how much she worked before losing
her job affected ho much her income is when she
loses her job.

Without EI, Katie maximizes her utility when MRS =
w. This is when C*=13,000 and L*=26. Her utility
at these points is 338000. But note, what is Katie’s
utility if she loses her job? 0, because she would
have no income to consume. So her expected
utility is 331,240.



   With EI, Katies faces a different budget
   constraint. Because EI contributions are 10%,
   her real take home wage is $450 per week, not
   $500. Going through the same maximization
   problem under this new constraint, Katie’s utility
   if she doesn’t lose her job is now lonely
   $304,200, but her utility if she does lose her job
   is much higher (than 0), because EI pays her
   $6435, plus she doesn’t work that year, so her
   utility would actually be higher than if she
   worked.

   But since her chances of losing her job are very
   small, Katie’s expected utility is 304,808, lower
   than that if she wasn’t participating in EI.
Individual’s can expect to gain from EI if their
expected utility under the program is higher
than the expected utility without it. Notice I say
‘expect to gain’. If I’m, on average, better off
without EI, but chances have it I lose my job, I
could turn out to be much worse off without the
program.

What are some things that will make me more
likely to prefer the program?




In general the higher the probability of losing
one’s job, the higher the expected gain from
UI. This creates incentives to ‘manipulate’ that
probability, especially if there are few costs
with working again. Of course, the lower the
payout while unemployed, the lower the
expected gain from the program, and the
greater the contribution, the lower the gain.


Once the program is set up, even if an
individual’s expected utility is lower under the
program, say because his probability of losing
their job is low, he still has an incentive to try
and receive EI. Suppose this individual has a
zero percent chance of losing their job. He is
worse off because the contribution rates lower
how much leisure and consumption he can
purchase. Note that if he did lose his job, he
would be worse off without the program. If he
could choose how much of EI to collect (how
much not to work), He would work less: the
way I’ve drawn the new budget constraint, the
substitution effect will lead to less work
because the wage rate, with contributions, has
gone down.
                                  An insurance program is actuarially fair if the
                                  total expected payout equals the total
                                  expected revenues of the program. Under an
                                  actuarially fair program, if the probabilities of
                                  losing a job are different for the population,
                                  but the contribution rates are generally the
                                  same, then the program will end up
                                  transferring resources from those with lower
                                  probability of losing their job to those with
                                  high probability. This is how our EI system
                                  works, because, in many cases, workers’
                                  contributions are not equal to their expected
                                  payment (some are higher, some are lower).
                                  If I had a choice to opt out of EI, I probably
                                  would, even though, if I did lose my job, I’d
                                be worse off than before. If the government
                                allowed it, I could probably find an insurance
                                company who is willing to insure me for loss of
                                job for a lot less than 6% of my pay.

                                It’s also interesting to note that the EI program
                                is not even actuarially fair: the government
                                receives more revenues from the program
                                each year than it receives. Those revenues
                                are used for other things (like paying down the
                                debt, or supporting other programs, or keeping
                                taxes low). Thus, when the size of
                                contributions are taken into account, we realize
                                that a large part of the EI program is a
                                redistribution program – not everyone gains
                                                from it, plus it creates incentives
                                                for people to ‘maniuplate’
                                                unemployment. That said, for
                                                those that do unpredictably lose
                                                their job, it’s helps a lot.

What does the job search model predict from increasing unemployment insurance
benefits? Why?
Empirical Evidence on the effects of Unemployment Insurance and incentives to
encourage employment.


Between 1984 and 1985 the state of Illinois conducted a claimant bonus experiment to
test whether providing cash bonuses to unemployment insurance recipients who found
a new job ‘quickly’ would be an effective way to reduce their durations of unemployment
without affecting their post unemployment wages. The idea was that the promise of a
cash bonus for rapid reemployment would cause UI recipients to increase the fraction of
time they spent searching for work.


UI recipients in the experiment were randomly assigned to two groups. The first served
as a control group and received regular benefits. Members of the second group were
promised an additional cash bonus of $500 if they found a full-time job within 11 weeks
and held that job for at least 4 months Given that individuals were randomly assigned to
the two groups, one would expect the two groups to exhibit, on average, roughly
equivalent durations of unemployment and post-unemployment wages in the absence
of any ‘bonus effect’.


The incentive created by the $500 bonus, which was actually paid to only 570 out of
4,186 UI claimants assigned to the experiment, reduced state regular benefits paid to
the randomly selected treatment group by an average of $158, and reduced average
weeks of insured unemployment by more than one week (over the full benefit year),
compared with the randomly selected control group.        These reductions in average
benefit payments and weeks of unemployment were achieved over all 4186 eligible
claimants whether or not they agreed to participate or acted on the incentive.


If the take-up rate in the claimant experiment had been 100 percent, and UI benefit
reductions had remained unchanged, then the benefit cost ratio of the experiment would
have fallen to 1.26 from 2.32. Thus, even with a 100 percent take-up rate, the claimant
experiment would have reduced UI benefit costs by considerably more than the bonus
costs incurred. Would take-up rates change in an actual program, and if so, how?
Earnings of members of the treatment groups after they became reemployed did not
differ from the control. Perhaps the introduction of the program would lead to many
more claiming unemployment insurance to begin with just so they can qualify for the
$500 bonus.
Canada’s Earnings Supplement Project (ESP)

The funding of the Social Research and Demonstration Corporation’s Earnings
Supplement Project (ESP) by HRSDC is another important development in EI’s
evaluation framework. This project began as a demonstration project to test the
effectiveness of a financial incentive in encouraging re-employment among unemployed
workers. Between March 1995 and June 1996 ESP enrolled over 11,000 claimants from
nine local offices across Canada in a randomized trial. Half of the claimants who
volunteered for this project were randomly assigned to the program group and offered
the financial incentive, and half were assigned to the control group and thus not offered
the incentive. ESP participants applying for regular benefits could receive an earnings
supplement if, within a specific period of time, they took a new full-time job that paid
less than the job from which they had been laid off. ESP would then make up 75 per
cent of the earnings loss for up to two years. The earnings supplement was offered to
two separate groups of claimants. The first was a group of 8,144 “displaced workers”
(claimants who had been working continuously for at least three years before becoming
unemployed and who did not expect to be recalled to the job they had lost). The second
group consisted of 3,414 “frequent claimants” (claimants who were applying for benefits
for at least their fourth consecutive year). The displaced workers were given 26 weeks
to find new full-time jobs while frequent claimants were given only 12 weeks to find new
jobs. The offer of the earnings supplement was found to have a small and short-lived
impact on the re-employment of displaced workers. Those in the program group were
four per cent more likely to be re-employed during the first six months after random
assignment compared with those in the control group, but all differences in the
employment of program and control group members had disappeared by the 11th
month. The results for frequent claimants were even more disappointing: fewer than half
of eligible frequent claimants were willing to volunteer for the project, and only five per
cent of those who volunteered and were assigned to the program group received a
supplement payment.


Policy Framework

Worker displacement is a natural feature of flexible labor markets. Changing
technologies, competition, and shifting demand all have the potential to push people
out of long-term, continuous, and even well-paying jobs. While unemployment
insurance enables such people to hold out for an attractive new employment
opportunity, it may also prolong their joblessness by reducing the urgency of finding
work. Canada’s Earnings Supplement Project (ESP) was designed to encourage
rapid reemployment by offering financial incentives to displaced workers. Sponsored
by the Canadian government, the demonstration was managed by the Social
Research and Demonstration Corporation (SRDC) and evaluated in a random
assignment study by MDRC in collaboration with SRDC.

Agenda, Scope, and Goals
    Two primary benefits, each of which could last as long as two years, characterized
    ESP’s offer to unemployment benefit claimants who found a full-time job within 26
    weeks:

             If the new job paid less than the old one, ESP enrollees received an
    earnings supplement equal to 75 percent of the difference between the two wages,
    up to a maximum of $250 per month.



            Earnings insurance        protected   ESP   enrollees   against   a   future
    reemployment earnings loss.

    By designing its incentives in this way, the Canadian government sought to avoid the
    largely disappointing results of earlier programs piloted in the U.S. that offered a
    lump sum bonus to displaced workers who became reemployed quickly.

    ESP’s goals were threefold:

             to compensate displaced workers for job loss associated with economic
    growth that benefits society as a whole



            to provide displaced workers with a source of temporary financial support
    that promotes rapid reemployment without lowering their earnings or increasing the
    unemployment rolls

to reduce unemployment insurance costs

    Design, Sites, and Data Sources

    About 8,000 displaced workers entered the ESP study over a one-year period from
    1995 to 1996. Half were randomly assigned to the supplement group, making them
    eligible for the earnings supplement or the earnings insurance if they found full-time
    work within 26 weeks. The other half were randomly assigned to the control group,
    making them ineligible for the supplement and earnings insurance but eligible for
    standard unemployment benefits. ESP’s effects on labor market reentry and other
    outcomes were estimated by tracking and comparing the two groups’ experiences over
    a                                  15-month                                   period.

    The demonstration sites were chosen to reflect a mix of labor market types and
    geographic areas. The sample — composed of Granby, Quebec; Oshawa, Ontario;
    Saskatoon, Saskatchewan; Toronto, Ontario; and Winnipeg, Manitoba — was therefore
    diverse but not fully representative of the Canadian labor market.

				
DOCUMENT INFO
Shared By:
Categories:
Tags:
Stats:
views:47
posted:8/9/2011
language:English
pages:40