8/12/2019 Does Fairness Prevent Market Clearing http://slidepdf.com/reader/full/does-fairness-prevent-market-clearing 1/16 Does Fairness Prevent Market Clearing? : An Experimental Investigation By Fehr, Kirchsteiger and Riedl (1993) Presented By Preetha Rajan Econ 776 Experimental Economics
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The experiment consisted of two stagesconstituting one period. Twelve periods in eachsession. Four sessions in total.
Before each session, all subjects picked a card – card with S - worker, card with B - employer.
First stage was a one sided oral auction withemployers as bidders, making wage proposals
with no opportunity to choose the worker withwhom they traded, since every worker couldaccept every offer. Stage one ended if the workeraccepted an offered wage p, concluding a binding
Continued Monetary effort costs for workers – given by
increasing function m=m(e), m(emin)=0
emin is the minimum effort level with zero effortcosts. The m(e) schedule is the same for allworkers.
u j = p j-c-m(e j) is the total monetary pay-off ofworker j with wage p j, effort level e j andmonetary cost of providing one unit of labourtime c
πi = (υ-pi)ei is the payoff of employer i whoseworker chose effort ei. The expression υei is suchthat one unit of effort produces υ units of outputwhich is sold for a price of one.
Hypothesis one: Effort level is increasing in thewage.
Hypothesis one is tested by fitting a regressione= α + β.p +μ – hypothesis not rejected if β is greater
than zero To account for behavioural differences among
workers with regard to the fairness notion, dummyvariables di are used for workers to run the followingregression : e= Σγidi + βp + μ - Wald statistic is usedto test the null hypothesis (pertaining to testing thesignificance of behavioural differences of workers)that all estimated γi are equal to the estimated α co-efficient
Period Dummy variables pt added to account forthe possibility that effort varies systematicallyacross periods – takes a value 1 if relevant
observation made in period t and value zero ifotherwise. The following regression equation isrun - e= Σθtpt + βp + μ – Wald statistic is used totest the null hypothesis that all θt are equal to the
estimated α co-efficient Hypothesis two states that the average wages in
the experiment are considerably greater than themarket clearing wage