Contract Enforcement, Social Efficiency, and Distribution:

Some Experimental Evidence1

Steven Wu and Brian Roe2

The Ohio State University AED Economics

Agricultural Administration Building 2120 Fyffe Road

Columbus, OH 43210-1067

Contact: wu.412@osu.edu (614)247-7494

Fax: (614)292-4749

This version: August 15, 2005

NOTE: THIS IS A PRELIMINARY VERSION. ADDITIONAL REVISIONS ARE FORTHCOMING

Copyright 2005 by Steven Wu and Brian Roe. All rights reserved. Readers may make verbatim copies of this document for non-commercial purposes by any means, provided that this copyright notice appears on all such copies.

1 We gratefully acknowledge funding from the USDA/NRICGP program for Markets and Trade or Rural Development, Award no. 2003-35400-12887 and the Ohio Agricultural Research and Development Center Research Enhancement Competitive Grants Program, no. 2005-084. The authors would like to thank Martin Brown, Armin Falk, and Ernst Fehr for supplying us with detailed information concerning their experiments and associated Z-Tree programming which facilitated implementation of our experiments. Myoungki Lee, Yun Jae Hwang, and Mike Brady provided excellent research assistance. 2 The authors are Assistant Professor and Associate Professor, respectively.

Contract Enforcement, Social Efficiency, and Distribution:

Some Experimental Evidence

Abstract

We use economic experiments to investigate how different contract enforcement regimes

affect efficiency and the distribution of surplus in vertically coordinated markets where

contractors have market power. We find that if a third party (e.g. government) provides

full enforcement of contracts, social efficiency is enhanced. Surprisingly, we find when

enforcement is completely absent, social efficiency will not necessarily decrease because

trading partners find ways to self enforce contracts. However, opportunistic behavior by

some traders widens the distribution of surplus generated and leaves some sellers

(growers) with ex-post profits below reservation levels. Finally, partial or one-sided

enforcement causes significant efficiency losses by constraining the ability of the

regulated party to self enforce contracts.

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Recent controversies surrounding contract production in the poultry industry have raised

concerns among policy makers that vertically coordinated industries might favor large

agribusiness at the expense of growers. Among the issues that have received increased

attention include the apparent lack of bargaining power possessed by growers when

negotiating and performing under contracts, and the lack of transparency concerning how

performance and payments are determined (Pierce and Stewart). As an example of the

latter, Schrader and Wilson analyze data from a survey of broiler growers and suggest

that many growers were concerned about the quality of inputs they received from

contractors and the timeliness and accuracy of bird weighing. Because both input quality

and the accuracy of weighing can affect performance outcomes, which in turn, determine

compensation, there might be a lack of transparency in the determination of pay. 3 Along

similar lines, Hamilton points out that many broiler contracts contain a provision that

allows a contractor to unilaterally change payment methods or pay rates, which provides

integrators with the option of making discretionary ex post adjustments in pay.

While the lack of transparency can make third-party enforcement costly, the

problem is exacerbated by the Secretary of Agriculture’s limited power to enforce the

Packers and Stockyard Act of 19214. While the Secretary may investigate alleged

violations of the Act, the Secretary has only limited power to bring administrative action

to resolve many violations of the Act; in fact, in the poultry industry, the Secretary only

has authority to bring administration action for problems related to payment (Farmer’s

3 Some states have sought to improve transparency of performance measures. For example, Georgia passed HB 648 on April 7, 2004. This bill requires processors to provide “any statistical information and data used to determine compensation paid” at a grower’s request. The bill also allows growers to be present when their birds are being weighed after growout and when feed is being weighed prior to delivery. 4 This act is meant to ensure free competition and fair trade practices in livestock and poultry markets. USDA-GIPSA is responsible for enforcing the Packers and Stockyards Act.

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Legal Action Group, Inc.). As such, many contract terms between growers and

processors are unenforceable by a third party, which can lead to contracting distortions.

This means contracts are rendered “incomplete” by the lack of third-party enforcement.

While concentration and enforcement problems appear to be key issues

for policy makers, there have been few efforts to clarify the consequences of increased or

relaxed contractual enforcement on efficiency and distribution. Because the economic

theory of contracts, as well as a theory of contract regulation, are still evolving areas of

scholarship (Schwartz), agricultural economists do not understand the workings of

contractually linked industries in the same way that they understand the functioning of

commodity markets. Textbook principal-agent models are inadequate for studying

enforcement problems because an underlying assumption of these models is that

institutions for third party enforcement exist and function perfectly. When contracts are

complete, as in the standard principal-agent model, there is little justification for

government intervention because such intervention will constrain allowable activity and,

hence, efficiency. Thus, most law and economics scholars focus on regulation of

incomplete contracts or contracts that have unenforceable components. However, the

theory of incomplete contracts has its own conceptual difficulties (Tirole; Maskin).

Hence, it has been difficult for economists to study these issues in a unified and logically

consistent microeconomic framework. In recent years, however, advances in the theory

of relational contracts (Levin; Malcomson and Macleod), which accommodates

unenforceable components in contracts, provides a promising framework that is relatively

free of conceptual difficulties for studying agricultural contracting relationships.

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Apart from theoretical issues, there has been a paucity of data for studying policy

issues in vertically coordinated industries. This is partly due to the difficulty of acquiring

data from firms, who often treat data as proprietary. Additionally, even when data is

available, it may not contain sufficient detail for conducting credible empirical analysis.

Wu points out that most contracting relationships tend to be very situation specific and

contracts are often “customized” to fit the economic realities of specific trading partners.

Moreover, explicit terms in contracts are often buttressed by numerous unwritten rules,

implicit incentives, and tacit expectations so that it is difficult find observational data that

captures every important aspect of the contracting environment. Finally, there is a lack of

historic precedent for many of the contracting issues that have emerged recently in U.S.

agriculture. Thus, there is little data available for assessing the impact of alternative

enforcement regimes on efficiency and distribution of gains from trade.

Given the paucity of theoretical and empirical research, it is not surprising that

economists and policy makers hold numerous opinions about how government

regulations of contracts would affect efficiency and distribution of rents in vertically

coordinated industries. Some economists suggest that too much regulation may have

unintended consequences that, for example, may cause livestock industries to relocate out

of states in which regulations are binding (e.g. Boehlje, et. al.). Others suggest that

regulations and enforcement are necessary to enhance both fairness and competitiveness

in contract agriculture which is becoming more concentrated and one-sided in favor of

large agribusinesses (Harl, Et al.; Taylor).

This study uses experimental economics to investigate the effects of alternative

enforcement regimes on contractually based markets where buyers have market power.

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An experimental approach allows us to control the trading environment and create

exogenous variation in third-party enforcement, which allows the researcher to isolate

and estimate causal relationships. We view this study as an initial step in understanding

the microeconomic forces that shape behavioral and trading patterns in a contractually-

based economy where buyers have bargaining power, and different levels of contractual

enforcement are available. Moreover, we motivate our experimental design using the

theory of relational contracting, which, we believe, is a coherent framework for

conceptualizing contractual relationships between trading parties and is representative of

the emerging business relationships that dominate vertical relationships in modern

agricultural markets. The insights generated in this study might inform policy makers

about how more rigorous enforcement of contracts by government agencies can impact

contractual efficiency and the distribution of rents across parties.

Noussair and Plott argue that experiments need not replicate field situations and

all institutional details to retain relevance for policy analysis. Instead, experiments are

valuable in that they allow economists to examine general theories that should apply

more broadly. If a theory does not apply in simple, controlled environments, one must

question whether the theory is appropriate for explaining behavior or predicting

responses in more complex environments. Moreover, abstracting from reality is not

unique to experiments; indeed, most economic studies base conclusions on models with

simplifying assumptions and abstractions.

The use of experiments to study relational contracting is even more critical than in

other areas of microeconomics. Because relational contracts are based on the notion of a

repeated game, there are typically many equilibria so that unique theoretical predictions

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are generally not forthcoming (Brown, Falk and Fehr). Thus, conducting empirical

studies in a controlled environment free of confounding factors can illuminate our

understanding of relational contracts.

One primary finding, which is fully consistent with intuition, is that full

enforcement of contracts promotes social efficiency. More surprising is that a regime

devoid of formal enforcement can generate comparable social efficiency. In such

regimes, many subjects use contractual renewal and discretionary adjustments in contract

terms to provide informal enforcement that is nearly perfectively substitutable with

formal enforcement in terms of achieving high levels of social welfare. However, a

negative side effect of informal enforcement is that it often exposes sellers (e.g. growers)

to opportunistic behavior – nearly one in five sellers make ex-post profits that fall below

reservation payoffs. Such opportunism does not occur under full enforcement. Another

surprising result is that one-sided formal enforcement (buyers’ obligations only)

constrains subjects’ ability to use informal enforcement, which results in significant

efficiency losses, but elevated average earnings of sellers.

One might question whether the use of students rather than farmers weakens our

results. We regard the use of students as a strength because growers’ attitudes toward

contracting issues may be politicized by recent discussions about the “oppressive” nature

of contracts. Most university students are less familiar with these political entanglements

and may therefore respond in a more neutral manner.

Experimental Design

Our experimental design captures several important features of agricultural contracting

relationships. First, it captures the idea that buyers (e.g. processors) have market power,

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i.e., there are fewer buyers than sellers (growers), so that not all sellers who want

contracts get them. Second performance, generically referred to as “quality,” is

unenforceable by a third party due to transparency problems. Third, buyers can make

discretionary ex-post adjustments in compensation. Fourth, parties can track the

reputations of past trading partners and have discretion to renew or dissolve existing

business relationships based on past performance. Each feature is present in an

experimental economy based on the design of Brown, Falk, and Fehr (BFF).

In the experiment subjects are partitioned into two groups: buyers and sellers. All

trading takes place on networked computers enclosed in cubicles to eliminate between-

subject visual contact. Moreover, anonymity is preserved by assigning all buyers and

sellers numeric ID numbers. We partition each experiment into two trading sessions.

Each trading session features a unique contract enforcement regime described below.

Each session has 17 trading rounds – two practice rounds and 15 ‘live’ rounds that may

determine eventual cash payment. ID numbers are fixed across rounds, which allows

buyers and sellers to establish long-term relationships by trading with the same partner

over multiple rounds, and changed between sessions, so that there is no reputational

carryover between contracting regimes.

Within each trading round, buyers offer “contracts” to sellers specifying a price-

quality combination for a unit of an abstract good.5 Sellers can accept or reject these

offers. A buyer can make as many offers as desired in each round, but once one offer is

accepted, all other offers are withdrawn and no additional offers can be made. Similarly,

once a seller accepts an offer, no other offers can be entertained. In short, each buyer and

5 While most agricultural production contracts are not sales contracts, e.g., the buyer (processor) owns the chickens throughout the production process; processors are in a sense “buying” quality from the grower. That is, they purchase grower services to produce high-quality and cost-effective chickens.

7

seller can conclude at most one trade per round. No buyers are obligated to make offers

and no sellers are obligated to accept offers in any round. When buyers or sellers do not

enter contracts, a reservation payoffs is received (see below). At the start of each round,

no buyer or seller has a contract; buyers must actively make offers to engage trade.

Buyers can extend two types of offers: public and private. Public offers are

displayed on the computer screens of all sellers and buyers; any seller can accept any

public offer. Private offers are extended by entering a specific seller’s ID number into

the computer. Only the seller identified is notified of the offer and he can chose to accept

or reject it. Private offers enable long-term relationships, which lie at the core of the

theory of relational contracts. For example, if a buyer predicts benefits from contracting

with a specific seller and wants to establish a long-term relationship, the buyer can make

a single, private offer to that seller at the beginning of a round rather than venturing into

the open market and hoping that that seller is the first to accept the public offer.6 This is

an essential feature of relational contracting as it implies that the promise of future

relationship-specific gains from trade can sustain high performance in the current period.

In every round there are five buyers and seven sellers, which represents an

unemployment rate of nearly 30 percent under full trading and means that buyers have

significant bargaining power. Subjects maintained the same role (e.g., buyer) during both

sessions and no subject participated in more than one experiment (two sessions).

In order to test the impact of enforcement on efficiency and surplus, we examine

three enforcement regimes. First, in the “complete contract” (C) treatment, the computer

fully and perfectly enforces all contractual components. That is, sellers must supply the

6 Firms often establish “private trades” by contacting specific suppliers with whom they have good relationships so they do not have endure costly public solicitations when the desired supplier is already known.

8

quality stipulated in the contract, and buyers must pay the agreed upon price. In the

second treatment, which we call “Relational Contract 1” (RC1), the computer only

enforces contractual price. Quality is unenforceable, i.e., sellers can supply quality that

differs from contractual specifications. Thus, buyers must use implicit or “relational

incentives” to enforce quality. In other words, the parties must use trust and the promise

of future relationship-specific payoffs to sustain high quality in the current round. This

treatment mimics real-world situations where neither input quality or the measurement of

output (e.g. weighing of birds) is verifiable by a third party. In this case, measured

performance is unenforceable because when quality is low, both parties can blame the

other party (e.g., grower claims poor quality inputs or inaccurate weighing, and processor

claims grower shirked) so that verifiability and enforcement of the contract is extremely

costly. The third treatment is called “Relational Contract 2” (RC2), which is identical to

RC1 with the added feature that the buyer can make ex-post adjustments to the promised

price. In other words, after a buyer observes the seller’s delivered quality, the buyer can

choose a price that deviates from contract specifications. This treatment is inspired by

Hamilton’s claim that integrators can unilaterally change payment methods or rates. Our

C and RC1 treatments are nearly identical to BFF’s experiments, with the exception that

we had fewer buyers and sellers in each trading session (though the ratio is nearly

identical). Our RC2 treatment is unique to our study and allows examination of a broader

range of implicit incentive mechanisms that can be used to regulate relational trading.

We show that our RC2 treatment can provide significant new insights into the nature of

relational contracting. All rounds in a particular session feature the same treatment.

Round specific payouts are determined for buyers as follows:

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(1) �b = 10 Q P −ÀÃÕ

if agreement reached 0 if no agreement reached

where �b is the buyer’s payment, Q is the actual quality chosen by the seller, and P is the

actual price received by the seller. All payments are given in experimental points where

subjects earn one dollar for 70 points. The seller’s profit is:

(2) �s = ÀÃÕ

(P − c Q ) if agreement reached r if no agreement reached

where r is a reservation payoff (=5 or =10 depending on session) in the absence of trade.

During the experiment, Q is restricted to be an integer in the set {1,2,…,10}, and P is

restricted to be an integer from the set {0,1,2,…,100}.7 The cost function, c(Q), is fully

represented by the following schedule of quality-cost combinations: {1,0}, {2,1}, {3,2},

{4,4}, {5,6}, {6,8}, {7,10}, {8,12}, {9,15}, {10, 18} so that c(Q) is increasing and

convex. At the end of each round, each subject learns the payoff for each subject (buyer

and seller) involved in the transaction.

We conducted thirteen experiments. Each experiment included two of the three

treatments (C, RC1, or RC2). Each treatment session lasted 17 rounds (two practice and

15 live) and each subject participated in both treatment sessions during an experiment,

which means that order effects might arise. Hence, the design counterbalances the order

of appearance for each of the three enforcement regime sessions.8 At the end of an

experiment, one session was randomly chosen via a public roll of a die to be the paying

session. Before subjects were paid, they provided demographic information. There were

a total of 26 sessions (two in each of the thirteen experiments) where 13 were C

7 Note that the P and Q offered in the contract are also restricted to these sets.8 For example, if C was the first session of the night and RC1 was the second session, we made sure that inthe next experiment RC1 was first followed by C. We did this for all of our treatments.

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treatments, seven were RC1 treatments, and six were RC2 treatments. One hundred fifty-

six subjects made 1,885 trades. The experimental economy was programmed using Z­

TREE software (Fischbacher). For five C treatments, r=10, and for the others, r=5; r=5

for all RC1 and RC2 sessions.

Subjects were recruited from existing e-mail lists from the various departments

throughout a Midwestern university, and through paid advertisements in campus

newspapers. Potential subjects were informed that actual earnings depend upon the rules

of the game and the participant’s and other participants’ actions. Average earnings were

$23 per subject and ranged from $13 to $41. Additional details of the experiment,

including instructions are available in the Appendix.

Predictions

Under C, quality specified in an agreement is enforceable, i.e., the seller cannot deviate

from contracted Q. Thus, the buyer’s profit-maximizing contract choice is determined by

solving the problem:

( ((3) max 10 Q − P) s.t. P − c Q ) Δ 5 (Participation constraint) ,Q P

If the constraint holds with equality (which it must for a profit-maximizing buyer),

solving for P, and substituting into the objective function yields:

( ((4) max 10 Q − 5 − c Q ))Q

which gives the first-order condition:

�((5) 10 − c Q ) = 0

However, one can see from the cost schedule above that marginal cost never exceeds 3 so

that the buyer chooses to implement the maximum quality level, Q* = 10. With Q* in

hand, it is easy to solve for P* = 23 from the participation constraint to ensure that the

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seller will accept the contract. Because buyer and seller can earn at least as much when

trading rather than not trading, we predict all five buyers make offers and five sellers

accept these offers; hence, in equilibrium, five trades take place in the round and joint

surplus per trade is given by:

S C(6) = �b +� − r s

The above prediction holds in the final round of a “live” session (round 15). But it is

straightforward to show, by backward induction, that the same outcome occurs in every

round prior to round 15.

Under RC1, quality is unenforceable so that the seller can deliver quality different

than contract specifications. To determine what quality the seller will choose and what

contract offer the buyer will make, note that it was common knowledge that each live

session ends at the end of period 15. Thus, focusing on round 15, we must analyze the

interaction between the buyer and seller by using backward induction. Because the seller

is the last mover, consider what the seller would do given that she has accepted a contract

and is guaranteed some payment, P. Note from her objective function (2) that profit is

maximized when Q = 1 so that production cost is zero. Hence, equilibrium quality is

R 1Q C = 1. The buyer, anticipating that the seller will deviate from agreements specifying

R 1Q> 1, will offer just enough to ensure participation; that is P C = 5 . Again, both buyers

and sellers earn at least as much under trade as under no trade. Thus, in equilibrium, five

R 1trades take place during the round and joint surplus is given by S C = 5 . The

unenforceability of quality leads to substantially lower joint surplus and quality. Using

backward induction, it is easy to verify the same outcome in all previous rounds.

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In RC2, the buyer first offers a contract, which specifies desired price and quality.

If a seller accepts, the seller then chooses actual quality, i.e, the seller may deviate from

desired quality. After the buyer observes delivered quality, she chooses a payment at her

discretion, which can deviate from the price specified in the contract.

In order to determine equilibrium in RC2, first consider how the buyer, who is the

last mover, will respond to a given quality, Q 0 , chosen by the seller. The buyer’s payoff

0 R 2−is � = 10 Q P and therefore profit is maximized by setting P C = 0 . The seller, b

anticipating that the buyer will renege on any contracting agreement with positive

RC 2 0 0payment, will expect to earn � = P − c (Q ) = 0 − c (Q ) < 5 from the contract, which s

is lower than reservation earnings. Thus, the seller accepts no contract. In equilibrium,

no trade takes place and no surplus is earned in round 15. A similar logic follows for

round 14 and earlier. With two-sided discretion, the contracting market is completely

destroyed by opportunism.

The above analysis provides us with several hypotheses:

HYPOTHESIS 1: When Q is unenforceable (RC1 or RC2):

a) Equilibrium quality will be lower than the case when quality is enforceable (C).

b) Total surplus will be lower than the case when quality is enforceable (C).

HYPOTHESIS 2: When buyers have bargaining power, whether quality is enforceable

or not, all surplus goes to the buyer and trading sellers earn reservation payoffs.

HYPOTHESIS 3: If both quality and payment are unenforceable (RC2), the contracting

market collapses and no trade occurs in equilibrium.

A key point to emphasize is that, due to market power, sellers never earn rents

above reservation payoffs. Hence, enforcement is predicted not to help growers. Sellers

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can only be helped by raising reservation payoffs. Moreover, enforcement is predicted

only to raise efficiency. One can see that quality (and hence total surplus) improves as

one moves from no enforcement (RC2), where no trade occurs, to one sided enforcement

(RC1), where the market is restored but only delivers minimal quality and surplus, to full

enforcement (C), where socially efficient quality and surplus emerges.

There are two complicating factors that may prevent the above predictions from

being manifested in actual trading. First, as mentioned earlier, multiple equilibria are not

uncommon in repeated games, so it should not be surprising if actual behavior deviates

from that predicted above. Second, emerging economic research on social preferences

suggest that the population is not comprised of only rational, self-regarding profit-

maximizing individuals (Fehr and Gachter; Charness and Rabin; Engelmann and Strobel,

among others) on which the above predictions depend. Charness and Rabin point out that

a non-trivial fraction of the population cares about social efficiency, but withdraw

willingness to sacrifice (i.e. concern withdraw) for the sake of social efficiency when

others are unwilling to sacrifice. The presence of these types of individuals will allow for

reputation building, which can fundamentally alter theoretical predictions as individuals

concerned about social welfare can sustain quality and surplus levels that exceed

predicted levels in RC1 and RC2, even in period 15. Moreover, if sellers manifest

concern withdrawal then buyers have an incentive to offer sellers a non-trivial share of

the surplus to prevent concern withdrawal. The presence of relationship-specific rents in

period 15 implies that in period 14 and earlier, buyers and sellers have an incentive to

stick to the terms of the contract to facilitate future trades. Thus, the promise of future

payoffs may discipline trading partners in any given round and provide an informal

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enforcement mechanism to sustain high quality, even in the absence of formal

enforcement. Given the possibility of multiple equilibria and the existence of types that

are not purely self interested, it becomes even more important to study subjects’ actual

behavior, rather than to rely purely on theory. Relying only on theory may lead to

conclusions that are misleading and policy prescriptions that are counter-productive.

Nonetheless, our theoretical predictions are useful for heuristic purposes as they provide

an organizing framework.

Results

Trading

In this section, we analyze trading data (table 1) from our three treatment sessions. A

striking result is that the data does not support hypothesis 3, which predicts that no trade

should take place under RC2. In fact more trade takes place under RC2 (nearly 100

percent) than under C or RC1. Of the three treatments, RC2 may most resemble

agricultural markets; one can see that such markets can remain active even if no formal

enforcement is possible. Two possible explanations for this result are that (1) subjects

are simply playing a different equilibrium than the one our model predicts, which is not

unexpected in repeated games, and (2) subjects have heterogeneous social preferences as

discussed earlier. Indeed, BFF ran experiments that are similar to our C and RC1 and

find that actual play under RC1 significantly differs from predicted levels. BFF postulate

that social preferences, which can make it possible for buyers to credibly promise sellers

positive relationship specific rents even in period 15, are used by buyers to discipline

sellers in earlier periods. If we carry this rationale over to our RC2, then it is possible

that buyers who care about social welfare can credibly promise not to shirk on payments

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to sellers after observing quality. If enough of these buyers exist in the economy and

sellers know this, then sellers may be willing to sign contracts and the market does not

collapse. This may be a mechanism through which relationship-specific rents can be

generated even in the last round of the finitely repeated game, which allows relational

contracting to form in earlier periods.

Quality and Price

Average quality (table 1) was highest in the C treatment at 9.20 followed by RC2 and

RC1. This is consistent with hypothesis 1a, which predicts that the highest quality level

would emerge under C. A Kruskal-Wallis (KW) test conducted across all three

treatments strongly suggests that the three treatments differ in average quality delivered

(p < 0.001). Surprisingly, RC2, which represents a lower degree of enforceability than

RC1 delivered higher quality than RC1. A possible explanation for this result is that the

ability of buyers to make discretionary ex-post adjustments in price provides a

mechanism for providing quality incentives even in the absence of formal enforcement.

That is, if sellers anticipate that buyers will reward for high performance or deduct for

poor performance, then sellers may be more reluctant to perform poorly. These sorts of

price adjustments are consistent with “discretionary bonuses” of the sort discussed by

Levin, which can be used to provide incentives in relational contracts. Lee and Wu

model a relational contracting problem in which buyers have market power and suggest

that negative bonuses (i.e. price deducts) will be used by buyers to incentivize sellers. If

buyers are indeed making discretionary adjustments to reward or punish seller

performance, then we ought to observe a correlation between performance and price

adjustments.

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Table 2 reports the types of adjustments made by buyers cross tabulated against

performance for all RC2 trades. The patterns indicate that buyers do make adjustments

contingent on performance which provides a mechanism for buyers to deliver incentives.

Note that conditional on good performance (quality at least meets agreed upon quality),

rewards (upward adjustments in price) are used 19% (10.9%/56.8% ≈19%) of the time

whereas conditional on poor performance, sellers are rewarded only 1.5% (0.6%/43.2%)

of the time. Conditional on good performance, deducts (downward price adjustments)

are observed 31% of the time, but this shoots up to about 80% conditional on bad

performance. These patterns suggest that (1) discretionary price adjustments do appear

to be dependent on quality which is consistent with our intuition that these adjustments

are informal means of providing incentives just as Levin predicts, and (2) that

opportunistic behavior, independent of incentive provision, still occurs as evidenced by

the fact that, in 31% of trades where sellers met performance obligations, buyers still

made downward adjustments. A final interesting observation is that deducts are used

much more frequently than rewards; specifically, while 56.8% of total trades in RC2

involved sellers meeting obligations, rewards were observed only 11.5% of the time.

Thus pattern is consistent with Lee and Wu’s prediction that deducts, not rewards, will be

used when buyers have market power.9

Table 3 allows us to examine the role of discretionary price adjustments further.

This table reports the results of a probit regression that regresses the probability of a

deduct on both positive and negative differences between quality supplied and quality

specified in the contract. A number of additional regressors were included as control

9 Lee and Wu’s prediction is not driven by social preferences as their relational contracting model makes neoclassical rationality assumptions about the preferences of agents. Instead, it is driven purely by market power.

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variables. The reported results are in terms of changes in probability for small changes in

the independent variables. Note that when suppliers exceed quality obligations, it does

not help them avoid deducts. However, when suppliers underperformed relative to the

contractually specified level of quality, this increased the probability of a deduct, as the

marginal effect is 0.167 and significant at the 5% level. It is interesting to note that the

probability of a deduct falls significantly if a trade was based on a private offer

suggesting that when buyers hand picked sellers, the buyer is less likely to punish or

behave opportunistically toward these sellers. One possible explanation is that, because

private trades indicate that relational trading is taking place, it is unlikely that the parties

will renege on their agreements for fear of violating self enforcement constraints. In

other words, in relational contracting, it is the promise of future payoffs that disciplines

behavior in a current period. If sellers or buyers shirk on their agreements for short term

gains, they risk being terminated by the other party and foregoing long term gains. Self

enforcement therefore place bounds on the degree to which parties can deviate from the

agreement without causing the relationship to unravel. Indeed, when we calculated

summary statistics (not shown in table), our data showed that average quality shortfall

was -0.29 under private trade whereas it was -1.46 under public trade. Similarly, average

price adjustment was -4.66 under private trade and -11.9 under public trade. This is

broadly consistent with the notion that subjects tend not to deviate from agreements as

much under private trade suggesting that the threat of separation can impose discipline on

the parties.

Surplus and Profits

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We begin by investigating the distribution of surplus across buyers and sellers. Table 1

indicates that average surplus differs across the three treatments, which is not surprising

considering that average surplus differences should track quality differences. What is

most interesting is that sellers earn the highest average profits under RC1; in fact, their

actual profit exceeds promised profit from the contract. One possible reason for this is

that, in RC1, sellers have the discretionary power to select Q as Q is unenforceable; thus,

this discretionary power appears to allow sellers to offset some of the market power of

buyers. Buyers only have informal means of enforcing quality either via termination or

by appealing to sellers’ social preferences. That is, if some sellers have a concern for

social efficiency, but have a tendency toward concern withdraw, then these sellers will

exert high quality so long as buyers are willing to share rents with these sellers. Indeed,

23% of trades (not reported in table 1) in RC1 involved sellers choosing Q =10 and these

sellers earned an average of 41.6. On the other hand, in the 77% of trades where sellers

supplied Q < 10, average seller profit was 21.4. This is broadly consistent with the

notion that some sellers are willing to supply the socially efficient amount of quality, and

that their buyers are also willing to share the gains from trade leading to efficient and

mutually beneficial trade.

We also investigate how much of the surplus is shared with sellers across the

three treatments. Note that hypothesis 2 suggests that, with buyer market power, sellers

will always receive rents equal to reservation payoffs. However, the data suggests that

average earnings are higher than reservation payoffs across all three treatments. For all

three treatments, Wilcoxon sign rank tests yielded p-values of 0.00 strongly rejecting the

equality of average profits and reservation payoffs for sellers. Also, average profits of

19

sellers differ across the three treatments as verified by a Kruskal-Wallis test (p-

value=0.00).

Two specific observations caught our attention. First, in RC1, sellers’ average

profit exceeds promised profit (25.98 vs. 21.29). We conjecture that sellers’

discretionary power to deviate from contracted quality gives them the ability to take back

some of the monopsony rents buyers had captured. In contrast, in RC2, sellers earned

significantly less ex post rents than they were promised (16.04 vs. 23.21). This could be

because some buyers behave opportunistically by making downward adjustments in price

even when their sellers performed (recall that conditional on good performance, deducts

were still observed 31% of the time). Second, in the C and RC1 treatments, sellers rarely

earned profits that fell below reservation levels so that, on average, sellers made good

decisions in accepting and rejecting contracts. This is verified by the fact that average

promised profits exceed reservation payoffs in all three treatments. 10 However, in RC2,

the possibility of opportunism by buyers resulted in sellers earning less than reservation

payoffs, ex post, in nearly 19% of trades. Thus, although sellers in RC2 accepted the best

contracts, on average, nearly one in five sellers ended up with profits that fell below

reservation payoffs. This is consistent with anecdotal evidence in the real world where

some growers complain that they did not earn as much as they were promised.

Figure 1 offers another perspective on how sellers did in terms of the proportion

of total surplus they captured across rounds. Note that in both C and RC2, sellers

consistently captured less than 50% of total surplus; in fact, in round 15, sellers earned a

negative fraction of total surplus, which is possible when surplus is positive but sellers

earn negative profits. At the other extreme, under RC1, sellers rarely earned less than

10 Reservation pay was 5 for RC1 and RC2 and either 5 or 10 in C.

20

50% of total surplus and in some cases earned more than 100% of surplus (surplus

positive, buyers earn negative profits, and sellers’ profits exceed surplus).

Table 4 allows for a more complete examination of surplus and profits. This table

reports the results from three regressions where the three dependent variables are surplus,

buyer profit and seller profit. These regressions allow us to determine the impact of RC1

and RC2 on each of the dependent variables. Moreover, a number of control variables

were used including demographic information obtained from post experiment surveys,

and fixed effects for experiments, rounds, buyers, and sellers. Note that a dummy for C

was omitted so that C represents the base treatment against which comparisons are made.

The “reservation” variable represents the seller’s reservation payoff to account for the

fact that reservation payoffs varied from 5 to 10 in some C sessions. While our main

variables of interest are RC1 and RC2, they were also interacted with a “private” dummy

because it is very likely that the incremental impact of RC1 and RC2 will depend on

whether trades were based on private or public offers. This is because sellers who

receive private offers may have established long term relational contracts with buyers,

which may affect the offers and responses they receive from buyers.

Focusing on regression (1) first, an F-test for the joint significances of RC1 and

RC1×Private yielded a p-value of 0.00 (not reported in table). This suggests that the

conditional mean of surplus differs between the C and RC1 treatments. To examine this

further, the incremental impact of RC1 on surplus given that trades are public is

estimated to be -47.04 and significant at the 5% level. Under private trading, the

incremental impact of RC1 on surplus is given by the sum of the coefficients for RC1 and

Private×RC1, which is estimated to be -21.33 (not reported in table) with a standard error

21

of 1.65 (p-value=0.00). Thus, irrespective of whether private or public trading occurs,

surplus decreases under RC1 relative to C, which suggests that the absence of quality

enforcement has significant efficiency costs. However, given that the estimated

coefficient for Private×RC1 is positive (25.72) and significant at the 5% level, private

trading appears to significantly mitigate efficiency losses. Sellers who do not trade

privately may have trouble establishing relational contracts; thus, these sellers conduct

most of their trading outside of relationships where no relational incentives exist to

enforce their behavior. These sellers appear to impose significant costs on society. To

put this into perspective, social surplus is maximized when Q= 10, which results in a

surplus of 77. The loss of 47.04 in surplus represents a 60% reduction in social

efficiency relative to first best. The fact that the coefficient Private× RC1 is 25.72 and

significant at the 5% level may imply that relational contracting can provide powerful

informal enforcement of quality. These results support Hypothesis 1b which predicts that

the absence of enforcement will lower total surplus.

Turning now to RC2, an F-test for the joint significance of RC2 and Private×RC2

yields a p-value of 0.00 (not reported in table). This suggests that the conditional mean

of surplus differs between C and RC2. The incremental impact of RC2 on surplus under

public trade is estimated to be -6.86 and significant at the 5% level. The incremental

impact of RC2 on surplus under private trade is given by the sum of the coefficients of

RC2 and Private× RC2, which was estimated to be 4.13 (not reported in table) with a

standard error of 3.44. Because the p-value is 0.34, this estimate is not significantly

different from zero; thus, RC2 does not appear to reduce surplus relative to C, provided

that subjects exploit private trades to facilitate relational contracting. This result is in

22

stark contrast to RC1 as it appears that relational contracting combined with the ability of

buyers to make discretionary adjustments in price provides informal enforcement that can

nearly perfectly substitute for formal enforcement in producing high levels of social

efficiency. Discretionary ex post adjustments in price are not unlike the discretionary

bonuses (deducts) discussed by Levin in reference to relational contracting. While these

discretionary price adjustments can clearly deliver incentives, they are less effective

when they are used outside of relational trading. Parties who trade privately, and

therefore are involved in relational contracts, tend to increase surplus by 10.99 over those

who are not involved in relational trading (public trade). These results suggest that

Hypothesis 1b will not hold when parties have a sufficient range of informal enforcement

mechanisms at their disposal.

Because relational contracts involve long term relationships which can only be

established through private trading, we have an indirect way of estimating the returns to

relational contracting. Note that the returns to private trading under RC1 (RC2 =0) is the

sum of the coefficients for Private and Private× RC1, which is estimated to be 22.08 (not

reported in table) with a standard error of 2.04 (p-value=0.00). Consequently, returns to

relational trading appears to be significant under RC1 yielding an average surplus gain of

22.08. For RC2, the estimated return to relational trading is 7.35 with a standard error of

2.13 (p-value=0.001). Again, relational trading appears to be important for enhancing

surplus, although the magnitude is smaller than in the case of RC1. In contrast, relational

trading appears to be counter-productive under C, as evidenced by the fact that the

Private coefficient is -3.64 and significantly different from zero at the 5% level of

significance. Thus, there appears to be no benefit to relational contracting in complete

23

contracting settings. It appears that formal enforcement essential crowds out informal

enforcement.

So far, we have established that the conditional mean of surplus under RC1 is

lower than under C, the conditional mean of RC2 surplus is not significantly different

from that of C under private trading, and that relational contracts provide powerful

informal incentives for quality. The next question is, how do our key treatments impact

profits to buyers and sellers?

Focusing on RC1 first, F-tests for the joint significance of RC1 and Private× RC1

yielded p-values of 0.00 for both regressions 2 and 3 (not reported in table). This suggests

that the conditional mean of both buyer and seller profits differ under C versus RC1. The

incremental impact of RC1 under public trade is estimated to reduce buyer profit by

51.85, but would increase seller profit by 4.81. Under private trade, the impact of RC1

on profits is given by the sum of coefficients for RC1 and Private×RC1. These estimates

are -29.53 (standard error=1.85) in regression 2 and 8.19 (standard error=1.32) in

regression 3, both with p-values of 0.00 (not reported in table). Hence, even under

private trade, RC1 reduces buyer profit and increases seller profit, which contradicts

Hypothesis 2. This supports our earlier analysis indicating that buyers are hurt by

unenforceable quality whereas sellers benefit as it gives them discretionary ex post power

to extract some of the buyer’s monopsony rents. Buyers, however, can still mitigate their

losses through private trade as the estimated coefficient for Private×RC1 is 22.33 in

regression 2 and significantly different from 0. Hence, buyers who are able to establish

relational contracts can still benefit and provide some informal quality enforcement. By

the same token, sellers who are engaged in relational contracts can enhance their surplus

24

even further as evidenced by the estimated Private×RC1 coefficient of 3.39 (significant at

10%) in regression 3.

In contrast to RC1, RC2 has very different effects on buyer and seller profits.

Joint significance tests of RC2 and Private×RC2 coefficients yield p-values of 0.00 and

0.001 (not reported in table) in regressions 2 and 3, respectively suggesting that RC2 does

affect the conditional means of profits (relative to C). The incremental impact of RC2

under public trade has virtually no impact on buyer profits, but reduces seller profits by

5.82 (significant at 5%). Under private trade, RC2’s impact on buyer profit is estimated

to be 10.71 (standard error=3.67), and its impact on seller profit is estimated to be -6.58

(standard error=2.09), both of which are significant at the 5% level (note reported in

table). An examination of the Private×RC2 coefficient in regression 3, which is -0.76

and not significantly different from 0, shows that the RC2 impact on seller profits is no

different under public or private trading. However, buyers have an incentive to establish

relational contracts as the same coefficient in regression 2 is 11.75 and significantly

different from 0 at the 5%. Recall that the same coefficient in regression 1 was 10.99,

which indicates that establishing relational contracts can enhance social surplus and this

relationship induced gain is completely captured by the buyer. Overall, sellers appear to

be worst off under RC2 than any other enforcement regime.

Conclusion and Implications

In this article we report the results of an economic experiment that investigates

contracting relationships between buyers and sellers in an environment that featured

market power on the part of buyers, and different degrees of formal enforcement of

contracts. Because the presence of market power and incomplete enforcement of

25

contracts are both common features of real world agricultural contracting, we believe that

our results can help policy makers understand the basic microeconomic forces that shape

contracting relationships between processors and growers. Moreover, by exogenously

varying our enforcement regimes, we provide some experimental counterfactuals that can

help economists and policy makers understand how government involvement in

contracting markets might affect social efficiency and the distribution of surplus.

Not surprisingly, we find that full enforcement of contracts promotes social

efficiency. Surprisingly, however, we find that when enforcement is completely non­

existent (i.e. the government is completely “hands off”), trading parties can use

discretionary adjustments to contract terms combined with relational contracting to create

a level of social surplus that nearly matches the level obtained under full enforcement.

Thus, when formal enforcement was missing, many of our subjects were able to

compensate with informal enforcement mechanisms. However, if formal enforcement is

one-sided or incomplete, this appears to constrain the ability of parties to make this

substitution so that there was a significant loss in social efficiency. The policy

implication is that if the government chooses to monitor and enforce contracts more

rigorously, doing so in a one-sided or incomplete manner can crowd out informal

incentives and undermine efficiency.

With regard to distribution, a very complex pattern emerges under our three

enforcement regimes. On the surface, it would be reasonable to assume that, with buyer

market power, most of the gains from trade would be captured by processors. We find

that this is generally true under the extreme cases of full enforcement and no enforcement

(government completely hands off). However, in the intermediate case, when there is

26

only partial or one-sided enforcement - where buyers’ contractual obligation are

rigorously enforced but sellers’ obligations are not - sellers can capture a significant share

of social surplus. However, the tradeoff is that social efficiency is reduced considerably.

The practical implication of this result is that, while government enforcement of

processor obligations would help growers, it may have significant costs in social

efficiency.

We close our article with a caveat. While efficient trading can still occur under a

“hands of policy” of no enforcement, there was evidence of opportunistic behavior on the

part of buyers. Specifically, while buyers’ ability to make discretionary adjustments in

price ex post can provide informal incentives to discipline sellers and enhance efficiency,

it appears that a non-trivial fraction of trades also exposed sellers to discretionary

downward adjustments even when they performed. Because of this opportunistic

behavior, sellers, on average, earned less than what they were promised in their contracts

and nearly one in five sellers earned profits that fell below their reservation profits. Thus,

while a “hands-off policy” may not significantly compromise efficiency, it could impose

considerable costs on growers.

27

References

Boehlje, M., L. Schrader, C. Hurt, K. Foster, and J. Pritchett. 2001. “The Producer Protection Act – Will It Protect Producers?” Agricultural Law Update, January.

Brown, M., A. Falk, and E. Fehr. 2004. “Relational Contracts and the Nature of Market Interactions.” Econometrica 72: 747-780.

Charness, G.and M. Rabin. 2002. “Understanding Social Preferences with Simple Tests.” Quarterly Journal of Economics 117: 817-69.

Engelmann, D. and M. Strobel. 2004. “Inequality Aversion, Efficiency, and Maxmin Preferences in Simple Distribution Experiments.” American Economic Review 94: 857-869.

Farmers’ Legal Action Group, Inc. 2001. “Contract Broiler Production – The Legal Context and Recommendations.” In Assessing the Impact of Integrator Practices on Contract Poultry Growers, Farmer’s Legal Action Group, Inc., St. Paul, MN, September.

Fehr, E., and S. Gachter. 2000. “Fairness and Retaliation: The Economics of Reciprocity.” Journal of Economic Perspectives 14: 159-181.

Fischbacher, U. 1999. “Z-Tree: Experimental Software.” University of Zurich.

Hamilton, N. 2001. “A Current Broiler Contract Analysis Addressing Legal Issues and Grower Concerns.” In Assessing the Impact of Integrator Practices on Contract Poultry Growers, Farmer’s Legal Action Group, Inc., St. Paul, MN, September.

Harl, N.E., M. Stumo, R.A. McEowen, W. Heffernan, and D. O’Brien. 2001. “The Producer Protection Act – Will It Protect Producers? A Rejoinder.” Agricultural Law Update, February.

Lee, M., and S. Wu. 2005. “Relational Contracts and Termination Damages.” Working Paper, Dept. of Agr., Env., and Dev. Econ., The Ohio State University.

Levin, J. 2003. “Relational Incentive Contracts.” American Economic Review 93: 835­857.

MacLeod, B. and J. Malcomson. 1989. “Implicit Contracts, Incentive Compatibility, and Involuntary Unemployment.” Econometrica 57: 447-480.

Maskin, E. 2002. “On Indescribable Contingencies and Incomplete Contracts.” European Economic Review 46: 725-733.

28

Noussair, C.N. and Plott, C.R. 1995. “An Experimental Investigation of the Patterns of International Trade.” American Economic Review 85: 462-487.

Pierce, J., and D. Stewart. 1997. “USDA Considers Regulations to Address Contract Grower Issues.” USDA News Release No. 0039.97, Feb. 10. Available at: http://www.usda.gov/news/releases/1997/02/0039

Roe, B. and A. Randall. 2001. “Survey and Experimental Techniques as an Approach for Agricultural Risk Analysis.” A Comprehensive Assessment of the Role of Risk in U.S. Agriculture. Edited by Richard Just and Rulon Pope. Kluwer Academic Publishers, Norwell, MA.

Schrader, L., and J. Wilson. 2001. “Broiler Grower Survey Report.” In Assessing the Impact of Integrator Practices on Contract Poultry Growers, Farmer’s Legal Action Group, Inc., St. Paul, MN, September.

Schwartz, A. 2002. “Contract Theory and Theories of Contract Regulation.” The Economics of Contracts. E. Brousseau and J.M. Glachant, eds., pp. 59-71. Cambridge, UK: Cambridge University Press.

Taylor, C.R. 2002. “Restoring Economic Health to Contract Poultry Production.” Agricultural and Resource Policy Forum, Auburn University, May. Available at: http://www.auburn.edu/~taylocr/topics/poultry/poultryproduction.htm

Tirole, J. 1999. “Incomplete Contracts: Where Do We Stand?” Econometrica 67: 741-782.

Wu, S. 2005. “Identifying Incentive Effects Using Agricultural Contracting Data.” Working Paper, Dept. of Agr., Env., and Dev. Econ., The Ohio State University.

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Table 1. Key Summary Statistics Quality

#Trades/#Possible Mean STD Min Max C 942/975 9.20 1.49 2 10

(97%)

RC1 512/525 5.13 3.55 1 10 (98%)

RC2 449/450 7.68 2.51 1 10 (99.8%)

Surplus #Trades/#Possible Mean STD Min Max

C “ 69.13 11.63 14 77

RC1 “ 38.90 28.42 5 77

RC2 “ 59.54 19.66 5 77

Buyer Profit #Trades/#Possible Mean STD Min Max

C “ 59.10 16.20 -10 85

RC1 “ 17.88 23.96 -90 99

RC2 “ 48.50 21.65 -25 100

Seller Profit #Trades/#Possible Promised Mean STD Min Max % of

Profit Actual Trades Profit where

Profits Fall Below

Reservation C “ 17.01 17.01 11.62 -5 82 5%

RC1 “ 21.29 25.98 18.44 -17 100 1.8%

RC2 “ 23.21 16.04 13.88 -18 55 18.7% Note. Promised profit is the amount the seller earns if both parties stick to the terms of the contract.

30

Table 2. Discretionary Adjustments Made by Buyers According to Performance. Discretionary Price Adjustment by Buyer

Reward No Adjust. Deduct Overall Q ≥ Q* 10.9% 29.3% 17.6% 56.8%

Q < Q* 0.6% 7.8% 34.7% 43.2%

Overall 11.5% 36.1% 52.3% 100% Note 1: Q* = quality supplier agreed to deliver in the contract. Note 2: Reported in % of total number of transactions.

31

Table 3. Probability of Deducts in RC2. Regressors Marginal Effects (� probability for small change

regressor) Amount Q exceeds Q* (defined as max[Q-Q* ,0])

Amount Q falls short of Q* (defined as max[Q*-Q,0])

Private dummy (1 if a private offer, 0 otherwise)

Gender of buyer (1 if male, 0 if female)

Buyer’s age

Buyer’s GPA

Buyer employed? (1 if yes, 0 if no)

Gender of seller

Seller’s age

Seller’s GPA

Seller employed?

N = 436 Log Pseudo Likelihood = -209.69 Pseudo R2 = 0.31

0.007 (0.068)

0.167** (0.03)

-0.288** (0.065)

-0.25** (0.06)

0.067** (0.026)

-0.078 (0.067)

-0.086 (0.069)

0.007 (0.06)

-0.024* (0.01)

0.163** (0.067)

0.087 (0.065)

**Significant at 5% level *Significant at 10% level

Note 1. The estimation procedure is a probit regression with robust standard errors (in parentheses) Note 2. Dummies for both rounds and experiments were included for round and experiment effects.

32

0

1

2

1 2 3 4 5 6 7 8 9

C

Figure 1. Seller's Share of Total Surplus Across Rounds

-0.5

0.5

1.5

10 11 12 13 14 15

Round

Por

port

ion

RC1

RC2

33

Table 4. Regressions Results (All Numbers are in Experimental $/points) Dependent Variables

Regressors (1) (2) (3) Surplus Buyer Profit Seller Profit

RC1 (dummy) -47.04** -51.85** 4.81** (1.44) (1.65) (1.13)

RC2 (dummy) -6.86** -1.04 -5.82** (2.79) (3.16) (1.65)

Private trade (dummy) -3.64** -10.51** 6.87** (1.40) (1.59) (1.17)

Private× RC1 25.72** 22.33** 3.39* (2.31) (2.60) (1.82)

Private × RC2 10.99** 11.75** -0.76 (2.44) (2.50) (1.61)

Reservation 0.66 2.65** -0.99** (0.59) (0.65) (0.35)

Buyer Gender (dummy) 12.12** 1.39 10.73** (3.20) (3.64) (2.12)

Buyer Age 0.77 -0.50 1.28** (0.59) (0.62) (0.38)

Buyer GPA -10.91** -1.05 -9.86** (3.70) (4.04) (2.06)

Buyer Employed -0.54 -1.53 0.99 (dummy) (3.08) (3.56) (2.22)

Seller Gender (dummy) -4.08 -2.24 -1.84 (4.03) (4.14) (2.14)

Seller Age 0.09 0.04 0.04 (0.46) (0.49) (0.26)

Seller GPA 9.32** 7.64** 1.68 (3.06) (2.78) (1.83)

Seller Employed 5.27 6.60* -1.32 (dummy) (3.89) (3.63) (2.12)

R

N 1885 F-Stat p-value 0.00

2 0.66

1885 1885 0.00 0.00 0.68 0.54

**Significant at 5% level. *Significant at 10% level.

Note 1. White’s robust standard errors are in parentheses. Note 2. All regressions include experiment, round, buyer and seller fixed effects. Note 3. Some fixed effects for buyers and sellers were dropped due to collinearity.

34