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1/219Falk: Behavioral Labor Economics: Psychology of Incentives

II. Psychology of incentives

Armin FalkIZA and University of Bonn

April 2004


Main Message

• There are important non-pecuniary motives of performing productive activities.

• Standard P-A-model neglects them because it only considers the motives for avoiding risks and achieving income through effort.

• Non-pecuniary motives interact with pecuniary incentives in important ways. They weaken or remove certain pecuniary incentives and they themselves often constitute powerful pecuniary incentives.

• Economists should take these interactions into account to improve the predictive and the prescriptive value of their models.


The Standard Principal-Agent Model

• Agents’ objective function is, in general, increasing and strictly concave in income, decreasing and strictly concave in effort and frequently separable in the two arguments.

• Neglects all motives except the motive for avoiding risk and achieving income through effort.

• Problem– Other motives may be as important as or even more

important than the desire to achieve income (shifts in the supply of effort schedule).

– Other motives may interact in important ways with the pecuniary incentives provided.


Overview of chapter II

a) Reciprocity as a contract enforcement device

b) Dysfunctional effects of incentives

c) Peer effects

d) Loss aversion, social norms and sabotage


a) Reciprocity as a contract enforcement device

Main idea

• Not all agents are selfish • There is a fraction of reciprocally motivated agents who

reward a fair treatment with a fair effort• Reciprocity as a contract enforcement device


Literature

• Fehr, E., Falk, A., 2002. Psychological Foundations of Incentives, European Economic Review 46, 687-724

• Fehr, E., Gächter, S., Kirchsteiger, G., 1997. Reciprocity as a contract enforcement device – experimental evidence. Econometrica 65, 833–860

• Gächter, S., Falk, A., 2002. Reputation and Reciprocity -Consequences for the Labour Relation, in: Scandinavian Journal of Economics 104 (2002), 1-26

• Fehr, E., Klein, A., Schmidt, K.M., 2004. Fairness, incentives and contractual incompleteness. Working Paper No. 72, Institute for Empirical Research in Economics, University of Zurich


Starting point

• Contract enforcement is of central economic importance• Very often there are enforcement problems because

contracts often inherently incomplete– in particular labor contracts

• legal restrictions on fines• imperfect monitoring• Unforeseen contingencies

• Result– Enforceable effort < efficient effort – Moral hazard problems and inefficiencies

• Voluntary cooperation highly relevant


What is Reciprocity?

• In the last decade experimental economists and psychologists have provided ample evidence that a substantial fraction of the people exhibit social preferences, i.e., these people value the pecuniary payoffs of others positively or negatively.


• Reciprocal preferences are contingent social preferences, i.e., behavior depends on the behavior of the person(s) with whom the agent interacts.

• If an agent perceives the actions of the principal as kind, the agent values the principal’s payoff positively. If the principal’s actions are perceived as hostile, the agent values the principal’s payoff negatively (Rabin AER 93, Falk/Fischbacher 99, Duwfenberg/Kirchsteiger, GEB 2004)

• Implications for contract enforcement?– Fair-wage-effort hypothesis– Empirical question


Reciprocity Generates Voluntary Cooperation

• Gift Exchange Experiment (Fehr, Gächter, Kirchsteiger, Ectra 1997)

• „Firms“ make a contract offer: w, ê where w ∈ { 0, 1, 2, ..., 100 }

• „Workers“, upon acceptance, choose the actual effort e which can differ from ê

• w not conditioned on e • anonymous one-shot interactions


Payoffs• „Firms“: 100e – w , e ∈{ 0.001, ..., 1}• „Workers“: w – c(e)• c(e) strictly increasing in e

20

1

18.51715.51412.5119753210c(e)

.9.8.7.6.5.4.3.2.1.064.027.008.001e


• Predictions with selfish subjects– Workers always choose the minimal effort level– Firms always choose the minimal feasible wage


Firms appeal to workers’ reciprocity

Firms' offered average rents as a function of effort demanded (Source: Fehr, Gächter & Kirchsteiger 1997)

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25

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35

40

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1Effort demanded

Ren

t


Workers respond, on average, reciprocally

Workers' effort as a function of firms' offered rents(Source: Fehr, Gächter & Kirchsteiger 1997)

0.10.2

0.30.40.50.6

0.70.8

0.91

0-5 6-10 11-15 16-20 21-25 26-30 31-35 36-40 41-45 46-50

Offered Rents

Effo

rt


Voluntary cooperation is not just an artefact of a single experiment

• Often replicated under different institutions (e.g., Fehr/Falk JPE 1998, Fehr/Kirchsteiger/Riedl QJE 1993, Charness forthcoming JLE, Brandts/Charness2000)

• Even when stake level amounts to three months’ income (Fehr/Tougareva/Fischbacher 1995)


Questionnaire evidence

• Truman Bewley 1999: Why Wages don’t fall during a Recession?

• “Workers have so many opportunities to take advantage of employers that it is not wise to depend on coercion and financial incentives alone as motivators.”

• “ In economics, it is normally assumed that people, being self-interested, must be either coerced or bribed into performing tasks. However, the main causes of downward wage rigidity have to do with employers’ belief that other motivators are useful as well, which are best thought of as having to do with generosity.” (p. 431)


Reciprocity and Loyalty

• Because in most jobs workers have many opportunities to take advantage of employers, employer place great value on workers who are loyal and who are committed to the goals of the firm.

• In the presence of only self-interested agents it is difficult to make sense of the notion of loyalty whereas it naturally follows from the notion of reciprocity.


• Loyalty means that workers take into account the interests of their employers (i.e., value the employers payoff positively) and in the presence of reciprocal people a positive valuation of the employer’s payoff can be created if employers also take into account the interests of their employees.

• The fact that much of the testing and screening of employees is not just about cognitive abilities but crucially about psychological properties of the prospective employee can be taken as a vindication of this viewpoint. Employers are not just interested in the abilities of the people they hire but also in their character.


• Thus, given reciprocal preferences and depending on the previous history of a relationship, a principal and an agent may develop a good relationship (value each other’s payoff positively) or they may develop a bad relationship (they value each other’s payoff negatively).

• In this sense reciprocity creates relation-specific preferences. Good relation-specific preferences can be viewed as a capital stock because they increase the surplus. Good relations can be viewed as relations with a high stock of goodwill on both sides.


Reciprocity as a source of material incentives

• So far: Many agents reciprocally motivated• Yet, we should not forget the large percentage of selfish

subjects that do not respond to fairness and generosity. • Does reciprocity also cause powerful material incentives

that help disciplining the selfish types?


• Three-stage Gift Exchange Experiment (Fehr, Gächterand Kirchsteiger Ectra 97)

• Add a third stage to the two-stage game in which principals can punish or reward a “worker” ex-post but punishing as well as rewarding is costly.

• Every $ spent on punishment reduces the worker’s payoff by $2.5 and every $ spent on rewarding increases the worker’s payoff by $2.5.

• Should have no impact with selfish principals but reciprocal principals will reward excess effort (e ≥ ê) and punish shirking (e < ê). – Provides material incentives for the workers


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Period

aver

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effort demanded three stages actual effort three stageseffort demanded two stages actual effort two stages


• Principals reward and punish (reciprocal behavior)• This is anticipated by workers (even though they expect

more rewards and less punishments than actually occur)• Compared to the 2-stage design, in the 3-stage design

– Average effort increases substantially– Shirking rate (e < ê) lower, from 65% to 21% – Rate of e = ê increases from 33% to 72%– Excess effort (e > ê) from 2% of the cases to 7%

• Both workers and firms are on average better off in the 3-stage compared to the 2-stage world


Reciprocity and contract choice

• Does reciprocity affect contractual choices and hence incentive provision?

• Does reciprocity give rise to contractual incompleteness?• Fehr, Klein and Schmidt (2004) study experiment where

employers can choose between a piece rate contract, a trust contract and a bonus contract

• Bonus and trust contract are doomed to fail in the absence of reciprocity


The Experiment

• Series of one-shot interactions between principals and agents, 10 periods in each session

• Three treatments– Trust versus Incentive Contracts (TI-Treatment)– Bonus versus Trust versus Incentive Contracts (BI-

Treatment)– Combined contracts (Extended Bonus-Incentive treatment,

EBI)


Trust Contract

• Principal proposes a wage w and a desired effort e*• Agent accepts or rejects

– (in case of rejection both receive zero)• In case of acceptance agent must choose an effort level

e, which can differ from e*

Payoffs:• Principal: 10e – w, e∈ {1, ..., 10} • Agent: w – c(e), c(e) strictly increasing


Cost function

20161310864210C(e)

10987654321e


Prediction trust contract

• Standard prediction– Agent: e = 1 Principal: w = 0

⇒ Principal earns 10 and the agent zero• Reciprocity Prediction

– Agent: e = e(w) and e’ > 0– Principal: w > 0 to avoid rejection and to elicit higher effort

levels– In principle a high wage-high effort outcome could be an

equilibrium depending on the fraction of reciprocal agents


Incentive Contract

• Principals make a contract offer: w, e*, f = (wage, desired effort, fine)– f is a fine, constrained by 0 ≤ f ≤ fmax = 13, collected by

the principal, to be paid by the agent in case of verifiable shirking (e < e*)

• Agents, upon acceptance, choose the actual effort e which can differ from e*

• Random mechanism determines with prob. 1/3 whether e < e* is verifiable

Payoffs in case of Non-shirking:• Principals: 10e – w – 10, e∈ {1, ..., 10}; fixed verifi-

cation cost of 10• Agents: w – c(e), c(e) as before


Standard prediction incentive contract

• A selfish agent will perform e*, if (1/3)f ≥ c(e*) holds• fmax determines the maximum enforceable e*

– which is e* = 0.4 for the implemented cost function (1/3*13=4.33)

• Principal proposes e* = 0.4, f = 13 and w = c(e*) = 4⇒ Principal earns 40 – 4 – 10 = 26

• Agent earns again zero⇒ Principals prefer the incentive over the trust contract


Reciprocity prediction incentive contract

• To prevent rejection principals also have to offer a rent to the agent

• Effort response depends on the assumed source of reciprocal behaviour

• If the rewarding of fair and the punishment of unfair intentions is the source, the incentive contract may ren-der agents unwilling to provide voluntary excess effort– Threatening a fine may be viewed as an unfair action– Threatening a fine my cause a hostile atmosphere

• Incentive contract less efficient than predicted by the standard model


• If reciprocal behaviour is equity (equality) driven principals may be able to induce e > 0.4 for sufficiently high wages

• Principals may also try to elicit reciprocal effort choices in the incentive treatment

• Incentive contract may be more efficient than predicted by the standard model

• Without an explicit model no clean predictions regarding principals’ contract preferences possible


Bonus Contract

• Principals make a contract offer:w, e*, b* = (wage, desired effort, bonus)

• No fine, but firms can announce to pay a bonus b*, in addition to the base wage w, after they have observed the actual effort

• Bonus announcement b* is not binding


Standard prediction bonus contract

• Actual bonus b = 0• Actual effort e is minimal, e = 1• Only minimal wages are offered by firms• Same payoffs as in trust contracts• Principals prefer the incentive contract over the bonus

contract


Reciprocity prediction bonus contract

• Fair principals reward the agent with a bonus for providing the desired effort

• If there are sufficiently many fair principals, the selfish agents have an incentive to perform in the bonus contract (see FGK 1997)

• Bonus contract may be more efficient than the trust contract, and perhaps even more important than the incentive contract


Share of incentive and trust contract (TI treatment)

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Share of Incentive ContractsShare of Trust Contracts


Average effort and average demanded effort in the Trust-Incentive treatment

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1 2 3 4 5 6 7 8 9 10

Period

averagedemanded effortincentive contracts

averagedemanded efforttrust contracts

average effortincentive contracts

average effort trustcontracts


Share of Incentive Compatible Contracts in the TI

1

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01 2 3 4 5 6 7 8 9

Period10


Average Profits in TI

10

Average Profit Incentive ContractAverage Profit Trust Contract

1 2 3 4 5 6 7 8 9 10

5

0

-5

-10

-15

Period


Wages, Effort and Principals’ Payoff in TI

-2.4213760-7.630481798.63512956all

-6.41713030-12.01828046-20.01001high 20<w

-1.049013-1.412201339.8196126medium10≤w≤20

3.7015217n.a.n.a.n.a.n.a.08.5156829Loww<10

P´spayoff

e>1

e=1rej.#P´spayoff

e>1e=1

rej.#P´spayoff

e≥e*e<e*rej.#

Trust ContractsNon-Incentive CompatibleIncentive Contracts

Incentive CompatibleIncentiveContracts

Wage Offer


Share of bonus and incentive contracts (BI treatment) (no single trust contract)

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Share of bonus bontracts Share of incentive contracts


Average bonus as a function of effort in the BI-treatment

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rage

Bon

us35

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Effort


Average effort and average demandedeffort in the BI-treatment

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averagedemanded effortbonus contracts

averagedemanded effortincentive contracts

average effortbonus contracts

average effortincentive contracts


Average Profits in BI-Treatment

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25

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-251 2 3 4 5 6 7 8 9 10

Average Profit Incentive ContractsAverage Profit Bonus Contracts


Average wages and average bonus over time in the BI treatment

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average bonus payment average wage in bonus contractsaverage wage in incentive contracts


What happens if principals can combine the bonus and the incentive?

Share of pure bonus and combined contracts in the Extended Bonus-Incentive treatment

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Share of pure bonus contracts Share of combined contracts


The principals’ profits over time in the Extended Bonus-Incentive treatment

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Profits in pure bonus contracts Profits in combined contracts


The agents’ income over time in the Extended Bonus-Incentive treatment

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PeriodIncome in pure bonus contracts Income in combined contracts


Average bonus payments conditional on effort in the Extended Bonus-Incentive treatment

pure bonus contracts combined contracts

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30

1 2 3 4 5 6 7 8 9 10Effort


Summary

• Fairness concerns have decisive impact on actual and optimal choice of contracts in moral hazard context.

• Principals prefer the incentive over the trust contract. The incentive contracts elicits more effort but is –overall–not more profitable.

• However, incentive compatible incentive contracts are more profitable than trust contracts and non-incentive compatible incentive contracts. – Over time principals prefer incentive compatible trust

contracts over non-incentive compatible incentive contracts.


• Principals have a strong preference for the bonus contract over the incentive contract because the former elicits much higher effort and leads to higher profits.– Creates incentives for selfish agents

• Principals also prefer the bonus contract over the combined contract.– The pure bonus contract is not more profitable than the

combined contract but workers are better off under the pure bonus contract.

– Principals who offer the pure bonus contract pay higher bonuses than principals who offer the combined contract.


Reciprocity-based material incentives and team compensation

• Team compensation like profit- or revenue-sharing typically involves a free-rider problem because a firm’s profits and revenues constitute a public good. They are therefore thought to be sub-optimal.

• But: A large fraction of the people behaves reciprocally, i.e., they are willing to increase their contributions to the public good in case that others’ increase on average their contribution as well (e.g. Fischbacher et al 2001).


• The interaction between reciprocal and selfish types often leads to the unraveling of cooperation.

• Yet, the punishment of free-riders naturally emerges even in anonymous one-shot interactions which greatly increases cooperation.– Punishments

• Social exclusion• Destruction of property• Mobbing


Public goods experiments (a snapshot)

• Stage 1:• Group of 4 players, contributions between 0 and 20

• Stage 2: Players decide simultaneously whether to assign punishment points to the other players after they observed (anonymously) how much the others contributed.

• Each punishment point reduces the Stage 1-Payoff of the punished subject by ten percent. Punishing is costly.

1(20 ) 0.4

n

i i jj

c cπ=

= − + ∑


Average contributions in finitely repeated public goods game(Source: Fehr and Gächter AER 2000)

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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20Periods

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without punishment with punishment


Repeated interaction• Material incentives created through reciprocal responses

are implicit because they are not based on contractual commitments.

• Incentives in repeated games are also implicit.• How do reciprocity-based incentives and implicit

repeated game incentives interact?– What happens in a finitely repeated (10 periods) gift

exchange game with exogenously fixed pairs? (Gächterand Falk, SJE 2002)

– What happens if subjects can voluntarily enter and exit bilateral gift exchange games for a finite number of periods? (Brown, Falk and Fehr, Ectra 2004) see below


Repeated games and reciprocity

• Gächter/Falk, SJE 2002• Firm makes a worker a wage offer• Worker accepts or rejects• Upon acceptance, she chooses an effort level

Payoffs:• If worker rejects, both get nothing• If worker accepts:

Firm:• Profit of firm: (120-w) e• Worker: U = w - c(e)


Effort levels and cost of effort

38353230282624222120c(e)

1.00.90.80.70.60.50.40.30.20.1effort


Distribution of effort in finitely repeated and one-shot gift exchange game (Source: Gächter and Falk, SJE 2002)

0.4

0.35

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.6

repeated interaction one-shot interaction


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es a

nd e

ffort

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ls1.8

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wRG/wOS eRG/eOS


• In the one-shot-treatment reciprocity is clearly observable

• In the the repeated-treatment, reciprocal patterns are observable– The difference between effort levels may roughly be

attributed to „reputation effects“• Moreover, the wage-effort relationship is steeper in the

H-treatment. This suggests that some people imitate reciprocity.

• Reciprocity and reputation are confounded.


Analysis of individual types

• Reciprocity Criterion 1 (“Reciprocity (OS)”)– A person is classified as a reciprocal type if the Spearman

rank correlation between wage and effort of that person is positive and statistically significant at the 1-percent level

• Selfishness Criterion 1 (“Egoism (OS)”)– A person is classified as a selfish type if she plays more

than half of the time (i.e., at least 6 times) the lowest possible effort irrespective of the wage she receives

• Reciprocity Criterion 2 (“Reciprocity (RG)”)– A person is classified as reciprocal if her Spearman rank

correlation between wage and effort is positive and statistically significant at the 1-percent level and if she chooses an effort level strictly larger than the lowest one in period 10


• Selfishness Criterion 2 (“Imitation”)– A person is classified as an imitator if her Spearman rank

correlation between wage and effort is positive and statistically significant at the 1-percent level and if she chooses the minimum effort level in period 10

• Selfishness Criterion 3 (“Egoism (RG)”)– A person is classified as an egoist if her Spearman rank

correlation between wage and effort is statistically insignificant at the 1-percent level and if she chooses the minimum effort level in period 10


Individual heterogeneity

20.021.420.048.053.4

‚Imitation‘‚Egoism (RG)‘

‚Egoism (OS)‘

‚Reciprocity (RG)‘

‚Reciprocity (OS)‘

Share of selfish types in percentShare of reciprocal types in percent

Share of reciprocal and selfish types and profits


Interaction of repeated games and reciprocity

• Repetition may strengthen social preferences– Successful cooperation in repeated interactions

strengthens the emotional and affective ties between the parties, i.e., they change the parties’ social preferences in a favorable way (Van Dijk, Sonnemans and van Winden, 2002: Social ties in a public good experiment; Journal of Public Economics 85, 275-299)

• Reciprocity strengthens repeated game incentives– The presence of reciprocal types generates incentives for

the selfish types to mimic the cooperative behavior of the reciprocal types so that even in finitely repeated games or in the presence of low discount factors cooperation can be sustained (Kreps, D., Milgrom, P., Roberts, J., and Wilson, R. (1982): ”Rational Cooperation in the Finitely Repeated Prisoners’ Dilemma”, Journal of Economic Theory 27, 245-252)


b) Dysfunctional effects of incentives

Main idea

• In the presence of social preferences or intrinsic motivation, the introduction of explicit incentives may increase effort to a lesser degree than predicted by the standard model

• If may even lead to lower efforts


Literature• Falk, A., Kosfeld, M., 2004. Trust and Incomplete Contracts• E. Fehr and S. Gächter, Do Incentive Contracts Crowd Out

Voluntary Cooperation?, Institute for Empirical Research in Economics, University of Zürich, Working Paper No. 34

• E. Fehr, Rockenbach, B., 2002. Detrimental effects of sanctions on human altruism, NATURE 422, 15 March 2002, 137-140

• Gneezy, U., Rustichini, A., 2000a. A Fine is a price. Journal of Legal Studies 29, 1–17

• Gneezy, U., Rustichini, A., 2000b. Pay enough or don’t pay at all. Quarterly Journal of Economics 115 (2), 791–810

• Gneezy, U. 2004. The W effect of incentives. The University of Chicago Graduate School of Business


Motivating agents

• Among all management objectives, motivating employees is one of the most important ones

• Traditional principal-agent theory offers a clear advice: Principals should motivate their agents with the help of explicit incentive contracts, promotions and other forms of material rewards or sanctions

• Assumption – All humans are selfish – Only material incentives motivate


Trust

• Idea: not all humans are selfish• Mutual trust can be decisive for work motivation• Introduction of incentives may signal distrust and

therefore backfire


Design (Falk and Kosfeld 2004)• Very simple Principal-Agent Game• Agent supplies productive activity x

– Work effort– Working time– Pieces of output– Investments

• Supplying x is costly with c(x) = x• Productive activity is beneficial for principal


Payoffs

• Agent: 120 – x• Principal: 2x

• Agent likes low x • Principal likes a high level of x• Efficiency always increasing in x

– Marginal cost < marginal benefit


Decision of the principal

• Before the agent decides on x, the principal decides whether to restrict the agent‘s strategy space or to let him decide freely.

• Restricting rules out the most opportunistic choices of the agent.

• Not restricting: x ∈ [0, 120]• Restricting: x ∈ [10, 120]

– Thus: Principal can force the agent to choose at least x = 10


Interpretation of restricting

• Minimum presence requirement • Minimum number or quality of items • Control and monitoring devices, which restrain the agent

from his most opportunistic choices


The key message of our study is nicely illustrated by the following interesting field example. In his memoirs David Packard, one of the founders of the computer company Hewlett-Packard (HP), notes:

“In the late 1930s, when I was working for General Electric …., the company was making a big thing of plant security. … GE was especially zealous about guarding its tool and parts bins to make sure employees didn’t steal anything. Faced with this obvious display of distrust, many employees set out to prove it justified, walking off with tools and parts whenever they could.”


“…When HP got under way, the GE memories were still strong and I determined that our parts bins and storerooms should always be open. … Keeping storerooms and parts bins open was advantageous to HP in two important ways. From a practical standpoint, the easy access to parts and tools helped product designers and others who wanted to work out new ideas at home or on weekends. A second reason, less tangible but important, is that the open bins and storerooms were a symbol of trust, a trust that is central to the way HP does business” (Packard 1995, pp 135-6)


Predictions

• Standard prediction– If principal does not restrict: x = 0– If principal does restrict: x = 10– Principal will restrict

• Alternative hypothesis: Restriction perceived as a signal of distrust– Agent must believe that principal does not trust him to

deliver more than 10– Negative behavioral response– It can pay not to restrict


Experimental details

• Participants randomly in the role of agents and principals• 144 participants, 72 agents, 72 principals• Students at University of Zurich and ETH Zurich• Computerized program: z-tree (Fischbacher 1999)• Duration of experiment 45 minutes• 1 point equals 20 Rappen• 10 CHF show up fee


Results: Agents

Table 1: Agents’ offers dependent on the principals’ restriction decision

Principal does restrict Principal does not restrict

Average offer 17.5 23.0

Median offer 10 20

Standard deviation 13.57 17.97

Number of observations 72 72

Wilcoxon signed rank test p < .001

• Trust pays on average• But: not all reward the trust


All x-decisions

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tive

freq

uenc

y

0.6

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16 22 5014 18 20 24 26 28 30 32 34 36 4810 4412 38 40 42 46

Agents

restricted not restricted


Cumulative distribution of x

00.10.20.30.40.50.60.70.80.9

1

0 5 10 15 20 25 30 35 40 45 50

x

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ulat

ive

frequ

ency

not restricted restricted


Cost and benefits of restricting

-35

-30

-25

-20

-15

-10

-5

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1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70

agents

x-ch

oice

if re

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if no

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Effects of restrictingpositive: 25 percentneutral: 18 percentnegative: 57 percent


Heterogeneous types

8.332.320.30.0Mean if not restricted

16.318.721.010.1Mean if restricted

4572118percent

3411513n

OtherDistrust averse

Inequity averseSelfish


Principals

• Principals– 70.8 percent do not restrict– 29.2 percent do restrict

• Expectations of principals quite accurate– Pessimistic principals do restrict (Median=10)– Optimistic principals do not restrict (Median=25)

• Expectations on average confirmed• Firm cultures as self-fulfilling prophecies


Cumulative distribution of principals’ belief about x, dependent on their decision to restrict or not to restrict

00.10.20.30.40.50.60.70.80.9

1

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x

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principal does not restrict principal restricts


Distrust aversion as a motive (n=72)

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The restriction by the principal signals that he does not trust me to transfer a positive amount.

I transfer less if the principal thinks I am not trustworthy compared to if he thinks I am trustworthy.


Distrust aversion in „the field“: Questionnaire evidence

• Situation 1: You began a new vacation job in a supermarket. Your task is to check the balances in the cash registers in the evening, meaning that you examine whether the amounts of money in the cash registers correspond with the entries. In theory, you could easily swindle the supermarket by simply removing money from the cash register.


– Condition 1: You examined the cash registers conscientiously and without cheating, and reported the results honestly. You realize on the way home that you forgot your umbrella. When you enter the supermarket, you see that the manager is again examining the amounts in the cash registers, as if he undoubtedly mistrusts you.

– Condition 2: You examined the cash registers conscientiously and without cheating, and reported the results honestly. You realize on the way home that you forgot your umbrella. When you enter the supermarket, you meet the manager, who is leaving for the day. He wishes you a pleasant evening.


• Situation 2: You have a new job. Your boss explains your tasks to you as well as the amount of work expected of you.– Condition 1: Before starting your work, you have to

sign a binding agreement. This defines your working times exactly.

– Condition 2: Your boss asks you to follow the work times exactly.


• Situation 3: During a job interview, you presented your knowledge, experience, and qualifications truthfully. You provide your previous employer as a reference who could confirm your information.– Condition 1: The new employer believes your

information and hires you.– Condition 2: Your new employer does not hire you

until he has gathered information about you from your previous employer and confirmed the accuracy of your information.


Distrust aversion in „the field“: questionnaire evidence

0.150.500.030.080.060.29very high

0.400.470.270.470.140.58high

0.360.030.440.350.330.13middle

0.080.000.240.090.370.00low

0.010.000.010.010.100.00very low

Employer consults

references (no trust)

Employer believes

statements (trust)

Formal agreement

(no trust)

Asked to meet

obligations (trust)

Manager controls

(no trust)

Manager does not control (trust)

Work motivation

Situation 3job interview

Situation 2working times at new job

Situation 1checking cash registers at

supermarket

“How high is your work motivation?” (n=144)


Conclusions

• Trust important for motivation• Explicit incentives as signal of distrust• Can be optimal not to use incentives• Depends on frequency of types


Reciprocity driven voluntary cooperation and explicit incentives

• Fehr/Gächter (2000)

• Principal offers contract (w, ê, f):w ∈ [0, 100]: fixed wagee ∈ [0.1, 1]: desired effort0 ≤ f ≤ 13: wage reduction in case of detected

shirking e < ê(detection probability 1/3)

• Agent can accept or reject the contract; if accepted: Agent chooses actual effort e ∈ [0.1, 1]

cost of c(e); c(0.1) = 0; c‘(e) > 0; c‘‘(e) > 0


Payoffs

• Principal:

• Agent:ˆ( ) if contract accepted and ˆ( ) (1/ 3) if contract accepted and

0 if contract rejected

w c e e eu w c e f e e

− ≥= − − <

<+−≥−

=rejectedcontractif0

ândacceptedcontractif)3/1(100ândacceptedcontractif100eefweeewe

π


Predictions

• Agent chooses e = ê only if (1/3)f ≥ c(ê)• In general:

• Agent accepts the contract only if w ≥ c(e*)• In the experiment: 0 ≤ f ≤ 13 („limited sanction

possibility“)The maximal enforceable effort is ê = 0.4

• Efficiency-enhancing e > 0.4 only possible with „voluntary cooperation“

≥<

=

)()3/1(:, allfor )()3/1(:, allfor 1.0

*êcfêfêêcfêf

e


Hypotheses

• Incentive contracts do not influence reciprocity-based voluntary cooperation

• Incentive contracts ”undermine” voluntary cooperation


Experimental Procedures

• 2 treatments:– Trust treatment (TT): (w, ê)– Incentive treatment (IT): (w, ê, s)

• 126 subjects• 6 Principals, 8 Agents in two rooms• Manually conducted at the University of Zürich• „posted bid market“; more agents than principals

competitive pressure• 12 Periods


• Effort is lower in the IT compared with the TT. This is due to the following reasons: – A fraction of agents shirks in the IT even when the No-

Shirking Condition (NSC) is met (ITÎC)– Voluntary cooperation (e – e* > 0) vanishes almost

completely for incentive compatible contracts in the IT – If the NSC is violated in the IT agents choose the minimum

effort in the vast majority of cases – In the TT effort levels above the minimum are provided in

the majority of cases– In the TT voluntary cooperation responds strongly to the

wage level while in the IT voluntary cooperation does no longer respond to the wage level


Voluntary cooperation

-0.1

0

0.1

0.2

0.3

0-10

11-2

0

21-3

0

31-4

0

41-5

0

50+

0-10

11-2

0

21-3

0

31-4

0

41-5

0

50+

0-10

11-2

0

21-3

0

31-4

0

41-5

0

50+

Intervals of offered wages

Volu

ntar

y co

oper

atio

n (e

-e*

) period 1-4 period 5-8 period 9-120.7

0.6

0.5

0.4

TTIT^NICITÎC


Evolution of wages

0

510

15

20

2530

35

40

1 2 3 4 5 6 7 8 9 10 11 12

Period

Ave

rage

wag

e

TrustIncentive


Voluntary cooperation in period 1

-0.3-0.2-0.1

00.10.20.30.40.50.60.70.80.9

0 20 40 60 80

Offered wage

Volu

ntar

y co

oper

atio

n (e

-e*)

-0.3-0.2-0.1

00.10.20.30.40.50.60.70.80.9

0 20

Volu

ntar

y co

oper

atio

n (e

-e*)

Trust Incentive

40 60 80

Offered wage


Why is there an undermining of voluntary cooperation?

• The redistributive effect of the fine may undermine voluntary cooperation?

• The explicit ex-ante threat to punish is perceived as a hostile action and reciprocal workers respond with hostility (shirk a lot) to hostile actions.– Does negative framing (“fine”) induce hostility?


100e – w + f

100e – w

w – c(e)

w – c(e) – f

Inequity aversion and effort choice

eeef

effort


Does the framing of incentives matter? The Bonus contract

• „Bonus contract“: If e ≥ ê a bonus of 0 ≤ b ≤ 13 will be paid; if e < ê the bonus will be paid with probability 2/3:

identical incentive structure to the sanction contractonly a different framing

<+−≥+−

=rejectedcontract if0

and acceptedcontract if)3/2()( and acceptedcontract if)(

êebecwêebecw

u


Framing of incentives and voluntary cooperation

-0.1

0

0.1

0.2

0.3

0.4

0.5

0.6

0.70-

10

11-2

0

21-3

0

31-4

0

41-5

0

50+

0-10

11-2

0

21-3

0

31-4

0

41-5

0

50+

0-10

11-2

0

21-3

0

31-4

0

41-5

0

50+

Interval of offered compensation (w(+b))

Volu

ntar

y co

oper

atio

n (e

-e*

)

Trust Treatment

Incentive Treatment

Bonus Treatment


Offered contracts, Profits and Efficiency

Incentive compatible contracts Mean Payoffs and EfficiencyNIC IC

• Trust:- Agents: 25.7 - Principals: 7.1

• Sanctions:- Agents: 19.6 9.1- Principals: 1.8 18.2

• Bonus:- Agents: 17.6 11.6- Principals: 7.3 8.8

20%

30%40%

50%

60%

70%

Perc

ent

10%

0%1 2 3 4 5 6 7 8 9 10 11 12

Period

Bonus-Treatment Sanction-Treatment


• If the use of a “hostile” incentive destroys voluntary cooperation, then the deliberate non-use of a hostile incentive may be perceived as a kind action and may, hence, increase voluntary cooperation.

• Experimental test: Trust Experiment by Fehr and Rockenback (Nature 2002)


Design

• Investor and a trustee receive 10 DM• Investor can send any amount between 0 and 10 to the

trustee• Each DM sent is tripled by the experimenter• Investor also announces a desired back-transfer• Trustee is free to send back any amount• Back-transfer is not tripled

– “Investment game” by Berg, Dickhaut, McCabe (1997)• Two treatments, a trust treatment and a punishment

treatment • In the punishment treatment the trustee’s payoff is

reduced by 4 DM if she sends back less than desired


Table 1. Average behaviour and average payoffs of investors and responders

Trust condition Incentive condition: fine chosen

Incentive condition: no fine chosen

Investment (x) 6.5 6.8 8.7

Desired back -transfer in percent of tripled investment (?/3x)

59.9 67.4 63.7

Actual back -transfer ( y) 7.8 6.0 12.5

Actual back -transfer in percent of tripled investment ( y/3x)

40.6 30.3 47.6

Actual back -transfer in percent of desired back -transfer ( y/? ) 74.38 54.50 74.08

Investor’s payoff 11.3 9.2 13.8

Responder’s payoff 21.8 22.4 23.5

Number of observations 24 pairs 30 pairs 15 pairs


• The average back-transfer of the responders as a function of the investors’ transfers – In the trust condition and the incentive condition the back-

transfers of the responders increase in the investors’ transfers – irrespective of whether the fine is imposed or not

– If the investors impose a fine in the incentive condition responders reduce their back-transfers indicating a detrimental effect of the incentive on cooperative behavior

– Responders’ back-transfers are highest if the investor deliberately refrains from imposing the fine


The average back-transfer of the responders as a function of the investors’ transfers

16Incentive condition - fine imposed

Ave

rage

bac

k-tr

ansf

er o

f tru

stee 14

Trust condition - no fine possible

Incentive condition - fine not imposed12

10

8

6

4

2

00-1 2-4 5-7 8-10

Transfer of investor


• Actual back-transfer in percent of tripled investment as a function of the investors’ desired back-transfers– The desired back-transfer is categorized as low if, in case

that the responder meets this back-transfer, it implies that the investor earns the same or less than the responder, it is categorized as high if the investor earns more than the responder

– At low desired back-transfers the sanctioning threat reduces actual back transfers in the incentive treatment but the effect is not significant. At high desired back-transfers the sanctioning threat has a large negative impact on the actual back-transfers in the incentive condition indicating that if sanctions are used to achieve a distributional advantage they strongly undermine cooperation


Actual back-transfer in percent of tripled investment as a function of the investors’ desired back-transfers

0

10

20

30

40

50

60

70

Act

ual b

ack-

tran

sfer

in p

erce

nt o

ftr

iple

d in

vest

men

t

Incentive condition - fine not imposed

Trust condition - fine not possibleIncentive condition - fine imposed

low high

Desired back-transfer


Students vs. CEOs

• Fehr and List (forthcoming JEEA) performed a similar study as Fehr/Rockenbach (2002)

• Both principal and agent receive endowment of 10• Trust treatment

– Principal offers any amount x between 0 and 10, which is triplicated

– Principal states a desired pay back– Agent decides on payback between 0 and 3 x

• Punishment treatment– Principal can threaten to punish agent if payback < desired

payback (fine either 0 or 4)– Fine not given to the principal


• Standard prediction:Principal can enforce x = 3 or 4 in the punishment treatment and 0 in the trust treatment

• Comparison of students and CEOs from Costa Rica• Important to study behavior of higher level decision-

makers• 126 students, 76 CEOs from the coffee mill sector who

attended THE COSTA RICA COFFEE INSTITUTE’S annual conference in March 2001

• All anonymous interaction (single blind)• Earnings: CEOs $65, Students $5.65


Results

• CEOs transfer more money than students• For a given transfer, CEOs pay back more than students• Not using the fine-option in the punishment treatment

leads to higher back transfers than in the trust treatment (where the option is not available)

• CEOs use the punishment option less often than students


Back-transfers of CEOs and Students in the Trust Treatment

0

2

4

6

8

10

12

14

0 to 5 6 to 8 9 and 10

Age

nt's

bac

k-tr

ansf

er

Transfer of the principal CEOs Students


Back-transfers of CEOs and Students in the Punishment Treatment

0

2

4

6

8

10

12

14

16

0 to 5 6 to 8 9 and 10

Transfer of the principal

Age

nt's

bac

k-tr

ansf

er

StudentsCEOs


The Impact of the Punishment Threat on CEOs’ Back-transfers

0

2

4

6

8

10

12

14

16

18

0 to 5 6 to 8 9 and 10Transfer of the principal

Age

nt's

bac

k-tr

ansf

er

Punishment used Punishment available; not used No punishment available


The Impact of the Punishment Threat on Students’ Back-transfers

0

2

4

6

8

10

12

14

16

18

0 to 5 6 to 8 9 and 10

Transfer of the principal

Age

nts

back

-tran

sfer

Punishment used Punishment available; not usedNo punishment available


Two Field studies Gneezy and Rustichini “Pay Enough or Don’t Pay At

All,” QJE, 2000

• Test of monetary incentives on performance• 160 students received a show-up fee of NIS 60• To solve 50 quiz problems (IQ-test) in 45 minutes• Subjects divided into four groups (treatments)• Treatments differ with respect to the marginal payoff for

a correct answer– Nothing (asked to answer as many questions as they can)– 10 cents of a Shekel– 1 Shekel– 3 Shekels


Summary statistics for the number of correct answers by treatment

0%0%27.5%15%Less than 16

2526020Aver. worst 10

43443540Aver. top 10

37372631Median

991514Standard dev.

34352328Average

3 Shekels1 Shekel10 centsNo payment


• Mann-U-Tests for significance of results (pair wise comparisons), p-values

.6964.0006.07083 NIS

.0004.06871 NIS

.087510 cents

1 NIS10 centsNo pay


• How well could people predict the behavior of the subjects in the IQ and donation studies?

• Participants were promised a payment proportional to the performance of “their agent,” and had to choose the incentive scheme for the agent

• 87% chose to be matched with agents who were paid 10 cents over unpaid agents

• Wrong anticipation of detrimental effects of incentives


• Second experiment• 180 high school students• Go from house to house to collect donations for

charitable organizations (typical volunteer work on a particular day each year)

• Divided into three groups (treatments)– No pay: Small speech recalling the importance of the

activity– Speech + Promise of 1 percent of collected money– Speech + Promise of 10 percent of collected money

• Money paid by experimentalists


• Significant differences (10 percent) between No/1percent and 1percent/10percent

• As before, “principals” chose the wrong incentive (76 percent choose the 1 percent incentive)

180150200median

219.3153.6238.6average

10 percent1 percentNo payMoney raised


Gneezy and Rustichini (2000) “A Fine is a Price” Journal of Legal Studies, 2000

• Suppose you are a daycare manager• The problem: Parents come late to collect their child• The solution: A fine • To test this solution, experimental study in Israeli day-

care centers


Background

• The contract signed at the beginning of the year states that the day-care center closes at 4.00 p.m

• No mention of sanction• Late coming is a problem


Organization of the field study

• 20 weeks • 10 day-care centers • 6 treatment, 4 control groups

Control group: Register the # of late coming parents

Experimental group:

no finefineno fine

Period 3(weeks 17-20)

Period 2 (weeks 5-16)

Period 1(weeks 1-4)


• The fine was 10 NIS – For a delay of 10 minutes or more– Per kid

• It was removed without any explanation


Average number of late-arriving parents each week, by group type

0

5

10

15

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

week number

No

.of l

ate

arriv

als

25

20

Control groupGroup with fine


• In first four weeks no significant difference between treatment and control group

• In treatment group increase in late-comings after fine is introduced

• Rate finally settled at an almost twice as high level as the initial one

• Removing the fine did not affect the number of late-coming; higher than in control group


Two further questions

• Is the detrimental effect of sanctions or incentives monotonous?

• What if the incentives get stronger?

• What if positive and negative incentives are used in one experiment (only one word is changed in the experiment)

• Study by Geneezy (2004)


Design: A Proposer-responder game (Andreoni, Harbaugh and Vesterlund, 2003)

• Stage 1: Proposer decides what portion of $24 she wants to transfer to the responder (between $4 to $24)

• Stage 2: Responder’s reaction – 5 treatments


Pay 1 cent for a 5 cent increaseHigh Reward

Pay 1 cent for a 1.5 cent increaseLow Reward

Pay 1 cent for a 5 cent decreaseHigh Punishment

Pay 1 cent for a 1.5 cent decrease in proposer´s payoffLow Punishment

NoneDictator

Responder‘s choiceTreatment

• Between subjects• In each treatment 40 proposers and 40 responders

(400 participants)• Anonymity


4

6

8

10

12

14

High Fine Low Fine Dictator Low Reward High Reward

Treatment

Offe

rs in

$


Proposers’ behavior

HighFine

LowFine

Dictator LowReward

HighReward

Average 10.4 6.9 9 7.2 12.7

Standard dev. 3.8 3.5 4.3 3.6 7.5

Median 12 4.5 10 4 12

Average top 20 offers 12.6 9.8 12.3 10.3 18.3

Standard dev.top 20 offers 2.7 2.7 2.8 2.3 5.9

Fraction of $4proposals 17.5% 50% 32.5% 52.5% 27.5%


Proposals: High Fine vs. High Rewards

High FineHigh Reward

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Offers in $

Frac

tion


Average payoff Proposer

Average payoff Responder

6

8

10

12


Treatment

Payo

ffs in

$

10

12

14

16

18

20

22


TreatmentPa

yoffs

in $


Joint payoff

Proposer’s share

0.5

0.55

0.6

0.65

0.7

0.75


Treatment

Prop

oser

s' s

hare

$

20

22

24

28

30

32

34


Treatment

Join

t pay

offs

in $

26


Possible reasons for negative effect of incentives (see discussion in Gneezy 2004 and Fehr/Falk EER 2002)

• Information (Learning about negative implications)• Distrust• Insult (Sex for money)• Fairness: payoff consequences• “Cooperation and social norms” vs. “exchange”• Signaling (Benabou/Tirole-story)• Crowding out of intrinsic motivation


c) Peer effects

Main idea• Individual behavior affected by behavior of peers:

independent of economic incentives• Phenomenon called: social interaction effects, peer

effects or neighborhood effects

• Potentially relevant for labor relations– Shirking and absenteeism– Job search– Cooperative behavior in teams


Literature

• Falk, A., Ichino, A. 2003. Clean evidence on peer effects. IZA Discussion paper 732.

• Ichino A. and G. Maggi, 2000. Work Environment and Individual Background: Explaining Regional Shirking Differentials in a Large Italian Firm. Quarterly Journal of Economics 115 (2000), 1057-1090.

• Zajonc, Robert B., “Social Facilitation”, Science 149 (1965), 269-274.


Falk/Ichino (2003) The paper in one slide

• Is individual behavior affected by peer effects?

• Confounding factors limit the possibility to answer this question with observational data

• Field experiments allow to obtain clean evidence– We measure the output of subjects who were asked to

stuff letters into envelopes• We find that:

– Outputs of workers who work in pairs are similar– Average output is higher for subjects working in pairs than

for subjects working alone– Peer effects depend on productivity


Why study peer effects?

• Peer effects have shown to be important for – Criminal behavior [Glaeser, Scheinkman and Sacerdote

1996]– Dynamics of urban poverty and crime [Case and Katz

1991; Ludwig, Duncan, and Hirschfield 2001; Katz, Kling, and Liebman 2001]

– Welfare participation [Bertrand, Luttmer, and Mullainathan2000]

– Absenteeism [Ichino and Maggi 2000]– Academic success [Sacerdote 2001]


Peer effects and confounding factors

• Consider two individuals working on separate tasks one in sight of the other and suppose that they behave similarly

• It could be peer effects: the output of i increases when the output of j increases and nothing else changes

• It could be due to confounding factors like:– “local attributes”– “similar personal attributes”– “sorting”


Literature• Recent studies on peer effects with observational data

made important progress– e.g.: Wilson [1987], Case and Katz [1991], Crane [1991],

Glaeser et al. [1996], Topa [1997], Encinosa et al. [1998], Aaronson [1998], Van Den Berg [1998], Bertrand et al. [2000], Ichino and Maggi [2000]

• Sacerdote [2001] and Katz et al. [2001]: randomized assignments of individuals to peer groups

• Lab experiments: Falk et al. [2002], Falk and Fischbacher[2000]

• Main differences to our approach:– cannot fully control for local attributes– attention is not directed to a work environment


Design: Recruitment

• High school students from different schools in Winterthur(Switzerland)

• Announcement posted on blackboards:– a simple side job requiring no previous knowledge– job is a one-time four hour job, which is paid 90 Swiss

Francs (1 Swiss Franc ≈ .70 US or ≈ .70 EURO)• Attractive payment: within 24 hours, we were able to

recruit all the subjects we had planned to recruit.• Date: spring vacations of 2002 • Location: a high-school building in Winterthur


Design: Procedure and task

• Upon arrival subjects were informed:– about the task and the procedural details– that they had to work for four hours– that they would be paid in the end, in cash and

independently of output• Task: stuff letters into envelopes for a questionnaire

study


The desk


Treatments

• Pair treatment: – Two subjects do the task at the same time in the same

room– The two desks are standing next to each other, subjects

can easily realize each other’s output– Peer effects possible– 16 subjects (8 pairs)

• Single treatment: – Each subject does the task all alone – Peer effects are ruled out by design– 8 subjects


Methodological aspects

• Unlike most lab experiments that study work behavior, our subjects performed a “real” task

• Only recently “real effort” experiments to study incentive mechanisms and efficiency wages: e.g., Fahr and Irlenbusch (2000), van Dijk et al. (2001), Gneezy (2002)

• Our study is unique insofar as subjects performed a regular and economically valuable job


Operationalizing peer effects

• xi = θi + βxj

– x = output player i and j– θi = player i’s innate productivity– β = strength of peer effects: measures how the output

of i depends on the output of j in a pair

• In equilibrium (partner treatment): xi = (θi + β θj)/(1-β²)• Single treatment: xi = θi


Three predictions

• In the presence of peer effects, output is “similar” in pairs

• In the presence of peer effects, output is higher in the pair compared to the single treatment– Compare social facilitation paradigm (Zajonc 1965)

• Less productive subjects are affected more strongly by peer effects compared to more productive subjects


P

S

Xi

Xjθj

θi

45°

Xi = θi + β XjXj = θj + β Xi

Xip

s

sXi =

Xj = PjX

P = PairS = Single


Output in groups is similar

0

50

100

150

200

250

300

pair 1 pair 2 pair 3 pair 4 pair 6 pair 5 pair 7 pair 8


Testing the similarity of output in pairs

• In the absence of peer effects, the standard deviations within true pairs should be identical to those generated by random configurations of hypothetical pairs constructed from the same group of people

• Comparing the standard deviations of the true and the hypothetical pairs allows constructing a test for the similarity of outputs



Output is higher in pair treatment

• Average output – single treatment: 190– pair treatment: 221

• Sizeable difference: 16.3 percent• Difference is statistically significant

– p-value = 0.068 in regression-based test– p-value = 0.049 in Wilcoxon one-sided rank sum test


Less productive subjects are affected more strongly by peer effects

3420717325th

926525690th2323621375th1821219450th

4217513310thdifferencepairsingleQuantile

Quanitles of the output distribution

• Difference between quantile outputs declines • Spearman rank correlation between these differences and

corresponding productivity levels is negative and significant (Spearman’s rho = -0.900, p= 0.018)


An estimate of β

• In the two treatments the outputs of subject i are respectively

Xpi = (θi + βθj)/(1 − β2)Xsi = θi

• Substituting the sample averages xp and xs, we can compute β solving:

• xp = (xs + βxs)/(1 − β2) → 221 = (190 + β190)/(1 − β2)• The implicit estimate is β = 0.14

• Comparable estimates in Maggi and Ichino (2002) with observational data are β = 0.14, β = 0.18 and β = 0.15 depending on controls and specifications


Conclusions

• In a controlled field experiment – behavior of subjects is strongly affected by peer effects– peer effects raise average productivity– less productive workers are more sensitive to peer effects

than more productive ones• Peer effects robust even though subjects interacted only

once and did not know each other• Implications for optimal allocation of low and high

productivity workers• Possible extensions:

– repeated interactions– different incentive schemes


Is cooperative behavior in teams affectedby the cooperativeness of co-workers?

• Tested by Falk, Fischbacher and Gächter 2002

• Public goods experiment, with groups of 3• Subjects get an endowment of 20 tokens.• Subjects can contribute ci to a project.• Payoffs:

– Dominant strategy to contribute 0.– Efficient to contribute 20, “effort” is positive externality

∑+−=j

jii cc 6.020π


• Each subject acts in two distinct, economically identical groups.

• If social interactions/peer effects matter: A subject contributes more in team A than in team B, if the others in A contribute more than the others in B.


Each subject is simultaneously in two groups

• 9 subjects form an “interaction group”• Each subject can contribute to public

goods in two groups of 3 persons each; Group 1 and Group 2

• Payoffs:

• Public goods are economically identical and independent

1 2 3

4 5 6

7 8 9 ∑∑==

+−++−=3

1

223

1

11 6.0)20(6.0)20(k

kij

jii ccccπ


A sample screen


Experimental Procedures

• Repeated 20 times; “Partner”-design.• Experimental software z-Tree (Fischbacher ’99).• Experiments conducted at University of St. Gallen.• Average earnings 41 CHF ≈ € 28 for 90 min.• 126 subjects, 14 independent obs.• 3480 contribution decisions.• Design controls for (Manski 2000):

– Self selection– Correlated effects (groups econ. ident.)– Contextual effects (random composition of group,

anonymous)


Subjects condition their behavior on behavior of others

-20

-15

-10

-5

0

5

10

15

20

-20 -15 -10 -5 0 5 10 15 20

Difference between Group1 and Group2 in contributions of other group members in the previous period (g1-g2)

Diff

eren

ce in

cur

rent

con

trib

utio

ns (c

1-c2

)

c1-c2

45°


The probability of contributing more to Group 1 or more to Group 2 (or the same)

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

[-20,-10) [-10,-6) [-6,-4) [-4,-2) [-2,0) 0 (0,2] (2,4] (4,6] (6,10] (10,20]

Difference between group 1 and group 2 contribution in previous period

Pr[ more in group 2] Pr[ same in both groups] Pr[ more in group 1]


Temporal stabilityc1

-c2

Graphs by Periodg1-g2

period==1

-20

-10

0

10

20period==2 period==3 period==4 period==5

period==6

-20

-10

0

10


period==11

-20

-10

0

10


period==16

-20 -10 0 10 20-20

-10

0

10

20period==17

-20 -10 0 10 20

period==18

-20 -10 0 10 20

period==19

-20 -10 0 10 20

period==20

-20 -10 0 10 20


The interaction groupsD

iffer

ence

in c

urre

nt c

ontri

butio

ns (c

1-c2

)

Between-group contribution difference of other members (g1-g2) in t-1

matchinggroupid==1-20 -10 0 10 20

-20

-10

0

10

20




-20

-10

0

10

20

matchinggroupid==5

-20

-10

0

10

20

matchinggroupid==6 matchinggroupid==7 matchinggroupid==8

-20

-10

0

10

20

matchinggroupid==9

-20

-10

0

10

20

matchinggroupid==10 matchinggroupid==11

-20 -10 0 10 20

matchinggroupid==12

-20 -10 0 10 20-20

-10

0

10

20

matchinggroupid==13

-20 -10 0 10 20-20

-10

0

10

20

matchinggroupid==14

-20 -10 0 10 20-20

-10

0

10

20


A field study

• Ichino/Maggi (QJE, 2002) analyze absenteeism among workers of a big Italian bank

• The prevalence of shirking within a large Italian bank appears to be characterized by significant regional differentials

• The average number of absence episodes officially registered as “due to illness” in a given year is:– 1.90 for the north– 2.91 for the south

• The average frequency of employees punished by the Personnel Office in a given year because of a misconduct episode is:– 0.7% for the north– 1.5% for the south


• The difference in the incidence of absenteeism and misconduct between north and south is the fact that is tried to be explained in Ichino/Maggi

• Note that:– the differences are not driven by outliers;– they hold also for days of absence and severity of

misconduct;– more than 95% of these employees are white collars;– the data have been collected for a different research

project


The firm under consideration

• A large bank with 442 branches disseminated all over the Italian territory and with an almost century-long tradition of activity at the heart of the Italian financial system

• Between 1975 and 1995: 28,642 employees have worked at this bank

• Approximately 73% of total employment is concentrated in the north, where the head-quarters of the firm are located, but the presence of the firm in the south has always been significantly increasing

• Employment by region of birth is more uniform, given the migration flows of the ’50s and ’60s


• Employees work predominantly in the region in which they are born, but 3304 migrated at least once from south to north and 934 migrated in the opposite direction between the year of birth and the year in which they are observed on the job

• There is also a significant number of employees (41%) who moved at least once from one branch to another while working at the bank


Indicators of shirking

• Absenteeism– Yearly number of absence episodes due to illness

observed between 1993 and 1995• Misconduct episodes:

– Episodes recorded and punished by the personnel office between 1975 and 1995 according to a procedure established by collective bargaining and by the Statuto deiLavoratori:

• Unjustified absence and late arrivals• Actions taken by the worker outside the relationship with the

bank, but potentially relevant for the latter• Violations of the internal regulations of the bank• Inappropriate behavior inside the workplace


Potential explanations of the shirking differentials

• Individual background– South-born and north-born employees may have different

preferences, and in particular different degrees of disutility from work

– Social and familial influences in the birth environment– Preferences correlated with individual characteristics

• Sorting– Hardworking individuals may tend to migrate to the north, and/or

lazier individuals may tend to migrate to the south– Choice of the individual or the family– Choice of the management

• Exogenous local attributes– Exogenous local attributes may make the incentive to shirk or

the likelihood that shirking is discovered higher in the south


• Environmental amenities– Availability of fake certificates for absenteeism– State of the local economy for misconducts– Efficiency-wage effects (Shapiro and Stiglitz, 1984)

• Group-interaction effects– A worker may be more tempted to shirk when more

coworkers shirk around him– Peer monitoring system– Psycho-sociological effects– Limited monitoring resources available to the management


• Discrimination– Shirking differentials could be due to discrimination against

southern employees in the implementation of personnel policies

– Discrimination in careers and wages– Discrimination in the identification of misconducts

• Hiring policy– If hiring were based on local decisions, the evidence could

imply that the hiring process is more selective in the north, leading to a higher quality workforce in the north


The analysis suggests

• Individual-background effects• Group-interaction effects• Sorting effects

– contribute together to explain the north-south shirking differential;

• Local attributes as a whole appear to push toward higher shirking in the north; however, this overall effect is driven by a few localvariables (most notably, local unemployment)

• None of the other explanations has first-order importance• Group-interaction effects contribute to explain the north-south

differential not by generating multiple equilibria, but by amplifying the effect of differences in individual background


d) Loss aversion, collusion and sabotage in the presence of tournament incentives

Main idea• Non-standard factors may dampen the power of

incentives• Loss-aversion, collusion and sabotage activities may in

particular limit the power of tournament incentives


Literature

• Falk, A., Fehr, E. 2002. The Power and Limits of Tournament Incentives, unpublished manuscript.

• Bull, C., Schotter, A., Weigelt, K., 1987. Tournaments and piece rates: an experimental study. Journal of Political Economy 95, 1 – 33.

• Harbring, C., Irlenbusch, B., 2003. An experimental study on tournament design. Labour Economics 10, 443–464.


Tournament incentives• Rank order tournaments have received a lot of theoretical

attention, starting with Lazear and Rosen (1981)• Idea: Group of agents compete for a fixed set of prizes• Very popular:

– Firms “primarily provide incentives through the prospect of promotion” (Prendergast 1999)

– Little pay variation within but across job grades (Baker/Gibbs/Holmstrom 1994)

• Attractive features– Applicable if impossible to contract on effort– Require only information on relative performance– Avoid possibility of reneging on wages as in subjective

performance evaluation (commitment to prize structure)


Research Questions

However: Important potential drawbacks• Do agents really respond to tournament incentives?• Dysfunctional behavioral responses: Sabotage (Lazear

1989)?• Psychological motives limit the power of tournament

incentives: Loss aversion?• Collusion?• Do principals optimally respond to agents’ behavior by

setting the right tournament incentives?


Why Experiments?Answering these questions requires:• Control about level and cost of chosen effort• Control about strength of incentives• Precise prediction

• Systematic ceteris paribus variation of the strategic environment:– Sabotage vs. no sabotage– Possibility of loss vs. no loss– Repeated vs. one-shot interaction– Repeated interaction with and without communication

• Ideally fulfilled in lab experiments and hardly to achieve with field data


Related Literature

Theoretical progress has been quite substantial, however,relatively little is known empirically

– Sport tournaments, e.g., Golf (Ehrenberg/Bognanno (1990), Horse racing (Fernie/Metcalf (1999)): Do incentives matter?

– Executive compensation in firms, e.g., Main/O’Reilly/Wade (1993), Eriksson (1999): Prize responds to number of agents.

– Experiments, e.g., Bull/Schotter/Weigelt (1987), Schotter/Weigelt (1992), Harbring/Irlenbusch (2002a,b), Harbring/Irlenbusch/Kräkel/Selten (2002), Harbring (2002)


The basic design: First Stage (1) (Falk/Fehr 2003)

• Sequential, two stage, three player game• 1st Stage

– One principal faces two agents– Principal chooses a contract, which defines the

tournament incentives


The basic design: First Stage (2)

Contract ∆ = wh-wWage for higher output ( wh)

Wage for lower output ( wl)

l

1 150 150 02 160 140 203 170 130 404 180 120 605 190 110 806 200 100 1007 210 90 1208 220 80 140


The basic design: Second Stage

• Agents see contract chosen by principal• Agents simultaneously choose an effort level e with e ∈ [1,

1.5, 2, …, 12]• Convex effort costs: c(e) = (1-e)2

• Output agent i: yi= ei + εi, where εi is an evenly distributed random number on the interval [0, 10]


The basic design: Payoffs

Principal:

π= α(yi + yj), with α = 8

Agent:

wh – c(ei) if yi > yj

Ui = wl – c(ei) if yi < yj

0.5 wh + 0.5 wl – c(ei) if yi = yj


The basic design: Information conditions

• Principals only informed about outputs, not efforts• Principals and agents informed about their own payoffs• Payoff functions of agents commonly known• Payoff function of principals only known by principals

(qualitatively by agents, reason: fairness)


The basic design: Procedures

• Roles as principal or agent randomly determined, no role reversal

• Stationary replication for 12 periods• In each period, principals and agents randomly matched

into groups of three• Control questions to check understanding• Anonymity• Computerized, software z-tree (Fischbacher 1999)• 300 Participants (non econ. students ETH, UniZh)• Average earnings 56 Franks (incl. show up)


Treatments• Baseline (B)• Sabotage (S)

- As B, plus sabotage (binary decision)- Sabotage: reduce the other agent’s output to zero at a cost

of c(s) = 27• Loss (L)

- As B, but wage sum is reduced by 160, i.e., the wage sum is 140 instead of 300

• Partner (P)- As B, but principal/agents together for 12 periods.

• Communication (PC)- As P, but agents communicate before the first and the sixth

round; Anonymity lifted


Wages in the Baseline and the Loss treatment

Baseline LossSpread w h w l w h w l

0 150 150 70 7020 160 140 80 6040 170 130 90 5060 180 120 100 4080 190 110 110 30

100 200 100 120 20120 210 90 130 10140 220 80 140 0


Treatment order

• 5 sessions: Baseline1 - Sabotage• 5 sessions: Loss-Baseline 2• 2 sessions: Partner – Partner Communication• 2 sessions: Partner Communication - Partner


Predictions

e* e* and s *∆ = wh-wl

in B, L, P and PC in S

0 1 e = 1, s = 020 2 e = 2, s = 040 3 e = 3, s = 060 4 e = 1, s = 180 5 e = 1, s = 1

100 6 e = 1, s = 1120 7 e = 1, s = 1140 8 e = 1, s = 1

∆ ∆= 140 = 40Optimal contract


Setting the stage: Mean effort dependent on spread (B-treatment)

1

2

3

4

5

6

7

8

0 20 40 60 80 100 120 140

spread

Baseline prediction


Sabotage

• Since agents are evaluated relatively– No incentive to help each other (Lazear 1989).– Sabotage other agent’s output

• In work environment: Multiple opportunities for sabotage activities– Not providing information– Erasing disk– Or…


…the case of Tonya Harding

• 1994: A man clobbered Nancy Kerrigan on the right knee with a blunt object during the U.S. National Championships. Kerrigan was the nation’s best female ice skater and top medal hope at the time

• Competitor Tonya Harding won the trial competition. But less than a week later, authorities were investigating Harding in connection with the attack

• Harding and four others were convicted and Harding pleaded guilty


Mean effort dependent on spread (S-treatment)

1

2

3

4

5

6

7

8

0 20 40 60 80 100 120 140spread

Mean EffortPrediction


Mean Sabotage behavior dependent on the spread (in percent)

0

0.2

0.4

0.6

0.8

1

0 20 40 60 80 100 120 140spread

Sabotage

Prediction


Effort choices for those who sabotage and those who don’t

8

7

6Baseline1S no sabotageS sabotage

5

4

3

2

10 20 40 100 120 14060 80

spread


Principals’ mean profits in the B- and the S-treatment dependent on the spread

0

50

100

150

200

0 20 40 60 80 100 120 140spread

Baseline1Sabotage


Relative frequency of wage spreads in the B- and the S-treatment

0

0.1

0.2

0.3

0.4

0.5

0.6

0 20 40 60 80 100 120 140spread

SabotageBaseline

0

0.1

0.2

0.3

0.4

0.5

0.6

0 20 40 60 80 100 120 140

spread

SabotageBaseline1


Loss aversion

• Relative to a given reference standard, subjects tend to value losses more than gains of equal size

• Loss aversion is behaviorally relevant (e.g., Tversky and Kahneman 1992)

• In tournaments losses are possible if investment or effort costs are relatively high compared to the wl

• In the presence of loss aversion: efforts response to spread is weaker


Agent’s payoffs in the L-and the B-treatment for predicted efforts

-100

-50

0

50

100

150

200

0 20 40 60 80 100 120 140

spread

expected Bloser Bexpected Lloser L


Loss aversion (LA-coefficient = 2)

Predictions

-25

-20

-15

-10

-5

0

5

10

15

-10 -5 0 5 10

U(x)

6.58140

57120

5.56100

5580

4460

3340

2220

110

LAno LA∆


Effort-wage spread relation in L- and B-treatmentOLS-estimates, robust standard errors, session clusters, n=1776

123456789

0 80 140spread

effo

rt

Baseline2Loss


Effort responses in the L- and the B2-treatment Dependent Variable: Effort

Model 1 Model 2 Model 3

L-treatment

B2-treatment

L-treatment

B2-treatment

L- and B2-

treatment

Spread

0.0299** (0.0056)

0.0422** (0.0049)

Low Spreads

0.0515** (0.0070)

0.0426** (0.0065)

0.0514** (0.0066)

High Spreads

0.0115 (0.0099)

0.0420** (0.0066)

0.0115 (0.0099)

Low Spreads×Treat

-0.0088 (0.0096)

High Spreads×Treat

0.0306* (0.0108)

Treat

-0.6450* (0.2282)

Period

-0.0524 (0.0413)

-0.0546 (0.0279)

-0.0641 (0.0351)

-0.0545 (0.0283)

-0.0592**(0.0107)

Constant

3.3909** (0.2343)

2.4164* (0.6380)

6.5123** (0.4458)

5.8051** (0.3033)

6.4790** (0.3005)

n 888 888 888 888 1776

Prob. > F 0.0024 0.0004 0.0025 0.0001 0.0675

R-squared 0.1480 0.1922 0.1692 0.1922 0.2133 Note: Low Spreads are all spreads ≤ 80, High Spreads are all spreads > 80. The estimation procedure is an OLS-regression with robust standard errors (in parentheses) clustered on sessions (n of clusters = 5).** indicates significance on the 1-percent level and * on the 5-percent level, respectively.


Relative frequency of wage spreads in the L- and the B-treatment

0

0.1

0.2

0.3

0.4

0.5

0.6

0 20 40 60 80 100 120 140spread

LossBaseline2


Cummulative Frequency of Spreads

0

0.2

0.4

0.6

0.8

1

0 20 40 60 80 100 120 140

SabotageLossBaseline1


Social norms and collusion

• Externalities produce demand for social norm (Coleman 1990)

• Tournament: Effort produces negative externality; norm against working

• Cooperation: e < e*.• Cooperation is not easy enforceable:

– Cooperation payoffs highly uneven (ex post)– Defection hard to detect (εi)

• No cooperation in the Baseline treatment


Repeated interaction and communication

• Finitely repeated interaction facilitates cooperation (Gächter/Falk 2002, Keser/van Winden 2000, Harbring2002; Kreps et al. 1982)– Partner treatment

• Communication: Social (dis-)approval and coordination facilitate cooperation (Ostrom/Gardner/Walker 1994, Sally 1995)– PC treatment

• Both institutional features common in real labor relations


Effort choices in the P-treatment dependent on spreads

1

2

3

45

6

7

8

0 20 40 60 80 100 120 140spread

PBaseline1prediction


Effort choices in the PC-treatment dependent on spreads

12

34

56

78

0 20 40 60 80 100 120 140

spread

PCBaseline1prediction


Relative frequency of wage spreads in the C-, the P-and the B-treatment

0

0.1

0.2

0.3

0.4

0.5

0.6

0 20 40 60 80 100 120 140spread

PCPB1


E ffo rt re sp o n se s in th e B 1 - P - a n d C -tre a tm e n t D ependen t V a r iab le : E ffo rt

M ode l 1 M ode l 2

B 1 -

tre a tm e n tP -

tre a tm e n tC -

tre a tm e n tB 1 -, P -, C -tre a tm e n t

S p read

.0 34 95** (.0 0068 )

.0 2 536** (.0 0427 )

-.0 0379 (.0 0269 )

.0 1893** (.0 0431 )

B 1 -D um m y

2 .07801** (.3 2704 )

C -D um m y

-2 .9 7103** (.4 2688 )

Pe r iod

.0 0 001 (.0 5403 )

.0 5986 (.0 3888 )

-.0 0531 (.0 3722 )

.0 3840 7 (.0 2837 )

C onstan t

2 .81807** (.4 1811 )

1 .46 30 3* * (.4 5919 )

1 .88885** (.4 1038 )

2 .22491** (.4 8322 )

n 888 468 468 1824

P rob . > F 0 .0000 0 .0002 0 .3926 0 .0000

R -squa red

0 .1737 0 .0672 0 .0078 0 .3690

n c lu s te r 5 13 13 31

N o te : The e s tim a tion p ro cedu re is an O LS -reg re ss ion w ith robust s tanda rd e rro rs ( in pa ren these s) c lu s te red on se ss ion s (B 1 -trea tm en t) o r pa rtn e r g roup (P - an d C t-trea tm en t).** ind ica te s s ign ifica n ce on the 1 -pe rcen t le ve l and * on the 5 -pe rcen t le ve l, re spective ly .


Conclusions

• Ideal environment- Tournaments create powerful incentives- Effort is monotonously increasing in spread, almost

exactly as predicted- Principals rationally respond by setting high incentives

• If sabotage is possible- Tournament incentives are counterproductive- Principals react with pay compression


Conclusions

• Potential losses relative to reference standard weaken tournament incentives (loss aversion)

• Finitely repeated interaction leads to collusion and weakens tournament incentives

• If agents communicate (social pressure and coordination) incentives are erased

• Endogenous work norms through choice of incentive (e.g.,Tournaments vs. Team)

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