Three Essays on Personnel Economics

Three Essays on Personnel Economics by Sacha Kapoor A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy Graduate Department of Economics University of Toronto Copyright c 2011 by Sacha Kapoor Abstract Three Essays on Personnel Economics Sacha Kapoor Doctor of Philosophy Graduate Department of Economics University of Toronto 2011 My dissertation focuses on the role of incentives in the workplace In Chapter 1, I study peer effects in pay-for-individual-performance jobs Specifically, I explore whether, how, and why coworker performance matters when rewards are based on individual performance When teamed with high-performing peers, I find that workers are more productive overall I also find that workers who resign are unaffected by coworker performance in the period after they hand in their resignation notice The findings suggest peer effects in pay-forindividual-performance jobs reflect reputational concerns about relative performance rather than competitive preferences In Chapter 2, I present field evidence that sheds new light on incentive provision in multitask jobs Specifically, I design and conduct a field experiment at a large-scale restaurant, where the pre-existing wage contract encourages workers to carry out their tasks in a way that is not perfectly aligned with the firm’s preferences The experimental treatment pays bonuses to waiters for the number of customers they serve, in addition to their tips for customer service and hourly wages I compare worker performance under the treatment to that under the pre-existing contract, where workers are rewarded for overemphasizing customer service, to evaluate the effect of a wage contract that encourages undesirable behavior I find that the average worker earns more, is more productive, and generates higher short-run profits for the firm when paid bonuses for customer volume Overall, the findings suggest ii that sharpening wage contracts to deal with incentive problems in multitask jobs has benefits for workers as well as the firm In Chapter 3, I present joint work (with Arvind N Magesan at the University fo Calgary) on the beauty premium’s role in the workplace Specifically, we investigate whether, how, and why the beauty premium can be explained by the behaviour of workers after they are hired We find that attractive workers earn more because they transfer effort from tasks that reward looks to tasks that reward effort We also provide evidence against favorable treatment by customers and the employer as sources for the beauty premium We conclude that the premium is largely driven by the worker’s on-the-job behavior iii Acknowledgements I thank my supervisors, Dwayne Benjamin, Gustavo Bobonis, and Nicola Lacetera for invaluable guidance during the course of this research Thanks also to the external examiner, Daniel Parent, for excellent comments and suggestions The essays in my dissertation have benefited from discussions with Victor Aguirregabiria, Iwan Barankay, Michael L Bognanno, St´ephane Bonhomme, Branko Boskovic, David P Byrne, Alain Cohn, Josse Delfgaauw, Christian Dippel, Robert Dur, Jean-Guillaume Forand, Daniel S Hamermesh, Joshua Lewis, Hugh Macartney, Arvind Magesan, Alexandre Mas, Robert McMillan, Peter Morrow, Justin Rao, Moritz Ritter, Carlos Serrano, Aloysius Siow, Robert Slonim, Jeffrey Smith, Junichi Suzuki, Trevor Tombe, and Tom Wilkening Thanks also to seminar participants at the University of Toronto, the 2010 Advances with Field Experiments Workshop, and the 2010 CLSRN Annual Conference This research was supported by the Social Sciences and Humanities Research Council and the Canadian Labour Market and Skills Research Network All omissions and errors are my own iv Contents Reputational Concerns or Competitive Preferences 1.1 Introduction 1.2 Context 1.2.1 Pay, Implicit Incentives, and Relative Performance 1.2.2 Composition of Teams Theoretical Framework 1.3.1 Setup 1.3.2 Reputation and Performance Comparisons 1.3.3 Competitive Preferences 10 1.4 Data and Descriptive Statistics 11 1.5 Identification and Econometric Framework 11 1.6 Results 14 1.6.1 Coworker Productivity Matters 14 1.6.2 It’s not just a production externality 16 1.6.3 It’s because of reputational concerns 20 Conclusion 22 1.3 1.7 Incentive Provision in Multitask Jobs v 23 2.1 Introduction 24 2.2 Context 27 2.2.1 The CEO’s Problem 27 2.2.2 Research Design 30 2.2.3 Assigning Consumers to Workers 33 2.2.4 Production Function 34 2.3 Data and Descriptive Statistics 35 2.4 Theoretical Framework 37 2.4.1 Setup 38 2.4.2 Misaligned Interests 40 2.4.3 Behavior Under the Treatment 42 2.4.4 Comparative Statics 43 2.4.5 Worker Heterogeneity 45 2.5 Identification and Econometric Framework 46 2.6 Results 47 2.6.1 Heterogeneous Treatment Effects 54 2.6.2 Employee Composition Matters 58 2.6.3 Repeat Business 60 2.7 Conclusion 60 2.8 Robustness Checks 67 2.8.1 Economic Shocks 67 2.8.2 Manager and Coworker Behavior 70 2.8.3 Hawthorne Effects 72 2.8.4 Incentive Effects of Piece Rates or Performance Standards 72 Beauty at Work 3.1 82 Introduction vi 83 3.2 3.3 3.4 Context 86 3.2.1 Earnings, Discrimination, and Worker Behavior 87 3.2.2 When, Where, and Who to Serve 88 Theoretical Framework 90 3.3.1 Setup 90 3.3.2 Customer Discrimination and Worker Behavior 92 3.3.3 Changes in the Returns to Beauty and Worker Behavior 93 Data and Descriptive Statistics 95 3.4.1 Measuring Beauty 95 3.4.2 Subject Pool 97 3.4.3 Performance Data 97 3.5 Research Design 101 3.6 The Returns to Beauty 102 3.7 3.8 3.6.1 Identifying the Returns 103 3.6.2 The Estimated Returns 104 Worker Behavior and Discrimination 106 3.7.1 Identification 106 3.7.2 Worker Behavior 108 3.7.3 Is it Customer Discrimination? 110 3.7.4 It’s not Employer Discrimination 113 Conclusion 115 Bibliography 116 vii Chapter Reputational Concerns or Competitive Preferences: Peer Effects and Pay for Individual Performance Chapter Reputational Concerns or Competitive Preferences 1.1 Introduction Workers often have concerns for the performance of their coworkers In some cases, these concerns have their origins in the way that workers are formally paid For example, in jobs where pay depends on team performance, workers care about coworker performance because it has strong role for how much they earn.1 In many cases, however, these concerns not originate in the formal pay scheme For example, in jobs where pay depends on individual performance, workers seem to care for coworker performance despite it having no explicit role for how much they earn Why care about coworker performance when it has little influence on individual earnings? One plausible explanation is that workers care about their relative performance (Falk and Ichino, 2006), either because they are competitive by nature (or nurture) or because they believe their reputation depends on their relative performance In the case where workers are naturally competitive, coworker performance matters because workers derive satisfaction from outperforming others (Charness and Rabin, 2002).2 Alternatively, when there’s a belief that reputation depends on relative performance, it matters because workers expect the employer (or other workers) to reward good relative performance today with favorable treatment tomorrow (Meyer and Vickers, 1997).3 In this paper, I investigate whether, how, and why workers care for the performance of others when they’re formally paid for their individual performance The setting is a large-scale restaurant The research subjects are the restaurant’s waiters These waiters are well-suited to an investigation of peer effects in jobs with individualbased pay They are suitable for several reasons The first reason is that their pay largely Examples include (Knez and Simester, 2001), (Bandiera et al., 2005), and (Hamilton et al., 2003) In other words, workers have competitive preferences, a special case of social preferences (Charness and Rabin, 2002) These workers prefer it when their payoffs are high relative to those of their coworkers For example, the employer may reward good relative performance today with favorable work or shift assignments tomorrow Chapter Reputational Concerns or Competitive Preferences depends on their individual performance Customers pay them tips, the firm pays them hourly wages, and neither is shared with other waiters The second reason is that the team of waiters varies naturally from day to day Each worker participates in several different teams, where the composition of each team is largely beyond their control On some days, waiters work with a high-performing peers On others, they not As a result, the natural variation in team composition can be used to estimate the effect of coworker performance on individual behavior The third reason is that the firm uses workers’ relative performance in a specific task to evaluate workers’ behavior Workers are aware that assessments are based on their performance in the task Moreover, they can monitor theirs and the performance of others in real time, from week to week, and from month to month The fourth reason is that the job is characterized by a high quit rate These quits can be used to explore why workers are affected by the performance of others If workers are competitive by nature, then coworker performance should influence them in a similar way before and after they give their resignation notice to the firm If workers have reputational concerns, then coworker performance should have a greater influence before they give their notice The empirical analysis has two main stages The first stage explores whether and why the performance of others matters I estimate the overall productivity spillovers among waiters I also estimate spillovers for the task the firm uses to evaluate worker performance In doing so, I rule out production externalities as the sole reason for the productivity spillovers The second stage explores why workers care about relative performance I find that the average worker sells $91 more per day (about percent of average daily sales) when the average sales of the peer group increases by $100 After parsing out the effects of production externalities, I find that the average worker sells $1.05 (about 2.8 percent of average sales per customer) more to each of their customers when the average sales per 107 Chapter Beauty at Work Table 3.4: Returns to Beauty (All Days) - Robustness Cluster-Robust Standard Errors are in parentheses with *** for p < 01, ** for 01 < p < 05, * for p < 1, and · for estimates marginally significant at the 10 percent level All regressions control for calendar date fixed effects, table fixed effects, gender, visible minority, over 30 years old, employment status (full-time/part-time), the number of sample days worked, and how the busy the worker considers that day of the week (relative to the other days) Beauty Percentile Coefficient Dependent Variable ln(Sales per hour) ln(Tip percentage) (1) (2) (3) (4) (5) (6) -0.002*** 0.001 (0.001) (0.001) (7) 0.002** 0.0013* 0.002** 0.002** 0.0014* (0.001) (0.0008) (0.001) (0.001) (0.0008) -0.0001 -0.0006 -0.0001 0.0000 0.0001 0.0001 0.001 (0.0004) (0.0005) (0.0006) (0.0006) (0.0006) (0.0006) (0.001) Sales per Customer, by Category Appetizers/Salads Alcohol Entrees Desserts Customers Served Sales per Customer 0.001 -0.001 0.0003 -0.0004 -0.001 -0.002 -0.002 (0.002) (0.003) (0.0034) (0.0034) (0.004) (0.004) (0.004) −0.008 -0.012* -0.01 -0.01 -0.01 -0.01 -0.003 (0.005) (0.006) (0.01) (0.01) (0.01) (0.01) (0.009) 0.001 0.006 0.009 0.011 0.015** 0.015** 0.14* (0.004) (0.005) (0.006) (0.007) (0.007) (0.007) (0.08) 0.001 0.003* 0.004* 0.004** 0.005** 0.005** 0.007*** (0.001) (0.002) (0.002) (0.002) (0.002) (0.002) (0.003) 0.02*** 0.03*** 0.04*** 0.03*** 0.03*** 0.03*** 0.01 (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) (0.01) -0.01 -0.01 -0.01 -0.001 0.001 0.001 0.01 (0.01) (0.01) (0.02) (0.016) (0.016) (0.016) (0.02) Prefers working with friends N Y Y Y Y Y Y Social skills (coworker reported) N Y Y Y Y Y Y Confidence N N Y Y Y Y Y Rationality N N N Y Y Y Y Number of coworkers who are N N N N Y Y Y N N N N Y Y Y Often works that day of the week N N N N N Y Y Overweight for Height N N N N N N Y Controls friends Number of times socialized with coworkers outside work last month Chapter Beauty at Work 108 individual, such as section characteristics (the number of booth seats, bench seats, and chair seats), days in sample, and average days in sample for members of the peer group Since the treatment is not randomized within shifts, we don’t include controls for calendar date fixed effects We assume that E[ǫid |αi , Td , Xid] = One concern with this identification strategy may involve recent aggregate shocks to the economy These shocks may have induced a shift in the restaurant’s patrons or in the spending habits of existing patrons As with Equation (3.4), another concern is that the treatment induced behavioral changes in the support staff and in managers We addressed the first concern in Chapter We address the second in later version of the paper 3.7.2 Worker Behavior After estimating Equation (3.5) with dessert sales as the dependent variable, we obtain our third result: Result 10 When paid bonuses for the number of customers served, workers with good looks reduce their dessert sales per customer We provide evidence for Result 10 in Table 3.5 The estimate in column suggests that a one standard deviation increase in beauty resulted in a $.08 reduction in dessert sales per customer (p < 1) Result 10 and the next result suggest that workers with above-average looks substitute their beauty for effort These workers direct their attention away from tasks where beauty and effort pay to tasks where just effort pays Result 11 Under the experimental treatment, workers with good looks served more customers Evidence for Result 11 is found in Table 3.6 Workers with above-average looks (one standard deviation above the mean) served more customer during the treatment period 109 Chapter Beauty at Work Table 3.5: Substitution Channels Robust Standard Errors are in parentheses with *** for p < 01, ** for 01 < p < 05, * for p < 1, and · for estimates marginally significant at the 10 percent level All regressions control for worker fixed effects, calendar week fixed effects, the day of the week (Friday or Saturday), section characteristics, customer arrivals, and days in sample (own and peers’) Dependent Variable Sales per Customer, by category Appetizers Entree Alcohol Desserts (1) (2) (3) (4) Beauty Percentile × -0.0003 0.008 -0.004 -0.004* Nov/Jan × 2009-2010 (0.0046) (0.006) (0.004) (0.002) Nov/Jan × 2009-2010 -0.39 -0.66 -0.68 0.10 (0.45) (0.54) (0.50) (0.20) 0.66 1.90*** 1.56*** 0.14 (0.44) (0.69) (0.63) (0.23) R2 0.05 0.06 0.12 0.05 Observations 897 897 897 897 Workers 34 34 34 34 Days 52 52 52 52 2009-2010 than workers with below-average looks (Columns 1-4) On the other hand, columns through show that sales per customer was statistically the same for workers with good looks as it was for workers with bad looks In the control period, Results 10 and 11 suggest that workers with good looks focused their effort on customer service rather than on the number of customers they serve Result 11 also suggests that bonuses for customer volume better align attractive-worker behavior with the firm’s preferences Since the pre-existing contract misaligns worker incentives (see Chapter 1), more customer turnover and Result 10 suggest that it’s more expensive Chapter Beauty at Work 110 to induce attractive workers to take the proper actions We explore the treatment’s implications productivity and earnings in the next result: Result 12 Under the experimental treatment, the overall gain in productivity and in earnings is largest for workers with good looks Table 3.7 provides information on the treatment effects for daily sales, tip percentages, and hours worked Columns through illustrate that a one standard deviation increase in the worker’s beauty percentile corresponds to a $43.87-66.20 increase in daily sales Columns through 12 show that the treatment had no statistically discernible influence on tip percentages or on hours worked As a consequence, good-looking workers earned more under the experimental treatment.24 3.7.3 Is it Customer Discrimination? We estimated Equation (3.5) by random effects to test the hypothesis that customers treat workers with good looks more favorably More specifically, we tested to see if beauty’s direct effect was negligible under the treatment We failed to reject the null beauty had no overall effect on dessert sales (p = 46) The effects for the other outcomes (including the number of customers served) were similar.25 The results from our tests are supported by the non-experimental evidence The evidence in Table 3.3 is inconsistent with discrimination based on tastes If customer purchases were to reflect a taste for good looks then the worker’s looks should have a similar influence on 24 We estimated specifications with ln(sales per hour) and found qualitatively similar, but imprecise, results We omitted this specification because we think the imprecision is partially driven by missing information on work hours 25 A potential criticism of these findings is that customers might discriminate when deciding on a restaurant to visit To investigate this criticism we regressed the number customer arrivals who decided not to stay on average beauty (across workers) While these regressions admittedly suffer from simultaneity, we could not reject the null hypothesis that average beauty has no effect (at conventional significance levels) for p < 1, and · for estimates marginally significant at the 10 percent level All regressions control for worker fixed effects, calendar week effects, and day effects (Friday or Saturday) Dependent Variable Customers Served Sales per Customer (1) (2) (3) (4) (5) (6) (7) (8) Beauty Percentile × 0.074* 0.047 0.052** 0.050** 0.01 0.01 0.005 0.005 Nov/Jan × 2009-2010 (0.042) (0.029) (0.025) (0.025) (0.01) (0.01) (0.01) (0.01) Nov/Jan × 2009-2010 -4.32 -1.11 -1.68 -1.86 -2.11** -2.17** -2.00* -1.96* (3.39) (2.25) (1.98) (1.95) (0.99) (1.04) (1.13) (1.13) 0.81 0.04 -3.20 -2.19 1.60*** 1.61*** 5.02*** 4.79*** (1.11) (0.90) (2.31) (2.38) (0.53) (0.55) (1.53) (1.54) R2 0.22 0.39 0.39 0.44 0.07 0.07 0.08 0.08 Observations 897 897 897 897 897 897 897 897 Workers 34 34 34 34 34 34 34 34 Days 52 52 52 52 52 52 52 52 Section N Y Y Y N Y Y Y Arrivals N N N Y N N N Y Days in Sample N N Y Y N N Y Y 2009-2010 Chapter Beauty at Work Table 3.6: Substitution Effects Robust Standard Errors are in parentheses with *** for p < 01, ** for 01 < p < 05, * Characteristics 111 (Own and Peers’) .05, * for p < 1, and · for estimates marginally significant at the 10 percent level All regressions control for worker fixed effects, calendar week effects, and day effects (Friday or Saturday) Dependent Variable Daily Sales ln(Tip Percentage) Hours (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) Beauty Percentile × 3.32* 2.21* 2.29* 2.20* -0.0002 -0.0002 -0.0004 -0.0004 0.013* 0.008 0.010 0.009 Nov/Jan × 2009-2010 (1.76) (1.24) (1.16) (1.12) (0.0006) (0.0006) (0.0006) (0.0006) (0.007) (0.006) (0.007) (0.006) Nov/Jan × 2009-2010 −232.58 -97.25 -115.40 -122.86 0.04 0.04 0.04 0.04 -0.85 -0.37 -0.37 -0.43 (140.87) (94.60) (91.54) (89.22) (0.06) (0.06) (0.06) (0.06) (0.60) (0.54) (0.58) (0.58) 80.52* 48.07 17.18 60.07 -0.005 -0.005 0.14 0.13 -0.18 -0.30** -1.23** -1.05** (46.31) (37.29) (106.10) (108.20) (0.035) (0.035) (0.09) (0.09) (0.15) (0.13) (0.47) (0.50) R2 0.18 0.35 0.35 0.39 0.03 0.03 0.03 0.03 0.11 0.18 0.18 0.21 Observations 897 897 897 897 894 894 894 894 826 826 826 826 Workers 34 34 34 34 34 34 34 34 34 34 34 34 Days 52 52 52 52 52 52 52 52 52 52 52 52 Section N Y Y Y N Y Y Y N Y Y Y Arrivals N N N Y N N N Y N N N Y Days in Sample N N Y Y N N Y Y N N Y Y 2009-2010 Chapter Beauty at Work Table 3.7: Productivity and Earnings Robust Standard Errors are in parentheses with *** for p < 01, ** for 01 < p < Characteristics 112 (Own and Peers’) Chapter Beauty at Work 113 the sales of each item Columns 3-6 show that looks matter for entree and dessert sales, but don’t matter for the appetizer and alcohol sales The evidence in Table 3.3 is also inconsistent with discrimination based on a belief that attractive workers are more productive If customer purchases reflect such a belief then the worker’s looks should matter less later in the sales process.2627 Our data suggests that beauty matters less appetizer and alcohol sales, items which are typically sold early in the process.28 3.7.4 It’s not Employer Discrimination We test the hypothesis that the employer treats workers with good looks more favorably Specifically, we investigate whether more attractive workers receive favorable section assignments In Table 3.8 we estimate Equation (3.5) where the number of booth seats, the number of bench seats, and the number of chairs are used as dependent variables The results suggest beauty has no role in section assignments The results fail to support employer discrimination based on tastes and on beliefs about the worker’s productivity In principle, the justification for statistical discrimination by the employer is weak After a worker is hired, the employer has repeated interactions with the employee As a consequence of these interactions, beauty becomes a less informative signal of the worker’s underlying productivity (Altonji and Pierret, 2001) 26 The argument extends to repeat customers When customers have a basis for comparison, the worker’s looks may have a negligible impact on their decisions 27 The idea that outward characteristics matter less as agents accumulate information is consistent with the findings of several experimental papers The evidence in (Todorov et al., 2005) suggests that beauty matters less for inferences about politician competence when voters accumulate information In the public goods game of (Andreoni and Petrie, 2008), the beauty premium diminishes when individual contributions are revealed 28 The corporation has guidelines on when items should be sold to customers The guidelines prescribe that items be sold in the following order: drinks appetizers/salads entrees desserts Workers are randomly monitored to ensure that the guidelines are met 114 Chapter Beauty at Work Table 3.8: Employer Discrimination Robust Standard Errors are in parentheses with *** for p < 01, ** for 01 < p < 05, * for p < 1, and · for estimates marginally significant at the 10 percent level All regressions control for calendar date fixed effects, table fixed effects, personal characteristics, employment status (full-time/part-time), sociability, expected sales, expected tips, whether the worker often works that day of the week, how the busy the worker considers that day of the week (relative to the other days), and individual rationality Dependent Variable Number of seats, by category Booth Bench Chair (1) (2) (3) -0.01 -0.002 -0.01 (0.02) (0.005) (0.01) Mean 9.57 1.90 3.28 R2 0.09 0.07 0.06 Observations 1748 1748 1748 34 34 34 51.4 51.4 51.4 Beauty Percentile Workers Average Days Worked Chapter Beauty at Work 3.8 115 Conclusion We conduct a field experiment to study the beauty premium’s role in the workplace We use the experiment and rich transactions-level data to place bounds on favorable treatment by customers and the employer as sources for the wage premium We find that the beauty premium that arises after workers are hired are largely driven by workers’ on-the-job behavior Overall, our findings suggest that the way workers behave may explain some of the wage premia for non-cognitive factors As a result, ours complement recent findings which show that pre-market treatment and behavior can underlie the wage premia More generally, our paper sheds light on why performance pay might generate earnings differentials within firms In this way our paper provides a reason for why rising wage inequality may be related to the rise of performance pay compensation schemes (Lemieux et al., 2009) Bibliography Altonji, J G and Pierret, C R (2001) Employer learning and statistical discrimination The Quarterly Journal of Economics, 116(1):313–350 Andreoni, J and Petrie, R (2008) Beauty, gender and stereotypes: Evidence from laboratory experiments Journal of Economic Psychology, 29(1):73–93 Arunachalam, R and Shah, M (2010) The prostitute’s allure: Examining returns to beauty, productivity and discrimination IZA, Discussion Paper 5064 Asch, B (1990) Do incentives matter? the case of navy recruiters Industrial and Labor Relations Review, XLIIIs:89S–106S Baker, G (2002) Distortion and risk in optimal incentive contracts The Journal of Human Resources, 37(4):728–751 Baker, G P (1992) Incentive contracts and performance measurement Journal of Political Economy, 100(3):598–614 Bandiera, O., Barankay, I., and Rasul, I (2005) Social preferences and the response to incentives: Evidence from personnel data The Quarterly Journal of Economics, 120(3):917– 962 116 117 BIBLIOGRAPHY Benjamin, D J and Shapiro, J M (2009) Thin-slice forecasts of gubernatorial elections The Review of Economics and Statistics, 91(3):523–536 Biddle, J E and Hamermesh, D S (1998) Beauty, productivity, and discrimination: Lawyers’ looks and lucre Journal of Labor Economics, 16(1):172–201 Charness, G and Rabin, M (2002) Understanding social preferences with simple tests The Quarterly Journal of Economics, 117(3):817–869 Courty, P and Marschke, G (2004) An empirical investigation of gaming responses to explicit performance incentives Journal of Labor Economics, 22(1) Datar, S., Kulp, S C., and Lambert, R A (2001) Balancing performance measures Journal of Accounting Research, 39(1):75–92 Dumont, E., Fortin, B., Jacquemet, N., and Shearer, B (2008) Physicians’ multitasking and incentives: Empirical evidence from a natural experiment Journal of Health Economics, 27(6):1436–1450 Falk, A and Ichino, A (2006) Clean evidence on peer effects Journal of Labor Economics, 24(1):39–57 Fehr, E and Schmidt, K M (2004) Fairness and incentives in a multi-task principal-agent model Scandinavian Journal of Economics, 106(3):453–474 Feltham, G A and Xie, J (1994) Performance measure congruity and diversity in multitask principal/agent relations The Accounting Review, 69(3):429–453 Gibbons, R (1998) Incentives in organizations Journal of Economic Perspectives, 12(4):115–132 Gibbons, R and Murphy, K J (1992) Optimal incentive contracts in the presence of career concerns Journal of Political Economy, 100(3):468–505 BIBLIOGRAPHY 118 Hamermesh, D S and Biddle, J E (1994) Beauty and the labor market The American Economic Review, 84(5):1174–1194 Hamermesh, D S., Meng, X., and Zhang, J (2002) Dress for success - does primping pay? Labour Economics, 9(3):361–373 Hamermesh, D S and Parker, A (2005) Beauty in the classroom: instructors’ pulchritude and putative pedagogical productivity Economics of Education Review, 24:369–376 Hamilton, B H., Nickerson, J A., and Owan, H (2003) Team incentives and worker heterogeneity: An empirical analysis of the impact of teams on productivity and participation The Journal of Political Economy, 111(3):465–497 Holmstrom, B (1979) Moral hazard and observability The Bell Journal of Economics, 10(1):74–91 Holmstrom, B (1982) Moral hazard in teams The Bell Journal of Economics, 13(2):324– 340 Holmstrom, B (1999) Managerial incentive problems: A dynamic perspective Review of Economic Studies, 66:169,182 Holmstrom, B and Milgrom (1991) Multitask principal-agent analyses: Incentive contracts, asset ownership, and job design Journal of Law, Economics, and Organization, 7(Special Issue):24–52 Holmstrom, B and Milgrom, P (1994) The firm as an incentive system The American Economic Review, 84(4):972–991 Holt, C A and Laury, S K (2002) Risk aversion and incentive effects The American Economic Review, 92(5):1644–1655 119 BIBLIOGRAPHY Kahn, C and Huberman, G (1988) Two-sided uncertainty and ‘up-or-out’ contracts Journal of Labor Economics, 6(4):423–444 Kandel, E and Lazear, E P (1992) Peer pressure and partnerships The Journal of Political Economy, 100(4):801–817 Kerr, S (1975) On the folly of rewarding a, while hoping for b The Academy of Management Executive, 18:769–783 Knez, M and Simester, D (2001) Firm-wide incentives and mutual monitoring at continental airlines Journal of Labor Economics, 19(4):743–772 Lazear, E P (1989) Pay equality and industrial politics Journal of Political Economy, 97(3):561–580 Lazear, E P (2000) Perfomance pay and productivity American Economic Review, 90(5):1346–1361 Lazear, E P and Oyer, P (2012) Personnel economics Handbook of Organizational Economics Lemieux, T., MacLeod, W B., and Parent, D (2009) Performance pay and wage inequality The Quarterly Journal of Economics, CXXIV(1):1–49 List, J A (2006) The behavioralist meets the market: Measuring social preferences and reputation effects in actual transactions Journal of Political Economy, 114(1):1–37 List, J A., Sadoff, S., and Wagner, M (2010) So you want to run an experiment, now what? some simple rules of thumb for optimal experimental design Experimental Economics Forthcoming Mas, A and Moretti, E (2009) Peers at work American Economic Review, 99(1):112–145 BIBLIOGRAPHY 120 Meyer, M A and Vickers, J (1997) Performance comparisons and dynamic incentives Journal Political Economy, 105(3):547–581 Mobius, M M and Rosenblat, T S (2006) Why beauty matters American Economic Review, 96(1):222–235 Mocan, N and Tekin, E (2010) Ugly criminals The Review of Economics and Statistics, 92(1):15–30 Mulford, M., Orbell, J., Shatto, C., and Stockard, J (1998) Physical attractiveness, opportunity, and success in everyday exchange The American Journal of Sociology, 103(6):1565– 1592 Murphy, K J (1999) Executive compensation Handbook of Labor Economics, 3(2):2485– 2563 Neal, D A and Johnson, W R (1996) The role of premarket factors in black-white wage differences The Journal of Political Economy, 104(5):869–895 Oyer, P (1998) Fiscal year ends and nonlinear incentive contracts: The effect on business seasonality The Quarterly Journal of Economics, 113(1):149–185 Paarsch, H J and Shearer, B S (1999) The response of worker effort to piece rates: Evidence from the british columbia tree-planting industry The Journal of Human Resources, 34(4):643–667 Persico, N., Postlewaite, A., and Silverman, D (2004) The effect of adolescent experience on labor market outcomes: The case of height Journal of Political Economy, 112(5):1019– 1053 Prendergast, C (1993) The role of promotion in inducing specific human capital acquisition Quarterly Journal of Economics, 108(2):523–534 BIBLIOGRAPHY 121 Prendergast, C (1999) The provision of incentives in firms Journal of Economic Literature, 37(1):7–63 Ramakrishnan, R T and Thakor, A V (1991) Competition and cooperation in agency Journal of Law, Economics, and Organization, 7(2):248–283 Shearer, B (2004) Piece rates, fixed wages and incentives: Evidence from a field experiment Review of Economic Studies, 71:513–534 Slade, M E (1996) Multitask agency and contract choice: An empirical exploration International Economic Review, 37(2):465–486 Solnick, S J and Schweitzer, M E (1999) The influence of physical attractiveness and gender on ultimatum game decisions Organizational Behavior and Human Decision Processes, 79(3):199–215 Stiglitz, J E (1991) Symposium on organizations and economics Journal of Economics Perspectives, 1(2):15–24 Thornhill, R and Gangestad, S W (1999) Facial attractiveness Trends in Cognitive Sciences, 3(12):452–460 Todorov, A., Mandisodza, A N., Goren, A., and Hall, C C (2005) Inferences of competence from faces predict election outcomes Science, 308(5728):1623–1626