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Chapter 3 Does Relative Performance Evaluation Reduce Noise in the Performance Evaluation? Preamble to Chapter 3 The current chapter addresses the claim that RPE reduces the room that managers have to behave opportunistically. By doing so, this study answers the first part of research question 3: is RPE effective at reducing noise and opportunism? The noise-reduction claim is also assessed in chapter 2. Chapter 2 refers to the noisereduction perspective to derive the effect of common uncertainty, a driver of noise, on RPE and finds support for this relation. However, the relation between these two variables may still be caused by mechanisms other than the reduction of noise in the performance evaluation. Prior literature has suggested several alternative perspectives on RPE use that could explain the findings in chapter 2. The current chapter analyses the noise-reduction perspective in a more direct manner by seeking additional proof for the noise-reduction explanation of RPE use. Instead of analysing whether RPE use is increased by noise-inducing factors, this chapter studies whether RPE effectively reduces noise in the performance evaluation. Further study of the noise-reduction perspective is important for our understanding of RPE’s consequences for Management Control. Together with chapter 2, the current chapter adds to our understanding of whether RPE use can be explained by an organizational wish to insulate the performance evaluation from the impact of external events, and to improve contractual efficiency between the manager and his superior. 59
60 CHAPTER 3. NOISE REDUCTION EFFECTIVENESS 3.1 Introduction This chapter empirically assesses one of the fundamental claims of Relative Performance Evaluation theory: the causal relation between RPE use and the reduction of noise in the performance evaluation of employees. Noise decreases the performance metrics’ informativeness about the efforts of the employee. Noise occurs if uncontrollable events affect the measured performance. Noisy performance measures do not purely reflect the efforts of the employee, as they are also affected by windfall gains and losses caused by uncontrollable events. For example, consider the situation of a sales-manager operating in a stagnating market. The uncontrollable market conditions reduce the sales manager’s revenues. Although he zealously attempts to boost his sales, the manager’s performance indicators suggest that he provided much less effort than last year, when the market conditions were favourable. In this situation external events (in casu: the stagnating market) reduce the manager’s performance score. However, the opposite effect is also possible when the conditions are highly favourable. In both scenarios, noise results in a less functional performance measurement system, as it informs the principal less accurately with regard to the agent’s efforts. This reduces the efficiency of the performance contract between the principal and the agent by imposing risk on the agent of not being rewarded for effort but for luck. According to agency reasoning, RPE can restore the quality of the performance evaluation by filtering out noise from the evaluated manager’s measured performance (Holmstrom 1982, Gibbons & Murphy 1990). RPE reduces noise by incorporating information about the attainable performance level into the evaluated manager’s performance evaluation. This works because of peer comparison (Holmstrom 1982). RPE compares the manager’s actual performance to the performance of a reference group that partially faces the same external events (i.e., market stagnation and dropping revenues). Thus, the performance of the reference group is impacted in a similar manner by shared external events. The performance of the reference group in a given period, with its specific external events, informs the principal about the performance level that should be attainable for the agent in that period. The comparison with peer performance constructs a performance norm that is (at least partially) insulated from the impact of external events. This causal relation between RPE use and noise in the performance evaluation is a cornerstone explanation for why organizations would use RPE. This noise-reduction explanation is prevalent in two streams of literature. The first stream is the analytical agency literature. In a seminal paper, Holmstrom (1982) shows that RPE reduces noise in the performance evaluation if benchmarked agents face some common uncertainties. According to Holmstrom’s analyses, RPE filters out the effects of common uncertainties such that the evaluation yields less noisy information about the agent’s performance.
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Relative Performance Evaluation in
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NYENRODE BUSINESS UNIVERSITEIT Rela
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Table of Contents Preface 1 General
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Preface Why do people make things h
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2 CHAPTER 1. GENERAL INTRODUCTION I
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4 CHAPTER 1. GENERAL INTRODUCTION o
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6 CHAPTER 1. GENERAL INTRODUCTION T
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Page 22 and 23: Chapter 2 The Use of Relative Perfo
Page 24 and 25: 2.1. INTRODUCTION 15 is not a promi
Page 26 and 27: 2.2. THEORETICAL BACKGROUND 17 The
Page 28 and 29: 2.2. THEORETICAL BACKGROUND 19 Sinc
Page 30 and 31: 2.2. THEORETICAL BACKGROUND 21 who
Page 32 and 33: 2.2. THEORETICAL BACKGROUND 23 suff
Page 34 and 35: 2.3. SAMPLE AND MEASUREMENT 25 2.2.
Page 38 and 39: 2.3. SAMPLE AND MEASUREMENT 29 can
Page 40 and 41: 2.3. SAMPLE AND MEASUREMENT 31 Comp
Page 42 and 43: 2.3. SAMPLE AND MEASUREMENT 33 this
Page 44 and 45: 2.3. SAMPLE AND MEASUREMENT 35 Emph
Page 46 and 47: 2.4. ANALYSES 37 2.4 Analyses This
Page 48 and 49: 2.4. ANALYSES 39 Table 2.8: RPE use
Page 50 and 51: 2.4. ANALYSES 41 2.4.2 Correlations
Page 52 and 53: 2.4. ANALYSES 43 Concerning the con
Page 54 and 55: 2.4. ANALYSES 45 Table 2.13: Result
Page 56 and 57: 2.4. ANALYSES 47 Table 2.15: Summar
Page 58 and 59: 2.5. CONCLUSIONS AND DISCUSSION 49
Page 62 and 63: 2.6. CONTRACTIBILITY MIMIC MODEL (A
Page 64 and 65: 2.6. CONTRACTIBILITY MIMIC MODEL (A
Page 66 and 67: 2.7. ANALYSES FOR FOR-PROFIT BUS (A
Page 70 and 71: 3.1. INTRODUCTION 61 Holmstrom’s
Page 72 and 73: 3.2. DEVELOPMENT OF THE MODEL 63 3.
Page 74 and 75: 3.2. DEVELOPMENT OF THE MODEL 65 RP
Page 76 and 77: 3.3. SAMPLE AND MEASUREMENT 67 3.3
Page 80 and 81: 3.3. SAMPLE AND MEASUREMENT 71 Tabl
Page 82 and 83: 3.3. SAMPLE AND MEASUREMENT 73 Tabl
Page 84 and 85: 3.4. ANALYSES 75 3.4 Analyses This
Page 86 and 87: 3.4. ANALYSES 77 Table 3.9: Pearson
Page 92 and 93: 3.4. ANALYSES 83 Larcker & Rusticus
Page 96 and 97: Chapter 4 Does Relative Performance
Page 98 and 99: 4.1. INTRODUCTION 89 Moreover, chap
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Page 102 and 103: 4.2. DEVELOPMENT OF THE MODEL 93 Sp
Page 104 and 105: 4.3. SAMPLE AND MEASUREMENT 95 4.3
Page 106 and 107: 4.3. SAMPLE AND MEASUREMENT 97 To i
Page 108 and 109: 4.3. SAMPLE AND MEASUREMENT 99 of R
Page 110 and 111: 4.3. SAMPLE AND MEASUREMENT 101 Tab
Page 112 and 113: 4.4. ANALYSES 103 Table 4.8: Items
Page 114 and 115: 4.4. ANALYSES 105 RPE use ✻ Posit
Page 116 and 117: 4.4. ANALYSES 107 The model does sh
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4.4. ANALYSES 109 RPE and RFMO. Mor
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4.4. ANALYSES 111 room for manageri
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4.5. CONCLUSIONS AND DISCUSSION 113
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4.5. CONCLUSIONS AND DISCUSSION 115
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Chapter 5 Conclusion 5.1 Summary, C
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5.1. SUMMARY, CONCLUSIONS AND DISCU
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5.2. IMPLICATIONS FOR PRACTICE 125
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5.3. LIMITATIONS AND SUGGESTIONS FO
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Appendix Overview of Questionnaire
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Q5 How often do the following thing
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Q14 When serving your clients, how
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Q23 Please indicate whether you agr
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Noise Q34 NOISE (primary measure) P
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References 1. Abernethy, M.A., Bouw
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26. Diamantopoulos, A. & Siguaw, J.
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52. Himmelberg, C.P. & Hubbard R.G.
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83. Towry, K. 2003. ‘Control in a
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148 beïnvloeden, veroorzaken ruis
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Biography Hilco van Elten (1979) ho
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