The Peter Principle: An Experiment

David L. Dickinson Marie-Claire Villeval Appalachian State CNRS-GATE, IZA

University

The Peter Principal

• Post-promotion, observed ability falls

• Lazear (2004) framework attributes this to transitory component of observed ability

• Testable implications include:– Observed ability declines (rises), on average, after

promotion (after non-promotion).– Job sorting is only efficient if workers self-select into jobs.– When employers choose jobs for workers, effort will be

distorted in predictable ways.

Experimental Design• Subjects are all agents (i.e., workers). An exogenous

promotion standard is applied when needed

• Real cognitive effort task with two difficulty levels to create “easy” and “hard” tasks– Grammatical transformation task (AXFND)

• Subjects paid for “observed” output, Y.– Y=actual output ± random error term

• Treatments are:– Calibration treatment to establish population parameters and

promotion cutoff point– Self-Selection versus Promotion rule comparison– Variance of error component manipulation within Promotion

treatments, Promotion-Low, Promotion-Medium, Promotion-High

Design of the promotion payment schemesFigure 2

Efficient job sorting involves low ability workers in easy task, high ability workers in hard task.

(achieved by setting relative wage rate WH/WE steeper than opportunity of hard task)

Figure 2. Proportion of lucky subjects in stage 3 sorted by task in stage 4

PERCENTAGE OF LUCKY SUBJECTS IN STAGE 3 SORTED BY TASK IN STAGE 4

0

10

20

30

40

50

60

70

80

90

Calibration Self-Selection Low Variance MediumVariance

High Variance

TREATMENT

PER

CE

NT

AG

E

Easy 4Hard 4

Table 3. Average ability of promoted and non-promoted subjects and mistakes in task assignment

Stage 3-average ability

Number of mistakes (percentages) Treatment

Non-promoted

Promoted Mistake 1 (promotion)

Mistake 2 (no-promotion)

Correct decisions

Calibration 59.95 58.68 2 (5.26) 2 (5.26) 34 (89.47) Self-Selection 61.7 72.35 9 (22.50) 6 (15.00) 25 (62.50) Promotion-Low 57.33 77.32 2 (5.41) 1 (2.7) 34 (91.89) Promotion-Medium 52.67 79.17 4 (10.53) 3 (7.89) 31 (81.58) Promotion-High 60.68 60.60 11 (29.73) 10 (27.03) 16 (43.24)

Table 4. Efficiency rate of promotion standard and self-selection vs. random task assignment

Self-Selection is NOT efficient as predicted

(imperfect knowledge of one’s abilities is likely the cause)

Treatment Simulated (random) Assignment Actual Assignment Self-Selection 45.00 % 62.50 % Promotion-Low 54.05 % 91.89 % Promotion-Medium 76.32 % 81.58 % Promotion-High 54.05 % 43.24 %

Effort Distortion• Theory predicts low (high) ability agents will distort effort

down (up) in promotion treatments to ensure efficient task assignment.

• We find no effort distortion in comparing Stage 3 and 4 outcomes for those promoted and not promoted (controlling for learning trends).

• Alternatively, outcomes variance should be higher in Stage 3 or Promotion treatments than in Stage 3 of Selection treatments (which was not followed by promotions), relative to Stage 1 of each treatment. – We find no significant difference, thus rejecting the effort

distortion hypothesis.

Conclusions

• Peter Principle is observed when transitory component of output is large relative to ability (as predicted)– Random assignment can even dominate a promotion standard if

transitory component is large enough.

• Contrary to theory, Self-Selection is NOT necessarily efficient, but often dominates random assignment– Likely due to imperfect knowledge of own-ability.

• Contrary to theory, effort is not distorted (pre-promotion)– Also likely due to imperfect knowledge of own-ability.

THE END