Worker Overconfidence: Field Evidence and Implications for Employee Turnover and Returns from Training

37 Pages Posted: 19 Mar 2017

See all articles by Mitchell Hoffman

Mitchell Hoffman

University of Toronto - Rotman School of Management; National Bureau of Economic Research (NBER)

Stephen V. Burks

University of Minnesota, Morris - Division of Social Science; Institute for the Study of Labor (IZA); Center for Decision Research and Experimental Economics (CeDEx); Center for Transportation Studies, University of Minnesota

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Date Written: March 2017

Abstract

Combining weekly productivity data with weekly productivity beliefs for a large sample of truckers over two years, we show that workers tend to systematically and persistently over-predict their productivity. If workers are overconfident about their own productivity at the current firm relative to their outside option, they should be less likely to quit. Empirically, all else equal, having higher productivity beliefs is associated with an employee being less likely to quit. To study the implications of overconfidence for worker welfare and firm profits, we estimate a structural learning model with biased beliefs that accounts for many key features of the data. While worker overconfidence moderately decreases worker welfare, it also substantially increases firm profits. This may be critical for firms (such as the main one we study) that make large initial investments in worker training.

Suggested Citation

Hoffman, Mitchell and Burks, Stephen V., Worker Overconfidence: Field Evidence and Implications for Employee Turnover and Returns from Training (March 2017). NBER Working Paper No. w23240, Available at SSRN: https://ssrn.com/abstract=2935446

Mitchell Hoffman (Contact Author)

University of Toronto - Rotman School of Management ( email )

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Stephen V. Burks

University of Minnesota, Morris - Division of Social Science ( email )

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Center for Transportation Studies, University of Minnesota ( email )

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