Using Behavioral Economic Experiments at a Large Motor Carrier: The Context and Design of the Truckers and Turnover Project
The Truckers and Turnover Project is a statistical case study of a single firm and its employees which matches proprietary personnel and operational data to new data collected by the researchers to create a two-year panel study of a large subset of new hires. The project’s most distinctive innovation is the data collection process which combines traditional survey instruments with behavioral economics experiments. The survey data include information on demographics, risk and loss aversion, time preference, planning, non-verbal IQ, and the MPQ personality profile. The data collected by behavioral economics experiments include risk and loss aversion, time preferences (discount rates), backward induction, patience, and the preference for cooperation in a social dilemma setting. Subjects will be followed over two years of their work lives. Among the major design goals are to discover the extent to which the survey and experimental measures are correlated, and whether and how much predictive power, with respect to key on-the-job outcome variables, is added by the behavioral measures. The panel study of new hires is being carried out against the backdrop of a second research component, the development of a more conventional in-depth statistical case study of the cooperating firm and its employees. This is a high-turnover service industry setting, and the focus is on the use of survival analysis to model the flow of new employees into and out of employment, and on the correct estimation of the tenure-productivity curve for new hires, accounting for the selection effects of the high turnover.
|Date of creation:||May 2007|
|Publication status:||published in: Stefan Bender, Julia Lane, Kathryn Shaw, Fredrik Andersson, and Till Von Wachter (eds.), The Analysis of Firms and Employees: Quantitative and Qualitative Approaches , NBER and University of Chicago Press, 2008, 45-106|
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References listed on IDEAS
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