Abstract
The theory of compensating differentials asserts that night shift workers should receive compensating wage differentials due to undesirable work conditions. In weak local economies, workers may have difficulty finding jobs; thus, these workers might be more likely to accept night shift work and be less concerned with the size of the compensating differential for night shifts. Using CPS data from 2001, this paper employs maximum likelihood estimation of an endogenous switching regression model to analyze wages of day and night shift workers and shift choice. The findings indicate the presence of selection bias, thus emphasizing the importance of correcting for self-selection into night shifts. The average of the estimated wage differentials for night shift work is negative for the overall sample, with differentials varying by worker characteristics. The shift differential is found to be a statistically significant predictor of shift choice, indicating that shift premiums play an important role in motivating individuals to select night shift work. Using two measures of local economic conditions and a new method of analyzing interaction effects in the context of an endogenous switching regression model, this paper finds limited evidence that weak local economic conditions lessen the impact of compensating differentials on shift choice.
Highlights
Smith [1] first proposed the idea that working conditions could impact wages and worker preferences for jobs
Selected coefficients from maximum likelihood estimation of the reduced form of the selection equation (10) with corresponding standard errors are reported in column 1 of Table 2
Due to the similarity of coefficients for the education, experience, gender, marital status, union membership, race, industry, and occupation variables, only the regression results from the model using the one month percentage change in the coincident index as the indicator of local economic conditions are shown for these variables
Summary
Smith [1] first proposed the idea that working conditions could impact wages and worker preferences for jobs. This paper uses a more general econometric model, an endogenous switching regression model (ESR), to analyze compensating wages, and selection into night shift work, with night shift selection modeled as a function of worker and job characteristics, night shift differentials, and local economic conditions. This paper builds upon the work of DeBeaumont and Nsiah [7] and Bender and Mridha [8] by using the more general ESR model, which allows for the estimation of the effect of wage differentials and local economic conditions on the decision to work a night shift and allows the returns to individual characteristics of day and night workers to differ. This paper offers a new method of investigating interaction effects by estimating lower and upper bounds on the probability of selecting night shift work for different values of the shift differential and the local economic conditions
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
