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Licensed Unlicensed Requires Authentication Published by De Gruyter Oldenbourg April 20, 2022

Does Variable Shift Work Explain Away Productivity Shocks? A Bayesian Approach

  • Lucas M. Engelhardt EMAIL logo

Abstract

In business cycle accounting, productivity is procyclical. However, this may be an illusion caused by improperly accounting for changes in procyclical capital utilization. This paper considers to what extent incorporating variable shift work into a dynamic stochastic general equilibrium model reduces the role played by productivity shocks in explaining variations in output. In the one shift version of the model, 81 percent of the variation in output is explained by productivity shocks. With variable shift work, the contribution falls to a minimum of 48 percent. While variable shift work decreases their importance, productivity shocks continue to be the most significant contributor to the variation of output over the business cycle.

JEL Classification: E22; E32

Corresponding author: Lucas M. Engelhardt, Kent State University – Stark Campus, 6000 Frank Ave NW, Canton, OH, USA, E-mail:

References

An, S. and Schorfheide, F. (2007). Bayesian analysis of dsge models. Econom. Rev. 26: 113–172, https://doi.org/10.1080/07474930701220071.Search in Google Scholar

Basu, S. (1996). Procyclical productivity: increasing returns or cyclical utilization? Q. J. Econ. 111: 719–751, https://doi.org/10.2307/2946670.Search in Google Scholar

Baxter, M., King, R.G., et al.. (1991). Productive externalities and business cycles. Technical report. Federal Reserve Bank of Minneapolis.Search in Google Scholar

Biddle, J.E. (2014). Retrospectives: the cyclical behavior of labor productivity and the emergence of the labor hoarding concept. J. Econ. Perspect. 28: 197–212, https://doi.org/10.1257/jep.28.2.197.Search in Google Scholar

Bresnahan, T.F. and Ramey, V.A. (1994). Output fluctuations at the plant level. Q. J. Econ. 109: 593–624, https://doi.org/10.2307/2118415.Search in Google Scholar

Burnside, C., Eichenbaum, M., and Rebelo, S. (1995). Capital utilization and returns to scale. NBER Macroecon. Annu. 10: 67–124, https://doi.org/10.1086/654266.Search in Google Scholar

Chib, S. and Jeliaskov, I. (2001). Marginal likelihood from metropolis-hastings output. J. Am. Stat. Assoc. 96: 270–281, https://doi.org/10.1198/016214501750332848.Search in Google Scholar

Fernald, J.G. and Wang, J.C. (2016). Why has the cyclicality of productivity changed? what does it mean? Annu. Rev. Econ. 8: 465–496, https://doi.org/10.1146/annurev-economics-080315-015018.Search in Google Scholar

Galí, J. and van Rens, T. (2021). The vanishing procyclicality of labour productivity. Econ. J. 131: 102–326.10.1093/ej/ueaa065Search in Google Scholar

Greene, W.H. (2003). Econometric analysis, 5th ed. Pearson.Search in Google Scholar

Kamihigashi, T. (1996). Real business cycles and sunspot fluctuations are observationally equivalent. J. Monetary Econ. 37: 105–117, https://doi.org/10.1016/0304-3932(95)01243-5.Search in Google Scholar

Kostiuk, P.F. (1990). Compensating differentials for shift work. J. Polit. Econ. 98: 1054–1075, https://doi.org/10.1086/261719.Search in Google Scholar

Kydland, F.E. and Prescott, E.C. (1982). Time to build and aggregate fluctuations. Econometrica 50: 1345–1370, https://doi.org/10.2307/1913386.Search in Google Scholar

Lucas, R. (1970). Capacity, overtime, and empirical production functions. Am. Econ. Rev. 60: 23–27.Search in Google Scholar

Mayshar, J. and Halevy, Y. (1997). Shiftwork. J. Labor Econ. 15: S198–S222, https://doi.org/10.1086/209861.Search in Google Scholar

Mayshar, J. and Solon, G. (1993). Shift work and the business cycle. Am. Econ. Rev. 83: 224–228.Search in Google Scholar

Prescott, E., McGrattan, E., et al.. (2012). The labor productivity puzzle. In: 2012 meeting papers, number 644. Society for Economic Dynamics.10.21034/wp.694Search in Google Scholar

Prescott, E.C. (1986). Theory ahead of business-cycle measurement. In: Carnegie-Rochester conference series on public policy, Vol. 25. Elsevier, pp. 11–44, https://doi.org/10.1016/0167-2231(86)90035-7.Search in Google Scholar

Roberts, G., Gelman, A., and Gilks, W.R. (1996). Efficient metropolis jumping rules. Bayesian Stat. 5: 599–607.Search in Google Scholar

Roberts, G., Gelman, A., and Gilks, W.R. (1997). Weak convergence and optimal scaling of random walk metropolis algorithms. Ann. Appl. Probab. 7: 110–120.10.1214/aoap/1034625254Search in Google Scholar

Sargent, T.J. (1978). Estimation of dynamic labor demand schedules under rational expectations. J. Polit. Econ. 86: 1009–1044, https://doi.org/10.1086/260726.Search in Google Scholar

Shapiro, M.D. (1993). Cyclical productivity and the workweek of capital. Am. Econ. Rev. 83: 229–233.Search in Google Scholar

Shapiro, M.D. (1996). Capacity utilization and the marginal premium for work at night. University of Michigan.Search in Google Scholar

Shapiro, M.D., Corrado, C., and Clark, P.K. (1996). Macroeconomic implications of variation in the workweek of capital. Brookings Pap. Econ. Activ. 1996: 79–133, https://doi.org/10.2307/2534620.Search in Google Scholar

Received: 2021-03-15
Accepted: 2022-02-27
Published Online: 2022-04-20
Published in Print: 2022-06-27

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