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The cyclical sensitivity of seasonality in US employment

There is a growing recognition in the literature on business cycles that production technologies may give rise to complicated interactions between seasonal and cyclical movements in economic time series, which can distort business cycle inference based on seasonally adjusted data. For the most part, however, the empirical research in this area has relied on standard univariate seasonal adjustment techniques that provide only a partial description of such interactions. In this paper, we develop an unobserved components model that explicitly accounts for the effects of business cycles on industry-level seasonality and for the potential feedback from seasonality to the aggregate business cycle. In particular, the model extracts an aggregate "common cycle" from industry-level data, allows formal statistical testing of seasonal differences in the comovement of an industry with the common cycle, and identifies economy-wide and industry-specific contributions to the seasonal and non-seasonal variation in the data. Applying the model to quarterly US payroll employment data, we frequently find evidence of statistically significant differences across seasons in the comovement between sectoral employment and the common cycle. On the other hand, we also find that seasonal fluctuations in employment at the industry level are largely idiosyncratic and that the proportion of the total variance of the common cycle accounted for by seasonality is much less than for aggregate employment. This suggests that seasonal shocks may have less of a business cycle element to them than one might infer from the seasonal movements in aggregate variables.

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Paper provided by Bank for International Settlements in its series BIS Working Papers with number 67.

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Length: 38 pages
Date of creation: May 1999
Date of revision:
Handle: RePEc:bis:biswps:67
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  1. Kenneth F. Wallis, 1979. "Seasonal Adjustment and Multiple Time Series Analysis," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 347-364 National Bureau of Economic Research, Inc.
  2. Barsky, Robert B & Miron, Jeffrey A, 1989. "The Seasonal Cycle and the Business Cycle," Journal of Political Economy, University of Chicago Press, vol. 97(3), pages 503-34, June.
  3. Hyllerberg, S. & Engle, R.F. & Granger, C.W.J. & Yoo, B.S., 1988. "Seasonal Integration And Cointegration," Papers 0-88-2, Pennsylvania State - Department of Economics.
  4. Breusch, T S & Pagan, A R, 1980. "The Lagrange Multiplier Test and Its Applications to Model Specification in Econometrics," Review of Economic Studies, Wiley Blackwell, vol. 47(1), pages 239-53, January.
  5. Ruud, Paul A., 1991. "Extensions of estimation methods using the EM algorithm," Journal of Econometrics, Elsevier, vol. 49(3), pages 305-341, September.
  6. Charles I. Plosser, 1978. "A Time Series Analysis of Seasonality in Econometric Models," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 365-408 National Bureau of Economic Research, Inc.
  7. Krane, Spencer D., 1993. "Induced seasonality and production-smoothing models of inventory behavior," Journal of Econometrics, Elsevier, vol. 55(1-2), pages 135-168.
  8. Ghysels, E., 1991. "Are Business Cycle Turning Points Uniformly Distributed Throughout the Year?," Cahiers de recherche 9135, Universite de Montreal, Departement de sciences economiques.
  9. James H. Stock & Mark W. Watson, 1989. "New Indexes of Coincident and Leading Economic Indicators," NBER Chapters, in: NBER Macroeconomics Annual 1989, Volume 4, pages 351-409 National Bureau of Economic Research, Inc.
  10. Plosser, Charles I., 1979. "The analysis of seasonal economic models," Journal of Econometrics, Elsevier, vol. 10(2), pages 147-163, June.
  11. Bell, William R & Hillmer, Steven C, 1984. "Issues Involved with the Seasonal Adjustment of Economic Time Series," Journal of Business & Economic Statistics, American Statistical Association, vol. 2(4), pages 291-320, October.
  12. Canova, F. & Ghysels, E., 1992. "Changes in Seasonal Patters: Are They Cyclical," Cahiers de recherche 9216, Universite de Montreal, Departement de sciences economiques.
  13. Watson, Mark W. & Engle, Robert F., 1983. "Alternative algorithms for the estimation of dynamic factor, mimic and varying coefficient regression models," Journal of Econometrics, Elsevier, vol. 23(3), pages 385-400, December.
  14. David A. Pierce & William P. Cleveland, 1981. "Seasonal adjustment methods for the monetary aggregates," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Dec, pages 875-887.
  15. Cecchetti, Stephen G & Kashyap, Anil K & Wilcox, David W, 1997. "Interactions between the Seasonal and Business Cycles in Production and Inventories," American Economic Review, American Economic Association, vol. 87(5), pages 884-92, December.
  16. J. Joseph Beaulieu & Jeffrey K. MacKie-Mason & Jeffrey A. Miron, 1991. "Why Do Countries and Industries with Large Seasonal Cycles Also Have Large Business Cycles?," NBER Working Papers 3635, National Bureau of Economic Research, Inc.
  17. Ghysels, Eric & Lee, Hahn S. & Noh, Jaesum, 1994. "Testing for unit roots in seasonal time series : Some theoretical extensions and a Monte Carlo investigation," Journal of Econometrics, Elsevier, vol. 62(2), pages 415-442, June.
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