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Estimating Turning Points Using Large Data Sets

  • James H. Stock
  • Mark W. Watson

Dating business cycles entails ascertaining economy-wide turning points. Broadly speaking, there are two approaches in the literature. The first approach, which dates to Burns and Mitchell (1946), is to identify turning points individually in a large number of series, then to look for a common date that could be called an aggregate turning point. The second approach, which has been the focus of more recent academic and applied work, is to look for turning points in a few, or just one, aggregate. This paper examines these two approaches to the identification of turning points. We provide a nonparametric definition of a turning point (an estimand) based on a population of time series. This leads to estimators of turning points, sampling distributions, and standard errors for turning points based on a sample of series. We consider both simple random sampling and stratified sampling. The empirical part of the analysis is based on a data set of 270 disaggregated monthly real economic time series for the U.S., 1959-2010.

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Paper provided by National Bureau of Economic Research, Inc in its series NBER Working Papers with number 16532.

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Date of creation: Nov 2010
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Publication status: published as Estimating Turning Points Using Large Data Sets (with James H. Stock), Journal of Econometrics, forthcoming.
Handle: RePEc:nbr:nberwo:16532
Note: EFG ME
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  1. Hamilton, James D., 2011. "Calling recessions in real time," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1006-1026, October.
  2. Hamilton, James D, 1989. "A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle," Econometrica, Econometric Society, vol. 57(2), pages 357-84, March.
  3. Harding, Don & Pagan, Adrian, 2006. "Synchronization of cycles," Journal of Econometrics, Elsevier, vol. 132(1), pages 59-79, May.
  4. Marcelle Chauvet & Jeremy M. Piger, 2005. "A comparison of the real-time performance of business cycle dating methods," Working Papers 2005-021, Federal Reserve Bank of St. Louis.
  5. Gerhard Bry & Charlotte Boschan, 1971. "Foreword to "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs"," NBER Chapters, in: Cyclical Analysis of Time Series: Selected Procedures and Computer Programs, pages -1 National Bureau of Economic Research, Inc.
  6. Jeremy J. Nalewaik, 2010. "The Income- and Expenditure-Side Estimates of U.S. Output Growth," Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 41(1 (Spring), pages 71-127.
  7. Gerhard Bry & Charlotte Boschan, 1971. "Cyclical Analysis of Time Series: Selected Procedures and Computer Programs," NBER Books, National Bureau of Economic Research, Inc, number bry_71-1, September.
  8. James H. Stock & Mark W. Watson, 2010. "Indicators for Dating Business Cycles: Cross-History Selection and Comparisons," American Economic Review, American Economic Association, vol. 100(2), pages 16-19, May.
  9. Stock, J.H. & Watson, M.W., 1989. "New Indexes Of Coincident And Leading Economic Indicators," Papers 178d, Harvard - J.F. Kennedy School of Government.
  10. Arthur F. Burns & Wesley C. Mitchell, 1946. "Measuring Business Cycles," NBER Books, National Bureau of Economic Research, Inc, number burn46-1, September.
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