Sectoral vs. Aggregate Shocks: A Structural Factor Analysis of Industrial Production

40 Pages Posted: 10 Oct 2008 Last revised: 27 Oct 2022

See all articles by Andrew T. Foerster

Andrew T. Foerster

Federal Reserve Banks - Federal Reserve Bank of San Francisco

Pierre-Daniel G. Sarte

Federal Reserve Bank of Richmond

Mark W. Watson

Princeton University - Princeton School of Public and International Affairs; National Bureau of Economic Research (NBER)

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Date Written: October 2008

Abstract

This paper uses factor analytic methods to decompose industrial production (IP) into components arising from aggregate shocks and idiosyncratic sector-specific shocks. An approximate factor model finds that nearly all (90%) of the variability of quarterly growth rates in IP are associated with common factors. Because common factors may reflect sectoral shocks that have propagated by way of input-output linkages, we then use a multisector growth model to adjust for the effects of these linkages. In particular, we show that neoclassical multisector models, of the type first introduced by Long and Plosser (1983), produce an approximate factor model as a reduced form. A structural factor analysis then indicates that aggregate shocks continue to be the dominant source of variation in IP, but the importance of sectoral shocks more than doubles after the Great Moderation (to 30%). The increase in the relative importance of these shocks follows from a fall in the contribution of aggregate shocks to IP movements after 1984.

Suggested Citation

Foerster, Andrew T. and Sarte, Pierre-Daniel and Watson, Mark W., Sectoral vs. Aggregate Shocks: A Structural Factor Analysis of Industrial Production (October 2008). NBER Working Paper No. w14389, Available at SSRN: https://ssrn.com/abstract=1278462

Andrew T. Foerster

Federal Reserve Banks - Federal Reserve Bank of San Francisco ( email )

101 Market Street
San Francisco, CA 94105
United States

Pierre-Daniel Sarte

Federal Reserve Bank of Richmond ( email )

P.O. Box 27622
Richmond, VA 23261
United States

Mark W. Watson (Contact Author)

Princeton University - Princeton School of Public and International Affairs ( email )

Princeton University
Princeton, NJ 08544-1021
United States

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

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