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Sectoral vs. aggregate shocks : a structural factor analysis of industrial production

  • Andrew T. Foerster
  • Pierre-Daniel G. Sarte
  • Mark W. Watson

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.

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Paper provided by Federal Reserve Bank of Richmond in its series Working Paper with number 08-07.

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Date of creation: 2008
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Handle: RePEc:fip:fedrwp:08-07
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  1. Andrew T. Foerster & Pierre-Daniel G. Sarte & Mark W. Watson, 2008. "Sectoral vs. Aggregate Shocks: A Structural Factor Analysis of Industrial Production," NBER Working Papers 14389, National Bureau of Economic Research, Inc.
  2. Danny Quah & Thomas J. Sargent, 1992. "A dynamic index model for large cross sections," Discussion Paper / Institute for Empirical Macroeconomics 77, Federal Reserve Bank of Minneapolis.
  3. Forni, Mario & Hallin, Marc & Lippi, Marco & Reichlin, Lucrezia, 1999. "The Generalized Dynamic Factor Model: Identification and Estimation," CEPR Discussion Papers 2338, C.E.P.R. Discussion Papers.
  4. Shea, John S, 2002. "Complementarities and Comovements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 412-33, May.
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  7. John Shea, 1995. "Complementarities and Comovements," NBER Working Papers 5305, National Bureau of Economic Research, Inc.
  8. Long, John B, Jr & Plosser, Charles I, 1987. "Sectoral vs. Aggregate Shocks in the Business Cycle," American Economic Review, American Economic Association, vol. 77(2), pages 333-36, May.
  9. Jushan Bai, 2003. "Inferential Theory for Factor Models of Large Dimensions," Econometrica, Econometric Society, vol. 71(1), pages 135-171, January.
  10. Jushan Bai & Serena Ng, 2000. "Determining the Number of Factors in Approximate Factor Models," Econometric Society World Congress 2000 Contributed Papers 1504, Econometric Society.
  11. Horvath, Michael, 2000. "Sectoral shocks and aggregate fluctuations," Journal of Monetary Economics, Elsevier, vol. 45(1), pages 69-106, February.
  12. Long, John B, Jr & Plosser, Charles I, 1983. "Real Business Cycles," Journal of Political Economy, University of Chicago Press, vol. 91(1), pages 39-69, February.
  13. Vasco M Carvalho, 2008. "Aggregate Fluctuations and the Network Structure of Intersectoral Trade," 2008 Meeting Papers 1062, Society for Economic Dynamics.
  14. Brock, William A. & Mirman, Leonard J., 1972. "Optimal economic growth and uncertainty: The discounted case," Journal of Economic Theory, Elsevier, vol. 4(3), pages 479-513, June.
  15. Connor, Gregory & Korajczyk, Robert A., 1988. "Risk and return in an equilibrium APT : Application of a new test methodology," Journal of Financial Economics, Elsevier, vol. 21(2), pages 255-289, September.
  16. Dupor, Bill, 1999. "Aggregation and irrelevance in multi-sector models," Journal of Monetary Economics, Elsevier, vol. 43(2), pages 391-409, April.
  17. Forni, Mario & Reichlin, Lucrezia, 1995. "Let's Get Real: A Dynamic Factor Analytical Approach to Disaggregated Business Cycle," CEPR Discussion Papers 1244, C.E.P.R. Discussion Papers.
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