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Factor demand linkages and the business cycle: interpreting aggregate fluctuations as sectoral fluctuations

  • Sean Holly
  • Ivan Petrella
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    This paper investigates the drivers of industry and aggregate fluctuations. We model the dynamics of a panel of highly disaggregated manufacturing sectors. This allows us to consider directly the linkages between sectors typical of any production system, in a framework where the sectors are fully heterogeneous. We establish that these features are fundamental for the propagation of the shocks in the aggregate economy. Aggregate fluctuations can be accounted for by small industry specific shocks. Moreover, a contemporaneous technology shock to all sectors in the economy, i.e. an aggregate technology shock, implies a positive response in both output and hours at the aggregate level. When this intersectoral channel is neglected we find a negative correlation as with much of the literature. This suggests that the standard technology driven Real Business Cycle paradigm is a reasonable approximation of a more complicated model featuring heterogeneously interconnected sectors.

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    Paper provided by Centre for Dynamic Macroeconomic Analysis in its series CDMA Conference Paper Series with number 0809.

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    Handle: RePEc:san:cdmacp:0809
    Contact details of provider: Postal: Department of Economics, University of St. Andrews, Fife KY16 9AL
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    1. Matthew D. Shapiro & Mark W. Watson, 1988. "Sources of Business Cycle Fluctuations," NBER Working Papers 2589, National Bureau of Economic Research, Inc.
    2. Yongsung Chang & Taeyoung Doh & Frank Schorfheide, 2006. "Non-stationary hours in a DSGE model," Working Papers 06-3, Federal Reserve Bank of Philadelphia.
    3. Mario Forni & Lucrezia Reichlin, 1998. "Let's get real: a factor analytical approach to disaggregated business cycle dynamics," ULB Institutional Repository 2013/10147, ULB -- Universite Libre de Bruxelles.
    4. Basu, Susanto & Fernald, John G., 2002. "Aggregate productivity and aggregate technology," European Economic Review, Elsevier, vol. 46(6), pages 963-991, June.
    5. M. Hashem Pesaran, 2006. "Estimation and Inference in Large Heterogeneous Panels with a Multifactor Error Structure," Econometrica, Econometric Society, vol. 74(4), pages 967-1012, 07.
    6. Jordi Gali, 1999. "Technology, Employment, and the Business Cycle: Do Technology Shocks Explain Aggregate Fluctuations?," American Economic Review, American Economic Association, vol. 89(1), pages 249-271, March.
    7. Jushan Bai & Serena Ng, 2002. "Determining the Number of Factors in Approximate Factor Models," Econometrica, Econometric Society, vol. 70(1), pages 191-221, January.
    8. 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.
    9. Susanto Basu & John G. Fernald & Miles S. Kimball, 1998. "Are technology improvements contractionary?," International Finance Discussion Papers 625, Board of Governors of the Federal Reserve System (U.S.).
    10. Yongsung Chang & Jay H. Hong, 2005. "Do technological improvements in the manufacturing sector raise or lower employment?," Working Papers 05-5, Federal Reserve Bank of Philadelphia.
    11. Young Sik Kim & Kunhong Kim, 2006. "How Important is the Intermediate Input Channel in Explaining Sectoral Employment Comovement over the Business Cycle?," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 9(4), pages 659-682, October.
    12. Hornstein, Andreas & Praschnik, Jack, 1997. "Intermediate inputs and sectoral comovement in the business cycle," Journal of Monetary Economics, Elsevier, vol. 40(3), pages 573-595, December.
    13. PESARAN M. Hashem & SCHUERMANN Til & WEINER Scott, . "Modelling Regional Interdependencies using a Global Error-Correcting Macroeconometric Model," EcoMod2003 330700121, EcoMod.
    14. Jordi Galí & David López-Salido & Javier Vallés, 2000. "Technology Shocks and Monetary policy: Assessing the Fed's Performance," Banco de Espa�a Working Papers 0013, Banco de Espa�a.
    15. Robert G. King & Charles I. Plosser & James H. Stock & Mark W. Watson, 1987. "Stochastic Trends and Economic Fluctuations," NBER Working Papers 2229, National Bureau of Economic Research, Inc.
    16. Michael Horvath, 1998. "Cyclicality and Sectoral Linkages: Aggregate Fluctuations from Independent Sectoral Shocks," Review of Economic Dynamics, Elsevier for the Society for Economic Dynamics, vol. 1(4), pages 781-808, October.
    17. Robert G. King & Sergio T. Rebelo, 2000. "Resuscitating Real Business Cycles," NBER Working Papers 7534, National Bureau of Economic Research, Inc.
    18. Pesaran, M. Hashem & Tosetti, Elisa, 2011. "Large panels with common factors and spatial correlation," Journal of Econometrics, Elsevier, vol. 161(2), pages 182-202, April.
    19. Timothy G. Conley & Bill Dupor, 2003. "A Spatial Analysis of Sectoral Complementarity," Journal of Political Economy, University of Chicago Press, vol. 111(2), pages 311-352, April.
    20. Lawrence J. Christiano & Martin Eichenbaum, 1990. "Current real business cycle theories and aggregate labor market fluctuations," Working Paper Series, Macroeconomic Issues 90, Federal Reserve Bank of Chicago.
    21. Christopher J. Erceg & Luca Guerrieri & Christopher J. Gust, 2004. "Can long-run restrictions identify technology shocks?," International Finance Discussion Papers 792, Board of Governors of the Federal Reserve System (U.S.).
    22. Douglas Staiger & James H. Stock, 1994. "Instrumental Variables Regression with Weak Instruments," NBER Technical Working Papers 0151, National Bureau of Economic Research, Inc.
    23. M. Hashem Pesaran, 2007. "A simple panel unit root test in the presence of cross-section dependence," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 22(2), pages 265-312.
    24. Dupor, Bill, 1999. "Aggregation and irrelevance in multi-sector models," Journal of Monetary Economics, Elsevier, vol. 43(2), pages 391-409, April.
    25. Jordi Gali & Pau Rabanal, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBS Model Fit Postwar U.S. Data?," NBER Working Papers 10636, National Bureau of Economic Research, Inc.
    26. Pesaran, M.H. & Smith, R., 1992. "Estimating Long-Run Relationships From Dynamic Heterogeneous Panels," Cambridge Working Papers in Economics 9215, Faculty of Economics, University of Cambridge.
    27. repec:tpr:qjecon:v:102:y:1987:i:2:p:395-409 is not listed on IDEAS
    28. King, Robert G. & Plosser, Charles I. & Rebelo, Sergio T., 1988. "Production, growth and business cycles : I. The basic neoclassical model," Journal of Monetary Economics, Elsevier, vol. 21(2-3), pages 195-232.
    29. Galí, Jordi & Rabanal, Pau, 2004. "Technology Shocks and Aggregate Fluctuations: How Well Does the RBC Model Fit Post-War US Data?," CEPR Discussion Papers 4522, C.E.P.R. Discussion Papers.
    30. Pagan, A.R. & Pesaran, M. Hashem, 2008. "Econometric analysis of structural systems with permanent and transitory shocks," Journal of Economic Dynamics and Control, Elsevier, vol. 32(10), pages 3376-3395, October.
    31. Shea, John S, 2002. "Complementarities and Comovements," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 34(2), pages 412-33, May.
    32. Jovanovic, Boyan, 1986. "Micro Shocks and Aggregate Risks," Working Papers 86-14, C.V. Starr Center for Applied Economics, New York University.
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