Estimating Sectoral Cycles Using Cointegration and Common Features

57 Pages Posted: 22 Aug 2007 Last revised: 18 Nov 2022

See all articles by João Victor Issler

João Victor Issler

Getulio Vargas Foundation (FGV) - FGV/EPGE Escola Brasileira de Economia e Finanças

Robert F. Engle

New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER); New York University (NYU) - Volatility and Risk Institute

Date Written: November 1993

Abstract

This paper investigates the degree of short run and long run comovement in U.S. sectoral output data by estimating sectoral trends and cycles. A theoretical model based on Long and Plosser (1983) is used to derive a reduced form for sectoral output from first principles. Cointegration and common features (cycles) tests are performed and sectoral output data seem to share a relatively high number of common trends and a relatively low number of common cycles. A special trend-cycle decomposition of the data set is performed and the results indicate a very similar cyclical behavior across sectors and a very different behavior for trends. In a variance decomposition exercise, for prominent sectors such as Manufacturing and Wholesale/Retail Trade, the cyclical innovation is more important than the trend innovation.

Suggested Citation

Issler, João Victor and Engle, Robert F., Estimating Sectoral Cycles Using Cointegration and Common Features (November 1993). NBER Working Paper No. w4529, Available at SSRN: https://ssrn.com/abstract=480272

João Victor Issler

Getulio Vargas Foundation (FGV) - FGV/EPGE Escola Brasileira de Economia e Finanças ( email )

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Robert F. Engle (Contact Author)

New York University (NYU) - Department of Finance ( email )

Stern School of Business
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National Bureau of Economic Research (NBER) ( email )

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New York University (NYU) - Volatility and Risk Institute ( email )

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New York, NY 10012
United States

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