Estimating Sectoral Cycles Using Cointegration and Common Features

57 Pages Posted: 22 Aug 2007

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 - Leonard N. Stern School of Business - Department of Economics; New York University (NYU) - Department of Finance; National Bureau of Economic Research (NBER)

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 )

Praia de Botafogo 190/1125, CEP
Rio de Janeiro RJ 22253-900
Brazil
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+55 21 2553-8821 (Fax)

Robert F. Engle (Contact Author)

New York University - Leonard N. Stern School of Business - Department of Economics ( email )

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New York, NY 10003
United States

New York University (NYU) - Department of Finance

Stern School of Business
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New York, NY 10012-1126
United States

National Bureau of Economic Research (NBER)

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Cambridge, MA 02138
United States

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