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Explaining Long- and Short-Run Interactions in Time Series Data

Lucio Picci

Journal of Business & Economic Statistics, 2001, vol. 19, issue 1, 85-94

Abstract: In this article, I extend the concept of separate cointegration to include the common-feature trend-cycle decomposition approach. This combined approach operates a reduction of the parameter space and permits the identification of the time series long- and short-run constituent factors. A careful assessment of their reciprocal relations, in turn, allows for the answering of potentially interesting economic questions. To show the usefulness of the proposed methodology, I apply it to the study of the relationships between the international business cycle and trade flows.

Date: 2001
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Handle: RePEc:bes:jnlbes:v:19:y:2001:i:1:p:85-94