Timing Structural Change: A Conditional Probabilistic Approach

25 Pages Posted: 13 Aug 2003

See all articles by David N. DeJong

David N. DeJong

University of Pittsburgh - Department of Economics

Roman Liesenfeld

University of Cologne, Department of Economics

Jean-Francois Richard

University of Pittsburgh - Department of Economics

Date Written: July 2003

Abstract

We propose a strategy for assessing structural stability in time-series frameworks when potential change dates are unknown. Existing tests for structural stability have proven to be effective in detecting the presence of structural change, but procedures for identifying timing are highly inprecise. We present a likelihood-based procedure for assigning conditional probabilities to the occurrence of structural breaks at alternative dates. We find the procedure to be effective in improving the precision with which inferences regarding timing can be made. We illustrate parametric and non-parametric implementations of the procedure through a series of Monte Carlo experiments, and an assessment of the volatility reduction in the growth rate of U.S. GDP.

Keywords: classification analysis, Monte Carlo experimentation, non-parametric approximation

JEL Classification: C22, C11, C14, C15

Suggested Citation

Dejong, David N. and Liesenfeld, Roman and Richard, Jean-Francois, Timing Structural Change: A Conditional Probabilistic Approach (July 2003). Available at SSRN: https://ssrn.com/abstract=428543 or http://dx.doi.org/10.2139/ssrn.428543

David N. Dejong

University of Pittsburgh - Department of Economics ( email )

4A21 Forbes Quad
Pittsburgh, PA 15260
United States
(412) 648-2242 (Phone)

Roman Liesenfeld

University of Cologne, Department of Economics ( email )

Albertus-Magnus-Platz
D-50931 Köln
Germany

Jean-Francois Richard (Contact Author)

University of Pittsburgh - Department of Economics ( email )

4901 Wesley Posvar Hall
230 South Bouquet Street
Pittsburgh, PA 15260
United States
412-648-1750 (Phone)

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