Evidence on Structural Instability in Macroeconomic Time Series Relations

James Stock and Mark Watson

Journal of Business & Economic Statistics, 1996, vol. 14, issue 1, 11-30

Abstract: An experiment is performed to assess the prevalence of instability in univariate and bivariate macroeconomic time series relations and to ascertain whether various adaptive forecasting techniques successfully handle any such instability. Formal tests for instability and out-of-sample forecasts from sixteen different models are computed using a sample of seventy-six representative U.S. monthly postwar macroeconomic time series, constituting 5,700 bivariate forecasting relations. The tests for instability and the forecast comparisons suggest that there is substantial instability in a significant fraction of the univariate and bivariate autoregressive models.

Date: 1996
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Working Paper: Evidence on structural instability in macroeconomic times series relations (1994)
Working Paper: Evidence on Structural Instability in Macroeconomic Time Series Relations (1994)
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