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Evidence on structural instability in macroeconomic times series relations

  • James H. Stock
  • Mark W. Watson

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.

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Paper provided by Federal Reserve Bank of Chicago in its series Working Paper Series, Macroeconomic Issues with number 94-13.

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Date of creation: 1994
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Handle: RePEc:fip:fedhma:94-13
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