Evidence on Structural Instability in Macroeconomic Time Series Relations

James H. Stock and Mark Watson

No 164, NBER Technical Working Papers from National Bureau of Economic Research, Inc

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 76 representative U.S. monthly postwar macroeconomic time series, constituting 5700 bivariate forecasting relations. The tests indicate widespread instability in univariate and bivariate autoregressive models. However, adaptive forecasting models, in particular time varying parameter models, have limited success in exploiting this instability to improve upon fixed-parameter or recursive autoregressive forecasts.

JEL-codes: C32 E37 (search for similar items in EconPapers)
Date: 1994-09
Note: EFG
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (10)

Published as Journal of Business and Economic Statistics (1996)

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