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A Bayesian vector error corrections model of the U.S. economy

  • Tom Stark
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    This paper presents a small-scale macroeconometric time-series model that can be used to generate short-term forecasts for U.S. output, inflation, and the rate of unemployment. Drawing on both the Bayesian VAR and vector error corrections (VEC) literature, the author specifies the baseline model as a Bayesian VEC. The author documents the model's forecasting ability over various periods, examines its impulse responses, and considers several reasonable alternative specifications. Based on a root-mean-square-error criterion, the baseline model works best, and the author concludes that this model holds promise as a workhorse forecasting tool.

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    Paper provided by Federal Reserve Bank of Philadelphia in its series Working Papers with number 98-12.

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    Date of creation: 1998
    Date of revision:
    Handle: RePEc:fip:fedpwp:98-12
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