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

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  • Tom Stark

Abstract

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.

Suggested Citation

  • Tom Stark, 1998. "A Bayesian vector error corrections model of the U.S. economy," Working Papers 98-12, Federal Reserve Bank of Philadelphia.
    • Handle: RePEc:fip:fedpwp:98-12
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    Cited by:

    1. Croushore, Dean & Stark, Tom, 2001. "A real-time data set for macroeconomists," Journal of Econometrics, Elsevier, vol. 105(1), pages 111-130, November.
    2. Stark, Tom & Croushore, Dean, 2002. "Forecasting with a real-time data set for macroeconomists," Journal of Macroeconomics, Elsevier, vol. 24(4), pages 507-531, December.
    3. Michal Benèík, 2022. "United in Diversity. Labor Markets in the CEE Countries," Journal of Economics / Ekonomicky casopis, Institute of Economic Research, Slovak Academy of Sciences, vol. 70(4), pages 333-348, April.
    4. Tom Stark, 2000. "Does current-quarter information improve quarterly forecasts for the U.S. economy?," Working Papers 00-2, Federal Reserve Bank of Philadelphia.
    5. René Lalonde, 2000. "Le modèle USM d'analyse et de projection de l'économie américaine," Staff Working Papers 00-19, Bank of Canada.
    6. Dean Croushore & Tom Stark, 2000. "A real-time data set for macroeconomists: does data vintage matter for forecasting?," Working Papers 00-6, Federal Reserve Bank of Philadelphia.
    7. Munehisa Kasuya & Tomoki Tanemura, 2000. "Small Scale Bayesian VAR Modeling of the Japanese Macro Economy Using the Posterior Information Criterion and Monte Carlo Experiments," Bank of Japan Working Paper Series Research and Statistics D, Bank of Japan.
    8. Dean Croushore & Tom Stark, 1999. "Does data vintage matter for forecasting?," Working Papers 99-15, Federal Reserve Bank of Philadelphia.

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