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A Bayesian vector error corrections model of the U.S. economy Author info | Abstract | Publisher info | Download info | Related research | Statistics Tom Stark
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: 1998Date of revision:
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Keywords: Forecasting ; Time-series analysis ; Other versions of this item:
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Full
references Cited by : (explanations , Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile , click on "citations" and make appropriate adjustments.)
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.
[Downloadable!]
Tom Stark & Dean Croushore, 2001.
"Forecasting with a real-time data set for macroeconomists ,"
Working Papers
01-10, Federal Reserve Bank of Philadelphia.
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Other versions:
Tom Stark and Dean Croushore, 2001.
"Forecasting with a Real-Time Data Set for Macroeconomists ,"
Computing in Economics and Finance 2001
258, Society for Computational Economics.
Stark, Tom & Croushore, Dean, 2002.
"Forecasting with a real-time data set for macroeconomists ,"
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[Downloadable!] (restricted) Tom Stark, 2000.
"Does current-quarter information improve quarterly forecasts for the U.S. economy? ,"
Working Papers
00-2, Federal Reserve Bank of Philadelphia.
[Downloadable!]
Dean Croushore & Tom Stark, 1999.
"Does data vintage matter for forecasting? ,"
Working Papers
99-15, Federal Reserve Bank of Philadelphia.
[Downloadable!]
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