Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/62189 
Year of Publication: 
2000
Series/Report no.: 
SFB 373 Discussion Paper No. 2000,37
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
Abstract: 
Alternative modeling strategies for specifying subset VAR models are considered. It is shown that under certain conditions a testing procedure based on t-ratios is equivalent to sequentially eliminating lags that lead to the largest improvement in a prespecified model selection criterion. A Monte Carlo study is used to illustrate the properties of different procedures. It is found that the differences between alternative strategies are small. In small samples, the strategies often fail to discover the true model. Nevertheless, using subset strategies results in models with improved forecast precision. To illustrate how these subset strategies can improve results from impulse response analysis, a VAR model is used to analyze the effects of monetary policy shocks for the U.S. economy. While the response patterns from full and subset VARs are qualitatively identical, confidence bands from the unrestricted model are considerably wider. We conclude that subset strategies can be useful modeling tools when forecasting or impulse response analysis is the main objective.
Subjects: 
Lag selection
model selection
monetary policy shocks
subset models
vector autoregressions
JEL: 
C32
E52
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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