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Using VARs and TVP-VARs with Many Macroeconomic Variables

Gary Koop

No 2013-35, SIRE Discussion Papers from Scottish Institute for Research in Economics (SIRE)

Abstract: This paper discusses the challenges faced by the empirical macroeconomist and methods for surmounting them. These challenges arise due to the fact that macroeconometric models potentially include a large number of variables and allow for time variation in parameters. These considerations lead to models which have a large number of parameters to estimate relative to the number of observations. A wide range of approaches are surveyed which aim to overcome the resulting problems. We stress the related themes of prior shrinkage, model averaging and model selection. Subsequently, we consider a particular modelling approach in detail. This involves the use of dynamic model selection methods with large TVP-VARs. A forecasting exercise involving a large US macroeconomic data set illustrates the practicality and empirical success of our approach.

Keywords: Bayesian VAR; forecasting; time-varying coefficients; state-space model (search for similar items in EconPapers)
Date: 2013
New Economics Papers: this item is included in nep-ets and nep-for
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Citations: View citations in EconPapers (1)

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Related works:
Working Paper: Using VARs and TVP-VARs with Many Macroeconomic Variables (2013) Downloads
Journal Article: Using VARs and TVP-VARs with Many Macroeconomic Variables (2012) Downloads
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