Using VARs and TVP-VARs with Many Macroeconomic Variables

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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.
Original languageEnglish
Place of PublicationGlasgow
PublisherUniversity of Strathclyde
Number of pages35
Publication statusPublished - 14 Jan 2013


  • bayesian var
  • forecasting
  • time-varying coefficients
  • state-space model


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