Forecasting economic and financial variables with global VARs

Rejoinder to Comments on Forecasting Economic and Financial Variables with Global VARs

Comment: “Forecasting economic and financial variables with global VARs” by Pesaran, Schuermann and Smith

This paper reports the short-term forecasting power of the large Global Vector Autoregressive (GVAR) model originally developed by Pesaran, Schuermann, and Weiner (2004a, 2004b; PSW), and subsequently fine-tuned and re-estimated over the period 1979Q1–2003Q4 by Dees, di Mauro, Pesaran, and Smith (2007; DdPS).1 The GVAR model explicitly specifies interdependencies between different countries and...

“ Forecasting Economic and Financial Variables with Global VARs ” by M . Hashem

This paper reports the near term forecasting power of a large Global Vector Autoregressive (GVAR) model originally developed by Pesaran, Schuermann and Weiner, PSW, (2004) and subsequently fine-tuned and re-estimated over 1979Q1-1 The GVAR model explicitly specifies interdependencies between different countries and sub-regions in terms of three transparent channels: i) domestic variables are re...

Forecasting with Dimension Switching VARs

This paper develops methods for Bayesian VAR forecasting when the researcher is uncertain about which variables enter the VAR and the dimension of the VAR may be changing over time. It considers the case where there are N variables which might potentially enter a VAR and the researcher is interested in forecasting N∗ of them. Thus, the researcher is faced with 2N−N ∗ potential VARs. If N is lar...

Using VARs and TVP-VARs with Many Macroeconomic Variables

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...