The presence of cross-sectionally correlated error terms invalidates much inferential theory of panel data models. Recently work by Pesaran (2006) has suggested a method which makes use of cross-sectional averages to provide valid inference for stationary panel regressions with multifactor error...

This paper considers alternative approaches to the analysis of large panel data models in the presence of error cross section dependence. A popular method for modelling such dependence uses a factor error structure. Such models raise new problems for estimation and inference. This paper compares...

This paper considers forecast averaging when the same model is used but estimation is carried out over different estimation windows. It develops theoretical results for random walks when their drift and/or volatility are subject to one or more structural breaks. It is shown that compared to...

A new modelling strategy that provides a practical approach to incorporating long-run structural relationships, suggested by economic theory, in an otherwise unrestricted VAR model is applied to construct a small quarterly macroeconometric model of the UK, estimated over 1965q1-1999q4 in nine...

This paper applies an extended and generalised version of the recursive modelling strategy developed in Persaran and Timmermann (1995) to the UK stock market. The focus of the analysis is to simulate investors search in in real time for a model that can forecast stock returns. It demonstrates...

This paper discusses the ?structural cointegrating VAR? approach to macroeconometric modelling and compares it to other approaches currently followed in the literature, namely, the large-scale simultaneous equation macroeconometric models, the structural VARs, and the dynamic stochastic general...