Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model. All authors are Fellows at the Rimini Centre for Economic Analysis. Corresponding author: Gary Koop, Department of Economics, University of Strathclyde, Glasgow, G4 0GE, UK, email: [email protected]