Research Article

Stochastic search variable selection in vector error correction models with an application to a model of the UK macroeconomy

  1. Markus Jochmann1,2,
  2. Gary Koop2,3,*,
  3. Roberto Leon-Gonzalez2,4,
  4. Rodney W. Strachan2,5

Article first published online: 28 MAR 2011

DOI: 10.1002/jae.1238

Additional Information

How to Cite

Jochmann, M., Koop, G., Leon-Gonzalez, R. and Strachan, R. W. (2011), Stochastic search variable selection in vector error correction models with an application to a model of the UK macroeconomy. J. Appl. Econ.. doi: 10.1002/jae.1238

Author Information

  1. 1

    Newcastle University, Newcastle upon Tyne, UK

  2. 2

    Rimini Centre for Economic Analysis, Italy

  3. 3

    Department of Economics, University of Strathclyde, Glasgow, UK

  4. 4

    National Graduate Institute for Policy Studies, Tokyo, Japan

  5. 5

    The Australian National University, Canberra, Australia

*Department of Economics, University of Strathclyde, Sir William Duncan Building, 130 Rottenrow, Glasgow G4 0GE, UK.

Publication History

  1. Article first published online: 28 MAR 2011

Funded by

  • Leverhulme Trust. Grant Number: F/00 273/J

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Abstract

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. Copyright © 2011 John Wiley & Sons, Ltd.

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