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Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions

  • Athanasopoulos, George
  • de Carvalho Guillén, Osmani Teixeira
  • Issler, João Victor
  • Vahid, Farshid

We study the joint determination of the lag length, the dimension of the cointegrating space and the rank of the matrix of short-run parameters of a vector autoregressive (VAR) model using model selection criteria. We suggest a new two-step model selection procedure which is a hybrid of traditional criteria and criteria with data-dependant penalties and we prove its consistency. A Monte Carlo study explores the finite sample performance of this procedure and evaluates the forecasting accuracy of models selected by this procedure. Two empirical applications confirm the usefulness of the model selection procedure proposed here for forecasting.

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Article provided by Elsevier in its journal Journal of Econometrics.

Volume (Year): 164 (2011)
Issue (Month): 1 (September)
Pages: 116-129

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Handle: RePEc:eee:econom:v:164:y:2011:i:1:p:116-129
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