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

AUTOR(ES)

Athanasopoulos, George

FONTE

Escola de Pós-Graduação em Economia da FGV

DATA DE PUBLICAÇÃO

27/01/2011

RESUMO

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.

ASSUNTO(S)

reduced rank models model selection criteria forecasting accurancy análise de regressão modelos macroecômicos previsão econômica método de monte carlo modelos de simulação

Documentos Relacionados

• Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
• Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
• Model selection, estimation and forecasting in VAR models with short-run and long-run restrictions
• ESTIMAÇÃO E PREVISÃO EM MODELOS VAR COM RESTRIÇÕES DE CURTO E LONGO PRAZO: UM ESTUDO MONTE CARLO
• Forecasting Accuracy and Estimation Uncertainty using VAR Models with Short- and Long-Term Economic Restrictions: A Monte-Carlo Study