The aim of this paper is to complement the minimum distance estimation-structural vector autoregression approach when the weighting matrix is not optimal. In empirical studies, this choice is motivated by stochastic singularity or collinearity problems associated with the covariance matrix of impulse response functions. Consequently, the asymptotic distribution cannot be used to test the economic model's fit. To circumvent this difficulty, we propose a simple simulation method to construct critical values for the test statistics. An empirical application with US data illustrates the proposed method.
机构:
Univ Modena & Reggio Emilia, Dipartimento Econ Marco Biagi, Modena, Italy
CEPR, London, England
RECent, Modena, ItalyUniv Modena & Reggio Emilia, Dipartimento Econ Marco Biagi, Modena, Italy
Forni, Mario
Gambetti, Luca
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机构:
Coll Carlo Alberto, Piazza Vincenzo Arbarello 8, I-10122 Turin, Italy
Univ Torino, Turin, Italy
BGSE, Barcelona, Spain
Univ Autonoma Barcelona, Barcelona, SpainUniv Modena & Reggio Emilia, Dipartimento Econ Marco Biagi, Modena, Italy
Gambetti, Luca
Sala, Luca
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机构:
Univ Bocconi, Dept Econ, Milan, Italy
Univ Bocconi, IGIER, Milan, Italy
Baffi Carefin, Milan, ItalyUniv Modena & Reggio Emilia, Dipartimento Econ Marco Biagi, Modena, Italy