Premium
Minimum Distance Estimation and Testing of DSGE Models from Structural VARs *
Author(s) -
Fève Patrick,
Matheron Julien,
Sahuc JeanGuillaume
Publication year - 2009
Publication title -
oxford bulletin of economics and statistics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.131
H-Index - 73
eISSN - 1468-0084
pISSN - 0305-9049
DOI - 10.1111/j.1468-0084.2009.00562.x
Subject(s) - weighting , vector autoregression , impulse response , covariance matrix , collinearity , dynamic stochastic general equilibrium , econometrics , mathematics , autoregressive model , covariance , mathematical optimization , statistics , economics , medicine , monetary policy , mathematical analysis , monetary economics , radiology
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.