Minimum Distance Estimation and Testing of DSGE Models from Structural VARs*
针对DSGE模型的最小距离估计中权重矩阵非最优的问题，提出用模拟方法构造检验统计量的临界值，并用美国数据演示。
Abstract 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.