Small-sample properties of GMM for business-cycle analysis

被引：27

作者：

Christiano, LJ ^{[1
]}

denHaan, WJ ^{[1
]}

机构：

[1] UNIV CALIF SAN DIEGO,DEPT ECON,SAN DIEGO,CA 92093

来源：

JOURNAL OF BUSINESS & ECONOMIC STATISTICS | 1996年 / 14卷 / 03期

关键词：

covariance matrix estimation; finite-sample analysis; hypothesis testing; Monte Carlo simulation; prewhitening; spectral density;

D O I：

10.2307/1392445

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

We investigate, by Monte Carlo methods, the finite-sample properties of generalized method of moment procedures for conducting inference about statistics that are of interest in the business-cycle literature. These statistics include the second moments of data filtered using the first-difference and Hodrick-Prescott filters, and they include statistics for evaluating model fit. Our results indicate that, for the procedures considered, the existing asymptotic theory is not a good guide in a sample the size of quarterly postwar U.S. data.

引用

页码：309 / 327

页数：19

共 63 条

[1] AN IMPROVED HETEROSKEDASTICITY AND AUTOCORRELATION CONSISTENT COVARIANCE-MATRIX ESTIMATOR [J].