MONTE-CARLO METHODOLOGY AND THE FINITE-SAMPLE PROPERTIES OF INSTRUMENTAL VARIABLES STATISTICS FOR TESTING NESTED AND NONNESTED HYPOTHESES

• 成果类型: Article
• 署名作者: ERICSSON, NR
• 刊物名称: ECONOMETRICA
• ISSN/ISSBN: 0012-9682
• DOI: 10.2307/2938367
• 发表日期: 1991
• 页码: 1249-1277
• 关键词: regression-models; least-squares; estimators; disturbances; specification; equation; approximations; distributions; selection

摘要

Using Monte Carlo methodology, this paper investigates the effect of dynamics and simultaneity on the finite sample properties of instrumental variables statistics for testing nested and non-nested hypotheses. Simple numerical-analytical formulae (response surfaces) are obtained which closely approximate the statistics' unknown size and power functions for a dynamic simultaneous equations model. The analysis illustrates the value and limitations of asymptotic theory in interpreting finite sample properties. Two practical results arise. The F form of the Wald statistic is favored over its chi-2 form, and large-sigma and small effective sample size strongly affect the test of over-identifying restrictions and the Cox-type test.