کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5096495 | 1376531 | 2012 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Simple and powerful GMM over-identification tests with accurate size
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
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چکیده انگلیسی
Based on the series long run variance estimator, we propose a new class of over-identification tests that are robust to heteroscedasticity and autocorrelation of unknown forms. We show that when the number of terms used in the series long run variance estimator is fixed, the conventional J statistic, after a simple correction, is asymptotically F-distributed. We apply the idea of the F-approximation to the conventional kernel-based J tests. Simulations show that the Jâ tests based on the finite sample corrected J statistic and the F-approximation have virtually no size distortion, and yet are as powerful as the standard J tests.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 166, Issue 2, February 2012, Pages 267-281
Journal: Journal of Econometrics - Volume 166, Issue 2, February 2012, Pages 267-281
نویسندگان
Yixiao Sun, Min Seong Kim,