کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10327828 | 681423 | 2005 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The wild bootstrap and heteroskedasticity-robust tests for serial correlation in dynamic regression models
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موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: The wild bootstrap and heteroskedasticity-robust tests for serial correlation in dynamic regression models The wild bootstrap and heteroskedasticity-robust tests for serial correlation in dynamic regression models](/preview/png/10327828.png)
چکیده انگلیسی
Conditional heteroskedasticity is a common feature of financial and macroeconomic time series data. When such heteroskedasticity is present, standard checks for serial correlation in dynamic regression models are inappropriate. In such circumstances, it is obviously important to have asymptotically valid tests that are reliable in finite samples. Monte Carlo evidence reported in this paper indicates that asymptotic critical values fail to give good control of finite sample significance levels of heteroskedasticity-robust versions of the standard Lagrange multiplier test, a Hausman-type check, and a new procedure. The application of computer-intensive methods to removing size distortion is, therefore, examined. It is found that a particularly simple form of the wild bootstrap leads to well-behaved tests. Some simulation evidence on power is also given.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 49, Issue 2, 30 April 2005, Pages 377-395
Journal: Computational Statistics & Data Analysis - Volume 49, Issue 2, 30 April 2005, Pages 377-395
نویسندگان
L.G. Godfrey, A.R. Tremayne,