کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
10482551 | 934105 | 2013 | 15 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Heteroskedasticity and non-normality robust LM tests for spatial dependence
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کلمات کلیدی
موضوعات مرتبط
علوم انسانی و اجتماعی
اقتصاد، اقتصادسنجی و امور مالی
اقتصاد و اقتصادسنجی
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چکیده انگلیسی
The standard LM tests for spatial dependence in linear and panel regressions are derived under the normality and homoskedasticity assumptions of the regression disturbances. Hence, they may not be robust against non-normality or heteroskedasticity of the disturbances. Following Born and Breitung (2011), we introduce general methods to modify the standard LM tests so that they become robust against heteroskedasticity and non-normality. The idea behind the robustification is to decompose the concentrated score function into a sum of uncorrelated terms so that the outer product of gradient (OPG) can be used to estimate its variance. We also provide methods for improving the finite sample performance of the proposed tests. These methods are then applied to several popular spatial models. Monte Carlo results show that they work well in finite sample.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Regional Science and Urban Economics - Volume 43, Issue 5, September 2013, Pages 725-739
Journal: Regional Science and Urban Economics - Volume 43, Issue 5, September 2013, Pages 725-739
نویسندگان
Badi H. Baltagi, Zhenlin Yang,