کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
5095658 | 1376477 | 2017 | 43 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Statistical inference for independent component analysis: Application to structural VAR models
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
آمار و احتمال
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Statistical inference for independent component analysis: Application to structural VAR models Statistical inference for independent component analysis: Application to structural VAR models](/preview/png/5095658.png)
چکیده انگلیسی
The well-known problem of non-identifiability of structural VAR models disappears if the structural shocks are independent and if at most one of them is Gaussian. In that case, the relevant estimation technique is the Independent Component Analysis (ICA). Since the introduction of ICA by Comon (1994), various semi-parametric estimation methods have been proposed for “orthogonalizing” the error terms. These methods include pseudo maximum likelihood (PML) approaches and recursive PML. The aim of our paper is to derive the asymptotic properties of the PML approaches, in particular to study their consistency. We conduct Monte Carlo studies exploring the relative performances of these methods. Finally, an application based on real data shows that structural VAR models can be estimated without additional identification restrictions in the non-Gaussian case and that the usual restrictions can be tested.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Econometrics - Volume 196, Issue 1, January 2017, Pages 111-126
Journal: Journal of Econometrics - Volume 196, Issue 1, January 2017, Pages 111-126
نویسندگان
Christian Gouriéroux, Alain Monfort, Jean-Paul Renne,