Wild bootstrap approach for testing slope homogeneity in panel data models

Wild bootstrap approach for testing slope homogeneity in panel data models

Various bootstrap methods can be used for econometric analysis. In certain circumstances, appropriately chosen bootstrap method generally work very well for regression models with independent and identically distributed error terms, and the regressors and error terms are strictly exogenous. However,...

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Main Author: Chong, Shun Jie
Other Authors: Xiang Liming
Format: Final Year Project
Language:English
Published: 2019
Subjects:
DRNTU::Science::Mathematics::Statistics
Online Access:http://hdl.handle.net/10356/77123
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-771232023-02-28T23:17:31Z Wild bootstrap approach for testing slope homogeneity in panel data models Chong, Shun Jie Xiang Liming School of Physical and Mathematical Sciences DRNTU::Science::Mathematics::Statistics Various bootstrap methods can be used for econometric analysis. In certain circumstances, appropriately chosen bootstrap method generally work very well for regression models with independent and identically distributed error terms, and the regressors and error terms are strictly exogenous. However, there exist some common case, where the pooled regression models has dependent error, thus normal bootstrap method does not always perform well. This paper considers hypothesis testing for slope homogeneity in panel data models with heteroscedastic disturbances using wild bootstrap approach. Simulation experiments show that using wild bootstrap to approximate the distribution of each test statistic performs well in this context. Bachelor of Science in Mathematical Sciences 2019-05-09T06:38:31Z 2019-05-09T06:38:31Z 2019 Final Year Project (FYP) http://hdl.handle.net/10356/77123 en 20 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Science::Mathematics::Statistics
spellingShingle DRNTU::Science::Mathematics::Statistics
Chong, Shun Jie
Wild bootstrap approach for testing slope homogeneity in panel data models
description Various bootstrap methods can be used for econometric analysis. In certain circumstances, appropriately chosen bootstrap method generally work very well for regression models with independent and identically distributed error terms, and the regressors and error terms are strictly exogenous. However, there exist some common case, where the pooled regression models has dependent error, thus normal bootstrap method does not always perform well. This paper considers hypothesis testing for slope homogeneity in panel data models with heteroscedastic disturbances using wild bootstrap approach. Simulation experiments show that using wild bootstrap to approximate the distribution of each test statistic performs well in this context.
author2 Xiang Liming
author_facet Xiang Liming
Chong, Shun Jie
format Final Year Project
author Chong, Shun Jie
author_sort Chong, Shun Jie
title Wild bootstrap approach for testing slope homogeneity in panel data models
title_short Wild bootstrap approach for testing slope homogeneity in panel data models
title_full Wild bootstrap approach for testing slope homogeneity in panel data models
title_fullStr Wild bootstrap approach for testing slope homogeneity in panel data models
title_full_unstemmed Wild bootstrap approach for testing slope homogeneity in panel data models
title_sort wild bootstrap approach for testing slope homogeneity in panel data models
publishDate 2019
url http://hdl.handle.net/10356/77123
_version_ 1759857173430534144

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