A simple wavelet-based test for serial correlation in panel data models
(2021) In Empirical Economics 60(5). p.2351-2363- Abstract
- Hong and Kao (2004) proposed a class of general applicable wavelet-based tests for serial correlation of unknown form in the residuals from a panel regression model. The tests can be applied to both static and dynamic panel models. Their test, however, is computationally difficult to implement, and simulation studies show that the test has poor small-sample properties. In this paper, we extend Gençay’s (2010) time-series test for serial correlation to panel data case. Our new test is also wavelet based and maintains the advantages of the Hong and Kao (2004) test, but it is much simpler and easier to implement. Furthermore, simulation results show that our test has quicker convergence rate and hence better small-sample properties, compared... (More)
- Hong and Kao (2004) proposed a class of general applicable wavelet-based tests for serial correlation of unknown form in the residuals from a panel regression model. The tests can be applied to both static and dynamic panel models. Their test, however, is computationally difficult to implement, and simulation studies show that the test has poor small-sample properties. In this paper, we extend Gençay’s (2010) time-series test for serial correlation to panel data case. Our new test is also wavelet based and maintains the advantages of the Hong and Kao (2004) test, but it is much simpler and easier to implement. Furthermore, simulation results show that our test has quicker convergence rate and hence better small-sample properties, compared to Hong and Kao (2004) test. We also compare our test with several other existing tests for series correlation, and our test has in general better statistical properties in terms of both size and power. (Less)
- Abstract (Swedish)
- Hong and Kao (2004) proposed a class of general applicable wavelet-based tests for serial correlation of unknown form in the residuals from a panel regression model. The tests can be applied to both static and dynamic panel models. Their test, however, is computationally difficult to implement, and simulation studies show that the test has poor small-sample properties. In this paper, we extend Gencay’s (2011) time series test for serial correlation to panel data case. Our new test is also wavelet- based and maintains the advantages of the Hong
and Kao (2004) test, but it is much simpler and easier to implement. Furthermore, simulation results show that our test has quicker convergence rate and hence better small-sample properties,... (More) - Hong and Kao (2004) proposed a class of general applicable wavelet-based tests for serial correlation of unknown form in the residuals from a panel regression model. The tests can be applied to both static and dynamic panel models. Their test, however, is computationally difficult to implement, and simulation studies show that the test has poor small-sample properties. In this paper, we extend Gencay’s (2011) time series test for serial correlation to panel data case. Our new test is also wavelet- based and maintains the advantages of the Hong
and Kao (2004) test, but it is much simpler and easier to implement. Furthermore, simulation results show that our test has quicker convergence rate and hence better small-sample properties, compared to Hong and Kao (2004) test. We also compare our test with several other existing tests for series correlation, and our test has in general better statistical properties in terms of both size and power. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1da95599-e36d-49e9-bbcb-c45158c152fe
- author
- Li, Yushu and Andersson, Fredrik N G LU
- organization
- publishing date
- 2021-05-01
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- serial correlation, wavelet, panel data
- in
- Empirical Economics
- volume
- 60
- issue
- 5
- pages
- 13 pages
- publisher
- Physica Verlag
- external identifiers
-
- scopus:85079798462
- ISSN
- 0377-7332
- DOI
- 10.1007/s00181-020-01830-6
- language
- English
- LU publication?
- yes
- id
- 1da95599-e36d-49e9-bbcb-c45158c152fe
- date added to LUP
- 2020-01-31 08:01:44
- date last changed
- 2022-04-18 20:10:32
@article{1da95599-e36d-49e9-bbcb-c45158c152fe,
abstract = {{Hong and Kao (2004) proposed a class of general applicable wavelet-based tests for serial correlation of unknown form in the residuals from a panel regression model. The tests can be applied to both static and dynamic panel models. Their test, however, is computationally difficult to implement, and simulation studies show that the test has poor small-sample properties. In this paper, we extend Gençay’s (2010) time-series test for serial correlation to panel data case. Our new test is also wavelet based and maintains the advantages of the Hong and Kao (2004) test, but it is much simpler and easier to implement. Furthermore, simulation results show that our test has quicker convergence rate and hence better small-sample properties, compared to Hong and Kao (2004) test. We also compare our test with several other existing tests for series correlation, and our test has in general better statistical properties in terms of both size and power.}},
author = {{Li, Yushu and Andersson, Fredrik N G}},
issn = {{0377-7332}},
keywords = {{serial correlation; wavelet; panel data}},
language = {{eng}},
month = {{05}},
number = {{5}},
pages = {{2351--2363}},
publisher = {{Physica Verlag}},
series = {{Empirical Economics}},
title = {{A simple wavelet-based test for serial correlation in panel data models}},
url = {{http://dx.doi.org/10.1007/s00181-020-01830-6}},
doi = {{10.1007/s00181-020-01830-6}},
volume = {{60}},
year = {{2021}},
}