A Simple Wavelet-Based Test for Serial Correlation in Panel Data Models

Yushu Li and Fredrik Andersson

No 2013:39, Working Papers from Lund University, Department of Economics

Abstract: Hong and Kao (2004) proposed a panel data test for serial correlation of unknown form. However, their test is computationally difficult to implement, and simulation studies show the test to have bad small-sample properties. We extend Gencay’s (2011) time series test for serial correlation to the panel data case in the framework proposed by Hong and Kao (2004). Our new test maintains the advantages of the Hong and Kao (2004) test, and it is simpler and easier to implement. Furthermore, simulation results show that our test has quicker convergence and hence better small-sample properties.

Keywords: energy distribution; MODWT; serial correlation; static and dynamic panel models (search for similar items in EconPapers)
JEL-codes: C11 C12 C15 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2013-11-28
New Economics Papers: this item is included in nep-ecm
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://project.nek.lu.se/publications/workpap/papers/WP13_39.pdf (application/pdf)
Our link check indicates that this URL is bad, the error code is: 500 Can't connect to project.nek.lu.se:80 (nodename nor servname provided, or not known)

Related works:
Journal Article: A simple wavelet-based test for serial correlation in panel data models (2021)
Working Paper: A simple wavelet-based test for serial correlation in panel data models (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:hhs:lunewp:2013_039

Access Statistics for this paper

More papers in Working Papers from Lund University, Department of Economics School of Economics and Management, Box 7080, S-22007 Lund, Sweden. Contact information at EDIRC.
Bibliographic data for series maintained by Iker Arregui Alegria ().