A simple wavelet-based test for serial correlation in panel data models

Yushu Li () and Fredrik Andersson
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Yushu Li: University of Bergen

Empirical Economics, 2021, vol. 60, issue 5, No 8, 2363 pages

Abstract: 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.

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)
Date: 2021
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Citations: View citations in EconPapers (1)

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Working Paper: A simple wavelet-based test for serial correlation in panel data models (2014)
Working Paper: A Simple Wavelet-Based Test for Serial Correlation in Panel Data Models (2013)
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DOI: 10.1007/s00181-020-01830-6

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