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The local power of some unit root tests for panel data

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  • Breitung, Jörg

Abstract

To test the hypothesis of a difference stationary time series against a trend stationary alternative, Levin and Lin (1993) and Im, Pesaran and Shin (1997) suggest bias adjusted t-statistics. Such corrections are necessary to account for the nonzero mean of the t-statistic in the case of an OLS detrending method. In this paper the local power of panel unit root statistics against a sequence of local alternatives is studied. It is shown that the local power of the test statistics is affected by two different terms. The first term represents the asymptotic effect on the bias due the detrending method and the second term is the usual location parameter of the limiting distribution under the sequence of local alternatives. It is argued that both terms can offset each other so that the test has no power against the sequence of local alternatives. This results suggest to construct test statistics based on alternative detrending methods. We consider a class of t-statistics that do not require a bias correction. The results of a Monte Carlo experiment suggest that avoiding the bias can improve the power of the test substantially.

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  • Breitung, Jörg, 1999. "The local power of some unit root tests for panel data," SFB 373 Discussion Papers 1999,69, Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes.
  • Handle: RePEc:zbw:sfb373:199969
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    3. Habibullah, M.S. & Law, Siong-Hook & Dayang-Afizzah, A.M., 2008. "Defense spending and economic growth in Asian economies: A panel error-correction approach," MPRA Paper 12105, University Library of Munich, Germany.
    4. Moon, Hyungsik Roger & Perron, Benoit & Phillips, Peter C.B., 2007. "Incidental trends and the power of panel unit root tests," Journal of Econometrics, Elsevier, vol. 141(2), pages 416-459, December.
    5. Andros Gregoriou, 2010. "Corporate Valuation and Dividends: UK Evidence from Panel Unit Root and Cointegration Tests," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 38(1), pages 15-22, March.
    6. Badi H. Baltagi & Chihwa Kao, 2000. "Nonstationary Panels, Cointegration in Panels and Dynamic Panels: A Survey," Center for Policy Research Working Papers 16, Center for Policy Research, Maxwell School, Syracuse University.
    7. Robin Johnson & W. A. Razzak & Steven Stillman, 2007. "Has New Zealand benefited from its investments in research & development?," Applied Economics, Taylor & Francis Journals, vol. 39(19), pages 2425-2440.
    8. Lee, Bun Song & Chun, Sun Eae & Kim, Suk Young, 2007. "The effects of regional characteristics on population growth in Korean cities, counties and wards," Journal of Asian Economics, Elsevier, vol. 18(3), pages 490-508, June.
    9. Stojkoski, Viktor & Kocarev, Ljupco, 2017. "The Relationship Between Growth and Economic Complexity: Evidence from Southeastern and Central Europe," MPRA Paper 77837, University Library of Munich, Germany, revised 2017.
    10. repec:eee:rensus:v:77:y:2017:i:c:p:506-514 is not listed on IDEAS
    11. Dutta, Champa Bati & Das, Debasish Kumar, 2016. "Does disaggregated CO2 emission matter for growth? Evidence from thirty countries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 825-833.
    12. Christopoulos, Dimitris K. & Tsionas, Efthymios G., 2004. "Financial development and economic growth: evidence from panel unit root and cointegration tests," Journal of Development Economics, Elsevier, vol. 73(1), pages 55-74, February.

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