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Tests for causality between integrated variables using asymptotic and bootstrap distributions: theory and application

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  • R. Scott Hacker
  • Abdulnasser Hatemi-J

Abstract

Causality tests in the Granger's sense are increasingly applied in empirical research. Since the unit root revolution in time-series analysis, several modifications of tests for causality have been introduced in the literature. One of the recent developments is the Toda-Yamamoto modified Wald (MWALD) test, which is attractive due to its simple application, its absence of pre-testing distortions, and its basis on a standard asymptotical distribution irrespective of the number of unit roots and the cointegrating properties of the data. This study investigates the size properties of the MWALD test and finds that in small sample sizes this test performs poorly on those properties when using its asymptotical distribution, the chi-square. It is suggested that use be made of a leveraged bootstrap distribution to lower the size distortions. Monte Carlo simulation results show that an MWALD test based on a bootstrap distribution has much smaller size distortions than corresponding cases when the asymptotic distribution is used. These results hold for different sample sizes, integration orders, and error term processes (homoscedastic or ARCH). This new method is applied to the testing of the efficient market hypothesis.

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Bibliographic Info

Article provided by Taylor & Francis Journals in its journal Applied Economics.

Volume (Year): 38 (2006)
Issue (Month): 13 ()
Pages: 1489-1500

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Handle: RePEc:taf:applec:v:38:y:2006:i:13:p:1489-1500

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  1. Abdulnasser Hatemi-J & Eduardo Roca, 2005. "Exchange rates and stock prices interaction during good and bad times: evidence from the ASEAN4 countries," Applied Financial Economics, Taylor & Francis Journals, vol. 15(8), pages 539-546.
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  3. Jurgen A. Doornik & Henrik Hansen, 2008. "An Omnibus Test for Univariate and Multivariate Normality," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 70(s1), pages 927-939, December.
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  7. Peter C.B. Phillips, 1985. "Understanding Spurious Regressions in Econometrics," Cowles Foundation Discussion Papers 757, Cowles Foundation for Research in Economics, Yale University.
  8. Hatemi-J, Abdulnasser, 2004. "Is the Equity Market Informationally Efficient in Japan? Evidence from Leveraged Bootstrap Analysis," Economia Internazionale / International Economics, Camera di Commercio di Genova, vol. 57(4), pages 461-473.
  9. Yamada, Hiroshi & Toda, Hiro Y., 1998. "Inference in possibly integrated vector autoregressive models: some finite sample evidence," Journal of Econometrics, Elsevier, vol. 86(1), pages 55-95, June.
  10. Abdulnasser Hatemi-J & Eduardo Roca, 2004. "An examination of the equity market price linkage between Australia and the European Union using leveraged bootstrap method," The European Journal of Finance, Taylor & Francis Journals, vol. 10(6), pages 475-488.
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  12. Granger, C. W. J., 1981. "Some properties of time series data and their use in econometric model specification," Journal of Econometrics, Elsevier, vol. 16(1), pages 121-130, May.
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  16. R. Scott Hacker & Abdulnasser Hatemi-J, 2005. "A test for multivariate ARCH effects," Applied Economics Letters, Taylor & Francis Journals, vol. 12(7), pages 411-417.
  17. Hatemi-J, Abdulnasser, 2004. "Multivariate tests for autocorrelation in the stable and unstable VAR models," Economic Modelling, Elsevier, vol. 21(4), pages 661-683, July.
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  1. Granger Nedenselliği in Wikipedia Turkish ne '')
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