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HETEROSKEDASTICITY-ROBUST TESTING FOR A FRACTIONAL UNIT ROOT
Published online by Cambridge University Press: 01 December 2009
Abstract
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This paper shows how fractional unit root tests originally derived under stationarity can be made robust to heteroskedasticity. This is done by using existing tests nested in a regression framework and then implementing these tests using White’s heteroskedasticity consistent standard errors (White, 1980). We show this approach is effective both asymptotically and in finite samples. We also provide some evidence on the asymptotic local power of different implementations of the tests, under both homoskedasticity and heteroskedasticity.
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- Econometric Theory , Volume 25 , Issue 6: Newbold Conference Special Issue , December 2009 , pp. 1734 - 1753
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- Copyright © Cambridge University Press 2009
References
REFERENCES
Agiakloglou, C. & Newbold, P. (1994) Lagrange multiplier tests for fractional difference. Journal of Time Series Analysis 15, 253–262.CrossRefGoogle Scholar
Breitung, J. & Hassler, U. (2002) Inference on the cointegration rank in fractionally integrated processes. Journal of Econometrics 110, 167–185.CrossRefGoogle Scholar
Cavaliere, G. (2004) Unit root tests under time-varying variances. Econometric Reviews 23, 259–292.CrossRefGoogle Scholar
Cavaliere, G. & Taylor, A.M.R. (2007) Testing for unit roots in time series models with non-stationary volatility. Journal of Econometrics 140, 919–947.CrossRefGoogle Scholar
Cavaliere, G. & Taylor, A.M.R. (2008a) Bootstrap unit root tests for time series with nonstationary volatility. Econometric Theory 24, 43–71.CrossRefGoogle Scholar
Cavaliere, G. & Taylor, A.M.R. (2008b) Time-transformed unit root tests for models with non-stationary volatility. Journal of Time Series Analysis 29, 300–330.CrossRefGoogle Scholar
Demetrescu, M., Kuzin, V., & Hassler, U. (2008) Long memory testing in the time domain. Econometric Theory 24, 176–215.CrossRefGoogle Scholar
Deo, R. (2000) Spectral tests of the martingale hypothesis under conditional heteroscedasticity. Journal of Econometrics 99, 291–315.CrossRefGoogle Scholar
Dolado, J.J., Gonzalo, J., & Mayoral, L. (2002) A fractional Dickey–Fuller test for unit roots. Econometrica 70, 1963–2006.CrossRefGoogle Scholar
Engle, R.F. (1982) Autoregressive conditional heteroskedasticity with estimates of the variance of United Kingdom inflation. Econometrica 50, 987–1007.CrossRefGoogle Scholar
Hamori, S. & Tokihisa, A. (1997) Testing for a unit root in the presence of a variance shift. Economics Letters 57, 245–253.CrossRefGoogle Scholar
Hansen, B.E. (1995) Regression with nonstationary volatility. Econometrica 63, 1113–1132.CrossRefGoogle Scholar
Kew, H. (2007) Estimation and testing of a fractionally integrated model under heteroskedasticity. Ph.D. Dissertation, University of Melbourne.Google Scholar
Kew, H. & Harris, D. (2008) Heteroskedasticity Robust Testing for a Fractional Unit Root. Working paper, University of Melbourne. Available at SSRN: http://ssrn.com/abstract=1184333.CrossRefGoogle Scholar
Kim, T.H., Leybourne, S., & Newbold, P. (2002) Unit root tests with a break in innovation variance. Journal of Econometrics 109, 365–387.CrossRefGoogle Scholar
Lobato, I.N. & Velasco, C. (2006) Optimal fractional Dickey–Fuller tests. Econometrics Journal 9, 492–510.CrossRefGoogle Scholar
Lobato, I.N. & Velasco, C. (2007) Efficient Wald tests for fractional unit roots. Econometrica 75, 575–589.CrossRefGoogle Scholar
Marinucci, D. & Robinson, P.M. (1999) Alternative forms of fractional Brownian motion. Journal of Statistical Planning and Inference 80, 111–122.CrossRefGoogle Scholar
Mayoral, L. (2007) Minimum distance estimation of stationary and non-stationary ARFIMA processes. Econometrics Journal 10, 124–148.CrossRefGoogle Scholar
McConnell, M.M. & Perez-Quiros, G. (2000) Output fluctuations in the United States: What has changed since the early 1980s? American Economic Review 90, 1464–1476.CrossRefGoogle Scholar
Nicholls, D.F. & Pagan, A.R. (1983) Heteroscedasticity in models with lagged dependent variables. Econometrica 51, 1233–1242.CrossRefGoogle Scholar
Phillips, P.C.B. & Xu, K.-L. (2006) Inference in autoregression under heteroskedasticity. Journal of Time Series Analysis 27, 289–308.CrossRefGoogle Scholar
Robinson, P.M. (1991) Testing for strong serial correlation and dynamic conditional heteroskedasticity in multiple regression. Journal of Econometrics 47, 67–84.CrossRefGoogle Scholar
Robinson, P.M. (1994) Efficient tests of nonstationary hypotheses. Journal of the American Statistical Association 89, 1420–1437.CrossRefGoogle Scholar
Tanaka, K. (1999) The nonstationary fractional unit root. Econometric Theory 15, 549–582.CrossRefGoogle Scholar
van Dijk, D., Osborn, D.R., & Sensier, M. (2002) Changes in Variability of the Business Cycles in the G7 Countries. Econometric Institute Report EI 2002–28.Google Scholar
Watson, M.W. (1999) Explaining the increased variability in long-term interest rates. Federal Reserve Bank of Richmond Economic Quarterly 85, 71–96.Google Scholar
White, H. (1980) A heteroskedasticity-consistent covariance matrix estimator and a direct test for heteroskedasticity. Econometrica 48, 817–838.CrossRefGoogle Scholar
Wooldridge, J. (1991) On the application of robust regression-based diagnostics to models of conditional means and conditional variances. Journal of Econometrics 47, 5–46.CrossRefGoogle Scholar
Xu, K.-L. & Phillips, P.C.B. (2008) Adaptive estimation of autoregressive models with time-varying variances. Journal of Econometrics 142, 265–280.CrossRefGoogle Scholar
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