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Bootstrap tests for unit roots based on lad estimation

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  • Moreno, Marta

Abstract

In this paper we propose a new bootstrap test for unit roots in first order autoregressive models based on least absolute deviation (LAD) estimators. It is known that the behaviour of this estimator when the distribution is heavy tailed is very good compared with least squares estimation. The innovations distribution dependence of the LAD asymptotic law is overcome using bootstrap, which automatically approaches the target distribution. We provide the bootstrap functional limit theory necessary to prove the asymptotic validity of the procedure. Our strategy avoids the usual problem of estimating the variance matrix and the density in zero, and the construction of distribution free statistics through linear combinations with the least squares estimator. Moreover, a large simulation study shows that our test has very good power behaviour compared with others proposed in the literature.

Suggested Citation

  • Moreno, Marta, 1997. "Bootstrap tests for unit roots based on lad estimation," DES - Working Papers. Statistics and Econometrics. WS 6210, Universidad Carlos III de Madrid. Departamento de Estadística.
    • Handle: RePEc:cte:wsrepe:6210
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    References listed on IDEAS

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    1. Herce, Miguel A., 1996. "Asymptotic Theory of LAD Estimation in a Unit Root Process with Finite Variance Errors," Econometric Theory, Cambridge University Press, vol. 12(1), pages 129-153, March.
    2. Phillips, P.C.B., 1991. "A Shortcut to LAD Estimator Asymptotics," Econometric Theory, Cambridge University Press, vol. 7(4), pages 450-463, December.
    3. Pollard, David, 1991. "Asymptotics for Least Absolute Deviation Regression Estimators," Econometric Theory, Cambridge University Press, vol. 7(2), pages 186-199, June.
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    Autoregrerrive process;

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