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Approximate Asymptotic Distribution Functions for Unit Roots and Cointegration Tests

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  • James G. MacKinnon

Abstract

This paper uses Monte Carlo experiments and regression methods to calculate approximate asymptotic distribution functions for a number of well-known unit root and cointegration test statistics. These allow empirical workers to calculate approximate P values for these tests. The results of the paper are based on a very extensive set of Monte Carlo experiments, which yield finite-sample critical values for a number of sample sizes. Response surface regressions are then used to obtain asymptotic critical values for a large number of different test sizes. Finally, regression methods are used to estimate approximate distribution functions with simple functional forms.

Suggested Citation

  • James G. MacKinnon, 1992. "Approximate Asymptotic Distribution Functions for Unit Roots and Cointegration Tests," Working Paper 861, Economics Department, Queen's University.
  • Handle: RePEc:qed:wpaper:861
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    References listed on IDEAS

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    8. Nabeya, Seiji & Tanaka, Katsuto, 1990. "A General Approach to the Limiting Distribution for Estimators in Time Series Regression with Nonstable Autoregressive Errors," Econometrica, Econometric Society, vol. 58(1), pages 145-163, January.
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