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.
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Paper provided by Queen's University, Department of Economics in its series Working Papers with number
861.
Length: 22 pages Date of creation: 1992 Date of revision: Publication status: Published in Journal of Business and Economic Statistics, 12, 1994 Handle: RePEc:qed:wpaper:861
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