Approximate Asymptotic Distribution Functions for Unit-Root and Cointegration Tests
Monte Carlo experiments and response surface regressions are used 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 an extensive set of Monte Carlo experiments, which yield finite-sample quantiles for several sample sizes. Response surface regressions are then used to obtain asymptotic quantiles for a large number of different test sizes. Finally, approximate distribution functions with simple functional forms are estimated from these asymptotic quantiles.
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Volume (Year): 12 (1994)
Issue (Month): 2 (April)
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References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Gregory, Allan W, 1994.
"Testing for Cointegration in Linear Quadratic Models,"
Journal of Business & Economic Statistics,
American Statistical Association, vol. 12(3), pages 347-60, July.
- Allan W. Gregory, 1991. "Testing for Cointegration in Linear Quadratic Models," Working Papers 811, Queen's University, Department of Economics.
- Engle, R. F. & Granger, C. W. J. (ed.), 1991. "Long-Run Economic Relationships: Readings in Cointegration," OUP Catalogue, Oxford University Press, number 9780198283393, December.
- Peter C.B. Phillips & Sam Ouliaris, 1987.
"Asymptotic Properties of Residual Based Tests for Cointegration,"
Cowles Foundation Discussion Papers
847R, Cowles Foundation for Research in Economics, Yale University, revised Jul 1988.
- Phillips, Peter C B & Ouliaris, S, 1990. "Asymptotic Properties of Residual Based Tests for Cointegration," Econometrica, Econometric Society, vol. 58(1), pages 165-93, January.
- Engle, Robert F. & Yoo, Byung Sam, 1987. "Forecasting and testing in co-integrated systems," Journal of Econometrics, Elsevier, vol. 35(1), pages 143-159, May.
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