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Generating Critical Values of Unit Root Tests

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Author Affiliations

  • 1Department of Natural Science, Daffodil International University, Dhaka, BANGLADESH
  • 2Department of Statistics, Jahangirnagar University, Dhaka, BANGLADESH

Res. J. Mathematical & Statistical Sci., Volume 1, Issue (6), Pages 7-13, July,12 (2013)

Abstract

In modeling time series econometrics nonstationarity test is very essential part to make some early decision. In order to test whether the time series is stationary or nonstationary, it is necessary to know the critical values for different sample sizes. Initially we required different critical values for testing unit root. But these critical values are not available in a wide range to us. So we need to generate extent tables of critical values. In this paper, we generated critical values for different sample size using Monte Carlo Simulation for testing unit root.

References

  1. Dickey D.A. and Fuller W.A., Distribution of the Estimators for Autoregressive Time Series with a Unit Root, Journal of theAmerican Statistical Association, 74, 427-431 (1976)
  2. Dickey D.A. and Fuller W.A., Likelihood Ratio Statistics for Autoregressive Time Series with a Unit Root, Econometrica,49, 1057-1072 (1981)
  3. Dickey D.A., Estimation and Hypothesis Testing for Nonstationary Time Series, Ph.D. Thesis, lowa Stat University, Ames,lowa (1976)
  4. Dickey D.A., Bell W.R. and Miller R.B., Unit roots series models: Tests and implications, Am, Statistical 40, 12-26 (1986)
  5. Gujarati D.N., Basic Econometrics, 4th ed., McGraw Hill, New York (2003)
  6. Hamilton J.D., Time Series Analysis, Princeton, N. J,: Princeton University Press (1994)
  7. Maddala G.S., Introduction to Econometrics, 2nd ed., Maxwell Macmillan, New York (1997)
  8. Dickey D.A. and Gonzalez-Farias G., A New Maximum Likelihood Approach to Testing for Unit Roots, unpublished paperpresented at the 1992 Joint Statistical meetings, August 9-13, Boston (1992)
  9. Dickey D.A., Hasza D.P. and Fuller, W.A., Testing for Unit Roots in Seasonal Time Series, Journal of the AmericanStatistical Association, 79, 355-367 (1984)
  10. Enders W., Applied econometric time series, John Wiley and Sons, New York (1995)
  11. Fuller, W. A., Introduction to Statistical Time Series, New York John Wiley (1976)
  12. Evans G. and Savin N.E., Testing for Unit Roots: I, Econometrica, 49, 753-779 (1981)
  13. Evans G. and Savin N.E., Testing for Unit Roots: II, Econometrica, 52, 1241-1269 (1984)
  14. Schwert G.W., Tests for Unit Roots: A Monte Carlo Investigation, Journal of Business and Economic Statistics, 7, 147-159,(1989)
  15. Greene W.H., Econometric Analysis, 3rd ed., Prentice Hall, Upper Saddle River, New Jersey (1997)
  16. DeJong D.N., Nankervis J.C., Savin N.E. and Whiteman C.H., The Power Problems of Unit Root Tests in Time Series withAutoregressive Errors, Journal of Econometrics, 53, 323-343 (1992)
  17. DeJong D.N. and Whiteman C.H., Reconsidering Trends and Random Walks in Macroeconomic Time Series, Journal ofMonetary Economics, 28, (1991)
  18. Judge G.G., Griffiths W.E., Hill R.C., Lutkephol H. and Lee T.C., The Theory and Practice of Econometrics, 2nd ed., JohnWilley and Sons, New York (1985)
  19. Majumder A.K., one-Sided and Partially One-Sided Hypothesis Testing in Economics, unpublished PhD Thesis, MonashUniversity, Australia (1999)
  20. Kwiatkowski D., Phillips P.C.B., Schmidt P. and Shin Y., Testing the Null Hypothesis of Stationary Against the Alternativeof a Unit Root, Journal of Econometrics, 54, 159-178 (1992)