Abstract
Ng and Perron (2001) designed a unit root test, which incorporates the properties of DF-GLS and Phillips Perron test. Ng and Perron claim that the test performs exceptionally well especially in the presence of a negative moving average. However, the performance of the test depends heavily on the choice of the spectral density estimators used in the construction of the test. Various estimators for spectral density exist in the literature; each have a crucial impact on the output of test, however there is no clarity on which of these estimators gives the optimal size and power properties. This study aims to evaluate the performance of the Ng-Perron for different choices of spectral density estimators in the presence of a negative and positive moving average using Monte Carlo simulations. The results for large samples show that: (a) in the presence of a positive moving average, testing with the kernel based estimator gives good effective power and no size distortion, and (b) in the presence of a negative moving average, the autoregressive estimator gives better effective power, however, huge size distortion is observed in several specifications of the data-generating process.
References
- Andrews, D. W. (1991). Heteroskedasticity and Autocorrelation Consistent Covariance Matrix estimation. Econometrica, 59 (3), 817-858.
- Atiq-ur-Rehman (2011). Impact of Model Specification Decisions on Performance of Unit Root Tests. International Econometric Review, 3 (2), 22-33.
- Dufour, J. M. and M. L. King (1991). Optimal Invariant Tests for the Autocorrelation Coefficient in Linear Regressions with Stationary or Nonstationary Errors. Journal of Econometrics, 47 (1), 115-143.
- Elliott, G., T. J. Rothenberg and J. H. Stock (1996). Efficient Tests for an Autoregressive Unit Root. Econometrica, 64 (4), 813-836.
- Libanio, G. A. (2005). Unit Roots in Macroeconomic Time Series: Theory, Implications, and Evidence. Nova Economia Belo Horizonte, 15 (3), 145-176.
- Ng, S. and P. Perron (2001). Lag length Selection and the Construction of Unit Root Tests with Good Size and Power. Econometrica, 69 (6), 1519-1554.
- Perron, P. and S. Ng (1998). An Autoregressive Spectral Density Estimator at Frequency Zero for Nonstationary Tests. Econometric Theory, 14, 560-603.
- Phillips, P. C. (1987). Time Series Regression with a Unit Root. Econometrica, 55 (2), 277- 301.
- Phillips, P. C. and P. Perron (1988). Testing for a unit root in time series regression. Biometrika, 75 (2), 335-346.
- Stock, J. H. (1990). A Class of Tests for Integration and Cointegration. Manuscript, Harvard University.
- Stock, J. H. (1994). Unit Roots, Structural Breaks and Trends. Handbook of Econometrics, 4, 2739-2841.
Abstract
References
- Andrews, D. W. (1991). Heteroskedasticity and Autocorrelation Consistent Covariance Matrix estimation. Econometrica, 59 (3), 817-858.
- Atiq-ur-Rehman (2011). Impact of Model Specification Decisions on Performance of Unit Root Tests. International Econometric Review, 3 (2), 22-33.
- Dufour, J. M. and M. L. King (1991). Optimal Invariant Tests for the Autocorrelation Coefficient in Linear Regressions with Stationary or Nonstationary Errors. Journal of Econometrics, 47 (1), 115-143.
- Elliott, G., T. J. Rothenberg and J. H. Stock (1996). Efficient Tests for an Autoregressive Unit Root. Econometrica, 64 (4), 813-836.
- Libanio, G. A. (2005). Unit Roots in Macroeconomic Time Series: Theory, Implications, and Evidence. Nova Economia Belo Horizonte, 15 (3), 145-176.
- Ng, S. and P. Perron (2001). Lag length Selection and the Construction of Unit Root Tests with Good Size and Power. Econometrica, 69 (6), 1519-1554.
- Perron, P. and S. Ng (1998). An Autoregressive Spectral Density Estimator at Frequency Zero for Nonstationary Tests. Econometric Theory, 14, 560-603.
- Phillips, P. C. (1987). Time Series Regression with a Unit Root. Econometrica, 55 (2), 277- 301.
- Phillips, P. C. and P. Perron (1988). Testing for a unit root in time series regression. Biometrika, 75 (2), 335-346.
- Stock, J. H. (1990). A Class of Tests for Integration and Cointegration. Manuscript, Harvard University.
- Stock, J. H. (1994). Unit Roots, Structural Breaks and Trends. Handbook of Econometrics, 4, 2739-2841.
Details
| Subjects | Business Administration |
|---|---|
| Other ID | JA49KM98BY |
| Journal Section | Articles |
| Authors | |
| Publication Date | September 1, 2015 |
| Submission Date | September 1, 2015 |
| Published in Issue | Year 2015 Volume: 7 Issue: 2 |