American Journal of Theoretical and Applied Statistics
Volume 2, Issue 6, November 2013, Pages: 293-298
Published: Jan. 30, 2014
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Agunloye, Oluokun Kasali, Department of Statistics, University of Botswana, Gaborone, Botswana
Arnab, Raghunath, Department of Statistics, University of Botswana, Gaborone, Botswana
Shangodoyin, Dahud Kehinde, Department of Statistics, University of Botswana, Gaborone, Botswana
This paper examines lag selection problem in unit root tests which has become a major specification problem in empirical analysis of non-stationary time series data. It is known that the implementation of unit root tests requires the choice of optimal truncation lag for good power proper ties and it is equally unrealistic to assume that the true optimal truncation lag is known a prior to the practitioners and other applied researchers. Consequently, these users rely largely on the use of standard information criteria for selection of truncation lag in unit root tests. A number of previous studies have shown that these criteria have problem of over-specification of truncation lag-length leading to the well-known low power problem that is commonly associated with most unit root tests in the literature. This paper focuses on the problem of over-specification of truncation lag-length within the context of augmented Dickey-Fuller (ADF) and generalized least squares Dickey-Fuller (DF-GLS)unit root tests. In an attempt to address this lag selection problem, we propose a new criterion for the selection of truncation lag in unit root tests based on Koyck distributed lag model and we show that this new criterion avoids the problem of over-specification of truncationlag-length that is commonly associated with standard information criteria.
Agunloye, Oluokun Kasali,
Shangodoyin, Dahud Kehinde,
A New Criterion for Lag-Length Selection in Unit Root Tests, American Journal of Theoretical and Applied Statistics.
Vol. 2, No. 6,
2013, pp. 293-298.
Schwert, G.W. (1989) "Tests for Unit Roots: A Monte Carlo Investigation," Journal of Business and Economic Statistics, 7, 147-160.
Campbell, J. C. and Perron, P. (1991) "Pitfall and Opportunities: What Macroeconomists shouldknow about Unit Roots," NBER Technical Working Paper # 100
Xiao, Z. and Phillips, P. C. B. (1997) "An ADF Coefficient Test for a Unit Root in ARMAModels of Unknown Order with Empirical Applications to the U.S. Economy," CowlesFoundation Discussion Paper # 1161,
Maddala, G. S. and Kim, I. M. (1998) Unit Roots, Cointegration and Time Series, Cambridge University Press
Cavaliere, G. (2012) "Lag-length Selection for a Unit Root test in the presence of non-stationaryVolatility," Cowles Foundation Discussion Paper # 1844.
Dufour, J. M and King, M. L. (1991) "Optimal Invariant Tests for the Autocorrelation Coefficient in Linear Regressions with Stationary or Non-stationary AR(1) errors," Journal of Econometrics,47, 115-143
Said, E. S. and Dickey, D. A. (1984) "Testing for a Unit Root in Autoregressive Moving Average Models of Unknown Order," Biometrika, 71, 3, 599-607.
Elliott, G. Rothenberg, T. J. and Stock, J. H. (1996) "Efficient Tests for an Autoregressive UnitRoot," Econometrica, 64, 4, 813-836
Hall, A. (1994) "Testing for a Unit Root in Time Series with Pretest Data-based ModelSelection," Journal of Business and Economic Statistics, 12, 4, 461-470
Ng, S. and Perron, P. (2001) "Lag Length Selection and the Construction of Unit Root Tests with Good Size and Power," Econometrica, 69, 6, 1519-1554
Shaowen Wu (2010)"Lag Length Selection In DF-GLS Unit Root Tests",Communication in Statistics-Simulation and computation,39:8,1590-1604
Akaike, H., 1969. Fitting Autoregressive Models for Prediction. Annalsof The Institute of Statistical Mathematics, 21(2), 243–247.
Akaike, H., 1973. Information theory and an extension of the maximum likelihood principle. In: Petrov, B.N., Csaki, F., 2ndInternational Symposium on Information Theory. AkademiaiKiado`, Budapest, pp. 267–281.
Schwarz, G. (1978) " Estimating the dimension of a model". Annals of Statistics, 6, 461 –464.
Hannan, E. J. and Quinn, B. G. (1978). "The determination of the order of an autoregression". Journal of Royal Statistical Society, 41, 190 – 195.
Koyck, L.M. (1954), Distributed Lags and Investment Analysis, Amsterdam: North-Holland.
Gujarati, D.(2005),Essentials of Econometrics, McGraw-Hill School Education Group.