Testing for seasonal unit roots in heterogeneous panels using monthly data in the presence of cross sectional dependence
Otero, Jesus, Smith, Jeremy (Jeremy P.) and Giulietti, Monica (2008) Testing for seasonal unit roots in heterogeneous panels using monthly data in the presence of cross sectional dependence. Working Paper. University of Warwick, Department of Economics, Coventry.
WRAP_Otero_twerp_865.pdf - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
Official URL: http://www2.warwick.ac.uk/fac/soc/economics/resear...
This paper generalises the monthly seasonal unit root tests of Franses (1991) for a heterogeneous panel following the work of Im, Pesaran, and Shin (2003), which we refer to as the F-IPS tests. The paper presents the mean and variance necessary to yield a standard normal distribution for the tests, for different number of time observations, T, and lag lengths. However, these tests are only applicable in the absence of cross-sectional dependence. Two alternative methods for modifying these F-IPS tests in the presence of cross-sectional dependency are presented : the first is the cross-sectionally augmented test,denoted CF-IPS, following Pesaran (2007), the other is a bootstap method, denoted BF-IPS. In general, the BF-IPS tests have greater power than the CF-IPS tests, although for large T and high degree of cross-sectional dependency the CF-IPS test dominates the BF-IPS test.
|Item Type:||Working or Discussion Paper (Working Paper)|
|Subjects:||Q Science > QA Mathematics|
|Divisions:||Faculty of Social Sciences > Economics|
|Library of Congress Subject Headings (LCSH):||Monte Carlo method, Panel analysis, Statistical hypothesis testing, Simulation methods, Time-series analysis|
|Series Name:||Warwick economic research papers|
|Publisher:||University of Warwick, Department of Economics|
|Place of Publication:||Coventry|
|Number of Pages:||30|
|Status:||Not Peer Reviewed|
|Access rights to Published version:||Open Access|
|References:||Beaulieu, J. and J. Miron (1993). Seasonal unit roots in aggregate U.S. data. Journal of Economet- rics 55, 305�328. Chang, Y. (2004). Bootstrap unit root tests in panels with cross-sectional dependency. Journal of Econometrics 120, 263�293. Dickey, D. A. and W. A. Fuller (1979). Distribution of the estimators for autoregressive time series with a unit root. Journal of the American Statistical Association 74, 427�431. Dreger, C. and H.-E. Reimers (2005). Panel seasonal unit root test: Further simulation results and an application to unemployment data. Allgemeines Statistisches Archiv 89, 321�337. Franses, P. H. (1991). Seasonality, nonstationarity and the forecasting of monthly time series. Inter- national Journal of Forecasting 7, 199�208. Franses, P. H. and B. Hobijn (1997). Critical values for unit root tests in seasonal time series. Journal of Applied Statistics 24, 25�47. Ghysels, E. and D. R. Osborn (2001). The Econometrics Analysis of Seasonal Time Series. Cam- bridge: Cambridge University Press. Hylleberg, S., R. F. Engle, C. W. J. Granger, and B. S. Yoo (1990). Seasonal integration and cointegration. Journal of Econometrics 44, 215�238. Im, K., M. H. Pesaran, and Y. Shin (2003). Testing for unit roots in heterogeneous panels. Journal of Econometrics 115, 53�74. Li, H. and G. S. Maddala (1996). Bootstrapping time series models. Econometric Reviews 15, 115� 195. Maddala, G. S. and S. Wu (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics 61, 631�652. O�Connell, P. G. J. (1998). The overvaluation of purchasing power parity. Journal of International Economics 44, 1�19. Otero, J., J. Smith, and M. Giulietti (2005). Testing for seasonal unit roots in heterogeneous panels. Economics Letters 86, 229�235. Otero, J., J. Smith, and M. Giulietti (2007). Testing for seasonal unit roots in heterogeneous panels in the presence of cross section dependence. Economics Letters 97, 179�184. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross section dependence. Journal of Applied Econometrics 22, 265�312.|
Actions (login required)