A Principal Components Analysis of Common Stochastic Trends in Heterogeneous Panel Data: Some Monte Carlo Evidence
In this paper we propose a new approach based on principal components analysis to test for the number of common stochastic trends driving the non-stationary series in a panel data set. This test has the advantage that it is also consistent when there is a mixture of I(0) and I(1) series, making it unnecessary to pre-test the panel for unit root. Furthermore, the test solves the problem of dimensionality encountered in large panel data sets. Copyright 1999 by Blackwell Publishing Ltd
Volume (Year): 61 (1999)
Issue (Month): 0 (Special Issue Nov.)
|Contact details of provider:|| Postal: |
Web page: http://www.blackwellpublishing.com/journal.asp?ref=0305-9049
More information through EDIRC
|Order Information:||Web: http://www.blackwellpublishing.com/subs.asp?ref=0305-9049|
When requesting a correction, please mention this item's handle: RePEc:bla:obuest:v:61:y:1999:i:0:p:749-67. See general information about how to correct material in RePEc.
If references are entirely missing, you can add them using this form.