Erschienen in:Syracuse University Center for Policy Research Working Paper ; No. 129
Umfang:
1 Online-Ressource (49 p)
Sprache:
Englisch
DOI:
10.2139/ssrn.1805728
Identifikator:
Entstehung:
Anmerkungen:
Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments February 1, 2011 erstellt
Beschreibung:
In this paper, we develop tests for structural change in cointegrated panel regressions with common and idiosyncratic trends. We consider both the cases of observable and nonobservable common trends, deriving a Functional Central Limit Theorem for the partial sample estimators under the null of no break. We show that tests based on sup-Wald statistics are powerful versus breaks of size , also proving that power is present when the time of change differs across units and when only some units have a break. Our framework is extended to the case of cross correlated regressors and endogeneity. Monte Carlo evidence shows that the tests have the correct size and good power properties