Some Further Developments in Cointe grating Regression Analysis: Theory for Applications
Abstrac:
The analy sis of linear cointegrating relationships in a regression framework is typi cally carried out using modified least squares estimators that involve corr ections for endogeneity and error serial correlation in order to obtain lim iting distributions that allow for asymptotic standard inference. Several s uch estimation procedures are available in the literature. In this talk we survey extensions of two of these estimators – Fully Modified OLS and Integ rated Modified OLS - along four dimensions: First, the considered functiona l forms are more general, with a focus on polynomial-type functions that oc cur in many applications (environmental Kuznets curves, Translog cost and p roduction functions, etc.). With respect to functional form choice, some ef fort is placed on specification analysis and testing. Second, we add the cr oss-sectional dimension to the analysis and discuss appropriate modelling a nd estimation strategies for situation with small cross-sectional dimension and cross-sectional dependences, a typical situation in applied macro-econ ometric analysis. Third, we relax the assumption of stationarity of the und erlying processes, thereby extending the cointegration concept to the integ rated locally stationary framework. The talk throughout illustrates the dif ferent aspects of the research agenda with applications and concludes with a brief outline of the steps ahead. The talk gives a bird’s eyes view of re search undertaken in Dortmund as well as in cooperation with Robert M. de J ong, Mathias Vetter and Timothy J. Vogelsang.
DTSTAMP:20260404T145545Z DTSTART:20180323T130000Z DTEND:20180323T140000Z SEQUENCE:0 TRANSP:OPAQUE END:VEVENT END:VCALENDAR