The training (in English) is delivered over two consecutive days.
The aim of this course is to introduce the panel threshold regression models. In econometrics, the threshold regression models specify that individual observations can be divided into classes based on the value of an observed variable. The slope parameters of the regression model are then supposed to be specific to each of these classes. In the panel data context, these models have particular appealing features. They allow to take into account the slope parameters heterogeneity, while explaining these heterogeneity by an economic threshold variable. Hence, they can be viewed as a parametric alternative to the random coefficient models. Notice that all the models presented in the course are developed for non-dynamic panels with individual specific "fixed” effects. The training will also propose an application of these models based on Matlab codes.
Christophe Hurlin, University of Orleans (personal website)
Christophe Hurlin is a specialist of financial econometrics and panel data econometrics. He is professor at the University of Orleans and vice-director of the research laboratory of economics (LEO, UMR CNRS 7322). He was previously associate professor at the University Paris Dauphine and he taught at HEC Geneva and HEC Lausanne. His research has been published in academic journals like the Journal of Financial Econometrics, the Review of Finance, the European Journal of Operational Research, the Journal of Banking and Finance or the Journal of Empirical Finance.
We will implement most of the methods discussed in lecture, using data sets covering a variety of areas in economics and finance. We will use Matlab as the main statistical software. The participants are invited to bring their personal laptop.
González, A., Teräsvirta, T., and van Dijk, D. (2005), Panel smooth transition regression model, Working Paper Series in Economics and Finance, No. 604.
Hansen, B.E. (1999), Threshold effects in non-dynamic panels: estimation, testing, and inference, Journal of Econometrics, 93, pp 334–368.
Hsiao, C. (2003), Analysis of Panel Data, Cambridge University Press.
van Dijk, D., Teräsvirta, T., and Franses, P. H. (2002), Smooth Transition Autoregressive Models - a Survey of Recent Developments, Econometric Reviews, 21(1), pp 1-47.
Candelon B., Colletaz G., and Hurlin C. (2013), "Network Effects and Infrastructure Productivity in Developing Countries", Oxford Bulletin of Economics and Statistics, 75(6), pp 887-913.
Franses, P. H. and D. van Dijk, (2000), Nonlinear Time Series Models in Empirical Finance. Cambridge University Press.
Fouquau, J., Hurlin, C. and Rabaud, I. (2008), ''The Feldstein-Horioka Puzzle: a Panel Smooth Transition Regression Approach'', Economic Modelling, 25(2), pp. 284-299.