Panel Smooth Transition Regression Models
Andres Gonzalez (),
Timo Teräsvirta (),
Dick van Dijk () and
Yukai Yang ()
CREATES Research Papers from Department of Economics and Business Economics, Aarhus University
We introduce the panel smooth transition regression model. This new model is intended for characterizing heterogeneous panels, allowing the regression coefficients to vary both across individuals and over time. Specifically, heterogeneity is allowed for by assuming that these coefficients are bounded continuous functions of an observable variable and fluctuate between a limited number of "extreme regimes". The model can be viewed as a generalization of the threshold panel model of Hansen (1999). We extend the modelling strategy originally designed for univariate smooth transition regression models to the panel context. The strategy consists of model specification based on homogeneity tests, parameter estimation, and model evaluation, including tests of parameter constancy and no remaining heterogeneity. The model is applied to describing firms' investment decisions in the presence of capital market imperfections.
Keywords: financial constraints; heterogeneous panel; investment; misspecification test; nonlinear modelling of panel data; smooth transition model (search for similar items in EconPapers)
JEL-codes: C12 C23 C52 G31 G32 (search for similar items in EconPapers)
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (6) Track citations by RSS feed
Downloads: (external link)
Working Paper: Panel Smooth Transition Regression Models (2017)
Working Paper: Panel Smooth Transition Regression Models (2005)
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
Persistent link: https://EconPapers.repec.org/RePEc:aah:create:2017-36
Access Statistics for this paper
More papers in CREATES Research Papers from Department of Economics and Business Economics, Aarhus University
Bibliographic data for series maintained by ().