We suggest using a class of semiparametric dynamic panel data models to capture individual variations in panel data. The model assumes linearity in some continu ous/discrete variables which can be exogenous/endogenous, and allows for nonlinearity in other weakly exogenous variables. We propose a...

We study a new class of semiparametric instrumental variables models with the structural function represented by a partially varying coefficient functional form. Under this representation, the models are linear in the endogenous/exogenous components with unknown constant or functional...

This paper gives a selective overview on the functional coefficient models with their particular applications in economics and finance. Functional coefficient models are very useful analytic tools to explore complex dynamic structures and evolutions for functional data in various areas,...

This study investigates the number of state variables needed for CDS pricing by conducting a principal component analysis using CDS data for the 2006-2009 period. Two state variables, approximated by the first two components, are found sufficient for pricing CDS spreads. The first component...

Recently Martins-Filho and Yao (J Multivar Anal 100:309–333, <CitationRef CitationID="CR7">2009</CitationRef>) have proposed a two-step estimator of nonparametric regression function with parametric error covariance and demonstrate that it is more efficient than the usual LLE. In the present paper we demonstrate that MY’s estimator...</citationref>