-based inference for plug-in PSE estimation of smooth or non-smooth functionals; and (4) root-n asymptotic normality of semiparametric …, semiparametric GARCH, and copula-based multivariate financial models are used to illustrate the general results. …

This paper develops a framework for the analysis of semiparametric conditional moment models with endogenous and … endogeneity and measurement errors of the causes of interest, which has been observed in linear parametric models. Two … method. It supports that correcting for both endogeneity and measurement errors on total expenditure is substantial in …

all of the regressors are arbitrarily correlated with the random coefficients, thus permitting endogeneity. We assume the … endogeneity via a collection of conditional moment inequalities, and we investigate the structure of these sets by way of …

Semiparametric models are characterized by a finite- and infinite-dimensional (functional) component. As such they … developed that exhibit standard parametric convergence rates. These two features have made semiparametric models and estimators … increasingly popular in applied economics. We give a partial overview over the literature on semiparametric modelling and …

as nonparametric and semiparametric models in forecasting the nominal interest rate setting that describes the South … results indicate that the semiparametric models perform particularly well relative to the Taylor rule models currently …

rule specifications as well as nonparametric and semiparametric models in forecasting the nominal interest rate setting … semiparametric models in forecasting the interest rates as the forecasting horizon lengthens. …

selected tools from the theory of copulas. We examine both the static and dynamic dependence via unconditional and conditional … copulas. We find significant asymmetric tail dependence in equity markets, with the overall larger lower tail dependence than …