We study the problem of selecting the optimal functional form among a set of non-nested nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL...

We study the problem of selecting the optimal functional form among a set of non-nested nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL...

We study the problem of selecting the optimal functional form among a set of non-nested nonlinear mean functions for a semiparametric kernel based regression model. To this end we consider Rissanen's minimum description length (MDL) principle. We prove the consistency of the proposed MDL...

This paper considers transformations of nonlinear semiparametric mean functions that yield moment conditions for estimation. Such transformations are said to be information equivalent if they yield the same asymptotic efficiency bound. I derive a unified theory of algebraic equivalence for...

This study presents the results of an extensive Monte Carlo experiment to compare different methods of efficiency analysis. In addition to traditional parametric-stochastic and nonparametric-deterministic methods recently developed robust nonparametric-stochastic methods are considered. The...

Observing prices of European put and call options, we calibrate exponential Lévy models nonparametrically. We discuss the implementation of the spectral estimation procedures for Lévy models of finite jump activity as well as for self-decomposable Lévy models and improve these methods....

There is an increasing awareness of the potential of nonlinear modeling in regional science, which can partly be explained by the recognition of the limitations of conventional equilibrium models in complex situationsand partly by the easy availability and accessibility of sophisticated...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...

This paper considers the dynamics of spot and futures prices in the presence of arbitrage. A partially linear error correction model is proposed where the adjustment coefficient is allowed to depend non-linearly on the lagged price difference. The model is estimated using data on the DAX index...