The focus of the present work is to study the impact of the second-hand market the collusivebehavior. I analyze firms' preferences for having an active second-hand market and whetherpolicies (i.e. leasing policy, buy-back policy and warranty policy) that affect the functioningof the second-hand...

A new way of constructing efficient semiparametric instrumental variableestimators is proposed. The method involves the combination of a large number ofpossibly inefficient estimators rather than combining the instruments into anoptimal instrument function. The consistency and asymptotic...

We propose a semiparametric IGARCH model that allows for persistence invariance but also allows for more flexible functional form. We assume that thedifference of the squared process is weakly stationary. We propose an estimationstrategy based on the nonparametric instrumental variable method....

In semiparametric models it is a common approach to under-smooth thenonparametric functions in order that estimators of the finite dimensionalparameters can achieve root-n consistency. The requirement of under-smoothingmay result as we show from inefficient estimation methods or technical...

This paper proposes a class of locally stationary diffusion processes. The modelhas a time varying but locally linear drift and a volatility coefficient that is allowed tovary over time and space. We propose estimators of all the unknown quantitiesbased on long span data. Our estimation method...

Local linear fitting is a popular nonparametric method in nonlinear statistical andeconometric modelling. Lu and Linton (2007) established the point wise asymptoticdistribution (central limit theorem) for the local linear estimator of nonparametricregression function under the condition of near...

We use local polynomial fitting to estimate the nonparametric M-regression function for strongly mixing stationary processes {(Y_i,?X_i ) } . We establish a strong uniform consistency rate for the Bahadur representation of estimators of the regression function and its derivatives. These results...

Many important models, such as index models widely used in limiteddependent variables, partial linear models and nonparametric demand studiesutilize estimation of average derivatives (sometimes weighted) of theconditional mean function. Asymptotic results in the literature focus onsituations...

In this paper we investigate a class of semiparametric models for panel datasetswhere the cross-section and time dimensions are large. Our model contains alatent time series that is to be estimated and perhaps forecasted along with anonparametric covariate effect. Our model is motivated by the...

We introduce a notion of median uncorrelation that is a natural extension of mean(linear) uncorrelation. A scalar random variable Y is median uncorrelated with a kdimensionalrandom vector X if and only if the slope from an LAD regression of Yon X is zero. Using this simple definition, we...