We consider an extension of conventional univariate Kaplan-Meier type estimators for the hazard rate and the survivor function to multivariate censored data with a censored random regressor. It is an Akritas (1994) type estimator which adapts the nonparametric conditional hazard rate estimator...

The explanation of productivity differentials is very important to identify the economic conditions that create inefficiency and to improve managerial performance. In literature two main approaches have been developed: one-stage approaches and two-stage approaches. Daraio and Simar (2003)...

This paper studies the nonparametric identification and estimation of voters' preferences when voters are ideological. We establish that voter preference distributions and other parameters of interest can be identified from aggregate electoral data. We also show that these objects can be...

This paper studies the nonparametric identification and estimation of voters' preferences when voters are ideological. We establish that voter preference distributions and other parameters of interest can be identified from aggregate electoral data. We also show that these objects can be...

In a recent paper Johnson and Kuosmanen (2011) propose a new, semi-parametric, general cost-frontier model, the stochastic nonparametric envelopment of data (StoNED). The model is semi-parametric in the sense that the cost function is estimated nonparametrically, while the functional form of the...

This paper studies the nonparametric identification and estimation of voters' preferences when voters are ideological. We establish that voter preference distributions and other parameters of interest can be identified from aggregate electoral data. We also show that these objects can be...

In this paper we introduce a non-parametric estimation method for a large Vector Autoregression (VAR) with time-varying parameters. The estimators and their asymptotic distributions are available in closed form. This makes the method computationally efficient and capable of handling information...

This paper studies the nonparametric identification and estimation of voters' preferences when voters are ideological. We build on the methods introduced by Degan and Merlo (2009) representing elections as Voronoi tessellations of the ideological space. We exploit the properties of this...

We extend the semi-parametric estimation method for dynamic discrete choice models using Hotz and Miller’s (1993) conditional choice probability (CCP) approach to the setting where individuals may have hyperbolic discounting time preferences and may be naive about their time inconsistency. We...

In many applications, covariates are not observed but have to be estimated from data. We outline some regression-type models where such a situation occurs and discuss estimation of the regression function in this context.We review theoretical results on how asymptotic properties of nonparametric...