This paper (i) derives a number of properties of a newly specified multi-input-single-output (MISO) production function with a derived error term, and (ii) using iteratively rescaled generalized least squares, presents estimates of the cross-sectionally varying coefficients of a...

Output and input market distortions manifest as wedges in the firm's first order conditions. The production approach to markup estimation recovers the markup wedge using the output elasticity for a variable and undistorted input. We show that using the revenue elasticity for any variable input,...

This paper employs recently developed non stationary panel methodologies that assume some cross-section dependence to estimate the production function for Italian regions in the industrial sector over the period 1970-1998. The analysis consists in three steps. First, unit root tests for...

Estimation of the one sided error component in stochastic frontier models may erroneously attribute firm characteristics to inefficiency if heterogeneity is unaccounted for. However, it is not clear in general in which component of the error distribution the covariates should be included. In the...

We consider fixed-effect estimation of a production function where inputs and outputs vary over time, space, and cross-sectional unit. Variability in the spatial dimension allows for time-varying individual effects, without parametric assumptions on the effects. Asymptotics along the spatial...

Simar and Wilson (J. Econometrics, 2007) provided a statistical model that can rationalize two-stage estimation of technical efficiency in nonparametric settings. Two-stage estimation has been widely used, but requires a strong assumption: the second-stage environmental variables cannot affect...

Heckman's (1979) sample selection model has been employed in three decades of applications of linear regression studies. The formal extension of the method to nonlinear models, however, is of more recent vintage. A generic solution for nonlinear models is proposed in Terza (1998). We have...

Nonparametric methods have been widely used for assessing the performance of organizations in the private and public sector. The most popular ones are based on envelopment estimators, like the FDH or DEA estimators, that estimate the attainable sets and its efficient boundary by enveloping the...

There have been numerous studies concerning productivity, representing two general approaches toward measuring the concept. Parametric approaches specify the actual form of the production function based on theoretical assumptions, while non-parametric approaches use empirical best-practice cases...

We discuss nonparametric regression models for panel data. A fully nonparametric panel data specification that uses the time variable and the individual identifier as additional (categorical) explanatory variables is considered to be the most suitable. We use this estimator and conventional...