In this paper we examine the finite sample performance of two estimators one developed by Blundell, Chen, and Kristensen (2007) (BCK) and the other by Gagliardini and Scaillet (2007) (TIR). This paper focuses on the generalization and expansion of these estimators to a full nonparametric...

Parametric Stochastic Frontier Models are widely used in productivity analysis and are commonly estimated using FRONTIER, STATA or LIMDEP packages, which only provide point estimates for firm-specific technical efficiency. Confidence intervals for technical efficiencies with superior coverage...

Heterogeneity in choice models is typically assumed to have a normal distribution in both Bayesian and classical setups. In this paper, we propose a semiparametric Bayesian framework for the analysis of random coefficients discrete choice models that can be applied to both individual as well as...

This paper introduces a heterogeneous agent discrete choice probit demand model with a structural interpretation of product choice covariance designed to overcome two hurdles in discrete choice demand modeling. One hurdle is the curse of dimensionality implicit in covariance probit demand models...

This is an updated version posted 12/12/12. In the previous version attribute labels in Table 5 were incorrect for tribs and jobs.

The intensity of agricultural production affects both nutrient and greenhouse gas emissions. Environmental policy designed to reduce one type of pollution may have complementary effects on the other type. This paper explores this issue in the Lake Rotorua catchment in New Zealand using an...

Selection logging in the tropics is increasingly moving to systems that reduce the impact of harvesting operations on forests and soils. While much of the focus has been on modifying the tractor logging system using RIL principles, alternative harvesting systems have also been introduced. One of...