A hypothetical market for renting and converting forested land into row cropping for biofuel production revealed that nearly half of the 1060 non-industrial landowners sampled in Florida are willing to accept payments for land type conversion and the resulting supply function is inelastic and...

A stochastic production frontier was used to measure the initial (i.e., bi-weekly) economic effects of hurricanes on commercial grouper (Serranidae) production in the Exclusive Economic Zone of the United States Gulf of Mexico from 2005 to 2009. We estimated the economic effects of productivity...

How do decision makers weight private and official information sources which are correlated and differ in accuracy and bias? This paper studies how traders update subjective risk perceptions after receiving expert opinions, using a unique data set from a prediction market, the Hurricane Futures...

This study examines the impact of individual fishing quotas (IFQs) on the technical efficiency (TE) and composition of the Gulf of Mexico red snapper commercial fishing fleet. Employing a parametric stochastic distance frontier framework we find that IFQs improved the TE of the vertical line and...

This paper uses data from small-scale potato farmers in Ecuador to examine the impact of the program Plataformas de Concertación on productivity growth. Using propensity score matching combined with a Stochastic Production Frontier model that corrects for sample selection bias, we disaggregate...

The main objective of this paper is to evaluate and analyse technical efficiency (TE) levels for hillside farmers under different levels of adoption of soil conservation in El Salvador and Honduras. A switching regression model is implemented to examine potential selectivity bias for high and...

A meta-regression analysis including 167 farm level technical efficiency (TE) studies of developing and developed countries was undertaken. The econometric results suggest that stochastic frontier models generate lower mean TE (MTE) estimates than non-parametric deterministic models, while...