The study aimed to measure the technical efficiency in production of crops (wheat and barley) Erbil Governorate. Using stochastic frontier analysis method Maximum-Likelihood (ML) Model, which combines both effects inefficiency models. based on preliminary data collected randomly for a sample 58 farms used Cobb-Douglas function using four traditional factors, are (land, labor, machinery, fertili...

This paper aims to estimate a translog stochastic frontier production function in the analysis of a panel of 150 mixed Catalan farms in the period 1989-1993, in order to attempt to measure and explain variation in technical inefficiency scores with a one-stage approach. The model uses gross value added as the output aggregate measure. Total employment, fixed capital, current assets, specific co...

In the standard stochastic frontier model with sample selection, the two components of the error term are assumed to be independent, and the joint distribution of the unobservable in the selection equation and the symmetric error term in the stochastic frontier equation is assumed to be bivariate normal. In this paper, we relax these assumptions by using two copula functions to model the depend...

The paper proposes to combine stochastic frontier models and linear programming methods by using DEA measures as priors of efficiency in the stochastic frontier model. These prior measures are revised to obtain posterior measures using Bayes theorem. Monte Carlo methods are developed to perform empirical Bayes inference in the new model. The methods are organized around Gibbs sampling with data...

Received analyses based on stochastic frontier modeling with panel data have relied primarily on results from traditional linear fixed and random effects models. This paper examines extensions of these models that circumvent two important shortcomings of the existing fixed and random effects approaches. The conventional panel data stochastic frontier estimators both assume that technical or cos...

In this paper we develop an approach that synthesizes the best features of the two main methods in the estimation of production efficiency. Specically, our approach first allows for statistical noise, similar to Stochastic frontier analysis, and second, it allows modeling multiple-inputs-multiple-outputs technologies without imposing parametric assumptions on production relationship, similar to...

this paper uses the concept of meta-frontier to investigate the relationship between meta technology ratios (mtr) and different varieties in datepalms including; mazafati, rabi and zardan that are produced widely in sistan and baluchestan province of iran. we used a stratified sampling of 300 date farmers of this province in 2010, 2011 and 2012 and estimated a stochastic production frontier usi...

This paper presents a performance evaluation of European airports, based on the application both parametric and non-parametric approaches. We have evaluated 115 busiest airports in Europe according to number passengers checked-in 2018. The four inputs we used were Terminals, Runways, Boarding gates, Aircraft stands. Three variables describe outputs, namely, Passengers, Movements, Cargo. method ...

Parametric stochastic frontier models have a long history in applied production economics, but the class of tractible parametric models is relatively small. Consequently, researchers have recently considered non–parametric alternatives such as kernel density estimators, functional approximations, and data envelopment analysis (DEA). The purpose of this paper is to present an information theoret...

This study aims to estimate the production function of black grape farming. The research was conducted in Buleleng Regency. area taken purposively. sample village is Kalianget Village. size 33 farmers. Sampling done by Simple Random method. data used were primary and secondary data. Data analysis method Cobb-Douglas Stochastic Frontier model. results showed that cultivation technology relativel...