6533b855fe1ef96bd12afcf1

RESEARCH PRODUCT

Stochastic frontier models using R

Giancarlo Ferrara

subject

Set (abstract data type)FrontierMathematical optimizationStochastic frontier analysisComputer scienceBoundary (topology)Production (economics)Production functionProduction–possibility frontierMeasure (mathematics)

description

Abstract The production function is usually assumed to specify the maximum output obtainable, from a given set of inputs, describing the boundary or frontier of the obtainable output from each feasible combination of input; it relates the production process of individual units to the efficient border of the production possibilities. The measure of the distance of each unit from the border is the most immediate way to assess its (in)efficiency. However, the production function is not generally known, but it has only a set of information on each production unit and it is therefore essential to develop techniques to estimate the production frontier. Starting from the packages already developed in the R environment, this work introduces the methodological aspects of the stochastic frontier models, including a brief introduction to the relative extensions in presence of contextual variables and spatial external factors, comparing the standard stochastic frontier analysis and the semiparametric one. Some simulation studies and an empirical application to agricultural data illustrate the different techniques.

yearjournalcountryeditionlanguage
2020-01-01
https://doi.org/10.1016/bs.host.2018.11.004