Stochastic Frontier Analysis: Foundations and Advances I

Kumbhakar, Subal C.; Parmeter, Christopher F.; Zelenyuk, Valentin

doi:10.1007/978-981-10-3450-3_9-1

Cited by 35 publications

(37 citation statements)

References 103 publications

(227 reference statements)

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“…This approach allows the measurement of errors, random shocks and requires a functional form [8]. It was also suggested to combine both techniques, which are mentioned as the semi-parametric or non-parametric Stochastic Frontier Analysis [30][31][32][33][34][35][36]. Pioneering studies for these methodologies were published by Fan and Weersink [31] and Kneip and Simar [32] that were applied by Kumbhakar, Parmeter and Zelenyuk [33], while the two-tiered stochastic frontier model was used in the work of Parmeter [37].…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Meta-regression Analysis of Technical (In)Efficiency in Agriculture: a Regional Approach

Santos¹,

Marta-Costa²,

Rodríguez

2021

EoR

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While scientific studies have not reached a consensus on the methodology for examining Technical Efficiency (or Inefficiency), the influence of regions appears to be important for efficiency scores. Therefore, this research aims to investigate the empirical procedures for the achievement of more robust results in the analysis of productive efficiency, as well as to evaluate the effect of the location of farms on such efficiency. The goal was to check whether the most developed regions are the most efficient. Meta-regression analysis provides an adequate method for an accurate assessment of both situations. This technique was applied based on a database of 166 observations on the agricultural sector from countries around the world, published in the period 2010–2017. The criteria used for the database collection and for the conceived model were not previously used and, thereby, enrich the discussion on the topic. The procedure aims to check the variation in the Mean of Technical Inefficiency and conduct an analysis using Quasi-Maximum Likelihood Estimation. The regressions showed that the Mean of Technical Inefficiency could be mainly explained by data, variables, employed empirical models and the region of study. The studies that focus on farms of developed countries present the lowest Mean of Technical Inefficiency, while studies for developing or low-income countries exhibit the opposite. Therefore, for future research on productive analysis, we suggest empirical procedures aimed at achieving robust results that take into account specific regional characteristics of farms.

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Section: Theoretical Backgroundmentioning

confidence: 99%

Meta-regression Analysis of Technical (In)Efficiency in Agriculture: a Regional Approach

Santos¹,

Marta-Costa²,

Rodríguez

2021

EoR

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“…To separate them, the empirical studies have been assuming asymmetric distribution to the efficiencies (usually a half-normal), while they used to assume that random errors follow a symmetric distribution (usually the standard normal) (Aigner et al , 1977). Even though the SFA is traditionally parametric, the latter improvements have given it some degrees of convergence with non-parametric models, which are referred as the non-parametric or semiparametric SFA (Banker and Maindiratta, 1992; Fan et al , 1996; Kneip and Simar, 1996; Kumbhakar et al , 2017; Kuosmanen and Kortelainen, 2012; Noh, 2014; Parmeter and Racine, 2013). Essentially, Fan et al (1996) and Kneip and Simar (1996) provided the baseline studies for these methodologies.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Essentially, Fan et al (1996) and Kneip and Simar (1996) provided the baseline studies for these methodologies. More recently, the advances in the stochastic frontier models were employed in Kumbhakar et al (2017).…”

Section: Literature Reviewmentioning

confidence: 99%

Efficiency analysis of viticulture systems in the Portuguese Douro region

Santos

Rodríguez

Marta-Costa

2020

IJWBR

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Purpose The purpose of this paper is to estimate and analyse the technical efficiency (TE) component of productivity for a sample of winegrowers from the Douro Demarcated Region in Portugal. Design/methodology/approach The data were collected through face-to-face surveys and includes a sample of 110 farmers’ vineyards with specific input-output information and other data about production systems during the year of 2017. The authors use a two-stage data envelopment analysis using bootstrap techniques to obtain TE scores in the farmers’ vineyards and to examine the determinants of its efficiency. Findings The results show that some farmers’ vineyards have a low efficiency level and that there are essential determinants of the production system, which can influence its efficiency. This suggests considerable opportunities for improvement of wine grape productivity through better use of available resources considering the state of technology. Originality/value This work has overcome the lack of data in the farmers’ vineyards, the lack of efficiency studies in the region and also allowed to evaluate the production systems and to assess their impact on efficiency.

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“…Over the past few decades, the original production specification has been widely applied and extended, many models have been developed to estimate the production and cost-efficient functions. Kumbhakar, Parmeter, and Zelenyuk (2017) provide an excellent review on the latest developments in the econometric estimation of productivity and efficiency using the stochastic frontier models.…”

Section: B Measurement Of Bank Efficiencymentioning

confidence: 99%

Bank Efficiency and the Bond Markets: Evidence from the Asia and Pacific Region

Park¹,

Tian²,

Wu³

2020

SSRN Journal

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The views expressed in this publication are those of the authors and do not necessarily reflect the views and policies of the Asian Development Bank (ADB) or its Board of Governors or the governments they represent.ADB does not guarantee the accuracy of the data included in this publication and accepts no responsibility for any consequence of their use. The mention of specific companies or products of manufacturers does not imply that they are endorsed or recommended by ADB in preference to others of a similar nature that are not mentioned.By making any designation of or reference to a particular territory or geographic area, or by using the term "country" in this document, ADB does not intend to make any judgments as to the legal or other status of any territory or area.

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Stochastic Frontier Analysis: Foundations and Advances I

Abstract: This chapter (as well as Chap. 11) reviews some of the most important developments in the econometric estimation of productivity and efficiency surrounding the stochastic frontier model.

Cited by 35 publications

References 103 publications

Meta-regression Analysis of Technical (In)Efficiency in Agriculture: a Regional Approach

Meta-regression Analysis of Technical (In)Efficiency in Agriculture: a Regional Approach

Efficiency analysis of viticulture systems in the Portuguese Douro region

Bank Efficiency and the Bond Markets: Evidence from the Asia and Pacific Region

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