The StoNED Age: The Departure into a New Era of Efficiency Analysis? – A Monte Carlo Comparison of StoNED and the 'Oldies' (SFA and DEA)

Andor, Mark; Hesse, Frederik

doi:10.2139/ssrn.2200837

Cited by 9 publications

(5 citation statements)

References 46 publications

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“…SFA is parametric and DEA is deterministic (no meaningful error term), so a main advantage of SFA's regression based structure over DEA is its ability to consider statistical noise. It also is less sensitive to outliers than DEA (Andor & Hesse, ). A disadvantage relative to DEA is that, because it is regression based, SFA is limited to one output.…”

Section: Methodsmentioning

confidence: 99%

Toward a valid approach to nonprofit efficiency measurement

Coupet

Berrett

2018

Nonprofit Mgmnt & Ldrshp

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Past literature in nonprofit management uses the overhead ratio of nonprofits as a measure of efficiency. Although the overhead ratio might measure top-heaviness, we argue that it does not measure nonprofit efficiency. To investigate this, we use financial and operational data to rank the efficiency of Habitat for Humanity affiliates with the overhead and administrative ratio, as well as data envelopment analysis (DEA) and stochastic frontier analysis (SFA), two of the most popular efficiency measures. While the DEA and SFA rankings are statistically correlated, overhead ratio rankings are negatively correlated with both SFA and DEA rankings. We argue that nonprofit scholars, managers, and donors should move away from concepts and measures of efficiency based on financial ratios, and toward ones that embrace maximizing what nonprofits are able to make and do.

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Section: Methodsmentioning

confidence: 99%

Toward a valid approach to nonprofit efficiency measurement

Coupet

Berrett

2018

Nonprofit Mgmnt & Ldrshp

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“…Their analysis revealed that a substantial number of studies utilised sample sizes smaller than 80. Concurrently, Andor and Hesse (2011) observed that with a minimum sample size of 50, the SFA method demonstrated significantly improved performance.…”

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confidence: 86%

“…The study involved a total of 80 respondents, 3 a sample size deemed sufficient to achieve the objectives, as supported by the arguments in relevant literature (Andor & Hesse, 2011;Coelli, 1993;Thiam et al, 2001).…”

Section: Mohd Khairul Hafifi Maidin Roslina Kamaruddin and Shri Dewi ...mentioning

confidence: 99%

Soil Properties and the Technical Efficiency of Paddy Production in Malaysia: An Application of Stochastic Frontier Analysis

Hafifi Maidin,

Kamaruddin,

Applanaidu

2023

MJES

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This study investigates the impact of soil properties on technical efficiency in paddy production, focusing on Malaysia’s two main paddy granaries: KADA and IADA BLS. These granaries play a significant role in Malaysia’s paddy production. The research employed three different models, with productivity as the dependent variable. In models 1 and 2, standard physical inputs were used as independent variables. Model 3, however, augmented the inputs with the addition of soil property variables. The empirical results revealed significant impacts from fertiliser, pesticide and land inputs, with the exception of land in model 1, where its coefficient was not statistically significant. Additionally, soil pH and the calcium+magnesium/potassium ratio emerged as crucial factors affecting paddy productivity. Importantly, incorporating soil property variables into the analysis resulted in a relatively lower technical inefficiency estimate. These insights are invaluable for policy formulation, highlighting key inputs that can optimise paddy production. The study’s findings regarding soil properties are particularly relevant for refining strategies in national paddy development programs, emphasising the importance of sustainable soil management. Looking ahead, the study advocates for comprehensive technical efficiency estimations that account for all forms of heterogeneity, including weather conditions, to ensure more accurate and insightful assessments.

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“…Our focus in this paper is on the concave least squares (CLS) problem under monotonicity assumption (MCLS). 2 One of the applications of this problem is to estimate a non-parametric production function that is monotonic and concave (Andor & Hesse, 2014;Cheng, Bjørndal, & Bjørndal, 2014;Eskelinen & Kuosmanen, 2013;Keshvari & Kuosmanen, 2013;Kuosmanen, 2011Kuosmanen, , 2012Wang, Wang, Dang, & Ge, 2014).…”

Section: Penalized Monotonic Concave Least Squaresmentioning

confidence: 99%

A penalized method for multivariate concave least squares with application to productivity analysis

Keshvari

2017

European Journal of Operational Research

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We propose a penalized method for the least squares estimator of a multivariate concave regression function. This estimator is formulated as a quadratic programming (QP) problem with ( 2 ) constraints, where is the number of observations. Computing such an estimator is a very timeconsuming task, and the computational burden rises dramatically as the number of observations increases. By introducing a quadratic penalty function, we reformulate the concave least squares estimator as a QP with only non-negativity constraints. This reformulation can be adapted for estimating variants of shape restricted least squares, i.e. the monotonic-concave/convex least squares. The experimental results and an empirical study show that the reformulated problem and its dual are solved significantly faster than the original problem. The Matlab and R codes for implementing the penalized problems are provided in the paper.

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The StoNED Age: The Departure into a New Era of Efficiency Analysis? – A Monte Carlo Comparison of StoNED and the 'Oldies' (SFA and DEA)

Cited by 9 publications

References 46 publications

Toward a valid approach to nonprofit efficiency measurement

Toward a valid approach to nonprofit efficiency measurement

Soil Properties and the Technical Efficiency of Paddy Production in Malaysia: An Application of Stochastic Frontier Analysis

A penalized method for multivariate concave least squares with application to productivity analysis

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