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A comparison of parametric and nonparametric estimation methods for cost frontiers and economic measures

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  • Bryon J. Parman
  • Allen M. Featherstone
Abstract
This article examines the empirical performance of alternative frontier estimators’ ability to replicate a known underlying technology and economic measures such as multi-product and product-specific economies of scale, and economies of scope. A cross sectional Monte Carlo procedure to simulate data is used to evaluate a two-sided error system, an OLS system restricting errors to be above the cost frontier, the stochastic frontier method, and data envelopment analysis (DEA). The data are generated assuming a half-normal distribution, and a uniform distribution. Data were also simulated with single and two output firms. The DEA estimator was most robust in estimating the “true” cost frontier and associated economic measures including data sets without single output firms and less effected by distributional assumptions.

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  • Bryon J. Parman & Allen M. Featherstone, 2019. "A comparison of parametric and nonparametric estimation methods for cost frontiers and economic measures," Journal of Applied Economics, Taylor & Francis Journals, vol. 22(1), pages 60-85, January.
    • Handle: RePEc:taf:recsxx:v:22:y:2019:i:1:p:60-85
    DOI: 10.1080/15140326.2018.1526868
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    1. Noah J Miller & Jason S Bergtold & Allen M Featherstone, 2019. "Economic elasticities of input substitution using data envelopment analysis," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-15, August.
    2. Chia-Nan Wang & Minh Nhat Nguyen & Anh Luyen Le & Hector Tibo, 2020. "A DEA Resampling Past-Present-Future Comparative Analysis of the Food and Beverage Industry: The Case Study on Thailand vs. Vietnam," Mathematics, MDPI, vol. 8(7), pages 1-24, July.
    3. Ahn, Heinz & Clermont, Marcel & Langner, Julia, 2023. "Comparative performance analysis of frontier-based efficiency measurement methods – A Monte Carlo simulation," European Journal of Operational Research, Elsevier, vol. 307(1), pages 294-312.
    4. Russell, Levi A. & Briggeman, Brian C. & Featherstone, Allen M., 2013. "Debt and Input Misallocation in Farm Supply and Marketing Cooperatives: A DEA Approach," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 150445, Agricultural and Applied Economics Association.
    5. Matheus Koengkan & José Alberto Fuinhas & Emad Kazemzadeh & Fariba Osmani & Nooshin Karimi Alavijeh, 2022. "Measuring the economic efficiency performance in Latin American and Caribbean countries: An empirical evidence from stochastic production frontier and data envelopment analysis," International Economics, CEPII research center, issue 169, pages 43-54.
    6. Rita, Rui & Marques, Vitor & Bárbara, Diogo & Chaves, Inês & Macedo, Pedro & Moutinho, Victor & Pereira, Mariana, 2023. "Crossing non-parametric and parametric techniques for measuring the efficiency: Evidence from 65 European electricity Distribution System Operators," Energy, Elsevier, vol. 283(C).
    7. Kao, Chiang & Pang, Rui-Zhi & Liu, Shiang-Tai & Bai, Xue-Jie, 2021. "Optimal expansion paths for hospitals of different types: Viewpoint of scope economies and evidence from Chinese hospitals," European Journal of Operational Research, Elsevier, vol. 289(2), pages 628-638.
    8. Roman Neyter & Oleg Nivievskyi, 2023. "Effect of subsidies on farms' exit decision," Agribusiness, John Wiley & Sons, Ltd., vol. 39(4), pages 941-959, October.
    9. Ben Amor, Tawfik & Mellah, Thuraya, 2023. "Cost efficiency of Tunisian water utility districts: Does heterogeneity matter?," Utilities Policy, Elsevier, vol. 84(C).
    10. Madhav Regmi & Allen M. Featherstone & Cortney A. Cowley & Mykel R. Taylor, 2021. "Big Banks versus Agricultural Banks: Has Too‐Big‐To‐Fail Regulation Affected Efficiency and Scale Economies Measures?," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(3), pages 1164-1178, May.

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