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A Stochastic Frontier Model with Endogenous Treatment Status and Mediator

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  • Yi-Ting Chen
  • Yu-Chin Hsu
  • Hung-Jen Wang

Abstract

Government policies are frequently used to promote productivity. Some policies are designed to enhance production technology, while others are meant to improve production efficiency. An important issue to consider when designing and evaluating policies is whether a mediator is required or effective in achieving the desired final outcome. To better understand and evaluate the policies, we propose a new stochastic frontier model with a treatment status and a mediator, both of which are allowed to be endogenous. The model allows us to decompose the total program (treatment) effect into technology and efficiency components, and to investigate whether the effect is derived directly from the program or indirectly through a particular mediator. Supplementary materials for this article are available online.

Suggested Citation

  • Yi-Ting Chen & Yu-Chin Hsu & Hung-Jen Wang, 2020. "A Stochastic Frontier Model with Endogenous Treatment Status and Mediator," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 38(2), pages 243-256, April.
    • Handle: RePEc:taf:jnlbes:v:38:y:2020:i:2:p:243-256
    DOI: 10.1080/07350015.2018.1497504
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    Cited by:

    1. Christopher F. Parameter & Léopold Simar & Ingrid Van Keilegom & Valentin Zelenyuk, 2021. "Inference in the Nonparametric Stochastic Frontier Model," CEPA Working Papers Series WP132021, School of Economics, University of Queensland, Australia.
    2. Mohammed, Sadick & Abdulai, Awudu, 2021. "Extension Participation and Improved Technology Adoption: Impact on Efficiency and Welfare of Farmers in Ghana," 2021 Conference, August 17-31, 2021, Virtual 315362, International Association of Agricultural Economists.
    3. Salm, Martin & Siflinger, Bettina & Xie, Mingjia, 2021. "The Effect of Retirement on Mental Health: Indirect Treatment Effects and Causal Mediation," Other publications TiSEM e28efa7f-8219-437c-a26d-2, Tilburg University, School of Economics and Management.
    4. Yitayew, Asresu & Abdulai, Awudu & Yigezu, Yigezu A., 2023. "The effects of advisory services and technology channeling on farm yields and technical efficiency of wheat farmers in Ethiopia," Food Policy, Elsevier, vol. 116(C).
    5. Huang, W. & Linton, O. & Zhang, Z., 2021. "A Unified Framework for Specification Tests of Continuous Treatment Effect Models," Cambridge Working Papers in Economics 2113, Faculty of Economics, University of Cambridge.
    6. Le-Yu Chen & Yu-Min Yen, 2021. "Estimations of the Conditional Tail Average Treatment Effect," Papers 2109.08793, arXiv.org, revised Sep 2021.
    7. Centorrino, Samuele & Pérez-Urdiales, María & Bravo-Ureta, Boris & Wall, Alan, 2022. "Binary endogenous treatment in stochastic frontier models with an application to soil conservation in El Salvador," Efficiency Series Papers 2022/02, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    8. Centorrino, Samuele & Perez Urdiales, Mari­a & Bravo-Ureta, Boris & Wall, Alan, 2021. "Binary Endogenous Treatment in Stochastic Frontier Models with an Application to Soil Conservation in El Salvador," 95th Annual Conference, March 29-30, 2021, Warwick, UK (Hybrid) 312058, Agricultural Economics Society - AES.

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