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A dynamic stochastic frontier production model with time-varying efficiency: comment

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  • Chunhua Wang

Abstract

Based on Desli et al. (2003), this comment defines a stochastic frontier production model in a panel data framework. The firms can learn from their past errors to improve technical efficiency. This is done by introducing the inefficiency error term as an AR(p) process. The ways to estimate the production function and technical inefficiency are provided.

Suggested Citation

  • Chunhua Wang, 2007. "A dynamic stochastic frontier production model with time-varying efficiency: comment," Applied Economics Letters, Taylor & Francis Journals, vol. 14(6), pages 415-417.
  • Handle: RePEc:taf:apeclt:v:14:y:2007:i:6:p:415-417
    DOI: 10.1080/13504850500447455
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    Cited by:

    1. Jin, Ding & Hedtrich, Johannes & Henning, Christian, 2018. "Applying Meta modeling for extended CGE-modeling: Sample techniques and potential application," Conference papers 332947, Purdue University, Center for Global Trade Analysis, Global Trade Analysis Project.
    2. Jin, Ding & Hedtrich, Johannes & Henning, Christian H. C. A., 2018. "Applying meta-modeling for extended CGE-modeling: Sampling techniques and potential application," Working Papers of Agricultural Policy WP2018-03, University of Kiel, Department of Agricultural Economics, Chair of Agricultural Policy.
    3. Assaf, A. George & Tsionas, Mike G., 2019. "A review of research into performance modeling in tourism research - Launching the Annals of Tourism Research curated collection on performance modeling in tourism research," Annals of Tourism Research, Elsevier, vol. 76(C), pages 266-277.

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