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Regularized conditi...
Regularized conditional estimators of unit inefficiency in stochastic frontier analysis, with application to electricity distribution market
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- Zeebari, Zangin (författare)
- Karolinska Institutet,Jönköping University,IHH, Statistik,Department of Global Public Health, Karolinska Institutet, Stockholm, Sweden,Jönköping International Business School, Jonkoping, Sweden; Karolinska Institutet, Stockholm, Sweden
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- Månsson, Kristofer, 1983- (författare)
- Jönköping University,IHH, Statistik,IHH, Centre for Entrepreneurship and Spatial Economics (CEnSE),Jönköping International Business School, Jonkoping, Sweden
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- Sjölander, Pär (författare)
- Jönköping University,IHH, Statistik,Jönköping International Business School, Jonkoping, Sweden
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- Söderberg, Magnus, 1973- (författare)
- Högskolan i Halmstad,Akademin för företagande, innovation och hållbarhet,Halmstad University, Halmstad, Sweden; Ratio Institute, Stockholm, Sweden; Centre for Applied Energy Economics and Policy Research, Griffith University, Brisbane, QLD, Australia
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(creator_code:org_t)
- 2022-12-05
- 2022
- Engelska.
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Ingår i: Journal of Productivity Analysis. - New York, NY : Springer. - 0895-562X .- 1573-0441. ; 59:1, s. 79-97
- Relaterad länk:
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https://doi.org/10.1...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://urn.kb.se/re...
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http://kipublication...
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Abstract
Ämnesord
Stäng
- In stochastic frontier analysis, the conventional estimation of unit inefficiency is based on the mean/mode of the inefficiency, conditioned on the composite error. It is known that the conditional mean of inefficiency shrinks towards the mean rather than towards the unit inefficiency. In this paper, we analytically prove that the conditional mode cannot accurately estimate unit inefficiency, either. We propose regularized estimators of unit inefficiency that restrict the unit inefficiency estimators to satisfy some a priori assumptions, and derive the closed form regularized conditional mode estimators for the three most commonly used inefficiency densities. Extensive simulations show that, under common empirical situations, e.g., regarding sample size and signal-to-noise ratio, the regularized estimators outperform the conventional (unregularized) estimators when the inefficiency is greater than its mean/mode. Based on real data from the electricity distribution sector in Sweden, we demonstrate that the conventional conditional estimators and our regularized conditional estimators provide substantially different results for highly inefficient companies. © 2022, The Author(s).
Ämnesord
- SAMHÄLLSVETENSKAP -- Ekonomi och näringsliv -- Nationalekonomi (hsv//swe)
- SOCIAL SCIENCES -- Economics and Business -- Economics (hsv//eng)
- NATURVETENSKAP -- Matematik -- Matematisk analys (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Mathematical Analysis (hsv//eng)
Nyckelord
- C01
- C12
- C51
- Conditional Estimators
- Constrained Estimators
- H21
- Productivity
- Regularized Estimators
- Uncertainty modelling
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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