Frontier estimation in the presence of measurement error with unknown variance
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DOI: 10.1016/j.jeconom.2014.09.012
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- Kneip, Alois & Simar, Leopold & Van Keilegom, Ingrid, 2015. "Frontier estimation in the presence of measurement error with unknown variance," LIDAM Reprints ISBA 2015004, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
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Citations
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Cited by:
- Jean-Pierre Florens & Léopold Simar & Ingrid Van Keilegom, 2020.
"Estimation of the Boundary of a Variable Observed With Symmetric Error,"
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- Florens, Jean-Pierre & Simar, Leopold & Van Keilegom, Ingrid, 2018. "Estimation of the Boundary of a Variable observed with Symmetric Error," LIDAM Discussion Papers ISBA 2018008, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Jean-Pierre Florens & Léopold Simar & Ingrid van Keilegom, 2020. "Estimation of the Boundary of a Variable Observed with A Symmetric Error," Post-Print hal-02929524, HAL.
- Florens, Jean-Pierre & Simar, Léopold & Van Keilegom, Ingrid, 2020. "Estimation of the Boundary of a Variable Observed With Symmetric Error," LIDAM Reprints ISBA 2020049, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Florens, Jean-Pierre & Simar, Léopold & Van Keilegom, Ingrid, 2019. "Estimation of the Boundary of a Variable Observed with A Symmetric Error," TSE Working Papers 19-990, Toulouse School of Economics (TSE).
- Florens, Jean-Pierre & Simar, Leopold & Van Keilegom, Ingrid, 2019. "Estimation of the Boundary of a Variable observed with Symmetric Error," LIDAM Reprints ISBA 2019023, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Jean-Pierre Florens & Léopold Simar & Ingrid Van Keilegom, 2018. "Estimation of the boundary of a variable observed with symmetric error," Working Papers of Department of Decision Sciences and Information Management, Leuven 630770, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2020.
"Robust frontier estimation from noisy data: A Tikhonov regularization approach,"
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- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2016. "Robust frontier estimation from noisy data: a Tikhonov regularization approach," TSE Working Papers 16-665, Toulouse School of Economics (TSE), revised Jul 2018.
- Abdelaati Daouia & Jean-Pierre Florens & Léopold Simar, 2020. "Robust frontier estimation from noisy data: a Tikhonov regularization approach," Post-Print hal-02573853, HAL.
- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Leopold, 2016. "Robust frontier estimation from noisy data: a Tikhonov regularization approach," LIDAM Discussion Papers ISBA 2016028, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Christopher F. Parmeter & Léopold Simar & Ingrid Van Keilegom & Valentin Zelenyuk, 2024.
"Inference in the nonparametric stochastic frontier model,"
Econometric Reviews, Taylor & Francis Journals, vol. 43(7), pages 518-539, August.
- 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.
- Parmeter, Christopher F. & Simar, Léopold & Van Keilegom, Ingrid & Zelenyuk, Valentin, 2021. "Inference in the Nonparametric Stochastic Frontier Model," LIDAM Discussion Papers ISBA 2021029, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022.
"Stochastic Frontier Analysis: Foundations and Advances I,"
Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 8, pages 331-370,
Springer.
- Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2022. "Stochastic Frontier Analysis: Foundations and Advances II," Springer Books, in: Subhash C. Ray & Robert G. Chambers & Subal C. Kumbhakar (ed.), Handbook of Production Economics, chapter 9, pages 371-408, Springer.
- Subal C. Kumbhakar & Christopher F. Parmeter & Valentin Zelenyuk, 2017. "Stochastic Frontier Analysis: Foundations and Advances," Working Papers 2017-10, University of Miami, Department of Economics.
- Subal C. Kumbhakar & Christopher F. Parameter & Valentin Zelenyuk, 2018. "Stochastic Frontier Analysis: Foundations and Advances," CEPA Working Papers Series WP022018, School of Economics, University of Queensland, Australia.
- Tsionas, Mike G., 2020. "Bounded rationality and thick frontiers in stochastic frontier analysis," European Journal of Operational Research, Elsevier, vol. 284(2), pages 762-768.
- Christopher F. Parmeter & Alan T. K. Wan & Xinyu Zhang, 2019.
"Model averaging estimators for the stochastic frontier model,"
Journal of Productivity Analysis, Springer, vol. 51(2), pages 91-103, June.
- Christopher F. Parmeter & Alan T. K. Wan & Xinyu Zhang, 2016. "Model Averaging Estimators for the Stochastic Frontier Model," Working Papers 2016-09, University of Miami, Department of Economics.
- Simar, Léopold & Vanhems, Anne & Van Keilegom, Ingrid, 2016.
"Unobserved heterogeneity and endogeneity in nonparametric frontier estimation,"
Journal of Econometrics, Elsevier, vol. 190(2), pages 360-373.
- Simar, Leopold & Vanhems, Anne & Van Keilegom, Ingrid, 2013. "Unobserved heterogeneity and endogeneity in nonparametric frontier estimation," LIDAM Discussion Papers ISBA 2013054, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Simar, Leopold & Vanhems, Anne & Van Keilegom, Ingrid, 2016. "Unobserved heterogeneity and endogeneity in nonparametric frontier estimation," LIDAM Reprints ISBA 2016007, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Jun Cai & William C. Horrace & Christopher F. Parmeter, 2021.
"Density deconvolution with Laplace errors and unknown variance,"
Journal of Productivity Analysis, Springer, vol. 56(2), pages 103-113, December.
- Jun Cai & William C. Horrace & Christopher F. Parmeter, 2020. "Density Deconvolution with Laplace Errors and Unknown Variance," Center for Policy Research Working Papers 225, Center for Policy Research, Maxwell School, Syracuse University.
- Zhou, Jianhua & Parmeter, Christopher F. & Kumbhakar, Subal C., 2020. "Nonparametric estimation of the determinants of inefficiency in the presence of firm heterogeneity," European Journal of Operational Research, Elsevier, vol. 286(3), pages 1142-1152.
- William C. Horrace & Yulong Wang, 2022.
"Nonparametric tests of tail behavior in stochastic frontier models,"
Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(3), pages 537-562, April.
- William & C. Horrace & Yulong Wang, 2020. "Nonparametric Tests of Tail Behavior in Stochastic Frontier Models," Papers 2006.07780, arXiv.org.
- William C. Horrace & Yulong Wang, 2020. "Nonparametric Tests of Tail Behavior in Stochastic Frontier Models," Center for Policy Research Working Papers 230, Center for Policy Research, Maxwell School, Syracuse University.
- Eric Weese & Masayoshi Hayashi & Masashi Nishikawa, 2015.
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- Eric Weese & Masayoshi Hayashi & Masashi Nishikawa, 2016. "Inefficiency and Self-Determination: Simulation-based evidence from Meiji Japan," Discussion Papers 1627, Graduate School of Economics, Kobe University.
- Eric Weese & Masayoshi Hayashi & Masashi Nishikawa, 2015. "Inefficiency and Self-Determination: Simulation-Based Evidence From Meiji Japan," Working Papers 1050, Economic Growth Center, Yale University.
- Eric Weese & Masayoshi Hayashi & Masashi Nishikawa, 2015. "Inefficiency and Self-Determination: Simulation-based Evidence from Meiji Japan," CIRJE F-Series CIRJE-F-989, CIRJE, Faculty of Economics, University of Tokyo.
- Weese, Eric & Hayashi, Masayoshi & Nishikawa, Masashi, 2015. "Inefficiency and Self-Determination: Simulation-Based Evidence From Meiji Japan," Center Discussion Papers 211545, Yale University, Economic Growth Center.
- Centorrino, Samuele & Parmeter, Christopher F., 2024. "Nonparametric estimation of stochastic frontier models with weak separability," Journal of Econometrics, Elsevier, vol. 238(2).
- Christopher F. Parmeter & Valentin Zelenyuk, 2019. "Combining the Virtues of Stochastic Frontier and Data Envelopment Analysis," Operations Research, INFORMS, vol. 67(6), pages 1628-1658, November.
- Parmeter, Christopher F. & Simar, Léopold & Van Keilegom, Ingrid & Zelenyuk, Valentin, 2024. "Inference in the nonparametric stochastic frontier model," LIDAM Reprints ISBA 2024013, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Song, Junmo & Oh, Dong-hyun & Kang, Jiwon, 2017. "Robust estimation in stochastic frontier models," Computational Statistics & Data Analysis, Elsevier, vol. 105(C), pages 243-267.
- Léopold Simar & Paul W. Wilson, 2023.
"Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs,"
Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 41(4), pages 1391-1403, October.
- Simar, Léopold & Wilson, Paul, 2021. "Nonparametric, Stochastic Frontier Models with Multiple Inputs and Outputs," LIDAM Discussion Papers ISBA 2021003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Preciado Arreola, José Luis & Johnson, Andrew L. & Chen, Xun C. & Morita, Hiroshi, 2020. "Estimating stochastic production frontiers: A one-stage multivariate semiparametric Bayesian concave regression method," European Journal of Operational Research, Elsevier, vol. 287(2), pages 699-711.
- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2021.
"Robustified Expected Maximum Production Frontiers,"
Econometric Theory, Cambridge University Press, vol. 37(2), pages 346-387, April.
- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Leopold, 2018. "Robustified expected maximum production frontiers," LIDAM Discussion Papers ISBA 2018003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Leopold, 2020. "Robustified expected maximum production frontiers," LIDAM Reprints ISBA 2020003, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
- Daouia, Abdelaati & Florens, Jean-Pierre & Simar, Léopold, 2018. "Robustified expected maximum production frontiers," TSE Working Papers 17-890, Toulouse School of Economics (TSE).
- Bao Hoang Nguyen & Robin C. Sickles & Valentin Zelenyuk, 2022.
"Efficiency Analysis with Stochastic Frontier Models Using Popular Statistical Softwares,"
Springer Books, in: Duangkamon Chotikapanich & Alicia N. Rambaldi & Nicholas Rohde (ed.), Advances in Economic Measurement, chapter 0, pages 129-171,
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- Nguyen, B.H. & Sickles, R. & Zelenyuk, V., "undated". "Efficiency Analysis with Stochastic Frontier Models using Popular Statistical Softwares," Working Papers 1, International Society for Efficiency and Productivity Analysis.
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- Jun Cai & William C. Horrace & Christopher F. Parmeter, 2024. "Penalized sieve estimation of zero‐inefficiency stochastic frontiers," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 39(1), pages 41-65, January.
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More about this item
Keywords
Deconvolution; Stochastic frontier estimation; Nonparametric estimation; Penalized likelihood;All these keywords.
JEL classification:
- C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
- C49 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Other
- D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
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