Estimating production functions with robustness against errors in the proxy variables
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DOI: 10.1016/j.jeconom.2019.05.024
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- Guofang Huang & Yingyao Hu, 2011. "Estimating Production Functions with Robustness Against Errors in the Proxy Variables," Economics Working Paper Archive 583, The Johns Hopkins University,Department of Economics.
- Guofang Huang & Yingyao Hu, 2011. "Estimating production functions with robustness against errors in the proxy variables," CeMMAP working papers CWP35/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
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Citations
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Cited by:
- Mike G. Tsionas & Subal C. Kumbhakar, 2023. "Proxy variable estimation of productivity and efficiency," Southern Economic Journal, John Wiley & Sons, vol. 89(3), pages 885-923, January.
- Ioannis Bournakis & Mike Tsionas, 2024.
"A Non‐parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax,"
Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 86(3), pages 641-671, June.
- Bournakis, Ioannis & Tsionas, Mike G., 2023. "A Non-Parametric Estimation of Productivity with Idiosyncratic and Aggregate Shocks: The Role of Research and Development (R&D) and Corporate Tax," MPRA Paper 118100, University Library of Munich, Germany.
- Manuel Arellano & Stéphane Bonhomme, 2017.
"Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models,"
Annual Review of Economics, Annual Reviews, vol. 9(1), pages 471-496, September.
- Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers CWP51/16, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear panel data methods for dynamic heterogeneous agent models," CeMMAP working papers 51/16, Institute for Fiscal Studies.
- Manuel Arellano & Stéphane Bonhomme, 2016. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2016_1607, CEMFI.
- Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2017_1703, CEMFI.
- Tong Li & Yuya Sasaki, 2017. "Constructive Identification of Heterogeneous Elasticities in the Cobb-Douglas Production Function," Papers 1711.10031, arXiv.org.
- Alvaro Aguirre & Matias Tapia & Lucciano Villacorta, 2021. "Production, Investment and Wealth Dynamics under Financial Frictions: An Empirical Investigation of the Selffinancing Channel," Working Papers Central Bank of Chile 904, Central Bank of Chile.
- Hu, Yingyao & Huang, Guofang & Sasaki, Yuya, 2020.
"Estimating production functions with robustness against errors in the proxy variables,"
Journal of Econometrics, Elsevier, vol. 215(2), pages 375-398.
- Guofang Huang & Yingyao Hu, 2011. "Estimating production functions with robustness against errors in the proxy variables," CeMMAP working papers CWP35/11, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
- Guofang Huang & Yingyao Hu, 2011. "Estimating Production Functions with Robustness Against Errors in the Proxy Variables," Economics Working Paper Archive 583, The Johns Hopkins University,Department of Economics.
- Li, Tong & Sasaki, Yuya, 2024. "Identification of heterogeneous elasticities in gross-output production functions," Journal of Econometrics, Elsevier, vol. 238(2).
- Dibyendu Maiti & Chiranjib Neogi, 2024.
"Endogeneity-corrected stochastic frontier with market imperfections,"
Empirical Economics, Springer, vol. 67(3), pages 1149-1183, September.
- Dibyendu Maiti & Chiranjib Neogi, 2020. "Endogeneity Corrected Stochastic Frontier with Market Imperfections," Working papers 313, Centre for Development Economics, Delhi School of Economics.
- Chen Yeh & Claudia Macaluso & Brad Hershbein, 2022.
"Monopsony in the US Labor Market,"
American Economic Review, American Economic Association, vol. 112(7), pages 2099-2138, July.
- Chen Yeh & Claudia Macaluso & Brah J. Hershbein, 2022. "Monopsony in the U.S. Labor Market," Upjohn Working Papers 22-364, W.E. Upjohn Institute for Employment Research.
- Manuel Arellano & Stéphane Bonhomme, 2017. "Nonlinear Panel Data Methods for Dynamic Heterogeneous Agent Models," Working Papers wp2018_1703, CEMFI.
- Kim, Kyoo il & Petrin, Amil & Song, Suyong, 2016. "Estimating production functions with control functions when capital is measured with error," Journal of Econometrics, Elsevier, vol. 190(2), pages 267-279.
- Abito, Jose Miguel, 2019. "Estimating Production Functions with Fixed Effects," MPRA Paper 97825, University Library of Munich, Germany.
- Chen, Hanxue & Wang, Shuhong & Song, Malin, 2021. "Global Environmental Value Chain Embeddedness and Enterprise Production Efficiency Improvement," Structural Change and Economic Dynamics, Elsevier, vol. 58(C), pages 278-290.
- Mike G. Tsionas & Subal C. Kumbhakar, 2023. "Productivity and Performance: A GMM approach," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 85(2), pages 331-344, April.
- Daniel A. Ackerberg & Kevin Caves & Garth Frazer, 2015. "Identification Properties of Recent Production Function Estimators," Econometrica, Econometric Society, vol. 83, pages 2411-2451, November.
- Ainagul T. Mamyralieva & Aziza B. Karbekova & Gulchehra B. Abdyrahmanova, 2022. "Analysis of the economic sectors? sustainability of the Kyrgyz Republic," RIVISTA DI STUDI SULLA SOSTENIBILITA', FrancoAngeli Editore, vol. 0(2), pages 185-204.
- Emir Malikov & Jingfang Zhang & Shunan Zhao & Subal C. Kumbhakar, 2023. "Accounting for Cross-Location Technological Heterogeneity in the Measurement of Operations Efficiency and Productivity," Papers 2302.13430, arXiv.org.
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More about this item
Keywords
Production functions; Proxy variables; Instrumental variables; Optimization errors; Measurement errors;All these keywords.
JEL classification:
- C14 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Semiparametric and Nonparametric Methods: General
Statistics
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