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Estimating efficiency effects in a panel data stochastic frontier model
Paul, Satya; Shankar, Sriram - In: Journal of productivity analysis : an official journal … 53 (2020) 2, pp. 163-180
Persistent link: https://www.econbiz.de/10012228833
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Internal meta-analysis for Monte Carlo simulations
Andor, Mark Andreas; Bernstein, David H.; Parmeter, … - 2023
performance of three different estimators of the generalized stochastic frontier panel data model. Besides contributing to the …
Persistent link: https://www.econbiz.de/10014285373
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Operational conditions in regulatory benchmarking models : a Monte Carlo analysis
Nieswand, Maria; Seifert, Stefan - 2016
Benchmarking methods are widely used in the regulation of firms in network industries working under heterogeneous exogenous environments. In this paper we compare three recently developed estimators, namely conditional DEA (Daraio and Simar, 2005, 2007b), latent class SFA (Orea and Kumbhakar, 2004;...
Persistent link: https://www.econbiz.de/10011483291
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Environmental factors in frontier estimation : a Monte Carlo analysis
Nieswand, Maria; Seifert, Stefan - In: European journal of operational research : EJOR 265 (2018) 1, pp. 133-148
Persistent link: https://www.econbiz.de/10011805379
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Some cautions on the use of nonlinear panel unit root tests : evidence from a modified series-specific non-linear panel unit-root test
Lau, Chi Keung; Suvankulov, Farrukh; Su, Yongyang; … - In: Economic modelling 29 (2012) 3, pp. 810-816
Persistent link: https://www.econbiz.de/10009545513
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The difference, system and 'double-d GMM panel estimators in the presence of structural breaks
Chowdhury, Rosen Azad; Russell, Bill - 2012
Persistent link: https://www.econbiz.de/10009620285
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Broken effects? : how to reduce false positives in panel regressions
Wibbens, Phebo D.; Li, Xina - 2020
Persistent link: https://www.econbiz.de/10012299997
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You can't always get what you want? : a Monte Carlo analysis of the bias and the efficiency of dynamic panel data estimators
Kufenko, Vadmin; Prettner, Klaus - 2017
We assess the bias and the efficiency of state-of-the-art dynamic panel data estimators by means of model-based Monte … data, the results obtained with the different panel data estimators range from 0.03% to 17%. This implies a range of the …
Persistent link: https://www.econbiz.de/10011761250
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Broken effects? : how to reduce false positives in panel regressions
Wibbens, Phebo D.; Li, Xina - 2021
Persistent link: https://www.econbiz.de/10012542764
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Finite sample performance of specification tests for correlated random effects quantile panel regressions
Haque, Samiul; Delgado, Michael S. - In: Applied economics letters 24 (2017) 7/9, pp. 515-519
Persistent link: https://www.econbiz.de/10011712426