On the estimation of total factor productivity: a novel Bayesian non-parametric approach

DOI10.1016/j.ejor.2019.03.035zbMath1430.90238OpenAlexW2926642641WikidataQ128203392 ScholiaQ128203392MaRDI QIDQ1740540

Mike G. Tsionas, Michael L. Polemis

Publication date: 30 April 2019

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://eprints.lancs.ac.uk/id/eprint/133199/1/Manuscript_R1_clean_Final_12.1.19.doc.pdf

zbMATH Keywords

manufacturingBayesian analysisMarkov chain Monte Carloestimation of TFPnon parametric models

Mathematics Subject Classification ID

Nonparametric estimation (62G05) Bayesian inference (62F15) Production models (90B30) Production theory, theory of the firm (91B38)

Related Items (3)

Do subsidies increase firm productivity? Evidence from Chinese manufacturing enterprises ⋮ Productivity spillovers and human capital: a semiparametric varying coefficient approach ⋮ Endogenous productivity: a new Bayesian perspective

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