Afficher la notice abrégée

Measuring productivity when technology is heterogeneous using a latent class stochastic frontier model

dc.rights.licenseopenen_US
dc.contributor.authorDAKPO, K. Hervé
hal.structure.identifierBordeaux Sciences Economiques [BSE]
dc.contributor.authorLATRUFFE, Laure
hal.structure.identifierBordeaux Sciences Economiques [BSE]
dc.contributor.authorDESJEUX, Yann
dc.contributor.authorJEANNEAUX, Philippe
dc.date.accessioned2024-06-03T15:28:33Z
dc.date.available2024-06-03T15:28:33Z
dc.date.issued2024-05-13
dc.identifier.issn0377-7332en_US
dc.identifier.urioai:crossref.org:10.1007/s00181-024-02604-0
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/200232
dc.description.abstractEnWe examine an extension of the latent class stochastic frontier model (LCSFM) to productivity estimation and the decomposition of productivity change into technical change, output-oriented technical efficiency change, and scale change. We base our productivity estimation on a Multi-class Grifell-Tatjé, Lovell & Orea Malmquist (GLOM) index. An advantage of this new productivity index is to account for classes' posterior probabilities to derive individual farm parameters. In addition, we extend our analysis to estimate a metafrontier GLOM productivity index to explore potentialities when all firms use the best available technologies. An empirical application to a sample of French sheep and goat farms observed between 2002 and 2021 confirms the necessity to account for technological heterogeneity when measuring productivity change. Among the two classes of farms identified by the LCSFM, the intensive class experiences TFP gains, while the extensive class sees its TFP worsening. However, the gap between intensive and extensive technologies seems to reduce over time. Finally, the multi-class GLOM reveals technical change as the primary driver of productivity for French goat and sheep farms.
dc.language.isoENen_US
dc.sourcecrossref
dc.subject.enMulti-class Grifell-Tatjé
dc.subject.enLovell
dc.subject.enOrea Malmquist productivity index
dc.subject.enMetafrontier GLOM productivity index
dc.subject.enLatent class stochastic frontier
dc.subject.enSheep and goat farms
dc.subject.enFrance
dc.title.enMeasuring productivity when technology is heterogeneous using a latent class stochastic frontier model
dc.typeArticle de revueen_US
dc.identifier.doi10.1007/s00181-024-02604-0en_US
dc.subject.halSciences de l'Homme et Société/Economies et financesen_US
dc.subject.jelC - Mathematical and Quantitative Methods::C4 - Econometric and Statistical Methods: Special Topics::C43 - Index Numbers and Aggregationen_US
dc.subject.jelD - Microeconomics::D2 - Production and Organizations::D24 - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacityen_US
dc.subject.jelQ - Agricultural and Natural Resource Economics; Environmental and Ecological Economics::Q1 - Agriculture::Q10 - Generalen_US
bordeaux.journalEmpirical Economicsen_US
bordeaux.hal.laboratoriesBordeaux Sciences Economiques / Bordeaux School of Economics (BSE) - UMR 6060en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionCNRSen_US
bordeaux.institutionINRAEen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
bordeaux.import.sourcedissemin
hal.identifierhal-04599393
hal.version1
hal.date.transferred2024-06-03T15:28:35Z
hal.popularnonen_US
hal.audienceInternationaleen_US
hal.exporttrue
workflow.import.sourcedissemin
dc.rights.ccPas de Licence CCen_US
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=Empirical%20Economics&rft.date=2024-05-13&rft.eissn=0377-7332&rft.issn=0377-7332&rft.au=DAKPO,%20K.%20Herv%C3%A9&LATRUFFE,%20Laure&DESJEUX,%20Yann&JEANNEAUX,%20Philippe&rft.genre=article


Fichier(s) constituant ce document

FichiersTailleFormatVue

Il n'y a pas de fichiers associés à ce document.

Ce document figure dans la(les) collection(s) suivante(s)

Afficher la notice abrégée