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Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms
Author(s) -
Dakpo K Hervé,
Latruffe Laure,
Desjeux Yann,
Jeanneaux Philippe
Publication year - 2021
Publication title -
journal of agricultural economics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.157
H-Index - 61
eISSN - 1477-9552
pISSN - 0021-857X
DOI - 10.1111/1477-9552.12422
Subject(s) - productivity , livestock , grazing , frontier , latent class model , transitive relation , index (typography) , geography , agricultural science , econometrics , mathematics , ecology , environmental science , statistics , economics , forestry , biology , computer science , archaeology , combinatorics , world wide web , macroeconomics
Our objective is to extend the latent class stochastic frontier (LCSFM) model to compute productivity change, using the robust transitive productivity Färe‐Primont index. The application is to three types of grazing livestock farms in France over the period 2002–2016. The LCSFM identified two classes of farms, intensive farms and extensive farms. Results indicate that productivity change and its components show only small differences between the LCSFM and the pooled model that does not account for heterogeneity. Differences across classes exist, but depend on farm type.