Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms
Overview & Synopsis
Our objective is to extend the latent class stochastic frontier (LCSFM) model to compute productivity change, using the robust transitive productivity Fare-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.
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Document Information
| Document Title | Latent Class Modelling for a Robust Assessment of Productivity: Application to French Grazing Livestock Farms |
|---|---|
| Author / Organization | K Hervé Hervé Dakpo, Laure Latruffe, Yann Desjeux, Philippe Jeanneaux |
| Subject & Discipline | Multidisciplinary Academic Open Research |
| Categories | Science & Mathematics |
| Publication Year | 2021 |
| License / Rights | Open Access / Creative Commons |
| Resource Verification | Listed PDF (Verification Pending) |
| Original Host Website |
HAL Open Science
(hal.science)
|
| File Format | application/pdf (Portable Document Format) |
| Language | EN |
| Catalog ID | DOC-163766 |
| Original Source Link | Visit Source Page on hal.science » |