Summary of identified research streams
| Cluster 1 | Cluster 2 | Cluster 3 | |
|---|---|---|---|
| Analysed country | Developing (14), developed (4), emerging (2) | Developing (3), developed (17), international comparison (5) | Developing (7), developed (11), international comparison (2) |
| Farm type | General farming sector (12), animal-dairy (4), crop (4) | General farming sector (19), animal (1) | General farming sector (9), animal (4), crop (7) |
| Time span | Short term (9), medium term (6), long term (5) | Short term (1), medium term (2), long term (15) | Short term (7), medium term (3), long term (10) |
| Level of analysis | International (4), province/county/region (9), farm (7) | International (5), province/country/region (14) | International (4), province/county/region (10), farm (6) |
| General approach | Frontier (21) including: parametric (15), non-parametric (6)a | Non-frontier (7), frontier (10) of which: parametric (3), non-parametric (7) | Frontier (20) of which: parametric (5), non-parametric (17) |
| Technical developments |
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| Contexts | R&D (7), institutional and policy reforms (9), natural environment (3) | R&D (9), institutional and policy reforms (4), natural environment (6) | R&D (9), institutional and policy reforms (5), natural environment (5) |
| Cluster 1 | Cluster 2 | Cluster 3 | |
|---|---|---|---|
| Analysed country | Developing (3), | Developing (7), | |
| Farm type | |||
| Time span | Short term (1), medium term (2), | Short term (7), medium term (3), | |
| Level of analysis | International (4), | International (5), province/country/region (14) | International (4), |
| General approach | Frontier (21) including: | Frontier (20) of which: parametric (5), | |
| Technical developments | Luenberger–Hicks-Moorsteen index Sequential technology in Malmquist index Random coefficient specification Generalised maximum entropy methods Bayesian methods Greene's SFA models, metafrontier models (including multiple output) Latent class models | Lowe index Nutrient total factor productivity index Panel vector autoregression (PVAR) Sequential primal-dual estimation routine to calculate TFP change Time-series panel models (e.g. common correlated effects mean group estimator) | Färe–Primont index New methods of decomposition Pollution adjustment Weather as an input Comparison of results for different methods/harming types/socio-economic features Clustering (latent class, classification tree, multiple correspondence analysis) Bootstrapping Two-step determinants assessment |
| Contexts | R&D (7), |
Note(s): Short term is up to 10 years, medium term is 11–20 years, long term is more than 20 years; ain some papers more than one method is used; the number of papers is in parentheses; the dominant feature is in italic
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