A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region
Structural change is integral to evolving economies (Goddard et al., 1993). Although increased agricultural productivity has allowed the release of resources needed by other sectors of the economy, structural change in agriculture usually has a negative connotation in public debate (Balmann and Vale...
| Autores principales: | , , , , |
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| Formato: | Resumen |
| Lenguaje: | Inglés |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/129665 |
| _version_ | 1855535884742426624 |
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| author | Mantziaris, Stamatis Rozakis, Stelios Karanikolas, Pavlos Tsiboukas, Konstantinos Petsakos, Athanasios |
| author_browse | Karanikolas, Pavlos Mantziaris, Stamatis Petsakos, Athanasios Rozakis, Stelios Tsiboukas, Konstantinos |
| author_facet | Mantziaris, Stamatis Rozakis, Stelios Karanikolas, Pavlos Tsiboukas, Konstantinos Petsakos, Athanasios |
| author_sort | Mantziaris, Stamatis |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | Structural change is integral to evolving economies (Goddard et al., 1993). Although increased agricultural productivity has allowed the release of resources needed by other sectors of the economy, structural change in agriculture usually has a negative connotation in public debate (Balmann and Valentinov, 2016). There are mainly two types of public concern about structural change in agriculture, with the former expressed as “dying peasants” and the latter as “factory farming” (Balmann and Valentinov, 2016). In this context, detailed and up-to-date information on structural change in agriculture is valuable for policymakers and stakeholders as it forms the basis for policy analysis (Espinosa et al., 2016). Moreover, modeling exercises can support the formulation of structural policies to obtain the “desired farm structure” or “optimal farm structure”, considering the constraints that societal demand places based on equity goals (Goddard et al., 1993; Finger and Benni, 2021). Simulation models such as recursive dynamic programming models and more sophisticated agent-based models allow for endogenous structural change, and they are considered appropriate for analyzing the structural effects of policy reforms on a region‟s agricultural structure (Happe et al., 2008; Espinosa et al., 2016). Based on the above, in this study, we present the structure of a recursive dynamic linear programming farm-level model coupled to the ARIMA stochastic process to simulate the impact of a policy regime reform on structural change. Determination of farm viability is not just based on traditional monetary criteria, but also on an innovative criterion, comparing the profitability of the farm with the standard of living of the reference group (neighboring farms) according to the concept of “pecuniary emulation” (Veblen, 1899). An additional innovative structural element of the proposed modeling approach corresponds to how resources are reallocated/allocated between viable neighboring farms following the theoretical model of efficient allocation (Ayerst et al., 2020). A representative sample of arable farms of the region of Karditsa (NUTS 3 level) is utilized for the empirical application of the suggested model. The model is validated for its ability to simulate the allocation of
actual activities and the farm size distribution of the reference period. Then we perform simulations for two policy scenarios: i) the business as usual (BAU) scenario and ii) the alternative policy scenario referred to as the CAP Post-2020 reform scenario based on the Greek Strategic Plan proposal for the CAP 2023-2027. Increasing average farm size and decreasing number of viable farms indicate that the characteristics of structural change are expressed in all policy scenarios. Nevertheless, the results of the simulation for the CAP Post-2020 reform scenario against the BAU scenario, prove a further reduction of the percentage of farms with a size of fewer than 30 hectares. |
| format | Abstract |
| id | CGSpace129665 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| record_format | dspace |
| spelling | CGSpace1296652025-11-05T12:24:59Z A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region Mantziaris, Stamatis Rozakis, Stelios Karanikolas, Pavlos Tsiboukas, Konstantinos Petsakos, Athanasios structural adjustment simulation models dynamic programming arable farming cambio estructural modelos de simulación programación dinámica Structural change is integral to evolving economies (Goddard et al., 1993). Although increased agricultural productivity has allowed the release of resources needed by other sectors of the economy, structural change in agriculture usually has a negative connotation in public debate (Balmann and Valentinov, 2016). There are mainly two types of public concern about structural change in agriculture, with the former expressed as “dying peasants” and the latter as “factory farming” (Balmann and Valentinov, 2016). In this context, detailed and up-to-date information on structural change in agriculture is valuable for policymakers and stakeholders as it forms the basis for policy analysis (Espinosa et al., 2016). Moreover, modeling exercises can support the formulation of structural policies to obtain the “desired farm structure” or “optimal farm structure”, considering the constraints that societal demand places based on equity goals (Goddard et al., 1993; Finger and Benni, 2021). Simulation models such as recursive dynamic programming models and more sophisticated agent-based models allow for endogenous structural change, and they are considered appropriate for analyzing the structural effects of policy reforms on a region‟s agricultural structure (Happe et al., 2008; Espinosa et al., 2016). Based on the above, in this study, we present the structure of a recursive dynamic linear programming farm-level model coupled to the ARIMA stochastic process to simulate the impact of a policy regime reform on structural change. Determination of farm viability is not just based on traditional monetary criteria, but also on an innovative criterion, comparing the profitability of the farm with the standard of living of the reference group (neighboring farms) according to the concept of “pecuniary emulation” (Veblen, 1899). An additional innovative structural element of the proposed modeling approach corresponds to how resources are reallocated/allocated between viable neighboring farms following the theoretical model of efficient allocation (Ayerst et al., 2020). A representative sample of arable farms of the region of Karditsa (NUTS 3 level) is utilized for the empirical application of the suggested model. The model is validated for its ability to simulate the allocation of actual activities and the farm size distribution of the reference period. Then we perform simulations for two policy scenarios: i) the business as usual (BAU) scenario and ii) the alternative policy scenario referred to as the CAP Post-2020 reform scenario based on the Greek Strategic Plan proposal for the CAP 2023-2027. Increasing average farm size and decreasing number of viable farms indicate that the characteristics of structural change are expressed in all policy scenarios. Nevertheless, the results of the simulation for the CAP Post-2020 reform scenario against the BAU scenario, prove a further reduction of the percentage of farms with a size of fewer than 30 hectares. 2022-09-14 2023-03-15T14:34:16Z 2023-03-15T14:34:16Z Abstract https://hdl.handle.net/10568/129665 en Open Access application/pdf Mantziaris, S.; Rozakis, S.; Karanikolas, P.; Tsiboukas, K.; Petsakos, A. (2022) A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region. In: Abstracts Book, 182nd EAAE Seminar "Sustainability via biodiverse agri-food value chains”, Mediterranean Agronomic Institute of Chania (MAICh) Chania, Greece, 14 - 15 September, 2022, 80 p. |
| spellingShingle | structural adjustment simulation models dynamic programming arable farming cambio estructural modelos de simulación programación dinámica Mantziaris, Stamatis Rozakis, Stelios Karanikolas, Pavlos Tsiboukas, Konstantinos Petsakos, Athanasios A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region |
| title | A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region |
| title_full | A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region |
| title_fullStr | A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region |
| title_full_unstemmed | A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region |
| title_short | A recursive dynamic linear programming farm-level model to simulate the structural change in the arable production system of a Greek region |
| title_sort | recursive dynamic linear programming farm level model to simulate the structural change in the arable production system of a greek region |
| topic | structural adjustment simulation models dynamic programming arable farming cambio estructural modelos de simulación programación dinámica |
| url | https://hdl.handle.net/10568/129665 |
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