Back to Search Start Over

A Synthesis on Agent-Based Impact Assessment Models from the Perspective of the EU Rural Development Policy Measures

Authors :
Rosalia Filippini
Carlos Leyva Guerrero
Pablo Baez Gonzales
Mario Veneziani
Selim Çağatay
Ali Koç
Peyman Uysal
Source :
Journal of Agricultural Sciences, Vol 30, Iss 4, Pp 628-643 (2024)
Publication Year :
2024
Publisher :
Faculty of Agriculture, Ankara University, 2024.

Abstract

The second pillar of the European Union’s (EU) Common Agricultural Policy (CAP) aims at supporting rural areas by meeting the economic, environmental and social challenges. To deal with these challenges, countries are faced with the question of selecting the best tools among a large set of policy instruments. The problem of choosing the best policy instruments is aggravated by the very heterogeneous character of the societal demands that differ among member countries with very different economic and institutional structures. This study aims to introduce the agent-based modelling platforms that have been widely used in the impact analysis of recent rural development policies in the EU in a comparative manner. It also aims to explain how the above-mentioned sources of heterogeneity are handled in these models. To achieve the stated objectives, the study first examines the historical development of rural development policies within the EU. Subsequently, it proceeds to analyse several agent-based platforms that have been employed for the purpose of assessing the impact of agricultural policies with respect to certain features such as integration of land market, modelling unit, decision rule, rules of exit, labour market and price formation. To conclude, it is observed that as the rural development policies are formulated on farm-basis and as farms have a heterogeneous structure within themselves, in addition, the expansion of databases and the development of empirical analysis tools and technologies have led to a shift in empirical analyses towards agent-based models. However, these modelling platforms still embody various problems, especially in terms of database adjustments and parameterization and calibration of the model.

Details

Language :
English
ISSN :
13007580
Volume :
30
Issue :
4
Database :
Directory of Open Access Journals
Journal :
Journal of Agricultural Sciences
Publication Type :
Academic Journal
Accession number :
edsdoj.2d89dd4c147541af8186cd005d18be7e
Document Type :
article
Full Text :
https://doi.org/10.15832/ankutbd.1287221