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The diffusion of greenhouse agriculture in northern Thailand: Combining econometrics and agent-based modeling

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  • Schreinemachers, Pepijn
  • Berger, Thomas
  • Sirijinda, Aer
  • Praneetvatakul, Suwanna

Abstract

This paper studies the diffusion of greenhouse agriculture in a watershed in the northern uplands of Thailand by applying econometrics and agent-based modeling in combination. Adoption has been rapid by farmers in the central valley of the watershed, while farmers at higher altitudes, lacking transferable land titles that could serve as mortgage collateral, have been unable to obtain loans for greenhouse investment. The objectives of the paper are both methodological and empirical. On the methodological side, it shows that econometrically estimated models of farm household behavior are useful to design and to parameterize an agent-based model. On the empirical side, simulation results show that if mortgage collateral would not be required, then adoption in the upper part of the watershed could reach nearly 77 percent of farm households by 2020, as compared to about 36 percent under current conditions. Further results suggest a significant increase in incomes related to the innovation and a substantially greater irrigation water use, especially in the central part. As bell pepper under greenhouses has replaced pesticide-intensive chrysanthemum, it has declined average levels of pesticide use. Nevertheless, pesticide use is high and farmers are struggling to control pests, which raises questions about the long-term sustainability of the innovation.

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  • Schreinemachers, Pepijn & Berger, Thomas & Sirijinda, Aer & Praneetvatakul, Suwanna, 2009. "The diffusion of greenhouse agriculture in northern Thailand: Combining econometrics and agent-based modeling," 2009 Conference, August 16-22, 2009, Beijing, China 50899, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae09:50899
    DOI: 10.22004/ag.econ.50899
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    Cited by:

    1. Grovermann, Christian & Schreinemachers, Pepijn & Riwthong, Suthathip & Berger, Thomas, 2017. "‘Smart’ policies to reduce pesticide use and avoid income trade-offs: An agent-based model applied to Thai agriculture," Ecological Economics, Elsevier, vol. 132(C), pages 91-103.
    2. Kopp, Thomas & Salecker, Jan, 2020. "How traders influence their neighbours: Modelling social evolutionary processes and peer effects in agricultural trade networks," Journal of Economic Dynamics and Control, Elsevier, vol. 117(C).
    3. Grovermann, Christian & Schreinemachers, Pepijn & Berger, Thomas, 2015. "Evaluation of IPM adoption and financial instruments to reduce pesticide use in Thai agriculture using econometrics and agent-based modeling," 2015 Conference, August 9-14, 2015, Milan, Italy 211690, International Association of Agricultural Economists.
    4. Schreinemachers, Pepijn & Potchanasin, Chakrit & Berger, Thomas & Roygrong, Sithidech, 2009. "The declining profitability of litchi orchards in northern Thailand: Can innovations reverse the trend?," 2009 Conference, August 16-22, 2009, Beijing, China 50954, International Association of Agricultural Economists.
    5. Thomas Kopp & Jan Salecker, 2018. "Modelling Social Evolutionary Processes and Peer Effects in Agricultural Trade Networks: the Rubber Value Chain in Indonesia," Papers 1811.11476, arXiv.org.
    6. Quang, Dang Viet & Schreinemachers, Pepijn & Berger, Thomas, 2014. "Ex-ante assessment of soil conservation methods in the uplands of Vietnam: An agent-based modeling approach," Agricultural Systems, Elsevier, vol. 123(C), pages 108-119.
    7. Grovermann, Christian & Schreinemachers, Pepijn & Berger, Thomas, 2012. "Private and Social Levels of Pesticide Overuse in Rapidly Intensifying Upland Agriculture in Thailand," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126341, International Association of Agricultural Economists.
    8. Thomas Berger & Christian Troost & Tesfamicheal Wossen & Evgeny Latynskiy & Kindie Tesfaye & Sika Gbegbelegbe, 2017. "Can smallholder farmers adapt to climate variability, and how effective are policy interventions? Agent-based simulation results for Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 48(6), pages 693-706, November.
    9. Laura Schmitt Olabisi & Ryan Qi Wang & Arika Ligmann-Zielinska, 2015. "Why Don’t More Farmers Go Organic? Using A Stakeholder-Informed Exploratory Agent-Based Model to Represent the Dynamics of Farming Practices in the Philippines," Land, MDPI, vol. 4(4), pages 1-24, October.
    10. Shang, Linmei & Heckelei, Thomas & Gerullis, Maria K. & Börner, Jan & Rasch, Sebastian, 2021. "Adoption and diffusion of digital farming technologies - integrating farm-level evidence and system interaction," Agricultural Systems, Elsevier, vol. 190(C).
    11. Utomo, Dhanan Sarwo & Onggo, Bhakti Stephan & Eldridge, Stephen, 2018. "Applications of agent-based modelling and simulation in the agri-food supply chains," European Journal of Operational Research, Elsevier, vol. 269(3), pages 794-805.
    12. Jaap Sok & Egil A J Fischer, 2020. "Farmers' heterogeneous motives, voluntary vaccination and disease spread: an agent-based model," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 47(3), pages 1201-1222.
    13. Marius Eisele & Christian Troost & Thomas Berger, 2021. "How Bayesian Are Farmers When Making Climate Adaptation Decisions? A Computer Laboratory Experiment for Parameterising Models of Expectation Formation," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(3), pages 805-828, September.
    14. James Nolan & Dawn Parker & G. Cornelis Van Kooten & Thomas Berger, 2009. "An Overview of Computational Modeling in Agricultural and Resource Economics," Canadian Journal of Agricultural Economics/Revue canadienne d'agroeconomie, Canadian Agricultural Economics Society/Societe canadienne d'agroeconomie, vol. 57(4), pages 417-429, December.
    15. Holderieath, Jason, 2016. "Spatiotemporal management under heterogeneous damage and uncertain parameters. An agent-based approach," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235850, Agricultural and Applied Economics Association.
    16. Rianne Duinen & Tatiana Filatova & Wander Jager & Anne Veen, 2016. "Going beyond perfect rationality: drought risk, economic choices and the influence of social networks," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 57(2), pages 335-369, November.
    17. Robert Huber & Hang Xiong & Kevin Keller & Robert Finger, 2022. "Bridging behavioural factors and standard bio‐economic modelling in an agent‐based modelling framework," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(1), pages 35-63, February.
    18. Chen, Assaf, 2017. "Spatially explicit modelling of agricultural dynamics in semi-arid environments," Ecological Modelling, Elsevier, vol. 363(C), pages 31-47.
    19. Tobias Buchmann & Patrick Wolf & Stefan Fidaschek, 2021. "Stimulating E-Mobility Diffusion in Germany (EMOSIM): An Agent-Based Simulation Approach," Energies, MDPI, vol. 14(3), pages 1-25, January.
    20. Shang, Linmei & Heckelei, Thomas & Börner, Jan & Rasch, Sebastian, 2020. "Adoption and Diffusion of Digital Farming Technologies – Integrating Farm-Level Evidence and System-Level Interaction," 60th Annual Conference, Halle/ Saale, Germany, September 23-25, 2020 305586, German Association of Agricultural Economists (GEWISOLA).
    21. Tesfamicheal Wossen & Thomas Berger & Salvatore Di Falco, 2015. "Social capital, risk preference and adoption of improved farm land management practices in Ethiopia," Agricultural Economics, International Association of Agricultural Economists, vol. 46(1), pages 81-97, January.
    22. Marohn, Carsten & Troost, Christian & Warth, Benjamin & Bateki, Christian & Zijlstra, Mink & Anwar, Faizan & Williams, Benjamin & Descheemaeker, Katrien & Berger, Thomas & Asch, Folkard & Dickhoefer, , 2022. "Coupled biophysical and decision-making processes in grassland systems in East African savannahs – A modelling framework," Ecological Modelling, Elsevier, vol. 474(C).

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