Economic value of seasonal climate forecast for corn production in Bansud, Oriental Mindoro, Philippines
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Wilma C. De Los Santos
Macario Jr. B. Masagca
Jaesma A. Asinas-Lopez
Randy A. Quitain
Christian Anthony C. Agutaya
Abstract
This study assessed the economic value of seasonal climate forecasts (SCFs) for corn (Zea mays) production in Bansud, Oriental Mindoro, by comparing expected corn income with that of squash (Cucurbita maxima L.). Farmers prioritized corn partly because its farm-gate price is more stable than prices of alternative crops such as squash. The researchers integrated qualitative and quantitative assessments with decision-tree modeling to determine how access to probabilistic rainfall forecasts from PAGASA affects cropping decisions and expected incomes. Without climate information, the model showed that expected corn income was approximately 32% higher than the squash income, supporting farmers' preference for corn under baseline conditions. When seasonal rainfall forecasts were incorporated into planting decisions, simulated corn income increased further. Under PAGASA’s near-normal rainfall probabilities, corn achieved 69% income advantage over squash. Comparison of modeled outcomes with and without forecast use revealed an average income difference of approximately PHP 4,800 per decision cycle, representing a meaningful gain or avoided loss for smallholder farmers. In Bansud, the combination of a stable corn market and actionable rainfall forecasts provide an opportunity to improve household income while reducing climate-related production risks. Continued investment in timely forecast dissemination, farmer training, and locally tailored decision-support tools can enhance the practical value of SCFs in smallholder farmers. Providing accessible probabilistic climate information and helping farmers translate forecasts into appropriate planting and crop-selection action can generate measurable economic benefits, strengthen adaptive capacity, and support more climate-resilient agricultural livelihoods and development.
How to Cite
De Los Santos WC, Masagca MJB, Asinas-Lopez JA, Quitain RA, Agutaya CAC. 2026. Economic value of seasonal climate forecast for corn production in Bansud, Oriental Mindoro, Philippines. The Palawan Scientist. 18(2):in press. https://doi.org/10.69721/TPS.J.2026.18.2.07.
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Keywords
climate information, decision-tree analysis, economic valuation, small-holder farmers
References
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Bertolozzi-Caredio D. 2024. The farm succession effect on farmers’ management choices. Land Use Policy. 137:107014. https://doi.org/10.1016/j.landusepol.2023.107014
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Hatfield JL, Antle J, Garrett KA, Izaurralde RC, Mader T, Marshall E, Nearing M, Philip Robertson G, Ziska L. 2020. Indicators of climate change in agricultural systems. Climatic Change. 163(4):1719–1732. https://doi.org/10.1007/s10584-018-2222-2
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Jansuwan P, Zander KK. 2021. What to do with the farmland? Coping with ageing in rural Thailand. Journal of Rural Studies. 81:37–46. https://doi.org/10.1016/j.jrurstud.2020.12.003
Jones JW, Hansen JW, Royce FS, Messina CD. 2000. Potential benefits of climate forecasting to agriculture. Agriculture, Ecosystems and Environment. 82(1–3):169–184. https://doi.org/10.1016/S0167-8809(00)00225-5
Klemm T, McPherson RA. 2017. The development of seasonal climate forecasting for agricultural producers. Agricultural and Forest Meteorology. 232:384–399. https://doi.org/10.1016/j.agrformet.2016.09.005
Lemos MC, Finan TJ, Fox RW, Nelson DR, Tucker J. 2002. The use of seasonal climate forecasting in policymaking: Lessons from Northeast Brazil. Climatic Change. 55(4):479–507. https://doi.org/10.1023/A:1020785826029
Lu H, Xue J, Guo D. 2017. Efficacy of planting date adjustment as a cultivation strategy to cope with drought stress and increase rainfed maize yield and water-use efficiency. Agricultural Water Management. 179:227–235. https://doi.org/10.1016/j.agwat.2016.09.001
Mahadevakumar S, Sridhar KR. 2021. Diversity of pathogenic fungi in agricultural crops. In: Dubey SK, Verma SK, editors. Plant, Soil and Microbes in Tropical Ecosystems. Singapore: Springer Singapore. p. 101-149. https://doi.org/10.1007/978-981-16-3364-5_6
Malhi G, Kaur M, Kaushik P. 2021. Impact of climate change on agriculture and its mitigation strategies: A Review. Sustainability. 13(3):1318. https://doi.org/10.3390/su13031318
Mayo RE, Villarta LJS. 2023. Obstacle in corn production and the livelihood activities of smallholder farmers in South Central Philippines. Open Journal of Social Sciences. 11(10):573–586. https://doi.org/10.4236/jss.2023.1110032
Nering RF, Fernandez-Cornejo J. 2005. The impacts of off-farm income on farm efficiency, scale, and profitability for corn farms. https://doi.org/10.22004/AG.ECON.1956
Osei-Kofi PS, Badu EE, Dadzie PS, Bandanaa J. 2023. Demographic characteristics of farmers and the effectiveness of disseminating information on agriculture in Ghana. Ghana Journal of Agricultural Science. 58(2):98–114. https://doi.org/10.4314/gjas.v58i2
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Rubas D, Hill H, Mjelde J. 2006. Economics and climate applications: exploring the frontier. Climate Research. 33:43–54. https://doi.org/10.3354/cr033043
Sadok W, Angevin F, Bergez J-É, Bockstaller C, Colomb B, Guichard L, Reau R, Doré T. 2008. Ex ante assessment of the sustainability of alternative cropping systems: implications for using multi-criteria decision-aid methods. A review. Agronomy for Sustainable Development. 28(1):163–174. https://doi.org/10.1051/agro:2007043
Salvacion AR, Martin AA. 2016. Climate change impact on corn suitability in Isabela province, Philippines. Journal of Crop Science and Biotechnology. 19(3):223–229. https://doi.org/10.1007/s12892-016-0019-2
Salvacion AR. 2015. Climatic change impact on corn productivity in the Philippines. International Journal of Sciences: Basic and Applied Research (IJSBAR). 23(1):54–68.
Sivakumar MVK, Hansen J. 2007. Climate prediction and agriculture: Summary and the way forward. In: Sivakumar Mannava V. K., Hansen James, editors. Climate Prediction and Agriculture: Advances and Challenges. Berlin, Heidelberg: Springer Berlin Heidelberg. p. 1–13. https://doi.org/10.1007/978-3-540-44650-7_1
Sultan B, Janicot S, Correia C. 2009. Medium lead-time predictability of intraseasonal variability of rainfall in West Africa. Weather and Forecasting. 24(3):767–784. https://doi.org/10.1175/2008WAF2222155.1
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Vermeulen SJ, Campbell BM, Ingram JSI. 2012. Climate change and food systems. Annual Review of Environment and Resources. 37(1):195–222. https://doi.org/10.1146/annurev-environ-020411-130608
Weaver CP, Lempert RJ, Brown C, Hall JA, Revell D, Sarewitz D. 2013. Improving the contribution of climate model information to decision making: the value and demands of robust decision frameworks. WIREs Climate Change. 4(1):39–60. https://doi.org/10.1002/wcc.202
Wilks DS. 1997. Forecast value: prescriptive decision studies. In: Katz RW, Murphy AH, editors. Economic Value of Weather and Climate Forecasts. 1st ed. Cambridge University Press. p. 109–146.
Yohannes H. 2016. A review on relationship between climate change and agriculture. Journal of Earth Science and Climatic Change. 07(02):335. https://doi.org/10.4172/2157-7617.1000335
Young KJ, Long SP. 2000. Crop ecosystem responses to climatic change: maize and sorghum. In: Reddy KR, Hodges HF, editors. Climate change and global crop productivity. First edition. UK: CABI Publishing. p. 107–131.
Zhao Y, Wang C, Wang S, Tibig LV. 2005. Impacts of present and future climate variability on agriculture and forestry in the humid and sub-humid tropics. Climatic Change. 70:73–116. https://doi.org/10.1007/s10584-005-5938-8
Arunanondchai P, Fei C, Fisher A, McCarl BA, Wang W, Yang Y. 2018. How does climate change affect agriculture? In: The Routledge Handbook of Agricultural Economics. 1st Edition. London: Routledge. p. 191–210.
Aryal JP, Sapkota TB, Khurana R, Khatri-Chhetri A, Rahut DB, Jat ML. 2020. Climate change and agriculture in South Asia: adaptation options in smallholder production systems. Environment, Development and Sustainability. 22(6):5045–5075. https://doi.org/10.1007/s10668-019-00414-4
Bertolozzi-Caredio D. 2024. The farm succession effect on farmers’ management choices. Land Use Policy. 137:107014. https://doi.org/10.1016/j.landusepol.2023.107014
Bryan E, Ringler C, Okoba B, Roncoli C, Silvestri S, Herrero M. 2013. Adapting agriculture to climate change in Kenya: Household strategies and determinants. Journal of Environmental Management. 114:26-35. https://doi.org/10.1016/j.jenvman.2012.10.036
Carnegie M, Cornish PS, Htwe KK, Htwe NN. 2020. Gender, decision-making and farm practice change: An action learning intervention in Myanmar. Journal of Rural Studies. 78:503-515. https://doi.org/10.1016/j.jrurstud.2020.01.002
Carter C, Cui X, Ghanem D, Mérel P. 2018. Identifying the economic impacts of climate change on agriculture. Annual Review of Resource Economics. 10(1):361-380. https://doi.org/10.1146/annurev-resource-100517-022938
Challinor A, Wheeler T, Garforth C, Craufurd P, Kassam A. 2007. Assessing the vulnerability of food crop systems in Africa to climate change. Climatic Change. 83(3):381–399. https://doi.org/10.1007/s10584-007-9249-0
Chirinos DT, Sánchez-Mora F, Zambrano F, Castro-Olaya J, Vasconez G, Cedeño G, Pin K, Zambrano J, Suarez-Navarrete V, Proaño V, and others. 2024. Entomofauna associated with corn cultivation and damage caused by some pests according to the planting season on the Ecuadorian Coast. Agronomy. 14(4):748. https://doi.org/10.3390/agronomy14040748
Cochran WG. 1977. Sampling techniques. Third edition. New York, New York: Wiley (Wiley series in probability and mathematical statistics).
DA-BAR (Department of Agriculture-Bureau of Agricultural Research). 2011. Philippine Rainfed Agriculture Research, Development and Extension Program (PhiRARDEP) framework and action agenda. Quezon City, Philippines, Applied Communication Division – Bureau of Agricultural Research. 21-45. [accessed on 2022 Jan 31]. https://bar.gov.ph/downloadables/publications/PhiRARDEP.pdf
Department of Agriculture. 2017. Squash production guide. [accessed 2023 Jan 31] https://cagayanvalley.da.gov.ph/wp-content/uploads/2018/02/Squash.pdf
Department of Agriculture. 2020. 2019 Annual Report. [accessed 2022 May 2]. https://drive.google.com/file/d/1nr2WOCo7uhKkxqIXVP1KrLsNoR06uv5Q/view.
Doblas‐Reyes FJ, García‐Serrano J, Lienert F, Biescas AP, Rodrigues LRL. 2013. Seasonal climate predictability and forecasting: status and prospects. WIREs Climate Change. 4(4):245–268. https://doi.org/10.1002/wcc.27
FAO (Food and Agriculture Organization of the United Nations). 2016. Sustainable crop production intensification. [accessed 2024 May 22]. https://openknowledge.fao.org/server/api/core/bitstreams/4fd44990-907a-4b82-b3f8-8991f1a4e85e/content
Gerpacio R, Labios J, Labios R, Diangkinay E. 2004. Maize in the Philippines: production systems, constraints, and research priorities. International Maize and Wheat Improvement Center. https://doi.org/10.22004/ag.econ.7650
Guido Z, Zimmer A, Lopus S, Hannah C, Gower D, Waldman K, Krell N, Sheffield J, Caylor K, Evans T. 2020. Farmer forecasts: Impacts of seasonal rainfall expectations on agricultural decision-making in Sub-Saharan Africa. Climate Risk Management. 30:100247. https://doi.org/10.1016/j.crm.2020.100247
Haigh T, Takle E, Andresen J, Widhalm M, Carlton JS, Angel J. 2015. Mapping the decision points and climate information use of agricultural producers across the U.S. Corn Belt. Climate Risk Management. 7:20–30. https://doi.org/10.1016/j.crm.2015.01.004
Hansen JW, Mishra A, Rao KPC, Indeje M, Ngugi RK. 2009. Potential value of GCM-based seasonal rainfall forecasts for maize management in semi-arid Kenya. Agricultural Systems. 101(1–2):80–90. https://doi.org/10.1016/j.agsy.2009.03.005
Hapinat HL, Montero ES. 2023. Development of Corn-based Farming System in Response to Climate Change. [accessed 2026 Sept 30]. https://doi.org/10.13140/RG.2.2.15308.28801
Hatfield JL, Antle J, Garrett KA, Izaurralde RC, Mader T, Marshall E, Nearing M, Philip Robertson G, Ziska L. 2020. Indicators of climate change in agricultural systems. Climatic Change. 163(4):1719–1732. https://doi.org/10.1007/s10584-018-2222-2
Hutchison W, Cira T. 2017. Economically important insect pests of maize. In: Burleigh Dodds Series in Agricultural Science. Burleigh Dodds Science Publishing. p. 263–292. [accessed 2026 Mar 11]. https://www.bdspublishing.com/webshop/chapters/crops/cereals/maize/economically-important-insect-pests-of-maize/.
Jansuwan P, Zander KK. 2021. What to do with the farmland? Coping with ageing in rural Thailand. Journal of Rural Studies. 81:37–46. https://doi.org/10.1016/j.jrurstud.2020.12.003
Jones JW, Hansen JW, Royce FS, Messina CD. 2000. Potential benefits of climate forecasting to agriculture. Agriculture, Ecosystems and Environment. 82(1–3):169–184. https://doi.org/10.1016/S0167-8809(00)00225-5
Klemm T, McPherson RA. 2017. The development of seasonal climate forecasting for agricultural producers. Agricultural and Forest Meteorology. 232:384–399. https://doi.org/10.1016/j.agrformet.2016.09.005
Lemos MC, Finan TJ, Fox RW, Nelson DR, Tucker J. 2002. The use of seasonal climate forecasting in policymaking: Lessons from Northeast Brazil. Climatic Change. 55(4):479–507. https://doi.org/10.1023/A:1020785826029
Lu H, Xue J, Guo D. 2017. Efficacy of planting date adjustment as a cultivation strategy to cope with drought stress and increase rainfed maize yield and water-use efficiency. Agricultural Water Management. 179:227–235. https://doi.org/10.1016/j.agwat.2016.09.001
Mahadevakumar S, Sridhar KR. 2021. Diversity of pathogenic fungi in agricultural crops. In: Dubey SK, Verma SK, editors. Plant, Soil and Microbes in Tropical Ecosystems. Singapore: Springer Singapore. p. 101-149. https://doi.org/10.1007/978-981-16-3364-5_6
Malhi G, Kaur M, Kaushik P. 2021. Impact of climate change on agriculture and its mitigation strategies: A Review. Sustainability. 13(3):1318. https://doi.org/10.3390/su13031318
Mayo RE, Villarta LJS. 2023. Obstacle in corn production and the livelihood activities of smallholder farmers in South Central Philippines. Open Journal of Social Sciences. 11(10):573–586. https://doi.org/10.4236/jss.2023.1110032
Nering RF, Fernandez-Cornejo J. 2005. The impacts of off-farm income on farm efficiency, scale, and profitability for corn farms. https://doi.org/10.22004/AG.ECON.1956
Osei-Kofi PS, Badu EE, Dadzie PS, Bandanaa J. 2023. Demographic characteristics of farmers and the effectiveness of disseminating information on agriculture in Ghana. Ghana Journal of Agricultural Science. 58(2):98–114. https://doi.org/10.4314/gjas.v58i2
PAGASA (Philippine Atmospheric, Geophysical and Astronomical Services Administration). 2022. Climatological Data. [accessed on 2022 Mar 15]. https://bagong.pagasa.dost.gov.ph/climate/climate-data
Pörtner H-O, Roberts DC, Tignor MMB, Poloczanska E, Mintenbeck K, Alegría A, Craig MH, Langsdorf S, Löschke S, Möller V, and others. 2023. Climate Change 2022 – Impacts, Adaptation and Vulnerability: Working Group II Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. First edition. Cambridge University Press.
PSA (Philippine Statistics Authority). 2021. 2021 Philippine Statistics Authority Annual Report. [accessed on 2021 Feb 18]. https://psa.gov.ph
Reyes CM, Gonzales KG, Predo CD, Guzman RGD. 2009. Assessing the value of seasonal climate forecasts on farm-level corn production through simulation modeling. Philippine Journal of Development. 36(1):35–63.
Rubas D, Hill H, Mjelde J. 2006. Economics and climate applications: exploring the frontier. Climate Research. 33:43–54. https://doi.org/10.3354/cr033043
Sadok W, Angevin F, Bergez J-É, Bockstaller C, Colomb B, Guichard L, Reau R, Doré T. 2008. Ex ante assessment of the sustainability of alternative cropping systems: implications for using multi-criteria decision-aid methods. A review. Agronomy for Sustainable Development. 28(1):163–174. https://doi.org/10.1051/agro:2007043
Salvacion AR, Martin AA. 2016. Climate change impact on corn suitability in Isabela province, Philippines. Journal of Crop Science and Biotechnology. 19(3):223–229. https://doi.org/10.1007/s12892-016-0019-2
Salvacion AR. 2015. Climatic change impact on corn productivity in the Philippines. International Journal of Sciences: Basic and Applied Research (IJSBAR). 23(1):54–68.
Sivakumar MVK, Hansen J. 2007. Climate prediction and agriculture: Summary and the way forward. In: Sivakumar Mannava V. K., Hansen James, editors. Climate Prediction and Agriculture: Advances and Challenges. Berlin, Heidelberg: Springer Berlin Heidelberg. p. 1–13. https://doi.org/10.1007/978-3-540-44650-7_1
Sultan B, Janicot S, Correia C. 2009. Medium lead-time predictability of intraseasonal variability of rainfall in West Africa. Weather and Forecasting. 24(3):767–784. https://doi.org/10.1175/2008WAF2222155.1
Tall A, Hansen J, Jay A, Campbell BM, Kinyangi J, Aggarwal PK, Zougmoré RB. 2014. Scaling up climate services for farmers: Mission Possible. Learning from good practice in Africa and South Asia. [accessed 2023 Dec 12]. https://ccafs.cgiar.org/resources/publications/scaling-climate-services-farmers-mission-possible-learning-good
Vermeulen SJ, Campbell BM, Ingram JSI. 2012. Climate change and food systems. Annual Review of Environment and Resources. 37(1):195–222. https://doi.org/10.1146/annurev-environ-020411-130608
Weaver CP, Lempert RJ, Brown C, Hall JA, Revell D, Sarewitz D. 2013. Improving the contribution of climate model information to decision making: the value and demands of robust decision frameworks. WIREs Climate Change. 4(1):39–60. https://doi.org/10.1002/wcc.202
Wilks DS. 1997. Forecast value: prescriptive decision studies. In: Katz RW, Murphy AH, editors. Economic Value of Weather and Climate Forecasts. 1st ed. Cambridge University Press. p. 109–146.
Yohannes H. 2016. A review on relationship between climate change and agriculture. Journal of Earth Science and Climatic Change. 07(02):335. https://doi.org/10.4172/2157-7617.1000335
Young KJ, Long SP. 2000. Crop ecosystem responses to climatic change: maize and sorghum. In: Reddy KR, Hodges HF, editors. Climate change and global crop productivity. First edition. UK: CABI Publishing. p. 107–131.
Zhao Y, Wang C, Wang S, Tibig LV. 2005. Impacts of present and future climate variability on agriculture and forestry in the humid and sub-humid tropics. Climatic Change. 70:73–116. https://doi.org/10.1007/s10584-005-5938-8
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