IDEAS home Printed from https://ideas.repec.org/p/ags/iaae12/126363.html
   My bibliography  Save this paper

Which Farmers Benefit the Most from Bt Corn Adoption in the Philippines? Estimating Heterogeneity Effects

Author

Listed:
  • Mutuc, Maria Erlinda M.
  • Rejesus, Roderick M.
  • Yorobe, Jose M., Jr.

Abstract

The potential contributions of new biotechnologies to sustainable food and income security have been the subject of widespread discussions around the turn of the twenty-first century. But distributional issues of which segments of GMO adopters benefit the most have not been given ample attention. Using propensity scores, we apply the (a) stratification-multilevel method of estimating heterogeneous treatment effects (SM-HTE); and the (b) matching-smoothing method of estimating heterogeneous treatment effects (MS-HTE) proposed by Xi, Brand, and Jann (2011). We find that the incidence of higher yields, lower insecticide use and reduced seed utilization in the Philippines diminishes progressively as a farmer’s propensity to adopt Bt corn increases. Farmers with a low propensity to adopt Bt are those who farm smaller, non-irrigated farms located farther from seed suppliers and farmers without previous training on pest identification. In most cases, while these farmers are typically poorer farmers in smaller parcels, cannot afford irrigation and are situated in remote areas away from easily accessible seed suppliers, there is no evidence, however, that profits differ across farmers with varying propensities to adopt the Bt variety.

Suggested Citation

  • Mutuc, Maria Erlinda M. & Rejesus, Roderick M. & Yorobe, Jose M., Jr., 2012. "Which Farmers Benefit the Most from Bt Corn Adoption in the Philippines? Estimating Heterogeneity Effects," 2012 Conference, August 18-24, 2012, Foz do Iguacu, Brazil 126363, International Association of Agricultural Economists.
  • Handle: RePEc:ags:iaae12:126363
    DOI: 10.22004/ag.econ.126363
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/126363/files/IAAE_Bt_Corn_Het.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.126363?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Gerpacio, Roberta V. & Labios, Jocelyn D. & Labios, Romeo V. & Diangkinay, Emma I., 2004. "Maize in the Philippines: Production Systems, Constraints, and Research Priorities," Maize Production Systems Papers 7650, CIMMYT: International Maize and Wheat Improvement Center.
    2. Ben Jann, 2010. "Heterogeneous treatment-effect analysis," German Stata Users' Group Meetings 2010 03, Stata Users Group.
    3. Imbens, Guido W & Angrist, Joshua D, 1994. "Identification and Estimation of Local Average Treatment Effects," Econometrica, Econometric Society, vol. 62(2), pages 467-475, March.
    4. Mendoza, Meyra Sebello & Rosegrant, Mark W., 1995. "Pricing behavior in Philippine corn markets: implications for market efficiency," Research reports 101, International Food Policy Research Institute (IFPRI).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sanglestsawai, Santi & Rejesus, Roderick M. & Yorobe, Jose M., 2014. "Do lower yielding farmers benefit from Bt corn? Evidence from instrumental variable quantile regressions," Food Policy, Elsevier, vol. 44(C), pages 285-296.
    2. Harold Alderman & John Hoddinott & Bill Kinsey, 2006. "Long term consequences of early childhood malnutrition," Oxford Economic Papers, Oxford University Press, vol. 58(3), pages 450-474, July.
    3. Elias Einiö & Henry G. Overman, 2016. "The (Displacement) Effects of Spatially Targeted Enterprise Initiatives: Evidence from UK LEGI," SERC Discussion Papers 0191, Centre for Economic Performance, LSE.
    4. Domenico Depalo, 2020. "Explaining the causal effect of adherence to medication on cholesterol through the marginal patient," Health Economics, John Wiley & Sons, Ltd., vol. 29(S1), pages 110-126, October.
    5. S Anukriti & Catalina Herrera‐Almanza & Praveen K. Pathak & Mahesh Karra, 2020. "Curse of the Mummy‐ji: The Influence of Mothers‐in‐Law on Women in India†," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(5), pages 1328-1351, October.
    6. Arnaud Chevalier & Colm Harmon & Vincent O’ Sullivan & Ian Walker, 2013. "The impact of parental income and education on the schooling of their children," IZA Journal of Labor Economics, Springer;Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 2(1), pages 1-22, December.
    7. Tjaden, Jasper & Dunsch, Felipe Alexander, 2021. "The effect of peer-to-peer risk information on potential migrants – Evidence from a randomized controlled trial in Senegal," World Development, Elsevier, vol. 145(C).
    8. Doyle, Joseph J., 2013. "Causal effects of foster care: An instrumental-variables approach," Children and Youth Services Review, Elsevier, vol. 35(7), pages 1143-1151.
    9. Timothy Tyler Brown & Erin Dela Cruz & Stephen Scott Brown, 2011. "The effect of dental care on cardiovascular disease outcomes: an application of instrumental variables in the presence of heterogeneity and self‐selection," Health Economics, John Wiley & Sons, Ltd., vol. 20(10), pages 1241-1256, October.
    10. Yoichi Arai & Yu‐Chin Hsu & Toru Kitagawa & Ismael Mourifié & Yuanyuan Wan, 2022. "Testing identifying assumptions in fuzzy regression discontinuity designs," Quantitative Economics, Econometric Society, vol. 13(1), pages 1-28, January.
    11. González-Uribe, Juanita & Reyes, Santiago, 2021. "Identifying and boosting “Gazelles”: Evidence from business accelerators," Journal of Financial Economics, Elsevier, vol. 139(1), pages 260-287.
    12. Mutuc, Maria Erlinda M. & Rejesus, Roderick M. & Pan, Suwen & Yorobe, Jose M., 2012. "Impact Assessment of Bt Corn Adoption in the Philippines," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 44(1), pages 117-135, February.
    13. Roxana Elena Manea, 2021. "School Feeding Programmes, Education and Food Security in Rural Malawi," CIES Research Paper series 63-2020, Centre for International Environmental Studies, The Graduate Institute.
    14. Heinesen, Eskil & Hvid, Christian & Kirkebøen, Lars & Leuven, Edwin & Mogstad, Magne, 2022. "Instrumental variables with unordered treatments: Theory and evidence from returns to fields of study," Memorandum 3/2022, Oslo University, Department of Economics.
    15. Clément de Chaisemartin & Luc Behaghel, 2020. "Estimating the Effect of Treatments Allocated by Randomized Waiting Lists," Econometrica, Econometric Society, vol. 88(4), pages 1453-1477, July.
    16. Giacomo De Giorgi & Michele Pellizzari & William Gui Woolston, 2012. "Class Size And Class Heterogeneity," Journal of the European Economic Association, European Economic Association, vol. 10(4), pages 795-830, August.
    17. David Card, 2022. "Design-Based Research in Empirical Microeconomics," American Economic Review, American Economic Association, vol. 112(6), pages 1773-1781, June.
    18. Nguezet, Paul Martin Dontsop & Diagne, Aliou & Okoruwa, Victor Olusegun & Ojehomon, Vivian, 2011. "Impact of Improved Rice Technology (NERICA varieties) on Income and Poverty among Rice Farming Households in Nigeria: A Local Average Treatment Effect (LATE) Approach," Quarterly Journal of International Agriculture, Humboldt-Universitaat zu Berlin, vol. 50(3), pages 1-25.
    19. Jeffrey S. DeSimone, 2008. "The Impact of Employment during School on College Student Academic Performance," NBER Working Papers 14006, National Bureau of Economic Research, Inc.
    20. Jeffrey Smith, 2000. "A Critical Survey of Empirical Methods for Evaluating Active Labor Market Policies," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 136(III), pages 247-268, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:iaae12:126363. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/iaaeeea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.