IDEAS home Printed from https://ideas.repec.org/p/col/000089/015665.html
   My bibliography  Save this paper

Cambio tecnológico y mejoras en el bienestar de los caficultores en Colombia: el caso de las variedades resistentes a la roya

Author

Listed:
  • Jorge Leonardo Rueda Gil

Abstract

Este artículo determina el impacto de la adopción de las variedades resistentes a la roya del cafeto en el bienestar del productor de café, medido por medio del índice SISBEN III y los ingresos brutos por hectárea. Se utilizan datos de corte transversal de 76.902 caficultores distribuidos en 21 departamentos de Colombia para 2014. Por medio de la metodología Propensity Score Matching, se encuentra que la adopción de variedades resistentes a la roya incrementa la productividad por hectárea al ano entre 29,5% y 34,9% (según el algoritmo de emparejamiento utilizado), lo que a su vez mejora entre 31,9% y 37,6% los ingresos brutos por hectárea al ano y el puntaje SISBEN III entre 3,4% y 5,0%. Estos impactos son mayores para los productores con fincas más pequenas y aquellos con altos niveles de educación. Los resultados son robustos a diferentes especificaciones del propensity score.

Suggested Citation

  • Jorge Leonardo Rueda Gil, 2017. "Cambio tecnológico y mejoras en el bienestar de los caficultores en Colombia: el caso de las variedades resistentes a la roya," Documentos CEDE 15665, Universidad de los Andes, Facultad de Economía, CEDE.
    • Handle: RePEc:col:000089:015665
    as

    Download full text from publisher

    File URL: https://repositorio.uniandes.edu.co/bitstream/handle/1992/8733/dcede2017-44.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. A. Smith, Jeffrey & E. Todd, Petra, 2005. "Does matching overcome LaLonde's critique of nonexperimental estimators?," Journal of Econometrics, Elsevier, vol. 125(1-2), pages 305-353.
    2. Jalan, Jyotsna & Ravallion, Martin, 2003. "Does piped water reduce diarrhea for children in rural India?," Journal of Econometrics, Elsevier, vol. 112(1), pages 153-173, January.
    3. Marco Caliendo & Sabine Kopeinig, 2008. "Some Practical Guidance For The Implementation Of Propensity Score Matching," Journal of Economic Surveys, Wiley Blackwell, vol. 22(1), pages 31-72, February.
    4. Feder, Gershon & Just, Richard E & Zilberman, David, 1985. "Adoption of Agricultural Innovations in Developing Countries: A Survey," Economic Development and Cultural Change, University of Chicago Press, vol. 33(2), pages 255-298, January.
    5. Mendola, Mariapia, 2007. "Agricultural technology adoption and poverty reduction: A propensity-score matching analysis for rural Bangladesh," Food Policy, Elsevier, vol. 32(3), pages 372-393, June.
    6. A. de Janvry & E. Sadoulet, 2002. "World Poverty and the Role of Agricultural Technology: Direct and Indirect Effects," Journal of Development Studies, Taylor & Francis Journals, vol. 38(4), pages 1-26.
    7. John Herbert Ainembabazi & Johnny Mugisha, 2014. "The Role of Farming Experience on the Adoption of Agricultural Technologies: Evidence from Smallholder Farmers in Uganda," Journal of Development Studies, Taylor & Francis Journals, vol. 50(5), pages 666-679, May.
    8. DiPrete, Thomas A. & Gangl, Markus, 2004. "Assessing bias in the estimation of causal effects: Rosenbaum bounds on matching estimators and instrumental variables estimation with imperfect instruments," Discussion Papers, Research Unit: Labor Market Policy and Employment SP I 2004-101, WZB Berlin Social Science Center.
    9. Shiferaw, Bekele & Kassie, Menale & Jaleta, Moti & Yirga, Chilot, 2014. "Adoption of improved wheat varieties and impacts on household food security in Ethiopia," Food Policy, Elsevier, vol. 44(C), pages 272-284.
    10. Kassie, Menale & Shiferaw, Bekele & Muricho, Geoffrey, 2011. "Agricultural Technology, Crop Income, and Poverty Alleviation in Uganda," World Development, Elsevier, vol. 39(10), pages 1784-1795.
    11. Melinda Smale & Richard E. Just & Howard D. Leathers, 1994. "Land Allocation in HYV Adoption Models: An Investigation of Alternative Explanations," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 76(3), pages 535-546.
    12. Khonje, Makaiko & Manda, Julius & Alene, Arega D. & Kassie, Menale, 2015. "Analysis of Adoption and Impacts of Improved Maize Varieties in Eastern Zambia," World Development, Elsevier, vol. 66(C), pages 695-706.
    13. Karanja, D. D. & Renkow, M. & Crawford, E. W., 2003. "Welfare effects of maize technologies in marginal and high potential regions of Kenya," Agricultural Economics, Blackwell, vol. 29(3), pages 331-341, December.
    14. Mahabub HOSSAIN & Manik L. BOSE & Bazlul A. A. MUSTAFI, 2006. "Adoption And Productivity Impact Of Modern Rice Varieties In Bangladesh," The Developing Economies, Institute of Developing Economies, vol. 44(2), pages 149-166, June.
    15. Akhter Ali & Awudu Abdulai, 2010. "The Adoption of Genetically Modified Cotton and Poverty Reduction in Pakistan," Journal of Agricultural Economics, Wiley Blackwell, vol. 61(1), pages 175-192, February.
    16. Shahidur R. Khandker & Gayatri B. Koolwal & Hussain A. Samad, . "Handbook on Impact Evaluation : Quantitative Methods and Practices," World Bank Publications, The World Bank, number 2693, September.
    17. Becerril, Javier & Abdulai, Awudu, 2010. "The Impact of Improved Maize Varieties on Poverty in Mexico: A Propensity Score-Matching Approach," World Development, Elsevier, vol. 38(7), pages 1024-1035, July.
    18. James Heckman & Hidehiko Ichimura & Jeffrey Smith & Petra Todd, 1998. "Characterizing Selection Bias Using Experimental Data," Econometrica, Econometric Society, vol. 66(5), pages 1017-1098, September.
    19. Haitao Wu & Shijun Ding & Sushil Pandey & Dayun Tao, 2010. "Assessing the Impact of Agricultural Technology Adoption on Farmers' Well‐being Using Propensity‐Score Matching Analysis in Rural China," Asian Economic Journal, East Asian Economic Association, vol. 24(2), pages 141-160, June.
    20. Minten, Bart & Barrett, Christopher B., 2008. "Agricultural Technology, Productivity, and Poverty in Madagascar," World Development, Elsevier, vol. 36(5), pages 797-822, May.
    21. Jonathan Haughton & Shahidur R. Khandker, 2009. "Handbook on Poverty and Inequality," World Bank Publications - Books, The World Bank Group, number 11985.
    22. Ingrid Rhinehart & C. Michael Deom, 2007. "Peanut Research and Poverty Reduction: Impacts of Variety Improvement to Control Peanut Viruses in Uganda," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 89(2), pages 448-460.
    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. Kassie, Menale & Shiferaw, Bekele & Muricho, Geoffrey, 2011. "Agricultural Technology, Crop Income, and Poverty Alleviation in Uganda," World Development, Elsevier, vol. 39(10), pages 1784-1795.
    2. Alexandra Peralta & Scott M. Swinton & Songqing Jin, 2018. "The Secret to Getting Ahead Is Getting Started: Early Impacts of a Rural Development Project," Sustainability, MDPI, vol. 10(8), pages 1-20, July.
    3. Emiliano Magrini & Mauro Vigani, 2016. "Technology adoption and the multiple dimensions of food security: the case of maize in Tanzania," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 8(4), pages 707-726, August.
    4. Becerril, Javier & Abdulai, Awudu, 2010. "The Impact of Improved Maize Varieties on Poverty in Mexico: A Propensity Score-Matching Approach," World Development, Elsevier, vol. 38(7), pages 1024-1035, July.
    5. Santosh K. Sahu & Sukanya Das, 2016. "Impact of Agricultural Related Technology Adoption on Poverty: A Study of Select Households in Rural India," India Studies in Business and Economics, in: N.S. Siddharthan & K. Narayanan (ed.), Technology, pages 141-156, Springer.
    6. Backson Mwangi & Ibrahim Macharia & Eric Bett, 2021. "Ex-post Impact Evaluation of Improved Sorghum Varieties on Poverty Reduction in Kenya: A Counterfactual Analysis," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 154(2), pages 447-467, April.
    7. Paudel, G. & Krishna, V. & McDonald, A., 2018. "Why some inferior technologies succeed? Examining the diffusion and impacts of rotavator tillage in Nepal Terai," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277149, International Association of Agricultural Economists.
    8. Manda, Julius & Alene, Arega D. & Tufa, Adane H. & Abdoulaye, Tahirou & Wossen, Tesfamicheal & Chikoye, David & Manyong, Victor, 2019. "The poverty impacts of improved cowpea varieties in Nigeria: A counterfactual analysis," World Development, Elsevier, vol. 122(C), pages 261-271.
    9. Islam, Abu Hayat, 2015. "Can Integrated Rice-Fish System Increase Welfare of the Marginalized Extreme Poor in Bangladesh? A DID Matching Approach," 2015 Conference, August 9-14, 2015, Milan, Italy 211792, International Association of Agricultural Economists.
    10. repec:lic:licosd:35214 is not listed on IDEAS
    11. Mishra, Ashok K. & Kumar, Anjani & Joshi, Pramod K. & D'souza, Alwin, 2016. "Impact of contracts in high yielding varieties seed production on profits and yield: The case of Nepal," Food Policy, Elsevier, vol. 62(C), pages 110-121.
    12. Khonje, Makaiko & Mkandawire, Petros & Manda, Julius & Alene, Arega, 2015. "Analysis of adoption and impacts of improved cassava varieties," 2015 Conference, August 9-14, 2015, Milan, Italy 211842, International Association of Agricultural Economists.
    13. repec:ags:bdbjaf:279932 is not listed on IDEAS
    14. Abdoulaye Diagne Author-Name: Fran ois J. Cabral, 2017. "Agricultural Transformation in Senegal: Impacts of an integrated program," Working Papers PMMA 2017-09, PEP-PMMA.
    15. Abebayehu Girma Geffersa & Frank W. Agbola & Amir Mahmood, 2022. "Improved maize adoption and impacts on farm household welfare: Evidence from rural Ethiopia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 66(4), pages 860-886, October.
    16. Garbero, A. & Marion, P., 2018. "IFAD RESEARCH SERIES 28 - Understanding the dynamics of adoption decisions and their poverty impacts: the case of improved maize seeds in Uganda," IFAD Research Series 280077, International Fund for Agricultural Development (IFAD).
    17. Duong, Pham Bao & Thanh, Pham Tien, 2019. "Adoption and effects of modern rice varieties in Vietnam: Micro-econometric analysis of household surveys," Economic Analysis and Policy, Elsevier, vol. 64(C), pages 282-292.
    18. Ainembabazi, John Herbert & Abdoulaye, Tahirou & Feleke, Shiferaw & Alene, Arega & Dontsop-Nguezet, Paul M. & Ndayisaba, Pierre Celestin & Hicintuka, Cyrille & Mapatano, Sylvain & Manyong, Victor, 2018. "Who benefits from which agricultural research-for-development technologies? Evidence from farm household poverty analysis in Central Africa," World Development, Elsevier, vol. 108(C), pages 28-46.
    19. Ali, Akhter & Hussain, Imtiaz & Rahut, Dil Bahadur & Erenstein, Olaf, 2018. "Laser-land leveling adoption and its impact on water use, crop yields and household income: Empirical evidence from the rice-wheat system of Pakistan Punjab," Food Policy, Elsevier, vol. 77(C), pages 19-32.
    20. Ashimwe, Olive, 2016. "An Economic Analysis Of Impact Of Weather Index-Based Crop Insurance On Household Income In Huye District Of Rwanda," Research Theses 265675, Collaborative Masters Program in Agricultural and Applied Economics.
    21. Musa Hasen Ahmed & Kassahun Mamo Geleta & Aemro Tazeze & Hiwot Mekonnen Mesfin & Eden Andualem Tilahun, 2017. "Cropping systems diversification, improved seed, manure and inorganic fertilizer adoption by maize producers of eastern Ethiopia," Journal of Economic Structures, Springer;Pan-Pacific Association of Input-Output Studies (PAPAIOS), vol. 6(1), pages 1-16, December.
    22. Bairagi, Subir & Bhandari, Humnath & Kumar Das, Subrata & Mohanty, Samarendu, 2021. "Flood-tolerant rice improves climate resilience, profitability, and household consumption in Bangladesh," Food Policy, Elsevier, vol. 105(C).

    More about this item

    Keywords

    Colombia; café; bienestar del productor; variedades resistentes; evaluación de impacto.;
    All these keywords.

    JEL classification:

    • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes
    • I31 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - General Welfare, Well-Being

    Statistics

    Access and download statistics

    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:col:000089:015665. 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: Universidad De Los Andes-Cede (email available below). General contact details of provider: https://edirc.repec.org/data/ceandco.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.