IDEAS home Printed from https://ideas.repec.org/a/taf/ragrxx/v56y2017i3p296-311.html
   My bibliography  Save this article

Estimating the impact of sericulture adoption on farmer income in Rwanda: an application of propensity score matching

Author

Listed:
  • Alexis Habiyaremye

Abstract

The adoption of an agricultural technology is often seen as a way to overcome the constraints imposed by the existing resources and/or production methods. As a small landlocked country, Rwanda sought to develop the capability to produce silk, a high value-to-volume ratio product, as a means to overcome the constraints of high transportation cost of exports. Sericulture was also seen as a handy strategy to boost rural farmer income by putting previously less productive land to use for mulberry plantations. Because sericulture was not introduced randomly, this study relied on observational data and applied propensity score matching to estimate its income and poverty reduction effects in six rural districts. The results indicate that sericulture adoption had beneficial effects both on increasing income and reducing poverty. The strengthening of related skills development and the supporting infrastructure remains crucial for the sericulture to successfully diffuse and yield economic benefits commensurate with its potential.

Suggested Citation

  • Alexis Habiyaremye, 2017. "Estimating the impact of sericulture adoption on farmer income in Rwanda: an application of propensity score matching," Agrekon, Taylor & Francis Journals, vol. 56(3), pages 296-311, July.
    • Handle: RePEc:taf:ragrxx:v:56:y:2017:i:3:p:296-311
    DOI: 10.1080/03031853.2017.1361853
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03031853.2017.1361853
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03031853.2017.1361853?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Lori Beaman & Ariel BenYishay & Jeremy Magruder & Ahmed Mushfiq Mobarak, 2021. "Can Network Theory-Based Targeting Increase Technology Adoption?," American Economic Review, American Economic Association, vol. 111(6), pages 1918-1943, June.
    2. 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.
    3. James Heckman & Salvador Navarro-Lozano, 2004. "Using Matching, Instrumental Variables, and Control Functions to Estimate Economic Choice Models," The Review of Economics and Statistics, MIT Press, vol. 86(1), pages 30-57, February.
    4. Al Raee, Mueid & Ritzen, Jo & Crombrugghe, Denis de, 2017. "Innovation policy & labour productivity growth: Education, research & development, government effectiveness and business policy," MERIT Working Papers 2017-019, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Khondoker A. Mottaleb & Roderick M. Rejesus & MVR Murty & Samarendu Mohanty & Tao Li, 2017. "Benefits of the development and dissemination of climate-smart rice: ex ante impact assessment of drought-tolerant rice in South Asia," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 22(6), pages 879-901, August.
    6. 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.
    7. Luc L. G. Soete & Bart Verspagen & Thomas H. W. Ziesemer, 2020. "The productivity effect of public R&D in the Netherlands," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 29(1), pages 31-47, January.
    8. Paul Winters & Alain De Janvry & Elisabeth Sadoulet & Kostas Stamoulis, 1998. "The role of agriculture in economic development: Visible and invisible surplus transfers," Journal of Development Studies, Taylor & Francis Journals, vol. 34(5), pages 71-97.
    9. James J. Heckman & Hidehiko Ichimura & Petra E. Todd, 1997. "Matching As An Econometric Evaluation Estimator: Evidence from Evaluating a Job Training Programme," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 64(4), pages 605-654.
    10. Kiyokawa, Yukihiko, 1984. "The Diffusion of New Technologies in the Japanese Sericulture Industry : The Case of the Hybrid Silkworm," Hitotsubashi Journal of Economics, Hitotsubashi University, vol. 25(1), pages 31-59, June.
    11. Xavier Irz & Lin Lin & Colin Thirtle & Steve Wiggins, 2001. "Agricultural Productivity Growth and Poverty Alleviation," Development Policy Review, Overseas Development Institute, vol. 19(4), pages 449-466, December.
    12. Ramani, Shyama V., 2017. "Role of WASH and Agency in Health: A study of isolated rural communities in Nilgiris and Jalpaiguri," MERIT Working Papers 2017-020, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    13. 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.
    14. Rosenberg, Nathan, 1972. "Factors affecting the diffusion of technology," Explorations in Economic History, Elsevier, vol. 10(1), pages 3-33.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Gamel Abdul-Nasser Salifu, 2019. "The Political Economy Dynamics of Rural Household Income Diversification: A Review of the International Literature," Research in World Economy, Research in World Economy, Sciedu Press, vol. 10(3), pages 273-290, December.
    2. Yuan Li Liu & Kai Zhu & Qi Yao Chen & Jing Li & Jin Cai & Tian He & He Ping Liao, 2021. "Impact of the COVID-19 Pandemic on Farm Households’ Vulnerability to Multidimensional Poverty in Rural China," Sustainability, MDPI, vol. 13(4), pages 1-16, February.
    3. Abrham Belay & Alisher Mirzabaev & John W. Recha & Christopher Oludhe & Philip M. Osano & Zerihun Berhane & Lydia A. Olaka & Yitagesu T. Tegegne & Teferi Demissie & Chrispinus Mutsami & Dawit Solomon, 2024. "Does climate-smart agriculture improve household income and food security? Evidence from Southern Ethiopia," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(7), pages 16711-16738, July.
    4. Sankhulani, Linda, 2021. "Impact evaluation of conservation agriculture on smallholder farmers’ livelihood in Zambia and Tanzania," Research Theses 334762, Collaborative Masters Program in Agricultural and Applied Economics.

    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. Bola Awotide & Arega Alene & Tahirou Abdoulaye & Victor Manyong, 2015. "Impact of agricultural technology adoption on asset ownership: the case of improved cassava varieties in Nigeria," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 7(6), pages 1239-1258, December.
    2. 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.
    3. 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.
    4. Deschamps-Laporte, Jean-Philippe, 2013. "The impact of extension services on farming households in Western Kenya: A propensity score approach," Working Papers 2013:5, Örebro University, School of Business, revised 10 Jun 2013.
    5. 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.
    6. Siddique Abu Bakkar, 2020. "Identity-based Earning Discrimination among Chinese People," IZA Journal of Development and Migration, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 11(1), pages 1-42, January.
    7. 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.
    8. Mariapia MENDOLA, 2005. "Agricultural technology and poverty reduction: a micro-level analysis of causal effects," Departmental Working Papers 2005-14, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    9. repec:ags:bdbjaf:279932 is not listed on IDEAS
    10. 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.
    11. Baiyegunhi, L.J.S. & Majokweni, Z.P. & Ferrer, S.R.D., 2019. "Impact of outsourced agricultural extension program on smallholder farmers’ net farm income in Msinga, KwaZulu-Natal, South Africa," Technology in Society, Elsevier, vol. 57(C), pages 1-7.
    12. Gensler, Sonja & Leeflang, Peter & Skiera, Bernd, 2012. "Impact of online channel use on customer revenues and costs to serve: Considering product portfolios and self-selection," International Journal of Research in Marketing, Elsevier, vol. 29(2), pages 192-201.
    13. Jasmin Kantarevic & Boris Kralj, 2013. "Link Between Pay For Performance Incentives And Physician Payment Mechanisms: Evidence From The Diabetes Management Incentive In Ontario," Health Economics, John Wiley & Sons, Ltd., vol. 22(12), pages 1417-1439, December.
    14. Dan Pan, 2014. "The Impact of Agricultural Extension on Farmer Nutrient Management Behavior in Chinese Rice Production: A Household-Level Analysis," Sustainability, MDPI, vol. 6(10), pages 1-22, September.
    15. Guido W. Imbens & Jeffrey M. Wooldridge, 2009. "Recent Developments in the Econometrics of Program Evaluation," Journal of Economic Literature, American Economic Association, vol. 47(1), pages 5-86, March.
    16. Richard Blundell & Monica Costa Dias, 2009. "Alternative Approaches to Evaluation in Empirical Microeconomics," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    17. Abebaw, Degnet & Haile, Mekbib G., 2013. "The impact of cooperatives on agricultural technology adoption: Empirical evidence from Ethiopia," Food Policy, Elsevier, vol. 38(C), pages 82-91.
    18. John C. Ham & Xianghong Li & Patricia B. Reagan, 2004. "Propensity Score Matching, a Distance-Based Measure of Migration, and the Wage Growth of Young Men," Working Papers 2004_3, York University, Department of Economics.
    19. Menale Kassie & Gunnar Köhlin & Randy Bluffstone & Stein Holden, 2011. "Are soil conservation technologies “win‐win?” A case study of Anjeni in the north‐western Ethiopian highlands," Natural Resources Forum, Blackwell Publishing, vol. 35(2), pages 89-99, May.
    20. Lechner, Michael & Wunsch, Conny, 2013. "Sensitivity of matching-based program evaluations to the availability of control variables," Labour Economics, Elsevier, vol. 21(C), pages 111-121.
    21. Markus Gangl & Thomas A. DiPrete, 2004. "Kausalanalyse durch Matchingverfahren," Discussion Papers of DIW Berlin 401, DIW Berlin, German Institute for Economic Research.

    More about this item

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

    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:taf:ragrxx:v:56:y:2017:i:3:p:296-311. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/ragr20 .

    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.