IDEAS home Printed from https://ideas.repec.org/a/ags/areint/355985.html
   My bibliography  Save this article

Does non-farm employment influence a farmer’s decision to adopt hybrid rice seeds or improved variety?

Author

Listed:
  • Nguyen, Hang Thi Thuy
  • Hung, Pham Xuan
  • Le, Phuong Nu Minh

Abstract

Purpose. The study aims to examine the effect of non-farm employment decisions on the adoption decision of rice hybrid seeds or improved variety in Vietnam. Methodology / approach. This study uses panel data from the Vietnam Access to Resources Household Survey (VARHS) 2008–2016 dataset. The study uses the correlated random effect Probit model with the Mundlak approach to control unobserved heterogeneity of panel data and the endogenous switching Probit model (ESPM) to solve the endogeneity problem and self-selection of the non-farm participation variable. Results. There has been increasing interest that the development of rural non-farm employment has effects on agricultural production as well as agricultural growth. However, still relatively poor understanding of how non-farm participation affects the farmers’ decision to adopt modern technologies in the face of market failure. Our findings indicate that non-farm employment has a positive effect on the adoption of rice hybrid seeds or improved varieties in Vietnam. The value ATT is predicted from the endogenous switching Probit model, which implies that farm households who engage in non-farm employment had a 35.1 % of probability of modern varieties adoption, vs. 19.0 % in the sample overall. Originality / scientific novelty. This study adds evidence from a developing country (using the example of Vietnam) to the broader literature on the role of non-farm employment participation on farmers’ adoption behaviour under market imperfections. In addition, the research addresses the limitations of unobserved heterogeneity of an unbalanced panel by applying the Mundlak approach and contributes to the literature by controlling the endogenous problem and self-selection problem of non-farm participation by using the endogenous switching Probit model. Practical value / implications. Based on the empirical results of this paper, some policy implications are provided to develop the rural non-farm sector and to diffuse modern technologies among rural farmers.

Suggested Citation

  • Nguyen, Hang Thi Thuy & Hung, Pham Xuan & Le, Phuong Nu Minh, 2024. "Does non-farm employment influence a farmer’s decision to adopt hybrid rice seeds or improved variety?," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 10(3), September.
    • Handle: RePEc:ags:areint:355985
    DOI: 10.22004/ag.econ.355985
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/355985/files/11_Nguyen_article.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.355985?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. Hailemariam Teklewold & Menale Kassie & Bekele Shiferaw, 2013. "Adoption of Multiple Sustainable Agricultural Practices in Rural Ethiopia," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(3), pages 597-623, September.
    2. Hang Thi Thuy Nguyen & Pham Xuan Hung, 2022. "Determinants of System of Rice Intensification Adoption and its Impacts on Rice Yield in the Upland Region of Central Vietnam," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society, vol. 12(4), pages 306-315.
    3. Poornima Varma, 2019. "Adoption and the impact of system of rice intensification on rice yields and household income: an analysis for India," Applied Economics, Taylor & Francis Journals, vol. 51(45), pages 4956-4972, September.
    4. Barrett, C. B. & Reardon, T. & Webb, P., 2001. "Nonfarm income diversification and household livelihood strategies in rural Africa: concepts, dynamics, and policy implications," Food Policy, Elsevier, vol. 26(4), pages 315-331, August.
    5. Di Falco, Salvatore & Feri, Francesco & Pin, Paolo & Vollenweider, Xavier, 2018. "Ties that bind: Network redistributive pressure and economic decisions in village economies," Journal of Development Economics, Elsevier, vol. 131(C), pages 123-131.
    6. Wooldridge, Jeffrey M., 2019. "Correlated random effects models with unbalanced panels," Journal of Econometrics, Elsevier, vol. 211(1), pages 137-150.
    7. Tom Hertz, 2009. "The effect of nonfarm income on investment in Bulgarian family farming," Agricultural Economics, International Association of Agricultural Economists, vol. 40(2), pages 161-176, March.
    8. Fernandez-Cornejo, Jorge & Hendricks, Chad & Mishra, Ashok K., 2005. "Technology Adoption and Off-Farm Household Income: The Case of Herbicide-Tolerant Soybeans," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 37(3), pages 1-15, December.
    9. Nguyen, Hang Thi Thuy & Hung, Pham Xuan, 2022. "Determinants of System of Rice Intensification Adoption and its Impacts on Rice Yield in the Upland Region of Central Vietnam," Asian Journal of Agriculture and Rural Development, Asian Economic and Social Society (AESS), vol. 12(04), January.
    10. Buchenrieder, Gertrud & Mollers, Judith, 2006. "A Synthesis of Theoretical Concepts for Analysing Non-Farm Rural Employment," 2006 Annual Meeting, August 12-18, 2006, Queensland, Australia 25475, International Association of Agricultural Economists.
    11. Anh, Tran Thi Tram & Epprecht, Michael & Minot, Nicholas & Trung, Le Quang, 2006. "Income diversification and poverty in the Northern Uplands of Vietnam:," Research reports 145, International Food Policy Research Institute (IFPRI).
    12. Haggblade, Steven & Hazell, Peter & Reardon, Thomas, 2010. "The Rural Non-farm Economy: Prospects for Growth and Poverty Reduction," World Development, Elsevier, vol. 38(10), pages 1429-1441, October.
    13. Langyintuo, Augustine S. & Mungoma, Catherine, 2008. "The effect of household wealth on the adoption of improved maize varieties in Zambia," Food Policy, Elsevier, vol. 33(6), pages 550-559, December.
    14. Gracious M. Diiro & Abdoul G. Sam, 2015. "Agricultural technology adoption and Nonfarm earnings in Uganda: a Semiparametric analysis," Journal of Developing Areas, Tennessee State University, College of Business, vol. 49(2), pages 145-162, April-Jun.
    15. Andrew D. Foster & Mark R. Rosenzweig, 2010. "Microeconomics of Technology Adoption," Annual Review of Economics, Annual Reviews, vol. 2(1), pages 395-424, September.
    16. Riju Joshi & Jeffrey M. Wooldridge, 2019. "Correlated Random Effects Models with Endogenous Explanatory Variables and Unbalanced Panels," Annals of Economics and Statistics, GENES, issue 134, pages 243-268.
    17. Davis, Benjamin & Winters, Paul & Carletto, Gero & Covarrubias, Katia & Quiñones, Esteban J. & Zezza, Alberto & Stamoulis, Kostas & Azzarri, Carlo & DiGiuseppe, Stefania, 2010. "A Cross-Country Comparison of Rural Income Generating Activities," World Development, Elsevier, vol. 38(1), pages 48-63, January.
    18. Zhang, Yingnan & Long, Hualou & Li, Yurui & Ge, Dazhuan & Tu, Shuangshuang, 2020. "How does off-farm work affect chemical fertilizer application? Evidence from China’s mountainous and plain areas," Land Use Policy, Elsevier, vol. 99(C).
    19. Asfaw, Solomon & Shiferaw, Bekele & Simtowe, Franklin & Lipper, Leslie, 2012. "Impact of modern agricultural technologies on smallholder welfare: Evidence from Tanzania and Ethiopia," Food Policy, Elsevier, vol. 37(3), pages 283-295.
    20. Huffman, Wallace E., 1991. "Agricultural Household Models: Survey and Critique," Staff General Research Papers Archive 11008, Iowa State University, Department of Economics.
    21. Mulubrhan Amare & Bekele Shiferaw, 2017. "Nonfarm employment, agricultural intensification, and productivity change: empirical findings from Uganda," Agricultural Economics, International Association of Agricultural Economists, vol. 48(S1), pages 59-72, November.
    22. Michael Lokshin & Zurab Sajaia, 2011. "Impact of interventions on discrete outcomes: Maximum likelihood estimation of the binary choice models with binary endogenous regressors," Stata Journal, StataCorp LLC, vol. 11(3), pages 368-385, September.
    23. Bekele Shiferaw & Tewodros Kebede & Menale Kassie & Monica Fisher, 2015. "Market imperfections, access to information and technology adoption in Uganda: challenges of overcoming multiple constraints," Agricultural Economics, International Association of Agricultural Economists, vol. 46(4), pages 475-488, July.
    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. Kazushi Takahashi & Rie Muraoka & Keijiro Otsuka, 2020. "Technology adoption, impact, and extension in developing countries’ agriculture: A review of the recent literature," Agricultural Economics, International Association of Agricultural Economists, vol. 51(1), pages 31-45, January.
    2. Diarra, Lacina, 2020. "Rural off-farm employment and agricultural production efficiency: evidence from Tazania," 2020 Annual Meeting, July 26-28, Kansas City, Missouri 304600, Agricultural and Applied Economics Association.
    3. Zeeshan & Geetilaxmi Mohapatra & Arun Kumar Giri, 2022. "How Farm Household Spends Their Non-farm Incomes in Rural India? Evidence from Longitudinal Data," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(4), pages 1967-1996, August.
    4. Aseres Mamo Eshetie & Eunice Matafwali & Gershom Endelani Mwalupaso & Jie Li & Aijun Liu, 2022. "Nexus of Cash Crop Production Using Improved Varieties and Household Food Security," The European Journal of Development Research, Palgrave Macmillan;European Association of Development Research and Training Institutes (EADI), vol. 34(4), pages 1803-1830, August.
    5. Aslihan Arslan & Kristin Floress & Christine Lamanna & Leslie Lipper & Solomon Asfaw & Todd Rosenstock, 2020. "IFAD RESEARCH SERIES 63 - The adoption of improved agricultural technologies - A meta-analysis for Africa," IFAD Research Series 304758, International Fund for Agricultural Development (IFAD).
    6. Beatrice W. Muriithi & Kassie Menale & Gracious M. Diiro & Michael N. Okal & Daniel K. Masiga, 2023. "Effect of use of tsetse repellant collar technology on the farm performance and household welfare of small-scale livestock farmers in Kenya," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 15(3), pages 751-770, June.
    7. Khushbu Mishra & Abdoul G. Sam & Gracious M. Diiro & Mario J. Miranda, 2020. "Gender and the dynamics of technology adoption: Empirical evidence from a household‐level panel data," Agricultural Economics, International Association of Agricultural Economists, vol. 51(6), pages 857-870, November.
    8. Raju Ghimire & Wen-Chi Huang, 2016. "Adoption Pattern and Welfare Impact of Agricultural Technology," Journal of South Asian Development, , vol. 11(1), pages 113-137, April.
    9. Varma, Poornima, 2016. "Agricultural Technology Adoption under Multiple Constraints: An Analysis of System of Rice Intensification (SRI) in India," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235806, Agricultural and Applied Economics Association.
    10. Murray, Anthony G & Mills, Bradford F, 2014. "Estimating the Resiliency of Zambian Smallholder Farmers: Evidence from a Three-Wave Panel," 2014 Annual Meeting, July 27-29, 2014, Minneapolis, Minnesota 170234, Agricultural and Applied Economics Association.
    11. Adere, Tilahun Habtamu & Mertens, Kewan & Maertens, Miet & Vranken, Liesbet, 2022. "The impact of land certification and risk preferences on investment in soil and water conservation: Evidence from southern Ethiopia," Land Use Policy, Elsevier, vol. 123(C).
    12. Ahmed, Mansur & Goodwin, Barry, "undated". "Agricultural Mechanization and Non-Farm Labor Supply of Farm Households: Evidence from Bangladesh," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 236131, Agricultural and Applied Economics Association.
    13. Varma, Poornima, 2017. "Adoption of System of Rice Intensification and its Impact on Rice Yields and Household Income: An Analysis for India," IIMA Working Papers WP2017-02-03, Indian Institute of Management Ahmedabad, Research and Publication Department.
    14. B.W., Muriithi & K., Menale & G., Diiro & M.O., Nyanganga & D., Masiga, 2021. "Micro-Economic Impact of Tsetse and Trypanosomiasis Control Interventions on Farmers’ Livelihoods in Kwale County, Kenya," 2021 Conference, August 17-31, 2021, Virtual 315235, International Association of Agricultural Economists.
    15. Laura Barasa & Bethuel K. Kinuthia & Abdelkrim Araar & Stephene Maende & Faith Mariera, 2023. "Nonfarm entrepreneurship, crop output, and household welfare in Tanzania: An exploration of transmission channels," Agribusiness, John Wiley & Sons, Ltd., vol. 39(3), pages 762-792, July.
    16. Antonelli, Chiara & Coromaldi, Manuela & Pallante, Giacomo, 2022. "Crop and income diversification for rural adaptation: Insights from Ugandan panel data," Ecological Economics, Elsevier, vol. 195(C).
    17. VAN DEN BROECK, Goedele & MAERTENS, Miet, 2016. "Moving Up or Moving Out? Insights on Rural Development and Poverty Reduction in Senegal," Working Papers 242367, Katholieke Universiteit Leuven, Centre for Agricultural and Food Economics.
    18. Mark Musumba & Cheryl A. Palm & Adam M. Komarek & Patrick K. Mutuo & Bocary Kaya, 2022. "Household livelihood diversification in rural Africa," Agricultural Economics, International Association of Agricultural Economists, vol. 53(2), pages 246-256, March.
    19. Varma, P., 2018. "Adoption and the Impact of System of Rice Intensification on Rice Yields and Household Income: A study for India," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 275986, International Association of Agricultural Economists.
    20. Pace, Noemi & Sebastian, Ashwini & Daidone, Silvio & Dela O Campos, Ana Paula & Prifti, Ervin & Davis, Benjamin, 2022. "Cash transfers’ role in improving livelihood diversification strategies and well-being: short- and medium-term evidence from Zimbabwe," World Development, Elsevier, vol. 154(C).

    More about this item

    Keywords

    ;
    ;

    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:ags:areint:355985. 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: http://are-journal.com/are .

    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.