IDEAS home Printed from https://ideas.repec.org/p/ags/gewi21/317074.html
   My bibliography  Save this paper

Farmers’ willingness to pay for digital and conventional credit: Evidence from a discrete choice experiment in Madagascar

Author

Listed:
  • Sarfo, Yaw
  • Musshoff, Oliver
  • Weber, Ron
  • Danne, Michael

Abstract

In recent decades, microfinance institutions (MFIs) with financial products designed for low income groups have been established all over the world. However, credit access for farmers in developing countries remains low. Digital financial services are rapidly expanding globally at the moment. They also bear great potential to address farmers in remote rural areas. Beyond mobile money services, digital credit is successively offered and also discussed in literature. Compared to conventional credit which is granted based on a thorough assessment of the loan applicant’s financial situation, digital credit is granted based on an automated analysis of the existing data of the loan applicant. However, empirical research on farmers’ preferences and willingness to pay (WTP) for digital credit is non-existent. We employ a discrete choice experiment (DCE) to compare farmers’ WTP for digital and conventional credit. Our results indicate a higher WTP for digital credit compared to conventional credit. Furthermore, we find that longer loan duration has a higher effect on farmers’ WTP for digital credit compared to conventional credit. Additionally, our results show that instalment repayment condition reduces farmers’ WTP for digital credit whilst increasing their WTP for conventional credit. Our results show the potential of digital credit for agricultural finance in rural areas of Madagascar if a certain level of innovation is applied in designing digital credit products.

Suggested Citation

  • Sarfo, Yaw & Musshoff, Oliver & Weber, Ron & Danne, Michael, 2021. "Farmers’ willingness to pay for digital and conventional credit: Evidence from a discrete choice experiment in Madagascar," 61st Annual Conference, Berlin, Germany, September 22-24, 2021 317074, German Association of Agricultural Economists (GEWISOLA).
  • Handle: RePEc:ags:gewi21:317074
    DOI: 10.22004/ag.econ.317074
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/317074/files/163-Sarfo_b.pdf
    Download Restriction: no

    File URL: https://libkey.io/10.22004/ag.econ.317074?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. Thorsten Beck & Asli Demirgüç-Kunt & Maria Soledad Martinez Peria, 2008. "Banking Services for Everyone? Barriers to Bank Access and Use around the World," The World Bank Economic Review, World Bank, vol. 22(3), pages 397-430, November.
    2. Paul Mpuga, 2010. "Constraints in Access to and Demand for Rural Credit: Evidence from Uganda," African Development Review, African Development Bank, vol. 22(1), pages 115-148.
    3. William Jack & Tavneet Suri, 2014. "Risk Sharing and Transactions Costs: Evidence from Kenya's Mobile Money Revolution," American Economic Review, American Economic Association, vol. 104(1), pages 183-223, January.
    4. Thomas Dohmen & Armin Falk & David Huffman & Uwe Sunde & Jürgen Schupp & Gert G. Wagner, 2011. "Individual Risk Attitudes: Measurement, Determinants, And Behavioral Consequences," Journal of the European Economic Association, European Economic Association, vol. 9(3), pages 522-550, June.
    5. Riccardo Scarpa & John M. Rose, 2008. "Design efficiency for non-market valuation with choice modelling: how to measure it, what to report and why ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 52(3), pages 253-282, September.
    6. Xavier Giné & Pamela Jakiela & Dean Karlan & Jonathan Morduch, 2010. "Microfinance Games," American Economic Journal: Applied Economics, American Economic Association, vol. 2(3), pages 60-95, July.
    7. Murendo, Conrad & Wollni, Meike, 2016. "Mobile money and household food security in Uganda," GlobalFood Discussion Papers 229805, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    8. Ron Weber & Oliver Musshoff, 2012. "Is agricultural microcredit really more risky? Evidence from Tanzania," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 72(3), pages 416-435, November.
    9. Marc Labie & Carolina Laureti & Ariane Szafarz, 2013. "Flexible Products in Microfinance: Overcoming the Demand-Supply Mismatch," Working Papers CEB 13-044, ULB -- Universite Libre de Bruxelles.
    10. Conning, Jonathan & Udry, Christopher, 2007. "Rural Financial Markets in Developing Countries," Handbook of Agricultural Economics, in: Robert Evenson & Prabhu Pingali (ed.), Handbook of Agricultural Economics, edition 1, volume 3, chapter 56, pages 2857-2908, Elsevier.
    11. Arne Risa Hole, 2007. "Fitting mixed logit models by using maximum simulated likelihood," Stata Journal, StataCorp LLC, vol. 7(3), pages 388-401, September.
    12. Byoung-Hwa Hwang & Camilo Tellez, 2016. "The Proliferation of Digital Credit Deployments," World Bank Publications - Reports 24567, The World Bank Group.
    13. Stephen R. Boucher & Michael R. Carter & Catherine Guirkinger, 2008. "Risk Rationing and Wealth Effects in Credit Markets: Theory and Implications for Agricultural Development," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 90(2), pages 409-423.
    14. Boucher, Stephen R. & Carter, Michael R. & Guirkinger, Catherine, 2008. "AJAE Appendix: Risk Rationing and Wealth Effects in Credit Markets: Theory and Implications for Agriculture Development," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 90(2), pages 1-6.
    15. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923, December.
    16. Daniel McFadden & Kenneth Train, 2000. "Mixed MNL models for discrete response," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 15(5), pages 447-470.
    17. Karlan, Dean & Kendall, Jake & Mann, Rebecca & Pande, Rohini & Suri, Tavneet & Zinman, Jonathan, 2016. "Research and Impacts of Digital Financial Services," Working Paper Series 16-037, Harvard University, John F. Kennedy School of Government.
    18. Ron Weber & Oliver Musshoff, 2013. "Can flexible microfinance loans improve credit access for farmers?," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 73(2), pages 255-271, July.
    19. Krah, Kwabena & Michelson, Hope & Perge, Emilie & Jindal, Rohit, 2019. "Constraints to adopting soil fertility management practices in Malawi: A choice experiment approach," World Development, Elsevier, vol. 124(C), pages 1-1.
    20. Peter Boxall & Wiktor Adamowicz, 2002. "Understanding Heterogeneous Preferences in Random Utility Models: A Latent Class Approach," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 23(4), pages 421-446, December.
    21. Mamudu A. Akudugu & Irene S. Egyir & Akwasi Mensah‐Bonsu, 2009. "Women farmers' access to credit from rural banks in Ghana," Agricultural Finance Review, Emerald Group Publishing Limited, vol. 69(3), pages 284-299, November.
    22. David A. Hensher & William H. Greene, 2011. "Valuation of Travel Time Savings in WTP and Preference Space in the Presence of Taste and Scale Heterogeneity," Journal of Transport Economics and Policy, University of Bath, vol. 45(3), pages 505-525, September.
    23. Bliemer, Michiel C.J. & Rose, John M. & Hensher, David A., 2009. "Efficient stated choice experiments for estimating nested logit models," Transportation Research Part B: Methodological, Elsevier, vol. 43(1), pages 19-35, January.
    24. Waldman, Kurt B. & Ortega, David L. & Richardson, Robert B. & Snapp, Sieglinde S., 2017. "Estimating demand for perennial pigeon pea in Malawi using choice experiments," Ecological Economics, Elsevier, vol. 131(C), pages 222-230.
    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. Rachna Madaan & Rajesh Kumar, 2024. "Influence of Digitalization on Agricultural Credit for Green Economy and Sustainable Development," Acta Universitatis Bohemiae Meridionalis, University of South Bohemia in Ceske Budejovice, Faculty of Economics, vol. 27(3), pages 1-16.
    2. Li, Yanru & Wang, Haijun & Gao, Huikun & Li, Qinghai & Sun, Guanglin, 2024. "Credit rating, repayment willingness and farmer credit default," International Review of Financial Analysis, Elsevier, vol. 93(C).
    3. Tim Ölkers & Oliver Mußhoff, 2024. "Exploring the role of interest rates, macroeconomic environment, agricultural cycle, and gender on loan demand in the agricultural sector: Evidence from Mali," Agribusiness, John Wiley & Sons, Ltd., vol. 40(2), pages 484-512, April.
    4. Annkathrin Wahbi & Oliver Musshoff, 2024. "Unlocking rural resilience: Exploring innovative digital saving solutions for farming households in Mali," Journal of Agricultural Economics, Wiley Blackwell, vol. 75(3), pages 931-954, September.

    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. Sarfo, Yaw & Musshoff, Oliver & Weber, Ron & Danne, Michael, 2021. "Farmers’ Willingness to Pay for Digital Credit: Evidence from a Discrete Choice Experiment in Madagascar," 2021 Conference, August 17-31, 2021, Virtual 315029, International Association of Agricultural Economists.
    2. Apurba Shee & Calum G. Turvey & Ana Marr, 2021. "Heterogeneous Demand and Supply for an Insurance‐linked Credit Product in Kenya: A Stated Choice Experiment Approach," Journal of Agricultural Economics, Wiley Blackwell, vol. 72(1), pages 244-267, February.
    3. Haghani, Milad & Bliemer, Michiel C.J. & Hensher, David A., 2021. "The landscape of econometric discrete choice modelling research," Journal of choice modelling, Elsevier, vol. 40(C).
    4. Yaw Sarfo & Oliver Musshoff & Ron Weber & Michael Danne, 2021. "Farmers’ willingness to pay for digital and conventional credit: Insight from a discrete choice experiment in Madagascar," PLOS ONE, Public Library of Science, vol. 16(11), pages 1-23, November.
    5. Mariel, Petr & Meyerhoff, Jürgen, 2018. "A More Flexible Model or Simply More Effort? On the Use of Correlated Random Parameters in Applied Choice Studies," Ecological Economics, Elsevier, vol. 154(C), pages 419-429.
    6. Ajayi, V. & Reiner, D., 2020. "Consumer Willingness to Pay for Reducing the Environmental Footprint of Green Plastics," Cambridge Working Papers in Economics 20110, Faculty of Economics, University of Cambridge.
    7. Kragt, Marit Ellen, 2013. "Comparing models of unobserved heterogeneity in environmental choice experiments," Working Papers 144447, University of Western Australia, School of Agricultural and Resource Economics.
    8. Elinor Benami & Michael R. Carter, 2021. "Can digital technologies reshape rural microfinance? Implications for savings, credit, & insurance," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 43(4), pages 1196-1220, December.
    9. Zhou, Heng & Norman, Richard & Xia, Jianhong(Cecilia) & Hughes, Brett & Kelobonye, Keone & Nikolova, Gabi & Falkmer, Torbjorn, 2020. "Analysing travel mode and airline choice using latent class modelling: A case study in Western Australia," Transportation Research Part A: Policy and Practice, Elsevier, vol. 137(C), pages 187-205.
    10. Boyce, Christopher & Czajkowski, Mikołaj & Hanley, Nick, 2019. "Personality and economic choices," Journal of Environmental Economics and Management, Elsevier, vol. 94(C), pages 82-100.
    11. Oyakhilomen Oyinbo & Jordan Chamberlin & Miet Maertens, 2020. "Design of Digital Agricultural Extension Tools: Perspectives from Extension Agents in Nigeria," Journal of Agricultural Economics, Wiley Blackwell, vol. 71(3), pages 798-815, September.
    12. Buchholz, Matthias & Danne, Michael & Musshoff, Oliver, 2022. "An experimental analysis of German farmers’ decisions to buy or rent farmland," Land Use Policy, Elsevier, vol. 120(C).
    13. Aparicio, Gabriela & Bobic, Vida & De Olloqui, Fernando & Carmen, María & Diez, María Carmen Fernández & Gerardino, Maria Paula & Mitnik, Oscar A. & Macedo, Sebastian Vargas, 2021. "Liquidity or Capital? The Impacts of Easing Credit Constraints in Rural Mexico," IZA Discussion Papers 14477, Institute of Labor Economics (IZA).
    14. Allison Benson & Jean-Paul Faguet & Maria del pilar López Uribe, 2020. "Increasing Access to Agricultural Credit: The Heterogeneous Effects of Collective Action," Documentos CEDE 18347, Universidad de los Andes, Facultad de Economía, CEDE.
    15. Shukri Ahmed & Craig McIntosh & Alexandros Sarris, 2020. "The Impact of Commercial Rainfall Index Insurance: Experimental Evidence from Ethiopia," American Journal of Agricultural Economics, John Wiley & Sons, vol. 102(4), pages 1154-1176, August.
    16. Feil, J.-H. & Anastassiadis, F. & Mußhoff, O. & Schilling, P., 2015. "Analysing Farmers’ Use of Price Hedging Instruments: An Experimental Approach," Proceedings “Schriften der Gesellschaft für Wirtschafts- und Sozialwissenschaften des Landbaues e.V.”, German Association of Agricultural Economists (GEWISOLA), vol. 50, March.
    17. Yan, Zhen & Zhou, Jie-hong, 2015. "Measuring consumer heterogeneous preferences for pork traits under media reports: choice experiment in sixteen traceability pilot cities, China," 2015 Conference, August 9-14, 2015, Milan, Italy 212609, International Association of Agricultural Economists.
    18. Anette Ruml & Martin C. Parlasca, 2022. "In‐kind credit provision through contract farming and formal credit markets," Agribusiness, John Wiley & Sons, Ltd., vol. 38(2), pages 402-425, April.
    19. Zawojska, Ewa & Bartczak, Anna & Czajkowski, Mikołaj, 2019. "Disentangling the effects of policy and payment consequentiality and risk attitudes on stated preferences," Journal of Environmental Economics and Management, Elsevier, vol. 93(C), pages 63-84.
    20. Franceschinis, Cristiano & Thiene, Mara & Scarpa, Riccardo & Rose, John & Moretto, Michele & Cavalli, Raffaele, 2017. "Adoption of renewable heating systems: An empirical test of the diffusion of innovation theory," Energy, Elsevier, vol. 125(C), pages 313-326.

    More about this item

    Keywords

    Farm Management;

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:gewi21:317074. 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/gewisea.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.