IDEAS home Printed from https://ideas.repec.org/a/eee/telpol/v47y2023i6s0308596123000812.html
   My bibliography  Save this article

Impact of information and communication technologies on agricultural households’ welfare in Benin

Author

Listed:
  • Armel Nonvide, Gbêtondji Melaine

Abstract

Information technologies are very important to transform the agricultural sector and improve economic performance. Nevertheless, does the use of information and communication technologies (ICT) improve agricultural households' welfare? To answer this, the study used a nationally representative household survey, the Comprehensive Food Security and Vulnerability Analysis (CFSVA) carried out in 2017 in Benin. The survey covered a sample of 15 000 households, however, the analysis focused on the 6502 agricultural households. An endogenous switching regression model was employed to control for selection bias and endogeneity issues. Results indicated that the use of ICT increases households' consumption expenditure by 89.6%. This implies that the use of ICT improves agricultural households' welfare. Other variables that affect agricultural households’ welfare include age, marital status, farm size, access to credit, ownership of livestock, membership in a farmer-based organization, and region of residence. Furthermore, the decision to use ICT in agricultural households depends on the level of education, age, sex, marital status, farm size, access to credit, ownership of livestock, membership in a farmer based organization, and location. These findings suggest that policies that promote the use of ICT are key to improving welfare of agricultural households in Benin. These policies must consider demographic, socio-economic, and institutional characteristics of households.

Suggested Citation

  • Armel Nonvide, Gbêtondji Melaine, 2023. "Impact of information and communication technologies on agricultural households’ welfare in Benin," Telecommunications Policy, Elsevier, vol. 47(6).
  • Handle: RePEc:eee:telpol:v:47:y:2023:i:6:s0308596123000812
    DOI: 10.1016/j.telpol.2023.102570
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0308596123000812
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.telpol.2023.102570?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 search for a different version of it.

    References listed on IDEAS

    as
    1. Yves Yao Soglo & Gbêtondji Melaine Armel Nonvide, 2019. "Climate change perceptions and responsive strategies in Benin: the case of maize farmers," Climatic Change, Springer, vol. 155(2), pages 245-256, July.
    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. Martínez-Domínguez, Marlen & Mora-Rivera, Jorge, 2020. "Internet adoption and usage patterns in rural Mexico," Technology in Society, Elsevier, vol. 60(C).
    4. James Heckman & Justin L. Tobias & Edward Vytlacil, 2001. "Four Parameters of Interest in the Evaluation of Social Programs," Southern Economic Journal, John Wiley & Sons, vol. 68(2), pages 210-223, October.
    5. Salvatore Di Falco & Marcella Veronesi & Mahmud Yesuf, 2011. "Does Adaptation to Climate Change Provide Food Security? A Micro-Perspective from Ethiopia," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 93(3), pages 825-842.
    6. Michael Lokshin & Zurab Sajaia, 2004. "Maximum likelihood estimation of endogenous switching regression models," Stata Journal, StataCorp LP, vol. 4(3), pages 282-289, September.
    7. 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.
    8. 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.
    9. Nawab Khan & Ram L. Ray & Hazem S. Kassem & Farhat Ullah Khan & Muhammad Ihtisham & Shemei Zhang, 2022. "Does the Adoption of Mobile Internet Technology Promote Wheat Productivity? Evidence from Rural Farmers," Sustainability, MDPI, vol. 14(13), pages 1-15, June.
    10. 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.
    11. Barnabas Kiiza & Glenn Pederson & Stephen Lwasa, 2011. "The Role of Market Information in Adoption of Agricultural Seed Technology in Rural Uganda," International Journal of ICT Research and Development in Africa (IJICTRDA), IGI Global, vol. 2(1), pages 29-46, January.
    12. Jenny C. Aker & Isaac M. Mbiti, 2010. "Mobile Phones and Economic Development in Africa," Journal of Economic Perspectives, American Economic Association, vol. 24(3), pages 207-232, Summer.
    13. James Heckman & Justin L. Tobias & Edward Vytlacil, 2001. "Four Parameters of Interest in the Evaluation of Social Programs," Southern Economic Journal, John Wiley & Sons, vol. 68(2), pages 210-223, October.
    14. Penard, Thierry & Poussing, Nicolas & Mukoko, Blaise & Tamokwe Piaptie, Georges Bertrand, 2015. "Internet adoption and usage patterns in Africa: Evidence from Cameroon," Technology in Society, Elsevier, vol. 42(C), pages 71-80.
    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. Verkaart, Simone & Munyua, Bernard G. & Mausch, Kai & Michler, Jeffrey D., 2017. "Welfare impacts of improved chickpea adoption: A pathway for rural development in Ethiopia?," Food Policy, Elsevier, vol. 66(C), pages 50-61.
    17. David W. Carter & J. Walter Milon, 2005. "Price Knowledge in Household Demand for Utility Services," Land Economics, University of Wisconsin Press, vol. 81(2).
    18. Hoang, Hung Gia, 2020. "Determinants of the adoption of mobile phones for fruit marketing by Vietnamese farmers," World Development Perspectives, Elsevier, vol. 17(C).
    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. 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).
    2. 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.
    3. 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.
    4. Benali, Marwan & Brümmer, Bernhard & Afari-Sefa, Victor, 2017. "Small producer participation in export vegetable supply chains and poverty: evidence from different export schemes in Tanzania," GlobalFood Discussion Papers 262583, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    5. Tesfaye, Wondimagegn & Tirivayi, Nyasha, 2018. "The impacts of postharvest storage innovations on food security and welfare in Ethiopia," Food Policy, Elsevier, vol. 75(C), pages 52-67.
    6. Bairagi, Subir & Mishra, Ashok K. & Durand-Morat, Alvaro, 2020. "Climate risk management strategies and food security: Evidence from Cambodian rice farmers," Food Policy, Elsevier, vol. 95(C).
    7. Doris Läpple & Thia Hennessy & Carol Newman, 2013. "Quantifying the Economic Return to Participatory Extension Programmes in Ireland: an Endogenous Switching Regression Analysis," Journal of Agricultural Economics, Wiley Blackwell, vol. 64(2), pages 467-482, June.
    8. Yang, Jinqiu & Hong, Yongmiao & Ma, Shuangge, 2016. "Impact of the new health care reform on hospital expenditure in China: A case study from a pilot city," China Economic Review, Elsevier, vol. 39(C), pages 1-14.
    9. Salvatore Falco & Marcella Veronesi, 2018. "Managing Environmental Risk in Presence of Climate Change: The Role of Adaptation in the Nile Basin of Ethiopia," Natural Resource Management and Policy, in: Leslie Lipper & Nancy McCarthy & David Zilberman & Solomon Asfaw & Giacomo Branca (ed.), Climate Smart Agriculture, pages 497-526, Springer.
    10. repec:mth:jas888:v:7:y:2019:i:1:p:82-102 is not listed on IDEAS
    11. Federico Antonioli & Simone Severini & Mauro Vigani, 2023. "Visa for competitiveness: foreign workforce and Italian dairy farms’ performance," European Review of Agricultural Economics, Oxford University Press and the European Agricultural and Applied Economics Publications Foundation, vol. 50(1), pages 115-150.
    12. Tezera W. Meskel & Mengistu Ketema & Jema Haji & Lemma Zemedu, 2021. "Welfare Impact of Moringa Market Participation in Southern Ethiopia," Sustainable Agriculture Research, Canadian Center of Science and Education, vol. 9(3), pages 1-98, December.
    13. Raghu, Prabhakaran T & Das, Sukanya & Veettil, Prakashan Chellattan, 2021. "Smallholder Adaptation to Flood Risks: Adoption and Impact of Swarna-Sub1 in Eastern India," 2021 Conference, August 17-31, 2021, Virtual 315867, International Association of Agricultural Economists.
    14. Seng, Kimty, 2021. "The mobile money’s poverty-reducing promise: Evidence from Cambodia," World Development Perspectives, Elsevier, vol. 22(C).
    15. Hambulo Ngoma, 2018. "Does minimum tillage improve the livelihood outcomes of smallholder farmers in Zambia?," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(2), pages 381-396, April.
    16. Yonas Alem & Håkan Eggert & Remidius Ruhinduka, 2015. "Improving Welfare Through Climate-Friendly Agriculture: The Case of the System of Rice Intensification," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 62(2), pages 243-263, October.
    17. Tanimonure, Victoria Adeyemi, 2021. "Impact of Climate Adaptation Strategies on the Net Farm Revenue of Underutilized Indigenous Vegetables’ (UIVs) Production in Southwest Nigeria," 2021 Conference, August 17-31, 2021, Virtual 315903, International Association of Agricultural Economists.
    18. 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.
    19. Song, Chunxiao & Liu, Ruifeng & Oxley, Oxley & Ma, Hengyun, 2018. "The adoption and impact of engineering-type measures to address climate change: evidence from the major grain-producing areas in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(4), October.
    20. Priyanka Parvathi, 2018. "Does mixed crop‐livestock farming lead to less diversified diets among smallholders? Evidence from Laos," Agricultural Economics, International Association of Agricultural Economists, vol. 49(4), pages 497-509, July.
    21. Akpalu, Wisdom & Zhang, Xu, 2014. "Fast-food consumption and child body mass index in China: Application of an endogenous switching regression model," WIDER Working Paper Series 139, World Institute for Development Economic Research (UNU-WIDER).

    More about this item

    Keywords

    Agricultural households; Information and communication technologies; Endogenous switching regression model; Welfare; Benin;
    All these keywords.

    JEL classification:

    • D6 - Microeconomics - - Welfare Economics
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets

    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:eee:telpol:v:47:y:2023:i:6:s0308596123000812. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/30471/description#description .

    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.