[go: up one dir, main page]
IDEAS home Printed from https://ideas.repec.org/p/jet/dpaper/dpaper875.html
   My bibliography  Save this paper

Mobile phone ownership, income diversification, and household welfare in rural Bangladesh

Author

Listed:
  • Matsuura,Masanori
  • Md Saiful Islam,Abu Hayat
  • Tauseef,Salauddin
Abstract
Mobile phone has been widely adopted in developing countries with potential to enhance opportunities for finding employment and business opportunities which builds resilience of rural livelihoods. Although the effect of mobile phones on income has been studied in the past, the potential to increase income diversification and reduce poverty has not been studied so much. To fill this gap, we investigate the linkage among mobile phone ownership, income diversification, and household welfare, using monetary and non-monetary aspects of poverty. Using instrumental variable approach, we find that mobile phone ownership increases income diversification then reduces the incidence and depth of poverty. It also has significant impact on non-monetary aspects of poverty. Our heterogeneity analysis shows the pro-poor impacts of mobile phone ownership as well as that female-headed households enjoy larger impact of mobile phone ownership on income diversification. Moreover, Gini decomposition of different income sources with propensity score matching indicates that the off-farm income results in an inequality-equalizing effect among the rural households owning mobile phones in Bangladesh, suggesting the income diversification through mobile phone ownership improves the overall welfare of the rural society.

Suggested Citation

  • Matsuura,Masanori & Md Saiful Islam,Abu Hayat & Tauseef,Salauddin, 2023. "Mobile phone ownership, income diversification, and household welfare in rural Bangladesh," IDE Discussion Papers 875, Institute of Developing Economies, Japan External Trade Organization(JETRO).
    • Handle: RePEc:jet:dpaper:dpaper875
    as

    Download full text from publisher

    File URL: https://ir.ide.go.jp/?action=repository_action_common_download&item_id=53606&item_no=1&attribute_id=22&file_no=1
    File Function: First version, 2023
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Haruna Sekabira & Matin Qaim, 2017. "Mobile money, agricultural marketing, and off-farm income in Uganda," Agricultural Economics, International Association of Agricultural Economists, vol. 48(5), pages 597-611, September.
    2. Asongu, Simplice A. & Nwachukwu, Jacinta C., 2016. "The Mobile Phone in the Diffusion of Knowledge for Institutional Quality in Sub-Saharan Africa," World Development, Elsevier, vol. 86(C), pages 133-147.
    3. Foster, James & Greer, Joel & Thorbecke, Erik, 1984. "A Class of Decomposable Poverty Measures," Econometrica, Econometric Society, vol. 52(3), pages 761-766, May.
    4. Simplice Asongu, 2015. "The impact of mobile phone penetration on African inequality," International Journal of Social Economics, Emerald Group Publishing Limited, vol. 42(8), pages 706-716, August.
    5. Maria Fay Rola‐Rubzen & Thelma Paris & Jacob Hawkins & Bibek Sapkota, 2020. "Improving Gender Participation in Agricultural Technology Adoption in Asia: From Rhetoric to Practical Action," Applied Economic Perspectives and Policy, John Wiley & Sons, vol. 42(1), pages 113-125, March.
    6. Adams, Richard H, Jr, 2002. "Nonfarm Income, Inequality, and Land in Rural Egypt," Economic Development and Cultural Change, University of Chicago Press, vol. 50(2), pages 339-363, January.
    7. Conrad Murendo & Meike Wollni & Alan De Brauw & Nicholas Mugabi, 2018. "Social Network Effects on Mobile Money Adoption in Uganda," Journal of Development Studies, Taylor & Francis Journals, vol. 54(2), pages 327-342, February.
    8. 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.
    9. Sekabira, Haruna & Qaim, Matin, 2017. "Can Mobile Phones Improve Gender Equality and Nutrition? Panel Data Evidence from Farm Households in Uganda," GlobalFood Discussion Papers 256215, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    10. 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.
    11. Muto, Megumi & Yamano, Takashi, 2009. "The Impact of Mobile Phone Coverage Expansion on Market Participation: Panel Data Evidence from Uganda," World Development, Elsevier, vol. 37(12), pages 1887-1896, December.
    12. Akhter U. Ahmed & Salauddin Tauseef, 2022. "Climbing up the Ladder and Watching Out for the Fall: Poverty Dynamics in Rural Bangladesh," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 160(1), pages 309-340, February.
    13. Pallavi Rajkhowa & Matin Qaim, 2022. "Mobile phones, off‐farm employment and household income in rural India," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 789-805, September.
    14. Miyajima, Ken, 2022. "Mobile phone ownership and welfare: Evidence from South Africa’s household survey," World Development, Elsevier, vol. 154(C).
    15. Tadesse, Getaw & Bahiigwa, Godfrey, 2015. "Mobile Phones and Farmers’ Marketing Decisions in Ethiopia," World Development, Elsevier, vol. 68(C), pages 296-307.
    16. Abu Hayat Md. Saiful Islam & Joachim Braun & Andrew L. Thorne-Lyman & Akhter U. Ahmed, 2018. "Farm diversification and food and nutrition security in Bangladesh: empirical evidence from nationally representative household panel data," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 10(3), pages 701-720, June.
    17. Bladimir Carrillo, 2020. "Early Rainfall Shocks and Later-Life Outcomes: Evidence from Colombia," The World Bank Economic Review, World Bank, vol. 34(1), pages 179-209.
    18. Lerman, Robert I & Yitzhaki, Shlomo, 1985. "Income Inequality Effects by Income," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 151-156, February.
    19. Khandker, Shahidur R., 2012. "Seasonality of income and poverty in Bangladesh," Journal of Development Economics, Elsevier, vol. 97(2), pages 244-256.
    20. Douglas Staiger & James H. Stock, 1997. "Instrumental Variables Regression with Weak Instruments," Econometrica, Econometric Society, vol. 65(3), pages 557-586, May.
    21. Jean N. Lee & Jonathan Morduch & Saravana Ravindran & Abu Shonchoy & Hassan Zaman, 2021. "Poverty and Migration in the Digital Age: Experimental Evidence on Mobile Banking in Bangladesh," American Economic Journal: Applied Economics, American Economic Association, vol. 13(1), pages 38-71, January.
    22. Ashok K. Mishra & Kh. A. Mottaleb & Samarendu Mohanty, 2015. "Impact of off-farm income on food expenditures in rural Bangladesh: an unconditional quantile regression approach," Agricultural Economics, International Association of Agricultural Economists, vol. 46(2), pages 139-148, March.
    23. Munyegera, Ggombe Kasim & Matsumoto, Tomoya, 2016. "Mobile Money, Remittances, and Household Welfare: Panel Evidence from Rural Uganda," World Development, Elsevier, vol. 79(C), pages 127-137.
    24. Mundlak, Yair, 1978. "On the Pooling of Time Series and Cross Section Data," Econometrica, Econometric Society, vol. 46(1), pages 69-85, January.
    25. Thomas Reardon & J. Edward Taylor & Kostas Stamoulis & Peter Lanjouw & Arsenio Balisacan, 2000. "Effects of Non‐Farm Employment on Rural Income Inequality in Developing Countries: An Investment Perspective," Journal of Agricultural Economics, Wiley Blackwell, vol. 51(2), pages 266-288, May.
    26. Maximilian Auffhammer & Tamma A. Carleton, 2018. "Regional Crop Diversity and Weather Shocks in India," Asian Development Review, MIT Press, vol. 35(2), pages 113-130, September.
    27. Ma, Wanglin & Renwick, Alan & Nie, Peng & Tang, Jianjun & Cai, Rong, 2018. "Off-farm work, smartphone use and household income: Evidence from rural China," China Economic Review, Elsevier, vol. 52(C), pages 80-94.
    28. Asfaw, Solomon & Scognamillo, Antonio & Caprera, Gloria Di & Sitko, Nicholas & Ignaciuk, Adriana, 2019. "Heterogeneous impact of livelihood diversification on household welfare: Cross-country evidence from Sub-Saharan Africa," World Development, Elsevier, vol. 117(C), pages 278-295.
    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. Wanglin Ma & R. Quentin Grafton & Alan Renwick, 2020. "Smartphone use and income growth in rural China: empirical results and policy implications," Electronic Commerce Research, Springer, vol. 20(4), pages 713-736, December.
    2. Peng Nie & Wanglin Ma & Alfonso Sousa-Poza, 2021. "The relationship between smartphone use and subjective well-being in rural China," Electronic Commerce Research, Springer, vol. 21(4), pages 983-1009, December.
    3. Ma, W. & Grafton, Q. & Renwick, A., 2018. "Gender and Income Effects of Smartphone Use: The Case of Rural China," 2018 Conference, July 28-August 2, 2018, Vancouver, British Columbia 277310, International Association of Agricultural Economists.
    4. Islam, Masanori Matsuura Yir-Huieh Luh Abu Hayat Md. Saiful, 2021. "Climate Variability, Livelihood Diversification, and Household Food Security in Bangladesh," 2021 ASAE 10th International Conference (Virtual), January 11-13, Beijing, China 329402, Asian Society of Agricultural Economists (ASAE).
    5. Masanori Matsuura‐Kannari & Yir‐Hueih Luh & Abu Hayat Md. Saiful Islam, 2023. "Weather shocks, livelihood diversification, and household food security: Empirical evidence from rural Bangladesh," Agricultural Economics, International Association of Agricultural Economists, vol. 54(4), pages 455-470, July.
    6. Haruna Sekabira & Shamim Nalunga, 2020. "Farm Production Diversity: Is It Important for Dietary Diversity? Panel Data Evidence from Uganda," Sustainability, MDPI, vol. 12(3), pages 1-21, January.
    7. Gershom Endelani Mwalupaso & Shangao Wang & Sanzidur Rahman & Essiagnon John-Philippe Alavo & Xu Tian, 2019. "Agricultural Informatization and Technical Efficiency in Maize Production in Zambia," Sustainability, MDPI, vol. 11(8), pages 1-17, April.
    8. Sekabira, Haruna & Qaim, Matin, 2017. "Can mobile phones improve gender equality and nutrition? Panel data evidence from farm households in Uganda," Food Policy, Elsevier, vol. 73(C), pages 95-103.
    9. Gershom Endelani Mwalupaso & Xu Tian & Xianhui Geng, 2020. "Rethinking Food Production: Nexus of Mobile Phones and Production Cost Minimization," IJERPH, MDPI, vol. 17(7), pages 1-12, April.
    10. Ma, Wanglin & Renwick, Alan & Nie, Peng & Tang, Jianjun & Cai, Rong, 2018. "Off-farm work, smartphone use and household income: Evidence from rural China," China Economic Review, Elsevier, vol. 52(C), pages 80-94.
    11. Sekabira, Haruna & Qaim, Matin, 2017. "Can Mobile Phones Improve Gender Equality and Nutrition? Panel Data Evidence from Farm Households in Uganda," GlobalFood Discussion Papers 256215, Georg-August-Universitaet Goettingen, GlobalFood, Department of Agricultural Economics and Rural Development.
    12. Kabbiri, Ronald & Dora, Manoj & Kumar, Vikas & Elepu, Gabriel & Gellynck, Xavier, 2018. "Mobile phone adoption in agri-food sector: Are farmers in Sub-Saharan Africa connected?," Technological Forecasting and Social Change, Elsevier, vol. 131(C), pages 253-261.
    13. Abate, Gashaw T. & Abay, Kibrom A. & Chamberlin, Jordan & Kassim, Yumna & Spielman, David J. & Paul Jr Tabe-Ojong, Martin, 2023. "Digital tools and agricultural market transformation in Africa: Why are they not at scale yet, and what will it take to get there?," Food Policy, Elsevier, vol. 116(C).
    14. Pallavi Rajkhowa & Matin Qaim, 2022. "Mobile phones, off‐farm employment and household income in rural India," Journal of Agricultural Economics, Wiley Blackwell, vol. 73(3), pages 789-805, September.
    15. Gershom Endelani Mwalupaso & Shangao Wang & Zhangxing Xu & Xu Tian, 2019. "Towards Auspicious Agricultural Informatization—Implication of Farmers’ Behavioral Intention Apropos of Mobile Phone Use in Agriculture," Sustainability, MDPI, vol. 11(22), pages 1-21, November.
    16. Ni Zhuo & Baozhi Li & Qibiao Zhu & Chen Ji, 2023. "Smartphone‐based agricultural extension services and farm incomes: Evidence from Zhejiang Province in China," Review of Development Economics, Wiley Blackwell, vol. 27(3), pages 1383-1402, August.
    17. Simplice A. Asongu, 2021. "The Effects of Mobile Phone Technology, Knowledge Creation and Diffusion on Inclusive Human Development in Sub-Saharan Africa," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 12(3), pages 1367-1398, September.
    18. Raya Das & Ravi Srivastava, 2021. "Income inequality among agricultural households in India: A regression‐based decomposition analysis," Review of Development Economics, Wiley Blackwell, vol. 25(3), pages 1128-1149, August.
    19. Koomson, Isaac & Bukari, Chei & Villano, Renato A, 2021. "Mobile money adoption and response to idiosyncratic shocks: Empirics from five selected countries in sub-Saharan Africa," Technological Forecasting and Social Change, Elsevier, vol. 167(C).
    20. Catherine Ragasa & Diston Mzungu & Kenan Kalagho & Cynthia Kazembe, 2022. "Role of interactive radio programming in advancing women’s and youth’s empowerment and dietary diversity: Mixed method evidence from Malawi," Food Security: The Science, Sociology and Economics of Food Production and Access to Food, Springer;The International Society for Plant Pathology, vol. 14(5), pages 1259-1277, October.

    More about this item

    Keywords

    ICT|Mobile phone|Instrumental variable approach|Poverty reduction|Gini decomposition|Bangladesh;

    JEL classification:

    • C26 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Instrumental Variables (IV) Estimation
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • Q12 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Agriculture - - - Micro Analysis of Farm Firms, Farm Households, and Farm Input Markets
    • Q55 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environmental Economics: Technological Innovation

    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:jet:dpaper:dpaper875. 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: Michitaka Imamitsu (email available below). General contact details of provider: https://edirc.repec.org/data/idegvjp.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.