Mobile Broadband, Poverty, and Labor Outcomes in Tanzania

What are the impacts of expanding mobile broadband coverage on poverty, household consumption, and labor-market outcomes in developing countries? Who benefits from improved coverage of mobile internet? To respond to these questions, this paper applies a difference-in-differences estimation using panel household survey data combined with geospatial information on the rollout of mobile broadband coverage in Tanzania. The results reveal that being covered by 3G networks has a large positive effect on total household consumption and poverty reduction, driven by positive impacts on labor-market outcomes. Working-age individuals living in areas covered by mobile internet witnessed an increase in labor-force participation, wage employment, and non-farm self-employment, and a decline in farm employment. These effects vary by age, gender, and skill level. Younger and more skilled men benefit the most through higher labor-force participation and wage employment, while high-skilled women benefit from transitions from self-employed farm work into non-farm employment.

[1]  M. Kugler,et al.  Mobile Access Expansion and Price Information Diffusion: Firm Performance after Ethiopia'S Transition to 3G in 2008 , 2021, Policy Research Working Papers.

[2]  T. Masaki,et al.  Mobile Internet Adoption in West Africa , 2021, Policy Research Working Papers.

[3]  D. Larcker,et al.  How Much Should We Trust Staggered Difference-In-Differences Estimates? , 2021, SSRN Electronic Journal.

[4]  Lin Tian,et al.  The Economic Impact of Internet Connectivity in Developing Countries , 2021, SSRN Electronic Journal.

[5]  T. Masaki,et al.  Broadband Internet and Household Welfare in Senegal , 2020, SSRN Electronic Journal.

[6]  Maude Hasbi,et al.  Determinants of mobile broadband use in developing economies: Evidence from Sub-Saharan Africa , 2020, Telecommunications Policy.

[7]  T. Masaki,et al.  The Welfare Effects of Mobile Broadband Internet: Evidence from Nigeria , 2020, SSRN Electronic Journal.

[8]  R. Gonzalez Cell Phone Access and Election Fraud: Evidence from a Spatial Regression Discontinuity Design in Afghanistan , 2020, American Economic Journal: Applied Economics.

[9]  H. Winkler,et al.  Does the Internet Reduce Gender Gaps?: The Case of Jordan , 2020 .

[10]  Pedro H. C. Sant'Anna,et al.  Doubly Robust Difference-in-Differences Estimators , 2018, Journal of Econometrics.

[11]  Pedro H. C. Sant'Anna,et al.  Difference-in-Differences with Multiple Time Periods , 2018, Journal of Econometrics.

[12]  Jianmei Zhao Internet Usage and Rural Self-Employment in China , 2020 .

[13]  F. Tarp,et al.  Can the Internet improve agricultural production? Evidence from Viet Nam , 2019, Agricultural Economics.

[14]  A. Mattoo,et al.  The internet and Chinese exports in the pre-ali baba era , 2019, Journal of Development Economics.

[15]  Jonas Hjort,et al.  The Arrival of Fast Internet and Employment in Africa , 2017, American Economic Review.

[16]  Olukorede Abiona,et al.  Financial Inclusion, Shocks, and Poverty: Evidence from the Expansion of Mobile Money in Tanzania , 2022, SSRN Electronic Journal.

[17]  Ingmar Weber,et al.  Using Facebook ad data to track the global digital gender gap , 2018, World Development.

[18]  Heiwai Tang,et al.  Do Information and Communication Technologies Empower Female Workers? Firm-Level Evidence from Viet Nam , 2018 .

[19]  Markus Goldstein,et al.  Disruptive Finance : Using Psychometrics to Overcome Collateral Constraints in Ethiopia , 2018 .

[20]  Nicholas O. Alozie,et al.  The Digital Gender Divide: Confronting Obstacles to Women's Development in Africa , 2017 .

[21]  William Jack,et al.  The long-run poverty and gender impacts of mobile money , 2016, Science.

[22]  Clovis Rugemintwari,et al.  Does Mobile Money Affect Saving Behavior? Evidence from a Developing Country , 2016 .

[23]  Nathan Eagle,et al.  Airtime transfers and mobile communications: Evidence in the aftermath of natural disasters , 2016 .

[24]  Michael Hübler,et al.  Are smartphones smart for economic development , 2016 .

[25]  G. Tadesse,et al.  Mobile Phones and Farmers’ Marketing Decisions in Ethiopia , 2015 .

[26]  Caroline Paunov,et al.  Overcoming Obstacles: The Internet's Contribution to Firm Development , 2015 .

[27]  L. Keele,et al.  Geographic Boundaries as Regression Discontinuities , 2015, Political Analysis.

[28]  Phanindra V. Wunnava,et al.  The Effect of Access to Information and Communication Technology on Household Labor Income: Evidence from One Laptop Per Child in Uruguay , 2017, SSRN Electronic Journal.

[29]  Sebastian Calonico,et al.  Robust Nonparametric Confidence Intervals for Regression‐Discontinuity Designs , 2014 .

[30]  Matteo Grazzi,et al.  Internet in Latin America: who uses it? … and for what? , 2014 .

[31]  William Jack,et al.  Risk Sharing and Transactions Costs: Evidence from Kenya's Mobile Money Revolution , 2014 .

[32]  Magne Mogstad,et al.  The Skill Complementarity of Broadband Internet , 2015, SSRN Electronic Journal.

[33]  Marcel Fafchamps,et al.  Mobile Phone Coverage and Producer Markets: Evidence from West Africa , 2013 .

[34]  Hilal Atasoy The Effects of Broadband Internet Expansion on Labor Market Outcomes , 2013 .

[35]  J. Aker,et al.  Can Mobile Money Be Used to Promote Savings? Evidence from Northern Ghana , 2013 .

[36]  Diether W. Beuermann,et al.  Mobile Phones and Economic Development in Rural Peru , 2012 .

[37]  Jenny C. Aker,et al.  Dial 'A' for Agriculture: A Review of Information and Communication Technologies for Agricultural Extension in Developing Countries , 2011 .

[38]  Dani Rodrik,et al.  Globalization, Structural Change and Productivity Growth , 2011 .

[39]  J. Aker,et al.  Mobile Phones and Economic Development in Africa , 2010 .

[40]  P. Nolen,et al.  Cell Phones and Rural Labor Markets: Evidence from South Africa , 2010 .

[41]  T. Yamano,et al.  The Impact of Mobile Phone Coverage Expansion on Market Participation: Panel Data Evidence from Uganda , 2009 .

[42]  Robert S. Chase,et al.  The Power of Information: The Impact of Mobile Phones on Farmers'Welfare in the Philippines , 2009 .

[43]  Joshua D. Angrist,et al.  Mostly Harmless Econometrics: An Empiricist's Companion , 2008 .

[44]  D. Yang,et al.  Agriculture and aggregate productivity: A quantitative cross-country analysis , 2008 .

[45]  R. Jensen The Digital Provide: Information (Technology), Market Performance, and Welfare in the South Indian Fisheries Sector , 2007 .

[46]  Alberto Abadie Semiparametric Difference-in-Differences Estimators , 2005 .

[47]  Bruce Bimber Measuring the Gender Gap on the Internet 1 , 2000 .

[48]  A. G. Longley,et al.  PREDICTION OF TROPOSPHERIC RADIO TRANSMISSION LOSS OVER IRREGULAR TERRAIN. A COMPUTER METHOD-1968 , 1968 .

[49]  T. Schultz Reflections on Agricultural Production, Output and Supply , 1956 .