JOURNAL ARTICLE

Mobile Broadband, Poverty, and Labor Outcomes in Tanzania.

  • Published In: World Bank Economic Review, 2023, v. 37, n. 2. P. 235 1 of 3

  • Database: Business Source Ultimate 2 of 3

  • Authored By: Bahia, Kalvin; Castells, Pau; Cruz, Genaro; Masaki, Takaaki; Rodríguez-Castelán, Carlos; Sanfelice, Viviane 3 of 3

Abstract

This article examines the impacts of expanding mobile broadband coverage—specifically 3G networks—on poverty, household consumption, and labor-market outcomes in Tanzania, a developing country in Sub-Saharan Africa. Using a difference-in-differences estimation with panel household survey data linked to precise geospatial mobile broadband rollout information from 2008 to 2013, the study finds that 3G coverage significantly increases total household consumption by 7–11 percent and reduces poverty rates by 5–7 percentage points. These welfare gains are largely driven by improved labor-market outcomes, including increased labor-force participation, wage employment, and non-farm self-employment, alongside a decline in farm employment. The benefits vary by demographic groups: younger and more educated men experience the largest gains in labor participation and wage employment, while skilled women tend to transition from farm self-employment to non-farm employment, though they do not see increases in labor-force participation or wage employment. The findings highlight both the positive economic effects of mobile broadband infrastructure and the persistent disparities in digital access and labor-market benefits across gender, education, age, and urban-rural divides.

Additional Information

  • Source:World Bank Economic Review. 2023/05, Vol. 37, Issue 2, p235
  • Document Type:Article
  • Subject Area:Women's Studies and Feminism
  • Publication Date:2023
  • ISSN:0258-6770
  • DOI:10.1093/wber/lhad003
  • Accession Number:163278989
  • Copyright Statement:Copyright of World Bank Economic Review is the property of Oxford University Press / USA and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Looking to go deeper into this topic? Look for more articles on EBSCOhost.