Scholars and policymakers have put much faith into the prospect of internet connectivity catalyzing development in low- and middle-income countries. In new research, Pinelopi Koujianou Goldberg and Gaurav Chiplunkar find that improved 3G coverage does lead to better employment opportunities for individuals and higher female labor force participation. However, these new opportunities mostly reflect the rise of the gig economy rather than the anticipated shift of workers from agriculture to manufacturing and services.

Reducing global poverty will require the expansion of internet connectivity: this case has been made by many. For example, in arguing for an agenda to reach universal internet access by 2030, former British Prime Minister Tony Blair stated, “Eradicating extreme poverty, solving the global education crisis, building better health-care systems and responding to pandemics effectively all require connectivity.” In launching an Internet Poverty Index, researchers at the World Data Lab argued that internet access is a basic human right important for promoting development. But does better internet connectivity improve tangible economic outcomes in low- and middle-income countries (LMICs)? 

To date, much of the political discussion and existing scholarship has focused on the potential of internet technology to “jump-start” the development process in LMICs. An influential study has evaluated the impact of access to fixed high-speed broadband internet on socio-economic outcomes. However, understanding the impact of mobile internet, which is far more accessible and far more prevalent in LMICs, has been limited.

Early studies assessing the impact of better 3G coverage focused more on its impact on political mobilization. Recent studies assessing the economic impacts of this technology have focused on a few individual countries (mostly in Africa) and, for the most part, on outcomes other than employment.

Our study attempts to address these knowledge gaps. In particular, we are interested in assessing whether 3G access accelerates the process of “structural transformation,” in the sense of shifting employment away from agriculture and towards manufacturing and services, to create a modern economy.

To pursue these questions, we created a sample of 14 countries across a range of developmental stages. We divided these countries into smaller sub-national regions, such as districts, counties and municipalities. After restricting the sample to those sub-regions where all variables can be observed (2G and 3G coverage, employment data, etc.), our final sample consisted of 6802 regions and 16,069 region-years evaluated from the period 2000-2015. We then used this sample to draw a causal relationship between access to 3G internet and employment outcomes. However, establishing such a link has traditionally presented three key challenges.

First, the lack of reliable data across multiple low-income countries and especially over a longer period of time. We addressed this by utilizing data from IPUMS International, which collates nationally representative surveys and censuses across multiple countries and over time. This allowed us to construct key employment outcomes relevant to our study (such as labor force participation rates, types of employment, etc.) that were harmonized across all countries in our sample, and consistent over time.

Second, there was little available data on the expansion of 3G coverage, especially at a local or sub-national level. To address this issue, we used maps for 3G network coverage from 2006-2015 collected by Collins Bartholomew Mobile Coverage Explorer, which consist of 1×1 km binary grids that take the value of 1 if the cell region has 3G coverage and 0 if it does not. We then aggregated these to generate a (population-weighted) measure of 3G coverage for each sub-national region over time. 

Lastly, it can be difficult to identify a causal relationship between 3G internet and employment due to the endogenous expansion of 3G networks with economic development. For example, it is possible that regions with higher economic activity are also the ones that are more likely to get access to 3G internet. This is known as “reverse causality.” A common method in economics used to address this issue is an instrumental variable strategy (IV). 

In a nutshell, the IV strategy generates a plausible source of exogenous variation in the rollout of 3G internet that gives us a way to estimate its causal effects on employment. Following the literature, we used lightning strikes as an “instrument,” i.e., we argued that conditional on geographic factors (such as elevation, precipitation, etc.) the intensity of lightning strikes in an area affects the rollout of 3G network but does not affect employment outcomes directly. In addition, we also controlled for 2G coverage in our specifications so as to isolate the effects arising from the availability of 3G, as opposed to other factors that may have affected cell phone expansion more generally.

Overall, we found that expanded 3G coverage has increased the employment rates of both men and women and meaningfully increased female labor force participation rates. 

Expansion of 3G coverage also seems to have impacted the nature of work, but these effects are gendered. Men have transitioned out of their unpaid agricultural and service jobs into small, owner-owned enterprises in agriculture or wage jobs in the service sector. Women, on the other hand, are more likely to take up the unpaid agricultural jobs vacated by men. But, similar to men, they also start small agro-enterprises or work in service sector wage jobs.

Put together, our results indicate that, contrary to what has been hypothesized by policymakers and researchers, there is no compelling evidence that 3G expansion has accelerated the process of structural transformation, in the sense of reallocation of labor away from agriculture towards manufacturing and services. While 3G expansion has created additional (primarily wage) jobs in services, it has also allowed individuals (both men and women) to start small-scale businesses in both agriculture and services. In this sense, the expansion of 3G coverage has impacted the “type” of employment rather than the “sector” of employment. 

“However, the patterns we document are more consistent with the rise of the ‘gig-economy’ rather than ‘structural transformation'”

Our results are, to a certain extent, consistent with the widespread optimism regarding the economic effects of the information and communications technologies (ICT): 3G increases female labor force participation and employment rates for both men and women. However, the patterns we document are more consistent with the rise of the “gig-economy” rather than “structural transformation.” 

3G (and now 4G and 5G) networks have made interpersonal communications faster and cheaper. The decline of information, communications, and transactions costs has led to new business models and employment opportunities. At the same time, it has changed the nature of work, making flexible work arrangements both more feasible and more valuable. It is therefore not surprising that 3G expansion has boosted labor force participation and employment of women who tend to place a particularly high value on flexibility, allowing them to combine work and family. Along the same lines, the changing nature of work seems to be boosting small scale entrepreneurship as manifested in our data in the increasing number of individuals who start their own businesses when 3G becomes available in their area.

Whether these developments have increased the welfare of the affected individuals remains an open question. We note that one of our findings reveals that women often take up unpaid jobs (especially in agriculture) vacated by men who move to better, paid, opportunities. It is unclear whether this presents an opportunity for women in the dynamic sense (as a first step towards paid work in the future) or an additional burden (double duty at unpaid work and home). Assessing such questions will require much more research and information from micro data in individual countries, including labor force surveys that provide information on wages and employment terms, and time-use surveys. Such work could provide insights into the specific mechanisms generating the patterns we document as well as the likely long-term impacts of new technologies on the lives of people in LMICs.

The authors thank Vanika Mahesh, communications Intern at the Yale Economic Growth Center, for significant editorial assistance.

Articles represent the opinions of their writers, not necessarily those of the University of Chicago, the Booth School of Business, or its faculty.