Mobile internet is changing employment in developing countries, but not always as expected – ProMarket

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

Reducing global poverty will require expanding Internet connectivity – this case has been argued by many. For example, in advocating for an agenda to achieve universal internet access by 2030, former British Prime Minister Tony Blair said: Eradicate extreme poverty, solve the global education crisis, build better health systems and respond effectively pandemics all require connectivity. In launching an Internet Poverty Index, researchers from the World Data Lab have argued that access to the Internet 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 existing scholarship and policy discussion has focused on the potential of Internet technology to start the development process in the LMICs. An influential study evaluated the impact of high-speed fixed broadband Internet access on socio-economic outcomes. However, understanding of the impact of mobile Internet, which is much more accessible and much more prevalent in LMICs, has been limited.

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

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

To answer these questions, we created a sample of 14 countries across a number of development stages. We have divided these countries into smaller subnational 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 assessed from the period 2000- 2015. We then used this sample to draw a causal relationship between 3G Internet access and employment outcomes. However, establishing such a link has traditionally presented three key challenges.

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

Second, little data was available on the expansion of 3G coverage, especially at the local or subnational level. To solve this problem, we used the 3G network coverage maps from 2006 to 2015 collected by Collins Bartholomew Mobile Coverage Explorer, which consist of 11 km binary grids that take the value of 1 if the cell region has 3G coverage and 0 if it doesn’t. We then aggregated them to generate a population-weighted measure of 3G coverage for each subnational region over time.

Finally, 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, regions with higher economic activity may also be the ones most likely to access 3G internet. This is known as reverse causation. A common method in economics used to address this problem is an instrumental variable (IV) strategy.

Simply put, strategy IV generates a plausible source of exogenous variation in the introduction of 3G Internet that gives us a way to estimate its causal effects on employment. Following the literature, we have used lightning as a tool, i.e. we have argued that subject to geographical factors (such as elevation, rainfall, etc.) the lightning intensity in an area affects the implementation of the 3G network but does not directly affect the results employment. Additionally, we also controlled for 2G coverage in our specifications in order to isolate the effects of 3G availability as opposed to other factors that may have influenced the expansion of mobile phones more generally.

Overall, we found that expanding 3G coverage increased both men’s and women’s employment rates and significantly increased female labor force participation rates.

The expansion of 3G coverage also appears to have affected the nature of the work, but these effects are gendered. Men moved from their unpaid jobs in agriculture and services to small owner-owned businesses in agriculture or paid jobs in the service sector. Women, on the other hand, are more likely to fill the unpaid agricultural jobs vacated by men. But, like men, they also set up small farm businesses or hold paid jobs in the service sector.

Taken together, our results indicate that, contrary to what policymakers and researchers have assumed, there is no convincing evidence that the expansion of 3G has accelerated the process of structural transformation, in the sense of reallocating labor from agriculture towards manufacturing and services. While the expansion of 3G has created additional (mainly wage) jobs in services, it has also enabled individuals (both men and women) to set up small-scale businesses in both agriculture and services. In this sense, the expansion of 3G coverage has affected the type of employment rather than the sector of employment.

However, the models we document are more consistent with the rise of the gig economy than structural transformation’

Our findings are, to some extent, consistent with widespread optimism about the economic effects of information and communication technologies (ICT): 3G increases female labor force participation and employment rates for both men and women women. However, the models we document are more consistent with the rise of the gig economy than structural transformation.

3G (and now 4G and 5G) networks have made interpersonal communications faster and cheaper. The decline in information, communication and transaction costs has led to new business models and employment opportunities. At the same time, it has changed the nature of work, making flexible working arrangements more feasible and more valuable. It is therefore not surprising that the expansion of 3G has increased the labor force participation and employment of women who tend to place a particularly high value on flexibility, enabling them to balance work and family. Along the same lines, the changing nature of work appears to stimulate small-scale entrepreneurship, as manifested in our data in the growing number of individuals starting their own businesses as 3G becomes available in their area.

Whether these developments have increased the well-being of those affected remains an open question. We note that one of our findings reveals that women often take on unpaid jobs (especially in agriculture) vacated by men who move on to better paying opportunities. It is unclear whether this represents an opportunity for women in a dynamic sense (as a first step towards paid work in the future) or an additional burden (double duty at unpaid work and at home). Assessing such questions will require much more research and information from microdata in individual countries, including labor force surveys that provide information on wages and working conditions, 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 people’s lives in LMICs.

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

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

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