variables).<sup>20</sup> We also run our main specification controlling for self-reported access to the internet to check the robustness of the analysis. This means the coefficient 1 captures changes in outcomes at the household or individual level, controlling for unobserved household characteristics and accounting for changes over time for both treated and untreated households (i.e., a difference-in-difference estimator). In order to account for ββ the existence of heteroskedasticity and serial correlation, we use a cluster-robust estimator with clustering at the household level.

Outcomes, mechanisms and heterogeneous effects In terms of the dependent variable i , we use two broad outcomes to measure household welfare; consumption and poverty. We explore breakdowns of consumption by looking at food and non-food ii consumption separately and we apply a logarithmic transformation due to large skewness and kurtosis YY values. For poverty, we use two measures; the first takes a value of 1 if the household per capita consumption is less than the international extreme poverty line of $1.90 per day (measured in purchasing-power-parity) and the second takes a value of 1 if the household per capita consumption is below the low-middle income international poverty line of $3.20 per day, which includes Nigeria.<sup>21</sup> We also consider two mechanisms through which mobile broadband translates into improvements (if any) in welfare: labor market outcomes and prices. We examine the impact of 3G/4G technologies on four different labor market outcomes: (i) labor force participation, (ii) farm self-employment, (iii) salaried/wage employment, and (iv) non-farm self-employment.<sup>22</sup> A predominant share of the employed population (about 80 percent) are self-employed working in agriculture or in nonfarm household enterprises. The effects of mobile broadband technologies on wage/salaried employment are particularly of interest, as a shift away from self-employment to more productive wage/salaried employment in private and public services is deemed as one potential way to reduce poverty rates across the country (World Bank 2015).

Besides its effects on the labor market, mobile broadband can also help ease information asymmetry problems, improving price information and making price setting mechanisms more efficient. This may induce lower prices (see for example Aker and Mbiti 2010). The internet may also impact prices if it induces greater competition in the marketplace, through reductions in transaction and information costs, which facilitate trade and firm entry. To test this potential causal channel, we assess the impact of 3G/4G coverage on the unit prices of food products by estimating the following model:

> 20 We also ran an alternative model where we restricted our sample to households that had access to 2G coverage across all three waves and the results were consistent.

> 21 <u>https://blogs.worldbank.org/developmenttalk/richer-array-international-poverty-lines.</u>

> 22 For this analysis, labor force participation is defined as those working-age (15-64) individuals who were employed or unemployed (looking for a job) in the past 7 days. Farm self-employment refers to working-age individuals who worked on a farm owned or rented by their own household members during the past 7 days and non-farm self-employment includes working-age individuals who worked on their own account during the last 7 days. Lastly, working-age individuals who worked for someone who was not their family members during the last 7 days were considered to be salaried/wage workers.

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