Therefore, in the second part of the analysis, I use an instrumental variable regression (IV) strategy that leverages regional convergence in mobile network expansion induced by harmonization of telecom policies across countries in the region as an instrument. In essence, I use the predicted mobile network penetration in other countries in the same geographic region as instrument for the district level mobile network penetration. The instrument follows the approach of Acemoglu et al. (2019) and Acemoglu et al. (2021) who used regional waves in democratization as an instrument for democracy in studies on the effects of democracy on GDP and support for democratic institutions. The exclusion restriction assumption behind the instrument used in this paper is that conditional on controls including measures of trade and economic shocks at the regional level, district and year fixed effects, mobile network penetration in other countries in the same region affects economic growth at the district level only through its effect on mobile connectivity in the district. Further, to supplement the main IV analysis, I construct another instrument by interacting the predicted regional mobile coverage rates with quintiles of lightning intensity at the district level and estimate an additional IV regression, the results of which confirm the baseline IV results. The motivation behind the second instrument is that the effect of regional harmonization of telecom policies on mobile penetration at the local level should be high in places where mobile operators would otherwise not extend mobile coverage due to the effect of lightning strikes which causes destruction to digital infrastructure (Andersen et al., 2012; Manacorda and Tesei, 2020; Guriev et al., 2021),<sup>2</sup> relative to places with low lightning strikes and hence lower cost of mobile network extension. Thus, even if individually, lightning intensity and the predicted regional mobile penetration rate may not satisfy the exclusion restriction assumption, their interaction(s) may plausibly suffice.

Three main findings emerge from the paper. First, mobile phones exert a positive impact on economic growth at the subnational level. A 1 percentage point (pp) increase in mobile network penetration increases the growth rate in nightlight intensity by 0.0596 –0.0777 pp. To understand how this translates into GDP growth, I rely on Henderson et al. (2012) who estimate a GDP-nightlights elasticity of 0.3. Combining these estimates, findings from the paper suggest a GDP growth – mobile penetration elasticity of 0.018 – 0.023. In other words, moving a district from no mobile network coverage to full coverage (100 pp) increases GDP growth by 1.8 pp – 2.3 pp. Secondly, while mobile broadband (3G/4G) penetration spurs economic activities in all income groups, the development effects of 2G penetration are largely present in developing countries. Finally, I find that the economic effects of expansion in mobile network connectivity are more pronounced in countries that hitherto had limited access to fixed line telephone in2Lightning strikes contain about a billion volts of electricity and have been known to cause severe destruction to electrical and digital infrastructure around the world, thereby increasing the cost associated with the diffusion of digital technologies (Andersen et al., 2012; Zeddam and Day, 2014; Martin, 2016).

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