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We identify key drivers of digital adoption, estimate fiscal costs to provide internet subsidies to households, and calculate social dividends from digital adoption. Using cross-country panel regressions and machine learning, we find that digital infrastructure coverage, internet price, and usability are the most statistically robust predictors of internet use in the short run. Based on estimates from a model of demand for internet, we find that demand is most price responsive in low-income developing countries and almost unresponsive in advanced economies. We estimate that moving low-income developing and emerging market economies to the levels of digital adoption in emerging and advanced economies, respectively, will require annual targeted subsidies of 1.8 and 0.05 percent of GDP, respectively. To aid with subsidy targeting, we use microdata from over 150 countries and document a digital divide by gender, socio-economic status, and demographics. Finally, we find substantial aggregate and distributional gains from digital adoption for education quality, time spent doing unpaid work, and labor force participation by gender.

Colombia --- Macroeconomics --- Economics: General --- Labor --- Women''s Studies' --- Foreign Exchange --- Telecommunications --- Taxation and Subsidies: Externalities --- Redistributive Effects --- Environmental Taxes and Subsidies --- National Government Expenditures and Related Policies: General --- Labor Standards: Labor Force Composition --- Education: General --- Aggregate Factor Income Distribution --- Economics of Gender --- Non-labor Discrimination --- Economic & financial crises & disasters --- Economics of specific sectors --- Labour --- income economics --- Education --- Gender studies --- women & girls --- Currency --- Foreign exchange --- Labor force participation --- Income --- National accounts --- Women --- Gender --- Purchasing power parity --- Currency crises --- Informal sector --- Economics --- Labor market --- Income economics --- Women & girls --- Women's Studies