{
  "title": "Determinants and Social Dividends of Digital Adoption",
  "publication": "IMF Working Papers, March 17, 2023",
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  "summary": "We identify key drivers of digital adoption, estimate fiscal costs to provide internet subsidies to households, and calculate social dividends from digital adoption.",
  "sections": [
    {
      "heading": "Key findings on drivers of digital adoption",
      "content": "- Digital infrastructure coverage, internet price, and usability are the most statistically robust predictors of internet use in the short run.\n- Using cross-country panel regressions and machine learning, these three factors emerge as primary determinants of internet use."
    },
    {
      "heading": "Demand elasticity and heterogeneity",
      "content": "- Demand for internet is most price responsive in low-income developing countries and almost unresponsive in advanced economies.\n- Microdata from over 150 countries document a digital divide by gender, socio-economic status, and demographics."
    },
    {
      "heading": "Fiscal cost estimates for subsidies",
      "content": "- Moving low-income developing economies to the levels of digital adoption in emerging economies will require annual targeted subsidies of 1.8 percent of GDP.\n- Moving emerging market economies to the levels of digital adoption in advanced economies will require annual targeted subsidies of 0.05 percent of GDP."
    },
    {
      "heading": "Social dividends and distributional effects",
      "content": "- Substantial aggregate and distributional gains from digital adoption are found for:\n  - Education quality.\n  - Time spent doing unpaid work.\n  - Labor force participation by gender."
    },
    {
      "heading": "Methods and data sources",
      "content": "- Analysis combines cross-country panel regressions, machine learning, and a model of demand for internet.\n- Microdata spanning over 150 countries are used to analyze within-country heterogeneity and to aid subsidy targeting.\n\nIMF Working Paper — Utkarsh Kumar, David Amaglobeli, Mariano Moszoro; March 17, 2023.\n\n---\n\n Content in this bundle\n\n- Working Paper\n  - Working Paper (Markdown version){rel=\"alternate\" type=\"text/markdown\"}\n  - Working Paper (PDF){rel=\"external\" type=\"application/pdf\"}\n\n---\n\nSource: https://www.imf.org/en/publications/wp/issues/2023/03/17/determinants-and-social-dividends-of-digital-adoption-531083"
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    "Authors: Utkarsh Kumar, David Amaglobeli, Mariano Moszoro",
    "Published: March 17, 2023",
    "Series: IMF Working Papers",
    "DOI: https://doi.org/10.5089/9798400237997.001",
    "Digital infrastructure coverage, internet price, and usability are the most statistically robust predictors of internet use in the short run.",
    "Using cross-country panel regressions and machine learning, these three factors emerge as primary determinants of internet use.",
    "Demand for internet is most price responsive in low-income developing countries and almost unresponsive in advanced economies.",
    "Microdata from over 150 countries document a digital divide by gender, socio-economic status, and demographics.",
    "Moving low-income developing economies to the levels of digital adoption in emerging economies will require annual targeted subsidies of 1.8 percent of GDP.",
    "Moving emerging market economies to the levels of digital adoption in advanced economies will require annual targeted subsidies of 0.05 percent of GDP.",
    "Substantial aggregate and distributional gains from digital adoption are found for:",
    "Analysis combines cross-country panel regressions, machine learning, and a model of demand for internet.",
    "Microdata spanning over 150 countries are used to analyze within-country heterogeneity and to aid subsidy targeting.",
    "**Working Paper**"
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