Internet Use and Food Production: The Moderating Role of Institutional Quality in a Global Panel of 139 Countries


KAYA T.

Sustainability (Switzerland), cilt.18, sa.17, 2026 (SCI-Expanded, SSCI, Scopus)

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 18 Sayı: 17
  • Basım Tarihi: 2026
  • Doi Numarası: 10.3390/su18178839
  • Dergi Adı: Sustainability (Switzerland)
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Social Sciences Citation Index (SSCI), Scopus, CAB Abstracts, Geobase, INSPEC
  • Anahtar Kelimeler: control of corruption, digital connectivity, food production, government effectiveness, institutional quality, internet use, panel data
  • Çukurova Üniversitesi Adresli: Evet

Özet

Internet connectivity has expanded rapidly across countries, but its relationship with food production may depend on institutional conditions. This study examines Internet use, institutional quality, and food production using a balanced panel of 139 countries from 2002 to 2022. The analysis uses Fixed Effects models with country and year effects and Driscoll–Kraay standard errors. The direct coefficient of Internet use is not statistically significant. Government Effectiveness is positively associated with food production, while the direct coefficient of Control of Corruption is not statistically significant. The interactions of Internet use with both institutional indicators are negative and statistically significant. Marginal effects also vary across the institutional distribution. They are more positive at lower institutional levels, become insignificant at intermediate values, and turn negative at higher levels. The interaction results remain significant in several robustness checks, including models using mobile subscriptions, but are not reproduced with fixed broadband, first-difference models, CS-DL, or CCE-MG estimation. The findings indicate a conditional relationship between Internet use and food production, but this pattern is sensitive to the measure of connectivity and estimation method. The results are interpreted as associations rather than causal effects.