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Table 6. System GMM estimates (dependent variable: gini)
Variable Coefficient
Gini (t−1) 0.971*** (0.075)
internet −0.021 (0.021)
internet² 0.00005 (0.0002)
ln(gdppc) 0.373 (2.048)
Controls Yes
Observations 1,054
Instruments 36
AR(2) z = 0.83 (p = 0.409)
Hansen J χ²(6) = 6.45 (p = 0.374)
Note: ***p < 0.01. Windmeijer-corrected SE.
Two-step estimator via xtabond2 (Roodman, 2009).
5. Conclusion
This paper estimates a statistically significant U-shaped (Digital Kuznets Curve)
relationship between internet penetration and the Gini coefficient across a global panel
of 128 countries over 2000–2022, with a global turning point at approximately 62 percent
(z = 2.55, p = 0.011). The turning point is reached earlier in high-income countries (≈52%)
than in middle-income economies (≈66%), consistent with institutional mediation. Fixed
broadband exhibits a significantly lower turning point (≈13 per 100), while mobile cellular
subscriptions show no significant nonlinearity — identifying cost barriers as the
mechanism driving technology-specific distributional dynamics. These findings contribute
the first globally applicable, cross-sectional dependence-robust estimate of the internet–
inequality turning point to the empirical literature, and quantify the income-group-
specific policy window within which internet expansion serves as an instrument of
inclusive development. Future research should exploit exogenous variation from
infrastructure rollouts to address the causal identification limitation, extend the sample
post-2022 to capture generative AI diffusion effects, and examine the role of
complementary redistribution policies in reshaping the post-threshold DKC trajectory.

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