Government AI Readiness, Resource Dependence, and Labor Productivity: A Comparative Panel Analysis of 14 Post-Soviet and Comparator Economies, 2021–2024

This paper examines the association between government artificial intelligence (AI) readiness and labor productivity in 14 post-Soviet and comparator economies of the Caucasus, Central Asia, and Central and Eastern Europe over 2021–2024 (56 country-year observations) and asks whether the association differs with resource dependence and institutional quality. We estimate two-way fixed-effects models on World Bank and Oxford Insights data, base inference on a null-imposed wild cluster bootstrap, and assess robustness with leave-one-country-out estimation. Within countries, a one-point increase in the Government AI Readiness Index is associated with 0.32 percent lower labor productivity at the sample-mean oil rent (bootstrap p = 0.013) and 0.40 percent lower productivity at zero oil rents (p = 0.014). The zero-rent association is significant at the 10 percent level in all 14 leave-one-out samples, and the readiness association also holds in the 2021–2023 subsample. The interaction with pre-period (2021) oil rents has a positive point estimate but is only weakly significant (p = 0.085), depends on Azerbaijan and Kazakhstan, and is not robust. We find no significant variation with government effectiveness. The estimates are associations with government readiness, not causal effects of AI use; they are consistent with, but do not test, an implementation-lag reading of general-purpose technologies.