We provide a quantitative synthesis of the literature studying the effect of foreign direct investment (FDI) on the productivity of locally owned firms in the Czech Republic. To this end, we collect 332 previously reported estimates and use Bayesian model averaging to address model uncertainty. We find no evidence of publication bias, i.e., no sign of selective reporting of estimates that are statistically significant and show an intuitive sign. Our results suggest that more advanced techniques yield substantially larger positive effects (FDI spillovers). When placing more weight on estimates that solve important identification problems in the literature (such as using data on existing linkages between firms instead of approximations based on input-output tables), we find that, as of 2018, a 10-percentage-point increase in foreign presence is likely to lift the productivity of domestic firms by 11%. The effect is even larger for joint ventures, reaching 19%.

Reference: Mojmir Hampl, Tomas Havranek, and Zuzana Irsova (2019), "Foreign Capital and Domestic Productivity in the Czech Republic: A Meta-Regression Analysis." Applied Economics, forthcoming.