Does Government Size Affect Per-Capita Income Growth? A Hierarchical Meta-Regression Analysis

Abstract

Abstract:We conduct a hierarchical meta-regression analysis to review 87 empirical studies that report 769 estimates for the effects of government size on economic growth. We follow best-practice recommendations for meta-analysis of economics research, and address issues of publication selection bias and heterogeneity. When size is measured as the ratio of total government expenditures to GDP, the partial correlation between government size and per-capita GDP growth is negative in developed countries, but insignificant in developing countries. When size is measured as the ratio of consumption expenditures to GDP, the partial correlation is negative in both developed and developing countries, but the effect in developing countries is less adverse. We also report that government size is associated with less adverse effects when primary studies control for endogeneity and are published in journals and more recently, but it is associated with more adverse effects when primary studies use cross-section data. Our findings indicate that the relationship between government size and per-capita GDP growth is context-specific and likely to be biased due to endogeneity between the level of per-capita income and government expenditures. JEL code: O40, H50, C1Keywords: Economic growth; Government size; Government expenditure; Government consumption; Meta-analysis; Evidence synthesis Acknowledgements: We would like to thank two anonymous reviewers of the Program Committee of MAER-Net Colloquium 2015 in Prague; and the participants in the conference for helpful comments.

Does intellectual property protection deliver economic benefits? A multi‐outcome meta‐regression analysis of the evidence

“…Moreover, most meta‐analysis studies focusing on a single outcome either overlook the issue of within‐study dependence or take account of the latter through clustered standard errors (e.g., Alptekin & Levine, 2012). Although some meta‐analysis studies take account of within‐study dependence and between‐study heterogeneity through multi‐level modeling (e.g., Awaworyi Churchill et al., 2017a; Ugur et al., 2018; Ugur et al., 2020; Ugur et al., 2016), the two‐level meta‐regression models in these studies are inadequate for synthesizing the evidence on the economic benefits of IP protection, where we have multiple effect‐size estimates for multiple outcomes that are theoretically related.…”

“…To the best of our knowledge, most meta‐analysis studies in economics have so far addressed within‐study dependence and between‐study heterogeneity through clustered standard errors (e.g., Alptekin & Levine, 2012; Awaworyi Churchill & Yew, 2018; Lichter et al., 2015) or two‐level hierarchical meta‐regression models (e.g., Awaworyi Churchill et al., 2017a; Balima et al., 2020; Ugur et al., 2018; Ugur et al., 2020). Nevertheless, issues of dependence and heterogeneity that may arise at higher levels have not been addressed.…”