Effects of sectoral and sub-sectoral foreign direct investment inflows on services exports: cross-country evidence from a dynamic panel model

Purpose This study aims to investigate the impact of sectoral (manufacturing and services) and sub-sectoral (financial and non-financial services) foreign direct investment (FDI) inflows on services exports across countries at different income levels using the longest available time span from 1990 to 2019. Design/methodology/approach This study uses the Driscoll–Kraay standard errors method to account for potential cross-sectional dependence and heteroskedasticity. To further assess the robustness of the findings, the dynamic panel Blundell–Bond system GMM estimator is also employed. Findings The results demonstrate a consistent and robust positive relationship between services FDI and services exports across all income groups, underscoring the strategic importance of promoting FDI inflows into the services sector. Furthermore, the analysis reveals a differentiated impact of financial and non-financial services FDI across income categories. Specifically, financial services FDI exerts a more significant influence on services export performance in upper-middle- and high-income countries, whereas non-financial services FDI is more strongly associated with services exports in low- and lower-middle-income economies. Additionally, the positive and statistically significant relationship between manufacturing FDI and services exports suggests the presence of cross-sectoral effects. Practical implications This study may serve as a foundational resource for policymakers and governments in formulating income-sensitive and sector-specific policy strategies essential for maximizing the benefits of FDI in promoting the development of services exports. Originality/value To the best of the authors’ knowledge, there is hardly any study that has explored the impact of FDI inflows on services exports at both the sectoral (manufacturing and services) and sub-sectoral (financial and non-financial services) levels across different income groups. This study addresses a gap in the existing literature by using robust methods, Driscoll–Kraay standard errors and the system GMM estimator to address key econometric issues.