Refugee inflows and macroeconomic performance: evidence from a cross-country panel (2000-2023)

The inflow of refugees has already become a stable feature of the world economy, with dire fiscal, social, and macroeconomic consequences for host nations. Even though the discourse on the effect of the arrival of refugees has been largely defined in the humanitarian context, over the years, the economic consequences of the given phenomena have been contested. This study analyzes the macroeconomic impacts of refugee inflows in 17 countries that received those between 2000 and 2023, in terms of growth performance measures and stability measures. Second-generation panel econometric methods consisting of a fixed-effects model and Driscoll-Kraay standard errors (DKSE) were used to undertake the analysis to deal with heteroskedasticity, autocorrelation, and cross-sectional dependence. The robustness measure was applied using Fully Modified Ordinary Least Squares (FMOLS), Canonical Cointegrating Regression (CCR), and Fixed-Effects Ordinary Least Squares (FE-OLS). The findings show that the impact of the inflow of refugees on the growth of GDP is statistically significant, negative, and mainly due to fiscal strains, unemployment influence, and increasing inflation. On the other hand, trade openness continuously increases economic performance, whereas inflation, unemployment, and excessive government expenditure are detrimental to performance. Causality analysis reveals that, instead of having a direct effect on GDP, refugee arrivals have an indirect effect on GDP via the labor market and fiscal effects. These findings highlight that refugee inflows are structural processes with long-term economic impact. The implications of the policy are the necessity to enhance the integration of the labor market, shift fiscal resources towards productive spheres, maintain macroeconomic stability, and foster the idea of burden sharing to reconcile humanitarian demands with economic sustainability.

© 2026 Ridwan, Antor, Ko, Leung, Doğan and Ming.