FINANCIAL RISK AND RETURN ANALYSIS IN MEGA PROJECTS: A PANEL DATA APPROACH WITH ECONOMETRIC MODELING

Mega project, defined as infrastructure investments exceeding USD one billion, play a central role in national development but often face significant financial risks. This study explores the dynamic relationship between macroeconomic risk factors and return on investment (ROI) in mega projects using a panel data econometric approach. A balanced dataset from 2000 to 2024 was constructed, covering five economies with significant mega infrastructure investment: Turkey, China, the United States, India, and Germany. The analysis incorporates both internal project risks (cost overruns, completion delays) and external macroeconomic shocks (exchange rate volatility, inflation, interest rates). Representative infrastructure projects in transport, energy, and urban sectors were selected based on official national data and international financial databases. Pedroni cointegration tests confirmed the existence of long-term equilibrium relationships, justifying the application of a panel Generalized Method of Moments (GMM) model to address endogeneity, heterogeneity, and dynamic effects. The results indicate that a 1% increase in budget allocation leads to a 0.21% rise in ROI (p < 0.001), while cost overruns are associated with a 0.84% ROI increase per 1% overspend (p = 0.003), suggesting potential value in strategic overspending. In contrast, a 1% increase in exchange rate volatility reduces ROI by 0.69% (p < 0.001). No significant effects were found for inflation or completion delays. These findings reflect aggregated financial behavior rather than individual project cases, offering generalizable insights into mega project finance. The study contributes to the literature by constructing a risk-adjusted, multi-country econometric model and offers policy guidance for enhancing financial resilience in large-scale infrastructure investments. © Mustafa Özyeşil, Havane Tembelo, 2025.