Investment Regime Changes in Emerging Markets

This research analyzed Foreign Direct Investment (FDI) flows in fifty emerging market economies to identify distinct investment regimes through advanced statistical modeling. The study employed Markov Switching Models (MSM), threshold regression analysis, and Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroskedasticity (DCC-GARCH) frameworks, analyzing quarterly data from 2010 to 2023 sourced from the United Nations Conference on Trade and Development (UNCTAD), the World Bank, and the Organisation for Economic Co-operation and Development (OECD) databases. Three distinct FDI regimes were identified: stable periods (2.84% of GDP), volatile periods (1.56% of GDP), and growth phases (3.92% of GDP). Critical economic thresholds were discovered at 2.45% GDP growth and 3.75% interest rates, where investment behavior fundamentally changes. The Dynamic Conditional Correlation analysis revealed time-varying relationships between FDI and macroeconomic variables, with correlations ranging from 0.225 to 0.685 for GDP growth and from 0.285 to 0.745 for political stability. Statistical validation through Phillips–Perron, Hansen, and Brock–Dechert–Scheinkman (BDS) tests confirmed the presence of non-linear dependencies and structural breaks in FDI patterns. The results challenge one-size-fits-all policy approaches, suggesting tailored strategies based on regime identification for managing FDI flows in emerging markets under different economic conditions.