Resolving the Credit-Growth Puzzle through the Dynamic Prescriptive Economics (DPE) Framework

The dataset and accompanying Python codes have been developed as part of the research project “From Thresholds to Trajectories: A Dynamic Prescriptive Economics (DPE) Framework for Enhancing Institutional Effectiveness in the Credit-Growth Nexus.” They capture normalized measures of institutional quality, credit-to-GDP ratios, and economic growth across a panel of 121 developing countries, enabling an in-depth analysis of the nonlinear and dynamic interactions between credit expansion and growth. The codes facilitate both visualization and empirical testing of the DPE framework, allowing for threshold-based regime analysis, scenario simulations, and policy-oriented diagnostics. By integrating dynamic trajectories rather than static thresholds, this dataset and computational framework provide a robust foundation for assessing institutional effectiveness in shaping sustainable credit-growth outcomes.