How Central Banks Control Inflation Monetary Policy, Interest Rates, and the Emerging Role of Artificial Intelligence
0 viewsAbstract
This study investigates the mechanisms through which central banks regulate inflation using traditional monetary policy instruments and explores the emerging capacity of Artificial Intelligence (AI) to enhance policy effectiveness. Utilizing a mixed qualitative-quantitative approach, the research analyzes macroeconomic data from 2005 to 2024 to evaluate the application of the Taylor Rule, the delayed inflationary impacts of unconventional tools like quantitative easing (QE), and the historical relationship between policy interest rates and inflation trends. Furthermore, the study compares the predictive accuracy of machine learning architectures (Deep Neural Networks and Random Forests) against traditional autoregressive (AR) models. The empirical findings confirm a strong inverse relationship between policy rates and inflation, affirming that central banks continue to rely fundamentally on interest rate adjustments and inflation targeting to anchor market expectations. Notably, AI-based models consistently outperformed traditional econometric models in short-term forecasting across multiple economic phases by successfully identifying non-linear relationships among macroeconomic variables. The study concludes that while AI will not replace existing institutional frameworks, it serves as a highly effective complementary tool that significantly improves forecasting precision, enabling central banks to proactively navigate and mitigate inflationary pressures in an increasingly data- driven global economy.
Keywords
Artificial Intelligence (AI), Central Banks, Economic Forecasting, Inflation Targeting, Macroeconomics, Monetary policy, Quantitative Easing, Taylor Rule