Macroeconomic Policy

Macroeconomic policy research aims to understand and optimize government interventions influencing the overall economy, focusing on fiscal and monetary policies' effects on various economic indicators. Current research heavily utilizes machine learning techniques, such as gradient boosting and double machine learning, alongside econometric models to analyze complex relationships between policies (e.g., interest rate changes, fiscal incentives) and outcomes (e.g., investment, stock prices, fund returns). This work emphasizes incorporating micro-level agent behavior and expectations into macroeconomic models, improving the accuracy of policy predictions and potentially leading to more effective policy design. The improved understanding of these complex interactions has significant implications for both economic forecasting and the development of more targeted and effective economic policies.