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SMU Data Science Review

Abstract

The Federal Funds Rate (FFR) is a tool used by the Federal Reserve to set monetary policy on borrowing costs for consumers and businesses. The Fed’s primary motivation with the FFR is to control macroeconomic factors such as inflation and unemployment. Over time, policy stances for the Fed have varied in response to events such as the Great Recession, and more recently the COVID-19 pandemic. In light of the Fed’s actions following these events, there is intensified debate over which macroeconomic factors should be prioritized, and what magnitude of change is sufficient to warrant action. Additionally, when action is taken (e.g., an increase in FFR), it is important to understand whether such action is consistent with historical trends based on the data, or whether the change resulted from a shift in policy stance. This research provides quantitative analysis and insight into the factors that drive the Fed to act. It also compares various time series modeling techniques to identify the most effective method and combination of variables for predicting the FFR.

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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