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### Governor Cook Highlights Nontraditional Data and Machine Learning in Macroeconomics Summit

Good morning, and welcome to the 5th annual conference on “Nontraditional Data, Machine Learn…

Welcome to the fifth annual conference on “Nontraditional Data, Machine Learning, and Natural Language Processing in Macroeconomics.” This event serves as a platform for academics and practitioners to delve deep into enhancing the conceptual framework that guides macroeconomic policymakers in a rapidly evolving information landscape and technological advancements. The aim is to drive improvements that can lead to more favorable economic outcomes.

The inaugural conference took place at the Federal Reserve in 2019, and since then, it has evolved into a global collaboration involving academics, central banks, analytical organizations, and international institutions. Subsequent editions have been hosted by esteemed institutions such as the Swedish Riksbank, Bank of Canada, and various Italian and Canadian banks. The partnership between the Central Bank Research Association and the Economics with Nontraditional Data and Analytical Tools software further extends the conference’s global reach.

The collaborative efforts fostered by this event and its successors, both on a global and local scale, have brought together around 90 in-person attendees from 30 different firms and foreign central banks. The synergy between data providers, policymakers, and experts utilizing cutting-edge methodologies is crucial in leveraging new data sources and emerging techniques to gain deeper insights into the economy, a shared objective that underscores the importance of cooperation between statistical agencies and policy institutions.

To fulfill the dual mandate of maximizing employment and maintaining price stability, the Federal Reserve continually evaluates the economic landscape, assesses economic activity, and gauges associated risks. The utilization of non-traditional, high-frequency data has been instrumental in understanding the real-time impacts of events like the COVID-19 pandemic and their financial implications. In this dynamic environment, a diverse set of tools, including machine learning and text analysis, are employed to extract valuable insights from the vast array of available data, complementing traditional statistical methods.

This conference holds significant importance for the Federal Reserve and other central banks, enabling the generation of more accurate assessments of the evolving economic landscape through timely data and advanced analytical techniques. The maturity of utilizing unconventional data sources and methodologies for research and policymaking is evident from the breadth and depth of studies featured in the agenda.

The lineup of distinguished speakers, including Jed Kolko, Julapa Jagtiani, Arthur Turrell, Hal Varian, Jesus Fernandez-Villaverde, Sydney Ludvigson, Stephen Hansen, and Chiara Farronato, will delve into the opportunities and challenges posed by nontraditional data, machine learning, and artificial intelligence in both public and private sectors. Furthermore, discussions on the advancements in relational AI, particularly in “explainable AI,” will shed light on the practical applications and implications for financial research and policy formulation.

The impact of relational AI tools on communication with central banks and the analysis of central bank communications through natural language processing techniques will be explored by speakers like Christopher Neely, Clara Vega, Xin Zhang, and Xu Zhang. Additionally, the influence of social media on economic outcomes, as studied by Corbin Fox, highlights the evolving landscape of information consumption and communication in today’s society.

The integration of machine learning techniques in economic modeling, as discussed by Philippe Goulet Coulombe, Jol Marbet, and Yucheng Yang, showcases the advancements in modeling economic variables’ volatility and understanding the microeconomic effects of policies. The progress in natural language processing and machine learning has enhanced the ability to forecast and analyze a wide range of economic indicators, a topic that will be further explored in upcoming sessions.

In conclusion, this conference aims to stimulate insightful discussions on the value of nontraditional data and innovative methodologies for economic analysis. Attendees are encouraged to continue conversations beyond the event, fostering collaboration opportunities to delve deeper into these exciting new tools.

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Last modified: February 6, 2024
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