Good Morning and Welcome Remarks: Embracing Nontraditional Data and Advanced Methodologies in Macroeconomics
A New Era of Economic Analysis
Distinguished guests, esteemed colleagues, and fellow economic enthusiasts, I extend a warm and heartfelt welcome to each of you as we gather for the 5th annual conference on “Nontraditional Data, Machine Learning, and Natural Language Processing in Macroeconomics.” Today marks a momentous occasion as we delve into the transformative power of nontraditional data and innovative methodologies in shaping the future of macroeconomic analysis.
The Genesis and Evolution of the Conference: A Collaborative Endeavor
The inaugural edition of this conference, hosted by the Federal Reserve in 2019, has blossomed into an international partnership, a testament to the growing recognition of the significance of these emerging fields. This collaborative effort, jointly organized with the Central Bank Research Association and the Economics with Nontraditional Data and Analytical Tools program, underscores our shared commitment to driving progress and fostering interdisciplinary dialogue.
Grateful Acknowledgments and the Importance of International Partnerships
On behalf of the organizing committee, I express our profound gratitude for the international and domestic partnerships that have emerged from this event and its predecessors. The in-person attendance of approximately 90 participants, representing 30 agencies and foreign central banks, exemplifies the global reach and impact of this conference. Your presence here today is a testament to the collective desire to advance our understanding of the economy and its intricate complexities.
Cooperation as a Cornerstone for Better Understanding the Economy
As we embark on this journey of exploration, I want to emphasize the paramount importance of cooperation among statistical agencies, policymaking institutions, and researchers employing cutting-edge methodologies. This collaboration is essential in achieving our shared goal: a deeper understanding of the economy. By pooling our expertise and resources, we can collectively navigate the evolving data landscapes and technological advancements that are redefining our field.
The Federal Reserve’s Reliance on Data and Emerging Techniques
At the Federal Reserve, we recognize the immense value of data in informing our policy decisions. We utilize a vast array of government and private-sector data to assess the economy’s state, forecast economic activity, and evaluate potential risks. The emergence of nontraditional, high-frequency data has proven invaluable in comprehending the real-time effects of the COVID-19 pandemic and its economic ramifications. To extract meaningful signals from this vast data, we employ a diverse toolkit that includes standard econometric methods, text analytics, and machine learning techniques.
Relevance to Central Banks and Improved Decision-Making
The focus of this conference on nontraditional data and techniques resonates strongly with the Federal Reserve and likely other central banks. More timely and accurate information, coupled with improved methodological approaches, enables central bank staff to produce more accurate economic outlook estimates. This, in turn, empowers policymakers to make more informed decisions, ultimately contributing to the stability and prosperity of our economies.
The Maturation of Nontraditional Data and Techniques in Academic Research and Policy
It is heartening to witness the growing maturity of nontraditional data and techniques in both academic research and policymaking. The breadth and depth of studies presented at this conference showcase the substantial inroads these data and methods have made in economic research. This progress bodes well for the future of our field and underscores the potential for these tools to transform economic policymaking.
Esteemed Contributors to the Field and Their Insights
We are honored to have a distinguished lineup of speakers who have made significant contributions to the field. Over the next two days, we will hear from experts such as Jed Kolko, Julapa Jagtiani, Arthur Turrell, and Hal Varian, who will address the opportunities and challenges faced by government and private-sector institutions in response to nontraditional data, machine learning, and artificial intelligence. Additionally, an academic panel comprising Jesus Fernandez-Villaverde, Sydney Ludvigson, Stephen Hansen, and Chiara Farronato will delve into how these data and methods have advanced research frontiers in areas ranging from macroeconomic modeling to online markets.
Generative AI: Excitement, Trepidation, and Potential Applications
The recent surge in interest and apprehension surrounding generative AI has captured our attention. This emerging technology has the potential to profoundly impact various aspects of our lives, including the way we conduct economic research and formulate policy. We eagerly anticipate Jack Clark’s keynote address, where he will share insights on the practical applications of generative AI in economic research and policymaking. Of particular interest to me is “explainable AI,” which can bridge the gap between the technical realm and users, enabling us to harness the power of AI in a responsible and transparent manner.
Generative AI’s Implications for Central Bank Communications
Central banks are also exploring the potential implications of generative AI tools for their communications. The growing body of literature employing natural language processing techniques to analyze how central bankers’ communications are perceived by the media and, subsequently, how this influences financial markets is of significant relevance to central banks. Presentations by Christopher Neely, Clara Vega, Xin Zhang, and Xu Zhang will shed light on the state of the art in this area.
The Role of Social Media in News Consumption and Economic Outcomes
In today’s digital age, social media plays an increasingly influential role in shaping how we consume news and interact with each other. Corbin Fox’s presentation will examine the impact of social media on bank runs that occurred earlier in the year, highlighting the importance of understanding the role of social media in economic outcomes.
Methodological Advancements and Their Impact on Macroeconomic Modeling
Machine-learning techniques have profoundly impacted how economists approach modeling complex macroeconomic outcomes. Philippe Goulet Coulombe’s presentation will focus on how neural networks contribute to modeling the volatility of various macroeconomic variables. Joël Marbet and Yucheng Yang will discuss novel methods for solving models with heterogeneous agents, crucial for assessing the distributional consequences of economic policies. Advances in natural language processing and machine learning have also enhanced the ability to forecast and nowcast a wide range of macroeconomic and financial indicators, a topic that will be covered in several sessions tomorrow.
Closing Remarks and Encouragement for Continued Collaboration
As we embark on these two days of engaging discussions and thought-provoking presentations, I hope that this conference will foster fruitful conversations and the exchange of informative insights regarding the utility of nontraditional data and innovative techniques in macroeconomic analysis. I encourage you to continue these discussions beyond the conference’s duration and to seek opportunities for joint research and collaboration. This collective effort will further advance our understanding of these exciting new tools and their potential to shape economic policymaking.
A Warm Welcome to the Federal Reserve and Wishes for an Enjoyable Conference
On behalf of the organizing committee, I extend a warm welcome to the Federal Reserve and express my hope that you will find this conference both enjoyable and intellectually stimulating. May these two days be filled with productive exchanges, new knowledge, and the forging of lasting collaborations.