Search Results
Speech
The Federal Reserve System and Community Development: The Why, The How, and The What 2017 Policy Summit on Housing, Human Capital, and Inequality, Cleveland, OH
Over the past 14 years, the Policy Summit has brought together community development practitioners, researchers, funders, policymakers, and others interested in strengthening our communities so that all people have the opportunity to productively engage in our economy and to share in its benefits. As is clear from the many conversations we?ve had over the past two days ? and over the past 14 years of this summit ? there are no easy answers. But there are some answers. I will touch on ?the why, the how, and the what? of this work: why we at the Fed see our community development efforts as ...
Newsletter
Ethical Use of Data with FRED
What are the ethical considerations for researchers who use data? This data primer describes standards for gathering, analyzing, storing, and distributing data for new data users and serves as a reference for advanced data users.
Speech
Elementary, Dear Data
Remarks at 2023 U.S. Treasury Market Conference, Federal Reserve Bank of New York, New York City.
Briefing
Creating Data Citation Templates for Economics
Copy and paste citation tools exist for traditional academic publication types from places like Citation Machine or Google Scholar, but similar plugins for datasets are scarce. In response, the Federal Reserve Bank of Kansas City built a data citation template for all acquired proprietary data sources and selected open data sources to allow economists to copy and paste data citations into their preferred word processing program.
Discussion Paper
Insights from Newly Digitized Banking Data, 1867-1904
Call reports—regulatory filings in which commercial banks report their assets, liabilities, income, and other information—are one of the most-used data sources in banking and finance. Though call reports were collected as far back as 1867, the underlying data are only easily accessible for the recent past: the mid-1980s onward in the case of the FDIC’s FFIEC call reports. To help researchers look farther back in time, we’ve begun creating a complete digital record of this “missing” call report data; this data release covers 1867 through 1904, the bulk of the National Banking Era. ...
Speech
Weighing the risks to the economic outlook: remarks at The Leo J. Meehan School of Business, Stonehill College, Easton, Massachusetts, September 3, 2019
It was an eventful August in the financial markets amid talk of additional tariffs and tax cuts, the falling 10-year Treasury rate, and volatility in stock prices. But the economic data and forecasts indicate a relatively good domestic economy.
Working Paper
Evaluating Local Language Models: An Application to Bank Earnings Calls
This study evaluates the performance of local large language models (LLMs) in interpreting financial texts, compared with closed-source, cloud-based models. We first introduce new benchmarking tasks for assessing LLM performance in analyzing financial and economic texts and explore the refinements needed to improve its performance. Our benchmarking results suggest local LLMs are a viable tool for general natural language processing analysis of these texts. We then leverage local LLMs to analyze the tone and substance of bank earnings calls in the post-pandemic era, including calls conducted ...
Discussion Paper
Monetizing Privacy with Central Bank Digital Currencies
In prior research, we documented evidence suggesting that digital payment adoptions have accelerated as a result of the COVID-19 pandemic. While digitalization of payment activity improves data utilization by firms, it can also infringe upon consumers’ right to privacy. Drawing from a recent paper, this blog post explains how payment data acquired by firms impacts market structure and consumer welfare. Then, we discuss the implications of introducing a central bank digital currency (CBDC) that offers consumers a low-cost, privacy-preserving electronic means of payment—essentially, digital ...
Working Paper
Introducing a Framework for Measuring the Quantitative Benefits of Privacy-Enhancing Technologies
This paper reviews privacy-enhancing technologies (PETs) and explores their benefits when used to make traditional payment processes more private. PETs can decrease privacy risk by reducing the amount of sensitive information accessible to payment-processing personnel and systems. This paper proposes a framework for quantifying the risk-reduction benefits of PETs. This method can be used to calculate the amount of privacy-risk exposure that may be created by a set of payment activities, estimate the amount by which PETs can decrease that exposure, and compare that quantified benefit against ...