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JEL Classification:C80 

Report
Measuring the US Employment Situation Using Online Panels: The Yale Labor Survey

This report presents the results of a rapid, low-cost survey that collects labor market data for individuals in the United States. The Yale Labor Survey (YLS) used an online panel from YouGov to replicate statistics from the Current Population Survey (CPS), the government’s source of household labor market statistics. The YLS’s advantages include its timeliness, low cost, and ability to develop new questions quickly to study labor market patterns during the coronavirus (COVID-19) pandemic. Although YLS estimates of unemployment and participation rates mirrored the broad trends in CPS ...
Current Policy Perspectives

Working Paper
Database of global economic indicators (DGEI): a methodological note

The Database of Global Economic Indicators (DGEI) from the Federal Reserve Bank of Dallas is aimed at standardizing and disseminating world economic indicators for policy analysis and scholarly work on the role of globalization. The purpose of DGEI is to offer a broad perspective on how economic developments around the world influence the U.S. economy with a wide selection of indicators. DGEI is automated within an Excel-VBA and E-views framework for the processing and aggregation of multiple country time series. It includes a core sample of 40 countries with available indicators and broad ...
Globalization Institute Working Papers , Paper 166

Discussion Paper
Estimating the output gap in real time

I propose a novel method of estimating the potential level of U.S. GDP in real time. The proposed wage-based measure of economic potential remains virtually unchanged when new data are released. The distance between current and potential output ? the output gap ? satisfies Okun?s law and outperforms many other measures of slack in forecasting inflation. Thus, I provide a robust statistical tool useful for understanding current economic conditions and guiding policymaking.
Staff Papers , Issue Dec

Working Paper
Total Recall? Evaluating the Macroeconomic Knowledge of Large Language Models

We evaluate the ability of large language models (LLMs) to estimate historical macroeconomic variables and data release dates. We find that LLMs have precise knowledge of some recent statistics, but performance degrades as we go farther back in history. We highlight two particularly important kinds of recall errors: mixing together first print data with subsequent revisions (i.e., smoothing across vintages) and mixing data for past and future reference periods (i.e., smoothing within vintages). We also find that LLMs can often recall individual data release dates accurately, but aggregating ...
Finance and Economics Discussion Series , Paper 2025-044

Working Paper
Harmonized Population and Labor Force Statistics

The official labor force statistics often exhibit discontinuities in January, when updated population estimates are incorporated into the Current Population Survey (CPS) for the current year but are not revised backward through history. We construct harmonized population estimates spanning five decades and produce new weights for the CPS microdata that are benchmarked to these estimates. Using these weights, we estimate harmonized labor force statistics that reflect the latest available information about the population and its characteristics. The harmonized labor force series are free from ...
Finance and Economics Discussion Series , Paper 2025-057

Working Paper
Validating Large Language Model Annotations

This paper proposes a validation framework for LLM-generated measurements when reliable benchmarks are unavailable. Validity is established by testing whether an LLM can reconstruct passages from annotated labels while maintaining semantic consistency with the original text. The framework avoids circular reasoning by establishing testable prerequisite properties that must be met for a validation to be considered successful. Application to news article data demonstrates that the framework serves as a practical alternative to human benchmarking, which offers advantages in objectivity, ...
Finance and Economics Discussion Series , Paper 2026-020

Working Paper
Is Economics Research Replicable? Sixty Published Papers from Thirteen Journals Say \"Usually Not\"

Finance and Economics Discussion Series , Paper 2015-83

Working Paper
Heterogeneity in Economic Shocks and Household Spending

Large swings in aggregate household-sector spending, especially for big ticket items such as cars and housing, have been a dominant feature of the macroeconomic landscape in the past two decades. Income and wealth inequality increased over the same period, leading some to suggest the two phenomena are interconnected. Indeed, there is supporting evidence for the idea that heterogeneity in economic shocks and spending are connected, most notably in studies using local-area geography as the unit of analysis. The Survey of Consumer Finances (SCF) provides a household-level perspective on changes ...
Finance and Economics Discussion Series , Paper 2015-49

Working Paper
Shedding Light on Survey Accuracy—A Comparison between SHED and Census Bureau Survey Results

The annual Survey of Household Economics and Decisionmaking (SHED) receives substantial research attention for topics related to household finances and economic well-being. To assess the reliability of data from the SHED, we compare aggregate statistics from the SHED with prominent, nationally representative surveys that use different survey designs, sample methodologies, and interview modes. Specifically, we compare recent statistics from the SHED with similar questions in U.S. Census Bureau surveys, including the Current Population Survey (CPS) and the American Community Survey (ACS). ...
Finance and Economics Discussion Series , Paper 2025-010

Working Paper
CardSim: A Bayesian Simulator for Payment Card Fraud Detection Research

Payment fraud has been high in recent years, and as criminals gain access to capability-enhancing generative AI tools, there is a growing need for innovative fraud detection research. However, the pace, diversity, and reproducibility of such research are inhibited by the dearth of publicly available payment transaction data. A few payment simulation methodologies have been developed to help narrow the payment transaction data gap without compromising important data privacy and security expectations. While these simulation approaches have enabled research advancements, more work is needed to ...
Finance and Economics Discussion Series , Paper 2025-017

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