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Working Paper
The perils of working with Big Data and a SMALL framework you can use to avoid them
The use of “Big Data” to explain fluctuations in the broader economy or guide the business decisions of a firm is now so commonplace that in some instances it has even begun to rival more traditional government statistics and business analytics. Big data sources can very often provide advantages when compared to these more traditional data sources, but with these advantages also comes the potential for pitfalls. We lay out a framework called SMALL that we have developed in order to help interested parties as they navigate the big data minefield. Based on a set of five questions, the SMALL ...
Working Paper
The perils of working with Big Data and a SMALL framework you can use to avoid them
The use of “Big Data” to explain fluctuations in the broader economy or guide the business decisions of a firm is now so commonplace that in some instances it has even begun to rival more traditional government statistics and business analytics. Big data sources can very often provide advantages when compared to these more traditional data sources, but with these advantages also comes the potential for pitfalls. We lay out a framework called SMALL that we have developed in order to help interested parties as they navigate the big data minefield. Based on a set of five questions, the SMALL ...
Working Paper
Safeguarding Research: A Review of Economics Journals’ Preservation Policies for Published Code and Data Files
For many years, economics researchers have discussed the importance of sharing codeand data files to ensure replicability. The discussion, however, rarely includes questions aboutlong-term access to those files. This paper looks in-depth at the code and data policies from topeconomics journals to understand the guidance provided to researchers regarding data sharingand asks if that guidance supports preservation of code and data files for access and use, longinto the future. We used content analysis to review journal policies from 184 economics journals.We discovered that while most journals ...
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 ...
Working Paper
Artificial Intelligence Methods for Evaluating Global Trade Flows
International trade policies remain in the spotlight given the recent rethink on the benefits of globalization by major economies. Since trade critically affects employment, production, prices and wages, understanding and predicting future patterns of trade is a high-priority for decision making within and across countries. While traditional economic models aim to be reliable predictors, we consider the possibility that Artificial Intelligence (AI) techniques allow for better predictions and associations to inform policy decisions. Moreover, we outline contextual AI methods to decipher trade ...
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 ...
Working Paper
Weather-adjusting employment data
First version: December 18, 2014. This version: January 12, 2015. This paper proposes and implements a statistical methodology for adjusting employment data for the effects of deviation in weather from seasonal norms. This is distinct from seasonal adjustment, which only controls for the normal variation in weather across the year. Unusual weather can distort both the data and the seasonal factors. We control for both of these effects by integrating a weather adjustment step in the seasonal adjustment process. We use several indicators of weather, including temperature, snowfall and ...
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.
Speech
Remarks at the fifth Data Management Strategies and Technologies Workshop
Remarks at the Fifth Data Management Strategies and Technologies Workshop, Federal Reserve Bank of New York, New York City
Report
Fed Transparency and Policy Expectation Errors: A Text Analysis Approach
This paper seeks to estimate the extent to which market-implied policy expectations could be improved with further information disclosure from the FOMC. Using text analysis methods based on large language models, we show that if FOMC meeting materials with five-year lagged release dates—like meeting transcripts and Tealbooks—were accessible to the public in real time, market policy expectations could substantially improve forecasting accuracy. Most of this improvement occurs during easing cycles. For instance, at the six-month forecasting horizon, the market could have predicted as much ...