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Working Paper
Internal Migration in the United States: A Comparative Assessment of the Utility of the Consumer Credit Panel
Whitaker, Stephan; Johnson, Janna; DeWaard, Jack
(2018-03-23)
This paper demonstrates that credit bureau data, such as the Federal Reserve Bank of New York Consumer Credit Panel/Equifax (CCP), can be used to study internal migration in the United States. It is comparable to, and in some ways superior to, the standard data used to study migration, including the American Community Survey (ACS), the Current Population Survey (CPS), and the Internal Revenue Service (IRS) county-to-county migration data. CCP-based estimates of migration intensity, connectivity, and spatial focusing are similar to estimates derived from the ACS, CPS, and IRS data. The CCP can ...
Working Papers (Old Series)
, Paper 1804
Working Paper
Missing Import Price Changes and Low Exchange Rate Pass-Through
Vigfusson, Robert J.; Gagnon, Etienne; Mandel, Benjamin R.
(2012)
A large body of empirical work has found that exchange rate movements have only modest effects on inflation. However, the response of an import price index to exchange rate movements may be underestimated because some import price changes are missed when constructing the index. We investigate downward biases that arise when items experiencing a price change are especially likely to exit or to enter the index. We show that, in theoretical pricing models, entry and exit have different implications for the timing and size of these biases. Using Bureau of Labor Statistics (BLS) microdata, we ...
International Finance Discussion Papers
, Paper 1040
Working Paper
The Labor Market Impact of a Pandemic: Validation and Application of a Do-It-Yourself CPS
Bick, Alexander; Blandin, Adam
(2020-12-22)
The Current Population Survey (CPS) is a central source of U.S. labor market data. We show that, for a few thousand dollars, researchers can quickly design and implement their own online survey to supplement the CPS. The survey closely follows core features of the CPS, ensuring that outcomes are conceptually compatible and allowing researchers to weight and validate results using the official CPS. Yet the survey also allows for faster data collection, added flexibility and novel questions. We show that the survey provided useful estimates of U.S. labor market aggregates several weeks ahead of ...
Working Papers
, Paper 2031
Journal Article
Recent changes to a measure of U.S. household debt service
Dynan, Karen E.; Pence, Karen M.; Johnson, Kathleen W.
(2003-10)
Changes in levels of aggregate household debt in the United States may contain information about the current state of the nation's economy and may affect its future direction. A commonly used measure of household indebtedness is the household debt service ratio (formerly known as the household debt service burden), published since 1980 by the Board of Governors of the Federal Reserve System. Recent changes in financial markets have prompted a comprehensive revision of this statistic. This article describes the revision and introduces a new measure, the financial obligations ratio, which adds ...
Federal Reserve Bulletin
, Volume 89
, Issue Oct
, Pages 417-426
Working Paper
Reaching the Hard to Reach with Intermediaries: The Kansas City Fed’s LMI Survey
Edmiston, Kelly D.
(2018-07-16)
Reaching hard-to-reach individuals is a common problem in survey research. The low- and moderate-income (LMI) population, for example, is generally hard to reach. The Kansas City Fed?s Low- and Moderate-Income Survey addresses this problem by sampling a database of organizations to serve as proxies for the LMI population. In this paper, I describe why the LMI population can be hard to reach. I then explore potential problems with using a nonrandom survey sample and address the empirical validity of the Kansas City Fed?s LMI Survey. I compare results from the survey using the standard sample ...
Research Working Paper
, Paper RWP 18-6
Working Paper
Big Data versus a Survey
Whitaker, Stephan
(2015-01-07)
Economists are shifting attention and resources from work on survey data to work on ?big data.? This analysis is an empirical exploration of the trade-offs this transition requires. Parallel models are estimated using the Federal Reserve Bank of New York Consumer Credit Panel/Equifax and the Survey of Consumer Finances. After adjustments to account for different variable definitions and sampled populations, it is possible to arrive at similar models of total household debt. However, the estimates are sensitive to the adjustments. Little similarity is observed in parallel models of nonmortgage ...
Working Papers (Old Series)
, Paper 1440
Working Paper
The perils of working with Big Data and a SMALL framework you can use to avoid them
Fogarty, Michael; Butters, R. Andrew; Brave, Scott A.
(2020-12-22)
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 Series
, Paper WP-2020-35
Working Paper
The perils of working with Big Data and a SMALL framework you can use to avoid them
Fogarty, Michael; Butters, R. Andrew; Brave, Scott A.
(2020-03-02)
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 Series
, Paper WP-2020-35
Working Paper
Finding Needles in Haystacks: Multiple-Imputation Record Linkage Using Machine Learning
Abowd, John M.; Abramowitz, Joelle Hillary; Levenstein, Margaret Catherine; McCue, Kristin; Patki, Dhiren; Raghunathan, Trivellore; Rodgers, Ann Michelle; Shapiro, Matthew D.; Wasi, Nada; Zinsser, Dawn
(2021-10-01)
This paper considers the problem of record linkage between a household-level survey and an establishment-level frame in the absence of unique identifiers. Linkage between frames in this setting is challenging because the distribution of employment across establishments is highly skewed. To address these difficulties, this paper develops a probabilistic record linkage methodology that combines machine learning (ML) with multiple imputation (MI). This ML-MI methodology is applied to link survey respondents in the Health and Retirement Study to their workplaces in the Census Business Register. ...
Working Papers
, Paper 22-11
Report
Heterogeneous inflation expectations and learning
Zafar, Basit; Madeira, Carlos
(2012)
Using the panel component of the Michigan Survey of Consumers, we estimate a learning model of inflation expectations, allowing for heterogeneous use of both private information and lifetime inflation experience. ?Life-experience inflation? has a significant impact on individual expectations, but only for one-year-ahead inflation. Public information is substantially more relevant for longer-horizon expectations. Even controlling for life-experience inflation and public information, idiosyncratic information explains a nontrivial proportion of the inflation forecasts of agents. We find that ...
Staff Reports
, Paper 536
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