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Working Paper
Technological innovation in mortgage underwriting and the growth in credit, 1985–2015
Foote, Christopher L.; Loewenstein, Lara; Willen, Paul S. (2019-11-01)
The application of information technology to finance, or ?fintech,? is expected to revolutionize many aspects of borrowing and lending in the future, but technology has been reshaping consumer and mortgage lending for many years. During the 1990s, computerization allowed mortgage lenders to reduce loan-processing times and largely replace human-based assessments of credit risk with default predictions generated by sophisticated empirical models. Debt-to-income ratios at origination add little to the predictive power of these models, so the new automated underwriting systems allowed higher ...
Working Papers , Paper 19-11

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
Integrating Prediction and Attribution to Classify News
Rayl, Nelson P.; Sinha, Nitish R. (2022-07-01)
Recent modeling developments have created tradeoffs between attribution-based models, models that rely on causal relationships, and â€œpure prediction modelsâ€ such as neural networks. While forecasters have historically favored one technology or the other based on comfort or loyalty to a particular paradigm, in domains with many observations and predictors such as textual analysis, the tradeoffs between attribution and prediction have become too large to ignore. We document these tradeoffs in the context of relabeling 27 million Thomson Reuters news articles published between 1996 ...
Finance and Economics Discussion Series , Paper 2022-042

Working Paper
Technological Innovation in Mortgage Underwriting and the Growth in Credit: 1985-2015
Foote, Christopher L.; Loewenstein, Lara; Willen, Paul S. (2018-12-07)
The application of information technology to finance, or ?fintech,? is expected to revolutionize many aspects of borrowing and lending in the future, but technology has been reshaping consumer and mortgage lending for many years. During the 1990s computerization allowed mortgage lenders to reduce loan-processing times and largely replace human-based assessment of credit risk with default predictions generated by sophisticated empirical models. Debt-to-income ratios at origination add little to the predictive power of these models, so the new automated underwriting systems allowed higher ...
Working Papers (Old Series) , Paper 1816

Working Paper
The Transmission of Financial Shocks and Leverage of Financial Institutions: An Endogenous Regime-Switching Framework
Waggoner, Daniel F.; Hubrich, Kirstin (2022-06-02)
We conduct a novel empirical analysis of the role of leverage of financial institutions for the transmission of financial shocks to the macroeconomy. For that purpose, we develop an endogenous regime-switching structural vector autoregressive model with time-varying transition probabilities that depend on the state of the economy. We propose new identification techniques for regime switching models.Recently developed theoretical models emphasize the role of bank balance sheets for the build-up of financial instabilities and the amplification of financial shocks. We build a market-based ...
FRB Atlanta Working Paper , Paper 2022-5

Working Paper
Internal Migration in the United States: A Comprehensive Comparative Assessment of the Consumer Credit Panel
Whitaker, Stephan; Johnson, Janna; DeWaard, Jack (2019-06-21)
We introduce and provide the first comprehensive comparative assessment of the Federal Reserve Bank of New York/Equifax Consumer Credit Panel (CCP) as a valuable and underutilized data set for studying internal migration within the United States. Relative to other data sources on US internal migration, the CCP permits highly detailed cross-sectional and longitudinal analyses of migration, both temporally and geographically. We compare cross-sectional and longitudinal estimates of migration from the CCP to similar estimates derived from the American Community Survey, the Current Population ...
Working Papers , Paper 18-04R

Working Paper
Economic Surveillance using Corporate Text
Hassan, Tarek A.; Hollander, Stephan; Kalyani, Aakash; van Lent, Laurence; Schwedeler, Markus; Tahoun, Ahmed (2024-09)
Full and correct order of authors: Tarek A. Hassan, Stephan Hollander, Aakash Kalyani, Laurence van Lent, Markus Schwedeler, and Ahmed Tahoun. This article applies simple methods from computational linguistics to analyze unstructured corporate texts for economic surveillance. We apply text-as-data approaches to earnings conference call transcripts, patent texts, and job postings to uncover unique insights into how markets and firms respond to economic shocks, such as a nuclear disaster or a geopolitical event---insights that often elude traditional data sources. This method enhances our ...
Working Papers , Paper 2024-022

Working Paper
Forecasting Consumption Spending Using Credit Bureau Data
Croushore, Dean; Wilshusen, Stephanie M. (2020-06-04)
This paper considers whether the inclusion of information contained in consumer credit reports might improve the predictive accuracy of forecasting models for consumption spending. To investigate the usefulness of aggregate consumer credit information in forecasting consumption spending, this paper sets up a baseline forecasting model. Based on this model, a simulated real-time, out-of-sample exercise is conducted to forecast one-quarter ahead consumption spending. The exercise is run again after the addition of credit bureau variables to the model. Finally, a comparison is made to test ...
Working Papers , Paper 20-22

Working Paper
Improving the Accuracy of Economic Measurement with Multiple Data Sources: The Case of Payroll Employment Data
Cajner, Tomaz; Crane, Leland D.; Decker, Ryan A.; Hamins-Puertolas, Adrian; Kurz, Christopher J. (2019-09-05)
This paper combines information from two sources of U.S. private payroll employment to increase the accuracy of real-time measurement of the labor market. The sources are the Current Employment Statistics (CES) from BLS and microdata from the payroll processing firm ADP. We briefly describe the ADP-derived data series, compare it to the BLS data, and describe an exercise that benchmarks the data series to an employment census. The CES and the ADP employment data are each derived from roughly equal-sized samples. We argue that combining CES and ADP data series reduces the measurement error ...
Finance and Economics Discussion Series , Paper 2019-065

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