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Working Paper
A New Tool for Robust Estimation and Identification of Unusual Data Points
Most consistent estimators are what Müller (2007) terms “highly fragile”: prone to total breakdown in the presence of a handful of unusual data points. This compromises inference. Robust estimation is a (seldom-used) solution, but commonly used methods have drawbacks. In this paper, building on methods that are relatively unknown in economics, we provide a new tool for robust estimates of mean and covariance, useful both for robust estimation and for detection of unusual data points. It is relatively fast and useful for large data sets. Our performance testing indicates that our baseline ...
Working Paper
Alternative Methods for Studying Consumer Payment Choice
Using machine learning techniques applied to consumer diary survey data, the author of this working paper examines methods for studying consumer payment choice. These techniques, especially when paired with regression analyses, provide useful information for understanding and predicting the payment choices consumers make.
Working Paper
How People Pay Each Other: Data, Theory, and Calibrations
Using a representative sample of the U.S. adult population, we analyze which payment methods consumers use to pay other consumers (p2p) and how these choices depend on transaction and demographic characteristics. We additionally construct a random matching model of consumers with diverse preferences over the use of different payment methods for p2p payments. The random matching model is calibrated to the share of p2p payments made with cash, paper check, and electronic technologies observed from 2015 to 2019. We find about two thirds of consumers have a first p2p payment preference of cash. ...
Working Paper
Predictive Modeling of Surveyed Property Conditions and Vacancy
Using the results of a comprehensive in-person survey of properties in Cleveland, Ohio, we fit predictive models of vacancy and property conditions. We draw predictor variables from administrative data that is available in most jurisdictions such as deed recordings, tax assessor?s property characteristics, and foreclosure filings. Using logistic regression and machine learning methods, we are able to make reasonably accurate out-of-sample predictions. Our findings indicate that housing professionals could use administrative data and predictive models to identify distressed properties between ...
Working Paper
Dissecting Idiosyncratic Earnings Risk
This paper examines whether nonlinear and non-Gaussian features of earnings dynamics are caused by hours or hourly wages. Our findings from the Norwegian administrative and survey data are as follows: (i) Nonlinear mean reversion in earnings is driven by the dynamics of hours worked rather than wages since wage dynamics are close to linear, while hours dynamics are nonlinear—negative changes to hours are transitory, while positive changes are persistent. (ii) Large earnings changes are driven equally by hours and wages, whereas small changes are associated mainly with wage shocks. (iii) ...
Working Paper
Important Factors Determining Fintech Loan Default: Evidence from the LendingClub Consumer Platform
This study examines key default determinants of fintech loans, using loan-level data from the LendingClub consumer platform during 2007–2018. We identify a robust set of contractual loan characteristics, borrower characteristics, and macroeconomic variables that are important in determining default. We find an important role of alternative data in determining loan default, even after controlling for the obvious risk characteristics and the local economic factors. The results are robust to different empirical approaches. We also find that homeownership and occupation are important factors in ...
Working Paper
Alternative Methods for Studying Consumer Payment Choice
Using machine learning techniques applied to consumer diary survey data, the author of this working paper examines methods for studying consumer payment choice. These techniques, especially when paired with regression analyses, provide useful information for understanding and predicting the payment choices consumers make.
Working Paper
Dissecting Idiosyncratic Earnings Risk
This paper examines whether nonlinear and non-Gaussian features of earnings dynamics are caused by hours or hourly wages. Our findings from the Norwegian administrative and survey data are as follows: (i) Nonlinear mean reversion in earnings is driven by the dynamics of hours worked rather than wages since wage dynamics are close to linear, while hours dynamics are nonlinear—negative changes to hours are transitory, while positive changes are persistent. (ii) Large earnings changes are driven equally by hours and wages, whereas small changes are associated mainly with wage shocks. (iii) ...
Working Paper
Labor Market Effects of Credit Constraints: Evidence from a Natural Experiment
We exploit the 1998 and 2003 constitutional amendment in Texas—allowing home equity loans and lines of credit for non-housing purposes—as natural experiments to estimate the effect of easier credit access on the labor market. Using state-level as well as micro data and the synthetic control approach, we find that easier access to housing credit led to a notably lower labor force participation rate between 1998 and 2007. We show that our findings are remarkably robust to improved synthetic control methods based on insights from machine learning. We explore treatment effect heterogeneity ...
Report
Latent Heterogeneity in the Marginal Propensity to Consume
We estimate the unconditional distribution of the marginal propensity to consume (MPC) using clustering regression and the 2008 stimulus payments. Since we do not measure heterogeneity as the variation of MPCs with observables, we can recover the full distribution of MPCs. Households spent at least one quarter of the rebate, and individual households used rebates for different goods. While many observables are individually correlated with our estimated MPCs, these relationships disappear when tested jointly, except for nonsalary income and the average propensity to consume. Household ...