Search Results
Working Paper
Is \"Fintech\" Good for Small Business Borrowers? Impacts on Firm Growth and Customer Satisfaction
?Fintech? is a rapidly expanding segment of the financial market that is receiving much attention from investors and increasing regulatory scrutiny. While the attention is rising, very little is known about the performance of these lending sources on the outcomes of small businesses that make use of them. The Federal Reserve?s 2015 Small Business Credit Survey has data on the experiences of business owners with this new funding source and can provide some useful insights into this expanding sector, if compositional differences among the businesses that get bank loans, those that get fintech ...
Working Paper
The Rise of Fintech Lending to Small Businesses: Businesses’ Perspectives on Borrowing
Online lending through fintech firms is a rapidly expanding segment of the financial market that is receiving much attention from investors and increasing scrutiny from regulators. Research is only beginning to assess how fintech firms’ entry is altering the choices and outcomes of small businesses that borrow from them. The Federal Reserve Small Business Credit Survey is a unique data source on the experiences of business owners with new and more traditional sources of credit. We find that the businesses using online lenders are not representative of small and medium-size enterprise in the ...
Working Paper
A distinction between causal effects in structural and rubin causal models
Structural Causal Models define causal effects in terms of a single Data Generating Process (DGP), and the Rubin Causal Model defines causal effects in terms of a model that can represent counterfactuals from many DGPs. Under these different definitions, notationally similar causal effects make distinct claims about the results of interventions to the system under investigation: Structural equations imply conditional independencies in the data that potential outcomes do not. One implication is that the DAG of a Rubin Causal Model is different from the DAG of a Structural Causal Model. Another ...
Working Paper
Common correlated effects estimation of heterogeneous dynamic panel data models with weakly exogenous regressors
This paper extends the Common Correlated Effects (CCE) approach developed by Pesaran (2006) to heterogeneous panel data models with lagged dependent variable and/or weakly exogenous regressors. We show that the CCE mean group estimator continues to be valid but the following two conditions must be satisfied to deal with the dynamics: a sufficient number of lags of cross section averages must be included in individual equations of the panel, and the number of cross section averages must be at least as large as the number of unobserved common factors. We establish consistency rates, derive the ...
Working Paper
Simultaneous Spatial Panel Data Models with Common Shocks
I consider a simultaneous spatial panel data model, jointly modeling three effects: simultaneous effects, spatial effects and common shock effects. This joint modeling and consideration of cross-sectional heteroskedasticity result in a large number of incidental parameters. I propose two estimation approaches, a quasi-maximum likelihood (QML) method and an iterative generalized principal components (IGPC) method. I develop full inferential theories for the estimation approaches and study the trade-off between the model specifications and their respective asymptotic properties. I further ...
Working Paper
A Local Projections Approach to Difference-in-Differences Event Studies
Many of the challenges in the estimation of dynamic heterogeneous treatment effects can be resolved with local projection (LP) estimators of the sort used in applied macroeconometrics. This approach provides a convenient alternative to the more complicated solutions proposed in the recent literature on Difference in-Differences (DiD). The key is to combine LPs with a flexible ‘clean control’ condition to define appropriate sets of treated and control units. Our proposed LP-DiD estimator is clear, simple, easy and fast to compute, and it is transparent and flexible in its handling of ...
Working Paper
Modelling Dependence in High Dimensions with Factor Copulas
his paper presents flexible new models for the dependence structure, or copula, of economic variables based on a latent factor structure. The proposed models are particularly attractive for relatively high dimensional applications, involving fifty or more variables, and can be combined with semiparametric marginal distributions to obtain flexible multivariate distributions. Factor copulas generally lack a closed-form density, but we obtain analytical results for the implied tail dependence using extreme value theory, and we verify that simulation-based estimation using rank statistics is ...
Working Paper
When is the Fiscal Multiplier High? A Comparison of Four Business Cycle Phases
We synthesize the recent, at times conflicting, empirical literature regarding whether fiscal policy is more effective during certain points in the business cycle. Evidence of state dependence in the multiplier depends critically on how the business cycle is defined. Estimates of the fiscal multiplier do not change when the unemployment rate is above or below its trend. However, we find that the multiplier is higher when the unemployment rate is increasing relative to when it is decreasing. This result holds using both a long time-series at the U.S. national level and for a panel of U.S. ...
Working Paper
Scenario-based Quantile Connectedness of the U.S. Interbank Liquidity Risk Network
We characterize the U.S. interbank liquidity risk network based on a supervisory dataset, using a scenario-based quantile network connectedness approach. In terms of methodology, we consider a quantile vector autoregressive model with unobserved heterogeneity and propose a Bayesian nuclear norm estimation method. A common factor structure is employed to deal with unobserved heterogeneity that may exhibit endogeneity within the network. Then we develop a scenario-based quantile network connectedness framework by accommodating various economic scenarios, through a scenario-based moving average ...
Working Paper
Does Medicaid Generosity Affect Household Income?
Almost all recent literature on Medicaid and labor supply has used Affordable Care Act (ACA)-induced Medicaid eligibility expansions in various states as natural experiments. Estimated effects on employment and earnings differ widely due to differences in the scope of eligibility expansion across states and are potentially subject to biases due to policy endogeneity. Using a Regression Kink Design (RKD) framework, this paper takes a uniquely different approach to the identification of the effect of Medicaid generosity on household income. Both state-level data and March CPS data from ...