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Working Paper
Even one is too much: the economic consequences of being a smoker
It is well known that smoking leads to lower wages. However, the mechanism of this negative relationship is not well understood. This analysis includes a decomposition of the wage gap between smokers and nonsmokers, with a variety of definitions of smoking status designed to reflect differences in smoking intensity. This paper finds that nearly two-thirds of the 24 percent selectivity-corrected smoking/nonsmoking wage differential derives from differences in characteristics between smokers and nonsmokers. These results suggest that it is not differences in productivity that drive the smoking ...
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
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
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
Evidence on the Production of Cognitive Achievement from Moving to Opportunity
This paper performs a subgroup analysis on the effect of receiving a Moving to Opportunity (MTO) housing voucher on test scores. I find evidence of heterogeneity by number of children in the household in Boston, gender in Chicago, and race/ethnicity in Los Angeles. To study the mechanisms driving voucher effect heterogeneity, I develop a generalized Rubin Causal Model and propose an estimator to identify transition-specific Local Average Treatment Effects (LATEs) of school and neighborhood quality. Although I cannot identify such LATEs with the MTO data, the analysis demonstrates that ...
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
Effects of US quantitative easing on emerging market economies
We estimate international spillover effects of US Quantitative Easing (QE) on emerging market economies. Using a Bayesian VAR on monthly US macroeconomic and financial data, we first identify the US QE shock with non-recursive identifying restrictions. We estimate strong and robust macroeconomic and financial impacts of the US QE shock on US output, consumer prices, long-term yields, and asset prices. The identified US QE shock is then used in a monthly Bayesian panel VAR for emerging market economies to infer the spillover effects on these countries. We find that an expansionary US QE shock ...
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
Large panel data models with cross-sectional dependence: a survey
This paper provides an overview of the recent literature on estimation and inference in large panel data models with cross-sectional dependence. It reviews panel data models with strictly exogenous regressors as well as dynamic models with weakly exogenous regressors. The paper begins with a review of the concepts of weak and strong cross-sectional dependence, and discusses the exponent of cross-sectional dependence that characterizes the different degrees of cross-sectional dependence. It considers a number of alternative estimators for static and dynamic panel data models, distinguishing ...