Tel. +34 93 542 1998
Available for interviews at
European Job Market for Economists (EEA)
Allied Social Science Associations (ASSA)
Primary: : Banking, Fintech, Sustainable Finance.
Secondary: Applied Econometrics and Data Science, Financial Decision-Making, Financial Stability.
"Fintech, Bank Branch Closings, and Mortgage Markets” (Job Market Paper)
This paper studies whether bank branch closures affect fintech mortgage lending in the U.S. using data for the 1999–2016 period. To generate plausibly exogenous variation in the incidence of closings, I use an instrument based on within-county, tract-level variation in exposure to post-merger branch consolidation. I find that branch closures lead to a persistent increase in fintech lending. Fintech mortgages grow by a total of 8% relative to non-closure tracts in the nine years that follow a closing, while bank mortgage lending falls by 44%, off an annual baseline of 340 mortgages. Fintech mortgage growth is driven by wealthier areas and areas with relatively smaller populations of women, seniors, and minorities.
"Do pictures affect investment? Typicality, Deep Learning & Crowdfunding Success” (with G. Le Mens)
In this paper, we test whether investments in a crowdfunding platform are higher valued if the picture used to promote them is most representative of their category. To explore this, we employ a novel application of Deep Learning using observational data obtained from the crowdfunding platform Indiegogo. We feed as inputs for our model the main picture of each crowdfunding project and obtain as output a measure of the confidence in the classification that we then transform to obtain a typicality measure. We find that crowdfunding projects are not more valued by customers if they are either advertised with a picture that a learning model correctly categorizes or the main image is most representative of its true category.
"How Selective Access to Financial Information Affect How Investors Learn" (with G. Le Mens)
In this study, we compare learning in two common settings in financial markets. One in which investors can observe the outcome of an investment alternative only if they invest in it, and another one in which they always can observe the outcome —even if they do not invest in it. We provide empirical evidence that investors’ beliefs are, on average, 5% closer to the objective Bayesian beliefs given the observed information when investors are in a setting in which they have access to the financial information because of endogenous choice. Then we are able to describe the mechanism that explains our findings. We show that the endogenous creation of the sample of information triggers different cognitive processes. These alternative processes cause better information processing and are of enough magnitude to help overcome the effect of sampling errors.
Research Papers in Progress
“Fintech and the Great Recession"
“Inequality Shocks and Fintech: Evidence from a Natural Experiment in Spain"
“Crowdlending to peers: Evidence from a Spanish crowdlending platform” (with A. Banal and J. Roig)