Upcoming Presentations

Abstract: This paper investigates colorism, racial discrimination based on skin color, in men’s football. Firstly, using machine learning algorithms, we extract players’ skin tones from online headshots to examine their impact on fan-based ratings and valuations. We find evidence of a skin tone penalty, where darker-skinned players face lower fan-driven market values and ratings. Secondly, using algorithm-based ratings and employing a Difference-in-Discontinuities design with geolocated penalty kicks data, we show that lighter-skinned players enjoy a premium higher by 1.25 standard deviations than their darker-skinned peers, conditional on scoring a penalty. Additionally, we find evidence that non-native players with dark skin face a double penalty. Leveraging the COVID-19 pandemic as a natural experiment, we highlight the role of fans’ stadium attendance in algorithm-based results. The findings underscore direct skin tone discrimination in football and highlight fans’ role in perpetuating algorithmic bias.

Abstract: We find evidence that patent grants influence the stock returns of firms that are connected through technological knowledge dependencies. Using the direction of patent citations between publicly listed companies, we construct a daily exposure of each firm to new patent grants to its knowledge upstream firms (neighborhood) weighted by how intensely they are cited by it. We find that a percent increase in the market value of patents granted to a firm’s neighborhood increases its ab- normal returns by about 0.5 basis points each day within three days of patent grant. These spillovers are about 20 percent in size relative to returns generated a firm’s own patents. Moreover, stock returns attributable a firm’s neighbors increase over the course the week of grant, whereas they fade out with respect to its own patent grants, suggesting a gradual diffusion of information in financial markets. We further show patents granted to product market rivals decrease, and patents granted to suppliers increase, stock returns of firms. However, accounting for them does not affect our estimates of financial spillovers attributable to techno- logical knowledge dependency. We test for robustness using alternative controls and measures of patenting, restricting analysis to firms operating across industries, using placebo weights for knowledge dependencies, and demonstrating that financial spillovers tend to be localized within a firm’s immediate connections.

Abstract: Business Improvement Districts (BIDs) represent an important place-management tool across the UK, investing more than 100 million pounds each year into street safety and other public goods provision for their local neighborhoods. This paper studies the effects of the opening of a BID on local housing markets in London, where the first BIDs started operating in 2004 and more than 20% of the active BIDs in the country are located. We show that BID openings lead to an increase in house prices by around 3%, using property transaction data and BID-level information. We record also an increase the share of new-building sales after the BID opening. We argue that these results are driven by demand effects from neighborhood improvements, since they seem to be driven by BIDs spending more on crime and environment. We rule out housing supply responses to BID openings using administrative records on housing planning applications. In the longer run, blocks exposed to BIDs activity present gentrification trajectories as they lower their share of social renters, BAME and unemployed residents to a greater extent compared to non-affected blocks.