Calendrier du 17 octobre 2023
Paris Trade Seminar
Du 17/10/2023 de 14:45 à 16:15
Sciences Po, 28 rue des Saints-Pères, 75007 Paris (M° Saint Germain des Prés), SALLE H 405
TASCHEREAU-DUMOUCHEL Mathieu (Cornell)
Endogenous Production Networks under Supply Chain Uncertainty
écrit avec Alexandr Kopytov, Bineet Mishra and Kristoffer Nimark
Supply chain disturbances can lead to substantial increases in production costs. To mitigate these risks, firms may take steps to reduce their reliance on volatile suppliers. We construct a model of endogenous network formation to investigate how these decisions affect the structure of the production network and the level and volatility of macroeconomic aggregates. When uncertainty increases in the model, producers prefer to purchase from more stable suppliers, even though they might sell at higher prices. The resulting reorganization of the network leads to less macroeconomic volatility, but at the cost of a decline in aggregate output. The model also predicts that more productive and stable firms have higher Domar weights—a measure of their importance as suppliers—in the equilibrium network. We calibrate the model to U.S. data and find that the mechanism can account for a sizable decline in expected GDP during periods of high uncertainty like the Great Recession.
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Applied Economics Lunch Seminar
Du 17/10/2023 de 12:30 à 13:30
Salle R2.21
KAMEL Donia (PSE)
Skin Tone Penalties: Bottom-up Discrimination in Football
écrit avec Guillermo Woo-Mora
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.
Macroeconomics Seminar
Du 17/10/2023
PSE- 48 boulevard Jourdan, 75014 Paris, Amphitheater