This seminar will provide an opportunity to discuss about the activities of the institute and will be organized in 5 sessions throughout the 2022-2023 academic year. It's purpose is twofold:
To attend, please contact: firstname.lastname@example.org
The second research seminar of the ACSS-PSL Institute to be held
on Friday, December 9 from 12:15 to 13:45
The Covid-19 Crisis: an NLP Exploration of the French Twitter Feed (February-May 2020)
The Covid-19 pandemic offers a spectacular case of disaster management. In this literature, the paradigm of participation is fundamental: the mitigation of the impact of the disaster, the quality of the preparation and the resilience of the society, which facilitate the reconstruction, depend on the participation of the populations. Being able to observe and measure the state of mental health of the population (anxiety, confidence, expectations, ...) and to identify the points of controversy and the content of the discourse, are necessary to support measures designed to encourage this participation. Social media, and in particular Twitter, offer valuable resources for researching this discourse. The objective of this empirical study is to reconstruct a micro history of users’ reactions to the pandemic as they share them on social networks. The general method used comes from new processing techniques derived from Natural Language Processing (NLP). Three analysis methods are used to process the corpus: analysis of the temporal evolution of term occurrences; creation of dynamic semantic maps to identify co-occurrences; analysis of topics using the SVM method. The main empirical result is that the mask emerges as a central figure of discourse, at least in the discourse produced by certain social media. The retrospective analysis of the phenomenon allows us to explain what made the mask a focal point not only in conversation, but also in behaviors. Its value resides less in its functional qualities than in its ability to fix attention and organize living conditions under the threat of pandemic.
Measuring Crime Reporting and Incidence: Method and Application to #MeToo
This paper studies the Me Too movement’s effects on sex criminality. As many victims do not report to the police, a long-standing empirical challenge with reported crime statistics is that they reflect variations in victim reporting and crime incidence. To separate both margins, I develop a duration model that studies the delay between the incident’s occurrence and its report to the police. The model accounts for unobserved heterogeneity, never-reporters, and double-truncation in the data. I apply it to the police records of large US cities. Contrary to the widespread view that #MeToo was a watershed moment, I find that sex crime reporting had already been increasing for years before its sudden mediatization in October 2017. Nonetheless, the movement had a positive, persistent impact on victim reporting, particularly for juveniles, racial minorities, and victims of misdemeanors and old crime incidents. The increase in reporting translates into drastically higher probabilities of arrest for sex offenders. Using reported non-sexual crimes as a control group, difference-in-differences estimates suggest the movement also had a sizable deterrent effect.
The first research seminar of the ACSS-PSL Institute to be held
on Friday, October 14 from 12:15 to 13:45
Bet on a bubble asset ? An optimal portfolio allocation strategy
Coauthors: Gilles de Truchis, Elena Dumitrescu, Sebastien Fries
We discuss portfolio allocation when one asset exhibits phases of locally explosive behavior. We model the conditional distribution of such an asset through mixed causal-non-causal models which mimic well the speculative bubble behaviour. Relying on a Taylor-series-expansion of a CRRA utility function approach, the optimal portfolio(s) is(are) located on the mean-variance-skewness-kurtosis efficient surface. We analytically derive these four conditional moments and show in a Monte-Carlo simulations exercise that incorporating them into a two-assets portfolio optimization problem leads to substantial improvement in the asset allocation strategy. All performance evaluation metrics support the higher out-of-sample performance of our investment strategies over standard benchmarks such as the mean-variance and equally-weighted portfolio. An empirical illustration using the Brent oil price as the speculative asset confirms these findings.
The Origins of Commodity Price Fluctuations
Coauthors: Sarah Mouabbi (Banque de France) et Adrien Rousset Planat (London Business School)
We build novel indexes of commodity price developments by simulating news-reading. Our proposed computer-based, narrative approach is flexible, unified and spans the global commodity market, including energy, industrial and precious metals, and agricultural commodities. Empirical evidence and human readings of news articles indicate that our indexes capture commodity-price supply and demand components. Index-peaks track the post-crisis collapse of commodity markets, other market-specific developments, as well as the recent COVID-19 crisis. The richness of news content allows us to decompose the supply and demand indexes into a number of key determinants that shaped commodity markets since the beginning of the 21st century, including business cycle effects, geopolitical risk, natural disasters, and climate change considerations. Preliminary results reveal that the nature of commodity price movements matters for macroeconomic outcomes, firms’ decisions, and asset prices.
© 2022 tous droits réservés.
Graphiques en page d'accueil issus de diverses recherches menées par des membres de l'institut.
Contact : email@example.com