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This paper proposes an empirical, replicable, and interpretable framework to decompose, in basis points (bps), daily changes in Brazil's 5-year DI futures rate (DI5Y). The approach combines three building blocks: (i) macroeconomic and…
We investigate the dynamics of the update of subjective homicide victimization risk after an informational shock by developing two econometric models able to accommodate both optimal decisions of changing prior expectations which enable us…
We study how sentiment shocks propagate through equity returns and investor clientele using four independent proxies with sign-aligned kappa-rho parameters. A structural calibration links a one standard deviation innovation in sentiment to…
We propose a two-stage estimation procedure for a copula-based model with semi-competing risks data, where the non-terminal event is subject to dependent censoring by the terminal event, and both events are subject to independent censoring.…
We develop a forecasting methodology for providing credible forecasts for time series that have recently undergone a shock. We achieve this by borrowing knowledge from other time series that have undergone similar shocks for which…
This study extends the CAPIRE framework with a macro-shock module to analyse the impact of teacher strikes and inflation on student trajectories in engineering education. Using data from 1,343 students across 15 cohorts (2004-2019) in a…
We describe a case study in the use of the Structured Process for Information Campaign Enhancement (SP!CE, version 2.1) to evaluate influence campaigns present in the 2nd round of the Brazilian presidential election in 2022 October. SP!CE…
Background Study individuals may face repeated events overtime. However, there is no consensus around learning approaches to use in a high-dimensional framework for survival data (when the number of variables exceeds the number of…
Our objective is to assess the performance of waveform cross-correlation technique, as applied to automatic and interactive processing of the aftershock sequence of the 2012 Sumatera earthquake relative to the Reviewed Event Bulletin (REB)…
Event extraction is an Information Retrieval task that commonly consists of identifying the central word for the event (trigger) and the event's arguments. This task has been extensively studied for English but lags behind for Portuguese,…
Event schemas encode knowledge of stereotypical structures of events and their connections. As events unfold, schemas are crucial to act as a scaffolding. Previous work on event schema induction focuses either on atomic events or linear…
Implicit event argument extraction (EAE) aims to identify arguments that could scatter over the document. Most previous work focuses on learning the direct relations between arguments and the given trigger, while the implicit relations with…
The analysis of randomized controlled trials is often complicated by intercurrent events (IEs) -- events that occur after treatment initiation and affect either the interpretation or existence of outcome measurements. Examples include…
How can we detect when global events fundamentally reshape public discourse? This study introduces a topological framework for identifying structural change in media narratives using persistent homology. Drawing on international news…
While distributed learning offers a new learning paradigm for distributed network with no central coordination, it is constrained by communication bottleneck between nodes. We develop a new event-triggered gossip framework for distributed…
Information asymmetry in financial markets, often amplified by strategically crafted corporate narratives, undermines the effectiveness of conventional textual analysis. We propose a novel multimodal framework for financial risk assessment…
Randomized controlled trials are a cornerstone of medicine and the social sciences as they enable reliable estimates of causal effects. However, they are costly and time-consuming to conduct, motivating interest in predicting causal effects…
This paper introduces a general framework for analyzing recurrent event data by modeling the conditional mean function of the recurrent event process as the solution to an Ordinary Differential Equation (ODE). This approach not only…
We show that, provided one focuses on properly selected episodes, one can apply to the social sciences the same observational strategy that has proved successful in natural sciences such as astrophysics or geodynamics. For instance, in…
This paper presents the development and validation of an eye-tracking dataset designed to investigate how second-language (L2) learners process idiomatic expressions. While native speakers often rely on direct retrieval of figurative…