arXiv subjects

Giovanni Angelini

Publications and source records attributed to Giovanni Angelini.

12 recordsLinked to original sources

arXiv2026

The Shape of Macroeconomic Beliefs

Macroeconomic expectations are usually observed through point forecasts or through asset prices whose mapping into beliefs is model-dependent. This paper uses prediction-market prices to recover high-frequency distributions of short-run macroeconomic beliefs. We construct a panel of Kalshi-implied distributions for CPI and core CPI releases by converting adjacent threshold contracts into probability mass over inflation outcomes. The data reveal market-implied means, uncertainty, and upper-tail probabilities from 30 days to one hour before each release. The market-implied mean contains meaningful forecast information, especially for headline CPI, but the main signal is distributional. Lagged Reuters Poll surprises do not predict systematic deviations of Kalshi means from the current Reuters consensus. By contrast, large lagged surprises are associated with higher implied uncertainty, and positive lagged surprises raise the probability assigned to fixed high-inflation outcomes. In the baseline specification with variable-by-horizon fixed effects, a 0.1 percentage point positive lagged surprise raises the probability of monthly inflation above 0.3 percent by about 4.7 percentage points, even after controlling for the current consensus forecast. In release-level validation tests, Kalshi upper-tail probabilities also predict the realization of high-inflation states, including episodes in which the market-implied mean remains close to the Reuters consensus. The evidence suggests that prediction markets can provide real-time information about inflation risk that is missed by point forecasts.

econ.EM↗

arXiv2026

When Do Markets Fully Process Public Information? Evidence from Real-Time Prediction Markets

How efficiently do markets update beliefs when public information arrives in rapid sequence? We use a real-time prediction market setting that combines binary payoffs, precisely observed public signals, and high-frequency market data, allowing us to compare market price changes with changes in a benchmark probability implied by publicly available information. We first show that prices are informative and become more accurate as resolution approaches. During the event, prices respond rapidly to public signals and move in the expected direction. However, directional responsiveness is not the same as efficient updating. Relative to an out-of-sample benchmark probability model, a one-minute change in the benchmark probability is associated with only about a 0.64-for-one contemporaneous change in market prices. The missing adjustment predicts future price drift over the following several minutes, including drift net of subsequent changes in the benchmark probability. We then study the mechanisms underlying this gradual adjustment. Salient public signals are incorporated relatively quickly in liquid markets, but the same signals generate substantially greater underreaction when liquidity is low. Underreaction gaps associated with salient states also predict stronger subsequent drift. The evidence therefore points to gradual price discovery shaped by the interaction between attention and trading frictions. The results contribute to the literatures on prediction markets, market efficiency, and behavioral finance. More broadly, they show that markets can aggregate public information quickly without necessarily incorporating it fully on impact. Market-implied probabilities are often directionally correct, yet adjustment remains incomplete and predictably depends on liquidity and salience.

econ.EM↗

arXiv2025

Shocking concerns: public perception about climate change and the macroeconomy

Public perceptions of climate change arguably contribute to shaping private adaptation and support for policy intervention. In this paper, we propose a novel Climate Concern Index (CCI), based on disaggregated web-search volumes related to climate change topics, to gauge the intensity and dynamic evolution of collective climate perceptions, and evaluate its impacts on the business cycle. Using data from the United States over the 2004:2024 span, we capture widespread shifts in perceived climate-related risks, particularly those consistent with the postcognitive interpretation of affective responses to extreme climate events. To assess the aggregate implications of evolving public concerns about the climate, we estimate a proxy-SVAR model and find that exogenous variation in the CCI entails a statistically significant drop in both employment and private consumption and a persistent surge in stock market volatility, while core inflation remains largely unaffected. These results suggest that, even in the absence of direct physical risks, heightened concerns for climate-related phenomena can trigger behavioral adaptation with nontrivial consequences for the macroeconomy, thereby demanding attention from institutional players in the macro-financial field.

econ.GN↗

arXiv2024

Invalid proxies and volatility changes

When in proxy-SVARs the covariance matrix of VAR disturbances is subject to exogenous, permanent breaks that cause IRFs to change across volatility regimes, even strong, exogenous external instruments yield inconsistent estimates of the dynamic causal effects. However, if these volatility shifts are properly incorporated into the analysis through (testable) "stability restrictions", we demonstrate that the target IRFs are point-identified and can be estimated consistently under a necessary and sufficient rank condition. If the shifts in volatility are sufficiently informative, standard asymptotic inference remains valid even with (i) local-to-zero covariance between the proxies and the instrumented structural shocks, and (ii) potential failures of instrument exogeneity. Intuitively, shifts in volatility act similarly to strong instruments that are correlated with both the target and non-target shocks. We illustrate the effectiveness of our approach by revisiting a seminal fiscal proxy-SVAR for the US economy. We detect a sharp change in the size of the tax multiplier when the narrative tax instrument is complemented with the decline in unconditional volatility observed during the transition from the Great Inflation to the Great Moderation. The narrative tax instrument contributes to identify the tax shock in both regimes, although our empirical analysis raises concerns about its "statistical" validity.

econ.EM↗

arXiv2023

The WebCrow French Crossword Solver

Crossword puzzles are one of the most popular word games, played in different languages all across the world, where riddle style can vary significantly from one country to another. Automated crossword resolution is challenging, and typical solvers rely on large databases of previously solved crosswords. In this work, we extend WebCrow 2.0, an automatic crossword solver, to French, making it the first program for crossword solving in the French language. To cope with the lack of a large repository of clue-answer crossword data, WebCrow 2.0 exploits multiple modules, called experts, that retrieve candidate answers from heterogeneous resources, such as the web, knowledge graphs, and linguistic rules. We compared WebCrow's performance against humans in two different challenges. Despite the limited amount of past crosswords, French WebCrow was competitive, actually outperforming humans in terms of speed and accuracy, thus proving its capabilities to generalize to new languages.

cs.CL↗

arXiv2023

Italian Crossword Generator: Enhancing Education through Interactive Word Puzzles

Educational crosswords offer numerous benefits for students, including increased engagement, improved understanding, critical thinking, and memory retention. Creating high-quality educational crosswords can be challenging, but recent advances in natural language processing and machine learning have made it possible to use language models to generate nice wordplays. The exploitation of cutting-edge language models like GPT3-DaVinci, GPT3-Curie, GPT3-Babbage, GPT3-Ada, and BERT-uncased has led to the development of a comprehensive system for generating and verifying crossword clues. A large dataset of clue-answer pairs was compiled to fine-tune the models in a supervised manner to generate original and challenging clues from a given keyword. On the other hand, for generating crossword clues from a given text, Zero/Few-shot learning techniques were used to extract clues from the input text, adding variety and creativity to the puzzles. We employed the fine-tuned model to generate data and labeled the acceptability of clue-answer parts with human supervision. To ensure quality, we developed a classifier by fine-tuning existing language models on the labeled dataset. Conversely, to assess the quality of clues generated from the given text using zero/few-shot learning, we employed a zero-shot learning approach to check the quality of generated clues. The results of the evaluation have been very promising, demonstrating the effectiveness of the approach in creating high-standard educational crosswords that offer students engaging and rewarding learning experiences.

cs.CL↗

arXiv2022

An identification and testing strategy for proxy-SVARs with weak proxies

When proxies (external instruments) used to identify target structural shocks are weak, inference in proxy-SVARs (SVAR-IVs) is nonstandard and the construction of asymptotically valid confidence sets for the impulse responses of interest requires weak-instrument robust methods. In the presence of multiple target shocks, test inversion techniques require extra restrictions on the proxy-SVAR parameters other those implied by the proxies that may be difficult to interpret and test. We show that frequentist asymptotic inference in these situations can be conducted through Minimum Distance estimation and standard asymptotic methods if the proxy-SVAR can be identified by using `strong' instruments for the non-target shocks; i.e. the shocks which are not of primary interest in the analysis. The suggested identification strategy hinges on a novel pre-test for the null of instrument relevance based on bootstrap resampling which is not subject to pre-testing issues, in the sense that the validity of post-test asymptotic inferences is not affected by the outcomes of the test. The test is robust to conditionally heteroskedasticity and/or zero-censored proxies, is computationally straightforward and applicable regardless of the number of shocks being instrumented. Some illustrative examples show the empirical usefulness of the suggested identification and testing strategy.

econ.EM↗

arXiv2022

Time-Varying Poisson Autoregression

In this paper we propose a new time-varying econometric model, called Time-Varying Poisson AutoRegressive with eXogenous covariates (TV-PARX), suited to model and forecast time series of counts. {We show that the score-driven framework is particularly suitable to recover the evolution of time-varying parameters and provides the required flexibility to model and forecast time series of counts characterized by convoluted nonlinear dynamics and structural breaks.} We study the asymptotic properties of the TV-PARX model and prove that, under mild conditions, maximum likelihood estimation (MLE) yields strongly consistent and asymptotically normal parameter estimates. Finite-sample performance and forecasting accuracy are evaluated through Monte Carlo simulations. The empirical usefulness of the time-varying specification of the proposed TV-PARX model is shown by analyzing the number of new daily COVID-19 infections in Italy and the number of corporate defaults in the US.

econ.EM↗

arXiv2022

Measurement of charged-pion production in deep-inelastic scattering off nuclei with the CLAS detector

Background: Energetic quarks in nuclear DIS propagate through the nuclear medium. Processes that are believed to occur inside nuclei include quark energy loss through medium-stimulated gluon bremsstrahlung and intra-nuclear interactions of forming hadrons. More data are required to gain a more complete understanding of these effects. Purpose: To test the theoretical models of parton transport and hadron formation, we compared their predictions for the nuclear and kinematic dependence of pion production in nuclei. Methods: We have measured charged-pion production in semi-inclusive DIS off D, C, Fe, and Pb using the CLAS detector and the CEBAF 5.014 GeV electron beam. We report results on the nuclear-to-deuterium multiplicity ratio for $π^{+}$ and $π^{-}$ as a function of energy transfer, four-momentum transfer, and pion energy fraction or transverse momentum - the first three-dimensional study of its kind. Results: The $π^{+}$ multiplicity ratio is found to depend strongly on the pion fractional energy $z$, and reaches minimum values of $0.67\pm0.03$, $0.43\pm0.02$, and $0.27\pm0.01$ for the C, Fe, and Pb targets, respectively. The $z$ dependences of the multiplicity ratios for $π^{+}$ and $π^{-}$ are equal within uncertainties for C and Fe targets but show differences at the level of 10$\%$ for the Pb-target data. The results are qualitatively described by the GiBUU transport model, as well as with a model based on hadron absorption, but are in tension with calculations based on nuclear fragmentation functions. Conclusions: These precise results will strongly constrain the kinematic and flavor dependence of nuclear effects in hadron production, probing an unexplored kinematic region. They will help to reveal how the nucleus reacts to a fast quark, thereby shedding light on its color structure, transport properties, and on the mechanisms of the hadronization process.

nucl-ex↗

arXiv2020

Photoproduction of the $f_2(1270)$ meson using the CLAS detector

The quark structure of the $f_2(1270)$ meson has, for many years, been assumed to be a pure quark-antiquark ($q\bar{q}$) resonance with quantum numbers $J^{PC} = 2^{++}$. Recently, it was proposed that the $f_2(1270)$ is a molecular state made from the attractive interaction of two $ρ$-mesons. Such a state would be expected to decay strongly to final states with charged pions, due to the dominant decay $ρ\to π^+ π^-$, whereas decay to two neutral pions would likely be suppressed. Here, we measure for the first time the reaction $γp \to π^0 π^0 p$, using the CLAS detector at Jefferson Lab for incident beam energies between 3.6-5.4~GeV. Differential cross sections, $dσ/ dt$, for $f_2(1270)$ photoproduction are extracted with good precision, due to low backgrounds, and are compared with theoretical calculations.

nucl-ex↗

arXiv2019

Exploring the Structure of the Bound Proton with Deeply Virtual Compton Scattering

In the past two decades, deeply virtual Compton scattering of electrons has been successfully used to advance our knowledge of the partonic structure of the free proton and investigate correlations between the transverse position and the longitudinal momentum of quarks inside the nucleon. Meanwhile, the structure of bound nucleons in nuclei has been studied in inclusive deep-inelastic lepton scattering experiments off nuclear targets, showing a significant difference in longitudinal momentum distribution of quarks inside the bound nucleon, known as the EMC effect. In this work, we report the first beam spin asymmetry (BSA) measurement of exclusive deeply virtual Compton scattering (DVCS) off a proton bound in $^4$He. The data used here were accumulated using a $6$ GeV longitudinally polarized electron beam incident on a pressurized $^4$He gaseous target placed within the CLAS spectrometer in Hall-B at the Thomas Jefferson National Accelerator Facility. The azimuthal angle ($ϕ$) dependence of the BSA was studied in a wide range of virtual photon and scattered proton kinematics. The $Q^2$, $x_B$, and t dependencies of the BSA on the bound proton are compared with those on the free proton. In the whole kinematical region of our measurements, the BSA on the bound proton is smaller by 20\% to 40\%, indicating possible medium modification of its partonic structure.

nucl-ex↗

arXiv2018

CLAS12 RICH: New Hybrid Geometry for Strangeness Studies

The Jefferson Lab CLAS12 detector will provide a world-leading facility for the study of electron-nucleon scattering. The CLAS12 physics program is very broad and includes studies on quarks dynamics as well as studies on the meson and baryon spectroscopy with quasi-real photoproduction in a large variety of final states. The particle identification will be complemented by a ring imaging Cherenkov detector (RICH), that will provide separation of kaons from protons and pions in the momentum range between 3 and 8 GeV/c allowing the study of pion and kaon electroproduction in semi-inclusive deep inelastic scattering as well as studying double and triple strange baryons. In this article, we will focus on the new technologies developed for the RICH, especially on the complex optical system, that allows to reduce the photo-detection area. Particular attention is given to the characterization of the surface in relationship with the simulation capability of GEANT4.

physics.ins-det↗