no code implementations • 13 Mar 2024 • Giovanni Angelini, Luca Fanelli, Luca Neri
When in proxy-SVARs the covariance matrix of VAR disturbances is subject to exogenous, permanent, nonrecurring breaks that generate target impulse response functions (IRFs) that change across volatility regimes, even strong, exogenous external instruments can result in inconsistent estimates of the dynamic causal effects of interest if the breaks are not properly accounted for.
no code implementations • 27 Nov 2023 • Kamyar Zeinalipour, Tommaso laquinta, Asya Zanollo, Giovanni Angelini, Leonardo Rigutini, Marco Maggini, Marco Gori
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.
no code implementations • 27 Nov 2023 • Giovanni Angelini, Marco Ernandes, Tommaso laquinta, Caroline Stehlé, Fanny Simões, Kamyar Zeinalipour, Andrea Zugarini, Marco Gori
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.
no code implementations • 10 Oct 2022 • Giovanni Angelini, Giuseppe Cavaliere, Luca Fanelli
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.
no code implementations • 22 Jul 2022 • Giovanni Angelini, Giuseppe Cavaliere, Enzo D'Innocenzo, Luca De Angelis
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.