Several authors have shown better results in forecasting economic variables by considering the sentiment values in their models. Few studies have focused on the identification of the causes which explain opinions and beliefs. In this paper, we propose a methodological framework based on Distributed Lag (DL) models in order to identify dynamic causal effects in the case of temporal aggregation of sentiment values.
Temporal sentiment analysis with distributed lag models / Carannante, Maria; Mattera, R; Misuraca, M; Scepi, G; Spano, M.. - (2019), pp. 149-156. (Intervento presentato al convegno Sis 2019 tenutosi a Milano nel Giugno 2019).
Temporal sentiment analysis with distributed lag models
CARANNANTE, MARIA;Mattera, R
;Scepi, G;Spano, M.
2019
Abstract
Several authors have shown better results in forecasting economic variables by considering the sentiment values in their models. Few studies have focused on the identification of the causes which explain opinions and beliefs. In this paper, we propose a methodological framework based on Distributed Lag (DL) models in order to identify dynamic causal effects in the case of temporal aggregation of sentiment values.File in questo prodotto:
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