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The power of text-based indicators in forecasting Italian economic activity
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Aprigliano, Valentina, Emiliozzi, Simone, Guaitoli, Gabriele, Luciani, Andrea, Marcucci, Juri and Monteforte, Libero (2023) The power of text-based indicators in forecasting Italian economic activity. International Journal of Forecasting, 39 (2). pp. 791-808. doi:10.1016/j.ijforecast.2022.02.006 ISSN 0169-2070.
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Official URL: http://doi.org/10.1016/j.ijforecast.2022.02.006
Abstract
Can we use newspaper articles to forecast economic activity? Our answer is yes; and, to this end, we propose a high-frequency Text-based Economic Sentiment Index (TESI) and a Text-based Economic Policy Uncertainty (TEPU) for Italy. Novel survey evidence regarding Italian firms and households supports the rationale behind studying text data for the purposes of forecasting. Such indices are extracted from approximately 1.5 million articles from 4 popular newspapers, using a novel Italian economic dictionary with valence shifters. The TESI and TEPU can be updated daily for the whole economy and for specific sectors or economic topics. To test the predictive power of our indicators, we propose two forecasting exercises. Firstly, we use Bayesian Model Averaging (BMA) techniques to show that our monthly text-based indicators greatly reduce the uncertainty surrounding the short-term predictions of the main macroeconomic aggregates, especially during recessions. Secondly, we employ these indices in a weekly GDP tracker, achieving sizeable gains in forecasting accuracy, both in normal and turbulent times.
Item Type: | Journal Article | ||||||||
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Subjects: | H Social Sciences > HB Economic Theory H Social Sciences > HD Industries. Land use. Labor Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software |
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Divisions: | Faculty of Social Sciences > Economics | ||||||||
Library of Congress Subject Headings (LCSH): | Business forecasting, Business forecasting -- Italy, Macroeconomics, Text data mining , Sentiment analysis | ||||||||
Journal or Publication Title: | International Journal of Forecasting | ||||||||
Publisher: | Elsevier | ||||||||
ISSN: | 0169-2070 | ||||||||
Official Date: | April 2023 | ||||||||
Dates: |
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Volume: | 39 | ||||||||
Number: | 2 | ||||||||
Page Range: | pp. 791-808 | ||||||||
DOI: | 10.1016/j.ijforecast.2022.02.006 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Copyright Holders: | Elsevier | ||||||||
Date of first compliant deposit: | 14 June 2022 |
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