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• W4387401832 abstract "ABSTRACTThis study examines the information content of narratives to inflation forecasts. Although text analysis of news articles, central bank policy statements, and economic outlooks have increasingly gained attention, few studies consider layperson narratives. Using novel text data from Japan, we find that the sentiment indexes constructed from narratives contain additional information on consumers’ inflation forecasts. Furthermore, a sentiment index constructed using naïve Bayes provides additional information on survey-based sentiment. These findings suggest that narratives provide useful information regarding monetary policies.KEYWORDS: Textual datamachine learninginformation efficiencyinflation expectationsmonetary policyJEL CLASSIFICATION: C38E37D84 AcknowledgementsWe are grateful for the helpful suggestions from anonymous referees. The opinions expressed herein are those of the authors and do not necessarily reflect those of Dentsu Cross Brain Inc. or KINTO Technologies Co. Yoichi Tsuchiya gratefully acknowledges the financial support from the Japan Society for thePromotion of Science (JSPS; grant number JP22K01510).Disclosure statementNo potential conflict of interest was reported by the author(s).Ethical approvalThis article does not contain any studies with human participants or animals performed by any of the authors.Notes1 See Gentzkow et al. (Citation2019) for a review of the methods and their applications using text data.2 See, for example, Clements and Reade (Citation2020) for a detailed discussions on forecast efficiency tests.3 See https://www.boj.or.jp/en/research/o_survey/index.htm/for details.4 Mean forecasts are also available. Although not reported, this study obtained similar results for the mean forecasts as those for the median forecasts.5 Please refer to the Appendix for its construction.6 See https://www5.cao.go.jp/keizai3/watcher-e/index-e.html for details.7 See the notes in Appendix Table A1 and Ootaka and Kan (Citation2018) for details. See, for example, Hastie et al. (Citation2009) and Murphy (Citation2012) for details about naïve Bayes and the other three methods used in this study.8 In line with a balanced measure, the sentiment index can be also defined without ‘equal’ as follows: S=U−D/U+D. Although not reported, using this alternative definition yields the same qualitative results with the main definition in the subsequent analysis.9 Given that consumers might have lagged information, encompassing tests were conducted as a robustness check. These were with and without survey-based sentiment, using heteroscedasticity and autocorrelation-consistent standard errors with a lag of four. Although not reported, these results were consistent with the main analysis.Additional informationFundingThe work was supported by the Japan Society for the Promotion of Science [JP22K01510]." @default.
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• W4387401832 date "2023-10-06" @default.
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• W4387401832 title "Information advantage of narratives to consumers’ inflation forecasts" @default.
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• W4387401832 doi "https://doi.org/10.1080/13504851.2023.2266558" @default.
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