专业预测人员是否对公众关于通货膨胀的讨论缺乏关注?阿根廷的案例

IF 3.4 3区 经济学 Q1 ECONOMICS
J. Daniel Aromí, Martín Llada
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引用次数: 0

摘要

我们评估了专业预测人员是否从社交媒体上的公众讨论中获取了有价值的信息。研究以阿根廷 2016-2022 年期间的通货膨胀为例。我们发现了与 "不关注 "一致的确凿证据。一个简单的指标表明,社交媒体上对通胀的关注度可以预测专业预测误差。该指标每增加一个标准差,随后一个月的平均预测误差就会增加 0.4%,并在接下来的 6 个月中累计增加 0.7%。此外,社交媒体内容预计会大幅修正针对未来多个月通胀和日历年通胀的预测。这些发现与之前记录的注意力不集中的形式不同。通过实施样本外预测和使用另一个社交网络的内容,验证了一致的结果。这项研究对在决策过程中使用专业预测具有重要意义,并为宏观经济学中不完全信息的性质提供了新的证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Are professional forecasters inattentive to public discussions about inflation? The case of Argentina

We evaluate whether professional forecasters incorporate valuable information from public discussions on social media. The study covers the case of inflation in Argentina for the period 2016–2022. We find solid evidence consistent with inattention. A simple indicator of attention to inflation on social media is shown to anticipate professional forecast errors. A one standard deviation increment in the indicator is followed by a rise of 0.4% in mean forecast errors in the subsequent month and by a cumulative increment of 0.7% over the next 6 months. Furthermore, social media content anticipates significant revisions in forecasts that target multiple months ahead inflation and calendar year inflation. These findings are different from previously documented forms of inattention. Consistent results are verified by implementing out-of-sample forecasts and using content from an alternative social network. The study has implications for the use of professional forecasts in the context of policymaking and sheds new evidence on the nature of imperfect information in macroeconomics.

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来源期刊
CiteScore
5.40
自引率
5.90%
发文量
91
期刊介绍: The Journal of Forecasting is an international journal that publishes refereed papers on forecasting. It is multidisciplinary, welcoming papers dealing with any aspect of forecasting: theoretical, practical, computational and methodological. A broad interpretation of the topic is taken with approaches from various subject areas, such as statistics, economics, psychology, systems engineering and social sciences, all encouraged. Furthermore, the Journal welcomes a wide diversity of applications in such fields as business, government, technology and the environment. Of particular interest are papers dealing with modelling issues and the relationship of forecasting systems to decision-making processes.
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