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新冠疫情及之后:关于短期工作者对国内生产总值当前信息及预测的信息含量回顾

Covid-19 outbreak and beyond: a retrospect on the information content of short-time workers for GDP now- and forecasting.

作者信息

Kaufmann Sylvia

机构信息

Study Center Gerzensee, Foundation of the Swiss National Bank, Dorfstrasse 2, 3115 Gerzensee, Switzerland.

Faculty of Business and Economics, University of Basel, Peter Merian-Weg 6, 4002 Basel, Switzerland.

出版信息

Swiss J Econ Stat. 2023;159(1):2. doi: 10.1186/s41937-023-00106-x. Epub 2023 Jan 31.

Abstract

We document whether a simple, univariate model for quarterly GDP growth is able to deliver forecasts of yearly GDP growth in a crisis period like the Covid-19 pandemic, which may serve cross-checking forecasts obtained from elaborate and expert models used by forecasting institutions. We include shocks to the log number of short-time workers as timely available current-quarter indicator. Yearly GDP growth forecasts serve cross-checking, in particular at the outbreak of the pandemic.

摘要

我们记录了一个用于季度GDP增长的简单单变量模型是否能够预测像新冠疫情这样的危机时期的年度GDP增长,这可以用于对预测机构使用的复杂专业模型所获得的预测进行交叉检验。我们将短期工人对数的冲击作为及时可得的本季度指标纳入其中。年度GDP增长预测可用于交叉检验,尤其是在疫情爆发时。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7c29/9887556/d507f68dad80/41937_2023_106_Fig1_HTML.jpg

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