Covid-19 爆发及其后:短工信息含量对现在和预测 GDP 的回溯。

Q1 Mathematics Swiss Journal of Economics and Statistics Pub Date : 2023-01-01 Epub Date: 2023-01-31 DOI:10.1186/s41937-023-00106-x
Sylvia Kaufmann
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引用次数: 0

摘要

我们记录了一个简单的单变量季度 GDP 增长模型是否能够在 Covid-19 大流行病这样的危机时期提供全年 GDP 增长预测,这可能有助于交叉检验预测机构使用的精心设计的专家模型所获得的预测。我们将短工人数对数的冲击作为及时可用的当季指标。年度 GDP 增长预测可用于交叉检验,尤其是在大流行病爆发时。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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.

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来源期刊
Swiss Journal of Economics and Statistics
Swiss Journal of Economics and Statistics Mathematics-Statistics and Probability
CiteScore
5.20
自引率
0.00%
发文量
18
审稿时长
15 weeks
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