A Cross-Country Analysis of Unemployment and Bonds with Long-Memory Relations

T. Dimpfl, Tobias Langen
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引用次数: 1

Abstract

We analyze the relationship between unemployment rate changes and government bond yields during and after the most recent financial crisis across nine industrialized countries. The study is conducted on a weekly basis and we therefore nowcast unemployment data, which are only available once a month, on a weekly frequency using Google search query data. In order to account for the time series' long-memory components during the first-stage nowcasting and the second-stage modeling, we draw on Corsi's (2009, JEF) heterogeneous autoregressive time series model. In particular, we adapt this idea to a setting of mixed-frequency nowcasting. Our results indicate that Google searches greatly increase the nowcasting accuracy of unemployment rate changes. The impact of an idiosyncratic rise in unemployment on bond yields turns out to be positive for European countries while it is negative for the United States and Australia. The speed of the response also varies. Not unexpectedly, bond yields do not have an impact on unemployment. Our findings have interesting implications for the way shocks are absorbed in economic systems that differ, in particular, with respect to the central bank's core tasks.
失业与长记忆关系债券的跨国分析
我们分析了九个工业化国家在最近一次金融危机期间和之后的失业率变化与政府债券收益率之间的关系。这项研究每周进行一次,因此我们使用谷歌搜索查询数据,以每周的频率预报每月只提供一次的失业数据。为了在第一阶段临近预测和第二阶段建模中考虑时间序列的长记忆成分,我们借鉴了Corsi (2009, JEF)的异构自回归时间序列模型。特别地,我们将这个想法适应于混合频率临近广播的设置。结果表明,谷歌搜索极大地提高了失业率变化的临近预报精度。失业率异常上升对债券收益率的影响对欧洲国家是积极的,而对美国和澳大利亚则是消极的。反应的速度也各不相同。不出所料,债券收益率对失业率没有影响。我们的研究结果对不同经济体系吸收冲击的方式有有趣的启示,特别是在央行的核心任务方面。
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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