贸易政策不确定性下的企业投资:过去的教训,未来的总统

IF 3.9 3区 经济学 Q1 BUSINESS, FINANCE
Vaibhav Keshav
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引用次数: 0

摘要

在2025-2028年美国总统任期内,我们可以从之前的中美贸易冲突中得到什么启示?2016年至2019年期间,中美贸易争端,美国的关税和中国的报复,贸易政策的不确定性(TPU)激增。与以往关注总体经济政策不确定性(EPU)的研究不同,本研究通过使用一个新的工具变量,报告了总体和企业层面的TPU与企业投资之间的反向因果关系。除了确认实物期权渠道外,我还确定了一个外汇渠道,突出了企业对基于汇率波动的TPU的敏感性。最后,我讨论了这项研究在即将到来的美国总统大选及其后的背景下的含义。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Corporate investment amid trade policy uncertainty: Past lessons, future presidency
What insights can we glean from the prior trade conflict between the US and China amidst its prominence in the 2025–2028 presidential term? Between 2016 and 2019, the US–China trade dispute, with US tariffs and Chinese retaliation, surged trade policy uncertainty (TPU). Departing from prior studies focusing on overall economic policy uncertainty (EPU), this study reports an inverse causal relation between aggregate and firm-level TPU and corporate investment by employing a novel instrumental variable. Apart from confirming the real options channel, I identify a foreign exchange channel, highlighting the susceptibility of firms to TPU based on exposure to exchange rate fluctuations. Lastly, I discuss the implications of this study in the context of the upcoming US presidential elections and beyond.
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来源期刊
CiteScore
7.30
自引率
8.30%
发文量
168
期刊介绍: The focus of the North-American Journal of Economics and Finance is on the economics of integration of goods, services, financial markets, at both regional and global levels with the role of economic policy in that process playing an important role. Both theoretical and empirical papers are welcome. Empirical and policy-related papers that rely on data and the experiences of countries outside North America are also welcome. Papers should offer concrete lessons about the ongoing process of globalization, or policy implications about how governments, domestic or international institutions, can improve the coordination of their activities. Empirical analysis should be capable of replication. Authors of accepted papers will be encouraged to supply data and computer programs.
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