通过高维中介分析理解行业对关税不确定性的响应

中文摘要 AI 辅助

本文进行了一项实证中介分析，以考察美国股市各行业如何应对2025年关税政策事件。利用标普500股票数据以及数百个公司层面的财务变量，我们研究了行业归属是否与股票回报差异相关，以及这些差异是否在统计上与公司财务特征相关。对于五个经济上截然不同的关税政策窗口中的每一个，我们使用高维线性因果中介模型来估计直接行业效应。我们使用线性回归模型估计总行业效应，然后通过总行业效应与直接行业效应之差来估计间接行业效应。为了容纳大量候选中介变量，我们采用部分惩罚最小二乘程序，该程序对财务变量系数进行正则化，同时不对所有行业指示变量的系数进行惩罚。使用Wald检验和F型检验分别检验间接效应和直接效应是否显著。结果表明，关税新闻并未产生统一的市场反应。行业效应在五个经济上截然不同的关税政策窗口之间有所不同。最清晰的发现体现在直接行业效应中。科技行业在最初下跌和升级崩溃期间受到负面影响最大，但在4月9日缓解反弹中也反弹最为强劲。结果表明，除科技行业外，能源和其他贸易敏感行业在最初下跌和升级阶段尤其受到影响。被选中的中介变量提供了证据，表明增长、投资、流动性、盈利能力和现金流特征有助于刻画与行业层面回报差异相关的公司特征。

英文摘要

This paper conducts an empirical mediation analysis to examine how U.S. stock-market sectors responded to the 2025 tariff-policy episode. Using S&P 500 stock data along with hundreds of firm-level financial variables, we study whether sector membership was associated with differences in stock returns and whether these differences were statistically related to firm financial characteristics. For each of five economically distinct tariff-policy windows, we use high-dimensional linear causal mediation models to estimate the direct sector effects. We use a linear regression model to estimate the total sector effects, and then estimate the indrect sector effects by using the difference between the total sector effects and the direct sector effects. To accommodate a large number of candidate mediators, we use a partially penalized least-squares procedure that regularizes financial-variable coefficients while unpenalizes coefficients of all sector indicators. Wald and F-type tests are used to examine whether indirect and direct effects are significant or not, respectively. The results show that tariff news did not produce one uniform market response. Sector effects vary across five economically distinct tariff-policy windows. The clearest findings are in the direct sector effects. Technology was the sector most negatively affected during the initial decline and escalation collapse, but it also rebounded most strongly during the April 9 relief rally. The results indicate that in addition to Technology, Energy and other trade-exposed sectors were particularly affected during the initial decline and escalation phases. The selected mediators provide evidence that growth, investment, liquidity, profitability, and cash-flow characteristics helped characterize firms associated with sector-level return differences.

发表机构

• Polytechnic School（理工学院）
• The Pennsylvania State University（宾夕法尼亚州立大学）

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