| 摘要: | 隨著地緣政治衝突升溫與全球供應鏈重組加速，供應鏈風險與貿易政策不確定性已成為影響金融市場波動的重要因素。本文旨在探討供應鏈壓力變化、全球運輸成本與貿易結構指標對美國股市之影響，並以 S&P 500 指數作為市場代表，建構一多元迴歸實證模型進行分析。研究期間涵蓋2012年至2024年，跨越中美貿易戰、COVID-19疫情與俄烏戰爭等重大事件。
實證模型中選用全球供應鏈壓力指數（GSCPI）、世界貨櫃運價指數（WCI）、美中雙邊關稅變化率、美國出口與進口指標、美國平均關稅稅率、世界貿易不確定性指數（WTUIGWA）、VIX波動率指數等多項變數，並設計「ISM製造業新訂單－非製造業新訂單」之差值作為產業景氣分化的代理變數。透過ADF單根檢定確認所有變數均具定態性，適合納入迴歸分析與因果檢定。
迴歸結果顯示，GSCPI、WTUIGWA、出口與進口變化、以及美國關稅等變數對 S&P 500 報酬率具高度顯著影響，顯示全球供應鏈壓力與政策不確定性為驅動市場的核心因子。部分變數如ISM新訂單差與中國關稅則未呈顯著，惟其在交互分析中仍具潛在價值。
本研究提供一套結合供應鏈、政策與市場三者之綜合評估框架，對於解釋近年市場波動來源、建構風險預警模型及判讀地緣經濟風險下資產表現，具有理論與實務貢獻。建議未來可延伸進行產業別回歸、事件研究法或地區性變數交互分析，以深化政策與供應鏈因素對金融市場之傳導機制理解。
;Amid escalating geopolitical tensions and the accelerated restructuring of global supply chains, supply chain risks and trade policy uncertainty have emerged as key drivers of financial market volatility. This study aims to investigate the effects of supply chain pressure, global transportation costs, and trade structure indicators on the U.S. stock market, using the S&P 500 index as a representative benchmark. A multiple regression empirical model is constructed to examine these relationships over the period from 2012 to 2024, encompassing critical global events such as the U.S.-China trade war, the COVID-19 pandemic, and the Russia-Ukraine conflict.
The empirical model incorporates several explanatory variables, including the Global Supply Chain Pressure Index (GSCPI), the World Container Index (WCI), bilateral tariff changes between the U.S. and China, U.S. export and import indicators, the U.S. average tariff rate, the World Trade Uncertainty Index (WTUIGWA), and the VIX volatility index. Additionally, the difference between ISM manufacturing and non-manufacturing new orders is introduced as a proxy for sectoral economic divergence. All variables are tested for stationarity using the Augmented Dickey-Fuller (ADF) test, ensuring their suitability for regression and causality analysis.
The regression results reveal that GSCPI, WTUIGWA, U.S. export and import changes, and U.S. tariff rates have statistically significant effects on the S&P 500 returns, indicating that global supply chain pressure and policy uncertainty are critical factors influencing market performance. Although variables such as the ISM order spread and Chinese tariffs do not show direct significance, they still exhibit potential value in interaction effect analysis.
This study provides an integrated framework combining supply chain, policy, and market variables, offering both theoretical and practical contributions to understanding the drivers of market volatility, constructing early warning models, and interpreting asset performance under geopolitical risks. Future research may extend the analysis by incorporating industry-level regressions, event study methodologies, or regional interaction variables to further clarify the transmission mechanisms of supply chain and policy shocks to financial markets. |
