本研究旨在探討全球碳定價機制在效益上的差異及其協調問題，並為建立一套跨境碳定價協調框架提供實證分析、創新思路和政策建議。面對日益嚴峻的氣候變遷挑戰，各國實施的碳定價機制存在顯著差異，導致碳洩漏、競爭力不均等問題，阻礙全球減排目標的實現。本研究運用Python大數據分析技術，收集並分析了全球主要經濟體的碳定價數據、雙邊貿易流數據以及產業碳排放數據，建立了多維度分析框架，評估不同碳定價機制的效能與影響。
研究結果顯示，碳定價與減排效果之間存在非線性關係，50-100美元/噸CO₂e區間有最佳減排效果，超過100美元/噸後減排效果反而下降，呈現"邊際遞減效應"。不同地區和收入群體間的碳定價水平存在顯著差異，歐洲與中亞地區和高收入國家維持較高碳定價，其他地區與中低收入國家碳定價相對較低，且差距呈擴大趨勢。透過複迴歸分析發現，地理區域(拉丁美洲與加勒比海地區、東亞與太平洋地區、撒哈拉以南非洲地區、北美地區、歐洲與中亞地區)、收入水平(高收入、中上等、中低收入)、政策工具類型(ETS)、轄區覆蓋比例、年份是影響群體碳定價的顯著因素，政策工具類型(碳稅)和機制實施年限不顯著。透過隨機森林模型分析發現，轄區覆蓋比例、機制實施年限和收入水平是影響群體碳定價水平的三大關鍵因素。此外，國家間碳定價差距與碳定價機制類型呈現相關性，較大的碳定價差距可能導致碳洩漏問題，這為碳邊境調整機制(CBAM)的實施提供了理論依據。

This study investigates the effectiveness of global carbon pricing mechanisms and the challenges of cross-border coordination. Using Python-based big data analytics, we compile carbon pricing data from major economies, bilateral trade flows, and sectoral emissions to construct a multi-dimensional assessment framework. Results reveal a nonlinear relationship between carbon pricing and emission reduction: the range of USD 50–100 per ton of CO₂e achieves the greatest mitigation effect, while effectiveness diminishes beyond USD 100 per ton. Significant disparities exist across regions and income groups, with Europe, Central Asia, and high-income countries maintaining higher prices, while other regions and lower-income countries set lower levels, widening the global gap.
Regression analysis shows that geographic region, income level, ETS adoption, coverage, and year significantly shape pricing levels, while carbon tax type and policy duration are not. Random forest models further highlight jurisdictional coverage, years of implementation, and income level as key drivers. Cross-country disparities in pricing are closely linked to mechanism types, with larger gaps increasing risks of carbon leakage and supporting the case for Carbon Border Adjustment Mechanisms (CBAM).

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