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Essays over de binnenlandse en internationale effecten van milieubeleid

環境政策の国内および国際的影響に関するエッセイ (AI 翻訳)

Mengxi Xie

Lirias (KU Leuven)📚 査読済 / ジャーナル2026-06-05#AI×ESGOrigin: Global経営インパクト: 調達リスク対象セクター: cross_sector
原典: https://lirias.kuleuven.be/handle/20.500.12942/787474

🤖 gxceed AI 要約

日本語

本博士論文は、機械学習(NLP)と計量経済学を組み合わせ、環境政策の効果を実証的に分析する。前半3章ではEUの炭素国境調整メカニズム(CBAM)を取り上げ、メタ分析、米国株式市場の反応、中国企業の開示戦略を検証。第4章では中国の環境モニタリング制度改革がグリーンイノベーションに与える影響を分析する。

English

This dissertation combines machine learning (NLP) with econometrics to empirically analyze environmental policies. The first three studies examine the EU's Carbon Border Adjustment Mechanism (CBAM) via meta-analysis, US equity market reactions, and Chinese firms' strategic disclosure. The fourth study evaluates China's environmental monitoring reform on green innovation.

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

📝 gxceed 編集解説 — Why this matters

日本のGX文脈において

EUのCBAMと中国の環境規制改革に関する実証分析は、日本のカーボンプライシング設計やSSBJに基づく開示実務にも示唆を与える。特に、NLPを用いた政策影響の抽出方法は、日本の気候関連開示の質的分析に応用可能。

In the global GX context

This paper provides robust empirical evidence on CBAM's market and leakage effects, and on how environmental monitoring spurs green innovation. The findings are directly relevant to global policy discussions on border carbon adjustments and regulatory design, offering lessons for the EU, US, and emerging economies.

👥 読者別の含意

🔬研究者:The NLP-based measurement of climate policy attention and strategic disclosure provides a methodological template for future policy evaluation studies.

🏢実務担当者:Firms exposed to CBAM can anticipate competitive dynamics and strategic disclosure pressures based on the market reaction and Chinese firm behavior evidence.

🏛政策担当者:The meta-analysis on leakage mitigation instruments and the Chinese monitoring reform offer evidence-based guidance for designing effective climate policies.

📄 Abstract(原文)

The intensification of climate concerns has prompted governments to adopt increasingly varied regulatory and market-based instruments intended to reduce emissions while preserving economic growth. This dissertation investigates how such environmental and climate policies affect market outcomes including firm valuation, strategic behavior, and innovation, across both international and domestic settings. The analysis comprises four empirical studies, combining text-based machine-learning methods with econometric identification strategies to provide new evidence on the consequences of environmental regulation. The first three studies examine the European Union's Carbon Border Adjustment Mechanism (CBAM), which addresses carbon leakage by pricing the emissions embodied in imported goods. The first conducts a meta-analysis of the numerical modeling literature, assembling 416 leakage-ratio estimates from 39 studies published between 2004 and 2022. Meta-regression estimates indicate that output-based rebating attains leakage mitigation comparable to that of border carbon adjustments. The second study estimates the response of U.S. equity markets to the CBAM announcement. Using a natural-language-processing measure of climate-policy attention constructed from NASDAQ financial news, it provides evidence that exposed firms in advanced economies may secure competitive gains under more stringent border carbon measures. The third study analyzes the strategic disclosure responses of Chinese firms through textual analysis of the Management Discussion and Analysis sections of their annual reports. Distinguishing disclosures concerning decarbonization from those concerning trade reallocation, and employing an event-study design with matched samples, it finds a significant increase in decarbonization disclosures among exposed firms and little evidence of trade reallocation. The fourth study turns to domestic regulation, evaluating an institutional reform of environmental monitoring of polluting firms in China. Motivated by the informational asymmetries that constrain enforcement, it assesses whether stronger monitoring induces green innovation, measured by green patent applications. A difference-in-differences design, supplemented by triple-differences estimation, yields robust evidence that enhanced monitoring significantly raises green innovation—particularly among privately owned firms—by increasing the detectability of noncompliance. Taken together, the studies integrate the international and domestic dimensions of environmental and climate policies. By extracting policy-relevant signals from large-scale textual data and combining them with credible identification strategies, the dissertation clarifies how policy shapes carbon leakage, firm valuation, strategic disclosure, and green innovation. Each study offers evidence-based implications for designing regulation that reconciles environmental objectives with economic growth and competitiveness.

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