From Informality to Green Development: How the Shadow Economy Affects Green Finance, Green Innovation, and Green Trade
インフォーマリティからグリーン開発へ：シャドウエコノミーがグリーンファイナンス、グリーンイノベーション、グリーントレードに与える影響 (AI 翻訳)
S. Rahman, Muhammad Ibrahim Khan, J. Hussain, Imran Ali Khan
🤖 gxceed AI 要約
日本語
本論文はOECD28カ国(1996-2024)を対象に、シャドウエコノミーがグリーンファイナンス、グリーンイノベーション、グリーントレードに与える影響を分析。MIMIC手法と機械学習・量子ニューラル予測モデルを用いて、インフォーマル経済がグリーン開発を阻害することを発見。政策提言としてシャドウエコノミー削減の必要性を強調。
English
This study examines the impact of the shadow economy on green finance, green innovation, and green trade across 28 OECD countries from 1996 to 2024. Using MIMIC estimation and advanced machine/deep learning models (Lasso, Ridge, Quantum-Inspired Neural Forecasting), it finds that a larger shadow economy significantly hinders green development, especially in regimes with higher green transition. Policy recommendations focus on reducing informality.
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
日本でもインフォーマル経済の規模は限定的だが、中小企業の脱税や非公式取引がグリーン投資の妨げになる可能性がある。本論文はOECD加盟国として日本への示唆を含むが、直接的な政策連動は薄い。
In the global GX context
The paper contributes to global understanding of how economic informality undermines green transition. While OECD-focused, it offers empirical evidence for policymakers in countries with large shadow economies, linking informality to reduced green finance and innovation. Not directly tied to disclosure frameworks but relevant for transition finance.
👥 読者別の含意
🔬研究者:Provides evidence on the macro-level link between shadow economy and green development, useful for studying barriers to green transition.
🏛政策担当者:Offers insights for designing enforcement mechanisms to support green policies by reducing informality.
📄 Abstract（原文）
Achieving green transition has become an essential policy priority for which economies need to mobilize green finance, increase green innovation, and promote trade in environmentally sustainable goods and services. However, the effectiveness of policies for enhanced green development depends not only on their design but also on their enforcement and mobilizing revenue, which may potentially be undermined by the shadow economy. This study investigates the impact of the shadow economy on green development dynamics—green finance, green trade, and green innovation—in the 28 OECD countries over the period of 1996–2024. To overcome the data limitation, the study estimates the size of the shadow economy till 2024 by employing the Multiple Indicators and Multiple Causes (MIMIC) technique. Methodologically, the study integrates advanced econometric techniques, such as Methods of Moments Quantile Regression and CS‐ARDL, with machine and deep learning models (Lasso, Ridge, and Quantum‐Inspired Neural Forecasting Model) to estimate and forecast the relationship among the variables, respectively. The study found a negative and significant impact of the shadow economy on green development, as increasing economic informality is negatively associated with green finance, innovation, and trade across quantiles. The forecasting models corroborate these outcomes and explore that the unfavorable impact of informality on green development intensifies in regimes with higher green transition. The results suggest that economic informality hinders not only the initiation but also the scaling of green development. The study suggests several policy recommendations to reduce the shadow economy and its adverse impact on green development.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1002/bse.71038first seen 2026-07-13 07:10:55
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