Risk and retraction: asymmetric nexus between monetary policy uncertainty and eco-friendly investment

IF 3.9 3区环境科学与生态学 Q1 ENGINEERING, CIVIL Stochastic Environmental Research and Risk Assessment Pub Date : 2024-09-11 DOI:10.1007/s00477-024-02812-1

Lansheng Cao, Ding Jin, Sajid Ali, Muhammad Saeed Meo, Raima Nazar

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Abstract

Monetary policy uncertainty casts long shadows, shaping the future of financial greenscapes by influencing investment decisions and sustainability initiatives, ultimately determining the pace of our transition to a greener, renewable energy-driven economy. This research analyses the asymmetric impact of monetary policy uncertainty on green finance in the top ten advocates of green funding (USA, China, Germany, UK, France, Sweden, Japan, the Netherlands, Canada, and Spain). Moving beyond traditional panel data methods that ignore country-specific nuances, we adopt the Quantile-on-Quantile approach for a more nuanced understanding. This approach enhances accuracy by offering a global overview and detailed insights for each country individually. The findings reveal that monetary policy uncertainty curtails green finance in most of the selected economies across various quantiles. Our estimation underscores the imperative for policymakers to conduct thorough analyses and develop strategies to address the changes in monetary policy uncertainty and green finance at various levels.

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风险与回缩：货币政策不确定性与生态友好型投资之间的非对称关系

货币政策的不确定性投下了长长的阴影，通过影响投资决策和可持续发展举措来塑造未来的绿色金融景观，最终决定了我们向更绿色、可再生能源驱动的经济转型的步伐。本研究分析了货币政策不确定性对十大绿色资金倡导国（美国、中国、德国、英国、法国、瑞典、日本、荷兰、加拿大和西班牙）绿色金融的非对称影响。传统的面板数据方法会忽略各国的细微差别，而我们采用的量化对量化方法则超越了这一局限，使我们对问题的理解更加细致入微。这种方法既能提供全球概览，又能针对每个国家的具体情况提供详细见解，从而提高了准确性。研究结果表明，在大多数选定经济体中，货币政策的不确定性抑制了不同量化值的绿色融资。我们的估算强调了政策制定者必须进行全面分析并制定战略，以应对货币政策不确定性和绿色金融在各个层面的变化。

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来源期刊

Stochastic Environmental Research and Risk Assessment 环境科学-工程：环境

CiteScore

7.10

自引率

9.50%

发文量

189

审稿时长

3.8 months

期刊介绍： Stochastic Environmental Research and Risk Assessment (SERRA) will publish research papers, reviews and technical notes on stochastic and probabilistic approaches to environmental sciences and engineering, including interactions of earth and atmospheric environments with people and ecosystems. The basic idea is to bring together research papers on stochastic modelling in various fields of environmental sciences and to provide an interdisciplinary forum for the exchange of ideas, for communicating on issues that cut across disciplinary barriers, and for the dissemination of stochastic techniques used in different fields to the community of interested researchers. Original contributions will be considered dealing with modelling (theoretical and computational), measurements and instrumentation in one or more of the following topical areas: - Spatiotemporal analysis and mapping of natural processes. - Enviroinformatics. - Environmental risk assessment, reliability analysis and decision making. - Surface and subsurface hydrology and hydraulics. - Multiphase porous media domains and contaminant transport modelling. - Hazardous waste site characterization. - Stochastic turbulence and random hydrodynamic fields. - Chaotic and fractal systems. - Random waves and seafloor morphology. - Stochastic atmospheric and climate processes. - Air pollution and quality assessment research. - Modern geostatistics. - Mechanisms of pollutant formation, emission, exposure and absorption. - Physical, chemical and biological analysis of human exposure from single and multiple media and routes; control and protection. - Bioinformatics. - Probabilistic methods in ecology and population biology. - Epidemiological investigations. - Models using stochastic differential equations stochastic or partial differential equations. - Hazardous waste site characterization.