Sovereign Environmental, Social, and Governance (ESG) assessments face unique challenges distinct from corporate ESG metrics. These include significant biases like the ingrained income bias, often skew results favouring wealthier nations. Current methodologies, adapted mainly from corporate frameworks, need to reflect sovereign states' diverse socio-economic and environmental landscapes adequately. The prevalent approach in sovereign ESG evaluation excessively relies on corporate ESG methodologies, resulting in a misalignment that fails to address specific sovereign contexts. This misapplication leads to biased assessments that disproportionately favour economically prosperous countries, as they have better resources to implement sustainability practices and access data. These biases manifest as perverse investment outcomes and discouraging political incentives for less wealthy nations. To rectify these issues, we propose a new framework that integrates native and alternative data sources. Native data includes local government reports and insights from local organisations, providing a grassroots perspective often overlooked by traditional metrics. Alternative data, such as satellite imagery and social media analytics, offers real-time, dynamic insights into a country’s environmental and social conditions. This dual-data approach aims to provide a more balanced and comprehensive view of a nation’s sustainability efforts, reducing the premium price developing countries pay in global markets despite harsher financial assessments. By enhancing transparency and adapting the data collection process to fit sovereign needs, our framework seeks to create a fairer and more effective system of ESG evaluation. Embracing a broader data spectrum and refining the assessment methodology are crucial steps towards equitable and accurate sovereign ESG evaluations. This shift will help ensure that countries are rated based on sustainability efforts, promoting fairer economic conditions and supporting global environmental and social progress.
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