Which Countries Are Leading in Protecting Our Planet?

Implementing DEA for ESG Efficiency: First step

In the previous article, we discussed the growing importance of Environmental, Social, and Governance (ESG) metrics, not only for businesses but also for countries. As we shift from merely understanding ESG factors to evaluating their efficiency, Data Envelopment Analysis (DEA) becomes a vital tool. With DEA, we can measure how well countries or organizations convert their resources (inputs) into positive ESG outcomes (outputs).

Now, we move into the practical application of DEA using real-world data. The goal is to assess the ESG performance of various countries by analyzing how efficiently they use resources like energy, land, and water to achieve outcomes such as access to electricity, social equity, and environmental protection.

1. Inputs and Outputs Selection:

For the DEA model, we will use a selection of inputs (resource usage) and outputs (ESG performance outcomes) based on the data available from the World Bank Group. The indicators are chosen to reflect core ESG dimensions, environmental sustainability, social progress, and governance efficiency.

• Inputs:
  • Annual Freshwater Withdrawals (% of internal resources): Reflecting water resource consumption, a key environmental resource.
  • Agricultural Land (% of land area): Representing the proportion of land used for agriculture, a measure of land resource consumption.
  • Energy Use (kg of oil equivalent per capita): Reflecting the energy consumption of a country, linked to both environmental sustainability and social development.
• Outputs:
  • Access to Electricity (% of population): Measuring social welfare through access to energy, a key aspect of development.
  • Access to Clean Fuels for Cooking (% of population): An indicator of environmental and social progress, reflecting access to clean energy resources.
  • Coastal Protection (% protected): Measuring efforts to protect vital environmental assets, linked to sustainability.
  • Control of Corruption (Estimate): A key governance outcome, refelcting how effectively a country manages corruption.

2. Optimistic Dataset Preparation:

Some ESG indicators in the dataset, such as those related to social metrics, may come with uncertainty bounds or plausible ranges, meaning that the exact values are not always known. However, many of the current inputs and outputs are provided as fixed values. For the cases where bounds exist, we’ll focus on the optimistic scenario, assuming the best possible outcomes. This involves:

• Using the lower bounds of the inputs (resources used) when available.
• Using the upper bounds of the outputs (performance outcomes) for those specific indicators.

By doing so, we can evaluate how efficiently each country operates under the assumption that they are performing at their best potential, within the given data range where such variability is present.

3. What’s Next?:

In the next article, we will dive deeper into the data preparation process:

• How do we extract and organize the relevant ESG data?
• What steps are involved in cleaning the data and handling missing values?
• How do we structure the data for efficiency evaluation? We will walk through these steps to ensure the dataset is ready for modeling. This preparation stage is essential for making sure our Data Envelopment Analysis results accurately reflect the performance of each country.