Controlling for exogenous environmental variables when using data envelopment analysis for regional environmental...

Area of Science:

• Environmental Science
• Operations Research
• Economics

Background:

• Data Envelopment Analysis (DEA) is commonly used to evaluate environmental policy and resource allocation efficiency.
• Standard DEA models assume homogeneous operating environments, which is often unrealistic for environmental performance.
• Environmental performance can be influenced by external variables beyond managerial control, necessitating adjustments in assessment.

Purpose of the Study:

• To develop a modified DEA approach that accounts for exogenous variables influencing environmental performance.
• To differentiate between environmental conditions and managerial efficiency in performance assessments.
• To identify opportunities for improving environmental performance and resource allocation.

Main Methods:

• A four-stage procedure was applied to adjust environmental impacts within a DEA model.
• The model aims to minimize environmental impacts while achieving socioeconomic outcomes.
• Exogenous variables like climate, hydrology, and topography were examined for their role in environmental impacts.

Main Results:

• The study successfully adjusted environmental impacts for uncontrollable variables.
• A performance index was created, bundling multiple indicators.
• The approach demonstrated advantages for environmental assessment by distinguishing controllable and uncontrollable factors.

Conclusions:

• The proposed DEA method offers a more accurate assessment of environmental performance by controlling for external factors.
• This approach facilitates better identification of inefficiencies and opportunities for environmental improvement.
• The methodology provides a robust tool for environmental policy evaluation and resource management.