Engineering Economics of Rate Design and Cost Allocation Forecasting for Public Infrastructure and Regulated Services

Course Description

Engineers in regulated and public-service environments face a unique challenge: balancing technical excellence with economic reality. Your expertise in demand curves, asset lifecycles, and system peaks directly influences how communities pay for essential infrastructure. You play a key role in conversations about fairness, affordability, and financial sustainability.

This course introduces engineers to the principles and methodologies behind cost-of-service studies and rate design for regulated infrastructure and public service systems. Whether working in utilities, public works, or private-sector consulting, engineers regularly influence or implement financial strategies tied to infrastructure investments, cost recovery, and public-facing service pricing.

This course explores how to design equitable and sustainable rate structures, allocate costs based on system usage and customer impact, and forecast financial needs over the long term. Engineers will gain actionable knowledge on how to integrate technical system data with economic models to ensure services remain reliable, affordable, and compliant with regulatory and stakeholder expectations. Learners will apply concepts through practical examples and scenario-based decision-making, with emphasis on ethical and professional responsibility in rate policy design.

Learning Objectives

1. Identify the principles of cost-of-service and evaluate engineering contributions to equitable cost allocation, while distinguishing among various cost allocation methodologies appropriate for different types of infrastructure.

2. Recall forecasting techniques to support effective infrastructure investment and rate planning, while analyzing the sensitivity of financial outcomes to key forecasting assumptions and underlying uncertainties.

3. Develop rate structures that balance revenue stability, equity, and public impact, and assess trade-offs across designs under operational, regulatory, and policy constraints.

4. Recognize technical, operational, and financial data into rate and cost modeling successfully as it applies to a scenario.