PUF Affordability Seminars

Publication of “The Electric Affordability Factbook” on the seventeenth of January and “Modeling Affordability of the Energy Transformation” on the first of February has stirred a lot of interest in this research and its implications.

So, the Public Utilities Fortnightly team has developed two seminars. One for an organization’s leaders and communications professionals. One for an organization’s analysts and regulatory professionals. Brief descriptions below.

Shoot us an email if your organization might want some more info on either. Joe Paparello, paparello@fortnightly.com.

Communicating Electric Affordability

This seminar, in two one-hour scheduled sessions, for leaders and communications professionals of an organization, will provide a new understanding of today's and tomorrow's affordability challenges facing the electric utilities industry. Based on a dozen years of quantitative research by Public Utilities Fortnightly Executive Editor Steve Mitnick.

"Communicating Electric Affordability" will explore these topics: defining affordability, affordability myths, the affordability paradox, identifying unaffordability households, effectively addressing unaffordability, today's versus tomorrow's affordability, role of the revenue requirements model, projecting tomorrow's affordability, talking about tomorrow's affordability.

Electric Affordability Analytics

This seminar, in two one-hour scheduled sessions, for analysts and regulatory professionals of an organization, will discuss quantitative methods and data sets for better assessing affordability challenges and strategies in given utility service territories. Based on a dozen years of quantitative research by Public Utilities Fortnightly Executive Editor Steve Mitnick.

"Electric Affordability Analytics" will explore these topics: getting the most out of the Consumer Expenditure Survey data sets, Gross Domestic Product data sets, Consumer Price Index and Real Earnings data sets, Census data sets, Federal Reserve Bank of St. Louis data sets, the several consumer sentiment data sets, and housing, construction and retail sales data sets; developing metrics of affordability; modeling affordability