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Low-Income Reality Check
Evaluating the impact of dynamic pricing.
Dynamic pricing will expose retail consumers to new opportunities and challenges in electric power markets. The impact of dynamic pricing on low-income consumers deserves special attention as low-income populations have different load profiles, resulting in different abilities to respond to price signals as compared to higher income households.
In the November 2010 Fortnightly article “ Dynamic Pricing and Low-Income Customers ” by Lisa Wood and Ahmad Faruqui (the “Wood/Faruqui article”), the authors conclude that low-income customers have much to gain from dynamic pricing. 1 Given the challenge of transitioning low-income consumers into dynamic pricing, the support for this conclusion deserves full evaluation.
When considering the impact of dynamic pricing on low-income consumers, the term “low income” must be carefully defined. While the Wood/Faruqui article reports information for verified 2 low-income consumers associated with some of the studies, it also designates other income categories associated with some pilots as “low income” (even if the pilot has a verified low-income component). Juxtaposing results from verified low-income customers with customers who fall into an arbitrarily defined lower income category is likely to result in households that aren’t subject to financial hardship to be counted as “low income.”
Income levels alone aren’t sufficient to identify households with financial hardship or poverty; family size and composition contribute to a proper definition of “low income.” For example, a household with annual income of $40,000 and one member will have a very different financial profile than a household at the same income level with four members. The Wood/Faruqui analysis doesn’t always make this distinction, and as a result is more likely to find that “high-” and “low- income” customers have similar pricing responses.
Review of Empirical Data
The Wood/Faruqui article reviews information from four dynamic pricing pilot programs and one dynamic pricing tariff. Each of these programs has been previously evaluated in reports filed with public utility commissions. However, these previous reports indicate that the low-income dynamic pricing response is either not clear or shows a more limited response than higher-income consumers (see Figure 1) . The Wood/Faruqui article reevaluates these programs and arrives at a different conclusion—that low-income customers do respond to dynamic rates, and many low-income customers benefitted even without shifting load. It’s important to understand the difference in perspective regarding the potential pricing response of low-income consumers.
The Connecticut Light & Power (CL&P) Plan-It Wise energy pilot illustrates a significant problem with research regarding low-income consumers; consumers are often reluctant to reveal their income level, resulting in missing data. In the CL&P pilot, 44.1 percent of participants declined to state their income levels. While the Wood/Faruqui article states that price responsiveness of the customers who did respond to the income question is about the same as the average customer, because of the missing data problem this conclusion isn’t convincing.
The CL&P pilot also illustrates the importance of income classifications. To determine the income status of pilot