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The Paradox of Inclining Block Rates

What goes up doesn’t always come down.

Fortnightly Magazine - April 2015

In an earlier paper , one of us showed that inclining block rates (IBRs) could be used to promote energy efficiency by reducing energy consumption. That paper1 simulated the effect on energy consumption of moving from a flat rate to each of four different two-tiered IBRs. For all four of the rates that I (Ahmad Faruqui) had examined in that earlier paper, aggregate consumption went down. I had found also that the steeper the rise between the tiers, the more was the amount of energy conservation. Subsequent to the paper's circulation, some analysts concluded that the paper had arrived at a general conclusion: that IBRs were synonymous with energy conservation.

In this paper, which I have coauthored with two of my colleagues, we put that proposition to the test by running a reverse simulation.

In this instance, however, instead of dealing with a hypothetical utility, we provide case studies of two California utilities, Pacific Gas & Electric Company (PG&E) and Southern California Edison (SCE). And understand also that the state of California has a long history with IBRs, going back to the introduction of lifeline rates in the seventies. During those days, there were only two tiers and the differential between the tiers was around 20 percent. After the energy crisis of 2001-02, three additional tiers were introduced, to mitigate the effect of the rate hike on small users. Over time, all inflation that occurred was piled on to the upper three tiers and the differential between the tiers was accentuated.

Figure 1 - Current and Proposed PG&E Rates

A few years ago the five tiers were reduced to four. The utilities are now proposing to further reduce the number of tiers down to two and to flatten the differential between the tiers.

In this paper we simulate the impact of this rate change under a variety of assumptions about the price elasticity of electricity consumption and using three different methodologies for modeling customer response to price changes: average price, marginal price and tier-specific price. The first two methodologies required the use of individual customer data which we were able to get in the form of random samples of a few thousand customers. The third methodology can be carried out with aggregate data and was used in the prior paper.

Using these two utilities as a test bed, we find that the effect of flattening the rates on consumption is very small, ranging from an increase in consumption of 1 percent to a decrease of 1 percent. The reason for this paradoxical result is that consumption in the lower tiers faces a higher price and consumption in the higher tiers faces a lower price. When summed up, these countervailing effects tend to cancel each other out.

We conclude by noting that the answer depends on three things: the specifics of the rate design change, the nature of the evaluation

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