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Winners and Losers from Flattening Tiered Electricity Prices

The California Public Utilities Commission is moving closer to major changes in the steeply increasing-block residential electricity rates that the state has had since the 2000-01 California electricity crisis.  This Friday the Commissioners may decide to significantly flatten the tiered rate structure.  In a blog post last fall, I discussed the inefficiency of charging tiered prices that don’t reflect cost and the unfairness of charging different customers different prices for the same good – a kilowatt-hour (kWh) of electricity.

In that blog, I also addressed the three standard arguments that defenders of such steeply tiered pricing commonly put forward.  The first is that increasing-block pricing yields conservation.  While in theory this could happen, the best empirical work on this subject, by (my former student) Professor Koichiro Ito shows that it is likely to have about zero effect on overall consumption.  It does encourage high-consumers to consume less, but it also encourages lower-using households to consume more.  Professor Ito shows that the net effect is no reduction in overall consumption.

The second argument is that supplying electricity to high-use households is more expensive per kWh on average, because they consume more at peak times.  My own research has shown the difference is so small that it would justify less than a one-cent differential in price between high-use and low-use customers.

The third argument carries the most weight, that higher-use customers are on average higher-income customers.  That’s true, as I showed in research published in 2012, using household consumption data from 2006.  However, like most states, California has a separate tariff for the lowest-income customers: households up to 200% of poverty-level income are eligible for the CARE program and pay much lower rates.  With the CARE program now covering about 30% of all residential customers, is tiered pricing in the standard residential rate an effective way to help lower-income households?

My 2012 paper just showed the average bill change for households in each income bracket, not the distribution of changes within each bracket.  There is another issue of equity if a program designed to transfer wealth from high-income to low-income households actually does a poor job of targeting either group, harming many low-income and/or benefitting many high-income customers.  This week I went back to the usage data from 2006 to see how great of a concern that should be.

Using PG&E data, I applied my earlier work on usage and household income to current electricity rates and the flatter tariff that a CPUC administrative law judge has proposed.  I estimated the range of impacts the proposed change would have on households across the income spectrum.


The figure above shows Pacific Gas & Electric’s current residential rate and an alternative rate that would raise the same revenue, but would have only two tiers with a 20% increase between them, as the ALJ has proposed.[1]  The first thing to note is that the new rate would be higher for consumption out to what is currently the third tier, the point where the two lines cross at 130% of baseline quantity.  In order to be a “structural” winner with the flatter rate – that is, paying less without changing consumption at all — the household would have to be consuming out beyond the crossing point in order to offset the higher marginal prices for the lower kWhs.

In this case, the breakeven point is at 216% of baseline quantity.  The median household consumes about 130% of baseline quantity, so that means most households would pay more.  By my calculation about 21% of households would save, while about 79% would see a bill increase if no one changed consumption.   This reflects the fact that since the electricity crisis the great majority of price increases have been placed on the highest-use customers, resulting in the steep tiers.

Using census data and applying a statistical matching method I developed in the 2012 research, I estimated into which of 5 income bracket each household falls.   I focused on the customers who are not on CARE, because CARE households are on a separate tariff.   The 5 income brackets are based on census categories that are roughly equal parts of the entire population.  As the table shows, however, in this analysis the bottom two brackets are smaller due to the substantial participation in CARE.

Income Bracket 1 2 3 4 5
Income ($2015) Under $27,400 $27,400-$54,800 $54,800-$82,200 $82,200-$137,000 Over $137,000
Share of non-CARE customers 2% 16% 23% 31% 28%
Average change in Monthly Bill with 2-tier tariff $5.84 $4.59 $2.40 $0.70 -$5.78
Percent Structural Winners 5% 12% 18% 22% 32%

Next, I calculated how much the average monthly bill of each household would change if the rate were changed to the two-tiered structure in the figure above (and the household did not change its consumption).  The third row of the table above shows the average bill change for households in each income bracket.  Not surprisingly, because lower income households consume less on average, they are more likely to see their bills go up with the change.  But even in the highest income bracket more than two-thirds of customers would see bill increases.

What was particularly surprising to me is the figure below, which shows the distribution of the change in bills for each of the income brackets.  The impacts across brackets are more similar than I expected.     In every income bracket two-thirds or more of the customers see their bills rise between $0 and $20 per month, even in the highest-income bracket.  Are these high-income households that don’t use much electricity super-conservers?  Maybe, but I bet many of them are households with only one or two people, who work and travel a lot, and don’t spend much time at home.


About 4% of households are the biggest winners with bills dropping by at least $50 per month under the proposed tariff.  Are these “energy hogs”? Maybe, but I bet some of them are big families and people who are home all day, because they are retired or have small children.   Among these biggest winners, I estimate that slightly less than half are in the highest-income bracket.

Undoing the steeply tiered rates that were created during California’s electricity crisis will on average cause lower-income households to pay more.  If there were no other consequences of the steep tiering, I could see keeping it on that basis.  But there are other impacts on both efficiency and fairness, not the least of which is the monthly harm to higher-consuming, middle- and lower-income households that is caused by a rate structure that has no basis in costs.

Some opponents of the two-tiered rate proposal have presented it as a simple shift of payments from poor to rich.  This analysis shows that the story is not that simple.  Both winners and losers are present at every income level.  The two-tier proposal makes bills more cost-based and more proportional to usage, as they were before 2000.  And as they are in nearly all other states, and in the parts of California served by municipal utilities.

I’m still tweeting energy news articles and new research papers @BorensteinS 

[1] All of these calculations assume no consumption response to the tariff change.  As I show in my 2012 paper, accounting for the small elasticity that has been estimated for response to a change in increasing-block pricing makes very little difference to these calculations.



Severin Borenstein View All

Severin Borenstein is E.T. Grether Professor of Business Administration and Public Policy at the Haas School of Business and Faculty Director of the Energy Institute at Haas. He has published extensively on the oil and gasoline industries, electricity markets and pricing greenhouse gases. His current research projects include the economics of renewable energy, economic policies for reducing greenhouse gases, and alternative models of retail electricity pricing. In 2012-13, he served on the Emissions Market Assessment Committee that advised the California Air Resources Board on the operation of California’s Cap and Trade market for greenhouse gases. He chaired the California Energy Commission's Petroleum Market Advisory Committee from 2015 until its completion in 2017. Currently, he is a member of the Bay Area Air Quality Management District's Advisory Council and a member of the Board of Governors of the California Independent System Operator.

19 thoughts on “Winners and Losers from Flattening Tiered Electricity Prices Leave a comment

  1. I fully agree with the findings reported in this blog. I agree with the call to flatten increasing-block pricing rates on the following grounds:
    • I can attest to the fact through my own research as an energy consultant that steeply increasing-block residential electricity rates do significantly contribute to more energy conservation at the higher rate tiers but significant increase in energy consumption at the lower energy conservation rate tiers. Unless steeply tiered rates are backed up with stringent end-use energy efficiency standards and programs, steeply increasing-block residential electricity rates can lead to excessive net growth in electricity consumption. The electricity demand growth rates exhibited by the GCC of 10% or about annually are a case in point. I elaborated on this point in my response to earlier EI blogs on electricity demand growth in the developing countries.
    • Steeply increasing-block residential electricity rates contribution to a correction in income inequality between the rich and the poor is minimal. Assistance to electricity consumers below the poverty level should be administered through a welfare mechanism totally separate from utility and regulatory agencies’ rate structure and administration.
    • As reported correctly by Professor Borenstein in a previous blog, high electricity tiers in combination with solar credits and subsidies do encourage higher income electricity consumers to adopt solar energy and at the same time discourage lower income electricity consumers to adopt solar energy. In absence of energy efficiency programs and policies that guide the adoption of residential solar power and end-use energy consumption, high tiers electricity rates would lead to the adoption of residential solar energy by higher income electricity consumers. This in turn directly leads to the reduction of their effective marginal cost of electricity that in turn 1) reduces the incentive for higher income electricity consumers to invest in end-use energy efficiency, 2) increases the potential for over sizing and hence suboptimal sizing of solar power installed, and 3) reduction in the utility’s blue chip customer revenue share and increase in their costs. Flattened tiered rates along with properly designed solar subsidies and energy efficiency programs will prevent residential solar crowding out end-use energy efficiency and achieve better sizing of residential solar.
    • Another reason I would venture to add in favor of flattened tiered electricity rates is the use of electricity pricing as well as electricity infrastructure planning as an instrument of public policy. This is likely to remain with us for a long time to come. This is in the nature of electricity as a public good. The flattening of tiered electricity rate structures and its replacement with a cost based rate structure is likely to lessen the extent to which pricing is used as an instrument of public policy.
    • Notwithstanding power industry developments over the past 40 years or about ranging from the realization of electricity markets as contestable, unbundling of electricity sectors’ accounts, divestiture of generation, the entry of organized markets, and the rise of demand response and management and finally the entry of renewables, flatter electricity pricing tiered rates is likely to be welcome news to utilities in the 21st century pondering the impact of distributed generation, micro grids, pricing of GHG, and fuel allocation would have for the utility of the future.

  2. Are you saying that electricity consumption is not really affected by adding a cost to GHG on the order of $40/ton? Utilities would switch fuels in response to this cost, but few consumers would change our behavior?

  3. One of the losers here is curious why we are paying SO much for electricity. I can’t find details anywhere: cost of fossil fuel, hydro, and nuclear kWh; transmission and distribution; repairing old infrastructure; billing; subsidies/higher rates for renewables; higher rates for fossil fuels backing up renewables; batteries; paying off the 2000-1 electricity fiasco… I assume some of the recent increase is the loss of cheap hydro all up and down the West Coast.

    EIA says that in 2014 average California retail price was 13.5 cents/kWh

    • As a relatively new resident of this state, I’ve been asking the same question. Surely there’s more policy makers could be doing to ease the pain of energy bill beyond merely arguing over rate structure – like somehow bringing down overall costs.

  4. I am skeptical that there is significant elasticity in demand in direct response to a tiered-rate structure. The only research I have seen that tried to measure that and control for other effects did not adequately separate the total monthly bill from the tiered marginal rates. It is easy to understand why this is hard to measure in the real world. The way steeply tiered rates have been implemented in California for the most part yields a higher average cost (i.e. total monthly bill) for the same quantity. So it is very difficult to find household pairs to compare gradual vs steep tiers with the same average cost and control all other factors.

    Given that, in my opinion, if the changes are revenue neutral they will not have any material net effect on total aggregate quantity demand in California. In that case, this is a purely political question of who pays for what.

    • Have you seen Ito’s study that Severin references? It largely solves the paired comparison problem.

      On the other hand, the E3 BC Hydro study fails to include the effects on low usage customers so it gives a biased result.

      • Yes I have.

        Without getting into the hard-core math, let me try to explain the same thing from a different direction in a more intuitive way that a broader audience might be able to appreciate. The usual way the effect of tiered-rates is studied is to find two houses in the same neighborhood that cross a tariff zone boundary (often literally on the two sides of the same street). Thus climate, income, building codes, demographics etc can be easily controlled. To differentiate between average rate and marginal rate elasticity responses you ideally want one of the pair to have a “mountain” style rate, with increasing tiers to a peak followed by decreasing tiers, compared to a standard “staircase” on the other side of the pair. Thus the “mountain” tier house could have a significantly higher bill for the same amount but experience significantly lower & declining marginal rates the more they use once they get over the peak. Thus after a rate change you would see the “mountain” paradoxically even further increase the total monthly bill to take advantage of the cheap marginal electricity on the other side. (That is, if it is true that usage is elastic to tiered rates)

        To my knowledge that “mountain” tier doesn’t really exist in California to be studied. The studies I have seen do not adequately separate average from marginal because the rate zones had significantly different averages.

  5. The prior comments highlight an important issue that seems to get short shrift, which is the problem of conflicting policy goals. Electric rates can be designed to redistribute income or promote energy efficiency and (more importantly) demand management, but I don’t think there’s any rational way to design electric rates that promote demand management and redistribute income efficiently. The most efficient way to promote energy efficiency and demand management is via rate design. The most efficient way to redistribute income is via direct payments that target low income consumers rather than low usage consumers. Politicians prefer to use electric rates because they can more easily hide what they’re doing, but it is terribly inefficient.

    Don;t forget that purportedly low income pot growers have taken advantage of tiered rates and the CARE program so that electric consumers are effectively subsidizing marijuana production. I’m not sure that’s what the politicians had in mind, but it is an unintended consequence.

    • Totally agree (even with the subsidized pot “unintended consequence”).

      NB: These same issues pop up with water. Better to separate cost recovery and conservation messages from income inequality…

    • First, the realistic answer is that the Legislature has used and will continue to use energy utility bills as a means to redistribute income, in this case through the CARE program. The tiered rate effect has become a second hidden program that is less sacrosanct so its up for debate.

      That said, there are better methods, such as SMUD’s bill rebate (a $20 credit to low income users vs a $6 fixed charge for other users.) This doesn’t have the same distortionary effect on consumption.

  6. Thank you for an interesting discussion. The premise to evaluate the re-distributive effects of tiered pricing seems to presume something about the merit of the goal underlying the third argument. The discussion runs directly past that question and goes directly to the accuracy of the argument. Certainly one could argue broadly on the merits of distributive economic policy. But at least bounding this blog a bit, that question is too far afield. Nonetheless, it seems that there are two specific questions missing from this treatment.

    First, is the utility bill an appropriate, (measured in terms of equity, efficiency, etc.) means to implement re-distributive economic policy? Simply asking this question will likely reveal the position of the inquisitor. For those who would answer no, it may well appear that the question has not been sufficiently evaluated within the context of policy decisions.

    Second, presuming that the answer to the first question is yes, then would this approach not be most appropriately (again, measured in terms of equity, efficiency, etc.) applied to all retail energy service companies? IOUs, POUs, ESCOs?

  7. Another reason for lower consumption is the proximity to the coast. Beach community residences typically do not have or use air conditioners, which is a large part of typical bills in California. So, who do we expect lives at the beach, lower income or higher income electricity users?

    • I had a similar thought, and yes, higher income residences are closer to the ocean in milder climates. Some of this is accounted for in the differences in baseline allowances, but not entirely. Severin’s analysis could be focused down by segmenting census data by climate zones and assessing the impacts at that level.

  8. everyone should pay the same rate from first kWh [low-income get CARE etc discounts below the top line]. the rate should be time varied based on cost of generation. fixed costs should be part of a ‘line-connection charge’, and should be set based on max load].
    The rate answer is ToU coupled with automation.
    A large portion of electric users now have smart meters. The utility can transfer projected rates to the users every 1-5-10-15-30 minutes in advance. The user can have controllers that control energy using equipment – air conditioners, ovens, lights, etc. So when the system sees the rate going up perhaps the air conditioners can be dialed ‘down’ [ie to higher temp settings]. I could do all my laundry and baking at night when the rate could [conceivably] be negative. OR I could even time-shift by storing electricity at low-rate periods. People all over South Asia do this to deal with the load shedding their utilities force on consumers.

    Life is simple. There is a technology solution for everything.

    • We currently have ToU pricing thanks to a plug in hybrid car. The cheap power is nights and weekends. It turns out to be quite easy to adjust (with minimal technology) by putting the car plug on a timer, doing laundry on weekends, and setting the programmable thermostat to run the A/C harder when power is cheap. In this case the thermal mass of the house is the storage medium that allows time shifting. In our monthly bill I see that this strategy is almost completely effective. Very little power is consumed at the peak rate.

      I am wondering what the effect of this change will be on power demand. When coupled with the “Duck” curve ( increased daytime supply due to solar ) it seems plausible that the cheap power may not always be at night.

      • Azmat used the ToU acronym, but described RTP (real-time pricing) so it would correct as the supply mix changed.
        Both systems would be less progressive than the current pricing system

  9. It would be interesting to analyze how would ToU fit in this scheme of relative increase or decrease in electricity bills for different classes, i.e. whether a ToU system can be designed where every class has greater net welfare as compared to the proposed two-tier system. I understand though that ToU is hard to model as it involves predicting consumer behavior in aggregate.

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