Abstract
This article examines the impact of market restructuring on retail prices, using the restructuring of the electricity industry as a case study. Utilizing synthetic control as an estimation strategy, this paper finds retail competition reduced retail prices across all sectors by an average of $1.5/MWh, relative to their counterfactual outcome. On average, prices fell for residential and commercial users and rose for industrial users. The price differential is consistent with the enactment of price ceilings and increased pass-through of changes in the price of natural gas.
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Source: EIA (2021)
Source: EIA (2021)
Source: EIA (2021) and Author’s calculations
Source: Authors’ calculations
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Notes
For a further review of the literature, see Bushnell et al (2017).
Rose et al. (2023) employs a synthetic control strategy to answer this question but with different explanatory factors, a different outcome variable and the inclusion of the Northeast. The pre-treatment match and similarity in explanatory factor values pre-restructuring of this paper provide evidence that this paper has generated more accurate estimates of the counterfactual.
For example, a coal-intensive state would create a poor counterfactual for a gas-intensive one.
Vermont is the only regulated Northeast state and its capacity mix and pre-trend price do not match other states.
See Abadie (2021) for a review of the synthetic control method and literature.
Full restructuring here is defined as the introduction of retail competition.
For example, Act 286 in Michigan caps electric choice participation at 10%.
While electricity is traded across state borders, transmission constraints makes plant location relevant.
For a technical understanding of the synthetic control methodology, see Abadie et al. (2010).
For internal consistency, multiple states were excluded due to partial restructuring, remoteness, and unique traits. This selection is covered in more detail later in this section.
Endogeneity concerns, typically the highest hurdle in empirical papers, are reduced by creating a synthetic state that is similar in the most important determinants of electricity prices except market regulation.
Factors such as construction costs (CC), labor differences (w), and plant age do not vary widely enough between states to significantly impact prices, relative to the generation mix.
Demand variance can be estimated at the balancing authority level, but these do not match state boundaries.
Heating degree days are not used due to limited use of electricity for heating in the Northeast and Midwest.
For example, Michigan’s reliance on coal impacts its electricity price, not its oil sector, which is excluded.
Taking the change from 1990 is similar to papers selecting comparison regions with similar pre-treatment slopes.
Generation is chosen instead of capacity as it more closely approximates what states use.
Oregon only opened its commercial and industrial sectors to competition, so its residential sector is excluded.
Section 5.5 explains further why Iowa and Wisconsin are outliers as donor states.
See Appendix D for more details on the Northeast common support problem.
See Appendix B for the state factors and Appendix C for which states were used to construct the counterfactual.
For further details, see Appendix A.
The large utilities Connecticut Light & Power and Baltimore Gas & Electric filed for rate increases of more than 70% once the freezes were lifted (Kwoka 2008).
This is especially true once you eliminate the period from 1998 to 2002, when many restructured states cut and capped their prices.
For example, it is unlikely that generators in fully-restructured states were less cost effective than those in regulated states from 2003 to 2008 and then more cost effective after.
The primary funding mechanism for stranded assets were either bonds or special fixed charges, such as the wire charge in New Jersey (FERC 2006).
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Appendices
Appendix A: State restructuring and price freeze information
When states began the process of restructuring their electricity markets, there was concern that consumers may have difficulty navigating the transition from one regional retailer to many. To ease the transition, the majority of state electricity regulatory commissions froze electricity prices for a varying number of years and, in many cases, reduced them (Kwoka, 2008). These freezes largely applied to the residential sector, although they were extended in some states to the other sectors (see Table
10 for details on each state in this study). This had the potential to create a financial problem for retailers if the cost of production rose during the price freeze period, as retailers would be subject to variable wholesale prices without the ability to pass on those costs to consumers. However, as Kwoka (2008) notes, it was expected that prices would fall, with the price freezes providing some funding for utilities’ stranded assets.Footnote 27
Due to an increase in natural gas prices and a failure of restructuring to reduce the cost of electricity provision, a gap formed between the rising cost of electricity provision and consumer prices that had been cut and frozen. This occurred first in California in 2001, as a surge in the cost of electricity provision left the three large utilities in California (Pacific Gas & Electric, San Diego Gas & Electric and Southern California Edison) either bankrupt or near bankruptcy. By 2006, all price freezes had been removed and a number of major electricity providers and retailers were in dire straits.Footnote 28 To address the imbalance, utilities were allowed by state commissions to book “deferred balances,” which could then be charged to ratepayers after the price freeze ended. The combination of rising natural gas prices, deferred balances, and prices that had been artificially held below market value for years led to a substantial rise in rates across states for several years.
1.1 Donor states
Alabama, Arkansas, Colorado, Florida, Georgia, Idaho, Indiana, Kansas, Kentucky, Louisiana, Minnesota, Mississippi, Missouri, Montana, Nebraska, Nevada, New Mexico, North Carolina, North Dakota, Oklahoma, South Carolina, South Dakota, Tennessee, Utah, Washington, West Virginia, Wyoming.
1.2 Excluded states
Alaska, Arizona, California, Connecticut, D.C., Hawaii, Iowa, Maine, Massachusetts, New Hampshire, New York, Rhode Island, Vermont, Virginia, Wisconsin.
Appendix B: Factors used in state counterfactual electricity price estimation
The factors in each state’s electricity price differ based on the state. For example, oil use is more important in Delaware than it is in Ohio, where it is zero. Matching on oil use in Ohio creates an additional constraint without adding any explanatory power. Therefore, only the two most important fuel mix factors that impact a particular state’s electricity price change since 1990 and CDD are included and shown in Table
11 below.
Appendix C: Synthetic donor selection
Synthetic control selects which donor states to create the synthetic restructured state with based on two criteria: pre-treatment factor values and pre-treatment trend in electricity prices, differenced from 1990. For example, the synthetic Illinois is constructed from 77% Missouri and 23% Arkansas because, when those are combined together, they mimic Illinois’ pre-treatment price trend and the value of the three factors Illinois is matched on from Table 11 (% gas generation, % baseload generation and CDD). States were excluded as donors due to unique factors in their electricity markets, partial restructuring and their location in the Northeast (described further in Appendix D).
Donor state | DE | IL | MD | MI | NJ | OH | OR | PA | TX |
|---|---|---|---|---|---|---|---|---|---|
Alabama | 0.004 | ||||||||
Arkansas | 0.23 | 0.034 | 0.002 | ||||||
Colorado | 0.056 | 0.014 | |||||||
Florida | 0.496 | 0.323 | 0.003 | ||||||
Georgia | 0.005 | ||||||||
Idaho | 0.002 | ||||||||
Indiana | 0.595 | 0.06 | 0.019 | ||||||
Kansas | 0.018 | ||||||||
Kentucky | 0.17 | 0.012 | |||||||
Louisiana | 0.4 | ||||||||
Minnesota | 0.008 | ||||||||
Mississippi | 0.003 | 0.004 | |||||||
Missouri | 0.77 | 0.03 | 0.255 | ||||||
Montana | 0.394 | 0.002 | |||||||
Nebraska | 0.014 | ||||||||
Nevada | 0.6 | ||||||||
New Mexico | 0.368 | 0.047 | |||||||
North Carolina | 0.006 | ||||||||
North Dakota | 0.03 | 0.152 | |||||||
Oklahoma | 0.183 | 0.939 | 0.004 | ||||||
South Carolina | 0.006 | ||||||||
South Dakota | 0.002 | ||||||||
Tennessee | 0.005 | ||||||||
Utah | 0.194 | ||||||||
Washington | 0.322 | 0.005 | 0.002 | ||||||
West Virginia | 0.107 | 0.45 | 0.009 | ||||||
Wyoming | 0.176 | 0.26 | 0.212 |
Appendix D: The Northeast
A key insight of this paper is that the inclusion of the six Northeastern states that restructured (New York, Connecticut, Rhode Island, Massachusetts, New Hampshire and Maine) in the estimation creates a common support problem. Without synthetic control, it is not clearly visible that these states are a problem. However, once an attempt is made to find synthetic matches for these states, it becomes clear this is an impossible task for two reasons. First, this region experienced an increase in electricity prices in the early 1990s that other regions didn’t. Therefore, as shown in the pre-treatment period in Fig.
Synthetic control results for northeastern states. Notes: running variable is number of years since restructuring. Treated is the sales-weighted average total electricity price among 6 Northeaster treated states. Synthetic is the same for the 6 synthetic states
13, there is no synthetic match for the pre-treatment trend (Sect. 2 of this paper describes why Vermont is not a feasible candidate).
Second, the region’s generation mix, particularly its reliance on oil, throughout much of this period is unique (see Table 3). Other than Florida, there is no other state in the donor group that uses oil to generate electricity at any significant level during this time period, and Florida does not match these states on any other factors. This results in poor matching of treatment factors (Table 3), which makes it unlikely that the difference in the treated and synthetic outcomes shown in Fig. 13 represents a valid counterfactual result. The combination of these two challenges presented by the Northeast suggests the region should be excluded from the estimation.
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Hill, A. Price freezes and gas pass-through: an estimation of the price impact of electricity market restructuring. J Regul Econ 63, 87–116 (2023). https://doi.org/10.1007/s11149-023-09459-w
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DOI: https://doi.org/10.1007/s11149-023-09459-w