One of the best means by which to predict future conflict is to look for two parties moving in fundamentally opposite directions. There exists such a situation in many areas of the United States when it comes to tax assessment of power generating real property. Indeed, a perfect storm might be brewing.
At a time when many states and municipalities are facing budget deficits of historic proportions, many power generators are struggling against declining demand, the lowest electricity prices in many years, and looming carbon legislation. As a result, tax authorities might be seeking to raise property tax receipts at the exact same time that many generators are looking to lower their assessments.
Conflict appears to be on the horizon, but where will it emerge? An examination of state budgets, as well as the expected changes in generator gross margins, reveals how tax collectors and taxpayers are most likely to respond.
In March 2006, just four years ago, nearly every state reported good or stable fiscal conditions to the National Conference of State Legislators (NCSL).1 These reports quickly were reversed under the current recession. Today, nearly every state faces a budget gap, and both the breadths and sizes of these gaps are unprecedented (see Figure 1). According to the July 2009 NCSL update, state lawmakers closed a cumulative budget gap of approximately $110 billion for the 2009 fiscal year.2
Balancing budgets will become tougher in the coming years, as fiscal conditions likely will worsen before they improve. According to the NCSL, states are expected to face budget gaps of over $140 billion for the 2010 fiscal year—an estimate that has been revised progressively higher over the last few months. Budget analyses suggest that the cumulative gap through 2012 will be significantly larger than occurred in the fiscal crisis between 2001 and 2004, when states largely relied on spending cuts, rainy day funds, and tax increases to close gaps.
Preliminary steps taken to bridge current budget gaps have focused mostly on reduced spending, though rainy day funds also are utilized where available. Many have relied on the American Recovery and Reinvestment Act of 2009. But what happens when stimulus funds are fully disbursed? Using recent history as a guide, if fiscal conditions remain severe, lawmakers might have limited options beyond increasing tax revenues.
Income and sales tax rates are the main revenue dials at the state level, but property tax rates are the primary tool for counties, municipalities, and school boards. Electric generators are some of the largest single taxpayers in certain localities and their property tax bills might grow higher in the next few years. But generators don’t lie entirely at the mercy of the taxing authority. What generators ultimately pay in property taxes also is governed by their assessments. When conditions dictate, generators can appeal assessments with the goal of lowering property tax bills.
Property assessments typically are based on fair market value determinations using generally accepted appraisal methodologies. Most nationally and internationally recognized appraisal standards recognize three basic approaches to determining fair market value: the reproduction or replacement cost approach, the sales comparison approach, and the income capitalization approach.
While the assessment standards for each authority are governed by property tax laws, the overwhelming majority of states establish clear guidelines indicating that a specific approach or combination of approaches may be used to determine an asset’s fair market value. Among the 50 states, 43 explicitly allow consideration of the income approach when performing fair market value determinations for property tax assessments.3 Three states, Arkansas, Wyoming and Indiana, have broadly-defined appraisal guidelines that lack an explicit reference to specific methodologies. Only Maine and Nevada appear to limit fair market value methodologies to the cost approach (see Figure 2).
For income-producing assets such as electric generators, value is derived from the asset’s future cash flows. By definition, the income approach requires a determination of future cash flows that, for electric generators, draws from market projections of fuel prices, market capacity profiles, generation queues, expected demand trends, market structure, anticipated technological advancements, and expected regulatory changes. In short, the income approach allows an appraiser to extract a present value for an asset based on its participation in tomorrow’s power market. Consequently, the income capitalization approach is the dominant approach recognized for valuing electric generators, and power market expectations are key inputs.
To quantify changes in market expectations over time, it’s important to use projections based on a consistent modeling framework, such as the projections and analyses generated by the National Energy Modeling System (NEMS). NEMS is a large-scale energy-economic equilibrium model that computes equilibrium fuel prices and quantities for the entire U.S. energy sector. The U.S. Department of Energy’s Energy Information Administration (EIA) publishes the NEMS forecasts every year as a part of its Annual Energy Outlook (AEO).
Having established a common basis, analysis focuses on the change in market projections from 2006 (based on the 2006 Annual Energy Outlook), presuming property assessments were determined as recently as four years ago.4 Expectations of the future power market have changed considerably since then, in that generators now are expected to operate in a carbon-constrained economy (as provided by a NEMS projection incorporating the American Clean Energy and Security Act).5 Based on performance data for each generator within a state, as provided in EPA’s Emissions & Generation Resource Integrated Database (eGrid2007), and the long-term price projections for fuel, energy, and carbon dioxide allowances, as provided in current and past EIA projections, the expected change in gross margins can be estimated for each generator.6 Specifically, gross margins for each generator in the eGrid2007 data file can be determined as the difference between energy prices and the sum of variable operations and maintenance costs, fuel costs, and carbon dioxide costs. The percentage change of gross margin for each generator is calculated using past (i.e., 2006 AEO) and recent projections (i.e., the “Basic” scenario in EIA’s analysis of the American Clean Energy and Security Act of 2009). The long-term average prices for energy, fuel, and carbon dioxide reflect the average price through 2030 in real 2007 dollars. Long-term average energy prices are calculated from the average electricity price in the “Total Energy and Supply Disposition Summary” table of both projections. Long-term fuel costs for each generator are calculated as the product of the unit’s heat rate as reported by eGrid2007 and the corresponding fuel price from the “Energy Prices by Sector and Source” table of both projections. Variable operating and maintenance costs for general classes of capacity can be derived from the operating characteristics of capacity as reported in the AEO. Carbon dioxide costs are calculated as the product of each generator’s carbon dioxide emission rate and the long-term average “Allowance Price in the Greenhouse Gas Compliance Results” table in the “Basic” scenario of EIA’s analysis of the American Clean Energy and Security Act. After estimating the change in gross margin for each generator, the capacity-weighted average by state is calculated based on each generator’s capacity as provided by eGrid2007.
More generally, however, estimates of gross-margin trends reveal the relative size and directional change of an assessment, should a generator trigger the appeal process today (see Figure 3).
Any effective policy that penalizes carbon dioxide emissions will transfer value from high-emission generation, such as coal and oil-fired capacity, to zero-emission generation, such as wind, solar, hydroelectric, and nuclear projects. Income streams and asset values for high-emission generators will fall as unrecoverable costs to operate and emit carbon dioxide increase.7 On the other hand, zero-emission capacity has no obligation to purchase carbon dioxide allowances and will benefit from the expected increase in energy prices.
Under current proposals for federal carbon regulations, states dominated by coal and oil-fired capacity are expected to experience larger negative changes to gross margins, while states with substantial shares of zero-emission capacity likely will see larger positive changes. Due to the aggregated analysis, some individual generators might experience changes that differ from the state average. A nuclear facility in New York, for example, likely will see higher gross margins, even though the state’s average capacity is projected to face lower gross margins.
States that are fairly diversified between high and zero-emission generation likely will face minimal changes on an aggregated basis, since the positive and negative gross margin impacts of these individual generators offset one another. Montana is such a state, with almost a 50-50 split of coal-fired and renewable capacity. Other states with small expected changes in gross margin are those that are dominated by natural gas-fired capacity. Unlike coal and oil-fired units, natural gas-fired units will recover a larger amount of carbon dioxide costs through the projected increase in energy prices, thereby limiting the impact on gross margins. Texas, for example, also falls into this category with its heavy reliance on natural gas-fired combined cycle and combustion turbine units.
By combining the above analyses, it’s possible to identify states where property tax disputes are more likely to materialize based on the anticipated responses by taxpayers and tax collectors. Taxing authorities and generators can be separated into three categories reflecting their relative tendencies toward conflict.8 Although these disputes ultimately will be governed by specific generators and local fiscal conditions, their aggregation to a state level allows the identification of those regions where generators and taxing authorities are most likely heading toward conflict (see Figure 4).
States with a low tendency for conflict likely will raise taxes in an effort to balance future budgets. However, the average generator within these states won’t face steep declines in value and some might even see positive changes, so plant owners might be relatively more accepting of increased tax bills and in less of a position to appeal assessments. With tax assessment activity held at the status quo, these states would have the least tendency for conflict.
The higher tendency for conflict in the medium category reflects the greater likelihood (or incentive) to appeal tax assessments. The average generator in these states can expect significantly lower gross margins and asset values. However, these states also face relatively less severe fiscal conditions (i.e., budget gaps are less than 5 percent) and, therefore, would be more willing than states with larger deficits to reach an agreement and settle property tax disputes without protracted negotiation or litigation.
States with the highest tendency for conflict reflect the perfect storm of tax assessment disputes—falling generator values and severe budget deficits. The average generator in these states can expect steep declines—from expectations of several years ago—in gross margins, which would translate to lower asset values and a spike in appeals to lower assessments. Already under severe fiscal stress, taxing authorities in these states likely will respond more aggressively to requests for reductions—and therefore conditions in these states lead to relatively more conflict.
So where does all of this lead? Conflict, after all, is one of the inevitabilities of the business world. Obtaining a successful outcome in an endeavor marked by conflict requires preparation. Prevailing means convincing the other side, whether through persuasive force in a negotiation or through a preponderance of the evidence in litigation. In either case, tax assessors and taxpayers in the states identified as having a high tendency for conflict might want to start marshalling the forces now. For many power plants, the economic reality is clear, and the parties who are best able to articulate that reality will in many cases control the outcome.
1. State Budget Update: March 2006, National Conference of State Legislators.
2. State Budget Update: July 2009, National Conference of State Legislators.
3. Alaska and Hawaii are excluded from the analysis due to their unique geographical characteristics.
4. 2006 Annual Energy Outlook, Energy Information Administration, U.S. Department of Energy, DOE/EIA-0383(2007).
5. Energy Market and Economic Impacts of H.R. 2454, the American Clean Energy and Security Act of 2009, Energy Information Administration, U.S. Department of Energy, SR-OIAF/2009-05. The NEMS modeling framework used in this analysis is the same as that used in the Annual Energy Outlook. Both analyses, therefore, have a common basis that can be used to evaluate changes in future expectations.
6. eGRID2007 Version 1.1, U.S. Environmental Protection Agency.
7. Wellington, Fred and Michael Scholand, “Carbon in Electricity Markets,” Public Utilities Fortnightly, August 2009.
8. The analysis wasn’t applied to a small number of states (those coded as “N/A” in Figure 4) because these states either didn’t report budget conditions to the NCSL or explicitly excluded consideration of the income approach in property tax assessments. In these cases, tendencies toward conflict would need to be examined by other means.