Synopsis

This study, conducted with Standard & Poors Rating Services, examines how climate change policy drivers could be incorporated into the evaluation of credit quality. It analyzes two types of federal climate policy scenarios – (1) a market-based GHG emissions reduction policy as approximated by the American Power Act (APA), and (2) Environmental Protection Agency (EPA) regulation of greenhouse gas emissions (GHG) – in the context of 13 energy-intensive chemicals subsectors.

Key Findings

Credit impact under cap-and-trade scenarios

If passed, the American Power Act (APA) would require companies to hold permits to emit GHGs for all emissions from facilities emitting more than 25,000 tons of carbon dioxide (CO2) or equivalent greenhouse gas. Most large U.S. chemical facilities would meet this threshold.(iv) By limiting the supply of these permits—known as emissions allowances—in the market, the government would be able to cap economy-wide emissions. The APA also includes provisions that would rebate free emissions allowances to facilities in select subsectors. Eligibility for these free allowance rebates is at the subsector level, and depends on a subsector’s energy intensity and trade exposure.(v) WRI has calculated that the APA provides enough free allowances to energy intensive, trade exposed manufacturing industries that any eligible subsector—as a whole—will receive enough free permits to cover all emissions in that subsector for 2016 and several years beyond (see WRI’s accompanying technical document). However, the risk remains that the supply of free permits relative to demand may decline over time and at a faster rate than originally envisaged.

Predicting how the APA would affect the economy is challenging. For their analysis, Standard & Poor’s and WRI have each relied on the U.S. Government’s Energy Information Administration’s (EIA) projections of APA’s impact on GDP, energy prices, and GHG emissions permit prices.(vi) As with any forecasting, these projections indicate what could happen, rather than what would happen.

Subsector-level evaluation

Standard & Poor’s and WRI based their respective analyses on EIA projections using three GHG permit price scenarios—low, medium, and high—under the APA. Based on these projections, most of the chemicals subsectors we examined would only see modest energy and compliance effects in the first year of assumed compliance (2016).

The EIA projects only modest changes relative to no policy for most natural gas and oil-derived energy inputs in 2016 under the APA. Only well-head natural gas prices increase significantly—from 4% to 25% higher relative to no policy in the three scenarios Standard & Poor’s and WRI considered— while petroleum and coal prices decrease modestly—from 1% to 9% lower relative to no policy.

These projections are premised on the assumption that users across the economy will likely switch away from emissions-intensive fuel/feedstock sources (i.e., petroleum and coal) and demand lower emissions fuel/feedstock sources (including natural gas) because of the price signal cap-and-trade policy creates. APA provisions require utilities to pass any free allowances they receive to industrial consumers, including chemicals manufacturers, in the form of lower electricity prices, which mutes electricity price changes.

WRI estimates that facilities in 10 of the 13 chemicals subsectors (as a whole) would be eligible to receive free allowance rebates under the APA. For these eligible subsectors, WRI expects no net compliance obligations—at the subsector level—in 2016 and through as far as 2033 (see WRI’s accompanying technical document). WRI expects only facilities in three of the 13 subsectors examined— the industrial gas, ethyl alcohol, and phosphatic fertilizer— would not be eligible to receive free allowances since these subsectors don’t meet the legislation’s threshold for trade exposure and or energy-intensity.

WRI compared the 13 GHG-intensive subsectors’ relative policy-related energy and compliance costs (based on EIA projections in 2016) against Standard & Poor’s ranking of relative competitive risks for each subsector (see Figure 1). WRI assumed that the ratio of these subsectors’ emissions and their energy-related fuel/feedstock purchases to their size, as measured by value of shipments, is the same in 2016 as in 2006 (the most recent data available for emissions estimates). This comparison appears to indicate the following:

  • While large energy-intensive commodity chemical subsectors (like the petrochemical, plastic material and resin, and other basic organic chemical subsectors) may have limited ability to pass along costs depending on market conditions, WRI doesn’t expect these subsectors to face significant compliance costs because of their eligibility for free allowances. At the same time, these subsectors also depend heavily on natural gas-derived feedstocks so they could face higher production costs. Standard & Poor’s expects higher production costs could make some of these subsectors less competitive in their markets, lower their export opportunities, and ultimately weaken their credit metrics.

  • The nitrogenous fertilizer subsector is likely to face moderate energy-related risks because of their natural gas purchases.

  • The industrial gas subsector may have the greatest compliance costs relative to its size, but it should also be in the best competitive position to pass along these costs to customers.

Company-level evaluation

Under the APA, companies in eligible subsectors receive free allowances based on their market share (by output) in a subsector, multiplied by the whole subsectors’ GHG emissions. As a result, companies with a lower ratio of GHG emissions to output than those of their peers would receive more free allowances than required to cover their facilities’ compliance requirements. These companies can sell their extra free allowances for cash or bank them for future use. Companies with a higher ratio of GHG emissions to output than their peers still receive free allowances, but these free allowances would only offset a portion of their compliance requirements and may put them at a cost disadvantage.

WRI and Standard & Poor’s expect that the credit impact at a company-level would likely vary within each subsector based on the following:

  • Current and projected emissions and the ability to reduce emissions. For companies eligible to receive free allowances, emissions data should be compared with the subsector average, since net compliance costs would depend on emissions intensity relative to the subsector average.

  • Current and projected fuel and feedstock mix. Dependence on GHG-intensive fuels like petroleum products and coal (and to a lesser extent, natural gas) increase compliance costs because GHG emissions are released upon combustion. Natural gas dependence, whether through direct purchases or natural gas-derived feedstocks, may result in higher energy purchase costs.

  • Competitive position, both domestic and international, including the ability to pass along costs.

Standard & Poor’s examined the potential credit impact on two hypothetical companies in energyintensive subsectors in 2016, using EIA projections of the APA and WRI’s analysis of free allowances:

  • Company A is a large carbon black producer with lower GHG emissions than most of its peers. WRI estimates that the value of free allowances Company A would receive under the APA would be greater than the costs of its compliance obligations, resulting in net revenue of $0.01 to $0.03 per dollar of U.S. sales in the first year of regulation—a negligible positive impact. Standard & Poor’s also expects the implications of raw material costs to be manageable for Company A because it focuses its energy purchases on refined crude oil products, which are expected to decline in cost relative to the no-policy case. Even in the downside case, where its energy outlays increase more than what the EIA projects, energy costs appear manageable because of the company’s geographic diversity and the expectation that Company A would retain sufficient pricing power due to the valueadded- nature of its products and favorable industry structure. Thus, under the EIA projections, Standard & Poor’s would not expect Company A’s profitability and leverage metrics to deteriorate.

  • Company B, as a large industrial gas producer, would not be eligible to receive compliance-related subsidies. As a result, WRI estimates Company B would face $0.06 to $0.17 in compliance costs per dollar of U.S. sales. The substantial costs of compliance could raise some uncertainty on future capital spending, and the EIA’s projection for slightly lower economic growth could affect demand growth. But we expect Company B to be able to pass through some costs to downstream customers as a result of the strength of its business model and lack of lower-cost substitutes. Here, Standard & Poor’s expects Company B’s profitability and leverage metrics to deteriorate modestly under the EIA projections.

The subsectors that are most likely to face EPA regulation

WRI believes that 2016 is likely the earliest year that future EPA regulation would cover GHGs from existing chemical facilities. The form of regulation is unclear. Previously, the EPA has used both market-based and command-and-control regulation to limit pollutants.

WRI believes that absolute emissions and emissions reduction potential are among the factors that the EPA will consider when regulating GHG emissions; other key criteria include cost feasibility and the remaining useful life of facilities (see Figure 2). Nitric acid and adipic acid production—part of the nitrogenous fertilizer and all other basic organic subsectors, and an input into fiber manufacturing—are also likely to come under regulation as a significant source of nitrous oxide (N2O) emissions (a potent GHG). (Because of data limitations, Figure 2 does not reflect cost feasibility, the remaining useful life of facilities, and nitric acid and adipic acid production.)

The credit differences between policy scenarios

Assuming the EPA does not use market-based mechanisms, WRI and Standard & Poor’s believe the key credit-related differences between the cap-and-trade and EPA regulatory scenarios include:

  • Cash flow flexibility. Cap-and-trade legislation provides companies with greater flexibility to choose between up-front capital expenditure and the purchase of emissions allowances, allowing companies to more easily manage cash flows in a given year.

  • Compliance-related revenue. Under the APA, companies that are both eligible for rebates and emit less GHGs than their peers (per unit of output) would presumptively receive more free allowances than required, and could bank or sell these allowances for cash. A non-market-based EPA regulatory approach would not provide a similar opportunity to gain compliance-related revenue.

  • Management strategy. Implementing an effective management strategy to comply with climate policy becomes more important in a cap-and-trade scenario. Benchmarking emissions reductions against peers and participating in GHG permit trading (“carbon”) markets will likely be a complex undertaking for any company, requiring input and coordination from all business segments. In contrast, meeting EPA regulatory standards is likely to be easier to manage within existing company operations.

As climate policy evolves, key policy variables to watch for include:

  • Stringency. How aggressively do policies target greenhouse gas emissions reductions?

  • Coverage. Which subsectors in the chemicals value chain do the regulations cover? And how and when do those regulations apply?

  • Transition provisions. What provisions are available to ease the economy and companies into reducing GHG emissions and minimize competitive pressures (for example, free allowances)?

Executive Summary

In the first part of the analysis, WRI describes scenarios under two types of potential federal climate policy—an economy-wide market-based system (specifically, cap-and-trade legislation) and Environmental Protection Agency (EPA) regulation of GHGs. In the second part, WRI and, in certain discrete issues, Standard & Poor’s look at how these policy scenarios could influence credit risk factors in 13 greenhouse gas-intensive chemicals subsectors. In the final, third part, Standard & Poor’s applies these findings.