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annex f
» Methodology for Analyzing Cap-and-Trade and Other Policies and Measures Using the REMI Model I. Introduction The U.S. Congress and the Obama Administration are actively working on the design of legislation to address the problem of climate change. While the proposed Senate and House bills differ in their particulars, they all basically establish a target reduction for greenhouse gases (GHGs) and specify policies and measures to achieve these goals over the course of a planning horizon. A key policy instrument in these bills is “cap and trade,” or emissions allowance trading. However, because many emission sources are not responsive to price signals, other policy and measures, most notably direct regulation, are included in the policy mix. Actions by emitters to reduce GHGs can achieve direct cost savings, as in the case of energy efficiency improvements, or can be cost-incurring, as in the case of shifting from coal-fired electricity generation to some more expensive types of renewable sources in the short run. However, any direct actions ripple through the economy, generating what are often referred to as indirect, multiplier, general equilibrium, or macroeconomic impacts. The last category is the broadest and takes into account: impacts from stimuli to successive rounds of suppliers and customers through a combination of material input needs and price changes in employment and income and successive rounds of re-spending effects, changes in investment, and changes in government revenues and expenditures. It is impossible to trace all of these linkages through the economy by direct observation, so instead various types of economic models are used. The purpose of this study is to estimate the macroeconomic impacts of the major features of recent climate change legislation in the form of a U.S. Senate bill sponsored by Senators Kerry and Lieberman and its combination with sector-based policies and measures. The impacts are expressed in terms of major macroeconomic indicators – output, employment, and income – for the economy as a whole and for each of 169 sectors of the economy in the year 2020. We identify the major features of the Kerry-Lieberman (K-L) bill relating to the emission cap, sectors covered by cap-and-trade programs and other major policy instruments, the allocation of allowances, the potential to use offsets from domestic and international sources, and the government spending (“recycling”) of allowance auction revenue. These design parameters, along with an extensive database built from stakeholder deliberations in nearly 20 states, facilitated by the Center for Climate Strategies (CCS), are fed into a macroeconomic model known as the Regional Economic Models, Inc., Policy Insight Plus (REMI PI+) to generate the macroeconomic impact estimates.
II. Overview of Policy Instruments for GHG Reduction
A. Cap and Trade Cap-and-trade programs limit emissions by placing a “cap” on the emissions of pollutants that can be released from regulated, or “covered,” sources within a specified geographic area and interval of time. The cap is implemented by the issuance of permits (often freely granted or “grandfathered”), or “allowances,” for each ton of GHG emissions, which must be surrendered by each covered source in an amount equal to its emissions. Over time, the number of allowances issued can be decreased, thereby further reducing total emissions.
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Since the government regulates only the total emissions, how the reductions are achieved is left to each covered source. Creating a market in which allowances can be traded gives these allowances a financial value, which encourages the covered sources, individually and collectively, to implement the least-cost measures to achieve the capped emission reductions. Participants with costs of compliance lower than the market price of allowances will take on additional mitigation (“overcomply”) and sell their additional reductions to participants for whom compliance costs are higher than the allowance price. In an auctionbased system, sometimes referred to as “cap and fee,” all emitters must purchase allowances to meet the caps; those with lower costs of compliance will need to purchase fewer allowances at auction. It should be noted that the most cost-effective or highest-value (including co-benefits) approach for some sectors or sources may not be cap and trade; it may instead be technology-forcing or incentive policies that address specific market barriers (often referred to as ‘‘policies and measures’’ or ‘‘nonprice instruments’’). A cap-and-trade program will not necessarily remove market barriers or lead to the fastest or broadest adoption of new technologies and practices. For instance, split incentives exist between the suppliers and the consumers of energy or products. Suppliers may not be able to participate in the benefits of lower-carbon goods or services provided to consumers at a higher production cost and lack an incentive to shift production, even though the net benefit of such action to society is positive. For example, electric utilities may not see it in their self-interest to provide energy-efficient technology options that reduce sales to consumers, and automobile companies may not see it in their self-interest to supply low-emitting vehicles that save consumers energy costs. Cap and trade has a solid foundation in theory and practice. It is based on the property rights approach to eliminating externalities, the most vivid example of which is environmental pollution. The seminal work was done by Nobel laureate Ronald Coase (1960), and its refinement for application to pollution problems was done by many others (see, e.g., Tietenberg, 1985, 2007; Rose, 2009). The practice of cap and trade was given a major boost in the 1990 Clean Air Act Amendments and is the basis for the U.S. sulfur allowance trading program for electric utilities (Ellerman et al., 2000). With respect to GHG reduction, the major experience has been the European Union Trading System, which, after a rocky start due to some design flaws, is proving successful as well (Ellerman, 2008).
B. Carbon Tax A typical carbon tax operates on the same principle as cap and trade, that is, it imposes a cost on regulated entities for the purpose of affecting behavior and investments through a price signal. In this form, a carbon tax may generate revenue or it may be ‘‘revenue neutral’’ by allowing dollar-for-dollar reductions in other taxes and government fees.1 At first blush, the similarities between cap and trade and the carbon tax are striking; both represent a fee imposed on the release of GHGs designed to create an incentive for investments in reduced emissions and other beneficial behavioral changes. With cap and trade, the government sets a limit on the total emissions and the market, through allowance trading or auctions, establishes the price. With the carbon tax, the government sets the price, or tax rate, and the market response to that price determines the total resulting emissions. The carbon tax has some distinct advantages over cap and trade, notably its administrative simplicity for both the government and the regulated community and the wide familiarity with taxation in general. The wide familiarity and broad unpopularity of taxation, however, work against the carbon tax, at least in the political realm (although such taxes currently exist as surcharges on electricity bills, gasoline prices, etc.).2 Regulated industries often favor the carbon tax over cap and trade because of the stability of the cost imposed by the tax, as opposed to the cap-and-trade allowance price, whose cost fluctuates as set 1. Another approach to carbon taxation is as a conventional tax imposed for the purpose of generating government revenue. The discussion here considers only the ‘‘price signal’’ form of carbon tax. 2. British Columbia began administration of a nearly economy-wide carbon tax without having to add a single new position to its taxation ministry.
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by the market. Most environmentalists and some political leaders tend to favor cap and trade due to the programmatic integrity offered by the cap and the fear that emission reduction targets will not be met due to the uncertainties associated with predicting industry and public response to the carbon tax price signal. The inclusion of cost containment mechanisms may, however, reduce environmental certainty and reduce the relative advantage of cap and trade to other approaches in this regard. Another advantage of cap and trade is that it is often institutionally easier to adjust the cap than to adjust the tax rate.
C. Other Policies and Measures The traditional, and by far most common, approach to limiting emissions of pollutants is through sectorbased policies and measures, including direct regulation (or the “command-and-control” approach), as well as other incentive systems in which emissions are limited at the source by enactment of codes and standards, funding and technical assistance, various forms of limited permitting, and other incentives or disincentives. Source-based standards, for instance, are set by rule and enforced by some combination of permit-based source monitoring, reporting, and inspection or verification. These systems can, and often do, include substantial flexibility and tailoring to local circumstance. They also can be constructed to allow “extra credit” for surplus environmental achievement that can be transferred to or purchased by entities that need additional help in meeting standards. In fact, this type of performance-based system of credits for overachievement largely defined early concepts of cap and trade. Financial incentives or assistance are often provided in conjunction with regulation to reduce cost, compensate losses, and/or accelerate responses. Direct regulation can carry a heavy administrative burden and lack the flexibility to allow sources to seek and fund least-cost mitigation opportunities (depending on the design of the program). However, through rulemaking, permit writing, and review, this approach has the advantage of flagging specific concerns with the proposed limits. Barriers to compliance are often identified and addressed through the close interaction between the regulator and the regulated community. These barriers may take the form of contradictory government regulation, such as when an excessive occupational health and safety requirement for workplace air exchanges prevent an employer from effectively reducing heating or cooling loads. Barriers may also take the form of market failures where the entity responsible for the capital investment to improve efficiency cannot reap the benefits of lower energy use, for example, rental housing where the tenants are responsible for heat, electricity, or water heating. Direct regulation offers the greatest opportunity to identify and address such barriers. Absent resolution of these barriers, a cap-and-trade or carbon tax policy may not have access to the lowest-cost mitigation opportunities. A price signal without concurrent policies and measures to reduce barriers could be relatively more expensive.
III. Methodology for Analyzing Environmental Policy Instruments This section summarizes the methodology to simulate the macroeconomic impacts of various policies and measures to implement climate action plans at the national, regional, and state levels. In effect, our work in Florida, Pennsylvania, and Michigan and U.S. simulations considered the implementation of all recommended mitigation/sequestration options (Rose and Wei, 2009; Rose and Wei, 2010; Miller et al., 2010). Most real-world policies would likely involve a more targeted approach. One prime example would be applying a cap-and-trade policy to those options that respond to a price signal, and applying regulation to those that do not. Other policy instruments would include subsidies and information campaigns. For now, we model those two additional instruments in the same manner we model regulation (i.e., assuming the subsidy and information campaigns are successful without further examining the subtleties of individual emitter behavior or responsiveness). For several of the policy instrument designs, it is not necessary to perform any additional simulations to ascertain the macroeconomic impacts of any individual options. We can simply use our previous individual option results for those options brought forth by these policy instruments and then add
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them up for the “simple summation” of cases as noted below. Exceptions are the case where permits are auctioned, and expenditures on them must be added to the cost of production. The major new simulations will be for the new groupings of options (actually sub-groups) of the totality of options that we will need to run together for each of the cases to obtain our “simultaneous” totals. The calculation steps are as follows:
A. Divide Mitigation Options into Three Categories: »»Fully price-responsive options (no market failures). »»Options that are generally not price-responsive (due to market failures or other barriers) and that require regulation. »»Other options for which the price responsiveness might improve with subsidies, information campaigns, etc., without formal regulation. This group might be modeled differently in the future.
B. Perform the Following Reference Case Simulations: 1. Cap and trade in the U.S. only (applying either all mitigation options or a subset of options). a. Simulate a specific allowance price, such as the reserve price of the auction allowances implied by the K-L bill ($12/CO2e in 2013, and increases at the rate of inflation plus 3% for each year after), to determine what level of GHG reduction that will bring forth. Only those options whose mitigation cost per ton is at or below the allowance price would be included in the macro simulations. b. Simulate a GHG cap and infer a permit price by using our U.S. marginal cost curve. Again, all the options whose mitigation cost is at or below the allowance price would be included. 2. Cap-and-trade with the possibility of the U.S. purchasing allowances from other nations, or offsets at home or abroad. This would require an estimate of a supply curve or price for these allowances/ offsets. The mitigation options included in the response would only be those with a cost equal to or lower than the international allowance and offset prices. a. Simulate a specific allowance price , as in 1a. In this case, the amount of foreign allowances/ offsets would be the difference between the reduction brought about by the K-L bill reserve allowance price and a predetermined overall cap on emissions. The issue would be how to add the allowance purchase price to individual emitters (sectors). b. Simulate a GHG cap and infer a permit price by using both our U.S. marginal cost curve and the foreign offset price, as well as any constraints on the use of offsets specified in the K-L bill. The purchases of foreign allowances/offsets would be determined by this equilibrium. 3. Mixed case of cap-and-trade and regulation. a. In addition to the carbon cap-and-trade policy, several of the regulatory (mandated) options relating to given sectors covered by a given policy would automatically be included in our macro analysis regardless of their cost (we would treat subsidies and information campaigns as regulated options). The price-responsive options would be included in the same manner as 1a. Three Residential, Commercial, and Industrial (RCI) options are partially price-responsive: demand side management (DSM), high performance buildings, and combined heat and power (CHP). We decided that 30% of the emission reductions of these options is responsive to price signals, while 70% of the desired results can only be brought forth through regulation. In the simulations, we will split each of these options into two sub-options, price-responsive sub-option and non-price-responsive suboption. Technically, we will treat the two sub-options as two separate options in the computation. The GHG reductions will be split using the ratio of 30:70, with 30% emission reductions assigned to the price-responsive sub-option. The cost-effectiveness will be assumed to be same for the two sub-options (equal to the original cost-effectiveness of the option).
Impacts of Comprehensive Climate and Energy Policy Options on the U.S. Economy 131
b. This would be a combination of 1b and 3a (3b corresponds to 1b, in terms of setting the cap first. Otherwise the bifurcation is like 3a). 4. Mixed case with the possibility of buying international allowances or offsets. a. Simulating a specific allowance price, having the possibility of buying allowances overseas, and having some of the options required by regulation is quite complicated. We can examine this after performing other cases. b. Simulating a specific reduction target under this heading might be easy because a low public price like the K-L bill reserve allowance price would probably bring forth enough U.S. mitigation options to make up the gap to achieve the target. A higher permit price, such as an upper bound of $100 per ton, would be even more likely to do so.
C. Mimic Workings of Policy Instruments: 1. Free allocation equal to equilibrium sector emission requirements. The basic application of the REMI model to cap and trade without further adjustment beyond the stipulation of an allowance price directly, or indirectly via specification of a GHG emissions cap, essentially mimics the following institutional arrangement: free allocation of allowances, such that each covered sector gets exactly the number of allowances it needs for its remaining emissions, and the overall emissions cap is met. Each sector implements mitigation to avoid paying for allowances up to the point where its marginal cost of mitigation is less than or equal to the allowance price. This is a stylized case, often used in the economics literature, to derive the least-cost solution, as does a cap-and-trade system, but with no auction revenues actually generated (sectors mitigate to avoid having to buy allowances) and no allowance trading complications. Again, it is a reference point for other cases. In the absence of various distortions — pre-existing taxes, capital constraints, etc. — free allocation and auction scenarios should be identical except in the distributional effects. This can be considered a lower bound on the cost of compliance for emitters, and hence an upper bound on the macro impacts. 2. Auctioning all allowances. This requires application of the allowance price to all non-mitigated emissions. These auction payments are then added to the production cost of each emitting sector. The cost can be distributed across the entirety of the REMI 169 sectors or a subset of sectors on the basis of sector emission weights from the emission inventories. Because the sector designations of the emissions inventory are coarser than the REMI classification, sectoral components may have to be based on fossil fuel use (in CO2 equivalents) or on the basis of output weights. Note that one other step is needed: re-injection of the option revenues back into the economy. There are at least two possibilities: a. Add to government expenditures. b. Decrease taxes by an equivalent amount. Increasing government expenditures has some expansionary offsetting effect to the effect of the cost increase. It should be noted that many studies of the “double-dividend” have found the second option to be expansionary as well if it is used to offset the most price-distorting taxes, usually considered to be sales, excise, or wage taxes. Note that this category represents an upper bound on the cost of implementation and hence a lower bound on the macro impacts.
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3. Allowance trading following a grandfathering. This case is problematic in two regards. First, is the issue of the initial allocation of permits, i.e., which allocation criterion will be involved (often these criteria are related to equity, or justice, considerations). Alternatives include distributing permits in equal proportions of emissions to each sector, or favoring certain sectors because they are anticipated to be most adversely affected, or are weak sectors in the first place. The second is the actual trading. Sectors with marginal mitigation costs higher than the allowance price will buy allowances from sectors with marginal mitigation costs lower than the allowance price. This is an issue in the modeling due to the difficulty of connecting individual mitigation options with sectors, especially where several of the options pertain to each of the 169 sectors plus the Residential sector. Conceptually, marginal costs curves can be specified and trading can be simulated with a separate Rose-Wei non-linear programming allowance trading model. In this study, we will simulate allowance trading among sectors at a relatively aggregated sectoral scheme. Then the resulting sectoral purchase cost or sales revenue will be disaggregated and distributed among the REMI 169 sectors based on the sectoral emissions before feeding them into the REMI model. The cost of compliance for this arrangement would be similar to that of Case 1. In effect, the expenditures and revenues from allowance trading cancel each other out to a zero net cost. Compliance costs are still just the actual mitigation costs. 4. Split case of auctioning and free granting (grandfathering) of allowances. This is actually the approach used by the Regional Greenhouse Gas Initiative. For methodological purposes, this is not much different from Case 2. Of course, the macro impacts will differ.
IV. Calculation Steps and Assumptions Mitigation options are aggregated into four sectors: Electricity Supply (ES), Residential, Commercial, and Industrial (RCI), Transportation and Land Use (TLU), and Agriculture, Forestry, and Waste Management (AFW). The following are major elements in the further design of the simulations and an indication of how the analysis proceeds: 1. How much mitigation will each sector undertake? In the Stakeholder/Senate (Full Stakeholder Implementation) scenario, it is assumed that the 23 super options will be used to the maximum. In the Senate scenario, the reduction potentials of the super options are scaled-back separately for the cap-and-trade sector and the non-cap-and-trade sector to the level that the aggregate efforts of the cap-and-trade sector super options match with the K-L bill reduction target for the cap-andtrade sector and the non-cap-and-trade sector super options match with the K-L bill reduction goal for the non-cap-and-trade sector. 2. Which sectors would be covered under the cap? The ES and TLU sectors would be covered by the cap starting in 2013. The Industry sector and the Residential and Commercial sectors’ use of natural gas will be covered by the cap three years later (i.e., starting in 2016). The Agriculture and Forestry sectors are often the sectors that provide carbon offsets. 3. What is the allocation (or effective cap) for each cap-and-trade covered sector? In the Full Stakeholder scenario, we assume all the 23 super options will be implemented to their maximum reduction potentials. According to Figure 2-4 (the U.S. cost curve), this is equivalent to a total of 42.09% reduction of the 2020 baseline emissions. In the Senate scenario, we will apply the K-L bill target. The 2020 reduction target of the cap-and-trade sector specified in the K-L bill is 17% below the 2005 emissions level. The allowance allocation scheme specified in the K-L bill is presented in Table 3-14. 4. How do we determine the allowance price? In both simulation scenarios, we use the auction reserve price to compute the auction payments/revenues. 5. What is the total cost/saving for each option? Data from CCS workbooks are used. 6. How many allowances are purchased by each sector in the auction case? Sectors covered by the cap
Impacts of Comprehensive Climate and Energy Policy Options on the U.S. Economy 133
need to purchase allowances from the auction market when the emission reductions from autarkic mitigations fall short of compliance. 7. How do allowance purchases affect the macro impacts? Once we determine the allowance purchases and the allowance price, we can compute the expenditure for buying allowances at auction by each sector. In the REMI simulation, we deem the appropriate variables to reflect these expenditures as a “Production Cost” increase. 8. How many allowances are purchased or sold by each sector in sectoral trading? Covered sectors with excess allowances can sell those allowances in the inter-sectoral trading market. We simulate the direct effect of revenue gains from allowance sales as a “Production Cost” decrease of the selling sectors, and simulate the direct effect of allowance payments as a “Production Cost” increase of the purchasing sectors. 9. How many offsets are purchased? In our analysis, we assume that the cap-and-trade covered sectors can also purchase offsets from non-cap-and-trade sectors (mainly AFW sectors) if they still fall short of allowances needed for compliance after purchases of allowances from the auction market and from the inter-sectoral trading market. For international offsets, the expenditures are added to purchasing sector production costs. No domestic sectors experience revenue gains though they do avoid incurring higher mitigation costs. The macro impacts of offset purchases of the cap-and-trade sector are simulated in a similar manner as the allowance purchases, i.e., the “Production Cost” variable is used to capture the direct impact of offset payments. 10. How many allowances are banked? We assume that a sector can bank any excess allowances for future compliance use, which are neither used for its own compliance purposes nor sold to other sectors in the inter-sectoral trading market. 11. How are the revenues recycled? The auction revenues are recycled in the following three ways in 2020 (please see details in Section V, Government Revenue Recycling): a. Consumer Relief. b. Highway Trust Fund. c. Deficit Reduction Fund. 12. Since the allowance allocation rule varies among the Residential, Commercial, and Industrial sectors (see Table F-1), we disaggregate each RCI option in Table F-2 into sub-components of Residential sector, Commercial sector, Energy-Intensive Industrial sector (Ind-EIS), and Other Industrial sector (Ind-Other), respectively. The disaggregation methods for the RCI options include: a. The reduction potentials of RCI-1 (DSM) are split among the Residential, Commercial, and Industrial sectors using the weights of the sectoral total energy consumption of electricity, natural gas, and oil. b. For RCI-2 (High Performance Buildings), RCI-3 (Appliance Standards), and RCI-4 (Building Codes), when we split emission reduction potentials, the weighting of the Industrial sector is computed based on just 9.4% of the sectoral total energy consumption. This is because, based on the U.S. Department of Energy’s Energy Information Administration 2002 report on energy consumption by manufacturers, which indicates approximately 9.4% of industrial energy use in the U.S. is for heating, ventilating, and air conditioning, lighting, and other facilities, i.e., energy use reductions from high performance buildings, appliance standards, and building codes apply only to 9.4% of the total industrial energy use. c. For RCI-5 (CHP), the emission reduction potentials are split 50/50 between the Commercial sector and the Industrial sector. d. The determination of the Energy-Intensive Industrial sector is based on the U.S. Environmental Protection Agency (EPA) preliminary assessment of six-digit North American Industry
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Classification System (NAICS) industries that are “presumptively eligible” for preferable allowance allocations under H.R.2454 (EPA, 2009b). The reduction potentials of the mitigation options of the Industrial sector are further disaggregated between the Energy-Intensive Industrial sector and Other Industrial sector based on their respective 2006 GHG baseline emissions. e. The cost-effectiveness (i.e., the per-ton costs/savings) of the RCI options remains the same after the disaggregation. Table F-1. Percentages for RCI Options Policy Option RCI–1: Demand Side Management
Residential 34%
Commercial 30%
Industrial–EIS
Industrial–Other
15%
21%
RCI–2: High Performance Buildings
51%
45%
2%
3%
RCI–3: Appliance Standards
50%
46%
2%
2%
RCI–4: Building Codes
52%
43%
2%
3%
0%
50%
20%
30%
RCI–5: Combined Heat and Power
EIS = Energy-Intensive Industrial Sector; RCI = Residential, Commercial, and Industrial.
V. Government Revenue Recycling The K-L bill specifies that the proceeds of the allowance auction will be devoted to “Consumer Relief,” “Universal Trust Fund,” “Highway Trust Fund,” and “Deficit Reduction Fund.” For the “Highway Trust Fund,” the increased government spending will be simulated as a “Production Cost” decrease of the “Transit and Ground Passenger Transportation” sector in REMI. Auction proceeds used to reduce the deficit cannot be simulated in the REMI model, because it does not contain the necessary linkages between government budgets and key variables, such as the interest rate. “Consumer Relief” and the “Universal Trust Fund” relate to the government recycling auction revenues to households. For the Universal Trust Fund, all households are likely to be eligible. However, this fund will not be established until 2026. Since our analysis is focused on the year 2020, we will not simulate the impacts of revenue recycling to this fund. The Consumer Relief Program includes the Working Families Refundable Credit Program and the Energy Refund Program. For the Working Families Refundable Credit Program, an eligible taxpayer is defined as an individual whose household income is less than 150% of the poverty line minus $1,000. For the Energy Refund Program, there are many criteria to define an eligible household, such as a household with an income less than 150% of the poverty line that is participating in the Supplemental Nutrition Assistant Program, Food Distribution Program, etc. In our simulation, we use the 150% federal poverty level to define the household income group that will be covered by the Energy Refund Program. We also assume that these government transfers to the low-income households are not subject to income taxes. Table F-2 shows the 2009/2010 U.S. Department of Health and Human Services Poverty Guidelines for all states (except Alaska and Hawaii) and for the District of Columbia. According to the U.S. Census Bureau data, the 2006–2008 average family size is 3.2 people (U.S. Census Bureau, 2009). Therefore, the 150% poverty level of the average family size is computed as $27,465 + 20% × ($33,075 – $27,465) = $28,587. This income level is used to identify eligible household income groups for Energy Refund Program. The income level used for the Working Families Refundable Credit Program is computed as $28,587 – $1,000 = $27,587. When we simulate revenue recycling favoring low-income groups in the REMI model, we cannot use the REMI “Transfer Payments (amount)” variable, since we cannot specify transfer payments for any specific income group in the model. An alternative way to do this simulation is to work with the consumption columns of the low-income brackets in IMPLAN3 and translate the transfer payment into “Exogenous Final Demand” changes for REMI sectors. 3. Minnesota IMPLAN Group, Inc. (MIG, Inc.) developed the IMPLAN® economic impact modeling system. IMPLAN® is used to create complete, extremely detailed Social Accounting Matrices and Multiplier Models of local economies.
Impacts of Comprehensive Climate and Energy Policy Options on the U.S. Economy 135
Table F-2. 2009/2010 HHS Poverty Guidelines Size of Family Unit
100% of Poverty Level
110% of Poverty Level
125% of Poverty Level
1 2
150% of Poverty Level
175% of Poverty Level
$10,830
$11,913
$14,570
$16,027
185% of Poverty Level
200% of Poverty Level
$13,538
$16,245
$18,213
$21,855
$18,953
$20,036
$21,660
$25,498
$26,955
$29,140
3
$18,310
$20,141
$22,888
$27,465
$32,043
$33,874
$36,620
4
$22,050
$24,255
$27,563
$33,075
$38,588
$40,793
$44,100
5
$25,790
$28,369
$32,238
$38,685
$45,133
$47,712
$51,580
6
$29,530
$32,483
$36,913
$44,295
$51,678
$54,631
$59,060
7
$33,270
$36,597
$41,588
$49,905
$58,223
$61,550
$66,540
8
$37,010
$40,711
$46,263
$55,515
$64,768
$68,469
$74,020
Source: U.S. Department of Health and Human Services.
Table F-3 shows the household income brackets used in IMPLAN. The first three income brackets and part of the fourth income bracket fall into the low-income household categories specified for the Energy Refund Program and the Working Families Refundable Credit Program in the K-L bill. Table F-4 shows how the government transfer to the Energy Refund Program and to the Working Families Refundable Credit Program will be distributed among the first four income brackets based on total consumptions plus savings of respective income bracket. The following steps show how to translate the government transfers to the low-income households into final demand changes by REMI sector: »»The 440 IMPLAN sectors are first aggregated to the 169 REMI sectors. »»The household consumption columns of the first four household income brackets are extracted from IMPLAN. »»Consumption coefficients are computed for each of the first four income brackets. »»The transfers distributed to each income bracket are computed based on the proportions shown in Table F-4. »»For each income bracket, the transfers from the two consumer relief programs are translated to increases in sectoral goods consumption by multiplying the total transfer to this income bracket by its consumption coefficient of each individual REMI sector. »»The total “Exogenous Final Demand” change to each REMI sector is the sum of consumption changes of the four income groups. Table F-3. IMPLAN Household Income Brackets (thousand 2008$) Income Brackets 1
2
3
4
< $10
$10–15
$15–25
$25–35
5
6
7
$35–50 $50–75 $75–100
8
9
$100–150
$150+
Table F-4. Income Transfer for the Energy Refund Program and Working Families Refundable Credit Program Income Brackets
Energy Refund Program
Working Families Refundable Credit Program
Income Transfer (billion 2008$)
Percentage
Income Transfer (billion 2008$)
Percentage
< $10
$1.97
$10–15
$1.37
23.4%
$0.42
24.7%
16.4%
$0.29
17.3%
$15–25
$3.47
41.3%
$0.73
43.6%
$25–28.6
$1.59
18.9%
$0.24
14.4%
Total
$8.40
100%
$1.68
100%
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References Coase, R. 1960. “The Problem of Social Cost,” Journal of Law and Economics 3(1): 1-44. Ellerman, A. D. 2008. “The EU Emission Trading Scheme: Prototype of a Global System?” Discussion Paper 08-02, The Harvard Project on International Climate Agreements. Ellerman, A. D., Joskow, P.L., Schmalensee, R., Montero, J., and Bailey, E.M. 2000. Markets for Clean Air: The U.S. Acid Rain Program. Cambridge, UK: Cambridge University Press. Miller, S., Wei, D., and Rose, A. 2010. The Economic Impact of the Michigan Climate Change Action Plan on the State’s Economy. Report to the Michigan Department of Environmental Quality, Center for Climate Strategies, Washington DC. Rose, A. 2009. The Economics of Climate Change Policy: International, National and Regional Strategies, Cheltenham, UK: Edward Elgar Publishing Company. Rose, A., and Wei, D. 2009a. The Economic Impact of the Florida Energy and Climate Change Action Plan on the State’s Economy. Report to the Office of the Governor of the State of Florida, Center for Climate Strategies, Washington DC. Rose, A., and Wei, D. 2009b. “Macroeconomic Assessment,” Chapter 11 in Pennsylvania Climate Action Plan. http://www.depweb.state.pa.us/energy/cwp/view.asp?q=539829. Rose, A., Wei, D., Wennberg, J., and Peterson, T. 2009. “Climate Change Policy Formation in Michigan: The Case for Integrated Regional Policies,” International Regional Science Review 32(4): 445-465. Tietenberg, T. 1985. Emissions Trading: An Exercise in Reforming Pollution Policy. Washington, DC: Resources for the Future). Tietenberg, T. 2007. “Tradable Permits in Principle and Practice,” in J. Freemand and C. Kolstad (eds.), Moving to Markets: Lessons from Twenty Years of Experience. New York: Oxford University Press. U.S. Department of Energy, Energy Information Administration. 2005. 2002 Energy Consumption by Manufacturers. http://www.eia.doe.gov/emeu/mecs/mecs2002/data02/shelltables.html. U.S. Department of Health and Human Services. Poverty Guidelines, Research, and Measurement. http://aspe.hhs.gov/poverty.