Macroeconomic Impact Analysis of Proposed Greenhouse Gas and Fuel Economy Standards for Medium- and Heavy-Duty Vehicles

Transcription

1 Macroeconomic Impact Analysis of Proposed Greenhouse Gas and Fuel Economy Standards for Medium- and Heavy-Duty Vehicles Prepared for the: Union of Concerned Scientists 2397 Shattuck Ave., Suite 203 Berkeley, CA Prepared by: Marshall Goldberg MRG & Associates Starduster Drive Nevada City, California January 2011

2 Summary of Findings In October 2010, the Environmental Protection Agency (EPA) and National Highway Transportation and Safety Administration (NHTSA) proposed greenhouse gas and fuel economy standards for medium and heavy-duty engines and vehicles. Implementing these standards would accelerate the development and adoption of medium and heavyduty vehicle fuel efficiency technologies between 2014 and 2018, resulting in increased fuel efficiency technology investments and substantial net fuel cost savings. These investments and savings are detailed in the regulatory impact analysis published by EPA and NHTSA as part of the rulemaking process. 1 Utilizing these investments and savings, this current study analyzed the net macro economic impacts that result; including the change in national employment, wage and salary income, and national gross domestic product. The key findings include, Significant fuel cost savings by trucking companies and consumer savings on product shipping costs. A net increase of 40,630 jobs economy-wide in 2020 and 78,140 jobs in Wage and salary income increases of $2.3 billion in 2020 and $5.5 billion in GDP increases of $2.9 billion in 2020 and $7.2 billion in Service, retail, and manufacturing sectors see the largest employment increases while petroleum-related employment decreases. A state-by-state breakdown shows employment gains are distributed widely throughout the country, with net job growth shown in every state. Introduction In this analysis, the impacts on the US economy from investments in fuel efficiency technologies in the medium and heavy-duty trucking sector are evaluated. The proposed EPA and NHTSA standards for medium and heavy-duty engines and vehicles would phase-in between model year 2014 and model year 2018, achieving up to a 20 percent reduction in fuel consumption compared to a 2010 baseline. These improvements would come from more efficient engines, improved aerodynamics, lower rolling resistance tires, and other vehicle technologies. To meet these standards, manufacturers would increase investments in implementing and deploying these technologies in their medium and heavy-duty vehicle fleets. Truck owners would initially pay more for their vehicles, but save far more in fuel costs over the life of the vehicle. These investments and fuel cost savings, evaluated by EPA and NHTSA as part of the proposed rule, are shown in Table 1 for year 2020 and 2030 and are in comparison to the fuel efficiency of a 2010 truck. 1 Environmental Protection Agency and National Highway and Transportation and Safety Administration, Draft Regulatory Impact Analysis: Proposed Rulemaking to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, October 2010, EPA-420-D

3 Table 1. EPA/NHTSA Proposed Standards Analysis Technology Investment Costs and Savings for Medium and Heavy-Duty Trucks (Above a 2010 baseline) 2020 Medium and Heavy-Duty Trucks ($Billion) 2030 Medium and Heavy-Duty Trucks ($Billion) Incremental Investments in Fuel Efficiency $1.98 $1.95 Fuel Cost Savings $9.3 $21.2 Source: Environmental Protection Agency and National Highway and Transportation and Safety Administration, Draft Regulatory Impact Analysis: Proposed Rulemaking to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles. October 2010, EPA-420-D All figures are in billions of 2008 dollars. Methodology for Deriving National Macro Economic Impacts To derive the economic and employment impacts from the analysis of the EPA/NHTSA regulations we began with the actual investments in vehicle efficiency and the changes in motor fuel expenditures brought about by these investments. Once the gains and losses were sorted out in each industry sector, we then evaluated the net benefits or impacts to the nation s overall economy. This includes: 1) the net contribution to the employment base (jobs); 2) the net gain in wage and salary compensation, measured in millions of year 2008 dollars; and 3) the net contribution to Gross Domestic Product (GDP), also measured in millions of year 2008 dollars. These three impacts were evaluated using data derived from the IMPLAN V3.0 software. IMPLAN is an input-output (I-O) model that identifies interactions between all sectors of the economy. The model incorporates interactions among 440 industrial sectors to trace supply linkages and evaluate how changes in spending affect employment, wages, and gross domestic product (GDP). For each of the benchmark years (2020 and 2030), each change in an industry s spending pattern is matched to an appropriate industry multiplier. Input-output models were initially developed to trace supply linkages in the economy. Thus, the impacts generated from the EPA/NHTSA proposed regulations for the truck transportation scenario depend on the structure of the economy. For example, I-O models can show how increasing purchases of more efficient trucks not only directly benefit the truck manufacturers, but also benefit those industries that provide inputs (i.e., goods and services) to these manufacturers. I-O models can also be used to show the benefits from indirect economic activity that occurs as a result of these transactions (e.g., banking and accounting services, among others) and the spending of fuel savings throughout the economy. Therefore, spending on more fuel efficient trucks has an effect on total employment, income (i.e., wage and salary compensation), and GDP. 3

4 For each industry sector within the economy we utilized multipliers that identify the employment and economic activity generated from a given level of spending in each sector. Changes in expenditures are matched with appropriate multipliers. For instance, employment multipliers show the number of jobs that are directly and indirectly supported for each one million dollars of expenditure in a specific sector. For this analysis, a job is defined as sufficient wages to employ one person full-time for one year in a given sector. The analysis in this study includes several assumptions and adjustments to the methodology of matching expenditures and multipliers. First, it was assumed that fuel efficiency improvements are a part of all new truck purchases. Second, we made an adjustment in the employment impacts to account for future changes in labor productivity in specific sectors. Utilizing data from the Bureau of Labor Statistics Economic and Employment Projections 1998, 2008 and 2018, we developed productivity trends for our analysis. These trends suggest that productivity rates are expected to vary widely among sectors. Annual productivity gains are forecast to range from little if any change in the education sectors to over 4.0 percent annual productivity gain in the medium and heavy-duty truck manufacturing sectors. Third, we assumed that 80 percent of the investments in new more fuel-efficient vehicles will be financed by bank loans carrying an average 6 percent interest rate over a five year period. 2 No parameters were established to account for changes in interest rates or in labor participation rates. While a demand for labor may tend to increase the overall level of wages (and potentially lessen economic activity), the employment benefits from the scenario are relatively small compared with the national level of unemployment or underemployment. Fourth, we distributed the projected fuel savings (dollars) between the trucking industries and fleets (where the fuel savings are occurring) and consumers. Fuel prices from the EPA/NHTSA regulatory impact analysis modeling were used for calendar years 2020 and These savings are then available for investment and spending in the economy. The analysis assumes 50 percent of the savings benefit the trucking industry and fleets directly and 50 percent are passed on in the form of lower shipping costs and the resulting lower costs of goods. The lower costs for goods represent savings for consumers and ultimately more disposable income. A sensitivity analysis, described later in this document, was performed to quantify the impact of different assumptions about retention of fuel savings. 2 No industry-wide financing references were found. However an internet search revealed interest rates for individual truck buyers in the range of 7 to 12 percent. Individual truck buyers generally pay higher interest rates on truck purchases while larger fleets may have access to more financing options and lower interest rates. The 6 percent rate was chosen to reflect this. 4

5 Methodology for Deriving State-by-State Employment Impacts The distribution of the national employment impacts across the states is difficult to predict. Some impacts are associated with the direct expenditures made for more fuelefficient medium and heavy-duty trucks while others are associated with the spending of fuel savings associated with driving these trucks. To take these factors into account, we developed indicative estimates of the distribution of the net national jobs gained across the fifty states and the District of Columbia. Absent a more detailed analysis of each individual state or region, the authors utilized a methodology incorporating the national impacts and a weighting of key variables to accomplish an overall state-by-state assessment. The key variables associated with the fuel savings analysis include: differences in distillate fuel oil energy prices in each state and the level of transportation energy consumed for each dollar of economic activity in the state. The key variables associated with the direct expenditure analysis include: the number of state jobs in the respective industries as a percent of national employment projected for the respective years. With the inherent uncertainties related to making these types of projections and then distributing national impacts to individual states, the methodology employed in this study reflects an averaging of two procedures. The first is a scaling of the national net employment changes for the respective years for each state and industry sector analyzed. We utilize employment projections from the Bureau of Labor Statistics to derive the results. This analysis assumes the impacts are distributed based on each state s industry share of employment. It captures the approximate supply impacts on energy producing states as well as industry demand for goods and services from the spending on higher efficiency vehicles and spending of fuel savings. The second procedure relies more heavily on motor fuel use and price parameters to allocate net energy savings and then estimate the net employment changes. First, we derive the changes in diesel fuel consumption for each of the states as a function of energy/gross state product and average energy prices in Then, utilizing the proportional shares of the national ratios for this same data, and the overall employment impacts from the national analysis, we apply coefficients from a regression analysis of these factors to derive the net jobs for each state. Given the significant transportation related energy and economic differences among the states and the strengths and weaknesses associated with the two procedures, we then average the two results. Similar to the national impacts, the state specific impacts are not intended to be precise forecasts of what will occur, but rather approximate estimates of overall impact. To further assess the industry sector-specific job impacts for each of the states would require significantly more analysis, well beyond the scope of the present study. Macroeconomic Results The investment and savings data from the EPA/NHTSA proposed standards were used to estimate three sets of impacts for the years 2020 and 2030, as shown in Table 2. These 5

6 included: net employment impacts, net change in wage and salary income (in 2008 dollars) and net change in gross domestic product (in 2008 dollars). Table 1 provides a summary of the national impacts. The impacts are positive in each year, in each of the categories. Employment gains range from 40,630 in 2020 to 78,140 in Income and GDP show similar gains. GDP increases almost $3 billion and just over $7 billion (in 2008 dollars) in 2020 and 2030, respectively. Wage and salary income increase $2.3 billion and $5.5 billion in 2020 and 2030, respectively. Table 2. EPA/NHTSA Proposed Standards Analysis Summary Impacts - Medium and Heavy-Duty Trucks Year Net Jobs (Actual) Wage and Salary Income Gross Domestic Product ,630 $2,286 $2, ,140 $5,515 $7,235 Note: All figures are in millions of 2008 dollars. Tables 3 and 4, on the following page, show how each of the major industry sectors are affected in 2020 and As noted previously, the results are not intended to be precise forecasts, but rather approximate estimates of the overall impact. Table 3. EPA/NHTSA Proposed Standards Analysis 2020 Impacts Medium and Heavy-duty Trucks Industry Net Jobs (Actual) Wage and Salary Income Gross Domestic Product Services 19,720 $1,028 $1,334 Other Manufacturing 7,830 $931 $1,248 Retail 5,840 $238 $392 6

7 Insurance/Real Estate 3,580 $165 $859 Finance 2,260 $312 $481 Durable Metals 1,860 $132 $211 Education 1,820 $59 $65 Transportation, Communication, and 1,410 $133 $211 Public Utilities Agric/Forestry 1,120 $26 $60 Primary Metals 780 $83 $125 Food 610 $39 $66 Trucking 600 $37 $50 Pulp and Paper 190 $19 $27 Mining 180 $20 $42 Stone, Glass, and Clay 160 $12 $19 Electric Utilities 150 $33 $115 Natural Gas Utilities 50 $9 $22 Petroleum Refining (40) ($16) ($25) Construction (300) ($15) ($17) Government (710) ($52) ($66) Wholesale Trade (1,710) ($185) ($318) Oil & Gas Extraction (4,790) ($724) ($2,030) Total 40,630 $2,286 $2,928 Note: All dollar values are 2008 dollars. Individual column totals may not add up due to independent rounding.. Table 4. EPA/NHTSA Proposed Standards Analysis 2030 Impacts Medium and Heavy-duty Trucks Wage and Salary Income Gross Domestic Product Net Jobs Industry (Actual) Services 40,980 $2,449 $3,178 Other Manufacturing 12,560 $2,133 $3,051 Retail 9,570 $545 $897 Insurance/Real Estate 7,290 $379 $1,972 Durable Metals 5,120 $431 $688 Education 4,160 $135 $149 Finance 2,660 $545 $839 7

8 Transportation, Communication, and 2,640 $322 $513 Utilities Primary Metals 2,210 $279 $421 Agric/Forestry 2,140 $61 $140 Food 1,220 $90 $152 Trucking 1,180 $95 $127 Mining 560 $67 $141 Stone, Glass, and Clay 480 $39 $64 Pulp and Paper 410 $51 $73 Electric Utilities 300 $86 $295 Natural Gas Utilities 140 $24 $56 Petroleum Refining (60) ($36) ($55) Construction (530) ($27) ($30) Government (1,510) ($117) ($149) Wholesale Trade (2,480) ($392) ($674) Oil and Gas Extraction (10,880) ($1,645) ($4,612) Total 78,140 $5,515 $7,235 Note: All dollar values are 2008 dollars. Individual column totals may not add up due to independent rounding.. 8

9 As might be expected, the oil and gas extraction industries and the petroleum related industries (including wholesale trade which delivers bulk petroleum and government which receives tax revenues from petroleum sales) incur losses in jobs, income and contribution to GDP. These negative employment impacts and the economic losses must be tempered somewhat as the industries and the overall economy undergo restructuring and there is a redistribution of jobs and future occupational tradeoffs. The tables also show four industries that incur significant gains in 2020 and 2030 and others that incur more modest gains. The services industry has the largest gain (approximately 41% of the total gains - of those industries showing gains in 2020) because it is the industry that benefits the most from both the trucking industry spending of their fuel savings and consumers spending their savings from lower costs of goods. The other industries that show significant gains include: other manufacturing (which includes a broad array of manufacturing industries including heavy duty truck manufacturing), retail, and insurance/real estate. The retail and insurance/real estate industry gains are primarily from consumer spending. The large gains in manufacturing are primarily associated with spending from the trucking industry and fleets. Sensitivity Analysis As with any analysis of this type and scope the assumptions used play an important role in influencing the results. Similarly, there is some uncertainty regarding exactly who will ultimately benefit directly from fuel savings in the trucking industry and in fleets and how the dollar savings will be spent. To better understand how changes in spending influence the results of the efficiency analysis we ran a sensitivity analysis of the macroeconomic impacts derived in this study. The first sensitivity assumes all fuel savings are retained and spent by the trucking industry and fleets. In this case the analysis assumes the trucking companies and fleets need the added profit to stay in business and/or do not need to lower their costs to remain competitive; thus fuel savings are not passed on as lower transportation costs or as lower cost of goods. The second sensitivity assumes all fuel savings are passed on. In this case the analysis assumes the trucking companies and fleets pass on the savings to remain competitive. This results in lower costs for goods (reflecting lower transportation costs) and then additional spending by consumers. The two effects were modeled separately with the results shown in Table 5. Table 5 indicates that regardless of who receives and spends the fuel savings, the analysis results in positive benefits for the national economy. In 2020, the benefits range from an employment gain of 25,890 (with 100 percent spending by the trucking industry) to 55,370 (with 100 percent spending by consumers). Spending of fuel savings by the trucking industry results in gains in almost all industries (with the exception of the petroleum related as noted previously) although three industries show the largest gains. These include: other manufacturing, services, and durable metals manufacturing. 9

10 Spending of all fuel savings by consumers results in significantly larger gains. This is due to the varied consumer spending patterns relative to that of the trucking industry. Similar to the results reported in this study, the services and retail sectors show the most significant gains; however, in this sensitivity analysis, these two industries combined account for a larger share, just over 67 percent of the total gains (i.e., all industries showing gains, not including those showing losses). Among other industries showing gains well above those of the trucking industry only spending analysis, are the education sectors, the finance sectors, and the transportation, communication and public utilities sectors. Table 5. Sensitivity Analysis of EPA/NHTSA Proposed Standards Analysis Medium and Heavy-duty Trucks Scenario Net Jobs (Actual) Wage and Salary Income Gross Domestic Product Results Reported in this Study Shared Spending of Fuel Savings (50% Trucking Industry 50% Consumers) ,630 $2,286 $2, ,140 $5,515 $7,235 Sensitivity Analysis A Consumers Only Spending of Fuel Savings (100%) ,370 $2,446 $3, ,290 $5,879 $8,888 Sensitivity Analysis B Trucking Industry Only Spending of Fuel Savings (100%) ,890 $2,126 $2, ,990 $5,150 $5,583 Note: All dollar values are 2008 dollars. See Appendix for sensitivity results by industry. 10

11 State-by-State Employment Impacts With the national impacts established from the medium and heavy-duty truck transportation efficiency base analysis, we see significant net employment gains. Providing state-by-state estimates of state level impacts provides additional insight into the benefits of these policy and investment initiatives. In Table 6 we see that the benefits are widely distributed throughout the country and the employment gains are positive in all states for both years analyzed. In those states with a large share of the nation s oil and petroleum related industries the industry losses (noted earlier) are offset by gains from spending of fuels savings primarily in other industry sectors. In 2020, the gains range from a low of 70 jobs in Vermont to a high of 4,350 jobs in California. By 2030, net job gains range from a low of 140 jobs in Vermont to a high of 8,500 jobs in California. Table 6. EPA/NHTSA Proposed Standards Analysis State-by-State Employment Impacts Net Job Gain Net Job Gain State State Alabama 710 1,380 Montana Alaska Nebraska Arizona 720 1,410 Nevada Arkansas New Hampshire California 4,350 8,500 New Jersey 1,060 2,070 Colorado 540 1,040 New Mexico Connecticut New York 1,880 3,600 Delaware North Carolina 1,210 2,300 District of Columbia North Dakota Florida 2,070 4,040 Ohio 1,920 3,690 Georgia 1,270 2,480 Oklahoma Hawaii Oregon 560 1,080 Idaho Pennsylvania 1,730 3,380 Illinois 1,780 3,450 Rhode Island Indiana 1,350 2,510 South Carolina 620 1,190 Iowa 520 1,000 South Dakota Kansas Tennessee 1,000 1,950 Kentucky 790 1,520 Texas 3,000 5,530 Louisiana Utah Maine Vermont Maryland 630 1,240 Virginia 1,050 2,030 Massachusetts 760 1,500 Washington 950 1,860 Michigan 1,330 2,470 West Virginia Minnesota 790 1,540 Wisconsin 890 1,710 Mississippi Wyoming Missouri 960 1,850 U.S. Total 40,630 78,140 11

12 12

13 References (noted in text): Minnesota IMPLAN Group Inc., IMPLAN V 3.0 software, ( U.S. Department of Labor, Bureau of Labor Statistics, Employment and Output by Industry, 1998, 2008, and Projected U.S. Department of Commerce, Bureau of Economic Analysis (BEA), Gross State Product, U.S. Department of Energy, Energy Information Administration, Transportation Sector Energy Consumption Estimates U.S. Department of Energy, Energy Information Administration, Transportation Sector Energy Expenditure Estimates by Source, U.S. Environmental Protection Agency and National Highway and Transportation and Safety Administration, Draft Regulatory Impact Analysis: Proposed Rulemaking to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, October 2010, EPA-420-D

14 Appendix A: Sensitivity Analysis Industry Data Tables. Table A1. EPA/NHTSA Proposed Standards Analysis 2020 Summary Results 100% of Fuel Savings Retained by Trucking Companies Industry Net Jobs (Actual) Wage and Salary Income Gross Domestic Product Other Manufacturing 13,870 $1,648 $2,316 Services 6,930 $361 $469 Durable Metals 5,020 $357 $571 Primary Metals 2,190 $232 $350 Finance 1,270 $175 $270 Transportation, Communication, and 800 $76 $120 Public Utilities Trucking 700 $44 $59 Mining 490 $54 $113 Stone, Glass and Clay 420 $31 $50 Agric/Forestry 360 $8 $19 Insurance/Real estate 290 $13 $70 Pulp and Paper 270 $28 $40 Retail 160 $7 $11 Electric Utilities 130 $29 $98 Natural Gas Utilities 80 $15 $34 Food 60 $4 $6 Education 10 $0 $0 Petroleum Refining (40) ($19) ($29) Construction (240) ($12) ($13) Government (780) ($58) ($73) Wholesale Trade (1,320) ($143) ($245) Oil & Gas Extraction (4,790) ($725) ($2,033) Total 25,890 $2,126 $2,203 Note: All dollar values are 2008 dollars. Individual column totals may not add up due to independent rounding. All fuel savings spent by Trucking industry. 14

15 Table A2. EPA/NHTSA Proposed Standards Analysis 2030 Summary Results 100% of Fuel Savings Retained by Trucking Companies Wage and Salary Income Gross Domestic Product Net Jobs Industry (Actual) Other Manufacturing 22,100 $3,765 $5,357 Services 15,540 $929 $1,205 Durable Metals 11,210 $944 $1,508 Primary Metals 4,900 $619 $933 Transportation, Communication, and 1,570 $192 $306 Utilities Trucking 1,370 $111 $148 Mining 1,200 $145 $303 Finance 1,130 $232 $358 Stone, Glass, and Clay 1,010 $82 $134 Agric/Forestry 720 $21 $48 Insurance/Real Estate 640 $33 $172 Pulp and Paper 580 $72 $102 Retail 310 $17 $29 Electric Utilities 260 $75 $258 Natural Gas Utilities 200 $36 $84 Food 120 $9 $15 Education 20 $1 $1 Petroleum Refining (70) ($41) ($63) Construction (380) ($19) ($21) Government (1,670) ($129) ($165) Wholesale Trade (1,870) ($296) ($509) Oil & Gas Extraction (10,890) ($1,647) ($4,619) Total 47,990 $5,150 $5,583 Note: All dollar values are 2008 dollars. Individual column totals may not add up due to independent rounding. All fuel savings spent by Trucking industry. 15

16 Table A3. EPA/NHTSA Proposed Standards Analysis 2020 Summary Results 100% of Fuel Savings Passed to Consumers Industry Net Jobs (Actual) Wage and Salary Income Gross Domestic Product Services 32,510 $1,695 $2,200 Retail 11,510 $469 $773 Insurance/Real Estate 6,870 $317 $1,649 Education 3,640 $119 $130 Finance 3,260 $449 $692 Transportation, Communication, and Public 2,010 $190 $302 Utilities Agric/Forestry 1,880 $44 $100 Other Manufacturing 1,800 $216 ($1,214) Food 1,170 $74 $126 Trucking 490 $31 $41 Electric Utilities 180 $38 $132 Pulp and Paper 100 $10 $14 Natural Gas Utilities 20 $4 $10 Petroleum Refining (30) ($14) ($22) Stone, Glass, and Clay (100) ($7) ($11) Mining (130) ($14) ($29) Construction (370) ($19) ($21) Government (630) ($47) ($59) Primary Metals (630) ($66) ($100) Durable Metals (1,300) ($93) ($148) Wholesale Trade (2,090) ($227) ($390) Oil & Gas Extraction (4,780) ($723) ($2,027) Total 55,370 $2,446 $3,653 Note: All dollar values are 2008 dollars. Individual column totals may not add up due to independent rounding. All fuel savings spent by consumers. 16

17 Table A4. EPA/NHTSA Proposed Standards Analysis 2030 Summary Results 100% of Fuel Savings Passed to Consumers Wage and Salary Income Gross Domestic Product Net Jobs Industry (Actual) Services 66,420 $3,970 $5,151 Retail 18,840 $1,072 $1,766 Insurance/Real Estate 13,940 $724 $3,772 Education 8,300 $270 $297 Finance 4,180 $857 $1,320 Transportation, Communication, and 3,700 $452 $720 Utilities Agric/Forestry 3,550 $101 $233 Other Manufacturing 3,020 $502 $744 Food 2,310 $171 $289 Trucking 990 $80 $107 Electric Utilities 340 $97 $333 Pulp and Paper 250 $30 $43 Natural Gas Utilities 70 $12 $28 Stone, Glass, and Clay (50) ($4) ($6) Petroleum Refining (60) ($31) ($48) Mining (80) ($10) ($21) Primary Metals (490) ($61) ($92) Construction (680) ($34) ($38) Durable Metals (970) ($82) ($131) Government (1,350) ($104) ($133) Wholesale Trade (3,090) ($489) ($840) Oil & Gas Extraction (10,860) ($1,642) ($4,606) Total 108,290 $5,879 $8,888 Note: All dollar values are 2008 dollars. Individual column totals may not add up due to independent rounding. All fuel savings spent by consumers. 17