this is a remake of the Coal article published in IJPA in 1995
ANALYSING THE IMPACT OF LOST COAL SALES USING THE ILLINOIS REMI MODEL
Mark A. Bonardelli
Strategic Planning Section
Illinois Department of Energy and Natural Resources
325 West Adams Street, suite 300,
Springfield, Illinois 62704-1892
Illinois is the fifth largest producer of coal in the nation. The high BTU or heat content makes it attractive to burn in the generation of electricity. However, the amount of sulfur in Illinois coal has made it a target of environmental legislation. As utilities work to meet the requirements of the 1990 Clean Air Act, it is likely that demand for Illinois coal will decline, thereby leading to a reduction in coal output of the coal-producing counties of the state. The sub-state REMI dynamic general equilibrium model was used to determine the impacts of the dramatic reduction of coal demand on the Illinois economy. While coal mining represents a small percentage of total gross state product, to some counties in the state, coal mining represents a significant amount of the regional product and is a principal source of employment for these areas.
The impacts of lost coal output on the economy of southern Illinois as predicted by the REMI model were significant. This led to policy prescriptions to provide incentives to utilities to burn Illinois coal. While the short-term outlook for Illinois coal may appear bleak even with incentives, it is expected that Illinois can eventually be competitive in world coal markets due to the high BTU content of the coal, the extensive reserves, and the existence of an excellent transportation network.
COAL'S IMPORTANCE TO ILLINOIS
Coal has been a driving force behind Illinois and United States economic growth over the years. From the late nineteenth century and into this century, Illinois coal has been available for heating, production processes, and the generation of electricity. During the Depression sales plummeted along with all economic activity in the nation but as the second World War began, Illinois production increased to serve the war effort. After 1945, Illinois coal production declined once again as the nation shifted back to a peacetime economy. In the 1950s, as competition with oil and natural gas increased, coal continued to lose ground, particularly in the railroad and home heating markets. However, since the 1960s, Illinois coal output has increased and has remained at around 60 million tons per year due to demand from the electric utility industry.
Of the 1 billion tons of coal produced in the U.S. in 1991, Illinois produced 60 million tons, making this state the fifth largest coal producer in the nation. In the last twenty-five years, Illinois coal production has been relatively stable, as seen in Figure 1. However, within the industry itself, there have been major swings in employment and productivity, along with shifts in the geographic location of the markets and changes in the markets themselves. In 1960, slightly over fifty percent of Illinois coal output was purchased by electric utilities, as indicated in Figure 2. Since then, utilities have demanded more coal to the meet electricity needs of their customers, while the industrial sector has reduced their demand and the retail sector has virtually disappeared.
In the 1970s, the adoption of environmental laws, especially the federal Clean Air Act and subsequent amendments, led to changes in the Illinois coal market. The results of these environmental initiatives caused utilities which burned Illinois coal to seek alternative coal producers to meet these pollution requirements. For example, Commonwealth Edison, the state's largest utility, switched to low sulfur western U.S. coal to meet air quality standards for the northern area of the nation. Similarly, the northern coal markets for Illinois coal reduced purchases from Illinois mines and switched to the low sulfur coal of the western states. An additional impact on the Illinois coal market was due to the construction of nuclear plants in Illinois and around the country. Illinois has become the largest generator of electricity from nuclear plants. Coal-fired generation of electricity in Illinois has declined to just above forty percent of total electricity generation. In spite of these events, some new markets were developed due to growth in electricity demand in the southern states and the economics of transporting the Illinois coal to those areas.
Illinois Coal Sales by Customer Group: 1960-1990.
To date, the Illinois coal industry has been able to adapt fairly well to the changes in economic and regulatory events. However, coal markets are expected to be altered dramatically once again. The passage of the 1990 Clean Air Act Amendments is expected to cause a significant decline in Illinois coal sales since it requires that electric utilities make large sulfur dioxide emission reductions by 1995 and then again in 2000.
To meet the requirements of the Act, a utility principally has two choices: installing scrubbers and using high-sulfur coal, such as Illinois coal or switching to low-sulfur western coal. Since there is a strong possibility that the utilities which presently burn Illinois coal will alter their present policy, the REMI Model was used to determine the impacts of switching on the state's economy. Of particular interest are the impacts on employment and personal income of the coal mining areas. Furthermore, the loss of non-mining jobs in the areas was also investigated with the REMI model.
DESCRIPTION OF THE REMI MODEL
The REMI model is a dynamic general equilibrium model of the Illinois economy and its sub-regions. The model used in the subsequent analysis of lost coal sales divides the state into seven sub-regions. According to the REMI manual, the structure of the model incorporates inter-industry transactions as well as behavioral equations from economic theory. This approach allows for detailed data to be incorporated into the model and allows the model to respond to policy-initiated changes. The REMI model therefore replicates the sub-national economy that predicts supply and demand conditions across 53 sectors, 94 occupations, 25 final demand sectors, and 202 age/sex cohorts.
In contrast to traditional regional models, the REMI model is estimated using data from all regions and then calibrated to a specific region. This method allows model parameters to be estimated using a large data set that produces more econometrically reliable results than would be possible using data from a smaller area. Other features include a Cobb-Douglas production function which allows for substitution among factors, along with the ability to track migration changes in response to income fluctuations, wage responses to changes in labor market conditions, and changes in the share of local and export markets in response to regional production costs.
The REMI model generates a forecast by solving for the equilibrium values in the labor, goods, and other markets of the economy for every year of the forecast. This dynamic approach is used to clear the markets instead of the traditional approach in regional models of using econometric estimates based on time-series observations for each region. Therefore, the REMI model is not an econometric model although some coefficients are determined econometrically for use in the clearing of the markets over the forecast time period.
The model can be summarized without the use of the many equations that are contained in the model. Five major components can be segregated in the REMI model:
1. final demand and output
2. labor and capital demand
3. population and labor supply
4. wages, prices, and profits
5. market shares.
As one would expect, each component is interrelated with each other. From Figure 1, one sees that the output component (1), the core of the model, drives labor demand (2). Labor demand interacts with the supply of labor (3) to determine the wage rate. Wages, along with the costs of the other factors of production, determine relative production costs and profitability (4). The relative costs thereby affect market shares (5). The market shares are the proportions of local demand in the region and exogenous export demand that local production fulfills.
Consumption, investment, and state and local government demand derives final demand. Consumption itself is a function of real disposable income. An identity equation defines nominal disposable income as wage income from components 2 and 4, plus property income related to the population (3), plus transfer income related to population less employment and retirement population, minus taxes. Nominal disposable income is then deflated by the price index (4). The optimal capital stock (2) drives investment. Population (3) drives state and local government final demand.
An input-output table, which captures detailed inter-industry relationships, is part of the REMI modeling system and can be used if detailed input information is available to the analyst. The I-O table is derived from actual observed production and consumption data in the various sectors of the economy. The basic unit is a broadly defined industry or sector that is assumed to use both labor and the products of the other industries as inputs. These industries produce output for either input to other industries or for final consumption. The I-O table gives a picture of the interrelations that exist in the economy at a moment in time.
The use of the input-output table allows for more precision in the impacts of a simulation. The increased precision comes from the ability to stimulate sectors that are more specific than the two-digit Standard Industrial Classification (SIC) industries in the forecasting portion of the REMI model. Since it is likely that the characteristics of the more disaggregated industry are different that its two-digit SIC grouping, greater weight is given to the disaggregated industry within its two-digit SIC grouping. The input-output data is aggregated to the two-digit SIC level and is transferred to the forecasting portion of the REMI model in the form of wage adjustments and employment. With the data from the input-output table, the forecasting portion of the REMI model can extrapolate into the future from the detailed change in economic activity.
The first step in this impact analysis was to develop the input variables to be used in the sub-state REMI model. The mining industry sales variable could be used to simulate the effects of lost coal sales. Using this variable, however, assumes that the coal mining industry purchases the same goods and services as the mining industry. The mining industry is the several sub-categories, including coal mining, petroleum and natural gas extraction, stone and clay mining, among others. Therefore, use of a policy variable (i.e. the mining industry) reflecting the average of all the smaller industries cannot be as precise as using a sub-category, such as the coal mining industry, with its specific purchases of excavation and earth-moving equipment. Since input data had been compiled at the more detailed level of the coal mining industry level, the input-output variable was used to provide increased accuracy in the impacts expected in the economy.
Coal sales in tons were placed into four risk categories based on several factors, such as the type of contract, the ability of the utility to scrub, and the announced plans of the utility regarding its policy on the Clean Air Act. Coal sales were assigned to one of the following categories:
Ninety percent of Illinois coal sales are to electric utilities. While the remaining amount of coal sales to the industrial and retail markets can also be classified into one of the risk categories, this analysis concentrates on coal sales to utilities.
A description of the sub-state REMI model regions is necessary at this juncture to illustrate the major coal-producing areas. The sub-state REMI model is divided into seven regions of the state: northeast (1), east (2), central west and east (4 and 5), and southwest and south (6 and 7). The remaining region, number 3, represents the Chicago area including the suburban counties. The majority of production is located in two southern REMI regions (6 and 7) of the sub-state model. Three other regions of the REMI model, the central areas and the east, also produce coal.
Illinois REMI Regions
Illinois coal is presently mined in nineteen counties, located predominantly in the southern portion of the state. Although coal mining represents a small percentage of gross state product, for some counties in the state, coal mining represents a significant amount of their regional product and provides a principal source of employment in the areas, as indicated in Table 5. Therefore, increased precision is an important factor in this analysis.
Coal output, sold to utilities, from the southwest (region 6) and the south (region 7), each constitute 43.3 percent of total utility purchases. The remaining REMI regions (2, 4, and 5) combined represent 13.4 percent of Illinois coal sales to utilities. Table 6 presents the amount of tons at risk by county and REMI region. Focusing on county data, one notices that certain counties have a large portion of coal sales to utilities in the two riskiest categories: for example, Christian (90%), Franklin (90%), Gallatin (84%). While all southern Illinois counties are heavily reliant on the coal industry for economic growth, a county such as Gallatin, with a large amount of coal sales and 25 percent of its personal income derived from mining, would be devastated if coal sales plummeted. On the REMI regional level, region 6 and 7, both significant coal regions, have 51.5 and 67.9 percent of coal sales in the two riskiest categories.
In Table 7, the tonnages of the risk categories are converted to dollar amounts using the average price for Illinois coal. These dollar amounts represent the value of potential lost coal output in the regions of the state and it is these amounts that were used as the inputs to the REMI model. Since these inputs represent a higher level of disaggregation than the two-digit SIC mining category, the input-output portion of the model was stimulated with these data.
1989 Employment and Personal Income of Coal-Producing Counties.
County/ Total Employment Personal Income:
REMI Population╣ Total╣ Miners▓ Miners Total╣ Miners╣ ▓ Miners
(jobs) (jobs) (%) (1000s) (1000s) (%)
Fulton/2 37,183 14,661 100 0.7% $548,781 $4,398 0.8
McDonough/4 33,754 16,866 99 0.6% $438,776 $4,326 1.0
Christian/4 35,409 14,544 609 4.2% $590,752 $24,116 4.1
Logan/4 31,328 15,637 270 1.7% $511,446 $11,655 2.3
Macoupin/4 48,946 17,339 682 3.9% $748,114 $15,131 2.0
Schuyler/4 7,718 3,278 43 1.3% $105,391 $1,642 1.6
Douglas/5 19,526 8,923 167 1.9% $288,321 $3,249 1.1
Clinton/6 33,760 14,061 653 4.6% $554,875 $24,022 4.3
Perry/6 21,850 9,455 1,476 15.6% $339,865 $78,538 23.1
Randolph/6 35,430 16,999 958 5.6% $506,134 $41,336 8.2
St. Clair/6 271,191 106,952 282 0.3% $4,240,946 $14,536 0.3
Washington/6 15,328 6,248 292 4.7% $246,257 $2,354 1.0
Franklin/7 41,623 14,579 1,495 10.3% $574,418 $70,252 12.2
Gallatin/7 7,163 3,057 496 16.2% $98,925 $24,473 24.7
Jefferson/7 37,037 21,412 789 3.7% $592,368 $24,316 4.1
Saline/7 27,740 11,839 1,263 10.7% $425,068 $58,462 13.8
Wabash/7 13,638 8,476 841 9.9% $215,449 $18,217 8.5
White/7 17,283 7,899 253 3.2% $267,800 $3,137 1.2
Williamson/7 57,273 23,265 195 0.8% $840,938 $9,860 1.2
2 802,000 394,000 100 0.0 $13,196,000 $4,398 0.0
4 592,475 294,293 1,703 0.6 $9,617,000 $56,870 0.6
5 749,239 397,812 167 0.0 $12,063,000 $3,249 0.0
6 667,647 273,978 5,156 1.9 $10,923,000 $123,786 1.1
7 545,354 251,606 3,837 1.5 $7,669,000 $208,718 2.7
total 3,356,715 1,611,689 10,963 0.68 $53,468,000 $397,021 0.7
Illinois 11,640,043 6,244,289 10,693 0.2% $225,361,286 $440,973 0.2
╣Bureau of Economic Analysis, 1989. Estimated from 1987 data.
▓Illinois Department of Mines and Minerals (unpublished data).
County Coal Production, Coal Sales to Utilities, and Degree of Risk.
1989 1989 1989 Coal Sales At Risk:
County/ Total Coal Sales NO LOW MOD HIGH
REMI Region Production to Utilities RISK RISK RISK RISK
(tons) (tons) (tons) (tons) (tons) (tons)
Fulton/2 504,005 162,380 380 0 0 162,000
Christian/4 2,049,364 2,029,000 0 0 2,029,000 0
Logan/4 1,327,207 979,800 555,100 351,700 0 73,000
Macoupin/4 2,808,596 2,693,000 2,693,000 0 0 0
Schuyler/4 552,269 809,600 384,700 424,900 0 0
Douglas/5 1,045,088 218,110 0 172,810 45,300 0
Clinton/6 2,762,147 2,748,700 0 2,748,700 0 0
Perry/6 11,241,331 10,418,940 2,009,500 1,167,420 4,780,770 2,461,250
Randolph/6 6,128,923 5,978,660 300,000 2,513,540 1,091,940 2,073,180
St. Clair/6 1,276,779 1,247,470 0 780,110 0 467,360
Washington/6 1,880,500 1,880,500 0 1,278,740 601,760 0
Franklin/7 7,539,989 7,057,360 251,200 0 3,091,360 3,714,800
Gallatin/7 2,233,481 1,893,920 0 0 1,893,920 0
Jefferson/7 3,572,604 1,686,720 0 511,950 0 1,174,770
Saline/7 5,994,595 5,445,100 758,620 0 2,843,144 1,843,336
Wabash/7 3,001,455 2,882,200 1,100,000 1,652,000 0 130,200
White/7 1,751,025 1,728,550 1,580,200 0 0 148,350
Williamson/7 1,733,424 1,620,700 1,193,820 110,600 2,080 314,200
2 504,005 162,380 380 0 0 162,000
4 6,737,436 6,511,400 3,632,800 776,600 2,029,000 73,000
5 1,045,088 218,110 0 172,810 45,300 0
6 23,289,680 22,274,270 2,309,500 8,488,510 6,474,470 5,001,790
7 25,442,782 22,314,550 4,883,840 2,274,550 7,830,504 7,325,656
Illinois 57,442,782 51,480,710 10,826,520 11,712,470 16,379,274 12,562,446
Coal Sales at Risk.
1989 Coal Sales At Risk:
County/ NO LOW MODERATE HIGH
REMI Region RISK RISK RISK RISK
($) ($) ($) ($)
Fulton/2 $9,300 $0 $0 $3,986,800
Christian/4 $0 $0 $58,841,000 $0
Logan/4 $14,071,800 $8,915,600 $0 $1,850,600
Macoupin/4 $88,922,900 $0 $0 $0
Schuyler/4 $11,937,200 $13,184,600 $0 $0
Douglas/5 $0 $3,753,400 $983,900 $0
Clinton/6 $0 $88,315,700 $0 $0
Perry/6 $49,956,200 $29,022,100 $118,849,900 $61,186,700
Randolph/6 $8,127,000 $68,091,800 $29,580,700 $56,162,400
St. Clair/6 $0 $19,237,500 $0 $11,525,100
Washington/6 $0 $35,996,500 $16,939,500 $0
Franklin/7 $6,646,800 $52,816,800 $81,797,400 $98,293,600
Gallatin/7 $0 $0 $57,878,200 $0
Jefferson/7 $0 $17,222,000 $0 $39,519,300
Saline/7 $24,564,100 $0 $92,061,000 $59,687,200
Wabash/7 $35,959,000 $54,003,900 $0 $4,256,200
White/7 $38,746,500 $0 $0 $3,637,500
Williamson/7 $37,927,700 $3,513,800 $66,100 $9,982,100
Illinois $316,868,400 $394,073,800 $456,997,700 $350,087,600
2 $9,300 $0 $0 $3,986,800
4 $114,931,900 $22,100,200 $58,841,000 $1,850,600
5 $0 $3,753,400 $983,900 $0
6 $58,083,200 $240,663,600 $165,370,100 $128,874,200
7 $143,844,100 $127,556,500 $231,802,700 $215,375,900
REGIONAL ASPECTS OF COAL OUTPUT LOSSES
Two scenarios were created regarding the impact of lost coal sales on the regions of Illinois. The low case scenario represents the highest probability of lost coal sales: the high risk category. The combined sales losses of the high risk and the moderate risk would be a worse occurrence for these regions and so was considered the high case scenario. Results of this analysis indicate that between 13,000 and 31,000 Illinois jobs (0.2% to 0.5% of statewide employment) are at risk under the low case and high case scenarios as indicated in Table 8. Coal job losses in REMI region 6 and 7 are over 25 percent of total job losses in those regions, while are much smaller in the remaining three regions. For the state as a whole, coal job losses represent 16 and 21 percent of all job losses for the low case and high case scenarios, respectively. However, as mentioned earlier, for many counties in REMI regions 6 and 7, the job losses in individual counties as a percent of total county job losses would be much more significant in both the low case and high case scenarios. Mining employment losses strongly affect other types of employment in the regions. For example, 70 percent of the job losses in REMI regions 6 and 7 occur in non-mining sectors, the majority of losses originating in retail, wholesale, and services. Table 9 presents lost personal income in the REMI regions for both the low and high case scenarios. For the state as a whole, lost income in the mining industry represents 16 percent of all lost income. Lost income for the mining industry reaches 29 percent of total lost personal income in REMI region 6, while remains less significant in the other regions. Significant personal income losses therefore, also occur in non-mining sectors of the economy. The general conclusion would be that, while the job and income losses are a small percentage of total Illinois employment and personal income, the REMI regions and especially the counties of southern Illinois, would experience large employment and income losses.
1995 Employment Forecast - Low and High Case Impacts.
1995 Employment Forecast (lost jobs):
Total Low Case Impacts :High Case Impacts
REMI Employment Mining All Mining All
(jobs) (jobs) (jobs) (jobs) (jobs)
2 399,000 -34 -359 -34 -359
4 307,230 -20 -131 -649 -4,289
5 413,893 0 0 -11 -314
6 287,217 -834 -3,043 -1,905 -6,946
7 263,866 -1,655 -5,889 -3,435 -12,227
Illinois 6,613,771 -2,787 -13,279 -6,424 -30,613
A few interesting results occurred in the REMI regions when the coal output scenario losses were run. In region 2, the number of lost jobs in the durable goods manufacturing sector (-59) appeared to be much too large for the $4 million reduction in coal output. What was occurring was that, as coal output declined in the other regions of the state, the demand for earth-moving equipment (and other durable equipment used in mining), declined. Both John Deere and Caterpillar, two major producers of this type of equipment, are located in REMI region 2 and responded to a decline in demand for their products with layoffs.
1995 Personal Income Forecast - Low and High Case Impacts.
Total 1995 Personal Income Forecast (lost income)
Personal Low Case Impacts High Case Impacts
REMI Region Income Mining All Mining All
($000) ($000) ($000) ($000) ($000)
2 19,509,670 -1,267 -14,164 -1,267 -14,164
4 14,851,220 -927 -4,818 -30,418 -158,023
5 18,477,210 0 0 -235 -9,784
6 16,901,900 -40,095 -137,274 -91,542 -313,424
7 11,790,910 -47,395 -249,429 -98,400 -517,882
Illinois 353,240,400 -91,957 -560,994 -211,997 -1,293,306
Note: Data in 1989 dollars.
With regards to the east central region, REMI region 5, service industry personnel increased when the only stimulation that this region received, was negative. Region 5 gained jobs in services counter to intuitive economic theory. This phenomenon is a result of agglomeration economies. If an area's economic activity declines, it may not able to support certain services and may have "to import" certain services from adjacent regions. The large declines in economic activity in the south and southeast areas of Illinois (REMI regions 6 and 7) meant that those communities were forced to receive many services from east central Illinois (REMI region 5). The significance of these occurrences indicates the strong inter-regional and inter-industry links that are built into the model.
Subsequent research analysed these regional impacts and converted them to county impacts using the county/regional ratios for employment and income. Additionally, this study provided impetus for subsequent research which compared scrubbing versus switching, pinpointing the specific utilities which could scrub Illinois coal for equal or less than the cost of switching.
Since it was felt that the impacts of such a massive decline in coal output would be economically and politically unacceptable for the state, two policy prescriptions were developed; one regarding out-of-state utilities and another regarding two Illinois utilities that are affected by the Clean Air Act. Where it was determined that switching was not cost effective for certain out-of-state utilities, an effort was made to convince these utilities which presently burn Illinois coal and which may switch, to continue to burn Illinois coal.
In addition, the state assembly passed a bill to provide a grant to the Illinois Power Company to help pay for a new technology scrubber on one of its coal units. A similar deal was also struck with Commonwealth Edison, the largest utility in the state, whereby, in exchange for scrubbing its Illinois minemouth plant, it may now pass through its western coal transportation costs on the fuel adjustment clause, heretofore forbidden. In spite of these developments in Illinois government policy, it is more difficult to influence policy of out-of-state utilities and other state governments regarding the burning of Illinois coal. Therefore, policy to divert the switch to western coal may have limited success.
THE FUTURE OF ILLINOIS COAL
If either of the two cases described in the above analysis comes to pass, the prospect for those coal-producing counties is not favorable. The demand for electricity is expected to grow very slowly, but some utilities within the Illinois coal marketing areas are expected to add to their capacity, according to the North American Reliability Council. Illinois coal could meet some of the demand for the coal that will generate this electricity. However, it still does not come close to the expected lost coal sales exhibited in the two scenarios.
Although the near term may look bleak, there appears to be opportunities for Illinois coal as the year 2000 is approached. The promotion of coal exports, especially to Eastern Europe and the newly industrialized nations of Asia, is an avenue that the Illinois coal industry has already begun to explore. The high BTU content of the coal, its extensive reserves, and the transportation infrastructure make Illinois coal competitive in world markets.
1. Ill. Dept. of Energy & Natural Resources, Outlook for the Illinois Coal Industry: 1995-2000, ILENR/CD-91/03, Springfield, Ill., November, 1991.
2. Ill. Dept. of Energy & Natural Resources, Outlook for the Illinois Coal Industry, ILENR/CD-92/01, Springfield, Ill., March, 1992.
3. Regional Economic Models, Inc., Model Documentation, Volume 1, Amherst, Mass., May, 1991.
4. Treyz, George I., D.S. Rickman, and G. Shao, "The REMI Economic-Demographic Forecasting and Simulation Model", International Regional Science Review. forthcoming.
The author would like to thank Gary Philo of the department's Coal Demonstration Section, who provided tables and coal industry information and Michael A. Scott of the department's Strategic Planning Section, who provided computer expertise.
Web Master an article of Toomey's
August 24, 2003