Forecasting the economic, energy, and environmental impacts of national energy plans, 1990–2000

TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE 18,301-320 (1980)

Forecasting the Economic, Energy, and Environmental Impacts of National Energy Plans, 1990-2000 HYDER LAKHANI

ABSTRACT The objective of this article is to project the energy, economic, and environmental trade-offs to the year 2000 of President Carter's energy policies. It compares the trade-offs resulting from the National Energy Act of 1978 (NEA) with those from the synfuels strategy of July 1979. A hybrid model is used that consistently links the interindustry forecasting model of the University of Maryland (INFORUM) and the strategic environmental assessment system model (SEAS) with the FOSSIL 79 and ECONOMY 1 models. The study concludes that both these scenarios will a) reduce the growth rate of the economy, b) increase investment at the expense of consumption, and c) develop energy resources but d) deteriorate the quality of the environment in the Mountain States. In particular, in the synfuels scenario, compared with the base case, the study concludes that in the year 2000 energy consumption will increase from 94 to 95 quads, the GNP will decrease from $1.95 to $1.94 triliion, and in the Mountain States the particulates will increase by 67%, sulfur dioxides will increase by 10%, and nitrogen oxides will increase by 40%.

This article analyzes the implications of a "big push" in energy investment to bring about a self-sustaining, energy-independent economy. The energy programs are discussed in terms of their implications for macroeconomic variables and their environmental repercussions. The model used in the analysis, integrating INFORUM, SEAS, ECONOMY 1, and FOSSIL 79, is called E3. Energy independence can be brought about by increasing energy production and cor.servation, and this in turn requires investment. Resources have to be diverted from alternative nonenergy investments, which can slow the growth rate of the economy if productivity is less in the energy sector than in the nonenergy sector. Further, the newer energy technologies, such as synfuels, can be more damaging to the environment than the existing ones, but these damages can be mitigated by an increase in energy conservation measures. In the long run, a slower growth rate for the economy can affect adversely both the energy and environmental efforts. This is because slower growth generates smaller increases in income and hence in savings. This could lead to a smaller pool of available HYDER LAKHANI is Chief of the Economic Analysis Division of the National Commission on Air Quality. Prior to holding this position, he worked as a Senior Economist for the Mitre Corporation, Wyle Laboratories, the State of Maryland, and the Bureau of Business and Economic Research of the University of Maryland. He also taught at the University of Maryland and the University of Bombay, India. This paper represents the author's personal views. Neither the National Commission on Air Quality nor the Mitre Corporation, where this article was completed for inclusion in Department of Energy's SEAS model, is in any way responsible for the views expressed in this study. © Elsevier North Holland, Inc., 1981

0040-1625/81/0103012052.50

302

HYDER LAKHANI

funds for energy production and conservation and for environmental protection. Alternatively, the savings rate could remain the same but consumption decrease owing to the decrease in income levels. More often than not, the ultimate outcome is a reduction in both savings and consumption. We first describe the interindustry forecasting model (INFORUM) of the University of Maryland and its conceptual framework for the analysis of the impact of energy investments on the economy. The suceeding section 3 deals with extensions of the INFORUM model in the strategic environmental assessment system (SEAS) by reference to energy and environmental costs and residual generation modules. The remaining limitations in SEAS, and hence the case for linking it to other models, are then discussed. The inputs to the E 3 model are then considered for the National Energy Act of 1978 and the presidential initiative of July 1979 for investments in synfuels. The economic impact of the two national plans on the total and composition of the GNP, the proportion of energy investments and investments in air and water pollution abatement for energy and nonenergy facilities are discussed, as are the impact of energy investments on energy production and consumption by technologies and on the environment. We conclude with a consideration of the real social costs and benefits. I N F O R U M in the SEAS Model: Input-Output Tables The INFORUM is an input-output and econometric model that forecasts the U.S. economy to the year 2000 [1]. The model is driven by exogenous final demands, such as the GNP, which determines disposable income and in turn personal consumption expenditure (PCE). Any required incremental effect of final demand, such as an increase in energy investment, can be simulated by additions to the vector of final demand multiplied by an inverse matrix of coefficients. The resulting product is the change in gross output due to direct and indirect effects. Three major assumptions of INFORUM and its concomitant limitations should be noted. First, the model assumes that the production function of the industries in the table is linear and homogeneous of degree 1; that is, all returns to scale are assumed constant. In other words, to double the production, the inputs must be doubled. These constant returns are observed in the constant ratio of dollar values of input to dollar of output. In practice, industries are often subject to increasing or decreasing returns. Second, the model assumes that the coefficients are given exogenously; that is, the input mix of any industry is determined by the engineering technology so that changes in relative factor prices do not influence the coefficients. In the model used for this study these coefficients refer to 1972 technologies and prices for the base case. In practice, entrepreneurs tend to substitute cheaper inputs when their relative prices change. Unlike INFORUM, the Hudson-Jorgenson model estimates these coefficients endogenously [2]. Third, the industries in the table are assumed to be distinct and exclusive. In practice, since there are multiproduct industries, INFORUM specifies an industry category according to its major product. Extensions of I N F O R U M in the SEAS Model ENERGY MODULES

INFORUM is inadequate for detailed analysis of energy technologies and energy investments. This is because it includes only six energy industries or products: crude petroleum and natural gas (15), petroleum refining (76), fuel oil (77), coal mining (14), electric utilities (176), and natural gas utilities (178).

FORECASTINGIMPACTSOF NATIONALENERGYPLANS

303

INFORUM cannot include investments in new energy technologies because the historic data required for its econometric equations do not exist. To analyze the emerging energy technologies, two new modules were added to form SEAS. One of these is the energy system network simulator (ESNS); the other is the energy investment feedback module. The ESNS deals with demand for and supply of energy in the INFORUM sectors. The demand-supply forecasts are taken from other models, such as the MEFS [midrange energy forecasts, formerly called the project independence evaluation system (PIES)] or FOSSIL 79. These models, unlike INFORUM, include such resource constraints as recoverable reserves and demand-supply interactions at market clearing prices by use of optimization techniques. In the ESNS, the aggregated energy demand forecasts from FOSSIL 79 and ECONOMY 1 are converted into forecasts of required energy production by adjusting for energy conversion and transmission losses. The estimates of energy requirements (in quads) from the ESNS are then fed into the energy investment feedback module in the SEAS. In this module, the quads of energy production are converted into dollar amounts of required investments by using the Bechtel Corporation's energy supply planning model [3]. This model gives data on the dollar investment required to generate a given amount of energy (in quads), the number of years required for completion of energy facilities, the temporal distribution of investment, and other factors. Investments in producers' durable equipment and structures are estimated separately. They are termed D and E matrices respectively, for feedback into INFORUM. All but two energy investments--petroleum refining and transportation and the distribution of fuels, which retained unchanged in INFORUM--were fed back into the INFORUM. An advantage of analyzing investments with ESNS [4] is that three other modules, with their specific regional environmental ramifications, feed into this simulator. These are (a) the electric utilities module, (b) the industrial fuel use module (IFUM), and (c) the coal mining module. Information from these modules flows into the regional disaggregation module (REGION), which localizes industrial, commercial, and consumer activities at various disaggregation levels. In particular, the pollution quantities estimated by this module are available for counties, states, air quality control regions (AQCRs), the Bureau of Economic Analysis (BEA) regions, the standard metropolitan statistical areas (SMSAs), aggregated subareas (ASAs), and major and minor river basins. The information on fuel use reflects nine types of fuel and includes the size and age distribution of industrial boilers with particular reference to prevailing pollution standards [state implementation plans for pre-1976 boilers, new source performance standards (NSPS) for post- 1976 plants, and revised NSPS for boilers planned after 1981 ]. POLLUTIONABATEMENTCOST MODULE INFORUM does not explicitly supply information on the cost of pollution abatement in the 200 industries. These costs are implicitly included in the investment (B and C matrices) and in operating and maintenance costs (A matrix) wherever historical data on these costs are available and are also included in total investment costs. Most of these data are conspicuous by their absence and have therefore been excluded. Since pollution control expenditures are generally considered unproductive and hence inflationary investments, it is necessary to analyze their nature and extent. To do so, SEAS has developed two modules. The first, the sector disaggregation or INSIDE module, is a bridge to the second, or pollution abatement (ABATE) module. The importance of INSIDE is that it aggregates or disaggregates the 200 industries in INFORUM according to

304

HYDER LAKHANI

their pollution standards, which are based on processes and products instead of industries. For instance, the steel industry in INFORUM is decomposed into the open hearth, electric arc, basic oxygen, and other specific processes. The ABATE module provides separate estimates by industry of capital and of operation and maintenance cost per dollar value of output. The industries are grouped as energy -related or nonenergy related; this is helpful in analyzing the impact of new energy technology. The control costs are estimated for both air and water pollutants. The costs of control, by industry, are based on typical plants and types of control technology (best available control technique, best practical technique, new source performance standards, etc.). The forecasts of aggregate control costs are based on projections of the growth rates of capacities of these industries in INFORUM. The forecasts of abatement costs are grouped according to INFORUM industry classification and fed back into INFORUM. The capital costs of equipment are fed into the B matrix, the construction costs are fed into the C matrix, and the operation and maintenance costs are added to the A matrix coefficients. RESIDUALS GENERATOR (RESGEN) MODULE

The RESGEN module follows from the R E G I O N A L I Z A T I O N module. It estimates gross (prior to control) and net quantities of residuals or pollutants associated with energy and industrial outputs. The difference between gross and net coefficients is based on percentage removal efficiency of the control technology and the fraction of waste load treated. Among the types of air pollutants reported in the model are total suspended particulates (TSP), sulfur oxides (SO.~.), carbon monoxide (CO), and nitrogen oxide (NQ.). The water pollutants include the biochemical oxygen demand (BOD), the chemical oxygen demand (COD), suspended solids (SS), dissolved solids (DS), acids, oils, and greases, and thermal pollutants. These are available at the regional levels noted above and are in such units as tons per year. Limitations of S E A S and their Resolution by E :~

LIMITATIONSOF SEAS One of the major limitations of the INFORUM module in SEAS is that it lacks a price model based on interactions of demand and supply of goods and services. (The INFORUM module at the University of Maryland has, however, recently incorporated a price model [5].) In view of the absence of a price model it is impossible to forecast changes in prices. Also, there are no constraints on the availability of resources, financial, physical, or natural. The second limitation is an absence of an income determination macromodel in SEAS-INFORUM. (The Maryland-INFORUM has such a model, but this has not yet been incorporated into SEAS-INFORUM [6].) The E 3 model has attempted to overcome these limitations by linking the SEAS-INFORUM to the FOSSIL 79 and ECONOMY 1 systems. The latter embody these constraints and have market clearing prices. In particular, FOSSIL 79 includes an energy price model and ECONOMY 1 an income determination model, and these two are already linked [7]. Linking SEAS to FOSSIL 79 and E C O N O M Y 1 in E 3 helps answer more questions than could any one of these models taken separately. Moreover, these answers will be in a consistent framework for all models in terms of units of inputs and outputs of the models, parameters and variables of the models, classification of industries and sectors, and their energy, economic, and environmental trade-offs. Each model is also enriched by its

FORECASTING IMPACTS OF NATIONAL ENERGY PLANS

305

linkage to others in, for e x a m p l e , aggregation or disaggregation o f industry or sectoral classification and consistency o f assumptions (see Table 1). AN OVERVIEW OF THE FOSSIL 79 AND ECONOMY l MODELS The F O S S I L 79 m o d e l has various versions [8-10]. In the M a s e v i c e version, which has also been consistently linked to E C O N O M Y 1, we have linked it with S E A S . This version explains energy d e m a n d - - b o t h gross and for each c o m p o n e n t , including electricity, coal, oil, and natural g a s - - a s a function of G N P , w h i c h is g i v e n e x o g e n o u s l y . Its relations a m o n g fuel d e m a n d , supply, and price take into account such constraints as financing, resource availability, utilization o f capacity, interfuel substitution, and relative profitability. The s u p p l y - d e m a n d balance m o d e l simulates a d y n a m i c market clearing process. As d e m a n d for energy increases, prices and utilization o f capacity increase, so that supply increases in the next period. The increase in supply, in turn, reduces not only d e m a n d but also capacity utilization and price, and hence supply in the next period. The assumption here is that in the short run producers can adjust supply through changes in

TABLE 1 Consistency of Definitions of Investment Technologies between Fossil 79-Economy 1 and SEAS

Fossil 79 and Economy 1 Sector number

Technology

SEAS Code

Technology

Sector number

Utilities: light water reactor Coal--combined cycle Coal--fluidized bed Coal--steam Oil--steam Gas--steam Synfuels: H-coal Methanol SRC Low Btu Gas Oil~gasextraction: onshore oil offshore oil Alaskan oil onshore gas offshore gas Alaskan gas Coal mining: underground--east underground--west surface--east surface--west Oil~gasextraction: enhanced Utilities: solar thermal central photovoltaic biomass--wood Synfuels: shale--surface mined shale--in situ TOSCO II shale--modified in situ shale--underground mined

509 511 512 513 514 515 517 518 598 520 523 524 525 526 527 528 531 533 532 534 564 570 578 579,582 521 522 595 596 597

1 2 3 4 5 6 7

Light water Combined cycle coal Fluidized bed coal Emission control coal Oil utilities Gas utilities Coal liquids

LWINV CCINV FBINV NCINV OUINV OUINV CLINV

8 9

Medium-Btu gas Conventional oil

MGINV COINV

10

Conventional gas

CGINV

11

Underground coal

UCINV

12

Surface coal

SCINV

13 14 15 16 17

Enhanced oil Solar thermal Photovoltaic Biomass electricity Shale oil

EOINV STINV PVINV BMINV SHINV

306

HYDERLAKHANI

utilization of capacity. Over the long run, changes in supply are brought about by changes in production capacity, which in turn are due to changes in prices and hence profitability. ECONOMY 1, which is also a system dynamics model [7], is a logical extension of FOSSIL 79. Unlike the latter model, however, it can determine GNP endogenously. The E3 model is a hybrid model that links SEAS to FOSSIL 79 and ECONOMY 1. It takes the endogenously estimated GNP forecasts of ECONOMY 1 as input and converts them into disposable income, consumption, and so on. The nonenergy forecasts for investment are retained as in SEAS and INFORUM, whereas the energy investment forecasts are taken from FOSSIL 79 and ECONOMY 1. The forecasts of energy investments, by technology of FOSSIL and ECONOMY 1 (Table 2), can be related to energy investments in SEAS-E a (Table 3) by comparing descriptions of the technologies. The technologies that were retained unchanged from the SEAS are shown in Table 4. The analysis of the composition of energy resource consumption and production, as well as energy imports, is based on FOSSIL 79 and ECONOMY 1. The SEAS-ABATE module gives estimates of pollution control costs, and SEAS-RESGEN provides forecasts of pollutants based on industrial production estimated in SEAS INFORUM.

The Base Case and the Synfuels Scenario In order to simulate the impact on the economy and the environment of President Carter's July 1979 synfuels strategy to the year 2000, we incorporated its major investment targets in the hybrid E ~ model (Table 5). The initiative was compared with the "business as usual" scenario and the base case, which included the ongoing National Energy Plan lI. This comprises the National Energy Act of 1978 (including the Power Plant and Industrial Fuel Use Act, a tax credit for insulation and solar, an increase in prices under the Natural Gas Policy Act of 1978, and the phased decontrol of domestic crude oil in 1980-1981). In view of the importance of the base case in progressing toward energy self-sufficiency, it should be examined in its own right. Estimates were based on the National Energy Plan II "high oil price" scenario, which is comparable to assuming under the synfuels scenario an oil price of $35 per barrel (in 1975 dollars) in the year 2000. The synfuels scenario included the impact of the base case as well as the following additional measures [ 11]: • increasing investment in the production of oil shale, coal liquids, coal gases, and unconventional gas from $88 to $142 billion between 1980 and 1990; • reducing oil imports from 8.5 million barrels per day (MMB/D) in 1980 to 5 MMB/D in 1990: • increasing the importance of solar energy to 20% of total energy demand by year 2000; • increasing investment in automobile fuel efficiency by $6.5 billion and in mass transit by $I0 billion over the 1980-1990 decade; • increasing investment in residential and commercial energy conservation so as to save 0.5 MMB/D oil by 1990; • increasing investment in electric utilities for switching from oil to coal so as to save 0.75 MMB/D of oil (by 1990); and • increasing production of synfuels to 2.5 MMB/D. The Ea model estimated that the production of 2.5 MMB/D of synfuels will require an investment of $124 billion, rather than the $88 billion proposed. We therefore chose

FORECASTING IMPACTS OF NATIONAL ENERGY PLANS

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TABLE 4 SEAS Investment, by Technology, Retained in E '~ Serial number

Description

Sector number

1 2 3 4 5 6

Synfuels: lurgi lignite synthetic--western bituminous synthetic--eastern bituminous synthetic--western sum synthetic --lignite Utilities: liquid metal feeder breeder reactor

124 125 126 127 128 508

$124 billion to simulate investment over the next decade, an approximate average of the range $88-$142 billion. The $124 billion represented the investment component of the final demand vector conceptualized in the INFORUM. Investments in automobile fuel efficiency standards, mass transit, and conservation were the same as in the above. The investment required for the conversion of electric utilities from oil to coal was not estimated but instead treated indirectly by assuming that existing oil facilities will be retired at an accelerated rate and replaced with coal utilities. The impact of the incremental investment of the synfuels scenario was studied with the base scenario in order to bring out the incremental effects on the GNP, PCE, and other indicators. The nonenergy investments in President Carter's initiative, namely, in auto fuel efficiency and mass transit, were taken directly into account in the S E A S - I N F O R U M model by converting $6.5 billion from future year dollars to 1972 dollars and adding the result to the motor vehicles industry vector in the B matrix (Sector 70, comprising SIC 3711, 3713, 3714, 3715, and 3717). These amounts were "front l o a d e d , " or added to the years 1982-1987, so that they lead to an energy saving in 1990. The $10 billion investment in mass transit was divided between 20% for producers' durable equipment and 80% for the construction of new transit systems or the expansion of existing ones. This is based on the breakdown available from the 1980 fiscal year capital budget of the U.S. government. These amounts were also deflated, "front l o a d e d , " and added to the relevant vectors in the B and C matrices (PDE to sector 80 in the B matrix and structures to sector 15 in the C matrix). The other nonenergy investments already in the S E A S - I N F O R U M were taken as estimated in A l m o n ' s model at the University of Maryland.

Economic Impact GNP

We used two separate estimates of the GNP to simulate the final demand vector for I N F O R U M in SEAS. One was an exogenous estimate, which was also used to run the F O S S I L 79 model, as shown in Table 5. The other was an estimate provided endogenously by the E C O N O M Y 1 model, as shown in Table 5. These used the investments in the synfuels strategy noted above. In either the base or synfuel scenarios it can be observed that the E C O N O M Y 1 estimates of GNP ($1.95 and $1.94 trillion) are lower than the F O S S I L 79 estimates ($2.63 and $2.64 trillion). This is because the E C O N O M Y 1 model assumes a high elasticity of substitution of labor and capital for energy relative to the F O S S I L 79 model, so that the increase in energy prices leads to a greater use of capital and labor. This results in the use of inferior technologies that tend to reduce productivity

FORECASTING

IMPACTS OF NATIONAL

ENERGY

PLANS

TABLE

311

5

G N P Estimates, by Scenario of the E 3 Model (trillions of 1972 dollars). E x o g e n o u s estimate

E n d o g e n o u s estimate

u s e d in f o s s i l 79

from economy 1 Year

Base

Initiative

Base

Initiative

1975

1.26

1.26

1.18

1.18

1985

1.52

1.51

1.69

1.68

1990 2000

1.63 1.95

1.63 1.94

1.98 2.63

1.98 2.64

and GNP. The growth rates of the GNP in the ECONOMY 1 and in FOSSIL 79 are 1.7 and 3.0%, respectively. The subsequent discussion will analyze only the endogenously reported input of the GNP from the ECONOMY 1 model because it appears to reflect the realities of higher energy prices that tend to bring about greater input substitution [ 12]. Table 5 also shows that the GNP differences for the base case and the initiative scenario for various years do not significantly differ. This observation is valid for both the ECONOMY 1 results and the exogenous values used for FOSSIL 79. This is because the difference between the two scenarios is largely in terms of synfuel, solar, and nonenergy investments of less than $200 billion over 10 years. These tend to make an insignificant dent in the $2 trillion economy of the United States. In Table 6 the estimates in ECONOMY 1 are shown to be low compared to those of other forecasters, such as Almon [13], the U.S. Department of Labor [14], and Data Resource Inc. [15]. This is because we assume a strong interaction between energy and the economy, in particular a slowdown in economic growth due to the assumed increases in energy prices. (It must be recalled that we are assuming the price of crude oil to be $35 per barrel in the year 2000 in 1975 dollars.) The recent increase in real GNP of less than 2% per annum seems to lend credence to our prediction.

TABLE6 ComparisonofGNPEstimatesqbiilionsof1972dollars) E 3, i n i t i a t i v e

Bureau of

scenario,

Data

Labor

Year

A l m o n [ 13]

Economy 1

R e s o u r c e s , inc. [ 15]"

Statistics [ 14] b

1975 1976

-1270.6

1260 --

---

---

1980

1455.4

--

--

--

1985 1986 1987

-1801.1 .

1510 --

---

1511 1803

--252&

-2113 --

1988 1989 1990 2000

. 1936.3 ---

.

.

.

.

.

.

-1630 1940

a P o l i c y 3 s c e n a r i o s i m u l a t i n g d e c o n t r o l o f oil p r i c e s a n d i m p o s i n g e x c i s e t a x e s on e n e r g y s u f f i c i e n t to r e d u c e e n e r g y i n p u t in the y e a r 2 0 0 0 to 90 q u a d s Btu. b B u r e a u o f L a b o r S t a t i s t i c s , b a s e c a s e , a s s u m e s s l o w e r g r o w t h rate (at 4 . 3 for 1 9 7 7 - 1 9 8 0 , 1980--1985 a n d 3 . 2 f o r 1 9 8 5 - 1 9 9 0 ) .

3 . 6 for

312

HYDER LAKHANI

CHANGES IN THE COMPOSITIONOF THE GNP Although the base case and the synfuels scenario do not differ significantly in their impact on the aggregate GNP, relative to a $2 trillion economy, they have a considerable effect on its components. This is brought out by the results of the SEAS-INFORUM module of the E3 model shown in Table 7. For instance, the personal consumption expenditure (PCE) will decline from about 64% of GNP to 55%'in both the base case as well as the synfuels scenario. Historically, the share of PCE in the GNP has increased from 62% in 1970 to 64.4% in 1978 [16]. The decrease in the share of PCE in both scenarios suggests the belt tightening required by the relative decrease in the consumption of goods and services: without this belt tightening the real resources required for energy investment cannot be released. In both models there is an increase in gross investment over time, from 12 to 16 or 17% of the GNP. This is a welcome departure from the historical trend, a decrease from 17.6% of the GNP in 1950 to 15.2% in 1978, with a trough of 12% in 1975 [16]. This increase will be at the expense of consumption, which decreases over time, as we have noted. Exports remain constant in both the scenarios owing to the absence of input changes affecting exports, such as foreign demand or varying exchange rates. In the synfuels initiative case the decrease in imports can be largely explained by a reduction in oil imports and the slight increase in government purchases by the new energy policy. ENERGY INVESTMENTAS PROPORTIONOF TOTAL INVESTMENTS Although the predicted increase in gross private domestic investment is not significant, the proportion of energy investment increases over time relative to nonenergy investments, from 20% in 1975 to 26% in 2000 in both the cases (see Table 8). The percentage increase is higher in the initiative scenario for 1985 and 1990 because of the front-loading of the big push investments in synfuels. The implication of such an increase at the expense of nonenergy investments is capital shortages in the nonenergy sector, and hence reduced productivity, higher interest rates, and decreased growth rate of the GNP. These deflationary forces could, to a certain extent, be offset by increases in the energy

TABLE 7 Impact on the Components of the GNP: Economy 1 and SEAS Scenarios

Basea

Initiativea

Component

1975

1985

1990

2000

1975

1985

1995

2000

GNP

1208

1524

1652

1852

1208

1515

1657

1763

Personal consumptionexpense

768 (64)

905 (59)

956 (58)

1021 (55)

768 (64)

890 (59)

955 (58)

978 (55)

Gross private domestic investment

152 (12)

233 (15)

271 (16)

312 (17)

152 (12)

237 (16)

283 (17)

278 (16)

Exports

89 (7)

119 (8)

141 (9)

200 (11)

89 (7)

119 (8)

141 (9)

200 (11)

Imports

68 (6)

135 (9)

143 (9)

169 (9)

68 (6)

133 (9)

128 (8)

134 (8)

266 (22)

357 (23)

390 (24)

444 (24)

266 (22)

357 (24)

390 (24)

444 (25)

Governmentpurchases

~In billionsof 1972 dollars. Percents of GNP are given in parentheses.

FORECASTING IMPACTS OF NATIONAL ENERGY PLANS

313

TABLE 8 Proportions of Energy Investment in Gross Private Domestic Investment (GPDI): Economy 1 and SEAS Scenarios Base

Initiative

Year

GPDI"

Energy"

GPDI"

1975 1985 1995 2000

152 233 271 312

31 (20) 55 (24) 66 (24) 82 (26)

152 237 283 278

Energy" 30 64 78 72

(20) (27) (28) (26)

"In billions of 1972 dollars. Percents of GPDI are given in parentheses.

sector. In general, however, the energy sector cannot offset completely the negative effects because the new investments in synfuels, solar energy, and so on, have a long gestation period for production: During this period there is likely to be a slowdown of the economy. ENERGY INVESTMENT T h e c o m p o s i t i o n o f e n e r g y i n v e s t m e n t s in various c o n v e n t i o n a l and n o n c o n v e n t i o n a l t e c h n o l o g i e s s h o w s an interesting t r e n d d i c t a t e d by the future availability o f e n e r g y r e s o u r c e s . F r o m Table 9 it can be o b s e r v e d that i n v e s t m e n t s in c o n v e n t i o n a l t e c h n o l o g i e s , such as oil, gas, and electric utilities, s h o w a d e c l i n i n g trend in both c a s e s . O n the o t h e r h a n d , i n v e s t m e n t s in e m e r g i n g t e c h n o l o g i e s , such as c o n s e r v a t i o n and solar e n e r g y , s h o w an i n c r e a s i n g t r e n d in b o t h cases. I n v e s t m e n t s in c o n s e r v a t i o n s h o w e d an i n c r e a s e to 28% o f total e n e r g y i n v e s t m e n t s in the initiative c a s e , c o m p a r e d to only 22% in the base case.

TABLE 9 Energy Investments by Technology: Economy 1 and SEAS Scenarios Energy technology

Base"

Initiativea

1975

1985

1990

2000

1975

1985

1990

2000

306

53.2

58.7

81.8

30.6

57.6

72.9

71.0

0 (0)

2.1 (4)

5.9 (10)

18.0 (22)

0 (0)

1.6 (3)

6.3 (9)

20.2 (28)

Nuclear

5.8 (19)

6.9 (13)

8.4 (14)

12.8 (16)

5.8 (19)

7.6 (13)

9.2 (13)

12.2 (17)

Electric utilities

19.0 (62)

17.1 (32)

13.9 (24)

26.8 (33)

19.0 (62)

18.2 (32)

31.1 (43)

7.7 (11)

Synfuels

0 (0)

0 (0)

0.05 (0.1)

7.2 (9)

0 (0)

6.3 (11)

0 (0)

0.01 (0)

4.6 (15)

24.2 (45)

21.3 (36)

1.9 (2)

4.6 (15)

19.9 (34)

11.3 (15)

7.2 (10)

Coal

0.9 (3)

1.3 (2)

1.3 (2)

2.9 (4)

0.9 (3)

1.4 (2)

2.5 (3)

3.4 (5)

Solar

0.2 (0.5)

1.6 (3)

7.7 (13)

12.1 (15)

0.2 (0.5)

2.4 (4)

12.5 (17)

20.3 (29)

Total Conservation

Oil and gas

Oln 1972 billions of dollars. Percents of total given in parentheses.

314

HYDER LAKHANI TABLE 10 Proportions of Pollution Abatement Expenditures in Gross Private Domestic Investment (GPDI): Economy 1 and SEAS Scenarios

Base('

Initiative"

Year

GPDI

Ai~

Water~

TotaP

Percent of GPDI

1975 1985 1990 2000

152 233 271 312

5 6 6 4

9 7 6 3

14 13 12 7

9 6 4 2

GPDI

Ai~

Water~

Tot~ b

Percent of GPDI

152 237 283 278

4 6 6 4

8 7 6 3

12 13 12 7

8 5 4 3

"In billions of 1972 dollars. "Includes capital and operation and maintenance costs.

Similarly, there is a considerably high increase in solar-energy investments in the initiative case. INVESTMENTS IN POLLUTION ABATEMENT AS A PROPORTION OF TOTAL INVESTMENTS Since production and pollution are generally simultaneous [17], investments in production also require investments in pollution abatement and control. Table i 0 presents estimates o f air and water pollution abatement expenditures for the base and the initiative cases. These estimates appear c o n s e r v a t i v e relative to other sources. For instance, Rutledge estimated 1975 expenditures (in 1972 dollars) for air and water at $9 and $10 billion respectively [18], c o m p a r e d to $5 and $9 billion for the base case in our study. It is interesting to observe, h o w e v e r , that the percent of total pollution investment in the gross private domestic investment decreases o v e r time in our study in both cases. This may be because our e n v i r o n m e n t is b e c o m i n g cleaner o v e r time o w i n g to the already substantial investment in cleanup efforts. There thus appears to be a decreasing need for such investment in the future. Also, the investments in energy facilities postulated in this study do not allow for change in environmental regulations. The inclusion of stipulations to prohibit a significant deterioration in e n v i r o n m e n t a l quality could require additional expenditures, increasing the proportion of total investment. POLLUTION ABATEMENT INVESTMENT IN ENERGY AND NONENERGY FACILITIES Because the energy sector is expanding relative to the n o n e n e r g y sector, one should expect an increasing trend in investment for pollution control in that sector. Table 11

TABLE 11 Pollution Abatement Investment in Energy Versus Nonenergy Sectors: Economy 1 and SEAS Scenarios

Base"

Initiative"

1975

1985

1990

2000

1975

1985

1990

2000

13,237

13,013

12,133

7,241

11,119

12,966

12,116

6,935

Energy

4,403 (33)

6,332 (49)

6,294 (52)

4,323 (60)

4,363 (38)

6,288 (48)

6,281 (52)

4,228 (61)

Nonenergy

8,833 (67)

6,680 (51)

5,839 (48)

2,919 (40)

8,832 (62)

6,571 (52)

5,105 (48)

2,707 (39)

Total

"In millions of 1972 dollars. Percents of total capital are in parentheses.

FORECASTING IMPACTS OF NATIONAL ENERGY PLANS

315

shows results of the ABATE module in SEAS. It can be seen that, as expected, the relative share of investment in pollution abatement for the energy facilities increases over time in both scenarios. In fact, the pollution-abatement investment in energy facilities will exceed the corresponding investment in nonenergy facilities by the year 1990. This indicates that the energy facilities are the more environment intensive. CAPITAL EXPENDITURE VERSUS OPERATION AND MAINTENANCE COST

The ABATE module also breaks down pollution abatement and control efforts into capital expenditures and the operation and maintenance (O&M) costs of the facilities. These are classified in Table 12 for both energy and nonenergy facilities. It is interesting to observe that capital costs decline and O&M costs increase over time in both scenarios and for both energy and nonenergy facilities. As an increasing number of pollution control plants are built, fewer are needed, leading to a decline in capital expenditure. At the same time the increasing number of plants have to be operated and maintained, and hence O&M costs continue to rise. The capital expenditure on control equipment for the increasing number of energy facilities of course declines less rapidly than that for nonenergy facilities.

Energy Resource Impact As a result of the "big push" in energy investment in unconventional energy resources, as well as the changes in relative prices, conservation policies, and other inputs, there are considerable changes in the energy resource availability mix over time. These shifts are indicated in Table 13, where it can be observed that the consumption of energy increases from 72 quads in 1972 to 94 quads in 2000 in the base case and to 95 quads in the initiative scenario with the ECONOMY 1 assumption. While the difference in total energy consumption between the two scenarios is not significant, there are substantial differences in consumption by the components. For instance, oil and gas imports are projected to be completely eliminated by the year 2000 because of the increase in oil prices to $35 per barrel (in 1975 dollars). The reduction in these imports is not made up by domestic production of oil and gas (owing to unavailability of resources). Instead, it will be met by an increase in the production of coal, nuclear, hydro/geothermal, and particularly solar energy. The contribution of these four resources is considerable in the initiative scenario relative to the base case. It must be noted that solar energy contributes only about 10% of total energy consumption, instead of the 20% expected. This is despite an increase in investment in solar to the tune of 29% by 2000, indicating the long gestation period for this technology. The forecast of 95 quads appears low relative to a recent study by Resources for the Future [19], which estimates 115 quads in 2000. This higher estimate is based on the assumption of a GNP growth rate of 2.2% per year (instead of the 1.7% endogenously estimated in the ECONOMY 1-SEAS scenario), and this appears less realistic in light of the recent GNP growth rate of less than 2% per year and accelerating conservation efforts, particularly in the industrial sector, where energy consumption remained the same between 1978 and 79 but the sectoral contribution to the GNP increased by 19%. PER CAPITAENERGYCONSUMPTION The relatively slow increase in energy consumption might imply that in the year 2000 the public will have to live with such discomforts such as lower thermostats in winter and

316

HYDER LAKHANI

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©

"~

o'1

o c~ 0

0

o

.°

©

o

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.J ~D ~0

© aa

o

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0

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o

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FORECASTING IMPACTS OF NATIONAL ENERGY PLANS

317

higher settings in summer. This need not happen if population grows more slowly than the consumption of energy. If population is assumed to be 260 million in 2000 [20], the per capita consumption of energy will be 365 million Btu. This compares favorably with the 1978 per capita consumption of 358 million Btu. In short, there will be no perceptible decline in energy consumption in the future. The increase will however be slower than that in the past, largely due to energy conservation brought about by insulation and higher fuel efficiency in automobiles, for example. ENERGY EFFICIENCY RATIO

It is interesting to compare energy consumption to the dollar GNP: The lower this ratio, the higher will be the efficiency with which energy is consumed. A decrease in this ratio suggests an increase in the GNP without a proportionate increase in energy consumption, so that conservation increases. This ratio has decreased from 61 thousand Btu/($1 GNP)' in 1972 to 56.3 thousand Btu/($1 GNP) in 1978. Our study forecasts this ratio at 52.4, 48.5, and 47.9 in 1985, 1990, and 2000, respectively. Hence energy efficiency will continue to increase in the future.

Environmental Impact The environmental impact of the synfuels initiative will be an increase in air pollution in mountain states. It is this area where considerable coal and shale reserves will be excavated by surface- and deep-mining techniques, so it was assumed that synfuels processing plants will be located in these six states, namely, Montana, Wyoming, Colorado, Utah, North Dakota, and South Dakota. The extent of increase in particulates, sulfur oxides, and nitrogen oxides due to synfuels, biomass combustion, and other sources is indicated in Figure 1. A 67% increase can be observed in particulates, a 10% increase in sulfur dioxide, and a 40% increase in nitrogen oxides in the synfuels case relative to the base case. This suggests that additional environmental control measures will have to be undertaken to prevent significant deterioration of air quality in these states. Social Costs and Benefits of Energy Programs The social costs of the energy development programs appear in the slower growth rate projected for the economy in general and the considerable reduction in personal consumption expenditures in particular. The reduction in consumption will be needed in order to release resources required for investment in energy production and consumption. The social costs will also be manifested in terms of a deterioration in the ambient air quality associated with increased emissions in the western and mountain states caused by the development of surface coal mining and shale oil. These social costs should, however, be related to the social benefits of the energy program, which are energy independence and its concomitant benefits, such as increased national security, the stability of the ~ollar in foreign markets, and the spillover effects in production of goods and services of investment in energy technologies. Most of the data used in our analysis are at market value and so conceal some of the nonmarket social costs and benefits. For instance, a slowdown in the economy is indicated by a reduction in the growth rate of the GNP, but the value of avoiding damages from a deterioration in ambient air quality cannot be monetized. Similarly, the relative decrease in personal consumption expenditure has been quantified, but it is difficult, if not impossible, to quantify the benefits associated with energy independence, national security,

3!8

HYDER LAKHANI

PARTICULATES 5.0

F-

.~ Other 4.0

3.0

NITROGEN OXIDES

>

r~

2.0 .S

Biomass

Combustion 1.0

Other

SULFUR OXIDES

I ~

Other Synfuels

-- ~uels Oi 3yn0(

oJ 0d m

m~

Fig. 1. Air pollution in the mountain states (Montana, Wyoming, Utah, Colorado, North Dakota, and South Dakota).

the stability of the dollar, and the spillover effects of energy technologies. Nevertheless, the benefits are real and will be reaped in the long run; in contrast, the social costs of the programs are borne in the short run. An accurate social cost-benefit analysis of these programs should, therefore, be not only intertemporal but also intergenerational. Summary and Conclusions This article presented an overview of the SEAS model with particular reference to the INFORUM module, which is an integrated interindustry and econometric model. It also outlined extensions of INFORUM in SEAS, such as the energy system network simulation module, the energy investment module, ABATE, and RESGEN, and gave reasons for these extensions. The limitations remaining in the SEAS, and hence in its link to FOSSIL 79 and ECONOMY 1, were noted with a view overcoming them and in order to raise a number of questions best answered by SEAS. The linked model was termed the energy, economic, environmental (E3) tradeoffs model. The inputs to the Es model included two cases: (1) policies in the National Energy Act of 1978 and (2) the presidential initiative of July 1979 for proposed investments in

FORECASTING IMPACTS OF NATIONAL ENERGY PLANS

319

synfuels. These were discussed along with nonenergy investments in automobile fuel efficiency and mass transit. The implications of the two scenarios for the economy, energy development, and the environment were discussed. It was concluded that the growth rate of the economy will be slower than in previous GNP forecasts. This was attributed to the stronger interactions in E a between energy prices and the economy. The forecasts of the GNP did not differ significantly in the initiative and base case scenarios. There were, however, considerable changes in the composition of GNP. For example, there will be an increase in total investment and a decrease in consumption. There will also be an increase in energy investments as a proportion of total investments, an increase in investments in energy conservation and solar energy, and a decrease in investments in conventional sources of energy, such as oil and gas. The total investment in pollution abatement will decrease if current standards are continued. There will, however, be a shift in pollution abatement expenditures from non-energy to energy facilities. In the future, the capital costs of pollution abatement will decline, whereas operation and maintenance costs associated with pollution will increase. The energy impact was then discussed. It was concluded that energy consumption will increase from 72 quads in 1972 to 95 quads in the year 2000. This will mean a small increase in the per capita consumption of energy. There will also be improvement in the efficiency with which energy will be produced and consumed. This aspect of the scenarios was discussed in terms of an energy/GNP ratio, which showed a declining trend; this was interpreted as an increase in energy efficiency, because it implies that a dollar increase in GNP will not require a proportionate increase in energy consumption and production. Above all, there will be significant change in the energy mix, from oil and natural gas to coal, nuclear, and solar sources. Despite the increase in solar energy use, however, this source will fail to meet with the ambitious target of 20% of all energy needs by the year 2000. Analysis of the environmental impact showed that under the existing environmental standards there will be significant increases in particulates and sulfur and nitrogen oxides in the mountain states. Hence steps will have to be taken to prevent a significant deterioration of air quality in these states. Finally, the social costs and benefits of the energy programs were considered. Social costs include not only the market costs manifested in slower growth of the economy but also the nonmarket costs of deteriorating ambient air quality in the western and the mountain states. Against these social costs appear social benefits, reflected in energy independence, national security, the stability of the dollar, and spillover effects of energy technologies. The real costs are incurred in the short run, but the real benefits will be realized only in the long run.

References 1. Almon, C., Jr. (ed. ),lnterindust~ Forecasts of the American Economy Lexington Books, Lexington, 1976. 2. Hudson, E. A., and Jorgenson, D. W., The Long Term Interindustry Transactions Model: A Simulation Model for Energy and Economic Analysis, Draft report prepared for the General Services Administration's Federal Preparedness Agency, Washington, D.C., September 1978. 3. CONSAD Research Corporation, Energy Investment Feedback Module: Documentation of Methodology, Data Base and Preliminary Results, McLean, Va., 1977. 4. Wing, B. J., Users Guide: Extensions to Interindustry Forecasting Model (INFORUM), prepared for U.S. Environmental Protection Agency and U.S. Department of Energy by Control Data Corporation, 15 October 1978.

320

HYDER LAKHANI

5. Almon, C., Jr., Belzer, D., and Taylor, P., Prices in Input-Output, presented at the Scientific and Technical Exchange Program on the Application of Computers to Management, Skyland, Va., 1979 May 16-19. 6. Belzer, D. B., Income Determination in the INFORUM Model of the U.S. Economy, presented at the 7th International Conference on Input-Output Techniques, Innsbruck, Austria, 9-13 April 1979. 7. Kannan, N. P., Energy, Economic Growth and Equity in the United States Praeger, New York, 1979. 8. Masevice, A., A Review and Assessment of the Fossil 1 Supply Structures, M.S. thesis, Dartmouth College, September 1978. 9. Backus, G. A., FOSSIL 1: Documentation, prepared for the Energy Research and Development Administration, Hanover, New Hampshire, July 1977. 10. Naill, R., COAL 1: A Dynamic Model for the Analysis of United States Energy Policy, Dartmouth Systems Dynamics Group, Thayer School of Engineering, Hanover, New Hampshire, 1978. 11. Office of the White House Press Secretary, Fact Sheet on the President's Import Reduction Program, 1979 July 16. 12. Berndt, E. R., and White, C. M., Energy, Capital and Productivity, presented to the IEEE, Washington, D.C., 1979 June 6. 13. Almon, C., Jr., et al., INFORUM: Summary Tables and Matrix Listings, June 1979. 14. Saunders, N. C., The U.S. economy to 1990: Two projections for growth, Mon. Labor Rev. December, 101(12), 36-46 (1978). 15. Hudson, E. A., and Jorgenson, D. W., Energy policy and U.S. economic growth, Am. Econ. Rev. 68(2), 118-134 (1978). 16. U.S. Department of Commerce, Survey of Current Business, several issues. 17. Ayres, R. U., and Kneese, A. V., Production, consumption and externalities, Am. Econ. Rev. 59(3), 282-297 (1969). 18. Rutledge, G. L., Pollution abatement and control expenditures in constant and current dollars, 1972-77, Survey of Current Business February, 59(2) 13-20 (1979). 19. Schurr, S. H., Darmstadter, J., Perry, H., and Russell, M., Energy in America's Future: The Choices Before Us, study by the staff of the Resources for the Future, National Energy Strategies Project, Johns Hopkins University Press, Baltimore, 1979. 20. U.S. Department of Commerce, Bureau of the Census, Current Population Reports: Illustrative Projections of State Populations, by Age, Race, and Sex: 1975-2000, Series P-25, No. 796, Washington, D.C., 1979. Received 26 August 1980; revised 12 December 1980