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In addition to the basic analysis using the cost estimates summarized in Table 1, four other sensitivity analyses were run using different assumptions about the level or timing of costs. The first of these assumed that, on the average, capital investment would be 20% less than estimated, but that operating and maintenance costs would be 15% higher. This adjustment was made to reflect the impact of an increased emphasis on process changes rather than end-of-the-pipe treatment for pollution abatement. The EPA/CEQ estimates (predominantly) assume "end-of-the-pipe” treatment.
The second cost sensitivity scenario assumed that all costs were increased by 25% in order to estimate the likely macroeconomic impact if the EPA/CEQ estimates were significantly understated. The third cost sensitivity scenario involved an "evening out” of costs over the ten-year period—and a delay of some costs beyond the period—in order to determine the impact of a delay in implementing the current compliance dates. Finally, because of the sharp drop in housing starts in some years, we returned the level of housing activity to its baseline level in order to determine what the effect of this policy might be when applied in conjunction with the pollution control expenditures.
METHODOLOGY AND ASSUMPTIONS
The baseline values for the overall economic scenario are taken from the Chase Econometrics long-term macroeconomic outlook. In this forecast we predict a continuation of the recession throughout 1974 and a rise in the rate of memployment continuing into 1975. After that, the economy gradually returns to a 412% rate of unemployment in 1978 and remains at that level through 1980. This baseline projects another small business cycle from 1980 to 1983, but the unemployment rate returns to 442% by 1983. The indicated growth rate for real GNP averages 4.0% for the period 1975–1980 and 3.7% for the period 1981–1983. The rate of inflation as measured by the consumer price index averaged 6.5% from 1975 to 1980 and 5.2% from 1981 to 1983.
Other major factors of the baseline forecast include the assumption that both the Federal and State and local government budgets will remain approximately in balance over the coming decade, with an average annual surplus of $3 billion over this period. The personal savings rate will average approximately 742% for the period, representing an increase from the postwar average of 612%; this will be due primarily to a higher average rate of inflation. New car sales will increase from a low level of 9.1 million units in 1974 to 11.2 million in 1976 and then rise slowly from that point to 12.8 million units in 1983. Housing starts will rebound from a low level of 1.4 million units this year to 1.9 million units in 1976 and will remain at approximately this level for the rest of the decade, but will not surpass the figure of 2.05 million starts recorded in 1973. Shortt-erm interest rates will decline from present peak levels, but long-term interest rates will continue to rise and will average approximately 11% over the decade.
An alternative scenario, called the “full employment baseline” is not vastly different from the cyclical baseline. The EPA/CEQ provided guidelines to Chase Econometrics which stated that the real growth rate should average 4.6% per year for the 1975–80 period and 3.2% per year for the 1981-83 period. Furthermore, it was stipuated that the unemployment rate should average 5.4% in 1975 and 3.9% in both 1980 and 1983. We have maintained these conventions in solving for the baseline full employment scenario. As we move to higher rates of employment, the rate of price increase is slightly larger. Thus the consumer price index increases at a 6.7% annual rate during the forecast period, compared to a 6.0% increase in the baseline forecast. Similarly, the implicit GNP deflator rises at 6.5% instead of 5.8%, and the wholesale price index rises at 5.8% instead of 5.0%. The model has been adjusted so that real GNP rises at an average rate of 4.1% compared to 3.9% in the cyclical baseline case. Other variables are not significantly affected; the personal avings rate remains around 712% and housing starts average just under 2 million units per year, although new passenger car sales rise about 1% a year faster.
We now consider the major steps which were taken to enter the EPA pollution cost figures into the Chase Econometrics industry and macro models. These can be briefly summarized as follows:
(1) Enter the estimated investment costs for each industry into the model as an addition to the year by year demand for plant and equipment in
vestment. These adjustments have two effects: (a) they are added directly to the investment functions in the model (see (7) below), and (b) they increase the asset base on which firms must earn the normal rate of return, hence resulting in higher prices.
(2) Enter the annual operation and maintenance costs and interest costs on pollution control investments into the model as an increase in each industry's production costs.
(3) Apply "markup” factors to the increase in production costs, including capital depreciation, interest charges, and operation and maintenance, to determine the increase in prices. The markup factors, which represent the proportion of increased costs passed along as higher prices, have already been calculated on an industry by industry basis and in the Chase Econometrics industrial models. The markups in general range from 0.8 to 1.0. A markup factor of 1.0 indicates that the average firm in the industry will be able to just recover all the increased costs through product prices.
(4) Calculate the effect which these price increases will have on all industries. The previous step calculated only the direct effect of pollution controls on prices; that is, the amount that the price of steel (e.g.) rises because the steel industry invests in pollution control plant and equipment. However, we must also consider the effects which an increase in steel will have on machinery, autos, and other steel-using industries. In other words, we must measure the indirect as well as the direct effects of the price increases in each industry.
(5) Convert the price increases by final demand categories to price in. creases by aggregate demand categories. We use a reverse bridge matrix to go from the 40 categories of final demand to the aggregate demand components contained in the Chase Econometrics macro model.
(6) Translate the price increases which come from the input-output table and the bridge matrix--as given in (5) above-into actual ex post price changes by using the markup factors at the macro level. Until this has been accomplished we do not yet know what changes in final product prices will be, since the cost increases may not be fully passed along. Thus we use the markup factors at the final demand level (consumption, investment, and exports) to determine what the price rise will be hefore taking into account interactive and dynamic factors. These markup factors range from 0.8 to 1.1.
(7) Adjust for changes in fixed business investment due to pollution control expenditures. Since more investment will be needed, the constant terms in the investment functions should be raised accordingly. However, we adjust the rental cost of capital upward by the percentage of investment for pollution control because it will now take more investment to produce a given amount of output. Hence the required rate of return on investment for capacity expansion will have to increase to offset the zero financial return on the pollution control investments.
(8) Labor productivity was adjusted downward through a decrease in capital stock to reflect the fact that the additional capital expenditures for pollution control do not increase output/manhour.
(9) The index of industrial production was increased to represent the manufacture of auto emission control devices.
(10) The consumption of transportation services was increased because of higher operating and maintenance costs due to the catalytic converters and other pollution control devices.
(11) Corporate profits were adjusted downward to take into account the added costs of pollution control. The existing profit functions would show an increase in profits if prices rose and unit labor costs, raw material prices, interest rates, output, and canacity utilization all stayed at the same level.
(12) The amount of financing undertaken by the Federal government increased, reflecting higher government debt because of increased spending in the public sector, and the amount of bond financing was also increased by the
amount necessary to keep the debt/equity ratio constant. A. final round of price and output changes were then obtained by solving the complete Chase macroeconomic model, taking into account the interactive and dynamic factors.
OPERATION OF MODEL We now consider the interactive and dynamic features of the macroeconomic model. The additional plant and equipment expenditures for pollution control will
reduce the amount of investment in the private sector undertaken for other purposes. Part of this effect has already been included by raising the value of the rental cost of capital term.? However, several other factors need to be taken into account. First, an increase in nominal investment will place greater pressure on the capital markets, thus increasing interest rates and lowering other investment. Second, the increased investment demand will cause an increase in the costs of construction materials, labor, and equipment which results in some decline in constant dollar investment for a given level of output and financial variables. Third, a significant substitution exists between residential and nonresidential construction. This substitution works through changes in three variables : credit availability, the cost of construction, and the availability of labor. Since housing is more sensitive than other construction to all three of these variables, it suffers the greatest decline when other sectors of investment increase. The average elasticity of substitution between pollution control expenditures and other fixed investment is approximately 0.4, as has already been mentioned. This value can reach even larger values during periods of overfull employment and stringent monetary policy, although it does not in these simulations.
It should be mentioned that a higher rate of inflation leads to a slower rate of growth in the economy for a number of other reasons. The most important link : a rise in the rate of inflation increases the savings rate and hence reduce consumption. According to the permanent income hypothesis, the marginal propensity to consume is lower for variable incomes than it is for fixed incomes. Yet clearly inflation penalizes those on fixed incomes at the expense of those on variable incomes. During inflation the deciine in consumption by those on fixed incomes is not nearly matched by the increase in consumption by those on variable incomes —even if we assume that income changes are the same-and thus the savings rate rises. This is one of the important endogenous relationships in the macro model, and works through the income distribution and relative price terms in the consumption function. In addition there is a relative decline in durable purchases which is not balanced by the slightly higher spending on services.
The other channels by which a rise in prices lowers real output are more straightforward and require only brief commentary. First, for a given nominal money supply, higher prices must lead to a lower real money supply and hence an increase in interest rates unless there has been a specific offsetting shift in the liquidity preference function; this leads to the effects on investment which have already been discussed. Second, an increase in domestic prices for a given level of foreign prices leads to a deterioration in the net foreign balance in constant prices, although if the sum of the price elasticities of exports and imports is less than unity, the balance in nominal terms may increase. Third, a government budget which is fixed in current dollars buys fewer goods and services and generates less employment if prices increase. If the government attemps to retain its real purchasing power, it can do so only by creating additional money, which will in turn raise prices, or by borrowing additional funds, which will raise interest rates. We have chosen to assume that this latter route is operative, as indicated in our earlier discussion of constant adjustments.
All of these linkages reinforce the result that a rise in costs and prices will reduce aggregate demand and raise unemployment. As soon as this happens, however, secondary effects which act in the opposite direction begin to surface. A rise in unemployment will result in a lower level of wage increases in following years. Thus unit labor costs and prices will not rise as much for a given increase in productivity. In addition, the lower level of capacity utilization leads to lower markup factors. When these events begin to increase in importance, the rate of price increase starts to diminish. The decline in real GNP and employment, which was originally caused by higher prices, also begins to slacken. As this continues, prices and real GNP tend to return toward the level which would have occurred if the additional costs had not been added. Under a fairly wide variety of assumptions it is likely that the economy will eventually return to
Pr(r+8)(1-02-2) 3 The rental cost of capital is defined as
Pw(1-2) where: Pr=supply price of capital goods q=cost of borrowed funds ö=depreciation rate u=marginal statutory tax rate 2=depreciation factor k=investment tax credit rate Pw=wholesale price index
the level of output and employment which would have occurred in the absence of expenditures for pollution control, although prices will remain somewhat higher because of a lower level of productivity.
RESULTS OF ANALYSIS Impact on Prices
The economic effects of pollution control expenditures are found to be rather modest. By 1978 the implicit GXP deflator is only 1.9% above the baseline case, the wholesale price index is only 3.0%, and the consumer price index only 1.2% above their baselines. The biggest price effect occurs in 1976, when the GNP deflator with pollution control costs rises 0.9% more than in the baseline scenario, and in 1977, when it rises 0.6% more. The difference in all other years is much less. Similarly, the wholesale price index rises an additional 1.9% in 1976 because of pollution control expenditures. This is the largest annual increase for any of the macroeconomic price indicators.
The fact that some price increase does occur is no surprise, since it is assumed that pollution control expenditures does not increase output per unit of labor or capital. The increased aggregate demand caused by the pollution control expenditures with no compensating increase in aggregate production inevitably results in higher prices. The amount of inflation will depend upon how much “slack” there is in the economy. At "full employment”, the price increases caused by the additional demand could be very significant, while a sluggish economy will result in less increase. Even with a sluggish economy, however, there will be some price increase as firms pass on higher production costs in the form of higher prices, and as resources are competed away from other sectors to the production and installation of pollution control equipment.