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An econometric analysis of residential expenditures on energy conservation and renewable energy sources
An econometric analysis of residential expenditures on energy conservation and renewable energy sources James E. Long
Economic theory suggests that residential expenditures on energy conservation and renewable energy sources will be determined by the ability of households to purchase conservation inputs, their incentive to invest in conserving energy, the energy eficiency of existing homes and miscellaneous factors such as climate and age of the home-owner. Empirical analyses of energy-related expenditures reported on individual income tax returns contrm the importance of household income, energy price increases and climate conditions in determining energy conservation investments. Income tax credits are also ,found to have stimulated residential spending on conservation and renewable energy. Ke~‘word.s:
Energy conservation: Tax credits; Renewable energy
In response to the energy crisis in the 1970s the US government enacted the Residential Energy Conservation Tax Credit of 1978. This legislation allowed eligible taxpayers to reduce their federal income tax liability by up to 15% of the amount spent on residential energy conservation inputs such as insulation and storm windows. The act also contained a tax credit for expenditures on renewable energy sources such as solar power. The 1978 tax credit programme had the ambitious goal of insulating 90% of the US homes needing additional energy conservation improvements. Studies have indicated that improved insulation can reduce household energy consumption by as much as 30-40%. Energy conservation is an important alternative to obtaining additional sources of energy which, in the case of building new electric power generation plants, can be extremely costly to public utilities and their customers.
The author is Torchmark Professor of Economics at Auburn University, 415 W. Magnolia - Room 203, Auburn, AL 36849-5242, USA. Funding support from the Auburn Utilities Research Center is gratefully acknowledged. Final manuscript received 6 January 1993.
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Previous economic studies have revealed that expected fuel costs, weather and climate conditions, housing characteristics such as size and age of dwelling and home-owner traits such as income influence energy conservation improvement activity. However, the availability of energy tax credits did not appear to stimulate conservation activity. Instead, homeowners were receiving a tax credit for purchasing extra insulation, installing storm windows and making other conservation improvements that they would have made anyway - in response to rising energy prices, for example. Perhaps because the tax credit was perceived to be an ineffective way for the federal government to subsidize energy conservation, or because the revenue losses from the programme were unacceptable in times of rising federal deficits, the federal tax credit expired after 1985. The prevailing conclusion that energy conservation tax credits are ineffective has been supported by both survey results and econometric evidence. However, prior econometric analyses of the tax credit programme have certain limitations that may have biased their conclusions. For instance, energy conservation activity has generally been measured by a qualitative variable indicating whether or not a particular conservation action (such as installing storm windows)
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Residential had been taken. These prior studies did not analyse the actual amounts spent by home-owners on energy conservation. Furthermore, the studies were often based on relatively small numbers of home-owners who reported energy conservation activity. This study will extend the existing research on residential energy conservation behaviour by analysing expenditures by home-owners on various home energy-reducing features. In other words, this study investigates the amount of energy conservation activity rather than its mere presence. Furthermore, the data used in the study are detailed enough to allow comparisons among different energy conservation inputs (eg insulation versus storm windows). In the next section of the study findings of prior research in this area are briefly summarized. The second section discusses the data used in the present study and presents a general overview of home-owners’ energy conservation expenditures. An econometric model of the determinants of energy-reducing investment is specified and estimated in the following section. The final section of the study contains a summary of the empirical results and discusses their implications for public utility policies in the areas of energy conservation and customer behaviour.
Previous research A review of the major studies of household energy conservation activity indicates the likely influence on such activity of three different sets of factors: (i) (ii) (iii)
tax credit or subsidy schemes; economic variables such as home-owner level and energy prices; and characteristics of the housing unit occupants.
income and
its
The belief that specific tax credits or subsidies do not induce energy conservation activity is held by most researchers in this area. Pitts and Wittenbach [4] found that many home-owners who had conservation improvements installed by local contractors did not claim federal tax credits even though they were eligible to do so. No home-owner surveyed reported that no energy conservation measures would have been undertaken if there had been no tax credit. Carpenter and Chester Cl] report that only 1% of western US home-owners who claimed an energy conservation tax credit said they ‘definitely would not’ have made a conservation improvement if no credit was available. The majority of households surveyed by the Energy Information Administration [2] indicated that they would have made the same energy conservation improvement had no tax credit existed. Walsh [S] rejected the survey approach to
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determining the role of tax credits in favour of statistically analysing the factors that are systematically associated with home improvements to reduce energy use. A federal (or state) tax credit reduces the net cost or price of energy conservation activity to the home-owner (taxpayer) and, if effective, may be expected to stimulate conservation behaviour. However, in every estimated equation Walsh found that the net price variable was either statistically insignificant or carried the wrong sign. None of his empirical results supported the hypothesis that tax credits prompt home-owners to undertake conservation improvements. Although tax credits appear to be unrelated to residential energy conservation, other economic factors have been found to influence home-owners’ behaviour in this area. Pitts and Wittenbach [4] report that owners respond to rising energy costs by making conservation improvements to their homes. Homeowners who make conservation improvements tend to be better educated, have higher incomes and live in larger houses than home-owners not claiming energy conservation tax credits. These survey-based conclusions are substantiated by Walsh’s [.5] econometric analyses. The probability that homeowners make a conservation improvement is positively related to household income, house size, and expected future power and fuel prices. These results are not surprising. The higher the prices of heating and cooling inputs, the larger the fuel cost savings generated by additional insulation, storm windows, etc. And higher income households are better able than lower income families to purchase energy conservation improvements. Walsh’s study also revealed that energy conservation activity is affected by certain characteristics of the housing unit and its occupants. Conservation improvements are less likely to be made by elderly home-owners and by persons renting their present residence. This implies that renters and older persons expect a relatively lower rate of return on energy conservation improvements, probably due to a shorter tenure (‘pay-back’ period) in their dwellings. Other things being constant, the older the housing unit, the more likely that energy conservation improvement is undertaken, which may reflect greater energy inefficiency in older homes because of decayed insulation and weather seals. Finally, Walsh observed that home-owners residing in warmer climates are statistically less likely to invest in energy conservation than are families living in colder states. The studies mentioned above differ substantially in methodology as well as the sizes of the samples on which their conclusions are based. For example, Pitts and Wittenbach’s [4] sample contained only 146
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Residential e.upenditures on energy: J. E. Long households, whereas Walsh examined 2911 households, of which 44% had made some energy conservation improvement. All studies can be described as investigating the decision to make an energy conservation improvement, rather than the amount of improvement undertaken. However, there are many forms of residential energy conservation improvement, and home-owners can vary the amount invested in each improvement activity. Nonetheless, prior studies of energy conservation using the ‘improvement’/‘no improvement’ format can provide direction for related research and can serve as benchmarks for evaluating conclusions derived from alternative analyses of residential energy conservation.
Energy conservation information provided on individual income tax returns Home-owners and other persons eligible for the federal energy tax credits available during 1978-85 were required to file Form 5695 (residential energy credit) along with their individual income tax return in order to receive credit against personal tax liability. Form 5695 asked for information on total energy conservation expenditures, which received a maximum tax credit of US$300, as well as renewable energy source costs, which were subject to a maximum credit of US$4000. In addition, the exact amount of expenditures on specific energy conservation inputs (eg insulation, storm windows, caulking) and renewable energy sources (eg solar power) had to be listed on the energy credit form. National estimates of energy conservation and renewable energy source investments in the residential sector in 1981 can be derived from the Internal Revenue Service’s 1981 Individual Tux Model File, a random sample of personal tax returns filed by Americans in 1981. Table 1 reveals that 3 741935 personal tax returns reported energy conservation expenditures in 198 1. In aggregate over US$2.9 billion ( 109) was spent by persons and families to make their residences more energy efficient. Since not every taxpayer who made conservation expenditures can be assumed to have filed Form 5695, and some expenditures could have been made by individuals who did not file a federal tax return, these estimates are lower bounds for residential energy conservation activity in 1981. The US$718 million expenditures on renewable energy sources is subject to the same qualification. Only 224758 tax returns reported a renewable energy source investment, but the average expenditure by these households (nearly US$3200) was more than four times as large as the typical energy conservation investment of US$779. One way to put the amount of expenditures on
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Table 1. Energy conservation and renewable energy investments by the residential sector, 1981.”
Type of investment activity
Number of residences
Energy conservation Total 3741935 INS 2 180673 SWD 2041 183 cw 958 906 OCP 622 389 Renewable Total SE GE WE
Aggregate expenditure (US% thousand)
Average investment per residence (US%)
2915477 1115872 1431669 62 168 305 768
779 512 701 65 491
717720 678 732 21930 17057
3 193 3914 4613 1 530
energy 224 758 212 533 4 754 11145
‘INS insulation: SWD - storm (or thermal) window or doors; CW - caulking or weatherstripping; OCP - other conservation products, consisting of (a) a replacement burner for an existing furnace that reduces fuel use, (b) a device for modifying flue openings to make a heating system more efficient, (c) an electrical or mechanical furnace ignition system that replaces a gas pilot light, (d) a thermostat with an automatic setback and (e) a meter that shows the cost of energy used: SE - solar energy; GE - geothermal energy; WE - wind energy. Source: Internal Revenue Service, 1981 Individual Tax Model File.
energy conservation and renewable energy into perspective is to compare them with outlays for energy used in the household sector. Personal consumption expenditures in 1981 for electricity, natural gas, fuel oil and coal, the major types of energy used in residences, were US$86.5 billion.’ Therefore, household spending on efforts to reduce conventional energy consumption was just over 4% of the outlays for energy actually used in the residential sector. Table 1 also indicates the popularity of various specific types of energy conservation products and renewable energy sources. Expenditures for insulation and storm windows or doors were reported on over two million tax returns in 1981. The average expenditure was relatively higher for thermal products (US$701) than for insulation (US$512), but slightly more taxpayers added insulation than installed new windows or doors. Caulking and weatherstripping was the next most popular energy conservation investment, but the average expense of US$65 appears trivial compared with that made on ‘major’ improvements to conserve residential energy. About one out of six persons claiming the federal energy tax credit added some other conservation product to their residence, at an average cost (US$49 1) nearly equal to the typical outlay on insulation. Individuals were not restricted
‘Expenditure data are reported in US Department Survey of Currenr Business,July 1982.
ENERGY
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of Commerce,
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Residential
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Table 2. Average energy conservation and renewable energy expenditure reported on Form 5695 according to taxpayer income level, 1981. Adjusted gross income (US% thousand)
All energy conservation (USV
INS (US%)
SWD (US%)
$S)
OCP (US%)
All renewable energy (US%)
O-10 IO-25 25--50 50-10 100-150 150-200 200 +
696 126 769 945 1291 1361 1529
473 499 492 596 881 953 1257
619 638 683 965 1234 1671 1 526
13 57 54 135 254 226 475
923 454 466 498 921 447 1088
1528 2 302 3 492 3941 4 658 4815 6 892
“Symbols as in Table 1. Sourer: Internal Revenue
Service,
I%‘/ Indiiridual TU.Y Model Fik.
to just one type of energy conservation improvement, but the 15% tax credit applied to only the first US$2000 of conservation expenditures. The data in Table 1 imply that many residences received more than one conservation improvement in 1981. Table 1 clearly indicates that most renewable energy source investments involved the use of solar power. Less than 5% of the tax returns reporting renewable energy source investments, and no more than 3% of the total expenditures for such investments, involved geothermal or wind sources of residential energy. Not surprisingly, the energy source which appeared most costly - geothermal ~ was relied on least frequently by home-owners seeking an alternative to conventional priced residential energy sources. Evidence of how total energy conservation expenses and its sub-component outlays vary among households with different income levels is presented in Table 2. Conservation expenses in aggregate exhibit a distinctly positive relationship with adjusted gross income, a common measure of household purchasing power. For example, taxpayers with income between US$lOOOO and USS25 000 in 1981 reported average energy conservation investments on Form 5695 of $726, whereas households in the US$lOOOOO-$150000 range spent nearly $1300. An examination of the specific conservation improvements shows that the income expenditure association is most pronounced in the case of storm windows and doors, followed by insulation. In contrast, residential expenditures on caulking or weatherstripping and other conservation products do not consistently increase as income rises. Because so few tax returns reported investments in geothermal and wind energy, renewable energy source components are not broken down by income level. Combined expenditure on renewable energy sources (primarily solar power) vary markedly with income, ‘however, Average expenditures in the highest income grouping (USS6892) are more than four times the
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amount, of renewable energy costs incurred by households in the lowest income category (USrSl528).
Identifying the determinants of residential enegy conservation expenditures The amount spent by households on energy conservation and renewable energy sources is seen to vary considerably among households and among the different forms of conservation improvements. In this section of the report an econometric model of the determinants of residential energy conservation and renewable energy expenditures is specified and estimated with individual tax returns which included Form 5695 (residential energy credit). Based on previous studies of residential energy conservation, the explanatory variables fall into these categories: economic factors, household characteristics and climate conditions. The economic factors hypothesized to influence residential energy conservation expenditures are household income, the trend in household energy prices and federal and state tax credits for conservation improvements. Household income (INCOME) is measured by the adjusted gross income reported by the taxpayer. Energy price changes (PRICECHG) are approximated by the annual percentage increase over the period 1978-81 in average residential electricity rates (US$ per 1000 kWh) in the taxpayer’s state of residence.’ The federal tax credit variable (FEDCREDIT) is defined as the maximum federal tax savings, taking into account prior-year conservation costs and the portion of conservation expenditures made from non-taxable government grants and subsidized financing. The existence of state subsidies ‘Electric power rates were computed from data reported in US Department of Energy, Energy Information Administration, Typical Electric Bills Junuary I, 1982. October 1982, and Typical Eleciric Bills - January I, 1978, August 1978.
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Residential
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rable 3. Regression analyses of residential energy conservation and renewable energy source investment (t-statistics in parentheses).
Explanatory fariable
Dependent variable: expenditures on All‘energy conservation INS (I) (2)
SWD (3)
All renewable energy sources
OCP (5)
(6)
‘NCOME US$ thousand)
5.55 (8.02)
3.76 (5.57)
6.79 (6.84)
1.58 (5.99)
1.48 (1.36)
17.71 (3.04)
PRICECHG
11.97 (3.75)
5.11 (1.69)
8.16 (1.86)
0.55 (0.55)
1.93 (1.61)
152.92 (3.89)
FEDCREDIT
0.92 (4.33)
0.28 (1.92)
0.27 (1.22)
0.07 (1.60)
0.50 (2.17)
0.91 (3.43)
STATESUB
25.14 (0.64)
111.24 (3.06)
112.06 (1.89)
PERSONS
- 15.58 (-1.42)
MARRIED
-8.42 (-0.20)
ELDERLY HEA TING DA YS (hundreds)
112.50 (2.49) (-0.91) (-1.14)
- 26.40 (-2.58) 65.56 (1.59) 195.74 (4.41)
-4.94 (-0.32)
-61.93 (-0.80)
1462.24 (4.34)
- 14.64 (-0.99)
-6.20 (-1.71)
- 26.76 (-1.41)
256.83 (2.12)
~ 138.68 (-2.36)
-5.25 (-0.33)
119.91 (1.86)
-2.69 (-3.68)
-0.79 (-0.70)
Constant
255.80 (2.64)
355.39 (4.38)
475.8 (4.06)
R2
0.3994
0.3598
0.3534
5871
3359
3099
Source: Author’s estimates based weighted regression analyses.
on sample
of tax returns
from the 1981 Individual
for home conservation is indicated by a dummy variable (STA TESUB) identifying states which allow tax credits or deductions for conservation improvements.3 Household characteristics include family size, measured by the number of persons (PERSONS) in the household besides the primary taxpayer, and dummy variables identifying taxpayers that are married (MARRIED) or 6.5 or older (ELDERLY). Climate conditions are measured by the annual number of heating degree-days (HEATING DA YS) in the taxpayer’s state of residence.4 The 1981 Tax Model File contained 8727 federal income tax returns reporting energy conservation and renewable energy investments. In order to identify the taxpayer’s state of residence it was necessary to exclude tax returns having adjusted gross incomes in excess of $200000 in 1981 (for confidentiality reasons, identifying variables such as location are deleted from 3Walsh [S] reported that Arizona, California, Colorado, Montana and Oregon allowed income tax credits, whereas Arkanas, Idaho and Indiana permitted tax deductions for energy conservation expenditures. ‘Tlimate data are reported in US Department of Commerce, National Oceanic and Atmospheric Administration, Monthly State, Regional. and Nuiional Healing Degree Days Weighted by Popularion: July 1980-Ocroher 1981, January 1982.
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81.49 (3.97) -0.34 (-1.20) 26.17 (0.94) 0.1969 1242
19.04 (0.26)
90.67 (0.18)
-68.39 (-0.92)
31.67 (0.06)
3.01 (2.07)
25.88 (3.89)
88.36 (0.63)
- 5365.88 (-396)
0.3771
0.4975
940
608
Tax Model File. Estimated
coefficients
are based
on
all such high-income tax returns). Forms 5695 filed by taxpayers residing in Alaska and Hawaii were also omitted from study because of the extreme weather climate in these areas. Finally, the empirical study was restricted to taxpayers having positive income in 198 1. A sample of 6346 households remained after these conditions were satisfied. These observations, after accounting for the sampling proportions employed by the IRS in assembling the Tax Model File, were responsible for over 99% of all energy conservation expenditures in 1981 and 95% of total renewable energy source investment. Therefore, the sample selection criteria employed in this study are unlikely to bias the empirical estimates of the determinants of energy conservation and renewable energy expenditures. The estimated determinants of residential energy conservation and renewable energy expenditures are presented in Table 3. Equations (1) and (6) are for total energy conservation and total renewable energy source investments respectively. Expenditures in both areas are positively and statistically related to the income level of taxpayers filing Form 5695. The INCOME coefficients imply that taxpayers with $60000 of income in 1981 spent US$222 (40 x 5.55) more on home energy conservation than households having
ENERGY ECONOMICS
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Kesidentiul income of US$20 000; the same income differential was associated with an extra US$708 of renewable energy investment. Energy (electricity) price changes are also found to be statistically related to conservation and renewable energy expenditures. If energy price inflation rises from 5 to 10% per year, household energy conservation outlays are estimated to increase by about US$60 annually. In elasticity terms, each percentage point rise in the cost of energy induces a 0.21 percentage point increase in conservation investments. The response of renewable energy investments to rising prices of conventional residential power sources is much greater - as reflected by an elasticity parameter of 0.63. Other factors being the same, residential spending on renewable energy sources would rise by about US$765 if electric power charges increased by an additional 5% annually. The estimated coefficient of the variable FEDCREDITis positive and highly significant in both Equations (1) and (6). Among taxpayers who made energy conservation or renewable energy investments in 198 1, those residences eligible for larger tax credits tended to spend more (at a rate of about 9Oc per each credit dollar) than taxpayers who could not receive as large a tax saving from the federal government. State government subsidies were estimated to influence renewable energy source investments only. On average, taxpayers in Arizona, California or other subsidy states who reported renewable energy costs on Form 5695 invested about US$lSOO more than comparable taxpayers in non-subsidy states. Households which installed renewable energygenerating features in 1981 tended to spend more on these products when family size was large; the reverse was observed in the case of energy conservation improvements. Neither aggregate conservation nor renewable energy expenditures were statistically different between married couple households and other family types. However, households occupied by elderly taxpayers received about US$I 13 of additional energy conservation improvements in 198 1 compared with non-elderly residences. The sign and significance of the ELDERLY coefficient in Equation (1) probably reflects the fact that the elderly typically reside in older, less energy-efficient, houses than other taxpayers. The age of the taxpayer filing Form 5695 is not statistically related to renewable energy source investment. The last variable in the regression model, HEATING DAYS, is statistically significant in Equation (6) but not Equation (1). Other factors held constant, expenditures on renewable energy (solar power, primarily) increase with the residential heating load. The HEATING DAYS coefficient implies that federal energy credit forms filed in 1981 by taxpayers living in a ‘cold’ state such as Minnesota (which had
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1993
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on energy: J. E. Long
8076 annual heating degree days) reported about US$l300 more renewable energy costs than households residing in warmer states such as Alabama or Georgia (having 3075 and 3031 heating degree days). An analysis of total energy conservation expenditures may conceal potential differences between the determinants of specific conservation inputs. Therefore, separate estimates for insulation, storm windows and doors, caulking and weatherstripping and other conservation expenses are reported in Equations (2)-(5). Several important differences in the variables associated with each conservation product are apparent. Increases in income lead to larger expenditures on INS, SWD and CW, but there is no statistically significant relationship between income and other conservation costs. Households experiencing large increases in residential energy prices tend to spend more on INS, SWD and OCP but not CW. All types of energy conservation expenditures except those for SWD are positively related to the federal tax credit, whereas state subsidy plans appear to induce greater outlays on INS and SWD alone. The variables measuring family size and marital status do not perform consistently in the separate equations. For example, married couples are estimated to spend US$66 more than other household types on INS, but US$139 less on SWD. The ELDERLY coefficients imply that taxpayers aged 65 and over report relatively larger expenditures on the most common conservation inputs (eg INS) but not items such as replacement burners, furnace ignition systems or new thermostats to limit energy usage. The final conclusion from Table 3 involves the influence of climate on residential energy conservation expenditures. The coefficient of HEATING DAYS is statistically significant in regressions (2) and (5), but with opposite signs. The lower the heating load in a state, ie the warmer its climate. the larger the expenditures on home insulation for walls and attic spaces. In contrast, taxpayers who spend the most on other conservation products, such as devices to improve the efficiency of residential furnaces, tend to be persons who live in colder states. As noted previously, prior studies of energy conservation in the residential sector have examined the decision of home-owners to make conservation improvements, rather than their decision of how much to invest in energy-saving improvements. Consequently, the results in Table 3 are not directly comparable to those of other studies. However, these regression estimates are consistent with economic theory and they appear reasonable. Higher-income families can afford to make larger conservation investments than less affluent families, and the conservation expenditure data are consistent with this
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J. IL Long
fact. A time trend of rising energy prices, and the anticipation of future price inflation, appears to induce households to increase spending on items and equipment which are capable of reducing the amount of power which must be purchased from market suppliers. Families are found to spend more on energy conservation and renewable energy when the private cost of these investments is subsidized by government tax policies. Finally, the weather conditions facing home-owners have a common-sense effect on the amount and type ofenergy conservation expenditure.
Implications for household utility suppliers In the past many utilities have offered their residential customers financial incentives to purchase energyefficient home appliances and install retrofit measures in their residences. Successful energy conservation programmes in the residential sector can benefit electric utilities in particular by deferring the need for additional, and increasingly costly, electricity generation facilities. However, utilities do incur costs in providing subsidies for residential energy conservation. The net benefit to utilities from energy conservation is reduced if households would have purchased more efficient furnaces, or refitted their home with additional insulation or storm windows, even if utility-provided financial incentives had not existed. In this case, the financial incentives constitute pure windfalls from utilities and their stockholders to customers. The ability of subsidy schemes to stimulate energy conservation in the residential sector has been examined with reference to government tax credits for conservation and housing retrofit expenditures. Most studies have concluded that such tax credits do not stimulate energy conservation improvements. Possibly taxpayers have been uninformed about the tax credit, have been unwilling to complete the required paperwork to claim the tax savings, or have found the maximum subsidy amount insufficiently large. In contrast to these prior studies, the results of the present study suggest that households will increase conservation activity when the private costs are reduced because of public subsidies. To the extent that privately administered subsidies (eg low-interest loans or rebates to electric utility customers) can be more
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publicized and simplified than government tax credits, there is additional reason to expect that utilities’ investments in residential energy conservation subsidies will not be wasted. A significant finding of the present as well as prior research relates to the influence of energy price movements on residential energy conservation activity. There is strong evidence that households increase conservation investment in response to the economic stimulus of rising electricity (and other household power) rates. Utility revenue forecasts that ignore customer conservation behaviour will be of questionable accuracy. In general a rate increase will not lead to a proportional rise in electric utility revenues, for example, because residential consumers will try to reduce power consumption. With sufficient time households will supplement the ‘simple’ conservation steps (eg adjusting thermostats, turning off lights) with conservation investments that permit comfortable room temperatures to be maintained with lower levels of power consumption. This household behaviour is part of the explanation for why the price elasticity of demand for residential power tends to be greater in the long run than the short run. Unless the effect of energy conservation activities on power consumption in the residential sector can be satisfactorily included in utility companies’ forecasting strategy, long-range projections of future generating needs or revenues may be seriously biased.
References E. H. Carpenter and S. T. Chester, ‘Are federal energy tax credits effective? A western United States survey’, The Energy Journal. Vol 5. No 2, 1984, pp 139-149. Energy Information Administration, An Economic Evaluation qf Energy Conservation and Renewable Energy Tar Credits, US Department of Energy, Washington, DC, 1985. Eric Hirst, ‘Energy and economic effects of utility financial incentive programs: the BPA residential weatherization program’, The Energy Journal, Vol8, No 2, 1987, pp 97-110. R. E. Pitts and J. L. Wittenbach, ‘Tax credits as a means of influencing consumer behavior’, Journal of Consumer Research, Vol 8, 1981, pp 335-338. ‘Energy tax credits and housing M. J. Walsh, improvement’, Energy Economics, Vol 11, 1989, pp 275-284.
ENERGY
ECONOMICS
October
1991
Economic theory suggests that residential expenditures on energy conservation and renewable energy sources will be determined by the ability of households to purchase conservation inputs, their incentive to invest in conserving energy, the energy eficiency of existing homes and miscellaneous factors such as climate and age of the home-owner. Empirical analyses of energy-related expenditures reported on individual income tax returns contrm the importance of household income, energy price increases and climate conditions in determining energy conservation investments. Income tax credits are also ,found to have stimulated residential spending on conservation and renewable energy. Ke~‘word.s:
Energy conservation: Tax credits; Renewable energy
In response to the energy crisis in the 1970s the US government enacted the Residential Energy Conservation Tax Credit of 1978. This legislation allowed eligible taxpayers to reduce their federal income tax liability by up to 15% of the amount spent on residential energy conservation inputs such as insulation and storm windows. The act also contained a tax credit for expenditures on renewable energy sources such as solar power. The 1978 tax credit programme had the ambitious goal of insulating 90% of the US homes needing additional energy conservation improvements. Studies have indicated that improved insulation can reduce household energy consumption by as much as 30-40%. Energy conservation is an important alternative to obtaining additional sources of energy which, in the case of building new electric power generation plants, can be extremely costly to public utilities and their customers.
The author is Torchmark Professor of Economics at Auburn University, 415 W. Magnolia - Room 203, Auburn, AL 36849-5242, USA. Funding support from the Auburn Utilities Research Center is gratefully acknowledged. Final manuscript received 6 January 1993.
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Previous economic studies have revealed that expected fuel costs, weather and climate conditions, housing characteristics such as size and age of dwelling and home-owner traits such as income influence energy conservation improvement activity. However, the availability of energy tax credits did not appear to stimulate conservation activity. Instead, homeowners were receiving a tax credit for purchasing extra insulation, installing storm windows and making other conservation improvements that they would have made anyway - in response to rising energy prices, for example. Perhaps because the tax credit was perceived to be an ineffective way for the federal government to subsidize energy conservation, or because the revenue losses from the programme were unacceptable in times of rising federal deficits, the federal tax credit expired after 1985. The prevailing conclusion that energy conservation tax credits are ineffective has been supported by both survey results and econometric evidence. However, prior econometric analyses of the tax credit programme have certain limitations that may have biased their conclusions. For instance, energy conservation activity has generally been measured by a qualitative variable indicating whether or not a particular conservation action (such as installing storm windows)
0140/9883/93/040232-07
c
1993 Butterworth-Heinemann
Ltd
Residential had been taken. These prior studies did not analyse the actual amounts spent by home-owners on energy conservation. Furthermore, the studies were often based on relatively small numbers of home-owners who reported energy conservation activity. This study will extend the existing research on residential energy conservation behaviour by analysing expenditures by home-owners on various home energy-reducing features. In other words, this study investigates the amount of energy conservation activity rather than its mere presence. Furthermore, the data used in the study are detailed enough to allow comparisons among different energy conservation inputs (eg insulation versus storm windows). In the next section of the study findings of prior research in this area are briefly summarized. The second section discusses the data used in the present study and presents a general overview of home-owners’ energy conservation expenditures. An econometric model of the determinants of energy-reducing investment is specified and estimated in the following section. The final section of the study contains a summary of the empirical results and discusses their implications for public utility policies in the areas of energy conservation and customer behaviour.
Previous research A review of the major studies of household energy conservation activity indicates the likely influence on such activity of three different sets of factors: (i) (ii) (iii)
tax credit or subsidy schemes; economic variables such as home-owner level and energy prices; and characteristics of the housing unit occupants.
income and
its
The belief that specific tax credits or subsidies do not induce energy conservation activity is held by most researchers in this area. Pitts and Wittenbach [4] found that many home-owners who had conservation improvements installed by local contractors did not claim federal tax credits even though they were eligible to do so. No home-owner surveyed reported that no energy conservation measures would have been undertaken if there had been no tax credit. Carpenter and Chester Cl] report that only 1% of western US home-owners who claimed an energy conservation tax credit said they ‘definitely would not’ have made a conservation improvement if no credit was available. The majority of households surveyed by the Energy Information Administration [2] indicated that they would have made the same energy conservation improvement had no tax credit existed. Walsh [S] rejected the survey approach to
ENERGY
ECONOMICS
October
1993
expenditures
on energy: J. E. Long
determining the role of tax credits in favour of statistically analysing the factors that are systematically associated with home improvements to reduce energy use. A federal (or state) tax credit reduces the net cost or price of energy conservation activity to the home-owner (taxpayer) and, if effective, may be expected to stimulate conservation behaviour. However, in every estimated equation Walsh found that the net price variable was either statistically insignificant or carried the wrong sign. None of his empirical results supported the hypothesis that tax credits prompt home-owners to undertake conservation improvements. Although tax credits appear to be unrelated to residential energy conservation, other economic factors have been found to influence home-owners’ behaviour in this area. Pitts and Wittenbach [4] report that owners respond to rising energy costs by making conservation improvements to their homes. Homeowners who make conservation improvements tend to be better educated, have higher incomes and live in larger houses than home-owners not claiming energy conservation tax credits. These survey-based conclusions are substantiated by Walsh’s [.5] econometric analyses. The probability that homeowners make a conservation improvement is positively related to household income, house size, and expected future power and fuel prices. These results are not surprising. The higher the prices of heating and cooling inputs, the larger the fuel cost savings generated by additional insulation, storm windows, etc. And higher income households are better able than lower income families to purchase energy conservation improvements. Walsh’s study also revealed that energy conservation activity is affected by certain characteristics of the housing unit and its occupants. Conservation improvements are less likely to be made by elderly home-owners and by persons renting their present residence. This implies that renters and older persons expect a relatively lower rate of return on energy conservation improvements, probably due to a shorter tenure (‘pay-back’ period) in their dwellings. Other things being constant, the older the housing unit, the more likely that energy conservation improvement is undertaken, which may reflect greater energy inefficiency in older homes because of decayed insulation and weather seals. Finally, Walsh observed that home-owners residing in warmer climates are statistically less likely to invest in energy conservation than are families living in colder states. The studies mentioned above differ substantially in methodology as well as the sizes of the samples on which their conclusions are based. For example, Pitts and Wittenbach’s [4] sample contained only 146
233
Residential e.upenditures on energy: J. E. Long households, whereas Walsh examined 2911 households, of which 44% had made some energy conservation improvement. All studies can be described as investigating the decision to make an energy conservation improvement, rather than the amount of improvement undertaken. However, there are many forms of residential energy conservation improvement, and home-owners can vary the amount invested in each improvement activity. Nonetheless, prior studies of energy conservation using the ‘improvement’/‘no improvement’ format can provide direction for related research and can serve as benchmarks for evaluating conclusions derived from alternative analyses of residential energy conservation.
Energy conservation information provided on individual income tax returns Home-owners and other persons eligible for the federal energy tax credits available during 1978-85 were required to file Form 5695 (residential energy credit) along with their individual income tax return in order to receive credit against personal tax liability. Form 5695 asked for information on total energy conservation expenditures, which received a maximum tax credit of US$300, as well as renewable energy source costs, which were subject to a maximum credit of US$4000. In addition, the exact amount of expenditures on specific energy conservation inputs (eg insulation, storm windows, caulking) and renewable energy sources (eg solar power) had to be listed on the energy credit form. National estimates of energy conservation and renewable energy source investments in the residential sector in 1981 can be derived from the Internal Revenue Service’s 1981 Individual Tux Model File, a random sample of personal tax returns filed by Americans in 1981. Table 1 reveals that 3 741935 personal tax returns reported energy conservation expenditures in 198 1. In aggregate over US$2.9 billion ( 109) was spent by persons and families to make their residences more energy efficient. Since not every taxpayer who made conservation expenditures can be assumed to have filed Form 5695, and some expenditures could have been made by individuals who did not file a federal tax return, these estimates are lower bounds for residential energy conservation activity in 1981. The US$718 million expenditures on renewable energy sources is subject to the same qualification. Only 224758 tax returns reported a renewable energy source investment, but the average expenditure by these households (nearly US$3200) was more than four times as large as the typical energy conservation investment of US$779. One way to put the amount of expenditures on
234
Table 1. Energy conservation and renewable energy investments by the residential sector, 1981.”
Type of investment activity
Number of residences
Energy conservation Total 3741935 INS 2 180673 SWD 2041 183 cw 958 906 OCP 622 389 Renewable Total SE GE WE
Aggregate expenditure (US% thousand)
Average investment per residence (US%)
2915477 1115872 1431669 62 168 305 768
779 512 701 65 491
717720 678 732 21930 17057
3 193 3914 4613 1 530
energy 224 758 212 533 4 754 11145
‘INS insulation: SWD - storm (or thermal) window or doors; CW - caulking or weatherstripping; OCP - other conservation products, consisting of (a) a replacement burner for an existing furnace that reduces fuel use, (b) a device for modifying flue openings to make a heating system more efficient, (c) an electrical or mechanical furnace ignition system that replaces a gas pilot light, (d) a thermostat with an automatic setback and (e) a meter that shows the cost of energy used: SE - solar energy; GE - geothermal energy; WE - wind energy. Source: Internal Revenue Service, 1981 Individual Tax Model File.
energy conservation and renewable energy into perspective is to compare them with outlays for energy used in the household sector. Personal consumption expenditures in 1981 for electricity, natural gas, fuel oil and coal, the major types of energy used in residences, were US$86.5 billion.’ Therefore, household spending on efforts to reduce conventional energy consumption was just over 4% of the outlays for energy actually used in the residential sector. Table 1 also indicates the popularity of various specific types of energy conservation products and renewable energy sources. Expenditures for insulation and storm windows or doors were reported on over two million tax returns in 1981. The average expenditure was relatively higher for thermal products (US$701) than for insulation (US$512), but slightly more taxpayers added insulation than installed new windows or doors. Caulking and weatherstripping was the next most popular energy conservation investment, but the average expense of US$65 appears trivial compared with that made on ‘major’ improvements to conserve residential energy. About one out of six persons claiming the federal energy tax credit added some other conservation product to their residence, at an average cost (US$49 1) nearly equal to the typical outlay on insulation. Individuals were not restricted
‘Expenditure data are reported in US Department Survey of Currenr Business,July 1982.
ENERGY
ECONOMICS
of Commerce,
October
1993
Residential
expenditures
on energy: J. E. Long
Table 2. Average energy conservation and renewable energy expenditure reported on Form 5695 according to taxpayer income level, 1981. Adjusted gross income (US% thousand)
All energy conservation (USV
INS (US%)
SWD (US%)
$S)
OCP (US%)
All renewable energy (US%)
O-10 IO-25 25--50 50-10 100-150 150-200 200 +
696 126 769 945 1291 1361 1529
473 499 492 596 881 953 1257
619 638 683 965 1234 1671 1 526
13 57 54 135 254 226 475
923 454 466 498 921 447 1088
1528 2 302 3 492 3941 4 658 4815 6 892
“Symbols as in Table 1. Sourer: Internal Revenue
Service,
I%‘/ Indiiridual TU.Y Model Fik.
to just one type of energy conservation improvement, but the 15% tax credit applied to only the first US$2000 of conservation expenditures. The data in Table 1 imply that many residences received more than one conservation improvement in 1981. Table 1 clearly indicates that most renewable energy source investments involved the use of solar power. Less than 5% of the tax returns reporting renewable energy source investments, and no more than 3% of the total expenditures for such investments, involved geothermal or wind sources of residential energy. Not surprisingly, the energy source which appeared most costly - geothermal ~ was relied on least frequently by home-owners seeking an alternative to conventional priced residential energy sources. Evidence of how total energy conservation expenses and its sub-component outlays vary among households with different income levels is presented in Table 2. Conservation expenses in aggregate exhibit a distinctly positive relationship with adjusted gross income, a common measure of household purchasing power. For example, taxpayers with income between US$lOOOO and USS25 000 in 1981 reported average energy conservation investments on Form 5695 of $726, whereas households in the US$lOOOOO-$150000 range spent nearly $1300. An examination of the specific conservation improvements shows that the income expenditure association is most pronounced in the case of storm windows and doors, followed by insulation. In contrast, residential expenditures on caulking or weatherstripping and other conservation products do not consistently increase as income rises. Because so few tax returns reported investments in geothermal and wind energy, renewable energy source components are not broken down by income level. Combined expenditure on renewable energy sources (primarily solar power) vary markedly with income, ‘however, Average expenditures in the highest income grouping (USS6892) are more than four times the
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amount, of renewable energy costs incurred by households in the lowest income category (USrSl528).
Identifying the determinants of residential enegy conservation expenditures The amount spent by households on energy conservation and renewable energy sources is seen to vary considerably among households and among the different forms of conservation improvements. In this section of the report an econometric model of the determinants of residential energy conservation and renewable energy expenditures is specified and estimated with individual tax returns which included Form 5695 (residential energy credit). Based on previous studies of residential energy conservation, the explanatory variables fall into these categories: economic factors, household characteristics and climate conditions. The economic factors hypothesized to influence residential energy conservation expenditures are household income, the trend in household energy prices and federal and state tax credits for conservation improvements. Household income (INCOME) is measured by the adjusted gross income reported by the taxpayer. Energy price changes (PRICECHG) are approximated by the annual percentage increase over the period 1978-81 in average residential electricity rates (US$ per 1000 kWh) in the taxpayer’s state of residence.’ The federal tax credit variable (FEDCREDIT) is defined as the maximum federal tax savings, taking into account prior-year conservation costs and the portion of conservation expenditures made from non-taxable government grants and subsidized financing. The existence of state subsidies ‘Electric power rates were computed from data reported in US Department of Energy, Energy Information Administration, Typical Electric Bills Junuary I, 1982. October 1982, and Typical Eleciric Bills - January I, 1978, August 1978.
235
Residential
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rable 3. Regression analyses of residential energy conservation and renewable energy source investment (t-statistics in parentheses).
Explanatory fariable
Dependent variable: expenditures on All‘energy conservation INS (I) (2)
SWD (3)
All renewable energy sources
OCP (5)
(6)
‘NCOME US$ thousand)
5.55 (8.02)
3.76 (5.57)
6.79 (6.84)
1.58 (5.99)
1.48 (1.36)
17.71 (3.04)
PRICECHG
11.97 (3.75)
5.11 (1.69)
8.16 (1.86)
0.55 (0.55)
1.93 (1.61)
152.92 (3.89)
FEDCREDIT
0.92 (4.33)
0.28 (1.92)
0.27 (1.22)
0.07 (1.60)
0.50 (2.17)
0.91 (3.43)
STATESUB
25.14 (0.64)
111.24 (3.06)
112.06 (1.89)
PERSONS
- 15.58 (-1.42)
MARRIED
-8.42 (-0.20)
ELDERLY HEA TING DA YS (hundreds)
112.50 (2.49) (-0.91) (-1.14)
- 26.40 (-2.58) 65.56 (1.59) 195.74 (4.41)
-4.94 (-0.32)
-61.93 (-0.80)
1462.24 (4.34)
- 14.64 (-0.99)
-6.20 (-1.71)
- 26.76 (-1.41)
256.83 (2.12)
~ 138.68 (-2.36)
-5.25 (-0.33)
119.91 (1.86)
-2.69 (-3.68)
-0.79 (-0.70)
Constant
255.80 (2.64)
355.39 (4.38)
475.8 (4.06)
R2
0.3994
0.3598
0.3534
5871
3359
3099
Source: Author’s estimates based weighted regression analyses.
on sample
of tax returns
from the 1981 Individual
for home conservation is indicated by a dummy variable (STA TESUB) identifying states which allow tax credits or deductions for conservation improvements.3 Household characteristics include family size, measured by the number of persons (PERSONS) in the household besides the primary taxpayer, and dummy variables identifying taxpayers that are married (MARRIED) or 6.5 or older (ELDERLY). Climate conditions are measured by the annual number of heating degree-days (HEATING DA YS) in the taxpayer’s state of residence.4 The 1981 Tax Model File contained 8727 federal income tax returns reporting energy conservation and renewable energy investments. In order to identify the taxpayer’s state of residence it was necessary to exclude tax returns having adjusted gross incomes in excess of $200000 in 1981 (for confidentiality reasons, identifying variables such as location are deleted from 3Walsh [S] reported that Arizona, California, Colorado, Montana and Oregon allowed income tax credits, whereas Arkanas, Idaho and Indiana permitted tax deductions for energy conservation expenditures. ‘Tlimate data are reported in US Department of Commerce, National Oceanic and Atmospheric Administration, Monthly State, Regional. and Nuiional Healing Degree Days Weighted by Popularion: July 1980-Ocroher 1981, January 1982.
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81.49 (3.97) -0.34 (-1.20) 26.17 (0.94) 0.1969 1242
19.04 (0.26)
90.67 (0.18)
-68.39 (-0.92)
31.67 (0.06)
3.01 (2.07)
25.88 (3.89)
88.36 (0.63)
- 5365.88 (-396)
0.3771
0.4975
940
608
Tax Model File. Estimated
coefficients
are based
on
all such high-income tax returns). Forms 5695 filed by taxpayers residing in Alaska and Hawaii were also omitted from study because of the extreme weather climate in these areas. Finally, the empirical study was restricted to taxpayers having positive income in 198 1. A sample of 6346 households remained after these conditions were satisfied. These observations, after accounting for the sampling proportions employed by the IRS in assembling the Tax Model File, were responsible for over 99% of all energy conservation expenditures in 1981 and 95% of total renewable energy source investment. Therefore, the sample selection criteria employed in this study are unlikely to bias the empirical estimates of the determinants of energy conservation and renewable energy expenditures. The estimated determinants of residential energy conservation and renewable energy expenditures are presented in Table 3. Equations (1) and (6) are for total energy conservation and total renewable energy source investments respectively. Expenditures in both areas are positively and statistically related to the income level of taxpayers filing Form 5695. The INCOME coefficients imply that taxpayers with $60000 of income in 1981 spent US$222 (40 x 5.55) more on home energy conservation than households having
ENERGY ECONOMICS
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Kesidentiul income of US$20 000; the same income differential was associated with an extra US$708 of renewable energy investment. Energy (electricity) price changes are also found to be statistically related to conservation and renewable energy expenditures. If energy price inflation rises from 5 to 10% per year, household energy conservation outlays are estimated to increase by about US$60 annually. In elasticity terms, each percentage point rise in the cost of energy induces a 0.21 percentage point increase in conservation investments. The response of renewable energy investments to rising prices of conventional residential power sources is much greater - as reflected by an elasticity parameter of 0.63. Other factors being the same, residential spending on renewable energy sources would rise by about US$765 if electric power charges increased by an additional 5% annually. The estimated coefficient of the variable FEDCREDITis positive and highly significant in both Equations (1) and (6). Among taxpayers who made energy conservation or renewable energy investments in 198 1, those residences eligible for larger tax credits tended to spend more (at a rate of about 9Oc per each credit dollar) than taxpayers who could not receive as large a tax saving from the federal government. State government subsidies were estimated to influence renewable energy source investments only. On average, taxpayers in Arizona, California or other subsidy states who reported renewable energy costs on Form 5695 invested about US$lSOO more than comparable taxpayers in non-subsidy states. Households which installed renewable energygenerating features in 1981 tended to spend more on these products when family size was large; the reverse was observed in the case of energy conservation improvements. Neither aggregate conservation nor renewable energy expenditures were statistically different between married couple households and other family types. However, households occupied by elderly taxpayers received about US$I 13 of additional energy conservation improvements in 198 1 compared with non-elderly residences. The sign and significance of the ELDERLY coefficient in Equation (1) probably reflects the fact that the elderly typically reside in older, less energy-efficient, houses than other taxpayers. The age of the taxpayer filing Form 5695 is not statistically related to renewable energy source investment. The last variable in the regression model, HEATING DAYS, is statistically significant in Equation (6) but not Equation (1). Other factors held constant, expenditures on renewable energy (solar power, primarily) increase with the residential heating load. The HEATING DAYS coefficient implies that federal energy credit forms filed in 1981 by taxpayers living in a ‘cold’ state such as Minnesota (which had
ENERGY
ECONOMICS
October
1993
expenditures
on energy: J. E. Long
8076 annual heating degree days) reported about US$l300 more renewable energy costs than households residing in warmer states such as Alabama or Georgia (having 3075 and 3031 heating degree days). An analysis of total energy conservation expenditures may conceal potential differences between the determinants of specific conservation inputs. Therefore, separate estimates for insulation, storm windows and doors, caulking and weatherstripping and other conservation expenses are reported in Equations (2)-(5). Several important differences in the variables associated with each conservation product are apparent. Increases in income lead to larger expenditures on INS, SWD and CW, but there is no statistically significant relationship between income and other conservation costs. Households experiencing large increases in residential energy prices tend to spend more on INS, SWD and OCP but not CW. All types of energy conservation expenditures except those for SWD are positively related to the federal tax credit, whereas state subsidy plans appear to induce greater outlays on INS and SWD alone. The variables measuring family size and marital status do not perform consistently in the separate equations. For example, married couples are estimated to spend US$66 more than other household types on INS, but US$139 less on SWD. The ELDERLY coefficients imply that taxpayers aged 65 and over report relatively larger expenditures on the most common conservation inputs (eg INS) but not items such as replacement burners, furnace ignition systems or new thermostats to limit energy usage. The final conclusion from Table 3 involves the influence of climate on residential energy conservation expenditures. The coefficient of HEATING DAYS is statistically significant in regressions (2) and (5), but with opposite signs. The lower the heating load in a state, ie the warmer its climate. the larger the expenditures on home insulation for walls and attic spaces. In contrast, taxpayers who spend the most on other conservation products, such as devices to improve the efficiency of residential furnaces, tend to be persons who live in colder states. As noted previously, prior studies of energy conservation in the residential sector have examined the decision of home-owners to make conservation improvements, rather than their decision of how much to invest in energy-saving improvements. Consequently, the results in Table 3 are not directly comparable to those of other studies. However, these regression estimates are consistent with economic theory and they appear reasonable. Higher-income families can afford to make larger conservation investments than less affluent families, and the conservation expenditure data are consistent with this
237
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J. IL Long
fact. A time trend of rising energy prices, and the anticipation of future price inflation, appears to induce households to increase spending on items and equipment which are capable of reducing the amount of power which must be purchased from market suppliers. Families are found to spend more on energy conservation and renewable energy when the private cost of these investments is subsidized by government tax policies. Finally, the weather conditions facing home-owners have a common-sense effect on the amount and type ofenergy conservation expenditure.
Implications for household utility suppliers In the past many utilities have offered their residential customers financial incentives to purchase energyefficient home appliances and install retrofit measures in their residences. Successful energy conservation programmes in the residential sector can benefit electric utilities in particular by deferring the need for additional, and increasingly costly, electricity generation facilities. However, utilities do incur costs in providing subsidies for residential energy conservation. The net benefit to utilities from energy conservation is reduced if households would have purchased more efficient furnaces, or refitted their home with additional insulation or storm windows, even if utility-provided financial incentives had not existed. In this case, the financial incentives constitute pure windfalls from utilities and their stockholders to customers. The ability of subsidy schemes to stimulate energy conservation in the residential sector has been examined with reference to government tax credits for conservation and housing retrofit expenditures. Most studies have concluded that such tax credits do not stimulate energy conservation improvements. Possibly taxpayers have been uninformed about the tax credit, have been unwilling to complete the required paperwork to claim the tax savings, or have found the maximum subsidy amount insufficiently large. In contrast to these prior studies, the results of the present study suggest that households will increase conservation activity when the private costs are reduced because of public subsidies. To the extent that privately administered subsidies (eg low-interest loans or rebates to electric utility customers) can be more
238
publicized and simplified than government tax credits, there is additional reason to expect that utilities’ investments in residential energy conservation subsidies will not be wasted. A significant finding of the present as well as prior research relates to the influence of energy price movements on residential energy conservation activity. There is strong evidence that households increase conservation investment in response to the economic stimulus of rising electricity (and other household power) rates. Utility revenue forecasts that ignore customer conservation behaviour will be of questionable accuracy. In general a rate increase will not lead to a proportional rise in electric utility revenues, for example, because residential consumers will try to reduce power consumption. With sufficient time households will supplement the ‘simple’ conservation steps (eg adjusting thermostats, turning off lights) with conservation investments that permit comfortable room temperatures to be maintained with lower levels of power consumption. This household behaviour is part of the explanation for why the price elasticity of demand for residential power tends to be greater in the long run than the short run. Unless the effect of energy conservation activities on power consumption in the residential sector can be satisfactorily included in utility companies’ forecasting strategy, long-range projections of future generating needs or revenues may be seriously biased.
References E. H. Carpenter and S. T. Chester, ‘Are federal energy tax credits effective? A western United States survey’, The Energy Journal. Vol 5. No 2, 1984, pp 139-149. Energy Information Administration, An Economic Evaluation qf Energy Conservation and Renewable Energy Tar Credits, US Department of Energy, Washington, DC, 1985. Eric Hirst, ‘Energy and economic effects of utility financial incentive programs: the BPA residential weatherization program’, The Energy Journal, Vol8, No 2, 1987, pp 97-110. R. E. Pitts and J. L. Wittenbach, ‘Tax credits as a means of influencing consumer behavior’, Journal of Consumer Research, Vol 8, 1981, pp 335-338. ‘Energy tax credits and housing M. J. Walsh, improvement’, Energy Economics, Vol 11, 1989, pp 275-284.
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ECONOMICS
October
1991