WEATHERIZATION AND MINORITY ENERGY USE: ANl/CP--75431

A PRELIMINARY ANALYSIS _ .,_,, DE92 013047_:,,

Elizabeth V. Earl and Nancy E. Col.lins 2

MA_ u 61992 "INTRODUCTION

Recent events in the Persian Gulf and intensified political support for environmental issues

have led to a renewed national concern for energy saving policies and programs. Reduced

residential energy consumption and expenditures, through conservation measures and efficiency

improvements, are important goals of the Department of Energy (DOE) 1991/1992 National

Energy Strategy. Several federal initiatives, DOE's Weatherization Assistance Program (WAP)

and the weatherization aspect of the Department of Health and Human Services's Low-Income

Home Energy Assistance Program (LIHEAP), aim to reduce energy consumption and

expenditures by providing free weatherization or conservation measures to low-income

households. The extent to which a weatherization measure improves the energy efficiency of a

dwelling unit can be viewed as a function of the housing and appliance characteristics, the

technical efficiency of the weatherization measure(s), and the behavior of the household, where

each of these factors is determined by household economics, fuel prices, demographic

characteristics, and climate (Hirst, 1981). As minority groups differ from non-minority groups

in terms of household economics, demographic characteristics, and regional location, we would

1Work supported by the U.S. Department of Energy, Office of Minority Economic Impact,

:'under contract W-31-109- Eng=38. r_l_frj,_ [ LR_r:_,,k:::Argonne National Laboratory (ANl.,).

The submitted manur,Crlpt has been authoredby a contractor of the U, S, Governmentunder contract No, W-31.100wENG-38.

Accordingly, the U, S. Government retains enonexclus=ve, royalty.free license to publishor redroduce the published form oi thiscontribution, or allow others to do so, for

U, S. Government purposes.,"w..j

DI,"_TRI_'_'TION OF THiS DOCOiviEN7 i_3 OkikiiviiTE[-..,

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expect a given level of weatherization to differentially impact minority and non-minority

households.

This paper presents an analysis of the patterns of minority and non-minority energy

consumption with and without weatherization measures. The behavior of the household in

reponse to a weatherization-induced income gain is modeled using ANL's Minority Economic

Assessment Model (MEAM). Weatherization is then examined from a programmatic perspective

in light of the MEAM findings. This work is the first part of a larger analysis to assess the

economic impact of weatherization on minority households and to examine the reallocation of

LIHEAP funds to weatherization. Time and funding have limited the scope of this analysis; thus,

it should be judged as very preliminary. Several limitations of this analysis are discussed below.

The unit of analysis, the household, is examined at the national level. This has the effect of

missing differential impacts occurring at the regional level. Census regions differ greatly with

respect to climate, fuel mix, fuel prices, and most significant in terms of this analysis, minority

concentration. Specitically, Blacks are more concentrated in the South and less concentrated in

the West, relative to non-Blacks. Thus, national level household data will not capture the effects

of weatherization specific to the areas where minority concentration is greatest, lt is our intent

to extend our analysis to at least the Census region level.

This preliminary analysis compares the United States (US) Black population to the Majority

population (non-Black, non-Hispanic). In the future, we intend to extend the analysis to examine

other minorities, including Hispanics, Native Americans, and Asians. Other analyses will focus

on the elderly and handicapped -- groups targeted for WAP and LIHEAP participation.

OVERVIEW

WAP and LIHEAP provide eligible households with free materials and labor to install

weatherization or conservation measures to their residences. A typical participant household

receives insulation (attic and/or wall), weatherstripping, caulking, storm door(s), and storm

window(s). An improvement in the energy efficiency of a residence results in an income gain

for the household (all things being equal). Weatherization allows a certain service or comfort

level to be maintained with less energy input; thus, the cost per unit of service is lower and total

energy expenditures are lower. However, the added income to the household from weatherization

may be spent on energy or on non-energy goods and services and that might increase the demand

for energy. This response to weatherization of a household consuming some or all of its

weatherization-induced energy savings has been called the "takeback," "snapback," or "rebound"

effect (Weihl, Gladhart, and Krabacher, 1988).

A major problem with building retrofits or weatherization is that actual energy savings as a

rule fall short of the audit predicted savings. Actual savings were found to be roughly two-thirds

of the predicted amount (Hirst and Goeltz, 1983; Hirst, White, and Goeltz, 1984) in several

program evaluations. In addition, substantial variation in actual savings due to weatherization

program participation has occurred between households (Hirst and Goeltz, 1984; Hirst, White,

Holub, and Goeltz, 1985).

In an attempt to explain the discrepancies between this predicted and actual savings, Hirst

and White (1985) examined utility records for 242 electrically heated housebelds that

participated in Bonneville Power Administration's (BPA) weatherization programs in 1982 and

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1983. Utility data were disaggregated using Fel's Princeton Scorekeeping Method (PRISM).

According to PRISM calculations, interior temperatures increased by 0.4°F in the 1982 sample

and 1.3°F for the 1983 sample. The control group did not experience significant changes. Hirst

and White concluded that 5% of the 1982 participant savings and 25% of the 1983 participant

savings were "taken back." Stovall and Fuller (1987) relied on electricity consumption and

monitored interior temperature data in a study of the Hood River Conservation Project. Interior

temperature was found to rise an average of 0.6°F for all sample households and 0.9°F for low-

income households. This study, like the Hirst and White (1985) study, did not specifically

monitor household behavior but instead used billing data and interior temperature as indicators

of household thermostat control behavior.

Weihl, Gladhart, and Krabuacher (1988) extended previous studies of ten weatherized

I,ansing, Michigan, low-income households. Their analysis consisted of an energy behavior

monitoring system that primarily measured thermostat setting and ventilation behavior of the

household. Very little "takeback" was found with eight of the households. The average

thermostat setting increased by 0.9°F, and the average high and low setting increased by 0.3°F

and 1.4°F, respectively. These changes were attributed to changes in household composition or

schedules.

Others have challenged the "takeback" effect theory by rejecting the notion dmt households

behave rationally with respect to energy use. Kempton and Montgomery (1982) assert that

consumers use informal, simplified measurement techniques that they refer to as "folk

quantification" in making residential energy decisions. Consumers are said to have cognitive

models and economic calculations that differ from those of the experts, leading to errors in

estimating the impact of conservation measures and an underestimation the benefits of these

measures. For example, consumers use dollars to compare the total amount of each fuel used.

Folk quantification, rather than the "takeback" effect, is said to explain the persistent difference

between predicted and actual savings.p

Temes and Stovall (1988) used data sets from two field tests -- the Hood River Conservation

Project and a Madison, Wisconsin, project, to measure the role of indoor temperature in predicted

and actual energy savings due to weatherization. They suggest that the discrepancy often found

between predicted and actual savings can be reduced by 20 - 60% if measured savings are

adjusted using the same indoor temperature conditions used in the audit-predicted savings

calculations. The temperature assumed when predicting savings (70°F) was found to be an

accurate temperature for only one-third of the households. Their analysis, which normalized

measured savings, found the average change in indoor temperature following weatherization was

0, with an small number of households increasing or decreasing their indoor temperatures. Other

explanations for the discrepancy between predicted and actual savings include (Hirst 1986) errors

in audit methodology, data collection, and interpretation; in;, iJropriate, poor quality, or poorly

installed weatherization measures; errors in billing data; errors in methods used to analyzed

energy-use data; and changes in occupant behavior after retrofit.

METHODS

The most recent version of MEAM (MEAM 591) was used to model the effect of

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weatherization on the patterns of energy consumption and energy expenditures of majority and

minority households. In its first stage, MEAM allocates household expenditures between energy

,and non-energy consumption. The second stage allocates energy expenditures between electric

and nonelectric consumption. The calibration data for the model are based on the 1987

DOE/Energy Information Administration Residential Energy Consumption Survey Set 5

(RECS 5). This data set contains a sample of over 6000 U.S. households with housing and

household characteristic variables. Economic growth and energy price model inputs are based

on the DOE National Energy Strategy Current Policy Base Case. Climate information, in terms

of heating and cooling degree days, was obtained from 1980 Census City and County Data. The

model inputs for this analysis are discussed below.

Change in energy service ratio (ESR)' The energy service ratio is the ratio of the quantity of

energy input to the quantity of energy output. The default ESR for the model is 1, with a 0%

change in ESR per year. To simulate a "typical" weatherization scenario, a -0.005 per yearq

change in ESR was assumed. This translates to an 11% change in the ESR over a 22-year

period.

Unit of analysis: U.S. Base household gives a basis for comparison of future analysis at the

regional level. Future regional analysis will reveal the differential impact due to climate and

minority population concentrations.

Race: Black and Majority (non-Hispanic, non-Black) only.

Income: Poor includes households at or below 125% of the poverty level as defined by tile

Office of Management and Budget (OMB).

Sample size of RECS% for MEAM analysis: 454 and 919 Black and Majority low-income

households, respectively.

Time period: Base year 1987 through 2009, with data for odd years only.

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Differences between Majority and Black energy consumption for the base case and the

weatherization case are presented in Figure 1. The Black household consurnes 17.9% more

energy than the Majority household. This difference in consumption between Black and Majority

households is likely due to Blacks living in older, less energy efficient homes, and owning

less efficient appliances. Relative to the base year 1987 and assuming no weatherization, the

quantity of energy demanded is projected to decrease by 11.5% (an average of 1.1% per year)

for Black households and 4.5% (an average of .4% per year) for Majority households between

1987 and 2009. The discrepancy between these groups is due to the model's assumption of a

9% per year turnover of Blacks into newer,, more energy efficient dwellings, while the Majority

turnover is only 3%. Blacks move into more efficient dwellings at a higher rate because, in the

base year, they lived in older homes that were in poorer physical condition. As these homes

deteriorate, Blacks can be expected to move into other older homes, yet these older homes are

_, newer and more energy efqcient than the homes occupied in the base year.

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************************ FIGURES 1 & 2 ************************************

Figure 2 presents projected total energy expenditures for Black and Majority households.

These expenditures represent 17.8% of Black total income and 13.6% of Majority total income,t

due to a lower average total income for the Black household. Non-low-income Majority and

Black households cons_ame more energy than low-income households, yet energy expenditures

represent a smaller percent of total income simply due to higher income levels. The base case

total energy expenditures are projected to increase by 29.1% and 25.6% for Majority and Black

households, respectively. Despite the aforementioned projected decreases in energy consumption

for both groups, prices are expected to rise at a greater rate than consumption declines. The

Black household's expected decrease in energy consumption is i65% greater than the Majority

household's expected decrease; however, the Black household's expenditures are only 12% less

than the Majority household's expenditures. This is due to differing fuel type prices and differingi

fuel mix between Black and Majority households.

The weatherization case, with a change in ESR of-0.005% per year, has a predicted reduced

energy consumption of 1% per two-year period. If households had no char, ge in behavior as a

result of weatherization and simply realized the full technological extent of the weatherization

measure, we would expect energy consumption to decline by 1% per year.

Differences between the base case and weatherization case (ESR=-0.005) are shown in i_igure

1. Relative to the base year, i987, the weatherization case consumption decreased by 14.4% by

2009 for the Majority household and 21.1% for the Black household. Comparing these numbers

to the base case, weatherization resulted in 10% less consumption for the Majority household and

9.3% less consumption for the Black household. Relative to the base year 1987, the

weatherization case resulted in 15.9% higher energy expenditures for the Majority household and

12.7% higher for the Black household. Energy expenditures differ 13.2% for the Majority

household and 12.9% for the Black household. These expenditures decrease at the rate of 1%t

per two.year period.

The next step in our analysis is to examine weatherization from a programmatic perspective.

As with the MEAM analysis, the focus here is on a Black household. However, as we do not

expect a differential impact for non-minorities, the Majority household could I:_, used. What

follows is a discussion of the likely effects of a WAP or LIHEAP weatherization scenario. This

analysis is not specific to either program; it takes a general approach to weatherization and low-

income households.

Our weatherization scenario contains several assumptions. It was beyond the scope of this

analysis to quantify the exact price of each weatherization measure, but measures were chosen

that roughly equalled $2,000 and the associated energy savings presented. These estimates are

in accord with prices and energy savings found in our literature review. This amount is greater

than WAP or LIHEAP expenditure per household, yet is certainly possible with coordination of

funds from both of these sources, as well as other state, local, or utility programs. Table 1 lists

the various weatherization measures carried out on the Black residence over a 14-year time

period. We assume the same household throughout the 14-year period, with no changes in

household characteristics and housing and appliance stock (except for weatherization changes).

Our estimates of potential energy savings are on the conservative side intentionally. By looking

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****************************** FIGURE 3 ************************************

at cumulative savings, we can compensate for the interaction between weatherization measures.

Applying weatherization measures often decreases the conservation potential of future

weatherization. For example, measures to improve the thermal integrity of the housing shell

(insulation, caulking, storm doors, and storm windows) change the household requirement for

space heating. Therefore, a new energy _fficient furnace would be operating in an environment

with a lower fuel demand and, therefor'_, the savings from the furnace would be lower than

without the thermal integrity improvement. We also assume there is no degradation of

weatherization materials once they have been inst'died; therefore, the initial savings will continue

through the 14-year time period.

TABLE 1. SELECTED WEATHERIZATION MEASURES ANDTHEIR PREDICTED ANNUAL ENERGY SAVINGS

WEATHERIZATION ANNUAL ENERGYTIME PERIOD MEASURE SAVINGS

1987-1989 attic insulation 14%

1989-1991 wall insulation 12%

1991-1993 4 storm windows 10%

1993-1995 caulk/weatherstrip 8%

1995-1997 2 storm doors 6%

1997-1999 upgrade water heater 4%

1999-2001 furnace tune-up 2%i ..= )

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Figure 3 graphically displays the decrease in energy consumption due to these energy

measures. The major feature of this graph is the cumulative nature of the weatherization

measures over time and the magnitude of the ultimate savings, 56% of the initial energy

consumption level. Energy expenditures will decrease by this same percent relative to non-

weatherization. If the MEAM base case 1987 Black household expenditure is used, total energy

savings over the 12-year time period amount to $2,189.67.

To examine the tradeoff with reallocation of LIHEAP funds to weatherization, we have

performed some basic calculations for the purpose of comparison to our weatherization scenm'io.

Over half of LIHEAP spending is for heating and cooling benefits to assist households in paying

their energy costs. The vast majority of these benefits are for heating rather than cooling.

Heating costs amount to roughly 39% of total home energy costs, and LIHEAP benefits offset

about 52% of recipient heating COSTS.3 Using the 1987 base year Black household total energy

expenditure level of $1,139.87, LIHEAP heating assistance over the 12-year time period would

amount to $3,236.24. As with the weatherization case presented above, this assumes no energy

price increase and no change in the household fuel mix.

CONCLUSIONS AND DIRECTION OF' FUTURE WORK

This analysis offers the following conclusions:

3Low-Income Home Energy Assistance: A Program Overvie._w United States GeneralAccounting Office, Washington, D.C., 1990.

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1. Low-income Black and Majority households do not appear to experience the "takeback"

effect and therefore will likely realize the full extent of the expected energy savings due to

weatherization. Therefore, we would expect federal programs designed to lower energy

consumption and expenditures of low-income households to achieve these goals.

2. Over the 12-year time period discussed, LIHEAP payments would provide $3,236.24 in

benefits, or roughly 20% of total household energy costs for a Black household. This type

of benefit is not expected to yield reduced energy consumption; in fact, economic theory

would predict that the household may consume more than it would otherwise, as it is not

bearing the full costs of consumption.

3. Our weatherization case benefits the Black and Majority households by reducing energy

consumption and expenditures by 56% over a 12-year period. A further benefit is the

reduced energy use of the same magnitude.

Future work should first extend our MEAM analysis to include Census region data,

Hispanics, Native Americans, and Asians. In addition, a sensitivity analysis using varying ESR's

should be conducted. MEAM could 'also be applied to analyze the impact of LIHEAP-type

payment for a portion of space heating costs on energy consumption and expenditures.

The next stage of analysis should include an examination of changes in energy consumption

and expenditures using state or utility level data for minority and non-minority households

receiving WAP, LIHEAP, or some combination of the two programs. The smaller geographic

unit of analysis wil! allow for the effects of climate, fuel prices, and fuel mix. Results of such

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an analysis would be valuable in assessing present federal weatherization initiatives and the

reallocation of LIHEAP funds to weatherization activities.

DISCLAIMER

This report was prepared as an account of work sponsored by an agency of the United States

Government. Neither the United States Government nor any agency thereof, nor any of their

employees, makes any warranty, express or implied, or assumes any legal liability or responsi-

bility for the accuracy, completeness, or usefulness of any information., apparatus, product, or

process di_losed, or represents that its use would not infringe privately owned rights. Refer-

en_ herein to any specific commercial product, process, or service by trade name, trademark,

manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recom-

mendation, or favoring by the United States Government or any agency thereof. The views

and opinions of authors expressed herein do not necessarily state or reflect those of the

United Stat¢_s Government or any agency thereof.

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REFERENCES

Anderson, J.L., K. Miller, D.A. Poyer, and A,P.S. Teotia, Minority Energy Assessment ModelPersonal Computer Software Documentation,ANL/ESD/TM-10, Argonne National Laboratory,Argonne, IL, 1990.

Hirst, E., Comparison of Actual and Predicted Energy Savings in Minnesota Gas-Heated Single-Family Homes,Oak Ridge National Laboratory, Oak Ridge, TN, March 1984.

Hirst, E., R. Goeltz, and J. Carney, Residential Ener_zv Use and Conservation Actions: Analysispf Disaz_regate Household Data, ORNL/CON-68, Oak Ridge National Laboratory, Oak Ridge,TN, March 1981.

Hirst, E., D. White, and R. Goeltz, Energy Savings due to the BPA Residential WeatherizationPilot Program Two Years after Participation, Oak Ridge National Laboratory, Oak Ridge, TN,January 1984.

Hirst, E., D. White, E. Holub, and R. Goeltz, Actual Electricity Savings for Homes Retrofit bythe BPA Residential Weatherization Program, Oak Ridge National Laboratory, Oak Ridge, TN,July 1985.

Kempton, W., and L. Montgomery. "Folk Quantification of Energy," Ener_zv-The InternationalJournal, 7(10):817-827, 1982.

U.S. Department of Energy, National Energy Strategy, First Edition 1991/92, DOE/S-0082P,U.S. Government Printing Office, Washington, DC, 1991.

U.S. General Accounting Office, Low-Incorne Home Energy Assistance - A Program Overview,U.S. Government Printing Office, Washington, DC, October 1990.

Stovall, T., and L. Fuller, Effect of Lifestyle on Energy Use Estimations and Predicated Savings,ORNL/CON-241, Oak Ridge National Laboratory, Oak Ridge, TN, 1987.

Ternes, M, and T. Stovall, "The Effect of House Indoor Temperature on Measured and PredictedEnergy Savings." ACEEE Summer Study on Energy Efficient Buildings, Vol.9, August 1988.

Weihl, J., P. Gladhart, and S. Krabacher, "The 'Takeback Effect' in Low-Income Weatherization:

Fact or Fiction?" ACEEE Summer Study on Energy Efficient Buildings, Vol. 9, August 1988.

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