Price Elasticity for Energy Use in 

Buildings in the United States

January 2021

Independent Statistics & Analysis

www.eia.gov

U.S. Department of Energy

Washington, DC 20585
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U.S. Energy Information Administration | Price Elasticity for Energy Use in Buildings in the United States i

This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and 

analytical agency within the U.S. Department of Energy. By law, EIA’s data, analyses, and forecasts 

are independent of approval by any other officer or employee of the U.S. Government. The views in 

this report should not be construed as representing those of the U.S. Department of Energy or other 

federal agencies.
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U.S. Energy Information Administration | Price Elasticity for Energy Use in Buildings in the United States ii

Table of Contents

Introduction .................................................................................................................................................. 1

Own-Price and Cross-Price Elasticities.......................................................................................................... 2

Energy Consumption in Selected Price Cases............................................................................................... 4

Natural Gas Consumption in Price Sensitivity Cases..................................................................................... 6

Electricity Consumption in Price Sensitivity Cases........................................................................................ 8

Costs in Elasticity Cases............................................................................................................................... 15

Conclusion................................................................................................................................................... 17

Appendix ..................................................................................................................................................... 18
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List of Tables

Table 1. Own-price elasticities in AEO2020 Residential Demand Module and Commercial Demand 

Module.......................................................................................................................................................... 3

Table 2. Cross-price elasticities in AEO2020 Residential Demand Module and Commercial Demand 

Module.......................................................................................................................................................... 3

Table 3. Own-price elasticities in AEO2020 Residential Demand Module and Commercial Demand 

Module for selected end uses....................................................................................................................... 4

Table 4. Changes in the number of residential heating equipment, 2050 .................................................10

Table 5. Summary of own-price elasticities in AEO2020 Residential Demand Module and Commercial 

Demand Module (using simulations where fuel price is cut in half between 2020 and 2050)..................18

Table 6. Summary of cross-price elasticities in AEO2020 Residential Demand Module and Commercial 

Demand Module (using simulations where fuel price is cut in half between 2020 and 2050) ..................18
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List of Figures

Figure 1. Delivered energy consumption in the commercial sector............................................................. 5

Figure 2. Delivered energy consumption in the residential sector............................................................... 6

Figure 3. Natural gas consumption in the residential sector across price cases.......................................... 7

Figure 4. Natural gas consumption in the commercial sector across price cases ........................................ 8

Figure 5. Electricity consumption in the commercial sector across price cases........................................... 9

Figure 6. Delivered electricity consumption in the residential sector across price cases............................9

Figure 7. Buildings distributed generation in price cases, 2050 ................................................................. 11

Figure 8. Percentage of improvement in efficiency of residential cooling equipment in the Electricity 

Price Doubled case relative to the Reference case..................................................................................... 13

Figure 9. Percentage of improvement in efficiency of commercial cooling equipment in the Electricity 

Price Doubled case relative to the Reference case..................................................................................... 13

Figure 10. Lighting service demand for the commercial sector, Reference case versus Electricity Price 

Doubled case in 2050.................................................................................................................................. 14

Figure 11. Water heating demand for the residential sector, Reference case versus Electricity Price 

Doubled case............................................................................................................................................... 15

Figure 12. Total fuel expenditures for energy customers in price cases.................................................... 16

Figure 13. Consumer, government, and utilities investment in equipment and shells, Reference case 

versus Electricity Price Doubled case.......................................................................................................... 17
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U.S. Energy Information Administration | Price Elasticity for Energy Use in Buildings in the United States 1

Introduction

Within the U.S. Energy Information Administration’s (EIA) National Energy Modeling System (NEMS), the 

Residential Demand Module (RDM) and Commercial Demand Module (CDM) are two separate modules

that are used to project energy consumption in the residential and commercial sectors. Despite 

similarities between these models, they differ in terms of equipment technology choice and internal 

accounting.

1

This report explains the responses in the Annual Energy Outlook 2020 (AEO2020) version of the NEMS 

RDM and CDM to changes in delivered energy prices. The economic concept is known as price elasticity 

of demand, or the percentage change in energy consumption relative to the percentage change in 

prices, all other factors being equal. In general, an increase in a fuel price causes consumers to use less 

of that fuel or switch to a different fuel. The extent to which each of these changes takes place is useful 

to stakeholders in the energy sector and, particularly, in energy policy design.

The NEMS residential and commercial models can provide both short-run and long-run responses to 

energy price changes.

2 Short-run responses to price changes are more behavioral and temporary in 

nature and may affect energy consumption of energy-using appliances or equipment. An example of a 

short-run response would be a building occupant adjusting the thermostat during cold or hot weather in 

response to high energy bills, leading to lower energy demand for heating or cooling. Long-run 

elasticities are driven by stock turnover and by technology choices for major fuels and major end uses,

and they usually take place over a longer time period. For example, installing a more efficient space 

conditioning system or upgrading windows in a building. 

To estimate responses to energy price changes, this analysis considers a series of simulations performed

by adjusting the energy price paths from the AEO2020 Reference case. Only the buildings3 modules are 

used in these simulations; integrated effects with the rest of NEMS are not included.4 The elasticities 

computed from the NEMS projections reflect the results of statistical analyses of historical energy price 

and consumption data, along with expert judgment. The three main energy sources for the commercial 

and residential sectors are electricity, natural gas, and distillate. To compute the price elasticities, for 

each simulation, the price of one of these energy sources is doubled. 

 1 For detailed information on both models, see U.S. Energy Information Administration (EIA), Model Documentation Report: 

Commercial Sector Demand Module of the National Energy Modeling System, DOE/EIA-M066; and Model Documentation 

Report: Residential Sector Demand Module of the National Energy Modeling System, DOE/EIA-M067. For modeling assumptions 

and general techniques, see EIA, Assumptions to AEO2020. 2 In economics, the short run is generally defined as a period over which capital stock remains fixed. Because the typical service 

lifetime of installed capital can vary among economic sectors, energy end uses, and equipment types, no single definition 

differentiates between short run and long run. 3 Throughout the paper “buildings” or “buildings sector” refer to the residential and commercial demand sectors.

4 NEMS is an integrated, modular system where fuel prices and energy demand interact until an equilibrium is met for the 

entire system for each model year. In the buildings modules of NEMS, energy demand equilibrates to fuel prices from other 

modules. Although year-to-year changes in fuel price have the biggest effect on energy demand during the year in which they 

occur, the full effect of fuel price change is also spread over the following two years to prevent unrealistic demand responses to 

price spikes of one year or other short-term durations. Table 1 and Table 2 present elasticity results for Years 1–3, where Year 1 

in the model is when the simulated price change from the Reference case was programmed to take place and Year 2 and Year 3 

are the two following years (Year 1 corresponds to 2020 in the model).
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U.S. Energy Information Administration | Price Elasticity for Energy Use in Buildings in the United States 2

Own-Price and Cross-Price Elasticities

The two types of fuel price elasticity presented in this report are own-price and cross-price elasticities. 

Own-price elasticity refers to changes in consumption of a particular fuel when the price for that fuel 

changes (for example, electricity use changes when electricity price changes), and cross-price elasticity 

refers to changes in consumption of a particular fuel when the price of a different fuel changes (for 

example, the change in electricity use when the price of natural gas changes). Own-price elasticities are 

usually negative—indicating that fuel consumption goes down as the price of that fuel goes up—and 

cross-price elasticities are usually positive—consumption of a fuel goes up when the price of a 

competing or substitute fuel goes up. Price responses are considered to be elastic if the absolute value 

of the price elasticity is greater than one (the proportionate change in energy consumption is greater 

than the proportionate change in price). The absolute value of the price elasticity of energy is generally 

less than one, in other words, inelastic (the proportionate change in energy consumption is less than the 

proportionate change in price).

Table 1 and Table 2 present the estimated own-price and cross-price elasticities, respectively. The 

estimates are based on simulations where a single fuel price is doubled in the AEO2020 Reference case 

for all years.5 The price doubling adjustments start in 2020 and continue through the end of model 

projections in 2050 (Year 30). By assumption, short-run price responses occur over a three-year interval 

(that is, the first three years of price changes). Long-run price responses refer to consumption changes 

in 2050. The elasticity results presented in the report show the percentage change in fuel use for every

1.0% increase in fuel price. For example, in Table 1, a 1.0% increase in electricity price results in a 0.13% 

decrease in electricity use in Year 1.6

 5 Elasticity calculations are based on simulations where a single fuel price is doubled. However, calculated elasticities would be 

different if different price paths were used. For example, the attached Appendix (Table 5 and Table 6) shows the elasticities 

that result if individual fuel prices are divided in half instead of doubled. The differences between the two sets of elasticities are 

caused by existing market conditions and consumer preferences in the buildings sector. 6 Elasticities are computed using the following expression: ln (Q1/Q0)/ln (P1/P0), where P0 and Q0 are base prices and 

quantities, and P1 and Q1 represent an alternative price-quantity combination.
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Table 1. Own-price elasticities in AEO2020 Residential Demand Module and Commercial Demand 

Module

Short run Long run

Year 1 Year 2 Year 3 Year 30

Residential

 Electricity -0.13 -0.22 -0.26 -0.50

 Natural gas -0.08 -0.13 -0.15 -0.23

 Distillate fuel -0.09 -0.16 -0.19 -0.24

Commercial

 Electricity -0.08 -0.13 -0.15 -0.18

 Natural gas -0.03 -0.18 -0.25 -0.28

 Distillate fuel -0.13 -0.22 -0.26 -0.30

Table 1 shows that the commercial sector contains larger long-run own-price elasticities than the 

residential sector for fossil fuel. The largest energy demand changes in the long run occur in the 

residential sector in response to electricity prices. The large long-run own-price elasticity for residential 

delivered electricity is partly explained by increases in distributed generation (DG), particularly solar 

photovoltaic. Short-run elasticities range from -0.03 to -0.13 in Year 1 and from -0.15 to -0.26 in Year 3.

Long-run elasticities at Year 30 ranged from -0.18 to -0.50.

Table 2 shows that long-run cross-price elasticities are lower, in absolute value, than own-price 

elasticities for all three fuels. In both sectors, the highest cross-price elasticities are between natural gas 

and electricity, perhaps because of conversions from electric to natural gas heating systems.

Table 2. Cross-price elasticities in AEO2020 Residential Demand Module and Commercial Demand 

Module

(Long run, Year 30)

Change in fuel price

Electricity Natural gas Distillate

Residential

Change in fuel use 

 Electricity -- 0.03 0.00

 Natural gas 0.10 -- 0.01

 Distillate fuel 0.02 0.02 --

Commercial

 Electricity -- 0.01 0.00

 Natural gas 0.04 -- 0.01

 Distillate fuel 0.00 0.01 --

Energy price elasticities also vary across end uses and fuels (Table 3). Based on the hypothetical doubling 

of prices, electricity price elasticities exceed natural gas elasticities in both sectors. For the reported end 

uses, own-price elasticities vary from -0.08 for residential natural gas space conditioning and water 

heating in the short run to -0.93 for residential electric water heaters in the long run.
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Table 3. Own-price elasticities in AEO2020 Residential Demand Module and Commercial Demand 

Module for selected end uses

Short run Long run

Year 1 Year 2 Year 3 Year 30

Commercial electricity

 Space heating -0.14 -0.23 -0.28 -0.41

 Space cooling -0.14 -0.23 -0.27 -0.39

 Water heating -0.15 -0.25 -0.31 -0.60

Commercial natural gas

 Space heating -0.13 -0.22 -0.26 -0.30

 Space cooling -0.12 -0.21 -0.25 -0.28

 Water heating -0.13 -0.22 -0.26 -0.28

Residential electricity

 Space heating -0.16 -0.27 -0.33 -0.48

 Space cooling -0.17 -0.29 -0.34 -0.66

 Water heating -0.17 -0.31 -0.38 -0.93

Residential natural gas

 Space heating -0.08 -0.13 -0.15 -0.21

 Space cooling -0.08 -0.14 -0.16 -0.16

 Water heating -0.08 -0.14 -0.17 -0.31

Energy Consumption in Selected Price Cases 

In this section, for the purpose of illustration, the report includes two additional scenarios:

• A permanent doubling of all electricity, natural gas, and distillate prices in all years from 2020 to

2050, relative to the Reference case (Permanent All Prices Doubled case)

• A temporary doubling of fuel prices between 2025 and 2030, relative to the Reference case

(Temporary All Prices Doubled case), in which prices from 2031 to 2050 are equal to the 

Reference case prices 

When prices are permanently doubled, commercial energy demand drops to less than the Reference 

case level in 2020 and drops 11.3% (1.1 quadrillion British thermal units [Btu]) from the Reference case

level in 2022 (Figure 1). The gap between the Reference case and the Permanent All Prices Doubled case 

widens slightly—with commercial energy demand 12.1% (1.3 quadrillion Btu) lower than the Reference 

case in 2050—as equipment and building stock continue to be replaced with more efficient options. The 

preference for more efficient options occurs in response to the higher fuel prices.

In contrast, the Temporary All Prices Doubled case projects a drop in energy demand to a similar level 

between 2025 and 2030 and then shifts back toward the Reference case a few years later. By 2033, the 

gap between the Temporary All Prices Doubled case and the Reference case is only about 1.3% (0.1 

quadrillion Btu). This gap continues to narrow through the rest of the projection period, but the 

Temporary All Prices Doubled case does not actually meet the Reference case by 2050. The continued 

difference is the result of purchase decisions with long-run effects that were made during the price 
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U.S. Energy Information Administration | Price Elasticity for Energy Use in Buildings in the United States 5

shock years. The upgrades in equipment and building shells purchased during the temporary price shock 

continue to provide some energy savings even after prices return to Reference case levels in 2030.

Figure 1. Delivered energy consumption in the commercial sector

Figure 2 shows the energy demand projections in the residential sector for the two cases. The 

residential sector and commercial sector share some similarities but with a few additional interesting 

features. Both sectors see an initial drop when price changes take effect, but instead of a near-constant

gap between energy demand in the Reference case and the Permanent All Prices Doubled case (like in 

the commercial sector), residential demand shows a widening gap after the initial drop.7 Energy demand 

in the residential sector drops 10.8% (1.2 quadrillion Btu) lower than the Reference case level by 2022 

and then continues falling to 16.8% (1.9 quadrillion Btu) lower than the Reference case level in 2050. 

This widening gap is associated with the continued selection of higher efficiency appliances and 

equipment under the higher price case.

 7 In the commercial sector, the gap in energy demand between the Reference case and the Permanent Prices Doubled case 

does increase in absolute terms between 2022 to 2050, albeit slowly, from 1.1 quadrillion Btu to 1.3 quadrillion Btu. 
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Figure 2. Delivered energy consumption in the residential sector

Natural Gas Consumption in Price Sensitivity Cases

Figure 3 illustrates the sensitivity of residential natural gas consumption in the cases when a single fuel 

price is doubled (used in computation of elasticities) and when all prices are doubled permanently. 

When only the electricity price increases, natural gas consumption grows at a faster rate than in the 

Reference case. This response is consistent with the positive long-run cross-price elasticity of natural gas 

with respect to electricity prices in Table 2 (+0.10). When natural gas prices are doubled, the simulation 

reflects a large drop in residential consumption, which parallels the corresponding negative long-run 

own-price elasticity in Table 1 (-0.23). The long-run cross-price elasticity of almost 0 with respect to 

distillate fuel prices explains why natural gas demand in the Distillate Price Doubled case remains 

virtually unchanged from the Reference case (Figure 3). Natural gas demand decreases when all fuel 

prices double. However, the effect is most pronounced when only the natural gas price doubles because 

doubling the other fuel prices keeps natural gas competitive, meaning fewer consumers in the 

residential sector will switch to other fuels when all fuel prices double compared with when only the 

natural gas price doubles. However, total delivered energy in the sector drops by 1.9 quadrillion Btu in 

2050 when all fuel prices are permanently doubled. As a result, when all fuel prices are doubled, 

improving efficiency and doing without energy services has a larger effect on lower natural gas demand 

than fuel switching.
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Figure 3. Natural gas consumption in the residential sector across price cases

 

Figure 4 illustrates a similar dynamic in the commercial sector. The absolute value of long-run own-price 

elasticity of natural gas is higher (-0.28) than the long-run cross-price elasticity with respect to the 

electricity price (0.04). These elasticities are consistent with the smaller absolute change in commercial 

natural gas demand by 2050, when the electricity price is doubled (0.1 quadrillion Btu), relative to the 

simulation with the doubled natural gas price (0.7 quadrillion). 
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Figure 4. Natural gas consumption in the commercial sector across price cases

Electricity Consumption in Price Sensitivity Cases

Figure 5 and Figure 6 show how electricity consumption changes in the price cases for the commercial 

and residential sectors, respectively. The largest drop in electricity consumption in both sectors occurs in 

the Electricity Price Doubled case. This case includes the highest combination of fuel switching away 

from electricity and of efficiency improvements in electricity end uses. 
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Figure 5. Electricity consumption in the commercial sector across price cases

Figure 6. Delivered electricity consumption in the residential sector across price cases
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The two primary ways electricity fuel switching occurs is replacing electric equipment with equipment 

that runs on another fuel and increasing distributed generation (DG).8 Equipment replacement could

occur in the normal equipment lifecycle, when an existing piece of equipment is due to be replaced, or it 

could happen before the expected lifetime ends. Table 4 illustrates an example of fuel switching as a 

result of equipment stock changes, specifically heating equipment in the residential sector. The table 

presents the total number of units used for heating in households, broken out by equipment type. 

Comparing heating equipment stocks between the cases shows that the Electricity Price Doubled case

has significantly fewer electric heaters (particularly electric furnaces) and significantly more equipment

that uses other fuels (particularly natural gas furnaces). 

Table 4. Changes in the number of residential heating equipment, 2050

a

Change from Reference case relative to the Electricity Price Doubled case.

Increased use of DG at building sites is another form of fuel switching and also results in building 

occupants using less electricity from central power plants. The large increase in DG in the Electricity 

Price Doubled case comes from rooftop solar panels (Figure 7). In this case, rooftop solar grows 7.3% per 

year between 2020 and 2050, compared with 4.6% per year in the Reference case.

 8 Distributed generation refers to a category of electricity generation that includes combined heat and power (CHP) and 

renewables, such as rooftop solar and wind power systems, at building locations. CHP is generating equipment that provides 

electric power for a building and uses residual heat from that process for heating services. The buildings sector use non-utilityscale CHP as a form of distributed generation. CHP is uncommon in the residential sector.

Equipment 

Reference 

case

Electricity Price 

Doubled case Changea

Electric furnace 31,756,901 29,519,232 -2,237,669

Air-source heat pump 

(electric) 18,282,896 16,734,275 -1,548,621

Geothermal heat pump 2,240,904 1,798,270 -442,634

Natural gas furnace 67,590,849 71,391,727 +3,800,878

Natural gas boiler 10,032,195 10,053,160 +20,965

Natural gas heat pump 1,158,852 1,158,854 +2

Propane furnace 4,324,370 4,478,750 +154,380

Distillate and kerosene 

furnace 2,400,326 2,418,123 +17,797

Distillate boiler 1,706,345 1,706,447 +102

Wood stove 2,351,929 2,587,379 235,450
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Figure 7. Buildings distributed generation in price cases, 2050

In addition to fuel switching, efficiency improvements also play a role in reducing electricity demand in 

the Electricity Price Doubled case. The case reflects efficiency improvements among most electric 

equipment, but the end uses that contribute the most electricity savings are space cooling, lighting, and 

water heating.

Figure 8 and Figure 9 show the average stock efficiency improvements in residential and commercial 

space cooling equipment where electricity prices are doubled relative to the Reference case. Central air 

conditioners and room air conditioners are the most prevalent space cooling equipment in the 

residential sector, accounting for 88% or more of household space cooling equipment throughout the 

projection period in both cases.

9 Although the percentage gains in efficiency are highest for geothermal 

heat pumps in this sector, this technology is relatively costly and is unlikely to gain wide adoption 

without further improvements in cost.

In the commercial sector, electric space cooling equipment accounts for 95% or more of the energy 

consumed for space cooling throughout the Reference case projections. Electric space cooling 

equipment shows smaller efficiency gains than natural gas space cooling equipment in the Electricity 

Price Doubled case. However, this smaller increase in efficiency leads to a greater reduction in energy 

consumption because of the large share of demand met by electric cooling equipment. In 2050, 

electricity demand for space cooling in the Electricity Price Doubled case is 0.45 quadrillion Btu (35%) 

 9 The RDM also has a category for natural gas heat pumps that provide space cooling, but that category was not included in 

Figure 8 because there was no efficiency improvement in that category for the Electricity Price Doubled case.
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lower than the Reference case level in the residential sector and 0.15 quadrillion Btu (23%) lower than

the Reference case level in the commercial sector.10

 10 After 2040, the average efficiency of space cooling in the Electricity Price Doubled case changes very little relative to the 

Reference case for residential geothermal heat pumps (Figure 8) and commercial natural gas (Figure 9). This trajectory is 

particularly affected by the residential and commercial technology choice models as the electricity price increases and 

improvement in the average efficiency of available equipment stabilizes in later projection years.
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Figure 8. Percentage of improvement in efficiency of residential cooling equipment in the Electricity 

Price Doubled case relative to the Reference case

Figure 9. Percentage of improvement in efficiency of commercial cooling equipment in the Electricity 

Price Doubled case relative to the Reference case
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In 2019, almost twice as much energy was consumed for lighting in the commercial sector (0.48 

quadrillion Btu) as in the residential sector (0.26 quadrillion Btu).

11 In the Reference case, electricity 

demand for lighting declines faster in the commercial sector than in the residential sector as a result of 

faster growth in use of efficient light-emitting diodes (LEDs). LEDs produce less waste heat while 

producing light, which makes them more efficient than other lighting options. In 2019, LED lighting 

technology accounted for 44% of the residential lighting market while LED lighting only accounted for 

17% of commercial lighting demand, providing greater potential for declines in energy demand as a 

result of efficiency gains in the commercial sector.

In the Electricity Price Doubled case, savings in electricity consumption for lighting come from efficiency 

improvements largely in the commercial sector. Energy use for lighting in the buildings sector in this 

case is 0.14 quadrillion Btu (27%) lower than the Reference case level in 2050, with 0.11 quadrillion Btu 

coming from the commercial sector. Figure 10 shows LED technologies are projected to meet most of

the service demand for commercial lighting by 2050 as a result of federal standards and increasing 

penetration of LED lighting technologies.

12 In the Electricity Price Doubled case, the share of commercial 

lighting demand for these lighting technologies increases. 

Figure 10. Lighting service demand for the commercial sector, Reference case versus Electricity Price 

Doubled case in 2050

 11 This result is the same in all cases presented because price effects begin in 2020. 12 Service demand is not the same as energy demand. Service demand is a modeling concept meaning how much an end user 

demands of a service (for example, lighting). The end user then has to use energy-using equipment to fulfill that service 

demand (for example, light bulbs). Different types of equipment (for example, incandescent lighting, fluorescent lighting, LED 

lighting) may use different amounts of energy to meet service demand. 
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Water heating accounts for about 10% of energy consumption in the buildings sector. Electricity savings 

in the Electricity Price Doubled case for water heating come almost entirely from the residential sector. 

In 2050, residential sector water heating electricity use is about 0.28 quadrillion Btu (46%) lower than

the Reference case level in the Electricity Price Doubled case. Figure 11 shows the amount of energy 

consumed for water heating in the residential sector, by fuel, in 2050. In the Electricity Price Doubled 

case, natural gas consumption for residential water heating increases by 19% relative to the Reference 

case. This expectation is consistent with the positive long-run cross-price elasticity that natural gas has 

with electricity prices (+0.10). 13

Figure 11. Water heating demand for the residential sector, Reference case versus Electricity Price 

Doubled case

Costs in Elasticity Cases

As shown in the preceding sections, price spikes cause changes in fuel consumption. This section 

examines the change in costs across the elasticity cases. Specifically, it examines costs for fuels supplied 

to buildings sector energy consumers and the equipment and shell upgrades that take place in buildings.

Figure 12 presents total expenditures for all fuels supplied to consumers in the buildings sector in the 

different cases simulated. Even with the decreased energy usage, total expenditures for fuels rise 

 13 Energy consumption for residential water heating is also affected by improvements in energy efficiency of water heating 

equipment.
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significantly because of the simulated doubling of fuel prices. Yet, interestingly, total fuel expenditures 

differ when different fuel prices rise. Compared with the Reference case, between 2020 and 2050, fuel 

expenditures increase by an average of $229 billion (2019 dollars) per year in the Electricity Price 

Doubled case, $63 billion per year in the Natural Gas Price Doubled case, and $10 billion per year in the 

Distillate Price Doubled case.

Figure 12. Total fuel expenditures for energy customers in price cases

Figure 13 shows the investment in higher-efficiency equipment, DG systems, and residential shell 

improvements across the cases.14 It combines what buildings sector energy consumers pay for upgrades 

and also what utilities and the federal government pay through tax credit and subsidy programs as 

currently legislated. 

Energy consumers pay a much higher share than the government and utilities in additional costs for 

upgraded equipment and shells. In the Electricity Price Doubled case, the upgrades cost consumers an 

average of $3.4 billion per year more than the Reference case between 2020 and 2050 and cost the 

government and utilities an average of $0.7 billion more per year. 

 14 Results for investment in commercial building shells are not available.
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Figure 13. Consumer, government, and utilities investment in equipment and shells, Reference case 

versus Electricity Price Doubled case

Conclusion

The three possible responses for an energy user to react to an increase in the cost of a particular fuel are 

to switch to another fuel, use that fuel more efficiently, or do without services provided by that fuel. 

Whether one option is more desirable than another, or even possible, depends on many factors. For 

example, lighting demand is powered almost entirely through electricity, and no general service lighting 

runs on natural gas. As a result, an increase in electricity price will not cause fuel switching in lighting, 

but it may persuade building occupants to purchase more efficient light bulbs or to be more aware of 

turning off lights when they are not needed. 

Electricity and natural gas are the most important fuels in the buildings sector. Even though predicting

an exact future price for these fuels is impossible, the simulations described in this report provide a 

range of possibilities to help understand price-demand dynamics, particularly for the buildings sector. In 

the Reference case, electricity accounts for 46% of delivered energy in 2020 and grows to 53% in 2050. 

The share of energy from natural gas is lower and accounts for 42% of delivered energy in 2020 and 39% 

in 2050. Most likely, the high and growing use of electricity results in larger elasticities when the 

electricity price is doubled than when other energy prices are doubled. These interactions, along with 
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the other described changes induced by fuel price increases, help in understanding energy consumption 

and planning for future energy needs.

Appendix 

Table 5. Summary of own-price elasticities in AEO2020 Residential Demand Module and Commercial 

Demand Module (using simulations where fuel price is cut in half between 2020 and 2050)

Short run Long run

Year 1 Year 2 Year 3 Year 30

Residential

 Electricity -0.12 -0.21 -0.25 -0.29

 Natural gas -0.07 -0.12 -0.15 -0.21

 Distillate fuel -0.08 -0.14 -0.17 -0.24

Commercial

 Electricity -0.07 -0.12 -0.14 -0.15

 Natural gas -0.03 -0.19 -0.25 -0.28

 Distillate fuel -0.13 -0.21 -0.25 -0.28

Table 6. Summary of cross-price elasticities in AEO2020 Residential Demand Module and Commercial 

Demand Module (using simulations where fuel price is cut in half between 2020 and 2050)

Change in fuel price

Electricity Natural gas Distillate

Change in fuel use

Residential

 Electricity -- 0.02 0.00

 Natural gas -0.13 -- -0.01

 Distillate fuel -0.18 0.01 --

Commercial

 Electricity -- 0.00 0.00

 Natural gas 0.00 -- -0.01

 Distillate fuel 0.01 0.02 --