The Behavioral Response to Voluntary Provision of an Environmental Public Good:
Evidence from Residen=al Electricity Demand
Grant Jacobsen University of Oregon
Ma.hew Kotchen
Yale University and NBER
Michael Vandenbergh Vanderbilt University
1
“Green” Goods • Growing market for green goods, especially carbon offsets and low-‐carbon products (e.g. hybrids).
• Financial mo=va=on is sufficient for the purchase of some green goods – e.g., energy efficient vehicles or appliances, residenEal weatherizaEon
• Environmental concern mo=vates the purchase of other green goods – e.g., carbon offsets, green electricity – Pay to improve environmental quality
• Policies encourage purchase of both types of these goods.
2
Are green purchases mo=vated by guilt? If so, does it maKer?
3
A New Kind of Rebound Effect?
• “Guilt-‐based” rebound effect – TradiEonal rebound effect occurs when energy efficiency improvements lower the price of an energy service
– Does a “guilt-‐based” rebound effect occur when green goods reduce the guilt associated with polluEng behaviors? • “Behavioral response” • “Non-‐pecuniary” rebound effect
• A psychology perspecEve – Moral licensing (Monin & Miller 2001) – Green consumer behavior (Mazar & Zhong 2010)
4
Some Exis=ng Evidence
• Kotchen & Moore (2008) study the behavioral response to parEcipaEon in a per-‐kWh green-‐electricity program – Program parEcipants paid a 25% premium on their bill to increase the producEon of renewable energy
– Changes the price of electricity – ContribuEon amount linked to consumpEon
• Results: – High consump=on households less likely to join – Par=cipants decreased consump=on aVer joining
• LimitaEon: Could not disentangle the effect of reducing emissions from the effect of the change in the marginal price
5
This Paper
• Evaluates a green electricity program based on fixed monthly contribu=ons – ContribuEons are not dependent on how much electricity is consumed at the residence
– ParEcipaEon does not change the marginal price of electricity
• Evaluates the possibility of a “buy-‐in mentality” – ExisEng research suggests that individuals that make small donaEons do so for different reasons than those that make larger donaEons • Rose-‐Ackerman (1982): Minimum donors “believe they have ‘bought in’ to the enEre range of services provided by the charity”
• DellaVigna et al. (2009): Minimum donors were doing so to avoid the displease of saying “no” to fundraisers 6
Summary of Main Empirical Results
• High-‐consump=on households more likely to par=cipate
• Behavioral response differs with level of par=cipa=on – Voluntary purchase of green electricity increases electricity demand for buy-‐in households by 2.5%
– Behavioral response not large enough to outweigh environmental benefits of green-‐electricity purchase
• Evidence of offset mo=ve, guilt-‐based (non-‐pecuniary) rebound effect and buy-‐in mentality
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Brief Theory
• A representaEve household solves
– is strictly increasing and strictly concave
– is strictly increasing and convex
– is an indicator variable for environmental concern
}:)()({max,
mypxyhyfx yyx=+−+ γ
)(⋅f
)(⋅h
}1,0{=γ
8
Solu=on: Conven=onal Electricity
€
y
€
MB,MC
€
Ù y
€
y €
py
€
ʹ′ f (⋅)
€
ʹ′ h (⋅) + py
9
Availability of Green Electricity
• Green electricity at price • Concern with net emissions • Household’s problem rewri.en
• First-‐order condiEons for an interior soluEon
€
y − g
€
pg
€
g
€
maxx,y,g{x + f (y) −γh(y − g) : x + pyy + pgg =m}
€
y : ʹ′ f (y) = py −γ ʹ′ h (y − g)
€
g : γ ʹ′ h (y − g) = pg
10
Solu=on: Conven=onal & Green Electricity
€
y
€
MB,MC
€
Ù y
€
ı y
€
y
€
ı y − ı g €
py€
py + pg
€
ʹ′ f (⋅)
€
ʹ′ h (⋅) + py
11 PredicEon: ParEcipants increase electricity consumpEon, but net effect is beneficial for environment
Heterogeneity of Direct Benefit of Electricity
€
y
€
MB,MC
€
Ù y
€
ı y
€
y
€
ı y − ı g €
py€
py + pg
€
α ʹ′ f (⋅)
€
ʹ′ h (⋅) + py
Greater alpha:!• Greater conv. elec. !• More likely to participate!• Greater increase in y!• Greater g!• Greater net reduction!
New parameter alpha!
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PredicEon: If green electricity program is moEvated by guilt, then individuals that consume more electricity will be most likely to parEcipate and will make larger donaEons.
The “Buy-‐In” Mentality
Susan Rose-‐Ackerman (1982) If a “donor’s gi< to a par>cular charity is at least equal to some minimum z, the donor believes that he or she has ‘bought in’ to the en>re range of services provided by the charity”
We capture the idea with
€
γ (g;z) =1 if g < z0 if g ≥ z.⎧ ⎨ ⎩
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The “Buy-‐In” Mentality
• Household solves
• Two possible soluEons for – No parEcipaEon – Buy-‐in parEcipaEon where solves
€
maxx, y, g
{x + f (y)−γ (g;z)h(y − g) : x + pyy + pgg = m , g = 0or g ≥ z}
€
{y , g }
€
{ Ù y , 0}
€
{y , z}
€
y
€
ʹ′ f (y) = py
14
Solu=on: To Buy In or Not?
€
y
€
MB,MC
€
Ù y
€
y €
py
€
ʹ′ h (⋅) + py Comparison of surpluses • Not par>cipate • Buy in minus
Two degrees of freedom with "
€
pgz
€
α ʹ′ f (⋅)
€
pgz
15
Buy-‐in Effect
€
y
€
MB,MC
€
Ù y
€
y €
py
€
ʹ′ h (⋅) + py
Larger increase in electricity consump2on with buy-‐in effect
With buy-‐in effect ambiguous net difference
€
α ʹ′ f (⋅)
16 ?"
Empirical Se\ng • Memphis Light, Gas and Water (MLGW) serves 430,00 customers in Shelby County, Tennessee
• Green Power Switch (GPS) program since April 2005 – Chose number of blocks to purchase – Each block is associate with 150 kWh of increased producEon of renewable energy
– Each block costs $4/month
17
GPS Online Sign-‐up
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GPS Program Par=cipa=on
19
GPS Enrollment Levels (N = 910)
20
Data Sets
• Monthly residenEal electricity billing data – May 2003 through Dec 2008 (GPS started April 2005)
– All 885 parEcipaEng households – Sample of 20,205 households
• Match with selected US Census data by zip-‐code – Income, educaEon, race, family size, populaEon density
• Electoral data for 2000 US PresidenEal elecEon – ProporEon for Bush, Gore, Nader 21
Summary Sta=s=cs (N = 20,205)
22
Empirical Analysis
• The par=cipa=on decision – Are households that consume more electricity more likely to parEcipate in the GPS program and, if so, do they purchase more blocks?
• The behavioral response to par=cipa=on – Does electricity demand increase upon parEcipaEon in the GPS program?
– Does electricity demand increase more for parEcipants that simply bought in to the GPS program? • If there is a behavioral response, what is the net effect on emissions? 23
Part 1
• The par=cipa=on decision – Are households that consume more electricity more likely to parEcipate in the GPS program and, if so, do they purchase more blocks?
24
Es=ma=on Strategy
• Regress mean daily electricity consumpEon and zip-‐code level demographic controls on parEcipaEon in the GPS program
• Probit and Truncated regression
25
Consump=on and par=cipa=on
Note: Results are opposite of what has been found for programs based on per kWh pricing 26
Part 2
• The behavioral response to par=cipa=on – Does electricity demand increase upon parEcipaEon in the GPS program?
– Does electricity demand increase more for parEcipants that simply bought in to the GPS program?
27
Es=ma=on Strategy
• Fixed effect regression – DV: ln(kWh/day) – Treatment variable: AcEve enrollment – Individual fixed effects – Month-‐year dummies – Clustered standard errors
• Iden=fica=on assump=on: ParEcipants and non-‐parEcipants would have had similar consumpEon trends absent the GPS program. – Examine potenEal biases by using different subsamples – 2 different subsamples: ParEcipants Only, IniEal Joiners and Controls
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Behavioral Response to Par=cipa=on
€
ln(kWh /dayit ) = βEnrolledit +δMit + vi +ε it
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Behavioral Response to Par=cipa=on
€
ln(kWh /dayit ) = β1Enrollment[1]it + β2Enrollment[>1]it +δMit + vi +ε it
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Net Consump=on (Emissions) Households purchasing blocks > 1
€
y
€
MB,MC
€
Ù y =
€
ı y
€
ı y − ı g €
py€
py + pg
€
ʹ′ f (⋅)
€
ʹ′ h (⋅) + py
Averaged"
510 kwh/month"
Net is -510 kwh/month of conventional electricity!!
Change annual emissions!• 8,129 lbs CO2!• 35 lbs SO2!• 15 lbs NOx!
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Net Consump=on (Emissions) for “Buy-‐In” Households
€
y
€
MB,MC
€
Ù y
€
y €
py
€
ʹ′ h (⋅) + py
€
ʹ′ f (⋅)30 kwh/month"
Averaged"
150 kwh/month"
Net is -120 kwh/month of conventional electricity!!
Change annual emissions!• 1,913 lbs CO2!• 8 lbs SO2!• 13 lbs NOx!
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Summary
• Evidence of offset moEve and buy-‐in mentality – High-‐consumpEon households more likely to parEcipate
– Behavioral response differs with level of parEcipaEon
• Voluntary purchase of green electricity increases electricity demand 2.5% or buy-‐in households
• Behavioral response not large enough to outweigh environmental benefits of green-‐electricity purchase
33
Broader Implica=ons
• Standards and cerEficaEon for green-‐electricity programs – CauEon about the buy-‐in effect – Green-‐E sets minimum of 100 kwh/month buy-‐in
• Some of the first evidence on the moral licensing (indulgence) hypothesis on environmental behavior – Evidence of a non-‐pecuniary (“guilt-‐based”) rebound effect
– Magnitude relaEvely small in our case • Future research on other behaviors
– Green behavior and support for environmental policy?
34