Using Behavioral Economics to Save the World:

Two studies on behavioral economics and climate policy

Benjamin HoCornell University

Johnson Graduate School of Management

Nov 18, 2008

Rebuilding my credibility

• The Bush White House looks different from the inside. (Maybe I drank the Kool Aid.)

• Not so much anti-science so much as scientists are anti-economics.

• A parable.

?

Science Policy

Science PolicyEconomics

Environmental Economics

Science Economics Politics Policy

Environmental Economics

Behavioral Economics

Plan

Two Studies:

Study 1: Using behavioral economics to “manipulate” the electorate.

Study 2: Voluntary carbon offset markets in a carbon-constrained regulatory environment.

Study 1: Paying for Climate Change: The Role of Social Information on Voter

Willingness to Pay

Antonio BentoCornell University

Benjamin HoCornell University

Gregory PoeCornell University

Two Motivating Stories

• New York Times survey on support for higher gasoline tax.

Culpability (guilt/responsibility) Matters.

• Nudge (Sunstein and Thaler) story on electric power usage and social norms.

Big Picture: How does knowing ones carbon footprint affect voter attitudes toward climate mitigation.

Addressing two literatures

1. What climate mitigation policies shouldvoters accept?Not which policies they will accept!

2. The role of behavioral/psychological factors in shaping decision making.But not normally applied to how they vote!

Background on Behavioral Economics and Public Goods

• Altruism (Becker, etc.) U(a) = u(y) + θu(Y)– People care about the welfare of others.

• Fairness (Fehr-Schmidt) U(a) = u(y) + αv(Y-y)– People care about how equitable society is.

• Warm-glow (Andreoni) U(a) = u(y) + βv(a)– People just like doing good.

• Social Norms (Schulze, etc.) U(a) = u(y) + ηv(A-a)– Powerful (see Shang Croson)

• Culpability (in the sense of degree of responsibility)– We will manipulate how culpable people feel.– We will measure how WTP depends on amount of responsibility.

Overview of Experimental Design

1. Elicit Willingness to Pay for Climate Policy

2. Show subject’s Footprint AND <treatment>

– Average footprint of others in their State

– Average footprint of others in their County

– A High average

– A Low average

3. Elicit Willingness to Pay Again

Calculate Carbon Footprint

Based on:

1. Housing characteristics

2. Energy usage (Utility bills)

3. Commuting habits (and Flying)

Information about Climate

• Give climate projections from UN Inter-governmental Panel on Climate Change

• Ask what policy option for carbon reduction people would prefer:1. Aggressive Reductions

2. Moderate Reductions

3. Small Reductions

Elicit WTP

“What is the highest cost you could be asked to pay and still vote yes for this climate change option? This cost would be an annual cost borne every year for the foreseeable future. It would come in the form of higher taxes and higher prices on goods that contribute to climate change.”

Four Treatment Groups

• Control:– Show only subject’s own

calculated carbon footprint

• Treatment:– Show Average County

Footprint

– Show Average StateFootprint

– Show High Avg Footprint

– Show Low Avg Footprint

Elicit WTP after Treatment

• Re-Elicit individual WTP

• Also Elicit

– WTP if everyone had to pay.

– WTP if costs based on Income.

– WTP if costs based on carbon Footprint.

Other WTP questions in detail

Demographics of Sample (and why students wouldn’t work)

• Political: Dem 37%, Ind 24%, Rep 26%

• Average Household Size: 2.9

• Average Age: 43

• Average Income close to US average

• Married: 56%

• Gender: 55% female

• Race: 85% White, 10% Black/Hispanic

• Educ: 24% HS, 41% < 4 yr college, 34% 4yr+

Percent who Increased WTP by Treatment

0%

5%

10%

15%

20%

25%

30%

all low CO2 high CO2

Control

Saw High Average

Saw Low Average

Percent who Increased WTP by Treatment by Low/High footprint

0%

5%

10%

15%

20%

25%

30%

all low CO2 high CO2

Control

Saw High Average

Saw Low Average

Summary of Treatment Effects

• Information about Carbon Footprint out of context has no effect on behavior.

• Information about Carbon Footprint affects those with low footprint, but not those with high footprint.

• People appear to believe their own footprint was appropriate and used information to judge culpability of others.

Other Social Preferences at Work

• Altruism (Becker, etc.) U(a) = u(y) + θu(Y)Compare individual WTP ($181) vs all WTP ($137)*

• Fairness (Fehr-Schmidt) U(a) = u(y) + αv(Y-y)Compare all WTP ($137) with income based WTP ($204)*

• Warm-glow (Andreoni) U(a) = u(y) + βv(a)<in progress>

• Social Norms (Schulze, etc.) U(a) = u(y) + ηv(A-a)<in progress>

• Culpability (in the sense of degree of responsibility)Compare all WTP ($137) with footprint based WTP ($163)*

Practical Implications of Experiment

• Policy design.– How distribution affects ability to implement a

policy (by income, by responsibility, etc.)

– How should policy makers “sell” policies to voters.

• Simple policy nudges/Soft paternalism.– How should we disclose information

– How to manipulate public opinion and behavior.

• Role of Carbon Footprint Calculators

• Impact of opinion polls on outcomes

Study 2: The Role of a Voluntary Offset Market in a Carbon Constrained Environment

Antonio BentoCornell University

Benjamin HoCornell University

Derek SixEnvironmental

Credit Corp.

Hugh WhalenEnvironmental

Credit Corp.

Potential Size of Voluntary Offset Market

Electricity Generation

Transportation

Combustion of fossil fuels for

heating, manufacture, etc

Manufacture of materials, chemicals

Agricultural Land Management

Agricultural Methane Capture

Landfill Methane Capture/Landfill Diversion

Coal Mine Methane Capture

Wastewater Methane Capture

Reduction of Natural Gas System Emissions

Reduction of PFC loss in manufacturing

Reduction of SF6 loss in Electrical Distribution

HFC-22 Production

Who buys offsets?

Two main groups:1. Industries who expect to be regulated in the

future.– To build relationships, to offset future regulation, to

practice, etc.

2. Retailers/Consumers– Due to Warm Glow– Due to Altruism– Due to Social Norms– Due to Guilt and Culpability– Due to Competition and Social Comparisons

Policy Issues

• Should offset projects be included in Cap and Trade regulation?

• How should current projects be grandfathered into future regulation?

• What are the implications for the voluntary offset market?

Note, if we implemented a Carbon Tax rather than Cap and Trade, these headaches all go away!

Main economic considerations

• Including Offsets could lead to significant cost reductions (likely in the form of lower energy price increases) in meeting emissions targets

• Which offsets are included could lead to significant reallocations of jobs in the economy (green collar, agricultural, energy, automotive, etc.)

• Allowing offsets could slow technological development in the regulated sectors.

• Allowing offsets could worsen the reliability of carbon reductions.

Conclusions

• Smart Policy requires an understanding not just science, and not just economics, but also political and behavioral/psychological factors.

– To understand both how to get policy accepted.

– But also what will be the potential effects.

Science Economics Politics Policy

Environmental Economics

Behavioral Economics

Appendix: Factors Impacting Voluntary Pricing1. Standards Used, Third-Party Verification- some buyers perceive different

levels of scientific and environmental integrity

2. Possibility that purchase might be applicable to current or future regulation (direct credit or early action)- standards, project types, and locations influence potential applicability

3. Ability to use the purchase for current commitments- CCX, EPA Climate Leaders

4. Geographic location- some buyers prefer US based projects, some even prefer projects from their state or town

5. Project types- different types of projects may have different marketing value to retail consumers or for advertising value

6. Other Social/Environmental impacts of the projects- buyers value projects which provide co-benefits

7. Additionality- some buyers prioritize projects which can most clearly demonstrate that they would not have occurred without carbon funding

8. Vintage year- some buyers believe that their purchases should correspond to the timing of their emissions, and value more recent reductions more highly