the Role of Energy Labels IAEE 2017 Mark Andor, Andreas Gerster, - - PowerPoint PPT Presentation

Consumer Inattention, Heuristic Thinking and the Role of Energy Labels

IAEE 2017 Mark Andor, Andreas Gerster, Stephan Sommer

August 24th, 2016

2 Consumer Inattention, Heuristic Thinking and the Role of Energy Labels

In brief

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Energy labels are an important policy instrument to increase investment in energy efficient appliances Motivation Methodology Stated-choice experiment with randomized information treatments Contribution How can energy labels with efficiency classes be made more effective? Extend the conceptual model of energy efficiency investment decisions Investigate whether households have a willingness to pay for efficiency class differences per se

Analyze the effects of enhancing the salience of energy costs as well as increasing the number of stimuli competing for attention

Investigate the channels through which the treatments operate

• Behavioral economics suggest that consumers might be

inattentive to energy costs in purchase decisions of appliances

• Consumers are inattentive to opaque value components (e.g. Chetty et al.

2009, AER)

• Consumers use decision heuristics when processing information (e.g.

Lacetera et al. 2012, AER)

• „Energy Efficiency Gap“: low tendency of consumers to invest into

cost-effective energy efficiency technologies

• To bridge this gap, energy labels have been introduced worldwide
• Literature is scarce and focused on the US energy labels (Newell

and Siikamäki, 2014, JAERE; Houde, 2014, NBER)

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Motivation

Introduction

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Overview of the experimental design

Experimental Design

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• Stated-choice experiment with four randomly ordered binary choice sets
• Randomized information treatments: a control group and two treatment

groups Experimental Groups (Randomized) Control group Treatment group I Treatment group II Choice Sets (Randomized) M1 M1 M1 M2 M2 M2 S1 S1 S1 S2 S2 S2

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Choice Sets

Experimental Design

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• Participants repeatedly chose between two refrigerators that differ in

purchasing price and energy use.

• Example: Choice Set M1 in the Control Group

• Control group:

Simplified version of the EU label

• Treatment group I:

Provision of annual cost information

• Treatment group II:

Additional non-energy related product attributes

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Treatments

Experimental Design

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Treatment group I Annual Operating Cost Condition Treatment group II Competing Stimuli Condition Control group

• Stated-choice experiment using the household panel of the survey institute

forsa, which is representative for Germany

• Random assignment of experimental groups and random sequence of

choice sets

• We estimate a linear probability model, which gives a consistent estimator

for the average treatment effect (Angrist and Pischke, 2009)

• As a robustness check, we estimate logit and probit models: the results are the same
• Dependent variable: 1 if energy efficient appliance is chosen

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Empirical Strategy

Results

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Hypotheses

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• Heuristics Hypothesis: households value efficiency class differences per se, i.e.

independent of energy consumption Choice set ∆𝐿 ∆𝑙𝑋ℎ ≙ ∆𝑄𝑊𝑃 ∆𝐹𝐷 M1 70 40 Yes M2 70 60 Yes S1 30 1 Yes S2 70 40 No

Heuristics Hypothesis

• 65% of the respondents are willing to pay at least 30 Euro for a higher

efficiency class, although electricity consumption is only marginally lower (1 kWh)

• Individuals with high information cost resort to the heuristic more often

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Heuristics Hypothesis

Results

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Choice set S1 Constant 0.649** (0.007) 0.373** (0.035) College degree

• 0.046**

(0.020) Uninformed 0.056** (0.017) Additional control variables  Number of observations 4,596 3,886

Note: Standard errors are in parentheses. **,* denote statistical significance at the 1 % and 5 % level, respectively .

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Hypotheses

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Cost Hypothesis: Enhancing the salience of operating cost raises the probability of choosing the more energy efficient appliance Stimuli Hypothesis: Increasing the number of competing stimuli, i.e. further product characteristics that are unrelated to energy use, leads to less frequent choices of the energy efficient appliance Choice set ∆𝐿 ∆𝑙𝑋ℎ ≙ ∆𝑄𝑊𝑃 ∆𝐹𝐷 M1 70 40 Yes M2 70 60 Yes S1 30 1 Yes S2 70 40 No

Cost and Stimuli Hypotheses

• Providing cost information increases the probability to choose the more

energy efficient appliance by 3.2%

• Increasing the number of stimuli decreases the choice probabilities by

2.2%

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Cost and Stimuli Hypotheses

Results

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Choice sets M1 and M2 Constant 0.861** (0.007) Treatment I: Annual Operating Cost 0.032** (0.010) Treatment II: Competing Stimuli

• 0.022*

(0.011) Number of observations 9,193

Note: Standard errors are in parentheses (for M1 and M2 clustered at the individual level). **,* denote statistical significance at the 1% and 5% level, respectively.

• A large share of respondents has a WTP for efficiency class differences =>

indicator of existence for decision heuristics

• Providing cost information and reducing the number of competing stimuli

increases the choice of energy efficient appliances in market settings

• When the energy label contains energy efficiency classes, the energy cost

information works by two channels:

• It increases the attention to operating cost
• And decreases the valuation of efficiency class differences

Based on the results, we expect positive welfare effects of adding estimated annual energy costs on the EU energy label

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Conclusions

Conclusion

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Paper: USAEE Working Paper No. 16-287. Further related studies:

› Andor/Fels: Behavioral Economics and Energy Conservation – A Systematic Review

• f Non-price Interventions and their Causal Effects (SFB 823 Discussion Paper #14)

› Andor/Gerster/Götte: The Role of Social Information, Incentives and Habits in Household Electricity Consumption (End of 2017) › Andor/Gerster/Peters: Information Provision and Residential Energy Consumption (Autumn of 2017) › Andor/Gerster/Peters/Schmidt: Social Norms and Energy Conservation beyond the US (Working Paper, next week)

Thank you for your attention!

• Dr. Mark Andor

E-Mail: andor@rwi-essen.de

Allcott, H., Taubinsky, D., 2015. Evaluating behaviorally motivated policy: Experimental evidence from the lightbulb market. American Economic Review 105 (8), 2501-2538. Chetty, R., Looney, A., Kroft, K., 2009. Salience and taxation: Theory and evidence. The American Economic Review 99 (4), 1145-1177 DellaVigna, S., 2009. Psychology and economics: Evidence from the field. Journal of Economic Literature 47 (2), 315-372. Gerarden, T., Newell, R. G., Stavins, R. N., et al., 2015. Deconstructing the energy-efficiency gap: Conceptual frameworks and evidence. American Economic Review 105 (5), 183-186. Houde, S., 2014. How consumers respond to environmental certification and the value of energy

• information. NBER working paper No. 20019

Lacetera, N., Pope, D. G., Sydnor, 2012. Heuristic Thinking and Limited Attention in the Car

• Market. American Economic Review 102(5): 2206-2236

Newell, R. G., Siikamäki, J. V., 2014. Nudging energy efficiency behavior: The role of information

• labels. Journal of the Association of Environmental and Resource Economists 1 (4), 555-598.

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Literature

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Choice Sets

• 3. Conceptual Model

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Choice set Alter- native Purchase price Electricity consump- tion Efficiency label Opera- ting cost Cooling compart- ment Freezing compart- ment Noise level Picture I A 239 80 A+++ 22 105 14 37 D B 169 120 A++ 34 106 15 39 C II A 449 120 A++ 34 104 14 39 C B 379 180 A+ 50 105 13 38 D III A 309 160 A+ 45 104 15 37 B B 239 200 A+ 56 106 14 38 A IV A 289 153 A++ 43 106 15 38 C B 259 154 A+ 43 104 14 39 A In C    In TC     In TN       

• Newell and Siikamäki (2014, JAERE): The inclusion of

annual electricity cost and energy efficiency ratings lead to a higher WTP for energy efficient heat pumps

• Houde (2014, NBER): three types of consumers; those

that rely on the label, those that rely on electricity cost, those that do not consider energy efficiency information at all

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Literature has focused on the US energy labels

Introduction

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