consumer inattention, heuristic thinking and the role of ... 2016/6.1... · consumer inattention,...

Consumer Inattention, Heuristic Thinking andthe Role of Energy Labels

envecon 2016

Mark Andor, Andreas Gerster, Stephan Sommer

March 18th, 2016

• Consumers are inattentive to opaque valuecomponents

• Trade-off between visible up-front cost andoperating cost => „Energy Efficiency Gap“

• Energy efficiency labels to bridge this gap => decision heuristics

• Discrete choice experiment with different information treatments

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

Motivation

1. Introduction

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• Mainly focused on the US

• Newell and Siikamäki (2014): Both the inclusion of annual electricity cost and energy efficiency ratings lead to a higher WTP for energy efficiency

• Houde (2014): three types of consumers; those that rely predominantly on the label, those that rely on electricity cost, those that do not consider energy efficiency information at all.

• Allcott and Taubinsky (2015): Information provision raises WTP for energy efficient light bulbs


Literature

1. Introduction

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• Agreed upon in 1992, firstly shownon appliances in 1995

• Ecodesign directives banrefrigerators that are less efficientthan A+

• Assignment of label class follows:

𝐸𝐸𝐼 =𝐸24ℎ∗364

𝑉𝑒𝑞∗𝑀+𝑁+𝐶𝐻∗ 100


The EU Label

2. The EU Energy Efficiency Label

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• Discrete choice experiment with four choice sets in three experimental groupsamong about 5,000 households in Germany.

• We implement two treatments: Provision of annual cost information (𝑇𝐶) andFurther attributes that are unrelated to energy efficiency (𝑇𝑆)


Experimental Design and Data

3. Conceptual Model

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Conceptual Model and Hypotheses

3. Conceptual Model

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• Slight modificaiton of Della Vigna (2009) and Geraden et al. (2015)

• Given cost-minimizing behavior, consumers choose the energy efficient alternative A if its perceived present value of costs (PPVC) is smaller than that of alternative B:

𝑃𝑃𝑉𝐶𝐴 − 𝑃𝑃𝑉𝐶𝐵 = ∆𝐾 + 𝜃 𝑁, 𝑆 𝑃𝑉𝑂𝐶 + 𝜏(𝑁, 𝑆)∆𝐸𝐶

Hypothesis Choice Sets Identification Strategy

Cost I and II Additional cost information on the label

Stimuli I and II Additional attributes on the label

Heuristic III Difference in efficiency classes, when ∆𝑃𝑉𝑂𝐶 ≈ 0

Ambiguity IVAdditional cost information/attributes, when either ∆𝑃𝑉𝑂𝐶 ≈ 0 or ∆𝐸𝐶 = 0

• 65% of the respondents are willing to pay at least 30 Euro for a higher efficiencyclass, which should only be worth 3 Euro.


Heuristics Hypothesis

4. Results

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Choice Set III (1) Choice Set III (2)

Cons 0.651** (0.007) 0.270** (0.040)

Female 0.096** (0.016)

Age 0.004** (0.001)

Pro-environmental attitudes 0.030 (0.026)

Middle low income 0.073** (0.020)

Middle high income 0.065** (0.023)

High income 0.058* (0.029)

Uninformed 0.055** (0.017)

Secondary school 0.063** (0.020)

College preparatory degree 0.022 (0.024)

Number of observations 4,808 4,063

• Providing cost information increases the probability to take up the more energyefficient appliance by 2.9%

• Increasing the number of stimuli decreases the choice of it by 2.2%


Cost and Stimuli Hypotheses

4. Results

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Choice Sets I and II

Cons 0.863** (0.007)

TC 0.029** (0.010)

TN -0.22* (0.011)

Number of observations 9,641

• Providing cost information decreases the probability to take up the more energyefficient appliance by 4.2%, when no differences in electricity usage are present(information substitution)

• It fosters the uptake when appliances do not differ in efficiency classes


Ambiguity Hypothesis I

4. Results

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Choice Set III Choice Set IV

Cons 0.656** (0.012) 0.714** (0.011)

TC -0.042* (0.017) 0.070** (0.015)

TN 0.025 (0.017) 0.000 (0.016)


• Decreasing utility to income

• Choice of energy inefficient appliances when the environment is cognitivelydemanding


Ambiguity Hypothesis II

4. Results

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Coeff. Std. Err. Coeff. Std. Err.

TC -0.247* (0.099) 0.079 (0.093)

TN 0.059 (0.098) 0.080 (0.096)

TC # High income 0.013 (0.070) -0.150* (0.065)

TN # Secondary school -0.034 (0.049) -0.132** (0.046)

TN # College preparatory degree 0.042 (0.067) -0.133* (0.054)


• A large share employs the label as a decision heuristic

• Providing cost information has ambiguous effects on the uptake of energyefficient appliances

• Label complexity decreases attention to operating cost for individuals with loweducational attainments.

• Results indicate potential to reduce welfare losses from both internalities andexternalities

• Adjust innovation policy


Conclusion

5. Conclusion

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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.

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.

Hossain, T., Morgan, J., 2006. . . . plus shipping and handling: Revenue (non) equivalence in field experiments

on ebay. B.E. Journal of Economic Analysis and Policy: Advances in Economic Analysis and Policy 6 (2),

1-27.

Houde, S., 2014. How consumers respond to environmental certification and the value of energy information. NBER working paper No. 20019

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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