1. The differential effects of energy-efficient technology adoption and energy policies: A research note Brad Mills & Joachim Schleich February 2010

2. Objective Assess distributional effects of increased diffusion of energy-efficient appliances Basis: findings from seco@home „Appliances Paper“ for German Data Set (20.000 observations)

3. Methodology Result from Mills/Schleich (2010): income has no statistically significant effect on diffusion of class-A appliances Focus on cool appliances: run 24/7 Same electricity cost savings for all income classes Need to calculate electricity cost savings from increased diffusion of class-A appliances

4. Electricity expenditure density estimates by income group

6. Summary For lower income households energy savings are higher as share of electricity costs For lower income households energy savings are higher as share of net income Increased diffusion of energy-efficient appliances associated with progressive income effects (c.p.) Incentives (via policies) result in higher relative savings in poorer households

7. Energy Efficient Appliance Choice under the EU Labeling Scheme Brad Mills & Joachim Schleich February 2010

8. Objectives Analyze determinants of Consumer knowledge of energy label Choice of appliance by energy class New: Allow for country-specific effects (compliance rate; electricity prices)

9. Introduction EU appliances labeling directives 1994 for refrigerators, freezers, combinations 1995 for washing machines 1997 for dishwashers Implementation dates differ across MS

10. Introduction

11. Data Multi country common survey in 11 EU Member States in 2007 5000 observations (household level) Mix of online and telephone surveys Appliance energy class for refrigerators, freezers, refrigerator and freezer combination units, dishwashers, and washing machines Socio-economic and technical variables Energy conservation behavior (create index) Knowledge of energy efficiency measures (create index) Relevance of energy costs and environmental motives

12. Labelling compliance rates

13. Empirical challenge Only households aware of energy labeling scheme respond to questions on appliance energy class Households may have purchased a particular class, but do not know Positive responders may have different observed and unobserved attributes Leads to knowledge-based selection bias if only positive responders are included in analyses

14. Model Model knowledge of energy class as Bivariate Probit Model appliance choice as Ordered Probit (for purchase within last five years) Joint estimation

15. Results Knowledge Equation

16. Results Appliance Choice Equation

17. Results Knowledge index significant for knowlege equation Efficiency index significant for knowlege equation, less so for choice equation Sociodemographics matter, but not all that much: – Age with negative effect on knowledge, less so on choice – Education with positive effect on knowledge, less so on choice Power prices matter for knowledge, less for choice Labelling compliance affects knowledge, less clear for choice Motives – Electricity savings matter for knowledge, but not for choice – Global warming has not effect on either knowledge or choice