1. Determinants for the take-up of energy efficient household appliances in Germany SECO@home Joachim Schleich (Co-Author: Bradford F. Mills) Fraunhofer ISI Projektreffen, 4.Juli 2008, ZEW Mannheim

2. Overview determinants characteristics of the household (occupants) characteristics of the residence characteristics of the measure (technology) economic factors weather and climate factors information diffusion attitudes/preferences towards the environment

3. Background Major household appliances –35 percent of EU-15 residential end-use electricity consumption European Council Action Plan –27 percent residential energy savings by 2020 Regulation: appliance energy consumption labeling scheme –Observable, uniform, and credible energy consumption standards (Class A – Class G) –Increase demand for energy-efficient appliances –Generate producer incentives

4. The Labeling Scheme EU implementing directives –1994 for refrigerators, freezers, combinations –1995 for laundry machines –1997 for dishwashers German national law –one of last EU Member States to implement –Start of 1998 for refrigerators, freezers, laundry machines –March 1999 for dishwashers

5. Data December 2002 multi-topic survey of an existing representative panel of German households 15,526 households with refrigerators 12,943 households with freezers 6,993 households refrigerator – freezer units 12,814 households with dishwashers 19,014 households with washing machines

7. Research Context Snap-shot 4-5 years into implementation for most major kitchen and laundry appliances: –knowledge of labeling scheme –purchase of class-A appliances Empirical problem –Only households aware of energy labeling scheme respond to questions on appliance energy class May not have purchased after implementation May have purchased, but do not know –Knowledge-based selection bias Observed and unobserved heterogeneity

8. Statistical Model Two latent variables – choice of class-A appliance latent measure of household preferences Purchase decision only observed if energy-class is known

9. Statistical Model (cont.) Knowledge of energy class also a latent variable Joint estimation of 2 latent variables 1 to N 1 energy-class of appliance known and class A chosen N 1 +1 to N energy-class known and class A not chosen, N+1 to M energy class not known

10. Results

12. Results (cont.)

14. Conclusions Energy label information will diffuse slowly –Long life span of major appliances –Little evidence for increases in purchase propensities over time Consumers' awareness increases with –regional power prices –PC ownership Household characteristics have little impact Propensity to purchase class-A strongly correlated across appliance types –Need to identify factors underlying common propensities

15. Analyzed determinants characteristics of the household characteristics of the residence (characteristics of the measure economic factors (incomplete) weather and climate factors (information diffusion) attitudes/preferences towards the environment (indirectly)

16. Next steps Analyze data from EU Project (REMODECE) for several MS (plus Nor); Smaller Dataset; no information on income; Additional Information: age of appliance Allow for attitudes; Analyze differences across EU countries