Residential Energy-Efficient Technology Adoption, Energy Conservation, Knowledge, and Attitudes: An Analysis for Europ

1. Residential Energy-Efficient Technology Adoption, Energy Conservation, Knowledge, and Attitudes: An Analysis for European Countries Bradford Millsa*and Joachim Schleicha,b a Virginia Polytechnic Institute and State University, 314 Hutcheson Hall, Blacksburg 24061-0401, Virginia, USA bFraunhofer Institute for Systems and Innovation Research, BreslauerStraße 48, 76139 Karlsruhe, Germany

2. Background • The household sector accounts for 25% of total final energy consumption in EU27 • Key role in meeting EU targets for greenhouse gas emissions, renewables and energy efficiency • 27% residential energy saving possible (compared to baseline growth) by 2020 through the adoption of cost-efficient residential energy efficient technologies and conservation practices (European Council 2006)

3. Policy • Residential energy policies may increase: • energy conservation practices (e.g. switching off lights when leaving a room, adjust indoor temperature at night, reduce heat in unused rooms, only use dishwasher and washing machines at full load, put lid on pots) • adoption of energy efficient technologies (e.g. insulation of outer walls, attic, window glazing; energy-efficient heating system; purchase energy efficient household appliances, office equipment or light bulbs).

4. Policy • Proper design of residential energy policies requires understanding of: • how technology adoption, conservation practices, energy use knowledge, and attitudes towards energy conservation are associated with household characteristics; • country-specific differences in energy-saving technology adoption and energy conservation in order to generate an appropriate combination of common and country-specific policies.

5. This Paper • Identifies differences in residential energy efficient technology adoption and energy conservation behavior due to household characteristics and country of residence • Explores relationships between household characteristics and household knowledge of energy use and energy-saving technologies and household attitudes towards energy conservation • Employs a unique dataset of almost 5,000 households from eleven European countries • Ten EU countries: Belgium, Bulgaria, The Czech Republic, Denmark, France, Germany, Greece, Hungary, Portugal, Romania • Norway • Is the first attempt to analyze residential energy conservation technologies, behavior, and attitudes jointly for a broad cross-section of European countries

6. Data • Residential Monitoring to Decrease Energy Use and Carbon Emissions in Europe Project (REMODECE) survey conducted in eleven countries in 2007. • Data on project website at: http://www.isr.uc.pt/~remodece/. • Sample contains 4,902 households. • Country sample sizes range from Romania with 622 households to France with 100

7. Dependent Variables • Household adoption of energy efficient technologies - two alternative measures • Index of adoption of energy efficient “white” appliances (refrigerators, freezers, dishwashers, washing machines, and dryers), office equipment, and light bulbs generated by factor analysis • The CFL share of all household bulbs • Household knowledge of energy use index based on three indicators • household knows its annual electricity consumption • household knows what the EnergyStar label stands for • household knows that computer monitor screensavers do not save electricity. • Household energy conservation index based on six indicators of energy conservation practices in home. • fully load the washing machine every time • cook frequently with a pressure-cooker • turn off the lights every time a room is vacated • turn off the TV when it is not being watched • set energy saving features on the computer monitor • set energy saving features on the computer desktop. • Household attitudes toward energy savings are captured through indicators of the stated importance of energy savings for environmental (greenhouse gas reduction) reasons and financial reasons.

8. Covariates and Estimators • Covariates are driven largely by data availability • Highest education level of any member of the household • Household composition • number of members less than 12 years of age • number of members 13 to 18 years of age • number of members 19 to 65 years of age • number of members over 65 years of age • Country specific indicators for Belgium, Bulgaria, The Czech Republic, Denmark, France, Greece, Hungary, Norway, Portugal, and Romania, with Germany being the base country. • Estimation • Continuous indexes estimated with OLS regression models • CFL share of household light bulbs estimated with a Tobit model • Discrete environmental attitude indicators estimated with Probit models.

9. Results

10. Regressions – Technology Adoption Indexes

11. Regressions – Knowledge and Conservation Indexes

12. Regressions – Stated Importance of Energy Savings

14. Conclusions • Knowledge is weakly associated with household energy conservation practices, but not associated with adoption of energy-efficient technologies. • Information campaigns focused strictly on the energy saving characteristics of improved technologies may have a limited impact on diffusion.

15. Conclusions • Environmental and financial concerns can both motivate technology adoption. • Environmental and financial concerns are associated with different education – income groups. • Low education (and presumably low income) households are motivated by financial savings • Energy conservation and energy-efficient technology adoption campaigns targeted at low education and low income households should highlight financial savings • Financial subsidies may also provide disproportionally strong incentives for low education and low income households • Higher education – income groups are more motivated by environmental concerns • Conservation and technology adoption programs targeted to higher education – income groups should highlight positive environmental spillovers

16. Conclusions • Young and middle-aged household cohorts show higher propensities for energy-efficient technology adoption and energy conservation • Motivations also appear to differ with the age structure • Households with younger children placing greater importance on energy savings for environmental reasons • Households with elderly place greater importance on financial savings • Different mechanisms may need to be developed to promote household energy-efficient technology adoption and energy conservation across age-cohorts.

17. Conclusions • Significant cross-country variation remains in propensities to adopt energy-efficient technologies and implement energy conserving practices • Households in Eastern European countries show lower energy-efficient technology adoption • may stem in part from later implementation of energy labeling frameworks. • Households in Eastern European countries also place less importance on electricity savings for environmental reasons • East – West differences in the use of energy conservation practices appear to be less pronounced • Overall the results suggest that effective EU policies to promote residential energy-efficient technology adoption and energy conservation must be sensitive to country differences. • Major challenge - generate a set of uniform EU energy policies that remain flexible enough to address country-specific constraints.