An innovative analytical framework for analysing policy instruments for improved energy efficiency

1. An innovative analytical framework for analysing policy instruments for improved energy efficiency Lena Neij och Luis Mundaca Internationella Miljöinstitutet Lunds Universitet The International Institute for Industrial Environmental Economics Lund University, Sweden

2. Scenarios for future emissions Do the result depend on the models we apply? How, and to what extent, do we include (the factors determining the choice of) energy efficient technologies in our models? What models are we to use to assess policy instruments for energy efficiency? Källa IPCC, 2007 The International Institute for Industrial Environmental Economics Lund University, Sweden

3. Objectives and sub-projects • Identify and explore the wide range of determinantsinfluencing households’ (non-)adoption of energy-efficient technologies • Analyse how different energy models simulate households’ purchase/investment decisions regarding energy-efficient technologies • Analyse/evaluate policy instruments for improved energy efficiency in Swedish households - using an energy (efficiency) model The International Institute for Industrial Environmental Economics Lund University, Sweden

4. Phase I- Determinants of choice • Based on an extensive literature review, we have identified determinants of choice in the (non)adoption of energy-efficient technologies in households • We present different determinants of choice applied for different types of technologies • The results show that capital cost prove to have an important influence on technology choice • However, the results clearly suggests that a broader set of determinants need to be considered and that different determinants will influence households’ technology choice in different markets under different circumstances and for different technologies The International Institute for Industrial Environmental Economics Lund University, Sweden

5. Phase I- Determinants of choice Investments in energy-efficient buildings Important determinants of choice • Comfort, reduction of noise • Investment and operating cost • Aesthetic appearance Important aspects– age of the house, frequency of moving, ownership Barriers for investment - space constraints, loss of storage space The International Institute for Industrial Environmental Economics Lund University, Sweden

6. Phase I- Determinants of choice Investments in energy-efficient lighting systems Important determinants of choice • Design, aesthetics, availability, compatibility, performance, quality • Investment cost • Operating cost Studies show that the use of CFLs decreases with age. The International Institute for Industrial Environmental Economics Lund University, Sweden

7. Phase I- Determinants of choice Investments in energy-efficient consumer appliances Important determinants of choice • Size, brand (seen as a guarantee for quality) • Investment cost • Operating cost The International Institute for Industrial Environmental Economics Lund University, Sweden

8. Phase I- Determinants of choice Discount rates • Many energy models use discount rates to simulate the households decision making process and their actual purchase of new (energy efficient) technologies • The literature review indicates that real (or normal/private) discount rates applied in energy models are in the range of 3-20 percent • Extensive literature show that consumers use much higher implicit discount rates • building envelope: 10-30 percent • appliances: 20-300 percent The International Institute for Industrial Environmental Economics Lund University, Sweden

9. How can we improve modelling of investment in energy effcient technologies? • The key question now is to what extent a better representation of empirically estimated determinants of choice is actually feasible in energy modelling tools • Which determinants are more workable than others in improving such tools in practice • What can be done in order to bridge the gap regarding real and implicit discount rates? The International Institute for Industrial Environmental Economics Lund University, Sweden

10. Phase II – Review of energy models In the second phase of the project we • review numerous existing bottom-up energy (efficiency) models and examine their decision-making rules to technology investments • analyse the approaches undertaken to evaluate energy efficiency policy instruments using the models reviewed • highlight advantages and disadvantages of the models regarding their approach to model technology choice in energy efficiency in households • identify key areas to further improve models for energy efficiency policy analysis targeting the household sector The International Institute for Industrial Environmental Economics Lund University, Sweden

11. Phase II - Review of energy models The International Institute for Industrial Environmental Economics Lund University, Sweden

12. Phase II - Review of energy modelsDrivers for energy demand forecasting • Mostly exogenous socio-economic and demographic factors: GDP, population, household size (e.g. MESSAGE, MARKAL) • ‘Activity levels’ are usually determined: housing stock, GDP per capita (e.g. LEAP, WEM, BUENAS) • A function of energy price (e.g PRIMES, REEPS), household growth rate (e.g. MURE), location (e.g. NEMS) or product stock (e.g. NIA, PAMS) The International Institute for Industrial Environmental Economics Lund University, Sweden

13. Phase II - Review of energy models Features of policy modelling approaches based on case studies • Research goals? Difficult to generalise; research assumptions/outcomes are case and context-specific • Modelled energy efficiency policy instruments? Large variety; great focus on minimum performance standards • Policy modelling approach? Mostly done through economic and technological ‘handles’ (e.g. energy intensity, tech. market availability & penetration, discount rates) • Approach to address barriers for implementation? Not explicitly addressed; they “exist” in historical data; discount rates are sometimes used The International Institute for Industrial Environmental Economics Lund University, Sweden

14. Phase II - Review of energy models Identified challenges (so far) to further advance models • Modelling dimension • Techno-economic dimension • Human-behavioural dimension • Policy analysis dimension The International Institute for Industrial Environmental Economics Lund University, Sweden

15. Phase II - Review of energy models Tentative conclusions • Get the right model to answer corresponding policy questions (e.g. impacts and/or outcomes) • Quantitative simulation of household behaviour is very difficult and complex • Need for more policy evaluation criteria and other methods to complement modelling tools/outcomes • Importance of careful scenario development to guide modelling work The International Institute for Industrial Environmental Economics Lund University, Sweden

16. Phase III – Policy analysis(2009-2010) • Chose and adapt/modify one of the models (Reeps, Nems?) • Apply Swedish data to the model • Analyse Swedish policy instruments for energy effciency The International Institute for Industrial Environmental Economics Lund University, Sweden

17. Tack! Lena Neij and Luis Mundaca International Institute for Industrial Environmental Economics (IIIEE) Lund University P.O. Box 196 (visiting address: Tegnérsplatsen 4) SE-221 00 LUND Phone: +46 46 222 02 68 Fax: +46 46 222 02 30 E-mail: Lena.Neij@iiiee.lu.se Homepage: http://www.iiiee.lu.se The International Institute for Industrial Environmental Economics Lund University, Sweden