According to intuition and theories of diffusion, consumer preferences develop along with technological change. However, most economic models designed for policy simulation unrealistically assume static preferences. To improve the behavioral realism of an energy-economy policy model, this study investigates the ''neighbor effect,'' where a new technology becomes more desirable as its adoption becomes more widespread in the market. We measure this effect as a change in aggregated willingness to pay under different levels of technology penetration. Focusing on hybrid-electric vehicles (HEVs), an online survey experiment collected stated preference (SP) data from 535 Canadian and 408 Californian vehicle owners under different hypothetical market conditions. Revealed preference (RP) data was collected from the same respondents by eliciting the year, make and model of recent vehicle purchases from regions with different degrees of HEV popularity: Canada with 0.17% new market share, and California with 3.0% new market share. We compare choice models estimated from RP data only with three joint SP-RP estimation techniques, each assigning a different weight to the influence of SP and RP data in coefficient estimates. Statistically, models allowing more RP influence outperform SP influenced models. However, results suggest that because the RP data in this study is afflicted by multicollinearity, techniques that allow more SP influence in the beta estimates while maintaining RP data for calibrating vehicle
After nearly two decades of debate and fundamental disagreement, top-down and bottom-up energy-economy modelers, sometimes referred to as modeling 'tribes', began to engage in productive dialogue in the mid-1990s (IPCC 2001). From this methodological conversation have emerged modeling approaches that offer a hybrid of the two perspectives. Yet, while individual publications over the past decade have described efforts at hybrid modeling, there has not as yet been a systematic assessment of their prospects and challenges. To this end, several research teams that explore hybrid modeling held a workshop in Paris on April 20-21, 2005 to share and compare the strategies and techniques that each has applied to the development of hybrid modeling. This special issue provides the results of the workshop and of follow-up efforts between different researchers to exchange ideas. 1. THE oRiGinAL BoTToM-uP / ToP-DoWn DiviSion Policy-makers are interested in a better understanding of the effectiveness and cost of policies whose purpose is to shift energy systems toward more environmentally desirable technology paths. What technologies would serve this purpose, and how could or would the economy adapt in response to policy to
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