Towards General Equilibrium in a Technology-Rich Model with Empirically Estimated Behavioral Parameters

Bataille, Chris; Jaccard, Mark; Nyboer, John; Rivers, Nic

doi:10.5547/issn0195-6574-ej-volsi2006-nosi2-5

Cited by 50 publications

(35 citation statements)

References 29 publications

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“…One objective of this study is to estimate preference dynamics associated with the adoption of HEVs to improve the behavioral realism of CIMS, an energy-economy model which has been frequently applied to real-world policy research (e.g., Jaccard et al, 2003;Horne et al, 2005;Bataille et al, 2006). In addition to financial attributes, such as purchase price and fuel costs, CIMS represents the intangible costs associated with a new technology, such as consumer perceptions of quality, reliability, availability, social desirability or popularity.…”

Section: Introductionmentioning

confidence: 99%

Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles

Axsen

Mountain

Jaccard

2009

Resource and Energy Economics

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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

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Section: Introductionmentioning

confidence: 99%

Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles

Axsen

Mountain

Jaccard

2009

Resource and Energy Economics

Self Cite

235

111

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“…In more recent years, the twin challenges of energy security and climate change have driven intense modeling efforts, which led in particular to the development of hybrid CGE models (e.g., Bataille et al, 2006, Bosetti et al, 2006, Edenhofer et al, 2006, Schäfer and Jacoby, 2006). …”

Section: Introductionmentioning

confidence: 99%

The resilience of the Indian economy to rising oil prices as a validation test for a global energy–environment–economy CGE model

2009

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“…NEMS uses the details found in engineering-economic models but retains the behavioral analysis found in topdown models, making it a hybrid model. Other examples include the CIMS model (see Bataille et al (2006)). …”

Section: Nems Falls In This Category Nems Is the Model Used By The Umentioning

confidence: 99%

Energy Demand Models For Policy Formulation: A Comparative Study Of Energy Demand Models

Bhattacharyya¹,

Timilsina²

2009

Policy Research Working Papers

127

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This paper critically reviews existing energy demand forecasting methodologies highlighting the methodological diversities and developments over the past four decades in order to investigate whether the existing energy demand models are appropriate for capturing the specific features of developing countries. The study finds that two types of approaches, econometric and end-use accounting, are used in the existing energy demand models. Although energy demand models have greatly evolved since the early 1970s, key issues such as the poor-rich and urban-rural divides, traditional energy resources, and differentiation between commercial and non-commercial energy This paper-a product of the Environment and Energy Team, Development Research Group-is part of a larger effort in the department to study climate change and clean energy issues. Policy Research Working Papers are also posted on the Web at http://econ.worldbank.org. The author may be contacted at gtimilsina@worldbank.org.commodities are often poorly reflected in these models. While the end-use energy accounting models with detailed sector representations produce more realistic projections compared with the econometric models, they still suffer from huge data deficiencies especially in developing countries. Development and maintenance of more detailed energy databases, further development of models to better reflect developing country context, and institutionalizing the modeling capacity in developing countries are the key requirements for energy demand modeling to deliver richer and more reliable input to policy formulation in developing countries. Energy Demand Models for Acronyms and Definitions DefinitionsA few terms appear recurrently in this report: tool, model, method, methodology, approach and framework. We give the dictionary meaning of these terms and indicate how we have used them in this paper.A "tool" is "the means whereby some act is accomplished" or "an implement used in the practice of a vocation". In this paper, we use the term to imply an implement or a kit that is used in analyzing energy demand or forecasting demand or in analyzing the energy system in its part or whole.A "model" is defined as "a simplified description of a complex entity or process". In this paper, we use models to imply a simplified representation of a complex problem or process, often in mathematical terms, that helps us in conceptualizing and analyzing the problem. In this sense, a model can be a tool or can employ a number of tools in a systematic way.A "framework" is defined as "a structure supporting or containing something" or "a simplified description of a complex entity or process". In this paper, we have used this term interchangeably with a model.A "method" is defined as "a way of doing something, especially a systematic way; implies an orderly logical arrangement (usually in steps)". We have used the term to mean a logical, systematic approach for accomplishing a task.An "approach" is defined as the "ideas or actions intended to deal with a problem or situatio...

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Towards General Equilibrium in a Technology-Rich Model with Empirically Estimated Behavioral Parameters

Cited by 50 publications

References 29 publications

Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles

Combining stated and revealed choice research to simulate the neighbor effect: The case of hybrid-electric vehicles

The resilience of the Indian economy to rising oil prices as a validation test for a global energy–environment–economy CGE model

Energy Demand Models For Policy Formulation: A Comparative Study Of Energy Demand Models

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