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Arnaud Blaser

Arnaud Blaser

 About Arnaud

Arnaud is currently a PhD candidate at the Institute of economic research (IRENE), Neuchâtel University (Switzerland). He engaged in his PhD research following an MSc degree in Environmental Economics and Environmental Management (EEEM) at the University of York (UK) and an initial economics formation (B.A) from the University of Fribourg (Switzerland). When not busy tackling environmental questions through computer-based econometrics he also like going out on the field to help out environmentally friendly projects. The last example was Costa Rica, where he recently participated during three months to a reintroduction and monitoring mission of the endangered red and great green macaws. 


Research interest and current project

His global research interests encompass all topics linking human activities with its surrounding natural environment from an economics perspective, such as agriculture, climate change impacts, natural resource management and valuation or energy use and production. His current research project focuses on the microeconomics of energy efficiency, specifically the rebound effect. This effect can be roughly defined as the loss of potential energy savings due to behavior change following an increase of energy efficiency.  For instance, if a consumer purchases a new car consuming 10% less gasoline then the price of driving one mile is decreased, providing under classical economics assumptions an incentive to drive more miles and thus the net energy savings will be less than 10%. In this frame SSI Web will be used primarily to collect information about respondents’ energy use and to run a choice experiment featuring improved (more energy efficient) goods than currently hold by the household in order to analyze their stated variation of usage following a change of efficiency. This project is financed by the Swiss National Science Foundation (SNSF) under the grant N°100018-14431.


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Lighthouse Studio

Lighthouse Studio is our flagship software for producing and analyzing online and offline surveys. It contains modules for general interviewing, choice-based conjoint, adaptive choice-based conjoint, adaptive choice analysis, choice-value analysis, and maxdiff exercises.

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