Open access
Date
2021-07Type
- Working Paper
ETH Bibliography
yes
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Abstract
For more than forty years analysts have pointed out that society might be too slow in adopting energy efficiency technologies, a phenomenon known as the Energy Efficiency Gap. There are persistent market barriers that impede these efforts. Eliciting these barriers and their heterogeneity is key for policy design. In this paper, we use narratives, a novel approach based on unstructured text answers in surveys, to elicit the barriers and determinants of energy efficiency investments. Using recent advances in Natural Language Processing (NLP), we turn narratives into quantifiable metrics to rank households’ barriers and determinants. We find that financial motives are not the primary barriers or determinants of energy efficiency investments. Instead, we find that such investments are highly opportunistic and co-benefits, such as ecological concerns and comfort, also play an important role. Although there is substantial heterogeneity across the population in the type of barriers and determinants, demographics and building characteristics poorly predict heterogeneity patterns. This has important implications for the targeting of policies. Narratives could be a novel and effective way to implement policy targeting. Show more
Permanent link
https://doi.org/10.3929/ethz-b-000495755Publication status
publishedJournal / series
Economics Working Paper SeriesVolume
Publisher
CER-ETH – Center of Economic Research at ETH ZurichSubject
energy efficiency gap; natural language processing; policy targeting; open-ended questionsOrganisational unit
03539 - Filippini, Massimo / Filippini, Massimo
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ETH Bibliography
yes
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