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Modeling household energy consumption and adoption of energy efficient technology
This study develops a model to study household energy use behavior that can impose common preferences for feasible demand estimation with multiple discrete technology choices and multiple continuous energy consumption uses. The model imposes fixed proportions production and additivity of uses for pl...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6548445/ https://www.ncbi.nlm.nih.gov/pubmed/31171884 http://dx.doi.org/10.1016/j.eneco.2018.04.019 |
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author | Li, Jia Just, Richard E. |
author_facet | Li, Jia Just, Richard E. |
author_sort | Li, Jia |
collection | PubMed |
description | This study develops a model to study household energy use behavior that can impose common preferences for feasible demand estimation with multiple discrete technology choices and multiple continuous energy consumption uses. The model imposes fixed proportions production and additivity of uses for plausible estimation feasibility while adopting a second-order translog flexible functional form to focus on flexibility in identification of consumer preferences that determine interactions among energy uses and between short-run and long-run choices. Using a unique household-level dataset from California, the model is applied to estimate short-run household demand for electricity and natural gas and the long-run technology choices with respect to clothes washing, water heating, space heating, and clothes drying. The estimation results support commonality of underlying preferences except in one case that is explained by an unavailable variable. |
format | Online Article Text |
id | pubmed-6548445 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-65484452019-06-04 Modeling household energy consumption and adoption of energy efficient technology Li, Jia Just, Richard E. Energy Econ Article This study develops a model to study household energy use behavior that can impose common preferences for feasible demand estimation with multiple discrete technology choices and multiple continuous energy consumption uses. The model imposes fixed proportions production and additivity of uses for plausible estimation feasibility while adopting a second-order translog flexible functional form to focus on flexibility in identification of consumer preferences that determine interactions among energy uses and between short-run and long-run choices. Using a unique household-level dataset from California, the model is applied to estimate short-run household demand for electricity and natural gas and the long-run technology choices with respect to clothes washing, water heating, space heating, and clothes drying. The estimation results support commonality of underlying preferences except in one case that is explained by an unavailable variable. 2018-04-18 2018-05 /pmc/articles/PMC6548445/ /pubmed/31171884 http://dx.doi.org/10.1016/j.eneco.2018.04.019 Text en This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Li, Jia Just, Richard E. Modeling household energy consumption and adoption of energy efficient technology |
title | Modeling household energy consumption and adoption of energy efficient technology |
title_full | Modeling household energy consumption and adoption of energy efficient technology |
title_fullStr | Modeling household energy consumption and adoption of energy efficient technology |
title_full_unstemmed | Modeling household energy consumption and adoption of energy efficient technology |
title_short | Modeling household energy consumption and adoption of energy efficient technology |
title_sort | modeling household energy consumption and adoption of energy efficient technology |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6548445/ https://www.ncbi.nlm.nih.gov/pubmed/31171884 http://dx.doi.org/10.1016/j.eneco.2018.04.019 |
work_keys_str_mv | AT lijia modelinghouseholdenergyconsumptionandadoptionofenergyefficienttechnology AT justricharde modelinghouseholdenergyconsumptionandadoptionofenergyefficienttechnology |