Bardsley, N, Buchs, M orcid.org/0000-0001-6304-3196 and Schnepf, SV (2017) Something from nothing: Estimating consumption rates using propensity scores, with application to emissions reduction policies. PLoS ONE, 12 (10). e0185538. ISSN 1932-6203
Abstract
Consumption surveys often record zero purchases of a good because of a short observation window. Measures of distribution are then precluded and only mean consumption rates can be inferred. We show that Propensity Score Matching can be applied to recover the distribution of consumption rates. We demonstrate the method using the UK National Travel Survey, in which c.40% of motorist households purchase no fuel. Estimated consumption rates are plausible judging by households’ annual mileages, and highly skewed. We apply the same approach to estimate CO2 emissions and outcomes of a carbon cap or tax. Reliance on means apparently distorts analysis of such policies because of skewness of the underlying distributions. The regressiveness of a simple tax or cap is overstated, and redistributive features of a revenue-neutral policy are understated.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2017 Bardsley et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
Keywords: | Fuels; Taxes; Carbon dioxide; Payment; Surveys; Rations; Skewness; Finance |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 20 Oct 2017 11:06 |
Last Modified: | 20 Oct 2017 11:06 |
Status: | Published |
Publisher: | Public Library of Science (PLoS) |
Identification Number: | 10.1371/journal.pone.0185538 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:122878 |