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Policy Design and Public Support for Carbon Tax: Evidence from a 2018 U.S. National Online Survey Experiment

DOI:10.1111/padm.12657
Authors:
Nives Dolsak at University of Washington Seattle
Nives Dolsak
Christopher Adolph at University of Washington Seattle
Christopher Adolph
Aseem Prakash at University of Washington Seattle
Aseem Prakash
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Abstract and Figures

Public support for policy instruments is influenced by perceptions of how benefits and costs are distributed across various groups. We examine different carbon tax designs outlining different ways to distribute tax revenues. Using a national online sample of 1,606 U.S. respondents, we examine support for a $20/ton carbon tax that is: (1) Revenue Neutral: revenue is returned to citizens via tax cuts; (2) Compensation‐focused: revenue is directed to helping actors disproportionately hurt by the tax; (3) Mitigation‐focused: revenue funds projects reducing carbon emissions; and (4) Adaptation‐focused: revenue is directed to enhancing community resilience to extreme weather events. We find devoting revenue to mitigation raises overall support for carbon tax by +6.3% versus the control (54.9%) where no information on spending is provided. Other frames raise support in specific subgroups only. Revenue neutrality raises support among lower‐income households (+6.6%) and political independents (+9.4%), while ompensation increases support among lower‐income repondents (+6.1%).
Sample average treatment effects on support for carbon tax Note: Entries represent the estimated average effect of each treatment on the sample of respondents; 95% confidence intervals shown as horizontal lines. Solid symbols indicate effects significantly different from zero at the .05 level. Partially shaded symbols indicate significance at the .1 level. Open symbols indicate non‐significant results. Estimates obtained from an ordered probit adjusting for all covariates, followed by simulation of the change in probability of any support for the carbon tax (support = 5, 6 or 7) resulting from applying each treatment to each subject, given that subject's observed covariates
Sample average treatment effects on support for carbon tax Note: Entries represent the estimated average effect of each treatment on the sample of respondents; 95% confidence intervals shown as horizontal lines. Solid symbols indicate effects significantly different from zero at the .05 level. Partially shaded symbols indicate significance at the .1 level. Open symbols indicate non‐significant results. Estimates obtained from an ordered probit adjusting for all covariates, followed by simulation of the change in probability of any support for the carbon tax (support = 5, 6 or 7) resulting from applying each treatment to each subject, given that subject's observed covariates
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Income‐specific sample average treatment effects on support for carbon tax Note: Entries represent the estimated average effect of each treatment on two subsamples of respondents (those above and those below the median household income); 95% confidence intervals shown as horizontal lines. Solid symbols indicate effects significantly different from zero at the .05 level. Partially shaded symbols indicate significance at the .1 level. Open symbols indicate non‐significant results. Estimates obtained from an ordered probit interacting treatment variables with income and adjusting for all covariates, followed by simulation of the change in probability of any support for the carbon tax (support = 5, 6 or 7) resulting from applying each treatment to each subject in each subsample, given that subject's observed covariates and the specific average treatment effect estimated for that subsample
Income‐specific sample average treatment effects on support for carbon tax Note: Entries represent the estimated average effect of each treatment on two subsamples of respondents (those above and those below the median household income); 95% confidence intervals shown as horizontal lines. Solid symbols indicate effects significantly different from zero at the .05 level. Partially shaded symbols indicate significance at the .1 level. Open symbols indicate non‐significant results. Estimates obtained from an ordered probit interacting treatment variables with income and adjusting for all covariates, followed by simulation of the change in probability of any support for the carbon tax (support = 5, 6 or 7) resulting from applying each treatment to each subject in each subsample, given that subject's observed covariates and the specific average treatment effect estimated for that subsample
… 
Party‐specific sample average treatment effects on support for carbon tax Note: Entries represent the estimated average effect of each treatment on three subsamples of respondents (self‐identified Democrats, Independents, and Republicans); 95% confidence intervals shown as horizontal lines. Solid symbols indicate effects significantly different from zero at the .05 level. Partially shaded symbols indicate significance at the .1 level. Open symbols indicate non‐significant results. Estimates obtained from an ordered probit interacting treatment variables with party and adjusting for all covariates, followed by simulation of the change in probability of any support for the carbon tax (support = 5, 6 or 7) resulting from applying each treatment to each subject in each subsample, given that subject's observed covariates and the specific average treatment effect estimated for that subsample
Party‐specific sample average treatment effects on support for carbon tax Note: Entries represent the estimated average effect of each treatment on three subsamples of respondents (self‐identified Democrats, Independents, and Republicans); 95% confidence intervals shown as horizontal lines. Solid symbols indicate effects significantly different from zero at the .05 level. Partially shaded symbols indicate significance at the .1 level. Open symbols indicate non‐significant results. Estimates obtained from an ordered probit interacting treatment variables with party and adjusting for all covariates, followed by simulation of the change in probability of any support for the carbon tax (support = 5, 6 or 7) resulting from applying each treatment to each subject in each subsample, given that subject's observed covariates and the specific average treatment effect estimated for that subsample
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ORIGINAL ARTICLE
Policy design and public support for carbon
tax: Evidence from a 2018 US national online
survey experiment
Nives Dolšak
1
| Christopher Adolph
2
| Aseem Prakash
2
1
School of Marine and Environmental Affairs,
University of Washington, Seattle, USA
2
Department of Political Science, University
of Washington, Seattle, USA
Correspondence
Aseem Prakash, Department of Political
Science, University of Washington, 39 Gowen
Hall, Seattle, WA 98195, USA.
Email: aseem@uw.edu
Abstract
Public support for policy instruments is influenced by
perceptions of how benefits and costs are distributed
across various groups. We examine different carbon tax
designs outlining different ways to distribute tax revenues.
Using a national online sample of 1,606 US respondents, we
examine support for a $20/ton carbon tax that is: (1) revenue
neutral: revenue is returned to citizens via tax cuts; (2) compen-
sation-focused: revenue is directed to helping actors dispro-
portionately hurt by the tax; (3) mitigation-focused: revenue
funds projects reducing carbon emissions; and (4) adaptation-
focused: revenue is directed to enhancing community resil-
ience to extreme weather events. We find devoting revenue to
mitigation raises overall support for carbon tax by 6.3 per cent
versus the control (54.9 per cent) where no information on
spending is provided. Other frames raise support in specific
subgroups only. Revenue neutrality raises support among
lower-income households (+6.6 per cent) and political indepen-
dents (+9.4 per cent), while compensation increases support
among lower-income repondents (+6.1 per cent).
1|INTRODUCTION
Public support is critical for policy success. Public administrators therefore seek public input to design policies that
citizens view as fair and effective (Page and Shapiro 1983; Lodge 1994; Majone 1999; Lodge and Stirton 2001;
Howlett 2009). Designing such policies becomes challenging when policies are perceived as imposing differential
costs and benefits across sectors (Soss and Schram 2007). And if these costs or benefits are perceived as concen-
trated on specific sectors (Lowi 1964; Wilson 1980), interest groups mobilize to support or oppose the policy. The
Received: 23 April 2019 Revised: 25 November 2019 Accepted: 21 January 2020
DOI: 10.1111/padm.12657
Public Admin. 2020;98:905–921. wileyonlinelibrary.com/journal/padm © 2020 John Wiley & Sons Ltd 905
... In order to overcome public opposition, a burgeoning literature has pointed to the potential of revenue recycling as a means of building public support for carbon taxes and carbon pricing more generally [47,48,50,[54][55][56]. In particular, a number of scholars and policy actors have identified lump-sum transfers, or equal per capita dividends, as a promising strategy for building public support [52,57]. ...
... To be sure, there is substantial evidence to suggest that information provision on the benefits of certain carbon tax designs can enhance support [48,54,61]. However, other research has questioned the extent to which information deficits are part of the problem, suggesting that a better strategy may be to avoid the complex task of communicating policy details altogether [62]. ...
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