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Policy Attribute Framing: A Comparison between Three Policy Instruments for Personal Emissions Reduction

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Title: Policy Attribute Framing: A Comparison between Three Policy Instruments for Personal Emissions Reduction
Language: English
Authors: Parag, Yael, Capstick, Stuart, Poortinga, Wouter
Source: Journal of Policy Analysis and Management. Aut 2011 30(4):889-905.
Availability: John Wiley & Sons, Inc. Subscription Department, 111 River Street, Hoboken, NJ 07030-5774. Tel: 800-825-7550; Tel: 201-748-6645; Fax: 201-748-6021; e-mail: subinfo@wiley.com; Web site: http://www3.interscience.wiley.com/browse/?type=JOURNAL
Peer Reviewed: Y
Page Count: 17
Publication Date: 2011
Document Type: Journal Articles
Reports - Research
Descriptors: Public Policy, Energy Conservation, Behavior Change, Taxes, Comparative Analysis, Foreign Countries
Geographic Terms: United Kingdom
DOI: 10.1002/pam.20610
ISSN: 0276-8739
Abstract: A comparative experiment in the UK examined people's willingness to change energy consumption behavior under three different policy framings: energy tax, carbon tax, and personal carbon allowances (PCA). PCA is a downstream cap-and-trade policy proposed in the UK, in which emission rights are allocated to individuals. We hypothesized that due to economic, pro-environmental and mental accounting drivers PCA would have greater potential to deliver emissions reduction than taxation. Participants (n = 1,096) received one version of a survey with the same energy-behavior-related questions and identical incurred costs under one of the following framings: energy tax (where carbon was not mentioned), carbon tax, and PCA. Results suggest that policies that draw people's attention to carbon (PCA and carbon taxation) could have greater impact on their stated willingness to reduce energy consumption, and on the reduction amounts prompted, than would a non-overt price signal (energy tax). There is mixed evidence, however, as to whether PCA or carbon taxation would produce the largest energy demand reductions. Some indication was found for a spillover toward wider carbon conservation under the PCA framing. (Contains 1 figure, 3 tables, and 1 footnote.)
Abstractor: As Provided
Number of References: 45
Entry Date: 2012
Accession Number: EJ958454
Database: ERIC
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  Value: <anid>AN0065131857;jpa01sep.11;2019Jun03.10:33;v2.2.500</anid> <title id="AN0065131857-1">Policy attribute framing: A comparison between three policy instruments for personal emissions reduction. </title> <p>A comparative experiment in the UK examined people's willingness to change energy consumption behavior under three different policy framings: energy tax, carbon tax, and personal carbon allowances (PCA). PCA is a downstream cap‐and‐trade policy proposed in the UK, in which emission rights are allocated to individuals. We hypothesized that due to economic, pro‐environmental and mental accounting drivers PCA would have greater potential to deliver emissions reduction than taxation. Participants (n = 1,096) received one version of a survey with the same energy‐behavior–related questions and identical incurred costs under one of the following framings: energy tax (where carbon was not mentioned), carbon tax, and PCA. Results suggest that policies that draw people's attention to carbon (PCA and carbon taxation) could have greater impact on their stated willingness to reduce energy consumption, and on the reduction amounts prompted, than would a non‐overt price signal (energy tax). There is mixed evidence, however, as to whether PCA or carbon taxation would produce the largest energy demand reductions. Some indication was found for a spillover toward wider carbon conservation under the PCA framing. © 2011 by the Association for Public Policy Analysis and Management.</p> <p>Mitigating climate change poses a substantial challenge for policymakers. Many countries have set themselves ambitious emissions reduction goals and issued policies that target emissions from different sectors in society. Emissions from individuals, which make up a significant proportion of total emissions globally, are typically hard to target. Although personal carbon emissions are individually negligible, collectively they are very significant: According to the International Energy Agency (IEA, [<reflink idref="bib19" id="ref1">19</reflink>]), they account for nearly half of all emissions in major developed countries. Within the UK, around 42 percent of total emissions can be considered direct personal emissions; of these about 55 percent derive from household energy use and a further 45 percent from personal transport (BERR, [<reflink idref="bib4" id="ref2">4</reflink>]).</p> <p>The UK, in keeping with a number of other industrialized countries, has set itself an ambitious target of an 80 percent reduction in greenhouse gases (GHG) from 1990 levels by 2050, with a 34 percent reduction by 2020, in the legally binding Climate Change Act 2008. Clearly, in order to meet these emission targets, emissions from the residential sector and personal transport would need to be reduced. Yet finding policy instruments that steer millions of individuals' energy‐use choices and behavior toward emissions reduction remains an unmet challenge.</p> <p>This paper presents an experimental study designed to test the impact of policy attribute framing on the willingness of individuals to reduce their personal carbon emissions. It compares three policies: personal carbon allowances (PCA), carbon tax, and energy tax. It is hypothesized that framings increasing the visibility of carbon will promote greater carbon savings than a nonspecific energy tax due to the activation of pro‐environmental motivations. We hypothesize, in addition, that the framing of costs in terms of an allowance—a resource in its own right—will lead to mental accounting or budgeting effects and therefore will promote greater carbon savings than either a carbon tax or a nonspecific energy tax.</p> <p>The paper proceeds as follows: First we set the policy context and briefly introduce the concept of personal carbon trading and allowances. Next, we elaborate on the potential motivations for behavioral change provided by each of the policies. We then present the experiment, which compares the impact of the three framings on the stated willingness to change energy consumption behavior, discuss the results, and draw some conclusions regarding carbon reduction policies.</p> <hd id="AN0065131857-2">THE POLICY CONTEXT OF PERSONAL EMISSIONS REDUCTION</hd> <p>To date, a variety of policies are being implemented in the UK and elsewhere to target personal emissions. These include, on the one end, regulation of energy providers, which commits them to reduce emissions from the residential sector (e.g., carbon emissions reduction targets, CERT, energy white certificates), as well as voluntary agreements such as those with car manufacturers to improve vehicle efficiency standards. On the other end there are programs that target energy consumers directly, such as information schemes, energy labeling, energy‐use feedback, taxes (e.g., a component of the vehicle excise duty), and to a lesser extent, economic incentives such as grants, rebates, and a feed‐in tariff for renewable energy. Misperception of energy consumption and savings has been identified as a barrier to improving energy savings by individuals (Attari et al., [<reflink idref="bib1" id="ref3">1</reflink>]). Hence, the rationale behind these policies is that increasing knowledge and understanding of climate change and energy use, in addition to information and a price signal, will encourage energy demand reduction, which would lead to emissions reduction. It seems, however, that these measures are unlikely to be sufficient for enabling the residential sector and personal transport to meet the targets set out in the 2008 climate change act (Defra, [<reflink idref="bib9" id="ref4">9</reflink>]). The UK government has acknowledged that additional policy interventions will be needed to deliver the 2020 targets (BERR, [<reflink idref="bib4" id="ref5">4</reflink>]).</p> <p>A number of radical policy options that target personal emissions have been proposed and discussed in the UK. These include personal carbon trading (PCT) and carbon taxation. PCT is a general term used to describe a variety of downstream cap‐and‐trade policy instruments whereby emission rights are allocated to individuals (for variations in PCT schemes see Roberts & Thumim, [<reflink idref="bib30" id="ref6">30</reflink>]; Fawcett & Parag, [<reflink idref="bib14" id="ref7">14</reflink>]). Some of these proposals have been formally investigated by the UK government (Defra, [<reflink idref="bib10" id="ref8">10</reflink>]) and Parliament (Environmental Audit Committee, [<reflink idref="bib13" id="ref9">13</reflink>]).</p> <p>Unlike existing policies, which are segmented (addressing appliance use, heating, or travel behavior separately), carbon tax and PCT both provide an overarching approach. This approach, it has been argued, has the potential to create a perceptual and cognitive framework enabling individuals to integrate understanding across emissions from different activities, and in the context of energy use as it occurs (Parag & Strickland, [<reflink idref="bib28" id="ref10">28</reflink>]). For example, such frameworks put into proportion the amount of carbon emissions savings gained by installing energy‐efficient light bulbs and those saved by flying less. It is suggested that this new cognitive framework may then lead to better awareness and understanding of personal emissions across activities, which may lead to further personal emissions cuts. This effect is known as "positive spillover," and is said to occur when engagement in particular pro‐environmental behavior increases the motivation to adopt other related behaviors (Thøgersen & Crompton, [<reflink idref="bib40" id="ref11">40</reflink>]; Whitmarsh & O'Neill, [<reflink idref="bib45" id="ref12">45</reflink>]). However, empirical evidence for such spillover effects is lacking.</p> <p>In this paper we focus on the personal carbon allowance (PCA) variation of PCT. PCA, as proposed by Mayer Hillman in 1998 (Hillman & Fawcett, [<reflink idref="bib18" id="ref13">18</reflink>]), is a mandatory policy in which all individuals receive an annual and equal per capita carbon emissions allowance ("budget") for their personal use. A PCA scheme covers emissions under direct personal control, such as household energy use (electricity and gas), private transport (not including public transport), and personal air travel. It does not include carbon embedded in products and services purchased by the individual as this would be expected to be covered, very largely, by other carbon cap and trade schemes—the EU Emissions Trading Scheme (EUETS) and in the UK by the Carbon Reduction Commitment (CRC).</p> <p>Under a PCA scheme, for each purchase of carbon‐based energy, allowances are deducted from the individual's carbon budget. If people emit more carbon than their allowance, they would need to buy additional carbon credits. On the other hand, those who emit less carbon than their allowance can sell their excess into the carbon market. The personal carbon allowances would be reduced periodically in line with UK emissions targets.</p> <hd id="AN0065131857-3">AIMS OF THE STUDY</hd> <p>In this study we aim to investigate whether the mode of presentation of information relating to energy‐use behavior—the framing of this information—contributes toward a policy's effectiveness. We compare the framing of specific attributes of three policies—a personal carbon allowances scheme (PCA), carbon tax (Ctax), and energy tax (Etax)—in terms of their ability to lead to a stated willingness to reduce personal carbon emissions.</p> <p>While a relatively novel approach toward testing policy impact, Hardisty, Johnson, and Weber ([<reflink idref="bib17" id="ref14">17</reflink>]) have previously used experimental psychology methods to test the impact of alternative attribute framings on individuals' preferences and willingness to pay for their personal carbon emissions. In their study they compared a price increase framed as a <emph>carbon tax</emph> and the same price increase framed as a <emph>carbon offset</emph>. The participants were advised that both increases are used to fund carbon reduction measures. However, while a tax highlights the increased cost required to provide the benefit, an offset highlights the benefit provided by the cost. Hardisty, Johnson, and Weber ([<reflink idref="bib17" id="ref15">17</reflink>]) demonstrated that framing, mediated by political affiliation, is an important factor that determines preferences and willingness to comply.</p> <p>Like Hardisty, Johnson, and Weber ([<reflink idref="bib17" id="ref16">17</reflink>]), we are interested in the power of framing manipulation on behavior and behavioral change. We aim to test how policy framing may impact individuals' energy‐use decisions. We argue that the framing of a carbon reduction policy will impact individuals' energy‐use decision making, as the different framings (PCA, Ctax, Etax) draw on a different set of economic, pro‐environmental, and mental accounting motivational mechanisms, as discussed in the next section.</p> <hd id="AN0065131857-4">Motivational Mechanisms</hd> <p>Each of the policies—Etax, Ctax, and PCA—provides a variety of economic, intrinsic, psychological, and social motivations for personal pre‐ and carbon‐related behavior (Parag & Strickland, [<reflink idref="bib28" id="ref17">28</reflink>]). This study, however, investigates in particular the psychological motivations, and how (if at all) policy framing might influence these. Figure 1 summarizes these motivations.</p> <p>Graph: 1 Motivations for energy‐related behavior provided by energy tax, carbon tax, and personal carbon allowances.</p> <hd id="AN0065131857-5">Economic Motivation: Etax, Ctax and PCA</hd> <p>Taxation provides a price signal, ultimately visible to the final energy user as a price rise. It is self‐evident that, in the most general terms, price increase leads to demand reduction. Yet people do not always react to price signals imposed by taxes in the manner predicted by neoclassical economics. The elasticity in demand for energy, in particular, may be limited with respect to price rises (e.g., Halvorsen & Larsen, [<reflink idref="bib16" id="ref18">16</reflink>]; Reiss & White, [<reflink idref="bib29" id="ref19">29</reflink>]), thus weakening the potential effectiveness of taxation schemes in delivering demand reduction. In addition, energy costs constitute a relatively low proportion of the total household budget for many countries. Consequently, the price signal—and any changes to it—may lead to a relatively weak behavioral impact (Baker & Blundell, [<reflink idref="bib2" id="ref20">2</reflink>]). Of course, major energy price rises are likely to reduce demand, yet rises of this scale impact the poor disproportionately and are likely to be politically and socially unacceptable.</p> <p>Economic considerations are clearly important when people make energy decisions, although they are not the only consideration guiding purchasing decisions or energy demand patterns (see, e.g., Lutzenhiser, [<reflink idref="bib22" id="ref21">22</reflink>]; Oxera, [<reflink idref="bib25" id="ref22">25</reflink>]). Indeed, for some consumers the connections between energy use and carbon emissions are important, and energy bills may be kept down to reduce environmental impact as well as costs.</p> <p>In respect of an economic signal alone, carbon taxation is identical to a generic energy tax in behavioral terms. The economic mechanism of PCA, by contrast, is driven by the price of carbon arising from a market of traded allowances. This price would be determined by supply and demand conditions, the value of the services carbon‐based energy can deliver, and the extent to which there is a well‐behaved market. Nevertheless, in a similar fashion to a carbon and nonspecific tax, PCA provides a price signal whereby the carbon price would provide the economic incentive for reducing emissions independently of the initial distribution of allowances.</p> <hd id="AN0065131857-6">Pro‐Environmental Motivations: Ctax and PCA</hd> <p>Environmentally significant behavior is influenced by a range of factors such as attitudes, values, beliefs, informational awareness, and perceived behavioral control (Black, Stern, & Elworth, [<reflink idref="bib5" id="ref23">5</reflink>]; Nordlund & Garvill, [<reflink idref="bib24" id="ref24">24</reflink>]; Swim et al., [<reflink idref="bib37" id="ref25">37</reflink>]; Attari et al., [<reflink idref="bib1" id="ref26">1</reflink>]). As part of this, carbon visibility, carbon awareness, and appropriate information may form crucial component parts for promoting behavioral change (Steg, [<reflink idref="bib34" id="ref27">34</reflink>]; Whitmarsh, [<reflink idref="bib44" id="ref28">44</reflink>]; Dietz, [<reflink idref="bib11" id="ref29">11</reflink>]).</p> <p>Unlike nonspecific energy taxation, under a carbon tax carbon visibility and carbon awareness should increase—provided the carbon price was perceptible separately from overall cost. This would in turn prompt pro‐environmental behavior (i.e., emissions reduction) for those individuals for whom climate change is a relevant concern. This would be in addition to the economic motivation described above. We propose that under a PCA scheme, pro‐environmental motivation would be driven in a similar way—although in this case carbon visibility and awareness would be connected to the possession and use of one's individual carbon allowance.</p> <hd id="AN0065131857-7">Mental Accounting Motivations: PCA Only</hd> <p>In addition to the economic and pro‐environmental motivations described above, it has been suggested by a number of authors that a PCA policy could engage additional psychological processes in a manner unique to this scheme. Capstick and Lewis ([<reflink idref="bib7" id="ref30">7</reflink>], [<reflink idref="bib8" id="ref31">8</reflink>]) have proposed that there may be a role for mental accounting where a PCA scheme is operational.</p> <p>Mental accounting as envisaged by Thaler ([<reflink idref="bib38" id="ref32">38</reflink>]) entails cognitive processes used in everyday situations by individuals and households "to organise, evaluate and keep track of financial activities" (Thaler, [<reflink idref="bib38" id="ref33">38</reflink>], p. 183). An important component of mental accounting is the allocation of specific resources to specific accounts—for example, one may assign funds to the payment of bills, travel needs, or leisure activities, in effect bracketing or ring‐fencing financial resources. While such mental accounting is inherently sensible and intuitive, Thaler has argued that it nevertheless violates the economic principle of fungibility—the assumption that financial resources are identical and equivalent no matter their provenance or the purpose to which they are put.</p> <p>It has been suggested that given a fixed carbon allowance, trade‐offs would be promoted between different carbon‐emitting activities. For example, frequent car driving may be enabled through restrictions exercised on home energy usage, or by limiting air travel (Capstick & Lewis, [<reflink idref="bib7" id="ref34">7</reflink>]; Parag & Strickland, [<reflink idref="bib27" id="ref35">27</reflink>]). The suggestion here is that, given a limited allowance (albeit one which may be extended through purchasing further credits), a form of carbon budgeting may occur at the individual or household level.</p> <p>Although Capstick and Lewis ([<reflink idref="bib8" id="ref36">8</reflink>]) provide some initial experimental data that indicates such budgeting may occur within a (simulated, experimental) PCA scheme, the evidence base for a distinct psychological effect of PCA nevertheless is limited. Bristow et al. ([<reflink idref="bib6" id="ref37">6</reflink>]) provide somewhat inconclusive evidence that PCA can promote different responses in terms of willingness to reduce emissions than carbon taxation. However, no studies so far have compared the three policies considered here to ascertain whether different responses are able to be detected in terms of the mechanisms hypothesized.</p> <p>As PCA schemes have the potential to activate pro‐environmental and mental accounting motivations in addition to economic motivations, it is suggested that this policy framing may lead to a greater spillover effect—where the adoption of a particular pro‐environmental behavior may lead to engaging in other pro‐environmental behaviors (Thøgersen & Crompton, [<reflink idref="bib40" id="ref38">40</reflink>]; Whitmarsh & O'Neill, [<reflink idref="bib45" id="ref39">45</reflink>])—than either the Etax or Ctax. Eliciting pro‐environmental motivations is likely to encourage people to adopt other carbon‐saving behaviors, while mental accounting effects may further stimulate changes in behaviors not directly covered by the scheme.</p> <hd id="AN0065131857-8">Hypotheses</hd> <p>While neither carbon taxation nor PCA has been devised intentionally with a particular framing in mind, the authors nevertheless suggest that due to the mechanisms outlined above, each policy emphasizes in a different manner the costs and benefits arising from personal emissions, thus rendering them appropriate to be tested in an experimental fashion. Importantly, there remains a fundamental equivalence between the policies—for each, carbon is priced and applied according to individual behavior—and yet we suggest that due to differences in the framing of these costs, differences in responses will emerge.</p> <p>In the present study, we focus specifically on everyday energy‐use behaviors ("daily use behaviors" in the categorization of Dietz et al., [<reflink idref="bib12" id="ref40">12</reflink>]). We assume that hypothetical reductions in these types of behaviors are more amenable to being framed in terms of simple financial or carbon increments, as suits the present survey design.</p> <p>The hypotheses tested in this study are the following:</p> <p></p> <p>• 1.</p> <p></p> <ulist> <item> Due to price signal, all framings will promote carbon emissions reduction.</item> <p></p> </ulist> <p>• 2.</p> <p></p> <ulist> <item> Due to the activation of pro‐environmental motivations via carbon visibility, both PCA and carbon taxation will promote greater carbon savings than a nonspecific energy tax under the same price signal. This preference is predicted to be demonstrated both in terms of stated willingness to reduce personal emissions and in the size of those reductions.</item> <p></p> </ulist> <p>• 3.</p> <p></p> <ulist> <item> Due to the activation of mental accounting motivations, PCA will lead to people indicating a greater preference for behavior change than under a carbon tax or nonspecific energy tax under the same price signal. This preference is predicted to be demonstrated both in terms of stated willingness to reduce personal emissions and in the size of those reductions.</item> <p></p> </ulist> <p>• 4.</p> <p></p> <ulist> <item> Due to different framing, PCA will have a greater spillover effect (encourage people to reduce personal emissions not covered by the scheme) than carbon tax or nonspecific energy tax.</item> </ulist> <hd id="AN0065131857-9">METHOD</hd> <p></p> <hd id="AN0065131857-10">Framing Effects of Carbon Reduction Policies</hd> <p>The experimental approach of this study is best understood within the paradigm of attribute framing (Levin, Schneider, & Gaeth, [<reflink idref="bib20" id="ref41">20</reflink>]), wherein a particular characteristic of (in this case) a policy is emphasized by means of description or by structuring information in a particular and deliberate fashion. In a variety of experimental psychology studies, such manipulation of information has been shown to affect participants' choices, including in cases where conditions are otherwise logically equivalent (see Tversky & Kahneman, [<reflink idref="bib41" id="ref42">41</reflink>], for seminal work in this area). For example, Levin, Schneider, and Gaeth ([<reflink idref="bib20" id="ref43">20</reflink>]) cite studies in which either failure or success rates are highlighted (e.g., 75 percent chance of success vs. 25 percent chance of failure) as leading to different response outcomes. In the context of climate change, it has been argued that a variety of social, governance, and economic frames may analogously be applied with equal plausibility. For example, as a policy challenge, climate change may be framed either as a market benefit or risk (Nisbet, [<reflink idref="bib23" id="ref44">23</reflink>]). Spence and Pidgeon ([<reflink idref="bib33" id="ref45">33</reflink>]) have demonstrated that different framings of climate change (in terms of gains vs. avoided losses from mitigation, and in respect of proximity of consequences) influence attitudes toward climate change mitigation.</p> <hd id="AN0065131857-11">Design</hd> <p>We used a between‐subjects experimental survey questionnaire method to compare responses among three framing conditions: nonspecific energy taxation, carbon taxation, and PCA.</p> <p>In each version of the questionnaire, participants were asked to assume that the scheme highlighted was in operation and asked to say to what extent (if at all) this would influence their reduction of energy consumption. Financial costs were kept constant between conditions; policy framing varied according to the stated objectives of the policy in the context of addressing climate change and reducing carbon emissions (carbon taxation and PCA) and situation of carbon and monetary costs in terms of an allowance (PCA only).</p> <p>Participants were presented with energy decisions in the context of personal transportation (car use), home energy use (space heating and washing machine usage), and in terms of a spillover question (dairy consumption); this last did not entail monetary costs or carbon consequences, but was included to explore whether PCA and carbon taxation effects might persist beyond the context of direct emissions.</p> <p>The Appendix shows an example of the wording used to describe each policy prior to survey completion, followed by one example of the wording used in each of its three different framings.1</p> <p>Each question in the survey also included contextual information to anchor decisions more realistically to everyday choices. Question 1 (driving behavior) included the following statement: "As a guideline, 1,000 miles relates to around 5 journeys from London to Bristol, or 200 short journeys by car (e.g., to the supermarket)." Question 2 (space heating and thermostat adjustment) was contextualized thus: "Average room temperature is 21°C. Temperature preferences vary considerably between individuals. As a rule of thumb, reducing by 1°C may mean you feel slightly cooler; 2°C will possibly require an extra layer of clothing; 3°C will be noticeably cooler and might require a warmer layer." Question 3 (washing machine) included the following statement: "The effectiveness of lowering temperature varies between appliances and washing powders. Innovative washing powders are increasingly available to clean at lower temperatures. Reducing the temperature by up to 10°C is unlikely to make much difference to the cleanliness of your washing. Reducing by 20°C or more might not clean well‐soiled clothes."</p> <p>Financial costs were estimated using the cost of carbon at the time of the design of the experiment, in the context of the relevant carbon‐emitting behaviors. Financial costs per year are reported in the Results section (see Table 1 on page 9, right column).</p> <p>1 Percent of each survey group willing to make any reductions.</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left">Willingness to Make Reductions (of Any Amount)</th><th align="center">Etax</th><th align="center">Ctax</th><th align="center">PCA</th><th align="center">Carbon Monetary Value per Year</th></tr></thead><tbody><tr><td>Personal mileage</td><td>44%</td><td>45%</td><td>65%</td><td>£35 per 1,000 miles</td></tr><tr><td>Room thermostat</td><td>77%</td><td>78%</td><td>83%</td><td>£30 per 1°C</td></tr><tr><td>Washing machine</td><td>75%</td><td>77%</td><td>78%</td><td>£5 per 10°C</td></tr><tr><td>Dairy consumption</td><td>17%</td><td>19%</td><td>28%</td><td>0</td></tr></tbody></table> </ephtml> </p> <p>Demographic data were recorded, as well as environmental attitude data. Environmental attitude data were recorded <emph>after</emph> the experimental manipulations, so as not to inadvertently prompt pro‐environmental motivations (e.g., by asking about levels of environmental concern or perceived responsibility for carbon emissions) in the energy tax condition.</p> <hd id="AN0065131857-12">Sample</hd> <p>A nationally representative sample of the British adult population was recruited via a market research company. The final sample (<emph>n</emph> = 1,096) was split approximately evenly between males and females, with a broadly representative age profile; age groups were divided into 10‐year bands (aside from 18 through 24 and 65+) with between 11 percent and 20 percent of the sample contained in each band. Social grade was also measured and found to be broadly representative. The majority of the sample (90 percent) had a household income of £40,000 per annum or less, and 92 percent were white.</p> <hd id="AN0065131857-13">Measures</hd> <p></p> <hd id="AN0065131857-14">Attitude to the Environment</hd> <p>An environmental attitude scale was constructed by averaging the scores on four environmental attitudes questions, each which could be answered on a 5‐point scale. The resulting scores varied from 1 (low pro‐environmental attitude) to 5 (high pro‐environmental attitude). The composite scale appeared to be internally consistent (Cronbach's α = 0.65).</p> <p>Our assumption was that environmental attitudes were distributed normally between the people who took the survey, and hence should be comparable across conditions. This was confirmed by a one‐way ANOVA (no differences in attitudes between conditions found).</p> <hd id="AN0065131857-15">Behavior Change Measures</hd> <p>Four dependent variables were used in the analyses. Respondents were asked to state to what extent they were willing to change their behavior in terms of (<reflink idref="bib1" id="ref46">1</reflink>) reducing their annual mileage (Mileage), (<reflink idref="bib2" id="ref47">2</reflink>) turning down their room thermostat (Thermostat), (<reflink idref="bib3" id="ref48">3</reflink>) lowering their washing temperature (Washing), and (<reflink idref="bib4" id="ref49">4</reflink>) reducing their dairy consumption (Dairy).</p> <p>Data for each participant corresponded, respectively, to number of miles per year (in reduction increments of 100 per year, from "no change" up to "more than 1,000"), amount of thermostat reduction (reduction increments of 1°C from "no change" to a maximum of "more than 3°C"), amount of washing machine temperature reduction (reduction increments of 10°C from "no change" up to "more than 30°C"), and amount of dairy consumption reduction (reduction increments of 10 percent per year from "no change" up to 50 percent).</p> <p>The four behavioral change variables were used in two different ways. First, the variables were dichotomized to examine how many respondents were willing to change their behavior. All respondents who indicated that they were willing to make <emph>any</emph> change (disregarding the size) were compared to those who indicated they were not willing to change their behavior. These variables were analyzed using logistic regression.</p> <p>Second, the original scaling of the questions was retained to conduct ordinal regressions to examine the impacts of the different framing conditions on the extent to which the participants were willing to reduce their personal mileage, room thermostat settings, washing machine temperature, and dairy consumption, respectively. Ordinal regression was used as the variables could not be assumed to be continuous and normally distributed.</p> <hd id="AN0065131857-16">Analysis</hd> <p>Logistic and ordinal regression analyses were conducted to examine people's stated willingness to change energy consumption behavior under the three policy framings (PCA, Ctax, Etax). For both the logistic regression and the ordinal regressions, a series of models were constructed for each of the four behaviors. The first models (Model 1) examined the differences between the three experimental framing conditions (PCA, Ctax, and Etax). Two dummy variables were used, representing the carbon tax (Ctax) and personal carbon allowances (PCA) conditions, respectively, thus considering the energy tax condition as the reference condition. The second models (Model 2) added the sociodemographic variables of gender, age, and income, as well as the composite measure of pro‐environmental attitude, to adjust for any compositional differences between the three experimental conditions. Model 3 further expanded the regression analyses by including interaction terms between the sociodemographic and pro‐environmental attitude variables on the one hand and the experimental conditions on the other. These interaction terms provide indicators of whether these groups respond differently to the three experimental conditions. Interactions of age, income, and pro‐environmental attitude with the different experimental conditions are reported below. No interaction terms with gender are reported as none of these interactions were significant. The logistic regression models are presented in Table 2 and the ordinal regression models are presented in Table 3.</p> <p>2 Logistic regressions.</p> <p> <ephtml> <table><thead valign="top"><tr><th align="left" /><th align="center">Mileage B (S.E.)</th><th align="center">Thermostat B (S.E.)</th><th align="center">Washing B (S.E.)</th><th align="center">Dairy B (S.E.)</th></tr></thead><tbody><tr><td align="left"><bold>MODEL 1</bold></td></tr><tr><td>CTAX</td><td>0.04 (0.17) n.s.</td><td>0.05 (0.18) n.s.</td><td>0.13 (0.17) n.s.</td><td>0.05 (0.18) n.s.</td></tr><tr><td>PCA</td><td>0.86 (0.17)***</td><td>0.38 (0.19)*</td><td>0.17 (0.18) n.s.</td><td>0.38 (0.19)*</td></tr><tr><td><bold><italic>R</italic></bold><sup>2</sup> (Model 1)</td><td><italic>0.04</italic></td><td><italic>0.00</italic></td><td><italic>0.00</italic></td><td><italic>0.01</italic></td></tr><tr><td align="left"><bold>MODEL 2</bold></td></tr><tr><td>CTAX</td><td>0.02 (0.18) n.s.</td><td>0.03 (0.18) n.s.</td><td>0.12 (0.18) n.s.</td><td>0.03 (0.018) n.s.</td></tr><tr><td>PCA</td><td>0.89 (0.18)***</td><td>0.32 (0.19) n.s.</td><td>0.09 (0.18) n.s.</td><td>0.32 (0.19) n.s.</td></tr><tr><td>Gender</td><td>0.02 (0.15) n.s.</td><td>−0.19 (0.16) n.s.</td><td>−0.35 (0.15)*</td><td>−0.19 (0.16) n.s.</td></tr><tr><td>Age</td><td>−0.11 (0.08) n.s.</td><td>−0.05 (0.08) n.s.</td><td>0.01 (0.08) n.s.</td><td>−0.05 (0.08) n.s.</td></tr><tr><td>Income</td><td>−0.47 (0.11)***</td><td>−0.08 (0.12) n.s.</td><td>−0.00 (0.11) n.s.</td><td>−0.08 (0.12) n.s.</td></tr><tr><td>Pro‐environmental attitude</td><td>0.37 (0.08)***</td><td>0.60 (0.08)***</td><td>0.60 (0.08)***</td><td>0.60 (0.08)***</td></tr><tr><td><bold><italic>R</italic></bold><sup>2</sup> (Model 2)</td><td><italic>0.09</italic></td><td><italic>0.07</italic></td><td><italic>0.07</italic></td><td><italic>0.04</italic></td></tr><tr><td align="left"><bold>MODEL 3</bold></td></tr><tr><td>CTAX</td><td>−0.17 (0.21) n.s.</td><td>−0.04 (0.22) n.s.</td><td>0.38 (0.23) n.s.</td><td>0.16 (0.26) n.s.</td></tr><tr><td>PCA</td><td>0.84 (0.19)***</td><td>0.48 (0.24)*</td><td>0.32 (0.21) n.s.</td><td>0.74 (0.24)**</td></tr><tr><td>Gender</td><td>0.02 (0.15) n.s.</td><td>−0.19 (0.16) n.s.</td><td>−0.35 (0.16)*</td><td>0.17 (0.16) n.s.</td></tr><tr><td>Age</td><td>0.15 (0.13) n.s.</td><td>0.29 (0.13)*</td><td>−0.06 (0.13) n.s.</td><td>−0.4 (0.15) n.s.</td></tr><tr><td>Income</td><td>−0.17 (0.18) n.s.</td><td>0.06 (0.20) n.s.</td><td>−0.21 (0.19) n.s.</td><td>−0.53 (0.24)*</td></tr><tr><td>Pro‐environmental attitude (PEA)</td><td>0.17 (0.12) n.s.</td><td>0.46 (0.13)***</td><td>0.33 (0.12)**</td><td>0.20 (0.14) n.s.</td></tr><tr><td>PEA × CTAX</td><td>0.48 (0.19)**</td><td>0.13 (0.18) n.s.</td><td>0.45 (0.19)*</td><td>0.34 (0.21) n.s.</td></tr><tr><td>PEA × PCA</td><td>0.14 (0.19) n.s.</td><td>0.42 (0.21)*</td><td>0.43 (0.20)*</td><td>0.31 (0.20) n.s.</td></tr><tr><td>Income × CTAX</td><td>−0.63 (0.28)*</td><td>−0.26 (0.28) n.s.</td><td>0.31 (0.28) n.s.</td><td>0.27 (0.33) n.s.</td></tr><tr><td>Income × PCA</td><td>−0.44 (0.26) n.s.</td><td>−0.07 (0.29) n.s.</td><td>0.34 (0.27) n.s.</td><td>0.47 (0.30) n.s.</td></tr><tr><td>Age × CTAX</td><td>−0.26 (0.19) n.s.</td><td>−0.41 (0.19)*</td><td>0.00 (0.19) n.s.</td><td>−0.07 (0.20) n.s.</td></tr><tr><td>Age × PCA</td><td>−0.54 (0.19)**</td><td>−0.65 (0.20)***</td><td>0.23 (0.19) n.s.</td><td>−0.05 (0.19) n.s.</td></tr><tr><td><bold><italic>R</italic></bold><sup>2</sup> (model 3)</td><td><italic>0.11</italic></td><td><italic>0.08</italic></td><td><italic>0.08</italic></td><td><italic>0.05</italic></td></tr></tbody></table> </ephtml> </p> <p>1 <emph>Note:</emph></p> <ulist> <item>2 * * <emph>p</emph> < 0.05;</item> <item>3 ** ** <emph>p</emph> < 0.01;</item> <item>4 *** *** <emph>p</emph> < 0.001; n.s. = nonsignificant.</item> <item>3 Ordinal regressions.</item> </ulist> <p> <ephtml> <table><thead valign="top"><tr><th align="left" /><th align="center">Mileage B (S.E.)</th><th align="center">Thermostat B (S.E.)</th><th align="center">Washing B (S.E.)</th><th align="center">Dairy B (S.E.)</th></tr></thead><tbody><tr><td align="left"><bold>MODEL 1</bold></td></tr><tr><td>CTAX</td><td>0.13 (0.16) n.s.</td><td>0.41 (0.13)**</td><td>0.37 (0.14)**</td><td>0.17 (0.19) n.s.</td></tr><tr><td>PCA</td><td>0.66 (0.16)***</td><td>0.10 (0.13) n.s.</td><td>0.05 (0.14) n.s.</td><td>0.61 (0.18)***</td></tr><tr><td><bold><italic>R</italic></bold><sup>2</sup> (Model 1)</td><td><italic>0.03</italic></td><td><italic>0.01</italic></td><td><italic>0.01</italic></td><td><italic>0.01</italic></td></tr><tr><td align="left"><bold>MODEL 2</bold></td></tr><tr><td>CTAX</td><td>0.11 (0.16) n.s.</td><td>0.42 (0.13)**</td><td>0.38 (0.14)**</td><td>0.16 (0.20) n.s.</td></tr><tr><td>PCA</td><td>0.68 (0.16)***</td><td>0.04 (0.13) n.s.</td><td>−0.01 (0.14) n.s.</td><td>0.60 (0.19)***</td></tr><tr><td>Gender</td><td>0.11 (0.14) n.s.</td><td>0.16 (0.11) n.s.</td><td>−0.01 (0.12) n.s.</td><td>0.17 (0.16) n.s.</td></tr><tr><td>Age</td><td>0.04 (0.07) n.s.</td><td>−0.24 (0.06)***</td><td>−0.10 (0.06) n.s.</td><td>−0.08 (0.08) n.s.</td></tr><tr><td>Income</td><td>−0.32 (0.10)***</td><td>−0.19 (0.08)*</td><td>−0.16 (0.08) n.s.</td><td>−0.23 (0.125) n.s.</td></tr><tr><td>Pro‐environmental attitude</td><td>0.40 (0.07)***</td><td>0.39 (0.06)***</td><td>0.50 (0.06)***</td><td>0.39 (0.08)***</td></tr><tr><td><bold><italic>R</italic></bold><sup>2</sup> (Model 2)</td><td><italic>0.09</italic></td><td><italic>0.08</italic></td><td><italic>0.09</italic></td><td><italic>0.05</italic></td></tr><tr><td align="left"><bold>MODEL 3</bold></td></tr><tr><td>CTAX</td><td>−0.10 (0.19) n.s.</td><td>0.24 (0.16) n.s.</td><td>0.38 (0.16)*</td><td>0.23 (0.26) n.s.</td></tr><tr><td>PCA</td><td>0.60 (0.17) n.s.</td><td>−0.07 (0.15) n.s.</td><td>0.03 (0.16) n.s.</td><td>0.74 (0.26)**</td></tr><tr><td>Gender</td><td>0.13 (0.14) n.s.</td><td>0.17 (0.11) n.s.</td><td>−0.01 (0.12) n.s.</td><td>0.19 (0.16) n.s.</td></tr><tr><td>Age</td><td>0.25 (0.12)*</td><td>0.07 (0.10) n.s.</td><td>−0.02 (0.10) n.s.</td><td>−0.04 (0.15) n.s.</td></tr><tr><td>Income</td><td>−0.06 (0.17) n.s.</td><td>0.10 (0.14) n.s.</td><td>−0.19 (0.15) n.s.</td><td>−0.54 (0.24)*</td></tr><tr><td>Pro‐environmental attitude (PEA)</td><td>0.19 (0.12) n.s.</td><td>0.29 (0.09)***</td><td>0.17 (0.09) n.s.</td><td>0.18 (0.14) n.s.</td></tr><tr><td>PEA × CTAX</td><td>0.53 (0.17)**</td><td>0.25 (0.13) n.s.</td><td>0.61 (0.14)***</td><td>0.35 (0.21) n.s.</td></tr><tr><td>PEA × PCA</td><td>0.19 (0.17) n.s.</td><td>0.18 (0.14) n.s.</td><td>0.44 (0.14)**</td><td>0.32 (0.20) n.s.</td></tr><tr><td>Income × CTAX</td><td>−0.60 (0.26)*</td><td>−0.54 (0.21)**</td><td>−0.02 (0.21) n.s.</td><td>0.31 (0.32) n.s.</td></tr><tr><td>Income × PCA</td><td>−0.33 (0.23) n.s.</td><td>−0.34 (0.20) n.s.</td><td>0.12 (0.20) n.s.</td><td>0.48 (0.29) n.s.</td></tr><tr><td>Age×CTAX</td><td>−0.35 (0.17)*</td><td>−0.61 (0.14)***</td><td>−0.40 (0.14)**</td><td>0.01 (0.20) n.s.</td></tr><tr><td>Age × PCA</td><td>−0.27 (.16) n.s.</td><td>−0.32 (0.14)*</td><td>0.17 (0.14) n.s.</td><td>−0.16 (0.19) n.s.</td></tr><tr><td><bold><italic>R</italic></bold><sup>2</sup> (Model 3)</td><td><italic>0.11</italic></td><td><italic>0.11</italic></td><td><italic>0.12</italic></td><td><italic>0.06</italic></td></tr></tbody></table> </ephtml> </p> <ulist> <item>5 <emph>Note:</emph></item> <item>6 * * <emph>p</emph> < 0.05;</item> <item>7 ** ** <emph>p</emph> < 0.01;</item> <item>8 *** *** <emph>p</emph> < 0.001; n.s. = nonsignificant.</item> </ulist> <hd id="AN0065131857-17">RESULTS</hd> <p></p> <hd id="AN0065131857-18">Willingness to Change Behavior</hd> <p>Table 1 shows the percentage of people in each group who indicated a willingness to make any change to their behavior (as opposed to those who are unwilling to change behavior). All three framings were found to be effective in promoting a stated willingness to change behavior. Most notable, however, is the willingness to reduce personal mileage and dairy consumption under PCA framing.</p> <p>Table 2 shows the results of the four sets of logistic regressions carried out to test for an effect of the framing conditions on willingness to change behavior. There was a significant effect of the PCA condition (Model 1) for all energy‐use behaviors, with the exception of washing machine temperature reduction. Those participants given the PCA framing were more likely to state a willingness to make reductions than those in the Etax framing. No significant differences were found between the Ctax and Etax framings (Model 1).</p> <p>The second model in Table 2 shows that—across framings and energy‐use behaviors—those with higher pro‐environmental attitudes were more likely to state a willingness to make any adjustments to their behavior. Additional main effects were also found for income (those with higher income were less likely to express willingness to adjust mileage) and gender (men were less likely to be willing to adjust washing machine temperature). The third model in Table 2 shows a number of significant interactions between pro‐environmental attitude and the framing conditions. In the case of thermostat reduction and washing machine temperature reduction, people with a higher pro‐environmental attitude showed greater willingness to make reductions in the PCA condition (than in the Etax condition). People with a higher pro‐environmental attitude showed greater willingness to make reductions in the Ctax condition in the case of mileage and washing machine temperature reduction. Further interactions were also obtained between age, income, and framing conditions: People with a higher income were less willing to lower their mileage in comparison to the Etax condition, while older participants were less willing to lower their thermostat in the Ctax and PCA conditions. Nevertheless, the same significant main effects of the PCA framing condition were found in Model 3 as were obtained in Model 1. No significant main effects of Ctax were found in Model 3.</p> <hd id="AN0065131857-19">Extent of Behavior Change Indicated</hd> <p>Table 3 shows the results of the four sets of ordinal regressions carried out to test for an effect of the framing conditions on the extent of willingness to change behavior indicated by participants.</p> <p>There was a significant effect of the PCA condition (Model 1) in the context of mileage reduction and reduction in dairy consumption. Significant effects were found for the Ctax condition in the context of thermostat and washing machine reduction (Model 1).</p> <p>The second model in Table 3 shows that—across framings and energy‐use behaviors—those with higher pro‐environmental attitudes were more likely to indicate a willingness to adjust their behavior. Significant main effects were also found for income—where those with higher income indicated lesser reductions to their mileage and thermostats than those with lower salaries. In the case of thermostat reduction, older participants indicated significantly lower reductions than did younger participants.</p> <p>The third model in Table 3 shows a number of significant interactions between pro‐environmental attitude and the framing conditions. For example, in the case of mileage reduction, people with a higher pro‐environmental attitude indicated greater reductions in mileage in the Ctax condition, while older respondents with a higher income were less likely to indicate reductions to their annual mileage in the Ctax condition. For the PCA framing, significant interactions were found, whereby older participants were less likely to indicate reductions to their thermostats in the PCA condition; those with a higher pro‐environmental attitude were more likely to indicate reductions in the PCA condition. Across the regressions, a significant main effect of Ctax remained for Model 3 in the case of washing machine temperature reduction and for PCA in the case of reduction in dairy consumption.</p> <hd id="AN0065131857-20">Summary and Interpretation of Results</hd> <p>The results indicate a consistent effect of the PCA manipulation on willingness to change behavior, with main effects found for three of the four energy‐use behaviors. For two of four of the energy‐use behaviors, PCA was also influential on extent of behavior change. It appears that the PCA manipulation is more pronounced in the case of driving behavior and the spillover variable (dairy consumption) than for the thermostat reduction or washing machine variables.</p> <p>The results also indicate a behavioral effect of the Ctax manipulation on the extent of behavior change in the case of thermostat reduction and washing machine temperature reduction. Ctax did not, however, emerge as a significant predictor of willingness to reduce any category of behavior in the full models.</p> <p>Not surprisingly, pro‐environmental attitude has a consistent and strong effect as a predictor variable across the regressions carried out. Perhaps of more interest are the interactions obtained between the framing conditions and pro‐environmental attitude. Those with higher pro‐environmental attitudes were in a number of cases willing to reduce their energy use in the Ctax and PCA conditions—that is to say, they appeared more responsive to these policy framings.</p> <p>It should be noted that, while containing significant predictors, the full models obtained only account for a relatively small proportion of variance (around 10 percent for each full model), with experimental conditions forming only a part of this. In the context of an experimental manipulation, such low effect sizes are not crucial because we are interested here to see only whether there is an effect and do not attempt to infer how powerful this would be under real‐life conditions.</p> <hd id="AN0065131857-21">DISCUSSION</hd> <p>The present study supports the first hypothesis that a price signal—even relatively small—has an impact on willingness to change behavior. In addition, we find some support for the second hypothesis, that "carbon visible" policies (Ctax and PCA) are in general terms better able to promote stated intentions to change behavior than an energy tax. Given the experimental manipulations used to compare carbon visible versus nonvisible framings, we can conclude that the presentation of policy choices in these terms was influential.</p> <p>As to the mechanisms by which this may have occurred, the use of an explicitly pro‐environmental rationale for a policy (namely, to address climate change) and reference to carbon impacts are likely to have served in the context of the present study to bring participants' preexisting pro‐environmental personal norms to the fore, influencing behavioral response. The interactions obtained in the regression models furthermore suggest that the carbon‐visible framings may have been particularly effective for those with higher pro‐environmental attitudes. Such an effect may best be explained with reference to Schwartz's ([<reflink idref="bib31" id="ref50">31</reflink>]) norm‐activation theory, which proposes that behaviors are influenced by personal norms most saliently where these are activated; that is, where individuals are aware of the positive impact of their actions and take personal responsibility for a problem, in this case climate change. That the Ctax and PCA framings drew attention to the rationales for the policies is likely to have led to such an activation effect. Other studies have also found that personal norms affect willingness to reduce energy use and other emissions‐related behavior (Black, Stern, & Elworth, [<reflink idref="bib5" id="ref51">5</reflink>]; Thøgersen, [<reflink idref="bib39" id="ref52">39</reflink>]; Nordlund & Garvill, [<reflink idref="bib24" id="ref53">24</reflink>]; Bamberg, Hunecke, & Blobaum, [<reflink idref="bib3" id="ref54">3</reflink>]; Verplanken et al., [<reflink idref="bib42" id="ref55">42</reflink>]), and energy policies are seen as more acceptable where they reflect views about personal and moral responsibilities (Steg, Dreijerink, & Abrahamse, [<reflink idref="bib35" id="ref56">35</reflink>]).</p> <p>The third hypothesis of this study—that PCA would lead to greater willingness and extent of behavior change—is not supported in a straightforward manner. While it would appear that PCA is more effective in prompting willingness to adjust behavior, results are more equivocal in respect of extent of change measures. If, as we proposed, PCA has the potential to operate in part through a mental accounting effect (see also Capstick & Lewis, [<reflink idref="bib8" id="ref57">8</reflink>]; Parag & Strickland, [<reflink idref="bib27" id="ref58">27</reflink>]) whereby carbon allowances are perceived as a limited resource to be conserved, a more pronounced influence on degree of behavioral change could have been anticipated. Higher levels of stated intentions to reduce energy within a PCA framing have indeed been obtained by others (Bristow et al., [<reflink idref="bib6" id="ref59">6</reflink>]), but this is not replicated convincingly in the present study. This could be due to a failure to bring about mental accounting processes through the survey‐based methods used or could simply reflect their absence. Should a role for mental accounting in PCA be relevant, its detection may require an alternative methodology, such as participants' exposure to scenarios in which one's personal carbon allowance is able to be perceived as depleting over time and contingent on choices made in a cumulative fashion (Capstick & Lewis, [<reflink idref="bib8" id="ref60">8</reflink>]).</p> <p>The fourth hypothesis of this study—that PCA would lead to a greater spillover effect—was supported in the study. The dairy question entailed no direct financial or carbon cost, and hence any stated willingness to change behavior could not be explained from a rational economic position. Should carbon visibility alone be responsible for this effect, we would expect both the Ctax and PCA conditions to lead to significant effects. Our finding therefore suggests that while both Ctax and PCA lead to activation of pro‐environmental norms, there are some differences in the level or process of activation between these policy framings. However, further research is needed to better explore this effect.</p> <p>It is unclear why more consistent findings were obtained for the driving question than in other cases. It may be the case that differences in the types of energy‐use behavior are important. For example, driving behavior as presented in this study can be seen as cumulative (number of miles driven over a year), whereas space heating and washing machine temperature is conveyed as more fixed (a thermostat setting). The cost figures used in the present study in the case of driving behavior are also absolutely larger, and so may have prompted greater consideration.</p> <p>One policy implication of our findings is that it may be possible to encourage people to save further emissions, given a low price signal, by altering the framing. While a higher price signal is likely to bring greater emissions reduction, it would be less publicly supported, especially in times of economic decline. (Having said that, we are well aware that high setup and running costs of any scheme, in particular a PCA scheme, would not automatically be publicly supported.)</p> <p>Another policy implication is that in order to maximize behavioral impact of policies, carbon needs to be visible. The risk for carbon tax is that if it is not well emphasized, people will attend only to the overall bottom line, ignoring the breakdown of price between use and carbon component (similar to VAT). In this case, the impact of a carbon tax on behavior might yet become similar to that of general tax.</p> <p>The interactions obtained between the framings and sociodemographic variables—in particular age and income—suggest that the same policy framing could impact different sections of society in different—and sometime opposite—ways. Previous studies have pointed to the cooperation on the one hand and antagonism on the other hand that carbon tax, carbon offset (Hardisty, Johnson, & Weber, [<reflink idref="bib17" id="ref61">17</reflink>]), and PCT (Parag & Eyre, [<reflink idref="bib26" id="ref62">26</reflink>]) schemes raise in various sectors. Hence, a further policy implication is that in the process of designing and implementing an energy or carbon policy, special consideration should be given to the perceptions and responses of those groups that may react negatively toward it. This might entail public consultation, tailored information schemes, or special campaigns that target these specific sectors and market the policy in a way that increases its public acceptability and support.</p> <p>It was beyond the scope of the present study to draw any conclusions about possible effects of social norms in the case of PCA. However, it has been suggested that PCA may have particular benefits in drawing out a "common purpose" (Fleming, [<reflink idref="bib15" id="ref63">15</reflink>]) such that new norms of socially fair carbon consumption are underlined. One of the (many) barriers that have been emphasized as contributing to lack of personal engagement with carbon reduction has been the "tragedy of the commons" interpretation (e.g., see Stoll‐Kleeman, O'Riordan, & Jaeger, [<reflink idref="bib36" id="ref64">36</reflink>]) and concern about the "free‐rider effect" (e.g., see Lorenzoni, Nicholson, & Whitmarsh, [<reflink idref="bib21" id="ref65">21</reflink>]). It has been argued that PCA, at least in principle, moves some way toward presenting a new social norm wherein fair and equal carbon usage is underlined (Parag & Strickland, [<reflink idref="bib28" id="ref66">28</reflink>]). However, neither the present study nor any other has yet been able to test this proposition.</p> <p>A limitation of the present study was the measurement of participants' self‐reported intentions to change behavior, rather than actual behavior change. Behavioral intention is very commonly used as a proxy for behavior in the psychological literature, with studies typically finding that a "medium‐to‐large" change in intention leads to a "small‐to‐medium" change in behavior (Webb & Sheeran, [<reflink idref="bib43" id="ref67">43</reflink>]), although the links between intentions and actual behavior are not always strong (Sheeran, [<reflink idref="bib32" id="ref68">32</reflink>]).</p> <p>A further limitation was the use of a constant ratio of carbon to financial costs within and between experimental conditions. Future research could benefit from varying marginal tax rates to ascertain at what point taxation and PCA costs are most consequential.</p> <p>In summary, the present study adds to a growing body of work attempting to provide empirical evidence of some aspect of the anticipated behavioral response to PCA and carbon taxation (see also Bristow et al., [<reflink idref="bib6" id="ref69">6</reflink>]; Capstick & Lewis, [<reflink idref="bib8" id="ref70">8</reflink>]). As these policies are not yet implemented, and given the lack of empirical evidence for PCA effects—which have been more extensively discussed at a theoretical and abstract level—this study is valuable for its contribution to the understanding of these policy mechanisms. Similar to the study by Bristow et al. ([<reflink idref="bib6" id="ref71">6</reflink>]), it demonstrates the utility of applying a framing‐based experimental paradigm that is intended to test for theorized effects of novel emissions‐reduction policy instruments.</p> <hd id="AN0065131857-22">Acknowledgements</hd> <p>This research was conducted under the auspices of the UK Energy Research Centre (UKERC), funded by the Natural Environment Research Council (grant number NE/G007748/1). Deborah Strickland of Oxford University and Professor Alan Lewis of the University of Bath offered valuable insights and assistance with the design and conduct of the survey. Two anonymous reviewers contributed substantially to the final version of the article.</p> <hd id="AN0065131857-23">APPENDIX An Example of the Different Framings Followed by One of the Questions</hd> <p></p> <hd id="AN0065131857-24">PCA FORMS</hd> <p></p> <hd id="AN0065131857-25">Overview</hd> <p>This survey asks you to consider what choices you would make upon the implementation of a scheme termed <emph>Personal Carbon Allowances</emph>.</p> <p>"Personal Carbon Allowances" are designed to get the country to reduce its carbon dioxide (or "carbon") emissions in order to combat climate change. Carbon emissions from individuals arise from actions such as driving a car, flying on holiday, heating a home, and using domestic appliances.</p> <hd id="AN0065131857-26">Question No. 2</hd> <p>It has been calculated that every 1°C of your heating and boiler thermostat is equivalent to around 300 carbon units over the course of a year (about 6 percent of your annual carbon allowance). For example, a home heated to 20°C would use 300 carbon units less than one heated to 21°C.</p> <p>For every 1°C reduction of your thermostat, you would therefore be using approximately 300 units less of your 5,000 unit allowance. This would be equivalent to about £30 to buy, sell or keep.</p> <hd id="AN0065131857-27">CTAX FORMS</hd> <p></p> <hd id="AN0065131857-28">Overview</hd> <p>This survey asks you to consider what choices you would make upon the implementation of a <emph>carbon taxation</emph> scheme.</p> <p>Carbon taxation is designed to get the country to reduce its carbon dioxide (or "carbon") emissions in order to combat climate change. Carbon emissions from individuals arise from actions such as driving a car, flying on holiday, heating a home, and using domestic appliances.</p> <hd id="AN0065131857-29">Question No. 2</hd> <p>It has been calculated that every 1°C of your room‐heating thermostat would result in an additional cost via a carbon tax scheme of around £30, over the course of a year. For example, a home heated to 20°C would pay £30 less carbon tax than one heated to 21°C.</p> <p>For every 1°C reduction of your thermostat, you would therefore pay £30 less of the new carbon tax.</p> <hd id="AN0065131857-30">ETAX FORMS</hd> <p></p> <hd id="AN0065131857-31">Overview</hd> <p>This survey asks you to consider what choices you would make upon the implementation of a new <emph>fuel and energy taxation</emph> scheme.</p> <hd id="AN0065131857-32">Question No. 2</hd> <p>It has been calculated that every 1°C of your heating and boiler thermostat would result in an additional cost via the new tax scheme of around £30, over the course of a year. For example, a home heated to 20°C would pay £30 less tax than one heated to 21°C.</p> <p>For every 1°C reduction of your thermostat, you would therefore pay £30 less of the new tax.</p> <p>Each participant received only one version of this description followed by the same question:</p> <p>Under the circumstances described by how much would you turn down your room thermostat?</p> <p></p> <ulist> <item> I would not turn it down</item> <p></p> <item> I would lower my thermostat by:</item> <p></p> <item> 1°C</item> <p></p> <item> 2°C</item> <p></p> <item> 3°C</item> <p></p> <item> More than 3°C</item> </ulist> <ref id="AN0065131857-33"> <title> Footnotes </title> <blist> <bibl id="bib1" idref="ref3" type="bt">1</bibl> <bibtext> All appendices are available at the end of this article as it appears in JPAM online. See the complete article at <ulink href="http://wileyonlinelibrary.com">http://wileyonlinelibrary.com</ulink>.</bibtext> </blist> </ref> <ref id="AN0065131857-34"> <title> REFERENCES </title> <blist> <bibtext> Attari, S. Z., DeKay, M. L., Davidson, C. I., & de Bruine, W. B. (2010). Public perceptions of energy consumption and savings. Proceedings of the National Academy of Sciences, 107, 16054 – 16059.</bibtext> </blist> <blist> <bibl id="bib2" idref="ref20" type="bt">2</bibl> <bibtext> Baker, P., & Blundell, R. (1991). The microeconometric approach to modelling energy demand: Some results for UK households. Oxford Review of Economic Policy, 7, 54 – 76.</bibtext> </blist> <blist> <bibl id="bib3" idref="ref48" type="bt">3</bibl> <bibtext> Bamberg, S., Hunecke, M., & Blobaum, A. (2007). Social context, personal norms and the use of public transportation: Two field studies. Journal of Environmental Psychology, 27, 190 – 203.</bibtext> </blist> <blist> <bibl id="bib4" idref="ref2" type="bt">4</bibl> <bibtext> BERR. (2007). Meeting the energy challenge: A white paper on energy. UK Department for Business, Enterprise and Regulatory Reform. Retrieved May 4, 2011, from <ulink href="http://www.berr.gov.uk/files/file39387.pdf">http://www.berr.gov.uk/files/file39387.pdf</ulink>.</bibtext> </blist> <blist> <bibl id="bib5" idref="ref23" type="bt">5</bibl> <bibtext> Black, J. S., Stern, P. C., & Elworth, J. T. (1985). Personal and contextual influences on househould energy adaptations. Journal of Applied Psychology, 70, 3 – 21.</bibtext> </blist> <blist> <bibl id="bib6" idref="ref37" type="bt">6</bibl> <bibtext> Bristow, A., Zanni, A., Wardman, M., & Chintakaya, P. (2008). PCA: Using stated preferences to investigate behavioral response. London : RSA (Carbon Limited Project).</bibtext> </blist> <blist> <bibl id="bib7" idref="ref30" type="bt">7</bibl> <bibtext> Capstick, S., & Lewis, A. (2008). PCA: Perspectives from psychology and behavioral economics. London : Institute for Public Policy Research.</bibtext> </blist> <blist> <bibl id="bib8" idref="ref31" type="bt">8</bibl> <bibtext> Capstick, S., & Lewis, A. (2010). Effects of PCA on decision‐making. Climate Policy, 10, 369 – 384.</bibtext> </blist> <blist> <bibl id="bib9" idref="ref4" type="bt">9</bibl> <bibtext> Defra. (2008a). Climate Change Act. London : UK Department for Environment, Food and Rural Affairs. Retrieved May 4, 2011, from <ulink href="http://www.decc.gov.uk/en/content/cms/legislation/cc%5fact%5f08/cc%5fact%5f08.aspx">http://www.decc.gov.uk/en/content/cms/legislation/cc%5fact%5f08/cc%5fact%5f08.aspx</ulink>.</bibtext> </blist> <blist> <bibtext> Defra. (2008b). Synthesis report on the findings from Defra's pre‐feasibility study into personal carbon trading. London : UK Department for Environment, Food and Rural Affairs.</bibtext> </blist> <blist> <bibtext> Dietz, T. (2010). Narrowing the US energy efficiency gap. Proceedings of the National Academy of Sciences, 107, 16007 – 16008.</bibtext> </blist> <blist> <bibtext> Dietz, T., Gardner, G. T., Gilligan, J., Stern, P. C., & Vandenbergh, M. P. (2009). Household actions can provide a behavioral wedge to rapidly reduce U.S. carbon emissions. Proceedings of the National Academy of Sciences, 106, 18452 – 18456.</bibtext> </blist> <blist> <bibtext> Environmental Audit Committee. (2008). Personal carbon trading. Fifth Report of Session 2007–08. Retrieved May 4, 2011, from <ulink href="http://www.publications.parliament.uk/pa/cm200708/cmselect/cmenvaud/565/565.pdf">http://www.publications.parliament.uk/pa/cm200708/cmselect/cmenvaud/565/565.pdf</ulink>.</bibtext> </blist> <blist> <bibtext> Fawcett, T., & Parag, Y. (2010). An introduction to personal carbon trading. Climate Policy, 10, 329 – 338.</bibtext> </blist> <blist> <bibtext> Fleming, D. (1997). Tradable quotas: Setting limits to carbon emissions. Discussion Paper 11. London : The Lean Economy Initiative.</bibtext> </blist> <blist> <bibtext> Halvorsen, B., & Larsen, B. M. (2001). The flexibility of household electricity demand over time. Resource and Energy Economics, 23, 1 – 18.</bibtext> </blist> <blist> <bibtext> Hardisty, D. J., Johnson, E. J., & Weber, E. U. (2010). A dirty word or a dirty world? Attribute framing, political affiliation, and query theory. Psychological Science, 21, 86 – 92.</bibtext> </blist> <blist> <bibtext> Hillman, M., & Fawcett, T. (2004). How we can save the planet. London : Penguin.</bibtext> </blist> <blist> <bibtext> International Energy Agency (IEA). (2007). Energy use in the new millennium: Trends in International Energy Agency countries. Paris : International Energy Agency.</bibtext> </blist> <blist> <bibtext> Levin, I. P., Schneider, S. L., & Gaeth, G. J. (1998). All frames are not created equal: A typology and critical analysis of framing effects. Organizational Behavior and Human Decision Processes, 76, 149 – 188.</bibtext> </blist> <blist> <bibtext> Lorenzoni, I., Nicholson‐Cole, S., & Whitmarsh, L. (2007). Barriers perceived to engaging with climate change among the UK public and their policy implications. Global Environmental Change, 17, 445 – 459.</bibtext> </blist> <blist> <bibtext> Lutzenhiser, L. (1993). Social and behavioral aspects of energy use. Annual Review of Energy and the Environment, 18, 247 – 289.</bibtext> </blist> <blist> <bibtext> Nisbet, M.C. (2009). Communicating climate change: Why frames matter for public engagement. Environment, 51, 12 – 23.</bibtext> </blist> <blist> <bibtext> Nordlund, A. M., & Garvill, J. (2003). Effects of values, problem awareness, and personal norm on willingness to reduce personal car use. Journal of Environmental Psychology, 23, 339 – 347.</bibtext> </blist> <blist> <bibtext> Oxera. (2006). Policies for energy efficiency in the UK household sector. London : UK Department for Environment, Food and Rural Affairs. Retrieved May 4, 2011, from <ulink href="http://www.decc.gov.uk/assets/decc/what%20we%20do/supporting%20consumers/saving%5fenergy/analysis/oxera‐report.pdf">http://www.decc.gov.uk/assets/decc/what%20we%20do/supporting%20consumers/saving%5fenergy/analysis/oxera‐report.pdf</ulink>.</bibtext> </blist> <blist> <bibtext> Parag, Y., & Eyre, N. (2010). Barriers to personal carbon trading in the policy arena. Climate Policy, 10, 353 – 368.</bibtext> </blist> <blist> <bibtext> Parag, Y., & Strickland, D. (2009). Personal carbon budgeting: What people need to know, learn and have in order to manage and live within a carbon budget, and the policies that could support them. UKERC Working Paper UKERC/WP/DR/2009/014. Retrieved May 4, 2011, from <ulink href="http://www.eci.ox.ac.uk/research/energy/downloads/paragstrickland09pcbudget.pdf">http://www.eci.ox.ac.uk/research/energy/downloads/paragstrickland09pcbudget.pdf</ulink>.</bibtext> </blist> <blist> <bibtext> Parag, Y., & Strickland, D. (2011). Personal carbon trading: A radical policy option for reducing emissions from the domestic sector. Environment: Science and Policy for Sustainable Development, 53, 29 – 37.</bibtext> </blist> <blist> <bibtext> Reiss, P. C., & White, M. W. (2005). Household electricity demand, revisited. Review of Economic Studies, 72, 853 – 883.</bibtext> </blist> <blist> <bibtext> Roberts, S., & Thumin, J. (2006). A rough guide to individual carbon trading: The ideas, the issues and the next steps. London : UK Department for Environment, Food and Rural Affairs. Retrieved May 4, 2011, from <ulink href="http://www.carbonequity.info/PDFs/defranov06.pdf">http://www.carbonequity.info/PDFs/defranov06.pdf</ulink>.</bibtext> </blist> <blist> <bibtext> Schwartz, S. H. (1977). Normative influences on altruism. In L. Berkowitz (Ed.), Advances in experimental social psychology, Vol. 10 (pp. 221 – 279). New York : NY Academic.</bibtext> </blist> <blist> <bibtext> Sheeran, P. (2002). Intention‐behavior relations: A conceptual and empirical review. European Review of Social Psychology, 12, 1 – 36.</bibtext> </blist> <blist> <bibtext> Spence, A., & Pidgeon, N. (2010). Framing and communicating climate change: The effects of distance and outcome frame manipulations. Global Environmental Change, 20, 656 – 667.</bibtext> </blist> <blist> <bibtext> Steg, L. (2008). Promoting household energy conservation. Energy Policy, 36, 4449 – 4453.</bibtext> </blist> <blist> <bibtext> Steg, L., Dreijerink, L., & Abrahamse, W. (2005). Factors influencing the acceptability of energy policies: Testing VBN theory. Journal of Environmental Psychology, 25, 415 – 425.</bibtext> </blist> <blist> <bibtext> Stoll‐Kleeman, S., O'Riordan, T., & Jaeger, C. (2001). The psychology of denial concerning climate mitigation measures: Evidence from Swiss focus groups. Global Environmental Change, 11, 107 – 118.</bibtext> </blist> <blist> <bibtext> Swim, J., Clayton, S., Doherty, T., Gifford, R., Howard, G., Reser, J., Stern, P., & Weber, E. (2009). Psychology and global climate change: Addressing a multifaceted phenomenon and set of challenges. Washington, DC : American Psychological Association Task Force on the Interface Between Psychology and Global Climate Change. Retrieved May 4, 2011, from <ulink href="http://www.apa.org/science/about/publications/climate‐change‐booklet.pdf">http://www.apa.org/science/about/publications/climate‐change‐booklet.pdf</ulink>.</bibtext> </blist> <blist> <bibtext> Thaler, R. H. (1999). Mental accounting matters. Journal of Behavioral Decision Making, 12, 183 – 206.</bibtext> </blist> <blist> <bibtext> Thøgersen, J. (1999). The ethical consumer: Moral norms and packaging choice. Journal of Consumer Policy, 22, 439 – 460.</bibtext> </blist> <blist> <bibtext> Thøgersen, J., & Crompton, T. (2009). Simple and painless? The limitations of spillover in environmental campaigning. Journal of Consumer Policy, 32, 141 – 163.</bibtext> </blist> <blist> <bibtext> Tversky, A., & Kahneman, D. (1981). The framing of decisions and the psychology of choice. Science, 211, 453 – 458.</bibtext> </blist> <blist> <bibtext> Verplanken, B., Walker, I., Davis, A., & Jurasek, M. (2008). Context change and travel mode choice: Combining the habit discontinuity and self‐activation hypotheses. Journal of Environmental Psychology, 28, 121 – 127.</bibtext> </blist> <blist> <bibtext> Webb, T. L., & Sheeran, P. (2006). Does changing behavioral intentions engender behavior change? A meta‐analysis of the experimental evidence. Psychological Bulletin, 132, 249 – 268.</bibtext> </blist> <blist> <bibtext> Whitmarsh, L. (2009). Behavioral responses to climate change: Asymmetry of intentions and impacts. Journal of Environmental Psychology, 29, 13 – 23.</bibtext> </blist> <blist> <bibtext> Whitmarsh, L., & O'Neill, S. (2010). Green identity, green living? The role of pro‐environmental self‐identity in determining consistency across diverse pro‐environmental behaviours. Journal of Environmental Psychology, 30, 305 – 314.</bibtext> </blist> </ref> <aug> <p>By Yael Parag; Stuart Capstick and Wouter Poortinga</p> <p>Reported by Author; Author; Author</p> </aug> <nolink nlid="nl1" bibid="bib19" firstref="ref1"></nolink> <nolink nlid="nl2" bibid="bib30" firstref="ref6"></nolink> <nolink nlid="nl3" bibid="bib14" firstref="ref7"></nolink> <nolink nlid="nl4" bibid="bib10" firstref="ref8"></nolink> <nolink nlid="nl5" bibid="bib13" firstref="ref9"></nolink> <nolink nlid="nl6" bibid="bib28" firstref="ref10"></nolink> <nolink nlid="nl7" bibid="bib40" firstref="ref11"></nolink> <nolink nlid="nl8" bibid="bib45" firstref="ref12"></nolink> <nolink nlid="nl9" bibid="bib18" firstref="ref13"></nolink> <nolink nlid="nl10" bibid="bib17" firstref="ref14"></nolink> <nolink nlid="nl11" bibid="bib16" firstref="ref18"></nolink> <nolink nlid="nl12" bibid="bib29" firstref="ref19"></nolink> <nolink nlid="nl13" bibid="bib22" firstref="ref21"></nolink> <nolink nlid="nl14" bibid="bib25" firstref="ref22"></nolink> <nolink nlid="nl15" bibid="bib24" firstref="ref24"></nolink> <nolink nlid="nl16" bibid="bib37" firstref="ref25"></nolink> <nolink nlid="nl17" bibid="bib34" firstref="ref27"></nolink> <nolink nlid="nl18" bibid="bib44" firstref="ref28"></nolink> <nolink nlid="nl19" bibid="bib11" firstref="ref29"></nolink> <nolink nlid="nl20" bibid="bib38" firstref="ref32"></nolink> <nolink nlid="nl21" bibid="bib27" firstref="ref35"></nolink> <nolink nlid="nl22" bibid="bib12" firstref="ref40"></nolink> <nolink nlid="nl23" bibid="bib20" firstref="ref41"></nolink> <nolink nlid="nl24" bibid="bib41" firstref="ref42"></nolink> <nolink nlid="nl25" bibid="bib23" firstref="ref44"></nolink> <nolink nlid="nl26" bibid="bib33" firstref="ref45"></nolink> <nolink nlid="nl27" bibid="bib31" firstref="ref50"></nolink> <nolink nlid="nl28" bibid="bib39" firstref="ref52"></nolink> <nolink nlid="nl29" bibid="bib42" firstref="ref55"></nolink> <nolink nlid="nl30" bibid="bib35" firstref="ref56"></nolink> <nolink nlid="nl31" bibid="bib26" firstref="ref62"></nolink> <nolink nlid="nl32" bibid="bib15" firstref="ref63"></nolink> <nolink nlid="nl33" bibid="bib36" firstref="ref64"></nolink> <nolink nlid="nl34" bibid="bib21" firstref="ref65"></nolink> <nolink nlid="nl35" bibid="bib43" firstref="ref67"></nolink> <nolink nlid="nl36" bibid="bib32" firstref="ref68"></nolink>
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  Data: Policy Attribute Framing: A Comparison between Three Policy Instruments for Personal Emissions Reduction
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  Data: <searchLink fieldCode="AR" term="%22Parag%2C+Yael%22">Parag, Yael</searchLink><br /><searchLink fieldCode="AR" term="%22Capstick%2C+Stuart%22">Capstick, Stuart</searchLink><br /><searchLink fieldCode="AR" term="%22Poortinga%2C+Wouter%22">Poortinga, Wouter</searchLink>
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  Data: <searchLink fieldCode="SO" term="%22Journal+of+Policy+Analysis+and+Management%22"><i>Journal of Policy Analysis and Management</i></searchLink>. Aut 2011 30(4):889-905.
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  Data: John Wiley & Sons, Inc. Subscription Department, 111 River Street, Hoboken, NJ 07030-5774. Tel: 800-825-7550; Tel: 201-748-6645; Fax: 201-748-6021; e-mail: subinfo@wiley.com; Web site: http://www3.interscience.wiley.com/browse/?type=JOURNAL
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  Data: <searchLink fieldCode="DE" term="%22Public+Policy%22">Public Policy</searchLink><br /><searchLink fieldCode="DE" term="%22Energy+Conservation%22">Energy Conservation</searchLink><br /><searchLink fieldCode="DE" term="%22Behavior+Change%22">Behavior Change</searchLink><br /><searchLink fieldCode="DE" term="%22Taxes%22">Taxes</searchLink><br /><searchLink fieldCode="DE" term="%22Comparative+Analysis%22">Comparative Analysis</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink>
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  Data: 10.1002/pam.20610
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  Data: 0276-8739
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  Data: A comparative experiment in the UK examined people's willingness to change energy consumption behavior under three different policy framings: energy tax, carbon tax, and personal carbon allowances (PCA). PCA is a downstream cap-and-trade policy proposed in the UK, in which emission rights are allocated to individuals. We hypothesized that due to economic, pro-environmental and mental accounting drivers PCA would have greater potential to deliver emissions reduction than taxation. Participants (n = 1,096) received one version of a survey with the same energy-behavior-related questions and identical incurred costs under one of the following framings: energy tax (where carbon was not mentioned), carbon tax, and PCA. Results suggest that policies that draw people's attention to carbon (PCA and carbon taxation) could have greater impact on their stated willingness to reduce energy consumption, and on the reduction amounts prompted, than would a non-overt price signal (energy tax). There is mixed evidence, however, as to whether PCA or carbon taxation would produce the largest energy demand reductions. Some indication was found for a spillover toward wider carbon conservation under the PCA framing. (Contains 1 figure, 3 tables, and 1 footnote.)
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      – SubjectFull: Behavior Change
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      – TitleFull: Policy Attribute Framing: A Comparison between Three Policy Instruments for Personal Emissions Reduction
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