## Public Perceptions of Climate Mitigation Policies: Evidence from Cross Country Surveys

## Source details

**Canonical URL:** [Public Perceptions of Climate Mitigation Policies: Evidence from Cross Country Surveys](https://www.imf.org/-/media/files/oap/oap-home/2023/session-2-1-public-perceptions-survey-sdn-jica-conference.pdf)

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### Context and survey design
- Presented at the IMF-JICA CONFERENCE, FEBRUARY 14, TOKYO.
- Survey span: run July 5 - Aug 11, 2022.
- Countries covered: novel surveys for 28 advanced and emerging market economies, including 11 in Asia.
- Sample size: representative surveys on more than 28,000 respondents (>1000 per country).
- Survey provider and mode: Standardized surveys run by YouGov (translated into local language as needed); online representative only in many emerging market countries.
- Core modules: Socio-economic background; Climate risk perceptions and knowledge; Views on climate policies (carbon tax, emissions trading, subsidies, regulations); International dimension and willingness to change behavior; Information treatments (policy efficacy vs. cost-of-living impacts); Open-ended question on policy aims.

### Public recognition of climate threat and timing
- Majority view climate change as a serious problem (share of respondents answering “a very serious problem” or “a fairly serious problem”).
- Perceived imminence is higher in emerging markets and correlated with country climate exposure (IMF’s INFORM Climate-driven Hazard and Exposure).
- Timing perceptions (share of responses) — aggregations shown in regional groups:
  - “Right now” responses by region (percent of respondents) — examples in Asia Pacific: 89, 79, 75, 75, 71, 70, 74, 70, 69, 68, 69, 60, 69, 79 (country-level entries shown in the source).
  - “Next 5 to 10 years” and “Over 10 years from now” and “Won't ever affect” shown in country distributions; differences across countries and regions noted.
- Correlation observed between “Climate change is affecting me or my family right now” and the IMF INFORM Climate-driven Hazard and Exposure.

### Individual drivers of risk perception
- Important correlates of higher perceived seriousness (OLS on z-scores with country fixed effects): gender (female), education (vocational/high-school, college), energy usage (car ownership, public transport use), news sources (traditional, modern), trust, support for government regulation of the economy, presence of children, age groups (35-54, 55+), employment, and income (medium, high).
- Cross-country heterogeneity:
  - Females have higher climate risk perception in Japan, but not in India.
  - More educated respondents show higher perceptions in Australia, but not in Korea.
  - News-following increases perception in Europe and the Americas, but generally not in Asia.

### Support for emission-reducing policies — levels and knowledge
- Preferred policies (share favorable responses, control group with no additional information):
  - Carbon pricing support varies by country/region: example values include 52, 55, 67, 46, 39, 58, 68, 58, 60, 60, 74, 40, 44, 47, 53 (country-level entries shown in the source).
  - Subsidies to low-carbon technologies/renewables consistently highest: example values include 65, 65, 66, 62, 45, 66, 73, 68, 61, 69, 71, 59, 56, 58, 65 (country-level entries shown in the source).
  - Regulations limiting emissions show mixed support: example values include 52, 50, 64, 44, 31, 53, 60, 48, 52, 56, 64, 40, 38, 46, 52 (country-level entries shown in the source).
- Baseline awareness of policies (share saying “Yes” they have heard of each):
  - Carbon tax: values include 65, 34, 28, 19, 34, ... (country-level entries shown in the source).
  - Cap-and-trade or emissions trading systems: values include 45, 43, 26, 21, 20, 27, ... (country-level entries shown in the source).
  - Law and regulations limiting carbon emissions: values include 70, 75, 61, 68, 63, 70, ... (country-level entries shown in the source).
  - Subsidizing renewable energy sources: values include 76, 71, 62, 55, 63, 70, ... (country-level entries shown in the source).

### Drivers of support for carbon pricing
- Key factors explaining support (share of variation in OLS on z-scores):
  - Perception of policy effectiveness and perceived benefits.
  - Perception of climate risk.
  - Equity/distributional concerns.
  - Perception of policy costs.
  - Demographic and socioeconomic controls, prior knowledge, and country fixed effects also contribute.
- Specific belief coefficients (illustrative directions from regressions):
  - Positive association: “Climate change affects you”, “Climate change serious”, “Carbon pricing effective”, “New low-carbon jobs”, “Better public transport”, “More investment in renewables”, “Better public health”, “Better air quality”, “More money for social goods and services”.
  - Negative association: beliefs that “Large corporations lose”, “Small businesses lose”, “High-income HHs lose”, “Middle-income HHs lose”, “Low-income HHs lose”, concerns about “Job losses”, “More expensive energy”, “Increased fuel costs”, “Higher prices”.

### Reasons for opposition
- Top concerns for not supporting carbon pricing (distributional differences between Advanced Economies and Emerging Markets):
  - “Increases energy costs”
  - “Costs me money”
  - “Harms economy/job losses”
  - “Ineffective at reducing climate change”
  - “Increases inequality”
  - “Not politically feasible”
  - “No need to reduce carbon/tackle climate change”
  - “My country should not pay to reduce climate change”

### Revenue recycling preferences and heterogeneity
- Which revenue uses increase support (multiple answers allowed; top choices shown):
  - Helping low-income households — high shares in many countries/regions (example aggregated flows: shown as 54, 51, 37, 48, ... in country-level entries).
  - Climate projects (renewables/green technology).
  - Social services (health care/education).
  - Reducing taxes on individuals (lower shares relative to compensating households or investing in climate projects).
- Demographic patterns (linear probability models with country fixed effects):
  - High-income, older, and educated respondents prefer earmarking revenues to clean technologies and renewables instead of compensating vulnerable households.
  - Belief that government should play a role in regulating the economy is associated with choosing revenues to support low-income households.

### Information interventions and heterogeneity
- Two randomized information treatments:
  - Policy efficacy treatment: told that carbon pricing provides correct incentives to decarbonize, can encourage innovation, and revenues can be recycled.
  - Cost-of-living (priming) treatment: told carbon pricing reduces greenhouse gases but increases cost of living.
- Effects:
  - Providing information on policy efficacy shifts the distribution toward greater support for carbon pricing; effect is statistically significant.
  - Priming on cost-of-living increases shifts distribution toward greater opposition or neutral responses.
  - Treatment effects are larger in countries with lower pre-existing knowledge of carbon pricing.

### International burden sharing and collective action
- Broad public support for collective action: many respondents agree that climate policy will only be effective if most countries adopt measures to reduce emissions.
- Views on who should pay (averages and country distributions):
  - Respondents more frequently support “All countries” paying than only rich countries; differences between Emerging Markets and Advanced Economies are significant at the 1 percent level.
  - When asked if payments should be based on “current emissions” or “past emissions”, both frames receive support across countries; country-level shares and “Don't know” responses vary.

### Policy implications and takeaways
- Devil is in the policy design:
  - Pre-existing beliefs regarding policy efficacy, costs, and progressivity are key drivers of support for carbon pricing.
  - There is scope to improve support with additional information on policy efficacy and co-benefits.
- Address distributional concerns to increase public acceptability:
  - Preferences for revenue recycling lean toward household support and investment in green technology, highlighting the need for complementary policies (e.g., strengthened social safety nets, green investment efficiency).
- Raising awareness is key:
  - Ensure continued communication on climate risks, costs of inaction, and concrete policy impacts.
- Securing international cooperation could foster political support for climate action.

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_Source: https://www.imf.org/-/media/files/oap/oap-home/2023/session-2-1-public-perceptions-survey-sdn-jica-conference.pdf_