The Norwegian Green Tax Commission proposes inter alia cost-effective taxes on red meat and city traffic to reduce greenhouse gas emissions and local air pollution. Implementation requires public support, but the acceptance of and willingness to pay (WTP) such taxes are not known. We conducted a national survey of the public's acceptance of and WTP the two taxes. The survey instrument showed the reduction in emissions/pollution dynamically for each tax level chosen. Despite survey information about the purpose of the taxes, only 25%, on average, were in favour of their introduction, the rest did not know, had zero WTP, or opposed the taxes. In this respect, preferences for the two taxes are similar. However, on average people are WTP approximately 90% of the cost-effective tax level for red meat, but only about 25%–35% of the tax on city traffic, depending on fuel type. The most important concern in designing environmental policy was to avoid increased economic inequality. Earmarking the tax revenue for environmentally friendly technology increased acceptable tax level for red meat. Earmarking tax revenues for reduced income tax did not increase the acceptability of proposed taxes on neither red meat nor city traffic.”

Energy generated by land-based wind power is expected to play a crucial role in the decarbonisation of the economy. However, with the looming biodiversity and nature crises, spatial allocation of wind power can no longer be considered solely a trade-off against local disamenity costs. Emphasis should also be put on wider environmental impacts, especially if these challenge the sustainability of the renewable energy transition. We suggest a modelling system for selecting among a pool of potential wind power plants (WPPs) by combining an energy system model with a GIS analysis of WPP sites and surrounding viewscapes. The modelling approach integrates monetised local disamenity and carbon sequestration costs and places constraints on areas of importance for wilderness and biodiversity (W&B). Simulating scenarios for the Norwegian energy system towards 2050, we find that the southern part of Norway is the most favourable region for wind power siting when only the energy system surplus is considered. However, when local disamenity costs (and to a lesser extent carbon costs) and W&B constraints are added successively to the scenarios, it becomes increasingly beneficial to site WPPs in the northern part of Norway. We find that the W&B constraints have the largest impact on the spatial distribution of WPPs, while the monetised costs of satisfying these constraints are relatively small. Overall, our results show that there is a trade-off between local disamenities and loss of W&B. Siting wind power plants outside the visual proximity of households has a negative impact on W&B.

We conducted a national survey on a high-quality internet panel to study landscape preferences in Norway, using photos as stimuli. We examined preference heterogeneity with respect to socio-demographic characteristics and latent topics brought up by the respondents, using ordinal logistic regression and structural topic modelling (STM), a machine learning-based analysis. We found that pasture landscapes are the most favoured (55%), while densely planted spruce forests are the least favoured (8%). The contrast was particularly strong between eastern and western Norway, between men and women, and between young and old. STM revealed that the choices were mainly driven by the preference for landscape openness, especially by women. Other important drivers were concerns regarding reforestation of former farmlands, aesthetic properties, forest management, biodiversity issues, and cultural values. Our results suggest that landscape policies may clash with socio-cultural preferences, and failure to account for these may undermine the success of a policy.

Altruistic preferences have been found to be important for explaining the substantial non-use values identified in numerous stated preference surveys. However, studies analysing the effect of altruism on willingness to pay (WTP) have underestimated the challenges of measuring altruism by stated measures. We exploit a naturally occurring decision domain to investigate the role of altruism in stated preference studies. We employ a novel dataset, collected from an Internet survey panel, that contains respondents’ past donations of earned survey coins to charities and use these data to analyse the effect of donation behaviour on the same respondents’ WTP. We analyse donation behaviour across two contingent valuation surveys on environmental topics. Donators are proven givers in an anonymous and unrelated setting, much like decision-making in a dictator game. We find that respondents’ past donations are associated with higher WTP, even after controlling forstatedmeasures of altruism, ecological, and environmental attitudes. The results suggest that measures of stated altruism fail to capture important aspects of altruism, implying that previous studies of altruism based on such measures may be questioned. The results also support research demonstrating that altruistic behaviour in one decision domain is a good predictor of altruistic behaviour in other domains.