Policies for mitigating the eutrophication of coastal waters typically focus on reducing land-based emissions. Fish and fisheries management have been suggested as a potentially efficient complementary measure. The purpose of this paper is to investigate the cost-effective achievement of targets for coastal water transparency with the help of adjusted harvesting strategies for predatory fish, biomanipulation of prey fish, and nutrient load mitigation, taking natural variations in water color into account. We develop an empirical steady-state bioeconomic model and apply it to two case areas along the Swedish Baltic Sea. Results show that prey fish stocks, which negatively affect water transparency, are reduced to a minimum in one study area, while an interior solution with a positive harvest is found in the other. Policies targeting fish management can be relevant for locally tailored strategies to mitigate eutrophication.

Livestock productivity and profitability are threatened by livestock diseases. In this study, we examine farmers' revealed preferences for testing and treating gastrointestinal parasites in sheep in Sweden, taking into account the sequential structure of these decisions. We control for preventive measures, as well as the potential impact of wildlife–livestock disease transmission on farmers' decisions. A zero-inflated ordered probit model is used to estimate the determinants of farmers' decisions, and we cross-validate the robustness of the results to alternative model assumptions. Results from the regressions are used to calculate the consequences of these choices for farmers' profits. The results show that treatment decisions are informed by faecal testing, while both testing and treatment are influenced by the grazing practices, the size of the operation and access to information. Contrary to expectations from the conceptual framework, preventive management practices are positively correlated with treatment. Farmers take multiple risk factors into account when deciding on testing, but we do not find that the same factors affect the outcome of treatment. The economic impacts are small and suggest that treatment without prior testing is more profitable for the farmer than informed treatment. If widespread treatment increases drug resistance, this could motivate policies that encourage testing.

Climate change is expected to induce climate variability. This paper aims to investigate how climate variability affects households’ decisions on sanitation facilities that differ in how much they rely on water to function. We use household-level panel data from the Ethiopia Socioeconomic Survey and location-matched, high-resolution weather data to construct climate variability variables. Using a panel fixed effects regression model, we find that increased precipitation variability is associated with a significant shift away from using improved sanitation facilities, in shared ones, toward unimproved sanitation facilities. Temperature variability, however, has the opposite impact. Both precipitation variability and temperature variability have heterogeneous impacts: the effect of precipitation variability is significant only in maleheaded households, while temperature variability particularly encourages the use of shared improved facilities in towns and urban areas. One explanation for the impact of precipitation variability is that heavy rain reduces access to piped water and sanitation networks due to physical damage. Moreover, climate variability reduces incentives to purchase water and water-related infrastructure. This occurs because precipitation variability restricts access to inputs post-flooding, while temperature variability aids the breakdown of solids in septic tanks, which would otherwise require a larger volume of water. These findings could help policymakers and practitioners implement evidence-based sanitation interventions to increase access to improved sanitation facilities. 

Greenhouse gas emissions from the transport sector can be reduced by decreasing fuel use by different means, and by blending biofuels into fossil fuels. A cost-effective combination of these measures is determined by spatially specific characteristics such as fuel demand, feedstock production costs, and greenhouse gas emissions from the feedstock production. We developed a spatially explicit model to explore the role of reduced transport fuel use and increased use of domestically produced biofuel, respectively, in a cost-effective policy for greenhouse gas abatement. The model is applied to domestic lignocellulosic biofuel from agricultural land, gasoline, and diesel for road transport in Sweden. The results show that the use of biofuel is particularly cost-effective under low and modestly stringent abatement targets. For more stringent targets, decreased fuel end use dominates the abatement portfolio. Replacing the emissions target by a biofuel production target increases the marginal cost of reducing emissions by up to 250%. With the current vehicle fleet, technical constraints on blendin possibilities limit the role of biofuels at higher target levels.

Several countries have imposed either a ban or a tax on single-use plastic packaging, motivated by their contribution to marine plastic pollution. This may lead consumers to opt for similar unregulated substitutes, potentially undermining or even counteracting the intended effect of the policy instrument. The purpose of this study is to theoretically and empirically compare the environmental and welfare effects of the first-best Pigouvian taxes on both plastic bags and a substitute (paper bags), with two alternative second-best policy instruments: a tax on plastic products alone, and a common uniform tax on all packaging materials. The empirical analysis accounts for two different types of environmental externalities from the use of both bag types: marine pollution and greenhouse gas emissions. It also compares results for two countries, Denmark and the USA, which differ in the demand for plastic and paper bags. The theoretical analysis shows that a unilateral tax on plastic bags should equal the marginal environmental damage of plastic bags minus a fraction of the marginal environmental cost of paper bags, hence being lower than the Pigouvian tax. The optimal common tax should equal a weighted average of the marginal environmental damage of the two bag types and would be lower than the Pigouvian tax on plastics if the marginal external cost of plastic bags exceeds that for paper bags. The empirical analysis shows that for default parameters, the variation in tax level across the studied scenarios is small. It also shows that if Pigouvian taxes cannot be implemented, a common uniform tax on both bag types would result in a higher welfare gain than a tax on plastic bags alone. Sensitivity analysis reveals that the level of the second-best taxes and their associated environmental and welfare impacts are sensitive to assumptions regarding the littering rate and decay rate of plastic bags in the marine environment.

To increase the speed of implementation of carbon mitigation technologies, many countries set up publicly funded investment programs, where private and/or public entities can apply for support. These schemes are often criticized for not being cost-effective. The purpose of this study is to evaluate the Swedish Climate Leap Program, which differs from most other programs through the multisector approach. We examine determinants of project approval and evaluate the heterogeneity in implicit carbon pricing across sectors. Several econometric methods are used to assess equality in carbon pricing. Results show that although the cost-effectiveness ratio plays an important role in project approval, carbon pricing differs significantly across project types. Project guidelines favor charging stations and transport measures that aid in adopting new technology and reaching economies of scale. However, the preference for transport measures is not reflected in the carbon pricing while instead energy conversion measures have a higher probability of being funded given the cost-effectiveness of the investment. Funding decisions favor densely populated municipalities, which could be motivated for investments in public goods, but is questionable for transport and housing.

The aim of this study is to compare policy schemes for ecological compensation applied at national and regional levels, using exploited inland wetlands as an example. We study whether uncertainty, due to natural variability and measurement difficulties, motivates compensation that is carried out in the same region as that of the exploited site, or whether it rather motivates nationwide compensation schemes. For this purpose, we develop an empirical, chance-constrained programming model of cost-effective wetland management. The model is spatially differentiated and accounts for heterogeneity in wetland quality across wetland types and regions. Wetland quality is defined by three alternative biodiversity indices: species richness, population-weighted species richness, and red-listed species richness, estimated from voluntarily reported data on breeding bird species observations. Results show that regional schemes are more expensive, in particular if the policy maker dislikes uncertainty and wants to prioritize uncommon species. Contrary to expectations from the theoretical analysis, regional schemes would lead to a higher risk-adjusted level of biodiversity at the national level. However, regionalization also implies that targets cannot be achieved if a high safety margin is imposed. Trading ratios are robust to the choice of wetland quality index.

The benefits and costs of wildlife are contingent on the spatial overlap of animal populations with economic and recreational human activities. By using a production function approach with dynamic spatial panel data models, we analyze the effects of human hunting and carnivore predation pressure on the value of ungulate game harvests. The results show evidence of dynamic spatial dependence in the harvests of roe deer and wild boar, but not in those of moose, which is likely explained by the presence of harvesting quotas for the latter. Results suggest the impact of lynx on roe deer harvesting values is reduced by 75% when spatial effects are taken into account. The spatial analysis confirms that policymakers’ aim to reduce wild boar populations through increased hunting has been successful, an effect that was only visible when considering spatial effects. 

In this study, we investigate how households' choice of energy source is influenced by the status of the local forest resource. We assume that households choose between clean fuels (e.g., kerosene, LPG, solar, and electricity), dirty biobased fuels (e.g., firewood, animal dung, crop residues, and charcoal), and mixed fuels. We integrate socioeconomic data with high-resolution satellite data on forest conditions from the Uganda National Panel Survey. The findings from a random-effects multinomial logit model indicate that households in vegetated areas are 6–7% less likely to rely solely on dirty biobased fuels, and 6–8% more likely to use mixed fuels, compared to those in non-vegetated areas. A larger forest stock is more strongly associated with lower use of firewood than charcoal. A possible explanation for the findings is the presence of policies for forest conservation and enhanced forest property rights, which improve forest conditions and limit opportunities to collect firewood. Given households' dependence on forest-based fuels, such policies could need to be modified to secure households’ access to these fuels.