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ABSTRACTThis paper analyzes the effect of different types of cookstoves on firewood demand at the household level. Using nationally representative household survey data from Nepal, we find that stove type significantly affects the firewood demand for household uses. Traditional mud-stove user households seem to use less firewood than the open-fire stove users. Surprisingly, households with the so-called 'improved' stoves seem to use more firewood than the households with mud stoves. Thus, converting traditional open-fire stoves to mud stoves may be a better conservation strategy in the short term rather than installing improved stoves, unless the technology improves. However, in the long run, making cleaner fuel more accessible to rural households is desirable to reduce indoor air pollution.

AbstractStated preference surveys are increasingly conducted online using internet panel samples, where a fast-growing share of respondents answer on smartphones. These panel members range from novices to "professionals" in terms of previous survey experience. Little is known about the potential effects of smartphone responding and survey experience on the data quality of stated preference surveys. This paper uses a discrete choice experiment dataset on the Norwegian population's willingness to pay to plant climate forests to explore how these two factors affect data quality. These data by type of response device, gathered using a probability-based internet panel, were combined with a unique dataset obtained from the survey company on respondents' actual experience answering surveys on different types of devices. Our results show that differences in elicited preferences between smartphone and computer respondents are not caused by the device used, suggesting that initial concerns about smartphone responses may be exaggerated. Furthermore, more experience is associated with an increasing scale parameter (indicating lower error variance), but at a decreasing rate; and a higher propensity to choose the status quo (indicating possible simplifying strategies employed by respondents). Combined this suggest some optimal level of experience that is neither too high nor too low. We discuss the implications of our results for stated preference research and provide a few avenues for future research.

AbstractAltruistic 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.

AbstractEnergy 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.

AbstractSensitivity to scope in nonmarket valuation refers to the property that people are willing to pay more for a higher quality or quantity of a nonmarket public good. Establishing significant scope sensitivity has been an important check of validity and a point of contention for decades in stated preference research, primarily in contingent valuation. Recently, researchers have begun to differentiate between statistical and economic significance. This paper contributes to this line of research by studying the significance of scope effects in discrete choice experiments (DCEs) using thescope elasticity of willingness to payconcept. We first formalize scope elasticity in a DCE context and relate it to economic significance. Next, we review a selection of DCE studies from the environmental valuation literature and derive their implied scope elasticity estimates. We find that scope sensitivity analysis as validity diagnostics is uncommon in the DCE literature and many studies assume unitary elastic scope sensitivity by employing a restrictive functional form in estimation. When more flexible specifications are employed, the tendency is towards inelastic scope sensitivity. Then, we apply the scope elasticity concept to primary DCE data on people's preferences for expanding the production of renewable energy in Norway. We find that the estimated scope elasticities vary between 0.13 and 0.58, depending on the attribute analyzed, model specification, geographic subsample, and the unit of measurement for a key attribute. While there is no strict and universally applicable benchmark for determining whether scope effects are economically significant, we deem these estimates to be of an adequate and plausible order of magnitude. Implications of the results for future DCE research are provided.

In a non-renewable resource market with imperfect competition, both the resource rent and current prices influence a large resource owner's optimal supply. New information regarding future market conditions that affect the resource rent will consequently impact current supply. Bleaker demand prospects tend to accelerate resource extraction. A more pessimistic outlook for future demand may, however, slow down the early resource extraction of producers with sufficiently large resource stocks and thus more limited resource rent, because the supply from these producers is driven more by current market considerations than by changes in the resource rent. As producers with relatively smaller resource stocks accelerate their supply in response to bleaker demand prospects, producers with sufficiently large resource stocks will reduce their current supply. A numerical model of the European gas market illustrates that the effect of the shale gas revolution is an accelerated supply by most gas producers, but a reduced supply by Russia who loses market shares even before the additional gas enters the market.