Environmental & Resource Economics最新文献

Coastal amenities are public goods that represent an important attraction for tourism activities. This paper studies the capitalization effects of beach characteristics using hedonic pricing methods. We examine the implicit economic value of several beach characteristics like sand type, width, longitude, accessibility, or frontage in the Airbnb rental market. Using data for 16,663 Airbnb listings located in 67 municipalities of the Balearic Islands (Spain) during the summer of 2016, together with detailed information about the attributes of 263 beaches, our modelling approach considers interaction terms between the beach amenities and distance to the closest beach. Controlling for a set of listings' structural characteristics, host attributes and municipality fixed effects, we find that Airbnb guests attach economic value to beach length, the presence of vegetation, the type of coastal frontage and beach accessibility and exclusivity. However, there is no evidence of capitalization effects associated with beach width or the type of sand.

Supplementary information: The online version contains supplementary material available at 10.1007/s10640-022-00735-5.

The Anthropocene can be read as being the era when the demand humanity makes on the biosphere's goods and services-humanity's 'ecological footprint'-vastly exceeds its ability to supply it on a sustainable basis. Because the 'ecological' gap is met by a diminution of the biosphere, the inequality is increasing. We deploy estimates of the ecological gap, global GDP and its growth rates in recent years, and the rate at which natural capital has declined, to study three questions: (1) at what rate must efficiency at which Nature's services are converted into GDP rise if the UN's Sustainable Development Goals for year 2030 are to be sustainable; (2) what would a sustainable figure for world population be if global living standard is to be maintained at an acceptably high level? (3) What living standard could we aspire to if world population was to attain the UN's near lower-end projection for 2100 of 9 billion? While we take a global perspective, the reasoning we deploy may also be applied on a smaller scale. The base year we adopt for our computations is the pre-pandemic 2019.

This study explores the nexus between digital and green transformations-the so-called "twin" transition-in European regions in an effort to identify the impact of digital and environmental technologies on the greenhouse gas (GHG) emissions originating from industrial production. We conduct an empirical analysis based on an original dataset that combines information on environmental and digital patent applications with information on GHG emissions from highly polluting plants for the period 2007-2016 at the metropolitan region level in the European Union and the UK. Results show that the local development of environmental technologies reduces GHG emissions, while the local development of digital technologies increases them, albeit in the latter case different technologies seem to have different impacts on the environment, with big data and computing infrastructures being the most detrimental. We also find differential impacts across regions depending on local endowment levels of the respective technologies: the beneficial effect of environmental technologies is stronger in regions with large digital technology endowments and, conversely, the detrimental effect of digital technologies is weaker in regions with large green technology endowments. Policy actions promoting the "twin" transition should take this evidence into account, in light of the potential downside of the digital transformation when not combined with the green transformation.

Given the drastic changes in the environment, resilience is a key focus of ecosystem management. Yet, the quantification of the different dimensions of resilience remains challenging, particularly for long-lived systems such as forests. Here we present an analytical framework to study the economic resilience of different forest management systems, focusing on the rate of economic recovery after severe disturbance. Our framework quantifies the post-disturbance gain in the present value of a forest relative to a benchmark system as an indicator of economic resilience. Forest values and silvicultural interventions were determined endogenously from an optimization model and account for risks affecting tree survival. We consider the effects of differences in forest structure and tree growth post disturbance on economic resilience. We demonstrate our approach by comparing the economic resilience of continuous cover forestry against a clear fell system for typical conditions in Central Europe. Continuous cover forestry had both higher economic return and higher economic resilience than the clear fell system. The economic recovery from disturbance in the continuous cover system was between 18.2 and 51.5% faster than in the clear fell system, resulting in present value gains of between 1733 and 4535 € ha^-1. The advantage of the continuous cover system increased with discount rate and stand age, and was driven by differences in both stand structure and economic return. We conclude that continuous cover systems can help to address the economic impacts of increasing disturbances in forest management.

Economists typically estimate the average treatment effect on the treated (ATT) when evaluating government programs. The economic interpretation of the ATT can be ambiguous when program outcomes are measured in purely physical terms, as they often are in evaluations of environmental programs (e.g., avoided deforestation). This paper presents an approach for inferring economic impacts from physical outcomes when the ATT is estimated using propensity-score matching. For the case of forest protection, we show that a protection program's ex post economic impact, as perceived by the government agency responsible for protection decisions, can be proxied by a weighted ATT, with the weights derived from the propensity of being treated (i.e., protected). We apply this new metric to mangrove protection in Thailand during 1987-2000. We find that the government's protection program avoided the loss of 12.8% of the economic value associated with the protected mangrove area. This estimate is about a quarter smaller than the conventional ATT for avoided deforestation, 17.3 percentage points. The difference between the two measures indicates that the program tended to be less effective at reducing deforestation in locations where the government perceived the net benefits of protection as being greater, which is the opposite of the relationship that would characterize a maximally effective program.

This study mainly investigates 14 Asia Pacific economies' environmental efficiency. Departing from previous studies ignoring environmental technology heterogeneity, we evaluate environmental efficiency through metafrontier super epsilon based model (EBM). We compare environmental efficiency convergence across different regions via unit root test and truncated regressions. We analyze how trade competitiveness impact environmental efficiency. We also explore effect of green technology and human capital on environmental efficiency from the perspective of endogenous growth. Our findings indicate that stochastic and absolute β-convergence tendencies were confirmed. Human capital can enhance environmental efficiency convergence. Trade competitiveness showed a mixed impact on environmental efficiency convergence, confirming scale, composition and technical effects. It is better to enhance human capital, strengthening environmental regulations under international competition as well as relentlessly pursuing green industrialization across Asia Pacific countries.