Ecological Economics最新文献

Sustainable socio-economic development requires a global reduction of greenhouse gas emissions. We utilize an incentivized experiment to map the preferences of ‘policymakers’ over climate actions of ‘decision-makers’. Our design guarantees that these preferences are unaffected by selfish motives such as a concern about being re-elected or an unwillingness to pay for the greater good. Few of our impartial policymakers choose interventions that leave the autonomy of decision-makers' completely untouched. The choice patterns of those who intervene suggest that policymakers care not only about minimizing emissions, but also about how emissions are reduced. Policymakers strongly prefer pricing policies over capping emissions, and among the pricing policies, they prefer those that include voluntary carbon offsets, even if this leaves considerable scope for decision-makers to selfishly emit CO₂. The reason is that policymakers expect decision-makers to voluntarily offset some of their emissions at their own cost, and believe that this would eventually improve the outcome in terms of both emissions and the decision-makers' profit relative to a standard carbon pricing policy (without offsetting). Our decision-making data confirm this expectation.

Overexploitation of ecosystems can cause drastic shifts to unfavourable states once ecosystems reach critical thresholds. Experimental studies have shown that the knowledge of such thresholds helps to foster sustainable resource management. However, warning resource users of a regime shift is difficult since knowledge about critical thresholds is often associated with considerable ambiguity. We conducted a continuous-time common pool resource lab experiment (N = 360; 90 groups of four participants) to assess how different levels of ambiguous information regarding the location of thresholds affect cooperation amongst resource users. Results show that groups informed only of the threshold's existence cooperate similarly to those provided with a range for the threshold, indicating that ambiguity levels do not significantly influence cooperation amongst resource users for sustaining resources at optimal levels. In addition, we analysed treatment differences once the ambiguity about the threshold location is resolved. We do not find lasting impacts of different ambiguity levels on the likelihood of avoiding crossing the threshold once the threshold location is communicated with certainty. Overall, our results suggest that the scope of providing imprecise threshold information which reduces the level of ambiguity may be limited in fostering more sustainable natural resource management.

Does exposure to tropical cyclones affect fertility? This paper addresses this question by constructing a panel dataset from geolocated micro-data about the fertility history of mothers along with their local exposure to tropical cyclones for a sample of six developing countries for the 1985–2015 period. We then estimate the causal effect of tropical cyclone shocks on women’s likelihood of giving birth. We find evidence that tropical cyclone exposure has a significantly negative effect on motherhood. A cyclonic wind exposure between 60 and 117 km/h (resp. at least of 118 km/h) decreases the probability of giving birth by 7.8 (resp. 7.0) points a year after exposure. We also observed that the magnitude of the effect varies with the degree of cyclonic exposure associated with the mothers’ living environment and the number of children ever born. In particular, the fall in the likelihood of giving birth is lower for mothers living in cyclone-prone areas and for those who already have children. Alternative specifications of our baseline model provide further insights: (i) recent past exposure to cyclones was associated with a lower decrease in fertility when exposed once again; and (ii) no evidence of non-linearities was observed in the effect.

Marine conservation and sustainable fisheries require diversified funding sources to align with Sustainable Development Goals. This study examined seven Fisheries Improvement Projects (FIPs) and seven community marine reserves in Mexico, spanning 60 months. FIPs averaged $60,296 USD annually, with variations based on FIP type and accessibility. Marine reserves required $2343.16 USD per square kilometer over 17 months, varying based on size and location. Private funding covered 91.5 % of costs, primarily from philanthropic donations (69.5 %) and fishing organizations (21 %), with a minor contribution from markets (1 %, only in FIPs). Public funding constituted 8.5 %, split between academia (4.5 %, only in reserves) and governmental sources (4 %). Despite efforts to engage other stakeholders, philanthropy remained the dominant funding source, most FIPs couldn't access a price premium and markets didn't support marine reserves. Community reserves heavily relied on philanthropy, raising concerns about long-term sustainability. Incorporating in-kind contributions, mainly from fishing organizations and communities, is crucial, particularly in small-scale fisheries in the Global South. Strengthening community agreements and public-private coordination is essential to attract new investments for small-scale fisheries' sustainability, addressing institutional challenges in the Global South.

Empirical research shows that loss framing appears to be a promising tool to promote pro-environmental behavior. However, only a limited amount of experimental research has examined the effect of loss framing on actual behavior. Here, we use a variation of the Work for Environmental Protection Task (Lange & Dewitte, 2022) to study voluntary pro-environmental behavior. In an online experiment (N = 897), we find a trend of higher working efforts in the LOSS frame. However, this effect is small and marginally statistically significant. Interestingly, as explorative analyses suggest, the effect of loss framing is consistent for people with low and high intrinsic values to protect the environment.

Ecosystems are likely to be severely affected by climate change. While the literature on this subject focuses primarily on climate variable means, increasing evidence has been gathered on the importance of changes in climate variability in determining ecosystem impacts. In this context, forests play a significant role. While, on the one hand, forests have often been identified to be a key element in mitigating greenhouse gas emissions, on the other, forests are also affected by changes in climate. However, the number of studies on optimal forest management under climate change remains limited and has overlooked the role of climate variability. This paper adds to that literature by developing a coupled ecological-economic forest stand model in which forest dynamics are a function of monthly climate variables. We show that accounting for changes in climate variability substantially changes earlier findings. In particular, ignoring climate variability may fail to adequately account for changes in optimal harvest age and lead to erroneous conclusions regarding the effects of climate change on forested land value.

We compare the results from a recent global expert survey on climate policy with answers to the same survey by the online artificial-intelligence chatbot ChatGPT. Such a study is timely and relevant as many people around the world are likely to use ChatGPT and similar language models to inquire about climate solutions, which in turn might influence public opinion. The comparison provides insights about performance criteria, policy instruments, and use of information from distinct academic disciplines. With a few exceptions, responses by ChatGPT are informative and of high quality. We find that ChatGPT answers questions with less bias than experts from various scientific disciplines. The latter may also be a disadvantage as it seems to weight all the information available equally without accounting well for relevance, which arguably may require human rather than artificial intelligence. On the other hand, experts from distinct disciplines show difference in average responses, with some even expressing opinions inconsistent with objective evidence, meaning there is no consistent and unbiased expert opinion on climate policy. As a new way of synthesizing large amounts of academic and grey literature, ChatGPT can serve policymaking. However, since the procedure that it follows for collecting and summarizing information remains a black box, it is best regarded as a complement rather than a substitute to traditional literature reviews and expert surveys.

Despite increasing concerns about climate change, many people struggle to translate their pro-environmental values into action. Here, we explore the origins of this value-action gap focusing on the role of behavioral barriers that are characteristic for many environmentally relevant decisions. Using incentivized online laboratory and vignette experiments, we find that individuals are less likely to behave in accordance with their environmental values if they are not immediately affected by the consequences of their actions, if the impacts of their actions are uncertain, and if they contribute only marginally to the outcome. The behavioral barriers also exert an indirect effect on environmental behavior by undermining reciprocity and positive peer effects. The value-action gaps are correlated across the different experimental settings with men and younger participants showing a particularly large gap. These insights are important for climate communication and education, highlighting the important role of the perceived relevance and potential consequences of personal behaviors in collective action.

Noting the rising importance of international trade in global warming, this study proposes a new decomposition of carbon productivity by dividing it into the part of true carbon productivity (consumption-based labor productivity and population-sustaining power of CO${}_2$) and the part with zero-sum nature (labor exploitation, carbon emission exploitation and trade surplus). By analyzing 66 countries/regions and the rest of the world in 2018, we find that by excluding the exploitation part, the differences in carbon productivity among countries – particularly between developed and developing countries – narrow. Analysis for selected economies (EU15, EU13, the United States, Japan, China and India) from 1995 to 2018 reveals that international exploitation of labor and carbon emissions has deepened from 1995 to 2006, and weakened from 2006 to 2018, but the structure of exploitation has been maintained through the entire period; the consumption-based labor productivity and population-sustaining power of CO${}_2$ effects are the principal driving factors of change in carbon productivity. The growth in true carbon productivity increased in the last half of the period, but the improvement is still quite modest.

This paper develops a new method to construct the household-based Human Development Index to examine the effects of extreme temperature shocks on human development at the household level. Four waves of the Vietnam Household Living Standard Survey from 2012 to 2018 are used to analyze the effects of temperature shocks on households in different regions. The findings reveal that if temperatures deviate from the long-run average by more than two standard deviations, the Human Development Index score will decline by 2 to 3.5 percentage points, with the most significant effect identified for households in the South and Central Highlands. Additionally, the paper identifies agricultural production, alcohol consumption and energy poverty as channels through which extreme temperatures affect human development. Finally, the findings suggest that policies aimed at mitigating the effects of climate change on vulnerable regions should focus on supporting households in these areas through measures such as developing climate-resistant crops, encouraging agricultural adaptation strategies, integrating local labor markets, and improving energy access.