Environmental information disclosure (EID) policies have been used in many jurisdictions, yet the impact on the environment and economic performance of enterprises remains a question. This study examines China's mandatory EID policy implemented in 2014 as an example of the potential relationship between environmental policy and enterprise performance. We applied a difference-in-differences (DID) and propensity score matching (PSM) sampling method to examine the issue, using a panel dataset of nearly 90 sugar enterprises in Guangxi in China from 2008 to 2016. Earnings before income and tax and pollution emissions are considered as proxies of economic and environmental performance, respectively. The results show that the 2014 MEID policy has a significantly positive effect on pollution reduction and a significantly adverse effect on economy. These effects vary with corporation size and ownership. Production shrinkage appears to be the main reason for pollution reduction in Guangxi's sugar industry rather than technological innovation in the pollution treatment process. Furthermore, we discuss the study's limitations and policy implications.

Australia will not meet Sustainable Development Goal target 6.1, to “achieve universal and equitable access to safe and affordable drinking water for all” by 2030, unless water service provision is improved to hundreds of small (less than 10,000 residents), rural and remote (SRR) communities. We have estimated the national benefits of a programme to upgrade drinking water services to ensure ‘good quality’ for 395 Australian SRR communities using a stated preference survey of 3,523 participants reflective of the Australian population. Using multiple model estimates, we calculated the willingness to pay at between AU$324 and AU$847 per Australian household per year for 10 years. Aggregating across the relevant Australian population, we calculated the aggregate willingness to pay for water quality improvements at AU$1.2–4.7 billion yr −1 , or AU$8.3–33.2 billion as a 10-year net present value. We further estimated the capital and operating costs to provide ‘good-quality’ drinking water in the 395 SRR communities under three scenarios; the costs range from AU$0.51 to AU$3.29 million per community and, in total, from AU$0.2 billion to AU$1.3 billion.

This paper provides an introduction to statistical analysis of choice data using example data from a simple discrete-choice experiment (DCE). It describes the layout of the analysis dataset, types of variables contained in the dataset, and how to identify response patterns in the data indicating data quality. Model-specification options include linear models with continuous attribute levels and non-linear continuous and categorical attribute levels. Advantages and disadvantages of conditional logit, mixed logit, and latent-class analysis are discussed and illustrated using the example DCE data. Readers are provided with links to various software programs for analyzing choice data. References are provided on topics for which there currently is limited consensus and on more advanced techniques to guide readers interested in exploring choice-modeling challenges in greater depth. Supplementary materials include the simulated example data used to illustrate modeling approaches, together with R and Matlab code to reproduce the estimates shown.

Abstract Introduction Public perception of the seriousness of the COVID-19 pandemic compared to six other major public health problems (alcoholism and drug use, HIV/AIDS, malaria, tuberculosis, lung cancer and respiratory diseases caused by air pollution and smoking, and water-borne diseases like diarrhea) is unclear. We designed a survey to examine this issue using YouGov’s internet panels in seven middle-income countries in Africa, Asia, and Latin America in early 2022. Methods Respondents rank ordered the seriousness of the seven health problems using a repeated best-worst question format. Rank-ordered logit models allow comparisons within and across countries and assessment of covariates. Results In six of the seven countries, respondents perceived other respiratory illnesses to be a more serious problem than COVID-19. Only in Vietnam was COVID-19 ranked above other respiratory illnesses. Alcoholism and drug use was ranked the second most serious problem in the African countries. HIV/AIDS ranked relatively high in all countries. Covariates, particularly a COVID-19 knowledge scale, explained differences within countries; statistics about the pandemic were highly correlated with differences in COVID-19’s perceived seriousness. Conclusions People in the seven middle-income countries perceived COVID-19 to be serious (on par with HIV/AIDS) but not as serious as other respiratory illnesses. In the African countries, respondents perceived alcoholism and drug use as more serious than COVID-19. Our survey-based approach can be used to quickly understand how the threat of a newly emergent disease, like COVID-19, fits into the larger context of public perceptions of the seriousness of health problems.

Contingent behavior (CB) trip data, eliciting intended trip decisions with hypothetical scenarios, has been popular in recreation demand models. Unlike other stated preference methods, the temporal re-liability of CB data has not been examined in recreation demand models, especially in a Kuhn-Tucker (KT) framework. This article as-sesses the temporal reliability of CB trip data collected over three years in KT models. We find that coefficient and welfare estimates are largely reliable over time. Our findings add confidence in using CB trip data to model de-mands within and beyond recreation contexts and provide insight into the broader applica-tion of KT models. (JEL Q26, Q51)

When participating in recreation individuals decide on where to go (locations) and when to participate (which time periods), and they respond to changes in external factors (e.g., environmental quality changes, provision of incentives). In examining economic decision-making, economists focus mostly on location choices, thus the behavioral and welfare impacts of the incentives associated with time choices are largely unknown. In this paper, we develop and estimate a flexible econometric model that combines spatial and temporal choices. The model is applied to examine individuals’ location and time choices of their recreation trips in response to extended recreation seasons that are proposed to encourage hunting for wildlife disease management. The data are from an online revealed and stated preference survey of recreational hunters in Alberta, Canada. We find that individuals substitute activities spatially and temporally, take more hunting trips, and gain welfare benefits when they can more flexibly choose the time of activities. Our findings show that increases in time flexibility can be used as an incentive to encourage beneficial outcomes.

La valeur de la réduction du risque de mortalité (VRRM) constitue un élément clé de l’analyse économique des politiques publiques. La réduction du risque de mortalité représente souvent la majeure partie des avantages totaux dans les analyses des politiques de santé, de sécurité et d’environnement. Par conséquent, il est essentiel de disposer de mesures précises et actualisées de la VRRM. Nous avons réalisé une méta-analyse afin de mettre à jour l’estimation de la VRRM du Canada sur la base de 158 estimations extraites de 18 études primaires publiées entre 1989 et 2018. Nous utilisons la méthode des moindres carrés pondérés, les erreurs groupées et les procédures de régression des données de panel pour traiter différentes questions empiriques dans notre méta-analyse. Notre analyse, qui s’appuie sur des études privilégiées incluant des échantillons représentatifs, aboutit à une estimation moyenne pondérée de la VRRM de 13 millions de dollars en 2020, alors que les valeurs inférieures et supérieures de deux méthodes d’évaluation alternatives vont d’environ 10 millions de dollars à 16,5 millions de dollars. La moyenne actualisée de la VRRM est de 43% plus élevée que l’estimation actuelle de la VRRM recommandée par le Secrétariat du Conseil du Trésor du Canada. L’analyse de méta-régression montre également que les niveaux de risque de base et de réduction du risque figurent parmi les principaux déterminants des estimations de la VRRM. Nous recommandons l’application d’une estimation actualisée de la VRRM dans les évaluations de politiques, étant donné que l’utilisation de la mesure actuelle peut mener à des calculs d’avantages et de coûts trompeurs, ainsi qu’à des recommandations de politiques potentiellement inexactes.

Externalities from recreation scale at the extensive and intensive margins of resource interaction. Recreators have differentiated demands for these margins, so unbundling the prices of access and intensive depletion could improve on traditional management. We use choice experiment data from U.S. Gulf of Mexico recreational headboat anglers to estimate structural models of trip and red snapper retention demand, then simulate aggregate harvest across a range of trip and harvest tag prices. In our simulations, the red snapper harvest tag market equilibrates at $15 per tag and generates $760,000 in management revenues per year while more efficiently allocating harvest.

Contingent behavior (CB), a stated preference (SP) method, elicits individuals' intentions about behavior in quantities or frequencies under hypothetical scenarios. CB has primarily been used to elicit preferences in recreation demand models or to assess market demand. Although CB shares the hypothetical nature of other SP methods, there has been limited assessment of CB validity and incentive compatibility. Focusing on hypothetical bias and framing effects, we design an incentive-compatible decision mechanism that examines the validity of CB in economic experiments. We find hypothetical bias associated with an overstatement of quantities in CB responses, but the overstatement does not appear to arise from strategic behavior. We also find that overstating quantities is not significantly affected by framing, but framing does affect the convergence of CB and revealed preference responses. These findings raise questions about the validity CB research and its demand revealing properties but provide some avenues to address these concerns.

Stated preference methods remain the only means capable of estimating non-use values yet can suffer from many types of well-known biases. We construct an approach to identify the role of social desirability bias, relative to other potential survey biases, using a stated preference survey for improving the status of species at risk. The survey respondents were asked how they would vote, how they think their fellow survey participants would vote, as well as how they think people in their region would vote in an actual referendum. We find that willingness-to-pay estimates for public good (passive use) values differ across these vote question types. Our results demonstrate how stated preference practitioners can use multiple referent groups to help disentangle social desirability bias from other survey biases.

There are over 450,000 registered oil and gas wells in the province of Alberta, Canada. A recent increase of the number of inactive wells creates significant environmental risk and financial liability in cleanup costs. By retrofitting wells for direct use geothermal heat energy production, these wells can produce clean, renewable energy and offset these risks and liabilities. This research is the first to create a model of well retrofit costs and power/benefits and to consider direct use of heat energy for ranching applications in Canada. We estimate the average cost to retrofit a suspended well to be $50,000 less than an identical abandoned well. The cost of retrofitting suspended wells varies little (<$11,000). The greatest variance in cost (>$120,000/well) is related to the distance between the well and user and resulting pipe/materials necessary to transport the hot water. Our model of well retrofit costs can be expanded to other geothermal re-purposing projects in North America and worldwide.

The paper investigates the validity of individuals’ perceptions of heart disease risks, and examines how information and risk perceptions affect marginal willingness to pay (MWTP) to reduce risk, using data from a stated preference survey. Results indicate that risk perceptions individuals held before receiving risk information are plausibly related to objective risk factors and reflect individual-specific information not found in aggregate measures of objective risk. After receiving information, individuals’ updates of prior risk assessments are broadly consistent with Bayesian learning. Perceived heart disease risks thus satisfy construct validity and provide a valid basis for inferring MWTP to reduce risk. Estimating MWTP based on objective rather than subjective risks causes misleading inferences about benefits of risk reduction. An empirical case study shows that benefits are 36% to 62% higher when estimated using objective rather than subjective risks, showing the importance of employing risk perception information to improve validity of benefit measures.

We use a paired-sample binary choice experiment to estimate willingness to pay (WTP) and willingness to accept (WTA) values when land is converted from agriculture to developed uses in Alberta, Canada. Validated principles for stated preference are followed in scenario design, elicitation format, experimental design, and ancillary questions. Preference uncertainty is addressed through alternative calibration of uncertain responses. Reliability and incentive compatibility measures indicate that respondents found both WTP and WTA scenarios to be plausible and incentive compatible. WTA-WTP value gaps are smaller than most previous studies, with consequentiality increasing WTA, WTP, and the gap between WTA and WTP.

Non-market valuation (NMV) can be effective to understand the value people place on ecosystem goods and services for which there are no market prices. Over the last 20 years, NMV has increasingly been applied to Indigenous contexts, albeit with important conceptual and methodological limitations. We conduct a global systematic literature review and detailed meta-synthesis of 63 peer-reviewed studies on NMV research applied to Indigenous peoples' values. Selected studies are categorized by methods, year of publication, geographic area and ecosystem components. Australia (n = 19), the USA (n = 9) and Canada (n = 8) account for over half of all articles. Important knowledge gaps remain in the NMV peer-reviewed literature for other geographic areas. Our taxonomy based on 'whose values' and 'which values' reveals that a large proportion of studies (n = 24) focused on values held by Indigenous peoples, predominately on direct-use values (n = 12) and total economic values (n = 10). Studies based on the general population (n = 17) typically examined altruistic and/or existence values (n = 15). Our analysis identified seven main strategies used by previous studies to overcome critical limitations of NMV when applied to Indigenous peoples' values. Strategies include: (1) engaging directly and ethically with Indigenous peoples; (2) investigating multi-dimensional values; (3) valuing health benefits; (4) adopting non monetary payment vehicles; (5) using market prices for valuation; (6) sampling the broad population; and (7) investigating non-cumulative values. Based on this review, we provide seven critical questions to guide future NMV research: (1) What is the purpose?; (2) How does Indigenous knowledge inform NMV?; (3) Who benefits?, (4) What ethical frameworks apply?; (5) Whose values are considered?; (6) What is the expected change?; and (7) How are NMV limitations handled? Our contribution provides researchers and policy-makers with the most upto-date review of the state-of-knowledge and suggestions for best-practice on the use of NMV methods when applied to Indigenous peoples' values.

Abstract We provide estimates of health priorities during the COVID-19 pandemic based on web-surveys administered in seven developing countries in Africa, Asia, and Latin America in 2022. Using the best-worst scaling method, respondents ranked the importance of seven health problems, including COVID-19 (the others were alcohol and drugs, HIV/AIDS, malaria, TB, other respiratory diseases, and water-borne diseases). Respondents in most countries considered COVID-19 a serious problem but ranked other respiratory illness as more serious. Respondents’ rankings were generally consistent with relative disease prevalence when it can be reasonably well measured (i.e., malaria and TB). Differences in priorities across countries were generally larger than within-country differences. The importance respondents assigned to COVID-19 was associated with their knowledge of COVID-19. These results have implications for the allocation of health resources: policymakers may face resistance if their actions are viewed as focusing too much on COVID-19 while neglecting other, potentially serious health problems.

In the past, public stakeholders have indicated strong negative preferences in response to some approaches, such as culling, for managing Chronic wasting disease (CWD). We collect data across Canada from the general public and several stakeholder groups and assess their preferences using a paired comparison approach. The results suggest that the public wants action in managing CWD. Members of the general public seem receptive to a number of different types of management approaches for CWD. Specifically, the public seems to support hunters reducing herd sizes, through increased tags and compensation for submitting positive testing CWD heads, and promoting environmental sampling on private land to detect CWD. In contrast, the public seems to dislike using sharpshooters to cull herds (on public or private land), and a number of options involving landowners, including increasing the number of licenses they may obtain, allowing them to charge hunters for access and providing them with extension services. Another stark result of our study is the remarkable homogeneity of preferences across different segments of society. There are very few cases where we find conflicting positive and negative preferences across groups.

Preference heterogeneity is one of the central behavioral concepts in applied econometrics. Its centrality is particularly evident in the choice modeling literature, notably in its widespread application to environmental and health economics, marketing, and transport. Despite conceptual and empirical advances in modeling preference heterogeneity, the generalizability of preference heterogeneity to different decision contexts and different data generation processes remains an open question. The basic premise of this paper is that latent sources of preference heterogeneity can be decomposed into components general to decision contexts and others specific to them. We study the structure of preference heterogeneity in different data generation processes with the goal of reliably identifying common (presumably generalizable) and specific (presumably not generalizable) sources of preference heterogeneity. The contribution of the paper is both conceptual and methodological, leading to the testing of five rival model specifications which together elucidate the heterogeneity structure present in two preference data sources of the same choice behavior. In the empirical application, we find that the multitrait-multimethod model of preference heterogeneity has the best fit and most sensible interpretations, indicating that while each data source contributes uniquely to certain heterogeneity components, both data sources contribute also to common (generalizable) preference heterogeneity. Recognition of the separability of the common versus source-specific preference heterogeneity will lead to more reliable and accurate demand model forecasts and assessments of welfare impacts.

The responses of policy makers, individuals, and businesses to COVID-19 contrast with typical responses to environmental issues. In most countries, governments have been willing to act decisively to implement costly restrictions on work and personal life, to a degree that has never been observed for an environmental issue. A number of possible lessons for environmental economists are identified. In addition to valuing natural environments, people also place a high value on social interactions. These two values may interact. Adaptation can substantially reduce the cost of restrictive policies and should be considered when policy proposals are being evaluated. Preparation for an emergency can substantially reduce its costs by allowing a more rapid response. The development of new technologies can play a key role in reducing externalities. As well, the effectiveness of policies that deliver public goods can be enhanced by credible leaders who provide clear, compelling, and consistent information, emphasizing both the private and public benefits of compliance.

Natural capital, and its substitutability with other forms of capital, occupies the heart of the sustainability debate. The existing theoretical and empirical literature in natural capital focuses on the static notions of substitutability and complementarity between natural capital and other forms of capital. We investigate the substitution or complementarity of natural capital stocks with other capital stocks in the forward-looking, firm production setting. We distinguish between the capital space and the services space and argue that stocks may be complements (substitutes) while flows are substitutes (complements). We show that the substitution or complementarity relationship depends on the nature of the investment, which may be unclear ex ante. We apply the approach to analyze the relationship between produced capital and natural capital in the case of the Panama Canal expansion and provide empirical evidence of complementarities between natural capital and produced capital.