How Much Does the Far Future Matter? A Hierarchical Bayesian Analysis of the Public's Willingness to Mitigate Ecological Impacts of Climate Change
遥远未来有多重要?公众减缓气候生态影响意愿的层级贝叶斯分析AI 解读 ↓
本页整理公开书目信息,不生成学术质量评分。AI 解读根据题名及所注明的摘要或原文片段生成,未完成全文核验,可能有误;具体假设、证明与结论请核对原文。摘要保留来源文本,未经模型改写。
DOI 首次登记不等于接收或发表日期。部分更正、评论等条目没有独立摘要;缺少可靠材料时保留待补状态。
引用量采用 OpenAlex 单条关联记录,不合计多个记录;关联记录可能包含正式发表版本,不等于此版本单独引用。缺失不视为零,引用指标不代表论文质量。
关注作者按书目中的完整姓名匹配,同名和姓名变体需人工辨别。相关论文先按共享细分方向和具体方法排列,再参考通用方法与发表日期。
AI 根据所提供的论文材料归类:摘要以情景调查中的有序响应和潜在效用刻画公众成本承担意愿,直接涉及离散选择与偏好建模。
遥远未来有多重要?公众减缓气候生态影响意愿的层级贝叶斯分析AI 解读 ↓
正在核对关联版本…
正在核对对应版本的资源…
How much does the far future matter? This question lies at the heart of many important environmental policy issues, such as global climate change, biodiversity loss, and the disposal of radioactive waste. Although philosophers, experts, and others offer their viewpoints on this deep question, the solution to many environmental problems lies in the willingness of the public to bear significant costs now to make the far future a better place. Short of national plebiscites, the only way to assess the public's willingness to mitigate impacts in the far future is to ask them. Using a unique set of survey data in which respondents were provided with sets of scenarios describing different amounts of forest loss due to climate change, along with associated mitigation methods and costs, we can infer the respondents' willingness to bear additional costs to mitigate future ecological impacts of climate change. The survey also varied the timing of the impacts, which allows us to assess how the willingness to mitigate depends on the timing of the impacts. The responses to the survey questions are a consequence of latent utilities with complex ordinal structures that result in nonrectangular probabilities. Whereas the nonrectangular probabilities complicate standard maximum likelihood–based approaches, we show how the nonrectangular probabilities fit neatly into a hierarchical Bayesian model. We show how to fit these models using the Gibbs sampler, overcoming problems in parameter identification to improve mixing of the induced Markov chain. The results indicate that the public's willingness to incur additional costs to mitigate ecological impacts of climate change is an increasing nonlinear function of the magnitude of the impact, and that they discount future impacts at somewhat less than 1%% per year.
二项逻辑混合模型中的信息差距与可行性感知推断
This paper studies the information gap between mixture detection and label recovery in binomial logistic mixtures. Standard likelihood-based criteria such as the Bayesian information criterion (BIC) can detect the presence of two components, but this does not guarantee that the corresponding labels are recoverable. We show that this gap is intrinsic to binomial logistic mixtures with a fixed number of trials: observed-data evidence for mixture structure and per-observation…
多重重复测量的多变量有序回归
In this paper we propose a multivariate ordinal regression model which allows the joint modeling of three-dimensional panel data containing both repeated and multiple measurements for a collection of subjects. This is achieved by a multivariate autoregressive structure on the errors of the latent variables underlying the ordinal responses, where we distinguish between the correlations at a single point in time and the persistence over time. The error distribution is assumed…
含未观测异质性的大规模面板选择模型:贝叶斯与极大似然分析
This paper considers the estimation and inference procedures for the case of a logistic panel regression model with interactive fixed effects, where multiple individual effects are allowed and the model is capable of capturing high-dimensional cross-section dependence. The proposed model also allows for heterogeneous regression coefficients. New Bayesian and non-Bayesian approaches are introduced to estimate the model parameters. We investigate the asymptotic behaviors of…
随机系数二元响应模型的非参数极大似然方法
The venerable method of maximum likelihood has found numerous recent applications in nonparametric estimation of regression and shape constrained densities. For mixture models the nonparametric maximum likelihood estimator (NPMLE) of Kiefer and Wolfowitz plays a central role in recent developments of empirical Bayes methods. The NPMLE has also been proposed by Cosslett as an estimation method for single index linear models for binary response with random coefficients.…
发达经济体重大产品与劳动力市场改革的稳健相关因素:Logit 模型的 BAMLE 证据
Summary The political economy literature has put forward a multitude of hypotheses regarding the drivers of structural reforms, but few, if any, empirically robust findings have emerged thus far. To make progress, we draw a parallel with model uncertainty in the growth literature and provide a new version of the Bayesian averaging of maximum likelihood estimates (BAMLE) technique tailored to binary logit models. Relying on a new database of major past labor and product…
从亚马逊到苹果:在线零售销售、购买发生与访问行为建模
In this study, we propose a multivariate stochastic model for Web site visit duration, page views, purchase incidence, and the sale amount for online retailers. The model is constructed by composition from carefully selected distributions and involves copula components. It allows for the strong nonlinear relationships between the sales and visit variables to be explored in detail, and can be used to construct sales predictions. The model is readily estimated using maximum…