Deep Uncertainties in Sea-Level Rise and Storm Surge Projections: Implications for Coastal Flood Risk Management

Sea levels are rising in many areas around the world, posing risks to coastal communities and infrastructures. Strategies for managing these flood risks present decision challenges that require a combination of geophysical, economic, and infrastructure models. Previous studies have broken important new ground on the considerable tensions between the costs of upgrading infrastructure and the damages that could result from extreme flood events. However, many risk-based adaptation strategies remain silent on certain potentially important uncertainties, as well as the tradeoffs between competing objectives. Here, we implement and improve on a classic decision-analytical model (Van Dantzig 1956) to: (i) capture tradeoffs across conflicting stakeholder objectives, (ii) demonstrate the consequences of structural uncertainties in the sea-level rise and storm surge models, and (iii) identify the parametric uncertainties that most strongly influence each objective using global sensitivity analysis. We find that the flood adaptation model produces potentially myopic solutions when formulated using traditional mean-centric decision theory. Moving from a single-objective problem formulation to one with multiobjective tradeoffs dramatically expands the decision space, and highlights the need for compromise solutions to address stakeholder preferences. We find deep structural uncertainties that have large effects on the model outcome, with the storm surge parameters accounting for the greatest impacts. Global sensitivity analysis effectively identifies important parameter interactions that local methods overlook, and that could have critical implications for flood adaptation strategies.     

Can Carbon Nanomaterials Improve CZTS Photovoltaic Devices? Evaluation of Performance and Impacts Using Integrated Life‐Cycle Assessment and Decision Analysis

In emergent photovoltaics, nanoscale materials hold promise for optimizing device characteristics; however, the related impacts remain uncertain, resulting in challenges to decisions on strategic investment in technology innovation. We integrate multi‐criteria decision analysis (MCDA) and life‐cycle assessment (LCA) results (LCA‐MCDA) as a method of incorporating values of a hypothetical federal acquisition manager into the assessment of risks and benefits of emerging photovoltaic materials. Specifically, we compare adoption of copper zinc tin sulfide (CZTS) devices with molybdenum back contacts to alternative devices employing graphite or graphene instead of molybdenum. LCA impact results are interpreted alongside benefits of substitution including cost reductions and performance improvements through application of multi‐attribute utility theory. To assess the role of uncertainty we apply Monte Carlo simulation and sensitivity analysis. We find that graphene or graphite back contacts outperform molybdenum under most scenarios and assumptions. The use of decision analysis clarifies potential advantages of adopting graphite as a back contact while emphasizing the importance of mitigating conventional impacts of graphene production processes if graphene is used in emerging CZTS devices. Our research further demonstrates that a combination of LCA and MCDA increases the usability of LCA in assessing product sustainability. In particular, this approach identifies the most influential assumptions and data gaps in the analysis and the areas in which either engineering controls or further data collection may be necessary.     

Crowdfunding digital platforms: Backer networks and their impact on project outcomes

Crowdfunding platforms serve to connect project creators and backers. Previous research has explored several project and platform determinants that impact crowdfunding outcomes. However, there has been limited research on these determinants at an individual level. Our paper addresses how backers may influence the outcomes of projects in crowdfunding platforms. We explore several methods commonly used in the industry to identify influence and show that centrality measures through a backer affiliation network best exemplifies influence. Using data from Kickstarter, we construct a weighted backer network based on 52,678 common projects backed by 11,134 backers. Controlling for digital media mentions and project quality, we find evidence that backers in central positions within the network have a positive impact on multiple project outcomes such as the project success rates, amount of funds raised, speed of reaching the crowdfunding goal as well as the number of backers contributing to the project. These findings are replicated and reinforced by using data from a different crowdfunding platform using the entire backer network based on 1095 projects backed by 87,896 backers. Several robustness tests are used to validate these results.     

Influential observations in GARCH models

This paper examines local influence assessment in generalized autoregressive conditional heteroscesdasticity models with Gaussian and Student-t errors, where influence is examined via the likelihood displacement. The analysis of local influence is discussed under three perturbation schemes: data perturbation, innovative model perturbation and additive model perturbation. For each case, expressions for slope and curvature diagnostics are derived. Monte Carlo experiments are presented to determine the threshold values for locating influential observations. The empirical study of daily returns of the New York Stock Exchange composite index shows that local influence analysis is a useful technique for detecting influential observations; most of the observations detected as influential are associated with historical shocks in the market. Finally, based on this empirical study and the analysis of simulated data, some advice is given on how to use the discussed methodology.     

发达国家对华输出电子废弃物的环境影响与对策

近年来,发达国家电子废弃物的流入给发展中国家的环境和民众健康带来了严重的危害。我国在阻止电子废弃物流入的相关法律规制与监管上存在漏洞,且经济发展战略不合理,发展水平相对落后。法律和经济方面的双重落差导致发达国家电子废弃物流入屡禁不止,迫切需要采取有效措施加以应对。分析国外电子废弃物涌入我国之现状与原因,并从法律制度建设、经济发展思路、经济发展战略、国内管理和国际合作5方面提出应对策略。     

人的思想道德与经济发展的关联

人的思想道德是人口素质的重要内容，人的思想道德在经济增长和经济发展中具有重要作用。但目前学术界还缺乏对人的思想道德素质与经济增长、经济发展和脱贫致富相关性的理论分析与实证检验。新时期反贫困实践应重视思想反贫困和思想扶贫。     

Social network effects on academic achievement

How peer groups contribute to educational outcomes has long interested researchers. However, the possibility that peer groups dominated by either low- or high-achieving youth can have substantively different effects on achievement has been largely ignored. In this paper, we show that while being embedded in a high-achieving network of friends is not associated with increased own achievement, being embedded in a low-achieving network is associated with decreased own achievement. In additional analyses, we present evidence that these associations are at least in part due to influence, as opposed to only selection effects or shared environment. We also examine whether the structure of the network in which a student is embedded might affect their educational achievement. We show that achieving at higher levels positively predicts how centrally located a student is in their network, but being more centrally located does not predict concurrent achievement. This finding suggests that the behavior of individuals is affecting the formation of network structure and not the reverse.     

多维视角下的老年人社会健康影响因素分析

采用全国老年人口健康状况调查项目2002年~2005年纵向数据作为研究样本,对中国老年人社会健康的影响因素进行多维分析。通过结构方程模型,在方法上解决了社会健康的多维性、抽象概念的定量分析和测量误差的问题。研究发现,经济社会因素是影响老年人社会健康的主要方面,其中老年人自身的经济条件是最重要的因素;心理健康是影响老年人社会健康的关键因素,其它因素通过心理健康对社会健康起间接作用;由于社会生活方式的改变,家庭因素对老年人社会健康的直接影响正在弱化,但是家庭因素对老年人社会健康的间接影响依然存在。     

Graphical and Numerical Methods for Detecting Influential Observations in Complex Bingham Data

We describe methods to detect influential observations in a sample of pre-shapes when the underlying distribution is assumed to be complex Bingham. One of these methods is based on Cook's distance, which is derived from the likelihood of the complex Bingham distribution. Other method is related to the tangent space, which is based on the local influence for the multivariate normal distribution. A method to detect outliers is also explained. The application of the methods is illustrated in both a real dataset and a simulated sample.     

The breakdown and influence properties of outlier rejection-plus-mean procedures

In a recent paper, Hampel (1985) studied the properties of rejection-plus-mean procedures as estimators of a location parameter. He reported that these procedures have low breakdown and high variance. In this article it is pointed out that these results are due to the outliers being rejected in a forwards-stepping manner, and when a more appropriate backwards-stepping approach is used, rejection-plus-mean procedures lead to estimators with high breakdown and high variance. In this article it is pointed out that these results are due to the outliers being rejected in a forwards-stepping manner, and when a more appropriate backwards-stepping approach is used, rejection-plus-mean procedures lead to estimator with high breakdown and redescending theoretical influence function.