Disaster Relief as Social Action: A Weberian Look at Postdisaster Donation Behavior

Disaster relief involves a broad range of participants, which often results in a disjunction between actual disaster needs and the perception of appropriate strategies in relief provision. This research examines data collected through interviews with donation drive operators responding to Superstorm Sandy in 2012 and the May 2013 Oklahoma tornadoes. Using Weber's ideal types of social action to understand motivations for engaging in disaster relief, this article argues that motivations for participating in and organizing such drives influence donation strategies, and these motivations can be used to explain persistent donation of nonuseful materiel items. Findings indicate several different motivations for involvement and that donation type appeared linked to motivation. We suggest that motivation for engaging in social action is a valuable approach to better understanding donation behavior and, consequently, addressing the social problem of materiel convergence in the postdisaster environment.     

Compulsory income management: Combatting or compounding the underlying causes of homelessness?

Compulsory Income Management (CIM) is a form of conditional welfare that involves the mandatory quarantining of a portion of welfare recipients’ social security payments. Quarantined funds are accessible via a government-issued debit card, with restrictions surrounding where and on what funds can be spent. Official justifications of CIM have framed these policies as attempts to combat substance abuse and gambling problems, and to thus secure better outcomes for welfare recipients and their families. Central to this narrative has been the argument that welfare quarantining will ensure more money is spent on ‘essentials’, including accommodation. No existing studies, however, have specifically interrogated the impacts of CIM on housing security. This article responds to this gap in the literature by reviewing existing research concerning CIM's impacts and locating this research within broader debates regarding the causes of homelessness and the efficacy of individualised policy interventions. In doing so, it highlights CIM's potential to exacerbate housing insecurity not only through technical issues such as rental transfer failures, but also by contributing to underlying stressors such as economic disadvantage; relationship difficulties, poor health and addiction; and social stigma. The article concludes that – far from addressing the structural causes of homelessness – CIM has enflamed them.     

Beyond tail median and conditional tail expectation: Extreme risk estimation using tail Lp-optimization

The conditional tail expectation (CTE) is an indicator of tail behavior that takes into account both the frequency and magnitude of a tail event. However, the asymptotic normality of its empirical estimator requires that the underlying distribution possess a finite variance; this can be a strong restriction in actuarial and financial applications. A valuable alternative is the median shortfall (MS), although it only gives information about the frequency of a tail event. We construct a class of tail L^p-medians encompassing the MS and CTE. For p in (1,2), a tail L^p-median depends on both the frequency and magnitude of tail events, and its empirical estimator is, within the range of the data, asymptotically normal under a condition weaker than a finite variance. We extrapolate this estimator and another technique to extreme levels using the heavy-tailed framework. The estimators are showcased on a simulation study and on real fire insurance data.     

考虑零售商质量控制和风险规避的供应链网络均衡研究

研究零售商质量控制和供应链成员风险规避背景下供应链网络均衡问题。应用条件风险值度量风险规避程度，利用变分不等式理论描绘供应链参与者的最优经济行为，设计供应链网络均衡模型，考虑风险规避和质量控制策略对均衡的影响，证明均衡解存在且唯一，并运用Levenberg-Marquardt算法求解均衡模型。最后对重要参数进行数值分析，揭示质量控制和风险规避对供应链均衡解以及参与者条件风险值的影响。研究表明：供应链参与者越规避风险越有利于产品质量水平的提高，风险规避程度的加深会降低制造商或零售商自身的CVaR，同时增大对方的CVaR，对因产品合格率提高带来的利益而言，制造商所得优于零售商。     

Measuring and Achieving Equity in Multiperiod Emergency Material Allocation

Emergency material allocation is an important part of postdisaster emergency logistics that is significant for improving rescue effectiveness and reducing disaster losses. However, the traditional single‐period allocation model often causes local surpluses or shortages and high cost, and prevents the system from achieving an equitable or optimal multiperiod allocation. To achieve equitable allocation of emergency materials in the case of serious shortages relative to the demand by victims, this article introduces a multiperiod model for allocation of emergency materials to multiple affected locations (using an exponential utility function to reflect the disutility loss due to material shortfalls), and illustrates the relationship between equity of allocations and the cost of emergency response. Finally, numerical examples are presented to demonstrate both the feasibility and the usefulness of the proposed model for achieving multiperiod equitable allocation of emergency material among multiple disaster locations. The results indicate that the introduction of a nonlinear utility function to reflect the disutility of large shortfalls can make the material allocation fairer, and minimize large losses due to shortfalls. We found that achieving equity has a significant but not unreasonable impact on emergency costs. We also illustrate that using differing utility functions for different types of materials adds an important dimension of flexibility.     

Combined multiple testing of multivariate survival times by censored empirical likelihood

In each study testing the survival experience of one or more populations, one must not only choose an appropriate class of tests, but further an appropriate weight function. As the optimal choice depends on the true shape of the hazard ratio, one is often not capable of getting the best results with respect to a specific dataset. For the univariate case several methods were proposed to conquer this problem. However, most of the interesting datasets contain multivariate observations nowadays. In this work we propose a multivariate version of a method based on multiple constrained censored empirical likelihood where the constraints are formulated as linear functionals of the cumulative hazard functions. By considering the conditional hazards, we take the correlation between the components into account with the goal of obtaining a test that exhibits a high power irrespective of the shape of the hazard ratio under the alternative hypothesis.     

Dynamic inference for non-Markov transition probabilities under random right censoring

The main contribution of this article is the verification of weak convergence of a general non-Markov (NM) state transition probability estimator by Titman, which has not yet been done for any other general NM estimator. A similar theorem is shown for the bootstrap, yielding resampling-based inference methods for statistical functionals. Formulas of the involved covariance functions are presented in detail. Particular applications include the conditional expected length of stay in a specific state, given occupation of another state in the past, and the construction of time-simultaneous confidence bands for the transition probabilities. The expected lengths of stay in a two-sample liver cirrhosis dataset are compared and confidence intervals for their difference are constructed. With borderline significance and in comparison to the placebo group, the treatment group has an elevated expected length of stay in the healthy state given an earlier disease state occupation. In contrast, the Aalen-Johansen (AJ) estimator-based confidence interval, which relies on a Markov assumption, leads to a drastically different conclusion. Also, graphical illustrations of confidence bands for the transition probabilities demonstrate the biasedness of the AJ estimator in this data example. The reliability of these results is assessed in a simulation study.     

Conditional variance estimation via nonparametric generalized additive models

Generalized additive models provide a way of circumventing curse of dimension in a wide range of nonparametric regression problem. In this paper, we present a multiplicative model for conditional variance functions where one can apply a generalized additive regression method. This approach extends Fan and Yao (1998) to multivariate cases with a multiplicative structure. In this approach, we use squared residuals instead of using log-transformed squared residuals. This idea gives a smaller variance than Yu (2017) when the variance of squared error is smaller than the variance of log-transformed squared error. We provide estimators based on quasi-likelihood and an iterative algorithm based on smooth backfitting for generalized additive models. We also provide some asymptotic properties of estimators and the convergence of proposed algorithm. A numerical study shows the empirical evidence of the theory.     

Local Estimation of the Conditional Stable Tail Dependence Function

We consider the local estimation of the stable tail dependence function when a random covariate is observed together with the variables of main interest. Our estimator is a weighted version of the empirical estimator adapted to the covariate framework. We provide the main asymptotic properties of our estimator, when properly normalized, in particular the convergence of the empirical process towards a tight centred Gaussian process. The finite sample performance of our estimator is illustrated on a small simulation study and on a dataset of air pollution measurements.     

Modified chain sampling plans for lot inspection by variables and attributes

The purpose of acceptance sampling is to develop decision rules to accept or reject production lots based on sample data. When testing is destructive or expensive, dependent sampling procedures cumulate results from several preceding lots. This chaining of past lot results reduces the required size of the samples. A large part of these procedures only chain past lot results when defects are found in the current sample. However, such selective use of past lot results only achieves a limited reduction of sample sizes. In this article, a modified approach for chaining past lot results is proposed that is less selective in its use of quality history and, as a result, requires a smaller sample size than the one required for commonly used dependent sampling procedures, such as multiple dependent sampling plans and chain sampling plans of Dodge. The proposed plans are applicable for inspection by attributes and inspection by variables. Several properties of their operating characteristic-curves are derived, and search procedures are given to select such modified chain sampling plans by using the two-point method.