Advancing Methodological Knowledge Within State and Local Demography: a Case Study

Much of the academic literature dealing with state and local demography involves the development and evaluation of methods for estimating population. The focus on estimation methods is not surprising because they are used in many states to allocate resources. The quality control in regard to the validity and reliability afforded these methods by the traditional academic peer review process is important because, among other things, it serves to reduce the high potential for conflict that exists when resources are at stake. There are, however, methods being used by state and local demographers that have not been subject to peer review. While not necessarily unsound, these fugitive methods serve to keep the potential for conflict high because of the uncertainty regarding their validity and reliability. This paper examines just such a situation in the form of a case study. It is a discussion of a regression model developed in Nevada following the 2000 census that led to conflict over its use to estimate the population of Clark County, Nevada in 2002. The discussion reveals statistical and methodological shortcomings in this model that lead to an alternative model not subject to these shortcomings. This example illustrates how this type of analysis and discussion can lead to a wider understanding of methods on the part of practitioners through the corrective process of academic peer review. It also suggests that states in which estimates are used to allocate resources would be well-served by subjecting new methods being considered for use to academic peer review before they are adopted.     

立法后评估结果的回应机制

立法后评估结果的回应机制,就是特定的国家机关针对立法后评估报告中提出来的问题,采取特定方式作出回复或反应的具体运作过程。有效的立法后评估的回应机制建立在立法后评估结果的信度与效度上,其回应主体是立法后评估报告所涉及的有关立法与执法机关或人员,同时还要求运用特定的回应方式与内容。为保障立法后评估结果顺畅的有效回应,还需要建立完善的立法后评估结果回应的监控制度。     

新凯恩斯主义视域下中国近十年货币政策轨迹

基于开放经济新凯恩斯主义货币政策动态随机一般均衡模型的新凯恩斯主义菲利普斯曲线、动态IS曲线、新凯恩斯主义工资菲利普斯曲线,考察了不同货币政策机制对中国近十年货币政策轨迹的拟合度。通过全样本预测,发现混合规则对于中国近十年的产出缺口具有最佳的拟合度,单一的价格规则或数量规则均无法较好地拟合中国现实数据;二阶矩匹配的结果进一步证实了这一论断。     

基于随机化适应性Lasso的高维变量选择

Lasso等惩罚变量选择方法选入模型的变量数受到样本量限制。文献中已有研究变量系数显著性的方法舍弃了未选入模型的变量含有的信息。本文在变量数大于样本量即p>n的高维情况下,使用随机化bootstrap方法获得变量权重,在计算适应性Lasso时构建选择事件的条件分布并剔除系数不显著的变量,以得到最终估计结果。本文的创新点在于提出的方法突破了适应性Lasso可选变量数的限制,当观测数据含有大量干扰变量时能够有效地识别出真实变量与干扰变量。与现有的惩罚变量选择方法相比,多种情境下的模拟研究展示了所提方法在上述两个问题中的优越性。实证研究中对NCI-60癌症细胞系数据进行了分析,结果较以往文献有明显改善。     

基于评级模型的违约率估计

违约率是信用风险建模的核心输入变量,文章基于评级模型对违约率进行估计。估计违约数据很少的低违约组合的违约率是一个比较困难的问题,用最大谨慎原则方法解决这类问题时结果偏大,过于保守。文章将最大谨慎原则的思想与极大似然方法相结合,估计了低违约组合的违约率。估计的结果比仅用最大谨慎原则得到的结果很大程度上降低了保守度。     

一种估计连续策略博弈的两阶段方法

 最近实证博弈研究的迅速发展为分析市场中的策略互动、进行政策分析与反事实实验提供了有效的工具。本文提出一种估计不完全信息连续策略博弈的两阶段方法,它可以处理私有信息的影响。第一阶段通过非参数分位数回归估计局中人的策略与期望支付函数;第二阶段利用贝叶斯——纳什均衡不等式构造模拟最小距离估计量,最终获得结构参数的估计。数值模拟显示本方法有良好的小样本表现。与现有文献的嵌套固定点方法相比,本方法不需计算均衡,极大地降低了计算量,并减轻了多重均衡的干扰。本方法既可以用于估计离散状态博弈,也适用于连续状态博弈。     

On the estimation and application of max-stable processes

The theory of max-stable processes generalizes traditional univariate and multivariate extreme value theory by allowing for processes indexed by a time or space variable. We consider a particular class of max-stable processes, known as M4 processes, that are particularly well adapted to modeling the extreme behavior of multiple time series. We develop procedures for determining the order of an M4 process and for estimating the parameters. To illustrate the methods, some examples are given for modeling jumps in returns in multivariate financial time series. We introduce a new measure to quantify and predict the extreme co-movements in price returns.     

Treatment-competing events in dynamic regimes

A dynamic treatment regime is a sequence of decision rules for assigning treatment based on a patient’s current need for treatment. Dynamic regimes are viewed, by many, as a natural way of treating patients with chronic diseases; that is, treating patients with adaptive, complex, longitudinal treatment regimens. In developing dynamic treatment strategies, treatment-competing events may play an important role in the overall treatment strategy, and their effects on subsequent treatment decisions and eventual outcome should be considered. Treatment-competing events may be defined generally as patient-specific, random events which interrupt the ongoing treatment decision process in a dynamic regime. Treatment-competing events censor later treatment decisions that would otherwise be made on a particular dynamic treatment regime had the competing events not occurred. For example, in therapeutic studies of HIV, physicians may assign treatment based on a patient’s current level HIV1-RNA; this defines a treatment assignment rule. However, the presence of opportunistic infections or severe adverse events may preclude a strict adherence of the treatment assignment rule. In other contexts, the “censoring”-by-death phenomenon may be viewed as an example of a treatment-competing event for a particular dynamic treatment regime. Treatment-competing events can be built into the dynamic treatment regime framework and counting processes are a natural mechanism to facilitate this development. In this paper, we develop treatment-competing events in a dynamic infusion policy, a random dynamic treatment regime where multiple infusion treatments are initiated simultaneously and given continuously over time subject to the presence/absence of a treatment-competing event. We illustrate how our methodology may be used to suggest an estimator for a particular causal estimand of recent interest. Finally, we exemplify our methods in a recent study of patients undergoing coronary stent implantation.     

Complexity and Adaptivity in Supply Networks: Building Supply Network Theory Using a Complex Adaptive Systems Perspective*

Supply networks are composed of large numbers of firms from multiple interrelated industries. Such networks are subject to shifting strategies and objectives within a dynamic environment. In recent years, when faced with a dynamic environment, several disciplines have adopted the Complex Adaptive System (CAS) perspective to gain insights into important issues within their domains of study. Research investigations in the field of supply networks have also begun examining the merits of complexity theory and the CAS perspective. In this article, we bring the applicability of complexity theory and CAS into sharper focus, highlighting its potential for integrating existing supply chain management (SCM) research into a structured body of knowledge while also providing a framework for generating, validating, and refining new theories relevant to real‐world supply networks. We suggest several potential research questions to emphasize how a CAS perspective can help in enriching the SCM discipline. We propose that the SCM research community adopt such a dynamic and systems‐level orientation that brings to the fore the adaptivity of firms and the complexity of their interrelations that are often inherent in supply networks.