Partial Identification of Economic Mobility: With an Application to the United States

Abstract

The economic mobility of individuals and households is of fundamental interest. While many measures of economic mobility exist, reliance on transition matrices remains pervasive due to simplicity and ease of interpretation. However, estimation of transition matrices is complicated by the well-acknowledged problem of measurement error in self-reported and even administrative data. Existing methods of addressing measurement error are complex, rely on numerous strong assumptions, and often require data from more than two periods. In this article, we investigate what can be learned about economic mobility as measured via transition matrices while formally accounting for measurement error in a reasonably transparent manner. To do so, we develop a nonparametric partial identification approach to bound transition probabilities under various assumptions on the measurement error and mobility processes. This approach is applied to panel data from the United States to explore short-run mobility before and after the Great Recession.     

人工智能生成物的著作权保护路径探析——兼评人工智能生成物著作权第一案

人工智能技术的发展对传统著作权制度带来了显著的冲击。以人工智能生成物著作权第一案为例,通过审视作品构成要件判断标准发现,独创性始终贯彻以人类作者为中心的评价标准,同时,智力成果要件则是认定人工智能生成物构成著作权法意义上作品与否的重要标准。从人类是否实际参与作品的创作过程来看,多数人工智能生成物不构成作品,而保护人工智能生成物的价值追求与邻接权制度的基本理念相适应,且邻接权制度的扩张趋势也为把人工智能生成物纳入其保护范畴创造了机会。建议立法通过扩张邻接权制度的权利内容与客体类型以对人工智能生成物提供必要保护。而在当前阶段,反不正当竞争法可以为人工智能生成物相关利益主体提供一定限度的过渡保护。     

Linking perceived organizational support with employee work outcomes in a Chinese context: Organizational identification as a mediator

Perceived organizational support (POS) is viewed as an important explanatory framework for understanding the relationship between employees and the workplace, and is regarded by some researchers as central in understanding job-related attitudes and behaviors of employees. However, less research has taken into account the role of organizational identification, which reflects how individuals define the self with respect to their organization, as a potential influence on such relationships. Drawing on a cross-organizational sample of 238 subordinate-supervisor dyads from the People’s Republic of China, we examined whether organizational identification mediates the effect of perceived organizational support (POS) on work outcomes including turnover intentions, work performance, and organizational citizenship behavior (OCB). Results from the current study showed that organizational identification fully mediates the relation of POS to OCB-directed to individuals, and partially mediates relations between POS and other work outcomes (turnover intention, work performance, OCB-directed to organization). Implications for management theory and practice are discussed.     

A knowledge chain management framework to support integrated decisions in global supply chains

Knowledge management has been identified as a key enabler to achieve organisation’s value chain competitiveness. It, however, has been facing fresh challenges in a global supply chain setting. This paper proposes a global knowledge chain management (GKCM) framework that identifies and prioritises critical knowledge that a global supply chain can focus on to support integrated decisions. The framework explores three types of global context knowledge, namely global market knowledge, global capacity knowledge and global supply network configuration knowledge. Empirical study has been undertaken within the manufacturing industry to evaluate the GKCM framework. Analytic network process has been explored as a key method to assess the importance of the global knowledge constructs from supply chain managers’ perspectives. A key contribution of the paper is that it advances existing knowledge chain management approaches within one organisation and its local supply chain to include the global context knowledge applicable to global manufacturing settings, and highlights how the GKCM framework can support global supply chain integrated decisions.     

Universal versus contextual effects on TQM: a triangulation study using neural networks

The objective of this study is to extend previous research on total quality management (TQM)-context-performance relationships and ‘fit’ using multiple methods. We combine artificial neural networks (ANNs) with structural equation modelling (SEM) to analyse several hypotheses and propositions. This is the first study in this area of research that utilises ANNs and a triangulation technique in the presence of several contextual factors. The SEM analyses suggest that company size and industry type may have contingency effects on some of the TQM practices and/or TQM-performance relationships. However, the ANN models have shown that these two contingency factors do not moderate TQM outcomes, implying that all organisations can benefit from TQM regardless of size and type. As well, these models show that formal TQM implementation and/or ISO certifications do not add any predictive power to the ANN models except in one case: TQM implementation and/or ISO certification added to organisational effectiveness and customer results to predict financial and market (F&M) results. The results further indicate that even though implementing TQM alone has a bigger impact on F&M results than obtaining ISO certification alone, combining the two will have an even greater impact on these results. Joint implementation leads to greater improvements in organisational effectiveness, which, in turn, has a positive effect on customer results and consequently F&M results. This is a unique finding within the context of moderator effects on TQM-performance relationships.     

Fairness and commitment to change in M&As: The mediating role of organizational identification

This paper examines the determinants of employees' affective commitment to change in the context of M&As. Based on the group engagement model (Tyler & Blader, 2000, 2003), we predicted that organizational identification with the newly formed organization mediates the positive impact of employees’ overall justice judgments and perceived change favorableness on affective commitment to change. We tested our predictions using data collected during an international merger. After controlling for country effects, results support our hypotheses. Implications for research and practice alike are discussed.     

Binary Response Models for Panel Data: Identification and Information

This paper considers a panel data model for predicting a binary outcome. The conditional probability of a positive response is obtained by evaluating a given distribution function (F) at a linear combination of the predictor variables. One of the predictor variables is unobserved. It is a random effect that varies across individuals but is constant over time. The semiparametric aspect is that the conditional distribution of the random effect, given the predictor variables, is unrestricted. This paper has two results. If the support of the observed predictor variables is bounded, then identification is possible only in the logistic case. Even if the support is unbounded, so that (from Manski (1987)) identification holds quite generally, the information bound is zero unless F is logistic. Hence consistent estimation at the standard pn rate is possible only in the logistic case.     

Calibration of FI‐ISK,an Invasiveness Screening Tool for Nonnative Freshwater Invertebrates

The Freshwater Invertebrate Invasiveness Scoring Kit (FI‐ISK) is proposed as a screening tool for identifying potentially invasive freshwater invertebrates. FI‐ISK was adapted from the Fish Invasiveness Scoring Kit (FISK) of Copp, Garthwaite, and Gozlan, which is an adapted form of the Weed Risk Assessment (WRA) of Pheloung, Williams, and Halloy. Initial assessments using FI‐ISK, which include confidence (certainty/uncertainty) rankings by the assessor to each response, were calibrated to determine the most appropriate score thresholds for classifying nonnative species into low‐, medium‐, and high‐risk categories, using both the original medium‐to‐high risk threshold scores for the WRA (i.e., ≥6) and for FISK (i.e., ≥19). Patterns of the assessor's confidence, when making the responses during the FI‐ISK assessments, were also examined. Using receiver operating characteristic (ROC) curves, FI‐ISK was shown to distinguish accurately (and with statistical confidence) between potentially invasive and noninvasive species of nonnative crayfish (Decapoda: Astacidae, Cambaridae, Parastacidae), with the statistically appropriate threshold score for high‐risk species scores being ≥16. FI‐ISK represents a useful and viable tool to aid decision‐ and policymakers in assessing and classifying freshwater invertebrates according to their potential invasiveness.     

基于违约鉴别能力组合赋权的小企业信用评级——基于小型工业企业样本数据的实证分析

信用评级是衡量债务违约的可能性,因此评级体系要有违约风险识别能力,能够将违约客户和非违约客户显著地区分开.通过逼近理想点的思路,构建多目标规划模型求解最优的组合权重,并对中国某区域性商业银行1 814笔小型工业企业贷款进行实证分析.本文的创新与特色一是以非违约企业的数据到正理想点的距离代数和最小为第一个目标函数,以违约企业的数据到负理想点的距离代数和最小为第二个目标函数,构建多目标非线性规划模型进行组合赋权,在满足了“非违约企业的评价得分越高、违约企业的评价得分越低”要求的目标下得到最优的组合赋权的权重系数,使赋权结果保证了评级模型能够将违约企业与非违约企业最大地区分开.改变了现有研究的组合赋权脱离评价目的的弊端,改变了现有研究中违约与非违约企业的评价得分存在大量重叠、对两类企业的区分能力低的弊端.二是通过检验“违约企业的信用得分是否显著小于非违约企业的信用得分”的J-T非参数检验,验证信用评价模型的合理性.改变现有研究忽略对信用评价模型的合理性进行验证的弊端.三是经过实证,发现本研究建立的组合赋权模型的违约鉴别能力(Z=5.546)要高于现有研究的两种常用组合赋权模型、即基于方差最大的组合赋权(Z=4.298)和基于偏差最小的组合赋权(Z=5.182)     

施工索赔机会发现的描述与求解方法

施工索赔机会发现是索赔管理的核心和关键内容,是索赔决策的瓶颈环节。分析了施工索赔机会发现的信息结构,给出了其灰描述,研究了施工索赔机会发现的两种求解方法,研究了索赔机会发现支持系统的工作机制。