Program Evaluation and Causal Inference With High‐Dimensional Data

In this paper, we provide efficient estimators and honest confidence bands for a variety of treatment effects including local average (LATE) and local quantile treatment effects (LQTE) in data‐rich environments. We can handle very many control variables, endogenous receipt of treatment, heterogeneous treatment effects, and function‐valued outcomes. Our framework covers the special case of exogenous receipt of treatment, either conditional on controls or unconditionally as in randomized control trials. In the latter case, our approach produces efficient estimators and honest bands for (functional) average treatment effects (ATE) and quantile treatment effects (QTE). To make informative inference possible, we assume that key reduced‐form predictive relationships are approximately sparse. This assumption allows the use of regularization and selection methods to estimate those relations, and we provide methods for post‐regularization and post‐selection inference that are uniformly valid (honest) across a wide range of models. We show that a key ingredient enabling honest inference is the use of orthogonal or doubly robust moment conditions in estimating certain reduced‐form functional parameters. We illustrate the use of the proposed methods with an application to estimating the effect of 401(k) eligibility and participation on accumulated assets. The results on program evaluation are obtained as a consequence of more general results on honest inference in a general moment‐condition framework, which arises from structural equation models in econometrics. Here, too, the crucial ingredient is the use of orthogonal moment conditions, which can be constructed from the initial moment conditions. We provide results on honest inference for (function‐valued) parameters within this general framework where any high‐quality, machine learning methods (e.g., boosted trees, deep neural networks, random forest, and their aggregated and hybrid versions) can be used to learn the nonparametric/high‐dimensional components of the model. These include a number of supporting auxiliary results that are of major independent interest: namely, we (1) prove uniform validity of a multiplier bootstrap, (2) offer a uniformly valid functional delta method, and (3) provide results for sparsity‐based estimation of regression functions for function‐valued outcomes.     

A Canadian experience with an intervention programme for vulnerable families: lessons for German social work and policy

Schools are an important community resource that can foster social connections and enhance the health and wellbeing of children and families in Germany through information, health promotion and interventions. While developing social connections between the school and vulnerable families—those who are most limited in their access to other sources of information, education and intervention—is complex and challenging, it is nonetheless critical. This paper reports on the role of Families and Schools Together (F&ST), a school-based intervention aimed at vulnerable families, in building and promoting the social connections, or social capital, that strengthen families and communities. Thematic analysis of semi-structured interviews revealed that programme participants perceived an increase in their social capital in all three of its dimensions (bonding, bridging and linking). The paper highlights the importance of social capital in building stronger, more resilient families and of strengthening relations between parents and schools, and contributes to the sharing of experience and views on matters concerning families in Germany.     

The effects of child support guidelines: An analysis of the evidence in court records

Court records from four Ohio counties were used to compare child support orders before and after promulgation of federally mandated guidelines in 1987. There was no significant change in probability of Court Ordered Child Support. Amount Ordered in constant dollars increased between 1985 and 1987–88. Variables influencing Court Ordered Child Support differed post-guidelines. Years Married, Attorney for Both and Attorney for Wife were significant in both years. Number of Children, Rural, and Wife's Motions were significant in 1987–88. Variables affecting amount ordered also differed after adoption of the guidelines. Wife Contested, Husband's Motions, Defendant and Plaintiff no longer were significant in 1987–88. Years Married and Payment by Father were significantly related to Amount Ordered in 1985 but not in 1987–88. Number of Children, Expenses Paid, and Number of Assets were significantly related to Amount Ordered in both years.Salaries and research support were provided by state and federal appropriations to the Ohio Agricultural Research and Development Center, and by the Department of Family Resource Management, and The Office of Research and Graduate Studies, The Ohio State University.Kathryn Stafford is Associate Professor, Department of Family Resource Management, 1787 Neil Avenue, Columbus, OH 43210-1295. Her research interests include household management and time use. She received her Ph.D. from Cornell University.Golden Jackson is Assistant Professor, Department of Family Resource Management, 1787 Neil Avenue, Columbus, OH 43210-1295. Her research is primarily in the area of the economic effects of divorce. She received her Ph.D. from The Ohio State University.Sharon Seiling is Assistant Professor and Extension Specialist in Family Resource Management, Department of Family Resource Management, 1787 Neil Avenue, Columbus, OH 43210-1295. Her research is on the impact of family change, especially divorce, on access to housing and overall financial well-being. She received her Ph.D. from Cornell University.     

股指期货信息内含股价变动信息的挖掘 ――小波框架与支持向量回归的金融建模应用

 内容提要：中国股指期货的推出指日可待，交易者多了一种投资工具的同时也带来了新的风险。建立准确的金融时间序列预测模型是逐利及避险的方法之一，一直是学者专家研究的热点。本研究结合小波转换与支持向量回归，提出一个二阶段时间序列预测模型。先以离散小波框架将预测变量分解成不同尺度的多个子序列，揭示隐藏在预测变量内的信息，再以支持向量回归为工具，以这些子序列为预测变量建构SVR模型。本研究以日经225指数开盘价为预测目标，以期货开盘价为预测变量对模型进行实证研究，结果显示，该模型的预测绩效比单纯SVR模型及随机漫步模型好。未来可尝试以不同的基底函数作进一步研究。     

A study of BIB designs through support matrices

This paper deals with the existence and nonexistence of BIB designs with repeated blocks. The approach is an algebraic one. The concept of a support matrix is introduced and some of its basic properties are noted. Some basic examples of support matrices are given when the block size is 3. The connection between full column rank proper support matrices and irreducible designs is explored and some examples of such matrices are given.     

一个一般的Gale定理及其应用

考虑局部凸拓扑向量空间中包含多值映射的不等式系统，在所谓广义近次类凸条件下建立了一个Gale型择一定理，并给出了该定理在向量最优化问题中的应用．本文结果涵盖并推广了许多已知的择一定理．     

The Effect of Support Expectations on Prenatal Attachment: An Evidence-Based Approach for Intervention in an Adolescent Population

This study was designed to determine the significant variables predicting prenatal attachment in an adolescent population. Scientifically supported knowledge of the factors enhancing attachment plays a crucial role in assisting social workers and other health care professionals to accurately assess and intervene to decrease pregnancy risks. Previous prenatal attachment studies demonstrated conflicting findings due to problems from using different theoretical frameworks and research methodologies. In order to ensure consistency, this study infused an attachment theory perspective. Bowlby’s attachment theory, Levitt’s support expectations model, and research from prenatal relationship studies were integrated. The social survey sampled 129 minority status pregnant adolescents attending public school. Measurements included the Prenatal Attachment Inventory (PAI) and the Support Expectations Index (SEI). Regression analyses revealed that support expectation was a powerful predictor of prenatal attachment with pregnancy planning and less stress adding importantly to explain over 33% of the variance. Support expectation was a greater predictor of prenatal attachment than the actual support available. Findings also supported the construct of prenatal attachment as the initial stage of development of the life cycle. Janis B. Feldman is an Assistant Professor, University, of Texas-Pan American.     

移动模架制梁施工技术

移动模架施工技术是世界桥梁施工的先进技术，成功应用于石太客运专线，克服了大吨位箱梁预制、运输和架设的困难。本工程的移动模架采用整体液压系统驱动，工效高，详细了介绍移动模架的工作原理和主要施工工艺。     

Newsvendor Problems with Demand Shocks and Unknown Demand Distributions

In today's competitive market, demand volume and even the underlying demand distribution can change quickly for a newsvendor seller. We refer to sudden changes in demand distribution as demand shocks. When a newsvendor seller has limited demand distribution information and also experiences underlying demand shocks, the majority of existing methods for newsvendor problems may not work well since they either require demand distribution information or assume stationary demand distribution. We present a new, robust, and effective machine learning algorithm for newsvendor problems with demand shocks but without any demand distribution information. The algorithm needs only an approximate estimate of the lower and upper bounds of demand range; no other knowledge such as demand mean, variance, or distribution type is necessary. We establish the theoretical bounds that determine this machine learning algorithm's performance in handling demand shocks. Computational experiments show that this algorithm outperforms the traditional approaches in a variety of situations including large and frequent shocks of the demand mean. The method can also be used as a meta‐algorithm by incorporating other traditional approaches as experts. Working together, the original algorithm and the extended meta‐algorithm can help manufacturers and retailers better adapt their production and inventory control decisions in dynamic environments where demand information is limited and demand shocks are frequent      

当代社会老年人赡养支持网研究

面对老龄化社会的到来,越来越多的人提出走"养老保障社会化"之路.但目前这种建议和对策实施的效果如何?延续了几千年的家庭养老方式是否被社会养老模式所代替?就此进行了深入的探讨和回答.