Intergenerational mobility of housework time in the United Kingdom

This paper analyzes the relationship between parents’ time devoted to housework and the time devoted to housework by their children. Using data from the Multinational Time Use Study for the UK, we find positive intergenerational correlations in housework for both parents, indicating that the more time parents devote to housework, the more time their children will devote to housework. Using data from the British Household Panel Survey, we find that a higher father–mother housework ratio is positively related to a higher child–mother housework ratio, even after allowing for individual fixed-effects. In order to address the potential exacerbation of errors-in-variables arising from the fixed-effects specification, we instrument the father–mother ratio of housework using father’s and mother’s lagged weekly working hours. The Instrumental-Variable estimates fully support the fixed-effects estimates, and suggest that the latter should be regarded as a lower bound. We also present evidence of the link between housework during adolescence and during adulthood, which may indicate that housework time during adulthood depends on the housework time during childhood, which may also be affected by parents’ housework time. Our results contribute to the field of the intergenerational mobility of behaviors.     

农村彩礼性质的区域比较研究

不同于宏观性的一般化概括和具体经验的描述总结,立足于中国农村区域差异的中观视角,在村庄社会结构和社会文化区域比较的基础上,理解农村彩礼性质的区域差异问题。南方团结型村庄,村庄宗族性结构力量及规范性强,代际关系厚重均衡,婚姻自主性较高,婚姻市场竞争性一般,农村彩礼还保持传统性的一面,缓慢稳定地变迁。北方分裂型村庄,村庄竞争性强,代际关系厚重但不均衡,婚姻自主性弱,婚姻市场竞争激烈,彩礼上涨迅速,成为代际剥削的手段。中部分散型村庄,社会结构力量弱,代际关系均衡,婚姻市场竞争弱,农民的理性化程度高,婚姻彩礼是一种理性化模式。农村区域差异的视角,为我们深刻理解农村彩礼的区域差异及变迁模式提供了中层理论建构。     

A link-free sparse group variable selection method for single-index model

For regression problems with grouped covariates, we adapt the idea of sparse group lasso (SGL) [10 J. Friedman, T. Hastie, and R. Tibshirani, A note on the group lasso and a sparse group lasso, Tech. Rep., Statistics Department, Stanford University, 2010. [Google Scholar]] to the framework of the sufficient dimension reduction. Assuming that the regression falls into a single-index structure, we propose a method called the sparse group sufficient dimension reduction to conduct group and within-group variable selections simultaneously without assuming a specific link function. Simulation studies show that our method is comparable to the SGL under the regular linear model setting and outperforms SGL with higher true positive rates and substantially lower false positive rates when the regression function is nonlinear. One immediate application of our method is to the gene pathway data analysis where genes naturally fall into groups (pathways). An analysis of a glioblastoma microarray data is included for illustration of our method.     

Local functional data model for characterizing shape variation of similar curves

“Similar curves” in the present article refers to a family of curves whose major shape are similar, but who have variation coming from curve-specific sources. The goal here is to develop a general methodology to describe small changes among similar curves. Previous methods mainly focus on dimension reduction through FPCA, which are not appropriate for quantifying local variation. Here, we consider a local functional data model which divides data into segments adaptively and models each segment with a shape invariant model. Such model has great flexibility in characterizing local variation of curves, as illustrated by simulation and real data examples.     

老龄化背景下中国劳动供给变动及其经济影响:基于CGE模型的分析

文章研究老龄化背景下中国未来劳动供给的变动趋势及其经济影响.基于可计算一般均衡(CGE)模型,将不同年龄劳动者在劳动效率方面的差异纳入劳动供给要素的考察范围,定量评估人口规模与年龄结构、劳动参与率与劳动力总量、有效劳动总量的变动趋势及其对劳动力要素价格、经济产出及产业结构变动的影响.结果表明,中国有效劳动供给在达到峰值后的降速将快于人口总量和劳动力总量的变动,且更具波动性;在以有效劳动衡量劳动供给变动的模拟情景下,21世纪上半叶中国GDP增长率的降速将快于只考虑人口总量或劳动力总量变动的情景;若只考虑劳动年龄人口变动对劳动供给的影响,而忽视不同年龄劳动者在劳动效率方面的异质性,则有可能低估未来经济增长.     

Multiple-population shrinkage estimation via sliced inverse regression

The problem of dimension reduction in multiple regressions is investigated in this paper, in which data are from several populations that share the same variables. Assuming that the set of relevant predictors is the same across the regressions, a joint estimation and selection method is proposed, aiming to preserve the common structure, while allowing for population-specific characteristics. The new approach is based upon the relationship between sliced inverse regression and multiple linear regression, and is achieved through the lasso shrinkage penalty. A fast alternating algorithm is developed to solve the corresponding optimization problem. The performance of the proposed method is illustrated through simulated and real data examples.     

Impact of intervention on breastfeeding outcomes and determinants based on theory of planned behavior

Background

Breastfeeding knowledge, attitude, subjective norm, and perceived control are significant determinants of breastfeeding, according to the theory of planned behavior (TPB). However, evidence concerning the effectiveness of the TPB-based intervention in breastfeeding promotion is sparse. Meanwhile, the changes of these determinants with time have not been examined in previous studies.

上海青年创业建设的研究

自20世纪80年代彼得·德鲁克提出“创业型经济”以来．创业开始引起各方的高度关注,上海的创业潮也日益高涨,上海青年在这股创业风潮中也扮演着非常重要的角色。本文立足于前人的研究基础,探析上海的创业现状,发现基于GEM下的创业环境优越,但少数纬度还未达到国际标准;探索上海青年的创业实际．发现创业信息平台建设滞后等问题;根据现状和问题,本文旨在提出“加快上海创业建设”等建议,以期为建设上海青年创业系统工程提供参考。     

Does Internet Use Affect Netizens’ Trust in Government? Empirical Evidence from China

Social Indicators Research - Although the Internet has had a profound influence on China’s economy and society, the empirical research pertaining to political consequences of the Internet is...     

A novel regularization method for estimation and variable selection in multi-index models

Multi-index models have attracted much attention recently as an approach to circumvent the curse of dimensionality when modeling high-dimensional data. This paper proposes a novel regularization method, called MAVE-glasso, for simultaneous parameter estimation and variable selection in multi-index models. The advantages of the proposed method include transformation invariance, automatic variable selection, automatic removal of noninformative observations, and row-wise shrinkage. An efficient row-wise coordinate descent algorithm is proposed to calculate the estimates. Simulation and real examples are used to demonstrate the excellent performance of MAVE-glasso.