中国生育率研究方法:30年回眸

改革开放30年是我国人口学及人口研究迅速成长的30年。生育率研究方法从一个侧面反映出改革开放以来我国人口学研究方法的发展。中国的生育率研究方法既有从西方引进的各种生育率指标和模型,也有中国学者为了适应自己的需要而改进和创建的方法和模型。笔者从生育率度量指标和生育率模型两个方面总结我国生育率研究方法的应用及变化。对在中国生育率研究中所使用的主要方法进行回顾并对这些方法对我国生育率研究的贡献进行总结。     

Clarifying the Association Between Mother–Father Relationship Aggression and Parenting

Although much research examines the association between fathers' relationship aggression and mothers' parenting, little attention is given to mothers' aggression, mutual aggression, or fathers' parenting. Using a sample of coresiding couples from the Fragile Families and Child Wellbeing Study (N = 973), the authors examine the association between mothers' and fathers' relationship aggression, measured as frequency and perpetration–victimization types (mutual, mother only, father only), and mothers' and fathers' parenting. Fixed effects regression models show that fathers' aggression is positively related to mothers' parenting stress, whereas father‐only or mother‐only aggression is related to fathers' stress. For both parents, aggression perpetration is negatively related to their own engagement with children. Mother‐only aggression is negatively related to mothers' spanking and positively related to fathers' spanking. These findings suggest the importance of examining both parents' aggression and perpetrators' as well as victims' parenting to better understand the link between relationship aggression and parenting.     

Relatives in Residence: Relatedness of Household Members Drives Schooling Differentials in Mozambique

Children typically receive investments from their fathers, but absent fathers often invest at low levels. In a father's absence, what types of nonfathers invest heavily in children? This article investigates educational participation as a reflection of childhood investments on Ibo Island, Mozambique, where only one third of school‐aged children live with their biological fathers. Father‐present children generally attended school at the highest rates. Stepchildren and father‐absent relatives (e.g., grandchildren, nieces) attended school at comparably high rates if any coresiding children were father‐present. This may signal high altruism among present fathers toward some nonoffspring. Consistent with this result, a fixed effects model indicates that, within the same household, adult males invested equally in their own children, relatives, and stepchildren. Prejudicially lower investments were made in children who were unrelated to the household's adult males, however; this result has strong negative implications for the well‐being of African children fostered by nonrelatives.     

Are all jobs created equal? A cross-national analysis of women's employment and child malnutrition in developing countries

Using multi-level models, the analysis examines female employment and child stunting across 49 developing countries. At the country level, female labor force participation is not associated with malnutrition after controlling for economic development. At the individual level, a binary measure of employment is not significantly associated with malnutrition. However, a more nuanced measure of seven occupational categories shows that certain types of employment improve malnutrition. Professional, clerical, sales, and domestic jobs are associated with reduced stunting. These effects are only partially mediated by wealth, perhaps suggesting that some jobs may bring benefits to the household beyond the sheer acquisition of tangible resources. Agricultural jobs are associated with increased malnutrition. Manual labor and service work do not have an effect on malnutrition, compared to unemployment. Thus, women's employment is not necessarily a mechanism for empowerment and wellbeing. Not all jobs are created equal, and many of them do not confer the benefits that are typically associated with working outside the home.     

Seemingly unrelated systems of econometric equations

A generalization of Zellner's SUR model is derived for sets of seemingly unrelated systems of econometric equations. The resulting structural form – worked out for a set of Cowles Commission-type simultaneous equations systems – is general enough to include any SUR-type or panel-type specification of systems of econometric equations with contemporaneously correlated errors. Maximum estimation efficiency is obtained by treating all the individual subsystems at once rather than in a subsystem-by-subsystem fashion.     

Quantile regression for robust estimation and variable selection in partially linear varying-coefficient models

In this paper, we develop a new estimation procedure based on quantile regression for semiparametric partially linear varying-coefficient models. The proposed estimation approach is empirically shown to be much more efficient than the popular least squares estimation method for non-normal error distributions, and almost not lose any efficiency for normal errors. Asymptotic normalities of the proposed estimators for both the parametric and nonparametric parts are established. To achieve sparsity when there exist irrelevant variables in the model, two variable selection procedures based on adaptive penalty are developed to select important parametric covariates as well as significant nonparametric functions. Moreover, both these two variable selection procedures are demonstrated to enjoy the oracle property under some regularity conditions. Some Monte Carlo simulations are conducted to assess the finite sample performance of the proposed estimators, and a real-data example is used to illustrate the application of the proposed methods.     

On the asymptotic normality of the R-estimators of the slope parameters of simple linear regression models with associated errors

ABSTRACT

The purpose of this paper is to prove, under mild conditions, the asymptotic normality of the rank estimator of the slope parameter of a simple linear regression model with stationary associated errors. This result follows from a uniform linearity property for linear rank statistics that we establish under general conditions on the dependence of the errors. We prove also a tightness criterion for weighted empirical process constructed from associated triangular arrays. This criterion is needed for the proofs which are based on that of Koul [Behavior of robust estimators in the regression model with dependent errors. Ann Stat. 1977;5(4):681–699] and of Louhichi [Louhichi S. Weak convergence for empirical processes of associated sequences. Ann Inst Henri Poincaré Probabilités Statist. 2000;36(5):547–567].     

Joint GEEs for multivariate correlated data with incomplete binary outcomes

This study considers a fully-parametric but uncongenial multiple imputation (MI) inference to jointly analyze incomplete binary response variables observed in a correlated data settings. Multiple imputation model is specified as a fully-parametric model based on a multivariate extension of mixed-effects models. Dichotomized imputed datasets are then analyzed using joint GEE models where covariates are associated with the marginal mean of responses with response-specific regression coefficients and a Kronecker product is accommodated for cluster-specific correlation structure for a given response variable and correlation structure between multiple response variables. The validity of the proposed MI-based JGEE (MI-JGEE) approach is assessed through a Monte Carlo simulation study under different scenarios. The simulation results, which are evaluated in terms of bias, mean-squared error, and coverage rate, show that MI-JGEE has promising inferential properties even when the underlying multiple imputation is misspecified. Finally, Adolescent Alcohol Prevention Trial data are used for illustration.     

Difference-based matrix perturbation method for semi-parametric regression with multicollinearity

This paper addresses the collinearity problems in semi-parametric linear models. Under the difference-based settings, we introduce a new diagnostic, the difference-based variance inflation factor (DVIF), for detecting the presence of multicollinearity in semi-parametric models. The DVIF is then used to device a difference-based matrix perturbation method for solving the problem. The electricities distribution data set is analyzed, and numerical evidences validate the effectiveness of the proposed method.