Dealing with selection bias in educational transition models: The bivariate probit selection model

This paper proposes the bivariate probit selection model (BPSM) as an alternative to the traditional Mare model for analyzing educational transitions. The BPSM accounts for selection on unobserved variables by allowing for unobserved variables which affect the probability of making educational transitions to be correlated across transitions. We use simulated and real data to illustrate how the BPSM improves on the traditional Mare model in terms of correcting for selection bias and providing credible estimates of the effect of family background on educational success. We conclude that models which account for selection on unobserved variables and high-quality data are both required in order to estimate credible educational transition models.     

Survival of related individuals: an extension of some fundamental results of heterogeneity analysis

"Many ideas in the analysis of heterogeneous mortality are based on the relationship between individual and observed hazard rates. This connection is established with the help of conditional averaging procedure: The observed risk of death at age x is calculated among those who survive this age. The analogy of this result for bivariate survival model with correlated individual hazards is derived. In the case of correlated frailty model the parametric specification of the mean, variance and correlation coefficient of the bivariate frailty distribution among survivors is obtained. The relationship between local association measure and the characteristics of the bivariate frailty distribution among survivors is established." (SUMMARY IN FRE)     

Survival of related individuals: An extension of some fundamental results of heterogeneity analysis

Many ideas in the analysis of heterogeneous mortality are based on the relationship between individual and observed hazard rates. This connection is established with the help of conditional averaging procedure: The observed risk of death at age x is calculated among those who survive this age. The analogy of this result for bivariate survival model with correlated individual hazards is derived. In the case of correlated frailty model the parametric specification of the mean, variance and correlation coefficient of the bivariate frailty distribution among survivors is obtained. The relationship between local association measure and the characteristics of the bivariate frailty distribution among survivors is established.     

Behavior genetic modeling of human fertility: findings from a contemporary danish twin study

Behavior genetic designs and analysis can be used to address issues of central importance to demography. We use this methodology to document genetic influence on human fertility. Our data come from Danish twin pairs born from 1953 to 1959, measured on age at first attempt to get pregnant (FirstTry) and number of children (NumCh). Behavior genetic models were fitted using structural equation modeling and DF analysis. A consistent medium-level additive genetic influence was found for NumCh, equal across genders; a stronger genetic influence was identified for FirstTry, greater for females than for males. A bivariate analysis indicated significant shared genetic variance between NumCh and FirstTry.     

私人转移支付与农村反贫困

文章利用中国农户的微观数据,分析了私人转移支付的决定因素及福利影响。处理效应模型、双变量Probit模型和回归分解的结果显示,私人转移支付具有利他动机,弱势农户更易获得私人转移支付;私人转移支付对接受者的支出、贫困没有影响,而对储蓄有显著正向影响;私人转移支付在缩小接受者和非接受者的福利不平等方面作用微弱。     

Family size and children’s education in Vietnam

Data from the nationally representative 1994 Inter-Censal Demographic Survey are used to examine the association between family size and children s schooling in Vietnam. The data provide information on several education measures for all children over age 10, including children no longer residing in the household. Although a clear inverse bivariate association between family size and children s school attendance and educational attainment is evident, multivariate analysis controlling for urban/rural residence, region, parents’ education, household wealth, and child’s age, reveals that much of this association, especially that predicting educational attainment, is attributable to these other influences. Moreover, much of the effect that remains after statistical adjustment for the other influences is seen mainly at the largest family sizes. We consider the implications of these findings for current population policy in Vietnam and the possible features of the Vietnamese context that might account for the modest association.     

Growth of U.S. population, 1940–1971, in the light of an interactive two-sex model

Since it is logically impossible to hold constant both male and female age-specific fertility rates, the intrinsic growth rates or the net reproduction rates for males and females, based on that assumption, are internally inconsistent. The interactive two-sex model presented in this paper holds constant a set of bivariate age-specific fertility rates by age of men and women and allows the male and female age-specific fertility rates to adjust themselves to achieve stability. The model gives the same intrinsic growth rate for both sexes and generates intrinsic age-specific fertility rates and intrinsic net reproduction rates for males and females which are consistent and can operate simultaneously on a population. The model is applied to the U.S. data for 1940–1971, and the results are compared with those obtained from the one-sex models.     

Do Health Insurance and Residence Pattern the Likelihood of Tubal Sterilization among American Women?

American women have increasingly opted for tubal sterilization or tubal ligation surgery in recent decades. While research has begun to examine the unequal access to health care in the United States, little research has considered how this may impact whether women opt for a tubal ligation surgery. We first profile women with and without tubal ligations using bivariate analysis of the most recent data available, a nationally representative sample of 7,643 women from the National Survey of Family Growth, Cycle 6 (NSFG, Public use data file, 2002). We then use logistic regression models to examine the relationship between having tubal ligation and two focal variables: (1) type of health insurance (Medicaid compared with private, government or military, and no health insurance), and (2) rural or urban place of residence. We find that women on Medicaid are nearly twice as likely to have had a tubal sterilization compared with women who have private health insurance coverage. Also, women on Medicaid are substantially more likely to have a tubal sterilization than women with government or military insurance and women with no health insurance (26% and 36%, respectively). Further, we find that women living in rural areas are nearly twice as likely to have a tubal sterilization, compared with women in urban or suburban areas, all else being equal.     

A modified Lee-Carter model for analysing short-base-period data

This paper introduces a new modified Lee-Carter model for analysing short-base-period mortality data, for which the original Lee-Carter model produces severely fluctuating predicted age-specific mortality. Approximating the unknown parameters in the modified model by linearized cubic splines and other additive functions, the model can be simplified into a logistic regression when fitted to binomial data. The expected death rate estimated from the modified model is smooth, not only over ages but also over years. The analysis of mortality data in China (2000-08) demonstrates the advantages of the new model over existing models.     

Skin Color and Intelligence in African Americans: A Reanalysis of Lynn's Data

Finding a modest yet statistically significant correlation between skin tone and vocabulary test scores among African Americans, Lynn (2002) concludes that intelligence in African Americans is significantly determined by the proportion of Caucasian genes (p. 365). In this reanalysis of Lynn's data, I demonstrate that his bivariate association disappears once childhood environmental factors are considered. Therefore, a genetic link between skin color and intelligence among African Americans cannot be supported in his data. Investigators seeking to establish a genetic connection between racial ancestry and intelligence must move beyond simple bivariate results to address the confounding influence of environmental conditions that affect cognitive development.     

The mismatch between employment and child care in Italy: the impact of rationing

In Italy the women’s participation is among the lowest in Europe. The female employment rate stands almost 13 percentage points below the EU average and 22 below the Lisbon target. One of the most important reasons is related to the characteristics of child care system. We analyze the characteristics of the child care system in Italy and its relationship to the labor market participation decision of mothers. The two decisions are jointly considered in a discrete choice framework, which also allows for simple forms of rationing. We go on to estimate a bivariate probit model of the child care and employment decisions and find evidence that rationing is an important factor in interpreting price effects on utilization rates and employment decisions. Responsible editors: Deborah Cobb-Clark & Tito Boeri     

The determinants of early fertility decline in Texas

This study examines the determinants of fertility control in a frontier population made up largely of German-Americans during the years from 1850 to 1910. The analysis employs a complex register of population constructed from census enumerations, civil and ecclesiastical vital registration, and tax assessment rolls. The article begins with a series of bivariate analyses with cohort of mother’s birth, religion, ethnicity, and husband’s occupation determining marital fertility. The second half of the paper presents a multivariate model of the determinants of fertility using these and other demographic characteristics as independent variables. The conclusions emphasize the importance of the overall trend toward fertility decline in the United States, as well as the role of religion and of occupational differences, in determining changes in fertility behavior in the population of Gillespie County, Texas.     

Obtaining multistate life table distributions for highly refined subpopulations from cross-sectional data: A bayesian extension of sullivan’s method

Multistate life table methods are often used to estimate the proportion of remaining life that individuals can expect to spend in various states, such as healthy and unhealthy states. Sullivan’s method is commonly used when panels containing data on transitions are unavailable and true multistate tables cannot be generated. Sullivan’s method requires only cross-sectional mortality data and cross-sectional data indicating prevalence in states of interest. Such data often come from sample surveys, which are widely available. Although the data requirements for Sullivan’s method are minimal, the method is limited in its ability to produce estimates for subpopulations because of limited disaggregation of data in cross-sectional mortality files and small cell sizes in aggregated survey data. In this article, we develop, test, and demonstrate a method that adapts Sullivan’s approach to allow the inclusion of covariates in producing interval estimates of state expectancies for any desired subpopulation that can be specified in the cross-sectional prevalence data. The method involves a three-step process: (1) using Gibbs sampling to sample parameters from a bivariate regression model; (2) using ecological inference for producing transition probability matrices from the Gibbs samples; (3) using standard multistate calculations to convert the transition probability matrices into multistate life tables.     

[A new study of the marital fertility model].]

The author critically examines the Coale-Trussell marital fertility model, asserting that it is not applicable to the situation in which the marital fertility rate decreases rapidly, such as in the case of China. The limitations of the Coale-Trussell model are outlined and a new model is developed, which is applicable to situations of both rapidly decreasing and moderately decreasing marital fertility rates. Empirical results drawn from an analysis of U.N. data for 1965 and 1981 indicate the greater accuracy and flexibility of the new model as compared with the Coale-Trussell model.     

Welfare reform and changes in the economic well-being of children*

Since the implementation of the Temporary Assistance for Needy Families (TANF) program in late-1996, welfare rolls have declined by more than half. This paper explores whether improvements in the economic well-being of children have accompanied this dramatic reduction in welfare participation. Further, we examine the degree to which the success or failure of welfare reform has been shared equally among families of varying educational background. We analyze data from the March Current Population Surveys (CPS) over the years 1988 through 2001. Specifically, we link data for families with children who are interviewed in adjacent years and determine whether their economic circumstances either improved or deteriorated. We use two alternative approaches to address this general issue: a variety of regression models and a difference-in-differences methodology. These approaches provide consistent answers. In a bivariate framework TANF is associated with higher incomes; but this association becomes insignificant in the presence of business cycle controls. We also determine that children who were poor at an initial time period benefit differently, depending on their parents' educational attainment level. Poor children with parents who do not have a high school degree are significantly worse off in the TANF era, relative to the era prior to welfare reform, than are poor children of more educated parents.     

Welfare reform and changes in the economic well-being of children*

Since the implementation of the Temporary Assistance for Needy Families (TANF) program in late-1996, welfare rolls have declined by more than half. This paper explores whether improvements in the economic well-being of children have accompanied this dramatic reduction in welfare participation. Further, we examine the degree to which the success or failure of welfare reform has been shared equally among families of varying educational background. We analyze data from the March Current Population Surveys (CPS) over the years 1988 through 2001. Specifically, we link data for families with children who are interviewed in adjacent years and determine whether their economic circumstances either improved or deteriorated. We use two alternative approaches to address this general issue: a variety of regression models and a difference-in-differences methodology. These approaches provide consistent answers. In a bivariate framework TANF is associated with higher incomes; but this association becomes insignificant in the presence of business cycle controls. We also determine that children who were poor at an initial time period benefit differently, depending on their parents' educational attainment level. Poor children with parents who do not have a high school degree are significantly worse off in the TANF era, relative to the era prior to welfare reform, than are poor children of more educated parents.     

Gender effect on housework allocation: Evidence from Spanish two-earner couples

In this paper we study the reasons behind the asymmetric distribution of housework within Spanish two-earner couples. Spouses' housework times are estimated jointly in a bivariate framework using data from the 1991 Work Situation and Time Use Survey. In order to understand the impact of gender-specific factors on the observed allocation of housework, we perform estimations that are in line with the Oaxaca decomposition. Our results suggest that the unequal division of domestic work between wives and husbands in our sample is mainly explained by gender-specific effects rather than by differences in their observable characteristics. All correspondence to Daniel Miles. We thank Juan F. Jimeno, a co-editor and two anonymous referees for helpful comments and the Spanish Instituto de la Mujer for providing us with the data. Financial support from the Cátedra de Estudios Feministas-Caixanova and from the Spanish Dirección General de Ense?anza Superior, grant number BEC2001-1270, is also gratefully acknowledged. Responsible editor: Daniel S. Hamermesh.     

Measuring housing quality in the absence of a monetized real estate market

Measuring housing quality or value or both has been a weak component of demographic and development research in less developed countries that lack an active real estate (housing) market. We describe a new method based on a standardized subjective rating process. It is designed to be used in settings that do not have an active, monetized housing market. The method is applied in an ongoing longitudinal study in north-east Thailand and could be straightforwardly used in many other settings. We develop a conceptual model of the process whereby households come to reside in high-quality or low-quality housing units. We use this theoretical model in conjunction with longitudinal data to show that the new method of measuring housing quality behaves as theoretically expected, thus providing evidence of face validity.     

On the estimation of multidimensional demographic models with population registration data

In this paper the estimation of multidimensional demographic models is investigated in situations where population registration data are available. With this kind of aggregate data, estimation by traditional methods is not possible. We look at two versions of the multidimensional model: the constant intensities model and the linear integration model. Some logical inconsistencies in the derivation of the latter are discussed. In particular, we argue that the linear integration model is not compatible with a Markov process. A new algorithm for the estimation of the constant intensities model with population registration data is proposed. Some preliminary results on the mathematical and statistical properties of this method are given. The algorithm is applied to Dutch nuptiality data.     

A mortality model based on a mixture distribution function

A new mortality model based on a mixture distribution function is proposed. We mix a half-normal distribution with a generalization of the skew-normal distribution. As a result, we get a six-parameter distribution function that has a good fit with a wide variety of mortality patterns. This mixture model is fitted to several mortality data schedules and compared with the Siler (five-parameter) and Heligman–Pollard (eight-parameter) models. Our proposal serves as a convenient compromise between the Heligman–Pollard model (which ensures a good fit with data but is often overparameterized) and the Siler model (which is more compact but fails to capture ‘accident humps’).