The effect of immigration on the internal migration of the native-born population, 1981–1990

This study examines the impact of immigration on the labor market opportunities of the native-born population by looking through the window of migration. We use Current Population Survey data to analyze the one-year migration patterns of Anglos and Blacks and include the presence of recent immigrants in the origin and (potential) destination US states among the covariates. Our departure model employs a logit specification to predict outmigration (vs not) from the state during the year prior to the survey. Our arrival model uses a conditional logit discrete choice specification with sampling among the alternatives to predict destination state. The data are taken from the 1981, 1984, 1987, and 1990 Current Population Surveys. This work adds to other knowledge of the migratory response of workers and sheds light on theories of substitution and complementarity in labor markets. States with high levels of recent immigration are less likely to retain Anglo workers or receive new Anglo interstate migrants, but this apparent substitution effect is partially offset by the presence of long-term immigrant stock. Lower skilled Anglos are more susceptible to this substitution effect than those of higher skill level. In the black population, results are more complex. Lower skilled blacks are less attracted to high immigrant locations, but African-Americans of higher skill level in selected occupations and industries are predicted to be more likely to remain in or choose states with many recent immigrants.     

Post-high school choices: New evidence from a multinomial logit model

A multinomial logit model is estimated to investigate the destination of students one-year after graduating from high school. The appropriate specification of the choice set available to high school leavers is as follows: private four-year college, public four-year college, private two-year college, public two-year college, employed and unemployed. We test for several possible combinations of these choices and find that these pooled models are all rejected in favour of the full model. The transition from high school to college and to work is more complex than previous studies have recognised. Received: 12 July 2002/Accepted: 2 November 2002 All correspondence to Jim Taylor. The authors are grateful to Steve Bradley and an anonymous referee for valuable comments on a previous draft of this paper. We alone are responsible for the errors and omissions. Anh Nguyen is grateful to the ESRC for providing financial support. Responsible editor: Daniel S. Hamermesh.     

农村独生子女生育选择影响因素及测度研究——基于Multinomial Logistic模型实证分析

本文基于北京市昌平区的农村独生子女调查数据,利用效用最大化离散选择模型,对农村独生子女生育选择模式及影响因素进行了分析。文章不仅考察了个体因素、经济与社会政策因素对生育选择模式的影响,更重要的是从生育选择的预测概率、离散变化以及Odds Ratios等多角度对影响因素的重要程度、影响大小等进行了定量测度分析。并从中推断起决定作用的因素发生变化时,可能导致的生育意愿、计划与行为的改变,探讨独生子女生育选择对中国未来人口变动趋势产生的影响和政策意义。     

A measure of quality of opportunity

A ratio measure of the quality of choice alternatives available to individuals is introduced that can be calibrated using either actual revealed choice data or theoretical choice models.     

The behaviour towards malaria care—a multinomial logit approach

This paper attempts to estimate a disease specific demand function to study the determinants of utilisation of the services of a health care provider or a treatment regiment for malaria. The study adapts a multinomial logit framework to look at both facility characteristics and individual patient features on demand for malaria care in Ghana. The individual patient characteristics form a set of social indicators which can be used to discriminate or put into groups patients with respect to their choice of provider.The study confirms the popular use of self-medication as a first choice of action in treating malaria. The choice of malaria care providers is found to be influenced by facility price, travel time, waiting time for treatment, education, age, sex and quality of care measured in terms of drugs availability. We further find that as income increases, the odds are in favour of self-medication when people get malaria.     

Multiple paths in educational transitions: A multinomial transition model with unobserved heterogeneity

In many countries educational branching points consist of more than two qualitatively different alternatives, and only some alternatives provide the opportunity of continuing into higher education. I develop a multinomial transition model for modeling the effects of family background characteristics and individual characteristics on these complex educational careers. The model controls for unobserved heterogeneity that may, if ignored, result in biased estimates. Compared to previous research, I explicitly include instrumental variables that ensure identification of the unobserved component. I apply the model to the Danish case and analyze data which covers the educational careers of a cohort of Danes born around 1954. I find that the model brings forward non-trivial heterogeneity in the influence of family background and ability on qualitatively different choice alternatives both within and across transitions. I also find that not controlling for unobserved heterogeneity leads to marked underestimation of the family background effect on both early and late transitions in the educational career.     

Marriage Markets and Intermarriage: Exchange in First Marriages and Remarriages

Drawing on data from the American Community Survey, we compare patterns of assortative mating in first marriages, remarriages, and mixed-order marriages. We identify a number of ascribed and achieved characteristics that are viewed as resources available for exchange, both as complements and substitutes. We apply conditional logit models to show how patterns of assortative mating among never-married and previously married persons are subject to local marriage market opportunities and constraints. The results reveal that previously married individuals “cast a wider net”: spousal pairings are more heterogamous among remarriages than among first marriages. Marital heterogamy, however, is reflected in systematic evidence of trade-offs showing that marriage order (i.e., status of being never-married) is a valued trait for exchange. Never-married persons are better positioned than previously married persons to marry more attractive marital partners, variously measured (e.g., highly educated partners). Previously married persons—especially women—are disadvantaged in the marriage market, facing demographic shortages of potential partners to marry. Marriage market constraints take demographic expression in low remarriage rates and in heterogamous patterns of mate selection in which previously married partners often substitute other valued characteristics in marriage with never-married persons.     

Accounting for dynamic selection bias in educational transitions: The Cameron-Heckman latent class estimator and its generalizations

The sequential logit model of educational transitions has long been the dominant modeling framework for the study of inequality of educational opportunity ever since the seminal works of [Mare, 1980] and [Mare, 1981]. But conventional applications of the model are known to be biased by the ubiquitous presence of unobserved heterogeneity. Cameron and Heckman (1998) propose a logit model that allows for two or three latent classes if the selection bias is solely generated by a person-specific component of stable unobserved heterogeneity. To evaluate the latent class logit regression estimator, this study makes use of simulated data to eliminate the influences of other problems of transition modeling. The simulation is based on five independent pairs of large samples generated from standard distributional assumptions of transition modeling. The new estimator appears to be an effective way to adjust for dynamic selection bias when family background effects are transition-invariant and sample size is in the order of ten thousand or above. By contrast, the conventional sequential logit model produces results that are very different from the data generating models. This study also considers two alternative ways to improve statistical efficiency: (1) incorporate a crude indicator of stable unobserved heterogeneity; (2) pool the effect estimates across transitions, background variables, and alternative estimators to smooth out noise under the null hypothesis of transition invariance. In addition, this study examines the impact of indicator reliability and sample size on the performance of the latent class regression models and suggests practical guidelines.     

The impact of local labour markets on investment in further education: Evidence from the England and Wales youth cohort studies

The paper focuses on the individual's choice of activity on completion of compulsory schooling – to remain in full-time education or to seek employment – and the factors influencing this decision. Information from the England and Wales Youth Cohort Studies, coupled with labour market data, is used to estimate of logit model of choice and assess the role played by social and market factors. The results show that labour market conditions play an influential role in determining outcomes, particularly in the case of young males with weaker academic qualifications. Consistent with the time-series evidence, we find that participation rates in further education for both males and females are positively related to the unemployment rate in the local labour market, the effects being greater at times of economic recession when unemployment rates are rising. Received: 5 May 1997/Accepted: 17 July 1998     

Effect of an Accessibility Measure in a Model for Choice of Residential Location,Workplace, and Type of Employment

A three-level nested logit model for the choice of residential location, workplace, and type of employment is used to assess the effect of an individual-specific measure of accessibility to employments that takes into account the attractiveness of different occupations when the choice of workplace is anticipated in the decision of residential location. The model allows for variation in the preferences for types of employment across individuals and accounts for individual heterogeneity of preferences at each choice level in education, age, gender, and children. Using data from the Île-de-France region, the model shows that the individual-specific accessibility measure is an important determinant of the choice of residential location and its effect differs along the life cycle. The attractiveness of the types of employment is a better predictor of the workplace location than the usual total number of employments.     

A Complexity Approach to Psychological Well-Being in Adolescence: Major Strengths and Methodological Issues

Psychological well-being in adolescence is an increasing field of study. Deepening in its knowledge during this period of life can be of a lot of help to the designing of more adjusted prevention programs aimed to avoid or reduce the problems adolescents might be experiencing. Complexity theories can be a productive alternative to the important limitations explanations about psychological well-being in adolescence have nowadays. Answers to a questionnaire have been obtained from a sample of 968 Catalan adolescents from 12 to 16 years old including 29 psychological well-being indicators measuring 8 dimensions related to satisfaction with specific life domains, self-esteem, perceived social support, perception of control and values.A structural equation modelling approach to complexity that focuses on the non-linearity property has been followed. Given the large number of dimensions, the model has been estimated in two steps. First, a confirmatory factor analysis model has been fitted to the 29 indicators and appropriate factor scores have been saved. Then all possible products and squared terms of the factor scores have been computed and have been used as predictors of the dependent variable using an ordered logit model.The results show that a non-linear model including interaction effects among the 8 dimensions, age and gender, has a higher explanatory power to predict satisfaction with life as a whole, compared to a linear model estimated from those same indicators.This work must be understood as a first step, basically a methodological one, to the future elaboration of new models of psychological well-being in adolescence to be based on the principles defended by complexity theories.     

Family Structure and Subjective Economic Well-Being: Some New Evidence

The paper investigates the main socio-demographic and economic determinants of subjective economic well-being in different typologies of households. Previous studies have used dummy variables to explore the effect of family structure. In this paper, however four different models—one for each family typology—have been estimated to test if each selected explanatory variable is significant and how it acts in determining the level of subjective economic well-being. To achieve this, we apply an under-used logit model—the partial proportional ordered model. Our analysis, based on data from the 2005 Italian Survey on Income and Living Conditions highlights the main variables affecting the subjective economic well-being of all household typologies. These main variables are related to income adequacy, such as being able to afford housing, clothes and holidays, and also include the work-status and level of education of the respondent. These variables produce notable differences in the level of subjective economic well-being. We find that couples with no children have the highest level of perceived economic well-being, while couples with two or more children and even more so one-person households are more economically insecure.     

Incorporating Neighborhood Choice in a Model of Neighborhood Effects on Income

Studies of neighborhood effects often attempt to identify causal effects of neighborhood characteristics on individual outcomes, such as income, education, employment, and health. However, selection looms large in this line of research, and it has been argued that estimates of neighborhood effects are biased because people nonrandomly select into neighborhoods based on their preferences, income, and the availability of alternative housing. We propose a two-step framework to disentangle selection processes in the relationship between neighborhood deprivation and earnings. We model neighborhood selection using a conditional logit model, from which we derive correction terms. Driven by the recognition that most households prefer certain types of neighborhoods rather than specific areas, we employ a principle components analysis to reduce these terms into eight correction components. We use these to adjust parameter estimates from a model of subsequent neighborhood effects on individual income for the unequal probability that a household chooses to live in a particular type of neighborhood. We apply this technique to administrative data from the Netherlands. After we adjust for the differential sorting of households into certain types of neighborhoods, the effect of neighborhood income on individual income diminishes but remains significant. These results further emphasize that researchers need to be attuned to the role of selection bias when assessing the role of neighborhood effects on individual outcomes. Perhaps more importantly, the persistent effect of neighborhood deprivation on subsequent earnings suggests that neighborhood effects reflect more than the shared characteristics of neighborhood residents: place of residence partially determines economic well-being.     

Modelling and analyzing density-dependent population processes: Comparison between wild and laboratory strains of the bean weevil,Callosobruchus chinensis (L.)

Three models were constructed for analyzing the population characteristics ofC. chinensis on stored beans; model A describing the whole reproductive process with a single equation, model B describing the three age-specific processes (oviposition, egg survival and larval survival) with separate equations, and model C which describes all these processes not for the whole habitat but for the individual beans comprizing it. The logit equation was employed here as a common basis to describe the density-response relationship involved. All three models showed very good fit to the experimental data obtained for both laboratory and wild strains of the weevil. The parameter values characterizing the population dynamics were, however, widely different between the two strains; the laboratory one which had been reared for some 500 generations showed significantly higher reproductive capacity, less sensitive and gentler response to crowding in both adult and egg stages, and more uniform egg distribution among individual beans, as compared with the wild strain newly introduced. Sensitivity analyses using these models suggested that these changes in population characteristics have been attained by the process of domestication or adaptation to stable laboratory conditions through a long period of time. This process seemed in effect to have optimized the population's performances in the laboratory environment. Evolutionary significance of such optimization was discussed with reference to the selection pressure which may have acted upon individuals.     

The Influence of Local Price and Availability on Parents’ Choice of Child Care

The striking variation in patterns of child care usage across states reflects differences in family characteristics, but may also reflect exogenous differences in local child care markets. Type of care selected will be influenced by the availability, cost, and accessibility of supply in the child care market as well as by family and child characteristics and cultural preferences. This study contributes to the growing literature on parental demand for child care by using a recent detailed data set from the state of Minnesota. We link household-level data on child care usage and family characteristics with county-level data on average provider rates and availability by type of care in order to estimate multinomial logit models analyzing the family, child, and market characteristics that predict type of care. Our analysis shows that using a relative or friend to care for a child is largely determined by availability, and choice of family care providers is most responsive to price for employed mothers. The types of care chosen by mothers who are not in the paid labor force differ substantially from the choices of employed mothers, and their use of center care is influenced by the prices of both center and family providers. Attitudes towards relative care are also shown to influence type of care chosen.     

Count data models for demographic data∗

Key demographic variables, such as the number of children and the number of marriages or divorces, can only take integer values. This papers deals with the estimation of single equation models in which the counts are regressed on a set of observed individual characteristics such as age, gender, or nationality. Most empirical work in population economics has neglected the fact that the dependent variable is a nonnegative integer. In the few cases where this feature was recognized, the authors advocated the use of the Poisson regression model. The Poisson model imposes, however, the equality of conditional mean and variance, a restriction which is often rejected by the data. We propose a generalized event count model to simultaneously allow for a wide class of count data models and account for over‐ and underdispersion. This model is successfully applied to German data on fertility, divorces and mobility.     

Group living decisions as youths transition to adulthood

This study follows teens through young adulthood as they transition to independent living. We focus on a little studied issue: why some youths live in groups rather than alone or with parents. This choice is important because the size of the group has a substantial impact on the demand for dwelling units; the more youths per dwelling the lower is aggregate demand and the greater is population density. Our study also adds to the knowledge of which factors influence youths' choice of destination as they leave the parental home. The empirical testing uses a discrete hazard model within a multinomial logit framework to allow for more than one possible state transition. We find that economic variables have little impact on the decision of whether to exit to a large versus a small group, while socio-demographic variables matter. We also test a new push-pull hypothesis and find that the pull of economic variables on the probability of exiting the parental home increases as youths reach their mid to late twenties. Received: 15 July 1999/Accepted: 15 May 2000     

Parental survival data: Some results of the application of Ledermann's model life tables

Summary Ledermann's one- and two-parameter model life tables are used in order to summarize and compare adult mortality estimates derived from parental survival data, and also to link parental survival with child survival data. The Ledermann models provide an alternative to the logit model used by Brass and Hill. Examination of life tables derived from actual child and adult mortality estimates reveals that although the two types of models yield similar overall levels of mortality, they show marked differences in the estimated patterns by sex and age. It has not been possible to disentangle completely how much of this divergence is due to the models themselves and how much to inadequacies in the data available. Finally, we question whether it is always wise to establish a full life table from child and adult mortality estimates when these are based on data which refer to different periods of exposure to the risk of dying, without allowance for possible distortions resulting from mortality change.     

Modeling approaches to the indirect estimation of migration flows: from entropy to EM

"The paper presents probability models to recover information on migration flows from incomplete data. Models are used to predict migration and to combine data from different sources.... Two models are considered: the binomial (multinomial) model, which underlies the logit model and the logistic regression, and the Poisson model, which underlies the loglinear model, the log-rate model and the Poisson regression.... By way of illustration, the probabilistic approach and the EM algorithm are applied to two different missing data problems." (EXCERPT)