The new immigrant survey pilot (NIS-P): Overview and new findings about U.S. Legal immigrants at admission

This paper provides an overview of the New Immigrant Survey Pilot (NIS-P), a panel survey of a nationally representative sample of new legal immigrants to the United States based on probability samples of administrative records of the U.S. Immigration and Naturalization Service (INS). The NIS-P links survey information about immigrants' pre- and post-immigration labor market, schooling, and migratory experiences with data available from INS administrative records, including the visa type under which the immigrant was admitted. Results indicate that the procedures followed for locating, interviewing, and reinterviewing respondents yielded representative samples of new legal immigrants and high-quality data. On the basis of data obtained from the first round of the survey, we present new information never before available on the schooling and language skills of new immigrants and their earnings gains from immigration.     

Intimate partner abuse of older men: considerations for the assessment of risk

Intimate partner abuse among older persons, though less common than among the general population, is a significant concern. Drawing from the intimate partner abuse and elder abuse literatures, this paper presents considerations for the assessment of risk for intimate partner abuse perpetrated against older men, with reference to the prevalent gendered view of abuse between intimate partners. Potential victim and perpetrator risk factors specific to this context are discussed and existing risk assessment tools are introduced. Implications and future research directions are discussed with regard to the application of risk assessment technology to this context.     

Will They Stay? Foreign-Born Out-Migration from New U.S. Destinations

Immigrants living in new destinations in 1995 were 2.5 times more likely to have migrated to another labor market by 2000 as immigrants living in traditional places. The researchers look at two competing explanations for immigrants’ differential internal migration patterns, namely that immigrants prefer areas with relatively large nativity concentrations which provide them with social support versus immigrants are target earners who prefer robust labor markets with strong employment growth and high wages. Utilizing confidential Census data for 1990 and 2000, the authors develop new destination classifications for 741 labor markets that take into account the differential growth and composition characteristics of 24 Asian, Latin American and Caribbean immigrant groups living in those markets. The empirical analysis of labor market out-migration indicates that immigrants do not see internal migration as an either/or choice between economics and social support but prefer residence places that allow them to maximize both conditions.     

Fiscal externalities of becoming a parent

Theoretical and empirical results suggest that there are externalities to childbearing, but those results usually assume that these externalities accrue uniformly within a homogeneous population. We advance this argument by developing separate estimates of the fiscal externalities associated with parents—those who devote time or material resources to minor children—and nonparents. Our analysis uses data from the US Panel Study of income Dynamics on the age profiles of taxes paid and publicly funded benefits consumed by parents and nonparents, together with a previously developed intertemporal economic-demographic accounting model. The accounting framework takes into account the net fiscal impacts of future generations as well as the present population. Our findings indicate that, with a 3 percent discount rate, parents produce a substantial net fiscal externality, about $217,000 in 2009 dollars. This is equivalent to a lifetime annuity of nearly $8,100 per year beginning at age 18. The results are sensitive to both the discount rate used and the proportion of parents within the cohort.     

Individual Decisions to Migrate During Civil Conflict

The existing literature on forced migration limits our understanding of how violence affects migration to competing destinations. This article adds to the literature on forced migration by studying how armed violence during a period of civil conflict in south-central Nepal influenced the likelihood of local, internal, and international migration. We find that violence has a nonlinear effect on migration, such that low to moderate levels of violence reduce the odds of movement, but when violence reaches high levels, the odds of movement increase. We also find that the effect of violence on mobility increases as the distance of the move increases. When we consider the influence of violence on microlevel decision-making, we find that the effects of individual and household-level determinants were mostly consistent with hypotheses derived from contemporary theories of voluntary migration and that no predictor of migration influenced the decision to migrate differently in the presence of violence.     

SOME CAUTIONARY NOTES ON THE USE OF CONJOINT MEASUREMENT FOR HUMAN JUDGMENT MODELING*

Conjoint measurement has been suggested as a methodology that might be useful in assisting research concerned with the identification of the structural form of a judge's model. This paper synthesizes the results of some recent research that examined the robustness of this methodology. This research suggests that conjoint measurement has three major weaknesses: (1) certain biases exist when diagnosing model structure, (2) model diagnosis is limited to a small set of potential models, and (3) error substantially compromises conjoint measurement's ability to diagnose model structure. An empirical example that demonstrates some of the difficulties of using this methodology with experimental data is also presented.     

Seeking Social Security: An Alternative Motivation for Mexico-US Migration

In this analysis we investigate the degree to which the absence of effective pension systems may generate motivations for international migration as a means of self-financing retirement. Using ethnosurvey data gathered in selected Mexican communities and US destination areas, we estimate models to predict the odds of US migration from indicators of relative wages and whether or not jobs in Mexico were covered by that country's social security system. We find that by holding constant the binational differential in expected wages, the odds of out-migration were much higher for male household heads working in jobs that were not covered by social security compared with those working in jobs that enjoyed such coverage. Subsequent analyses showed that the odds of receiving a pension in old age were systematically higher for former US migrants, and that the likelihood of pension receipt rose steadily as the number of US trips and amount of US experience accumulated.     

Adoption Issues in Perspective: An Introduction to the Special Issue

The process and dynamics of adoption have changed considerably in the last 50 years, assisted by both social change and new knowledge of human development. The current status of 3 important aspects of adoption is reviewed: 1) the general effects of relinquishment and adoption, 2) the effects of secrecy in adoption, and 3) the need to add information on the dynamics of adoption to the training of therapists. The articles contained in this special adoption issue of the Journal of Social Distress and the Homeless are summarized and are placed in context of the 3 aspects reviewed.     

Integrating linear discriminant analysis,polynomial basis expansion,and genetic search for two-group classification

We propose a hybrid two-group classification method that integrates linear discriminant analysis, a polynomial expansion of the basis (or variable space), and a genetic algorithm with multiple crossover operations to select variables from the expanded basis. Using new product launch data from the biochemical industry, we found that the proposed algorithm offers mean percentage decreases in the misclassification error rate of 50%, 56%, 59%, 77%, and 78% in comparison to a support vector machine, artificial neural network, quadratic discriminant analysis, linear discriminant analysis, and logistic regression, respectively. These improvements correspond to annual cost savings of $4.40–$25.73 million.