The welfare economics of immigration control

This paper develops a Harris-Todaro (HT) type model of East-West migration in which labour market imperfections prevent market clearing in both blocs. The model encompasses two extremes of perfectly flexible wages with full employment on the one hand, and the HT scenario where the real wage in the host country is fixed, on the other. Welfare analysis compares the laissez-faire migration equilibrium based on explicit calculations of potential migrants without immigration controls in the West, with the socially optimal level of migration. The paper examines the issue of immigration control by developing a model of illegal immigration in which the incentives facing the potentially illegal immigrant are explicitly modelled. Received: 3 April 1997/Accepted 16 March 1998     

Modeling Longitudinal Obesity Data with Intermittent Missingness Using a New Latent Variable Model

We propose a latent variable model for informative missingness in longitudinal studies which is an extension of latent dropout class model. In our model, the value of the latent variable is affected by the missingness pattern and it is also used as a covariate in modeling the longitudinal response. So the latent variable links the longitudinal response and the missingness process. In our model, the latent variable is continuous instead of categorical and we assume that it is from a normal distribution. The EM algorithm is used to obtain the estimates of the parameter we are interested in and Gauss–Hermite quadrature is used to approximate the integration of the latent variable. The standard errors of the parameter estimates can be obtained from the bootstrap method or from the inverse of the Fisher information matrix of the final marginal likelihood. Comparisons are made to the mixed model and complete-case analysis in terms of a clinical trial dataset, which is Weight Gain Prevention among Women (WGPW) study. We use the generalized Pearson residuals to assess the fit of the proposed latent variable model.     

Sampling distributions of kruskal's measure of stress for an asymmetric matrix

In the past ten years multidimensional scaling of nonmetric data has been widely applied in behavioral and business research. This paper investigates the asymmetric data matrix and develops stress distributions based upon a null hypothesis of equal like­lihood in the ranking of a set of proximities.     

Analytic bounds on causal risk differences in directed acyclic graphs involving three observed binary variables

We apply a linear programming approach which uses the causal risk difference (R_DC)$(R{D}_C)$ as the objective function and provides minimum and maximum values that R_DC$R{D}_C$ can achieve under any set of linear constraints on the potential response type distribution. We consider two scenarios involving binary exposure X, covariate Z and outcome Y. In the first, Z is not affected by X, and is a potential confounder of the causal effect of X on Y. In the second, Z is affected by X and intermediate in the causal pathway between X and Y. For each scenario we consider various linear constraints corresponding to the presence or absence of arcs in the associated directed acyclic graph (DAG), monotonicity assumptions, and presence or absence of additive-scale interactions. We also estimate Z-stratum-specific bounds when Z is a potential effect measure modifier and bounds for both controlled and natural direct effects when Z is affected by X  . In the absence of any additional constraints deriving from background knowledge, the well-known bounds on R_Dc$R{D}_c$ are duplicated: -Pr(Y≠X)?R_DC?Pr(Y=X)$-\mathit{Pr}(Y\ne X)?R{D}_C?\mathit{Pr}(Y=X)$. These bounds have unit width, but can be narrowed by background knowledge-based assumptions. We provide and compare bounds and bound widths for various combinations of assumptions in the two scenarios and apply these bounds to real data from two studies.     

Adapting the jury trial for program evaluation: A report of an experience

A portion of the graduate program in clinical community psychology at SUNY Buffalo was subjected to a jury trial as a form of program evaluation. The theory of the trial as evaluation, the problems of implementation, and a posttrial evaluation are discussed. The trial, while time-consuming, especially in its pretrial phases, has the potential for presenting a dramatic picture of a program through the medium of human testimony. The jury was able to arrive at clear decisions on questions put to it, with a high degree of confidence. Decision makers accepted some of the jury's conclusions, and subjective evidence suggests that many of the controversial issues which generated the trial were resolved for the group by the procedure. The posttrial evaluation revealed limitations, such as evidence which was not presented at the trial. The experience proved useful for purposes of interdisciplinary education, providing another lens through which the evaluation problem could be viewed.     

In-vehicle fatalities,seat belts,and compulsory seat belt legislation: The Manitoba experience

Using medical data from the Medical Officer of Health (MOH) the paper presents an exploratory mutivariate statistical analysis of in-vehicle mortality in Manitoba, 1983–85. It is found that total mortality had increased in excess of 31% following the introduction of compulsory seat-belt legislation in April, 1984. It is also found that in-vehicle mortality is related to average age of drivers/occupants, sex of victims, blood alcohol level, and in some cases seat-belt use. Since the data represents a chronological series it is not possible to disentangle the physical effect of seat-belts and the compulsory seat-belt legislation.     

The Roles of Instability and Housing in Low-Income Families’ Residential Mobility

Given the repercussions of residential mobility, increased understanding of correlates of mobility is important for efforts to support family well-being. Using survey data on low-income families from the Three City Study (N = 2393), multilevel mixed longitudinal analyses examined factors associated with family residential mobility across the domains of family instability, housing and neighborhood contexts, and family characteristics. Results revealed contributions of family instability and housing and neighborhood contexts to residential mobility, with a higher rate of residential moves associated with experiences of intimate partner violence, relationship transitions, and job transitions, as well as with living in private-market rentals, substandard housing, and disordered neighborhoods. However, owning a home and living in disadvantaged neighborhoods predicted a lower rate of residential moves.