Social vulnerability and migration in the wake of disaster: the case of Hurricanes Katrina and Rita

This study explores the relationship between place-based social vulnerability and post-disaster migration in the U.S. Gulf Coast region following Hurricanes Katrina and Rita. Using county-level data from the U.S. Census Bureau, we develop a regional index of social vulnerability and examine how its various dimensions are related to migration patterns in the wake of the storms. Our results show that places characterized by greater proportions of disadvantaged populations, housing damage, and, to a lesser degree, more densely built environments were significantly more likely to experience outmigration following the hurricanes. Our results also show that these relationships were not spatially random, but rather exhibited significant geographic clustering. We conclude with a discussion of the implications of these findings for future research and public policy.     

The Influence of Acculturation on Breastfeeding Initiation and Duration for Mexican-Americans

This paper uses data from the Fragile Families and Child Wellbeing Study to test the hypotheses that (1) similar to other positive pre- and post-natal outcomes, Mexican immigrant mothers are more likely to breastfeed, and to breastfeed longer, than white or Mexican-American mothers; and (2) acculturation accounts for the ethnic/nativity differential in breastfeeding initiation and duration. The results support both hypotheses. Mexican immigrants to the U.S. are much more likely than whites to breastfeed, and to breastfeed longer. Mexican-American mothers, after controlling for background characteristics, have similar initiation and duration to whites. Using expanded acculturation measures developed for this paper, acculturation accounts for some of the difference between whites and Mexican immigrants in breastfeeding initiation, and much of the difference for breastfeeding duration. The results suggest that low levels of acculturation operate to protect Mexican immigrants from choosing to formula-feed, which gives their babies many health advantages, and may be associated with better health outcomes across the life course. The results also suggest that successive generations of Mexican immigrants may abandon breastfeeding, which is deleterious for their infants.     

Ethnic Classification in Global Perspective: A Cross-National Survey of the 2000 Census Round

Academic interest in official systems of racial and ethnic classification has grown in recent years, but most research on such census categories has been limited to small case studies or regional surveys. In contrast, this article analyzes a uniquely global data set compiled by the United Nations Statistical Division to survey the approaches to ethnic enumeration taken in 141 countries. The motives for this analysis combine theoretical, applied, and policy objectives. I find that 63% of the national censuses studied incorporate some form of ethnic enumeration, but their question and answer formats vary along several dimensions that betray diverse conceptualizations of ethnicity (for example, as “race” or “nationality”). Moreover, these formats follow notably regional patterns. Nonetheless, the variety of approaches can be grouped into a basic taxonomy of ethnic classification approaches, suggesting greater commonality in worldwide manifestations of the ethnicity concept than some have recognized.

Providing Spatial Data for Secondary Analysis: Issues and Current Practices Relating to Confidentiality

Spatially explicit data pose a series of opportunities and challenges for all the actors involved in providing data for long-term preservation and secondary analysis—the data producer, the data archive, and the data user. We report on opportunities and challenges for each of the three players, and then turn to a summary of current thinking about how best to prepare, archive, disseminate, and make use of social science data that have spatially explicit identification. The core issue that runs through the paper is the risk of the disclosure of the identity of respondents. If we know where they live, where they work, or where they own property, it is possible to find out who they are. Those involved in collecting, archiving, and using data need to be aware of the risks of disclosure and become familiar with best practices to avoid disclosures that will be harmful to respondents.

M-quantile models with application to poverty mapping

Over the last decade there has been growing demand for estimates of population characteristics at small area level. Unfortunately, cost constraints in the design of sample surveys lead to small sample sizes within these areas and as a result direct estimation, using only the survey data, is inappropriate since it yields estimates with unacceptable levels of precision. Small area models are designed to tackle the small sample size problem. The most popular class of models for small area estimation is random effects models that include random area effects to account for between area variations. However, such models also depend on strong distributional assumptions, require a formal specification of the random part of the model and do not easily allow for outlier robust inference. An alternative approach to small area estimation that is based on the use of M-quantile models was recently proposed by Chambers and Tzavidis (Biometrika 93(2):255–268, 2006) and Tzavidis and Chambers (Robust prediction of small area means and distributions. Working paper, 2007). Unlike traditional random effects models, M-quantile models do not depend on strong distributional assumption and automatically provide outlier robust inference. In this paper we illustrate for the first time how M-quantile models can be practically employed for deriving small area estimates of poverty and inequality. The methodology we propose improves the traditional poverty mapping methods in the following ways: (a) it enables the estimation of the distribution function of the study variable within the small area of interest both under an M-quantile and a random effects model, (b) it provides analytical, instead of empirical, estimation of the mean squared error of the M-quantile small area mean estimates and (c) it employs a robust to outliers estimation method. The methodology is applied to data from the 2002 Living Standards Measurement Survey (LSMS) in Albania for estimating (a) district level estimates of the incidence of poverty in Albania, (b) district level inequality measures and (c) the distribution function of household per-capita consumption expenditure in each district. Small area estimates of poverty and inequality show that the poorest Albanian districts are in the mountainous regions (north and north east) with the wealthiest districts, which are also linked with high levels of inequality, in the coastal (south west) and southern part of country. We discuss the practical advantages of our methodology and note the consistency of our results with results from previous studies. We further demonstrate the usefulness of the M-quantile estimation framework through design-based simulations based on two realistic survey data sets containing small area information and show that the M-quantile approach may be preferable when the aim is to estimate the small area distribution function.     

A Bayesian approach for zero-modified Skellam model with Hamiltonian MCMC

Statistical Methods & Applications - In this paper is presented the zero-modified poisson difference and present possible applications of them in the analysis of paired count data. The...     

Recent Mortality Trend Reversal in Russia: Are Regions Following the Same Tempo?

After several decades of negative trends and short-term fluctuations, life expectancy has been increasing in Russia since 2004. Between 2003 and 2014, the length of life rose by 6.6 years among males and by 4.6 years among females. While positive trends in life expectancy are observed in all regions of Russia, these trends are unfolding differently in different regions. First, regions entered the phase of life expectancy growth at different points in time. Second, the age- and cause-specific components of the gains in life expectancy and the number of years added vary noticeably. In this paper, we apply decomposition techniques—specifically, the stepwise replacement algorithm—to examine the age- and cause-specific components of the changes in inter-regional disparities during the current period of health improvement. The absolute inter-regional disparities in length of life, measured by the population-weighted standard deviation, decreased slightly between 2003 and 2014, from 3.3 to 3.2 years for males, and from 2.0 to 1.8 years for females. The decomposition of these small changes by ages and causes of death shows that these shifts were the result of diverse effects of mortality convergence at young and middle ages, and of mortality divergence at older ages. With respect to causes of death, the convergence is mainly attributable to external causes, while the inter-regional divergence of trends is largely determined by cardiovascular diseases. The two major cities, Moscow and Saint Petersburg, are currently pioneering mortality improvements in Russia and are making the largest contributions to the inter-regional divergence.     

What’s in a Name? The Negative Implications of Gender Neutrality in the Intimate Partner Violence Prevention and Intervention Literature

Research and interventions for intimate partner violence in current use largely consist of practices aimed at getting victims to leave their abusers, rather than helping perpetrators stop their violence. In the context of parenthood, the focus on programs targeting women experiencing violence has resulted in an emphasis on mothers’ responsibility for mitigating the adverse effects of witnessing violence on children. This has led to insufficient understanding of violent men’s identities as fathers. This narrative review employed content analysis to analyze the discursive constructions of men and women as parents in a selection of peer reviewed articles about the prevention of intimate partner violence during childbearing years that were published between January 2000 and January 2015 (N = 37). A quantitative word count was conducted in order to determine the frequency with which these articles referred to men and women in their parental roles when employing prevention and intervention strategies. Women were consistently identified as mothers in all areas of the literature, while the prevalence of men’s identities as fathers was confined only to the specific, specialized area of the literature that is aimed at men alone. The implications of these findings for future research and practice in the area of prevention and intervention of intimate partner violence specifically in the context of parenthood are discussed.     

Modeling Local BES Indicators by Copula-Based Bayesian Networks

In Italy, the measure of the Equitable and Sustainable Well-being is provided by the Italian Institute of Statistics by means of a dashboard of basic and composite indicators. To investigate the dependence structure between the different domains of well-being, we propose the use of Non-Parametric Bayesian Networks based on the normal copula distribution, that allow to explore the conditional independence relationships between the composite indicators. The main advantage of the non-parametric models is that, as opposed to the parametric approach, they do not require any assumption on the marginal distributions of the variables. The proposed model is applied to the Equitable and Sustainable Well-being indicators measured at the provincial level and enriches the analysis of well-being by inspecting similarities and differences between Italian urban areas and territories.