Foreign-born emigration: A new approach and estimates based on matched CPS files

The utility of postcensal population estimates depends on the adequate measurement of four major components of demographic change: fertility, mortality, immigration, and emigration. Of the four components, emigration, especially of the foreign-born, has proved the most difficult to gauge. Without "direct" methods (i.e., methods identifying who emigrates and when), demographers have relied on indirect approaches, such as residual methods. Residual estimates, however are sensitive to inaccuracies in their constituent parts and are particularly ill-suited for measuring the emigration of recent arrivals. Here we introduce a new method for estimating foreign-born emigration that takes advantage of the sample design of the Current Population Survey (CPS): repeated interviews of persons in the same housing units over a period of 16 months. Individuals appearing in a first March Supplement to the CPS but not the next include those who died in the intervening year, those who moved within the country, and those who emigrated. We use statistical methods to estimate the proportion of emigrants among those not present in the follow-up interview. Our method produces emigration estimates that are comparable to those from residual methods in the case of longer-term residents (immigrants who arrived more than 10 years ago), but yields higher--and what appear to be more accurate--estimates for recent arrivals. Although somewhat constrained by sample size, we also generate estimates by age, sex, region of birth, and duration of residence in the United States.     

Reinvigorating the social contract and strengthening social cohesion: Social protection responses to COVID-19

The COVID-19 pandemic has exposed the vulnerability of those who are inadequately covered by social protection in more and less developed countries alike, and has exacerbated the fragility of a social contract that was already under strain in many countries. A weak social contract in the context of an exceptional crisis poses a very real risk to social cohesion. Nevertheless, many States have reasserted themselves as the guarantor of rights by protecting public health and incomes. By sustaining these measures, economic recovery will be supported which will help minimize risks that may weaken social cohesion. However, this is a fast-moving, inherently unstable and protracted crisis. Social protection stands at a critical juncture. Decisive policy action will be required to strengthen social protection systems, including floors, as one of the cornerstones of a reinvigorated social contract.     

Evaluating social investment in disability policy

Disability policy in European countries is displaying a shift towards social investment: increasing human capital and access to the labour market. The reasoning that underlies this transition is that disabled persons would benefit from mainstream employment, but are impeded in traditional policy by deficiencies in labour supply and demand. However, the shift towards more activating policies in many countries is accompanied by a decline in social protection. It is unclear whether social investment may effectively promote the employment chances of disabled persons within this context. The present research examines this question through a quantitative, cross-sectional, multilevel analysis on microdata from 22 EU countries. Our findings suggest greater activation to predict lower employment chances, while reducing passive support shows mixed effects. Conversely, measures for facilitation in daily life predict greater employment chances, as do measures for sheltered work. These findings raise questions over the value of social investment for disabled persons—and underline the need to overcome broader barriers in the labour market and in society.     

Preregistration in infant research—A primer

Preregistration, the act of specifying a research plan in advance, is becoming more common in scientific research. Infant researchers contend with unique problems that might make preregistration particularly challenging. Infants are a hard‐to‐reach population, usually yielding small sample sizes, they can only complete a limited number of trials, and they can be excluded based on hard‐to‐predict complications (e.g., parental interference, fussiness). In addition, as effects themselves potentially change with age and population, it is hard to calculate an a priori effect size. At the same time, these very factors make preregistration in infant studies a valuable tool. A priori examination of the planned study, including the hypotheses, sample size, and resulting statistical power, increases the credibility of single studies and adds value to the field. Preregistration might also improve explicit decision making to create better studies. We present an in‐depth discussion of the issues uniquely relevant to infant researchers, and ways to contend with them in preregistration and study planning. We provide recommendations to researchers interested in following current best practices.     

Semiparametric sieve maximum likelihood estimation under cure model with partly interval censored and left truncated data for application to spontaneous abortion

Lifetime Data Analysis - This work was motivated by observational studies in pregnancy with spontaneous abortion (SAB) as outcome. Clearly some women experience the SAB event but the rest do not....     

Demographic differences in response rates for PHQ9 in a university student population

Objective: To examine differences in complete response rates for depression screening questions based on demographic characteristics. Methods: Cross-sectional study examining associations between demographic characteristics and completely responding depression-screening questions. Participants: “Healthy Minds Study” data, collected in a public University in February 2016, where 7,326 students participated. Results: women (AOR: 0.69; 95% CI =0.57–0.83) and gay/lesbian students (AOR: 0.24; 95% CI =0.10–0.60) had better complete response rates. Non-US (AOR: 1.46; 95% CI =1.03–2.07), black (AOR: 3.32; 95% CI =1.92–5.77), and Middle-Eastern students (AOR: 3.73; 95% CI =1.73–8.02) had lower complete response rates. Conclusions: Our study shows sex, gender, citizenship, and race categories have significant differences in complete response rates for the outcome. Our findings have several implications; including recognizing interventions for depression based on responders may not target those that tend to be “partial-responders”. Efforts in survey design, recruiting and completion of surveys should be maximized.     

If all you have is a hammer,everything looks like a nail: Operationalization matters

Operationalization has been the focus of less research than many other methodological topics. In this article, we argue that considering operational decisions is particularly critical for those who study stratification, because measures of inequality often involve multiple layers of operationalization: researchers first decide how to assign individuals to social groups (e.g., race), which are then themselves used to construct measures of group‐level differences and inequality (e.g., racial segregation). We provide examples of this by drawing on contemporary debates about how to operationalize social groups based on class, race, gender, and religion. Then we discuss three examples (religion, racial segregation, and family type) of second layer operationalization decisions, focusing on the consequences of operational decisions for research findings. We conclude by discussing the broader implications of operational decisions, focusing particularly on issues of power and applications for policy makers.