Simplex Mixed‐Effects Models for Longitudinal Proportional Data

Abstract. Continuous proportional outcomes are collected from many practical studies, where responses are confined within the unit interval (0,1). Utilizing Barndorff‐Nielsen and Jørgensen's simplex distribution, we propose a new type of generalized linear mixed‐effects model for longitudinal proportional data, where the expected value of proportion is directly modelled through a logit function of fixed and random effects. We establish statistical inference along the lines of Breslow and Clayton's penalized quasi‐likelihood (PQL) and restricted maximum likelihood (REML) in the proposed model. We derive the PQL/REML using the high‐order multivariate Laplace approximation, which gives satisfactory estimation of the model parameters. The proposed model and inference are illustrated by simulation studies and a data example. The simulation studies conclude that the fourth order approximate PQL/REML performs satisfactorily. The data example shows that Aitchison's technique of the normal linear mixed model for logit‐transformed proportional outcomes is not robust against outliers.     

Exploring the Predictors of Organizational Preparedness for Natural Disasters

There is an extensive body of research on the determinants of disaster preparedness at the individual and household levels. The same cannot be said for the organizational level. Hence, the purpose of this study is to shed light on the predictors of organizational preparedness for natural disasters. Since leaders of organizations have an incentive to overstate their level of preparedness and because surveys of organizational leaders suffer from selection bias and low response rates, we take the novel approach of interviewing employees about the organizations that employ them. Using an online survey, we collected information from a national sample of 2,008 U.S. employees and estimated the predictors of preparedness at the organizational level. We find, among other results, that organization size (facility level) is a consistent predictor of preparedness at the organizational level. We conclude with policy recommendations and outline an agenda for future research on organizational preparedness for natural disasters.     

Politics and Growth

Theories of growth have made progress in understanding the mechanisms of growth in economic terms. However, there is less understanding of the political processes that enable or obstruct these mechanisms. This article provides a four‐stage framework to clarify and analyse the connections between politics and growth: (i) discussing the basic conditions essential for growth; (ii) suggesting that whether or not these conditions emerge depends on specific forms of public‐private interaction; (iii) linking these relationships to the incentives facing those in political power and investors; and (iv) considering the factors at country level that may help to push incentives in a pro‐growth direction.     

New Global Politics of Reproductive Labor: Gendered Labor and Marriage Migration

The feminization of international migration nowadays has demonstrated a new global politics of reproductive labor (work necessary for the reproduction of families). This paper reviews recent studies that manifest similarity, affinity, and continuity across multiple forms of reproductive labor carried out by migrant women in four aspects. First, the recruitment of women as foreign maids or foreign brides provides class‐specific parallel strategies to the global care crisis. Second, paid and unpaid forms of reproductive labor constitute intersecting circuits of labor and marriage migration through which women partake in continuous migration. Third, various categories of migrant women are discursively conflated and attached to similar images as sexualized others. Finally, global care chains not only involve migrant reproductive labor conducted at home but also operate on the level of social reproduction as indicated by the expansion of international nursing migration.     

Nonparametric adaptive likelihood weights

The weighted likelihood can be used to make inference about one population when data from similar populations are available. The author shows heuristically that the weighted likelihood can be seen as a special case of the entropy maximization principle. This leads him to propose the minimum averaged mean squared error (MAMSE) weights. He describes an algorithm for calculating these weights and shows its convergence using the Kuhn‐Tucker conditions. He explores the performance and properties of the weighted likelihood based on MAMSE weights through simulations.