Spillover effects of retirement: Does health vulnerability matter?

The current literature investigating the impact of retirement and the associated spousal spillover effects overlooks the unintended effects of retirement on spouses in vulnerable health, namely spouses with long-term health conditions (LTHCs). In this paper, we fill this gap in the literature and investigate the impact of an individual's retirement on their partner's health outcomes when their partner has LTHCs. Given the inherent identification challenges associated with entry into retirement, we use the pension-qualifying age in Australia as an instrument. Based on data from the Household Income and Labour Dynamics in Australia survey, we find that the husband's retirement has a positive impact on the wife's quality-adjusted life years (QALY) and other physical and mental health outcomes. We also identify redistribution of domestic workload as a key transmission mechanism of the spousal spillover effects. Women with LTHCs will see their QALY and health improve only if their husband devotes more time to domestic tasks after retirement.

On absolute socioeconomic health inequality comparisons.

This paper introduces a new graphical tool: the mean deviation concentration curve. Using a unified approach, we derive the associated dominance conditions that identify robust rankings of absolute socioeconomic health inequality for all indices obeying Bleichrodt and van Doorslaer's (J Health Econ 25:945-957, 2006) principle of income-related health transfer. We also derive dominance conditions that are compatible with other transfer principles available in the literature. To make the identification of all robust orderings implementable using survey data, we discuss statistical inference for these dominance tests. To illustrate the empirical relevance of the proposed approach, we compare joint distributions of income and health-related behavior in the United States.

A Pragmatic Method for Identification of Long-Stay Patients in the PICU.

OBJECTIVES: To develop a pragmatic method of identifying long-stay patients (LSPs) in the PICU. METHODS: We surveyed 40 expert stakeholders in 14 Canadian PICUs between February 2015 and March 2015 to identify key factors to use for defining LSPs in the PICU. We then describe a pragmatic method using these factors to analyze 523 admissions to an academic, tertiary-care PICU from February 1, 2015, to January 31, 2016. RESULTS: The overall response rate was 70% (28 of 40). Of respondents, 75% (21of 28) stated that it was important to define LSPs and identified present and future resource consumption (18 of 21 [86%] and 16 of 21 [76%], respectively) as the key reasons for defining LSPs. Respondents valued a definition that was consistent and ranked a percentile cutoff as the preferred analytic method for defining LSPs. Of respondents, 86% (24 of 28) though the LSP definition should include factors other than length of stay. We developed a surrogate marker for LSPs using mechanical ventilation and presence of a central venous catheter in our sample population to compare to varying percentile cutoffs. We identified 108 patients at the 80th percentile as LSPs who used 67% of total bed days and had a median length of stay of 11.3 days. CONCLUSIONS: We present a pragmatic method for the retrospective identification of LSPs in the PICU that incorporates unit- and/or patient-specific characteristics. The next steps would be to validate this method using other patient and/or unit characteristics in different PICUs and over time.

A framework for testing the equality between the health concentration curve and the 45-degree line.

The health concentration curve is the standard graphical tool to depict socioeconomic health inequality in the literature on health inequality. This paper shows that testing for the absence of socioeconomic health inequality is equivalent to testing if the conditional expectation of health on income is a constant function that is equal to average health status. In consequence, any test for parametric specification of a regression function can be used to test for the absence of socioeconomic health inequality (subject to regularity conditions). Furthermore, this paper illustrates how to test for this equality using a test for parametric regression functional form and applies it to health-related behaviors from the National Health Survey 2014.

Income-related health transfers principles and orderings of joint distributions of income and health.

The objective of this article is to provide the analyst with the necessary tools that allow for a robust ordering of joint distributions of health and income. We contribute to the literature on the measurement and inference of socioeconomic health inequality in three distinct but complementary ways. First, we provide a formalization of the socioeconomic health inequality-specific ethical principle introduced by Erreygers et al. (2012) . Second, we propose new graphical tools and dominance tests for the identification of robust orderings of joint distributions of income and health associated with this new ethical principle. Finally, based on both pro-poor and pro-extreme ranks ethical principles we address a very important aspect of dominance literature: the inference. To illustrate the empirical relevance of the proposed approach, we compare joint distributions of income and a health-related behavior in the United States in 1997 and 2014.

Robust rankings of socioeconomic health inequality using a categorical variable.

When assessing socioeconomic health inequalities, researchers often draw upon measures of income inequality that were developed for ratio scale variables. As a result, the use of categorical data (such as self-reported health status) produces rankings that may be arbitrary and contingent to the numerical scale adopted. In this paper, we develop a method that overcomes this issue by providing conditions for which these rankings are invariant to the numerical scale chosen by the researcher. In doing so, we draw on the insight provided by Allison and Foster (2004) and extend their method to the dimension of socioeconomic inequality by exploiting the properties of rank-dependent indices such as Wagstaff (2002) achievement and extended concentration indices. We also provide an empirical illustration using the National Institute of Health Survey 2012.

Avoiding blindness to health status in health achievement and health inequality measurement.

The concentration index, being focused on the socioeconomic dimension of health inequality and overlooking aversion to pure health inequality, can produce ethically contestable rankings of health distributions. A health transfer from a sicker but richer individual to healthier but poorer individual will decrease the concentration index. This paper presents a new class of health inequality indices that avoid this limitation by trading off socioeconomic-related health inequality against pure health inequality.

Peer effects, fast food consumption and adolescent weight gain.

This paper aims at opening the black box of peer effects in adolescent weight gain. Using Add Health data on secondary schools in the U.S., we investigate whether these effects partly flow through the eating habits channel. Adolescents are assumed to interact through a friendship social network. We propose a two-equation model. The first equation provides a social interaction model of fast food consumption. To estimate this equation we use a quasi maximum likelihood approach that allows us to control for common environment at the network level and to solve the simultaneity (reflection) problem. Our second equation is a panel dynamic weight production function relating an individual's Body Mass Index z-score (zBMI) to his fast food consumption and his lagged zBMI, and allowing for irregular intervals in the data. Results show that there are positive but small peer effects in fast food consumption among adolescents belonging to a same friendship school network. Based on our preferred specification, the estimated social multiplier is 1.15. Our results also suggest that, in the long run, an extra day of weekly fast food restaurant visits increases zBMI by 4.45% when ignoring peer effects and by 5.11%, when they are taken into account.

Measuring socioeconomic health inequalities in presence of multiple categorical information.

While many of the measurement approaches in health inequality measurement assume the existence of a ratio-scale variable, most of the health information available in population surveys is given in the form of categorical variables. Therefore, the well-known inequality indices may not always be readily applicable to measure health inequality as it may result in the arbitrariness of the health concentration index's value. In this paper, we address this problem by changing the dimension in which the categorical information is used. We therefore exploit the multi-dimensionality of this information, define a new ratio-scale health status variable and develop positional stochastic dominance conditions that can be implemented in a context of categorical variables. We also propose a parametric class of population health and socioeconomic health inequality indices. Finally we provide a twofold empirical illustration using the Joint Canada/United States Surveys of Health 2004 and the National Health Interview Survey 2010.