Gender and poverty : a life cycle approach to the analysis of the differences in gender outcomes

The authors study complex interactions between gender and poverty in postwar Bosnia and Herzegovina. The goal of their analysis is to uncover how a spectrum of gender differentials at different parts of the life cycle varies across income groups. Using the data from the 2001 Bosniaand Herzegovina Living Standards Measurement Study, the authors find strong gender-poverty interaction in the patterns of labor force participation, gender gap in earnings, individuals'school finances, and school attendance. The main source of gender inequality seems to come from differences in investments in girls'and boys'educations that increase with declines in income levels. Short-term income shocks could lead to long-term increases in gender inequality in households with school age children, unless there is ready access to credit markets. The authors also find that the magnitude of the impact of economic development on gender differences in Bosnia will depend on where the growth is concentrated. If the poor capture at least some benefits of economic growth, the gender differences in household investment in human capital of their children will decline. If, on the other hand, growth is concentrated among the richest, then important gender disparities could remain pervasive.Health Monitoring&Evaluation,Economic Theory&Research,Environmental Economics&Policies,Labor Policies,Public Health Promotion,Health Monitoring&Evaluation,Inequality,Housing&Human Habitats,Economic Theory&Research,Environmental Economics&Policies

Estimating the Effects of Covariates on Health Expenditures

This paper addresses estimation of an outcome characterized by mass at zero, significant skewness, and heteroscedasticity. Unlike other approaches suggested recently that require retransformations or arbitrary assumptions about error distributions, our estimation strategy uses sequences of conditional probability functions, similar to those used in discrete time hazard rate analyses, to construct a discrete approximation to the density function of the outcome of interest conditional on exogenous explanatory variables. Once the conditional density function has been constructed, we can examine expectations of arbitrary functions of the outcome of interest and evaluate how these expectations vary with observed exogenous covariates. This removes a researcher's reliance on strong and often untested maintained assumptions. We demonstrate the features and precision of the conditional density estimation method through Monte Carlo experiments and an application to health expenditures using the RAND Health Insurance Experiment data. Overall, we find that the approximate conditional density estimator that we propose provides accurate and precise estimates of derivatives of expected outcomes for a wide range of types of explanatory variables. We find that two-part smearing models often used by health economists do not perform well. Our results, both in Monte Carlo experiments and in our real application, also indicate that simple one-part OLS models of level health expenditures can provide more accurate estimates than commonly used two-part models with smearing, provided one uses enough expansion terms in the one-part model to fit the data well.

Problems of Sample-selection Bias in the Historical Heights Literature: A Theoretical and Econometric Analysis

An extensive literature uses anthropometric measures, typically heights, to draw inferences about living standards in the past. This literature's influence reaches beyond economic history; the results of historical heights research appear as crucial components in development economics and related fields. The historical heights literature often relies on micro-samples drawn from sub-populations that are themselves selected: examples include volunteer soldiers, prisoners, and runaway slaves, among others. Contributors to the heights literature sometimes acknowledge that their samples might not be random draws from the population cohorts in question, but rely on normality alone to correct for potential selection into the sample. We use a simple Roy model to show that selection cannot be resolved simply by augmenting truncated samples for left-tail shortfall. Statistical tests for departures from normality cannot detect selection in Monte Carlo exercises for small to moderate levels of self-selection, obviating a standard test for selection in the heights literature. We show strong evidence of selection using micro-data on the heights of British soldiers in the late eighteen and nineteenth centuries. Consequently, widely accepted results in the literature may not reflect variations in living standards during a soldier's formative years; observed heights could be predominantly determined by the process determining selection into the sample. A survey of the current historical heights literature illustrates the problem for the three most common sources: military personnel, slaves, and prisoners

The Long-Term Effects of Youth Unemployment

Using National Longitudinal Survey of Youth data on young men, we estimate the long-term effects of youth unemployment on later labor market outcomes. A spell of involuntary unemployment can lead to sub-optimal investments in human capital among young people in the short run. A theoretical model of dynamic human capital investment predicts a rational “catch-up” response to such a spell. Using semiparametric techniques to control for the endogeneity of prior behaviors, our estimates provide strong evidence of this response. We also find evidence of persistence in unemployment. Despite the catch-up response, however, we find the negative effect of prior unemployment on earnings to be large, to be persistent and to taper off slowly over time. The theoretical model predicts each of these three effects. Combining our semiparametric estimates with a dynamic approximation to the lifecycle, we find that unemployment experienced as long ago as ten years continues to affect earnings adversely

Bony ingrowth potential of 3D-printed porous titanium alloy: a direct comparison of interbody cage materials in an in vivo ovine lumbar fusion model.

Background contextThere is significant variability in the materials commonly used for interbody cages in spine surgery. It is theorized that three-dimensional (3D)-printed interbody cages using porous titanium material can provide more consistent bone ingrowth and biological fixation.PurposeThe purpose of this study was to provide an evidence-based approach to decision-making regarding interbody materials for spinal fusion.Study designA comparative animal study was performed.MethodsA skeletally mature ovine lumbar fusion model was used for this study. Interbody fusions were performed at L2-L3 and L4-L5 in 27 mature sheep using three different interbody cages (ie, polyetheretherketone [PEEK], plasma sprayed porous titanium-coated PEEK [PSP], and 3D-printed porous titanium alloy cage [PTA]). Non-destructive kinematic testing was performed in the three primary directions of motion. The specimens were then analyzed using micro-computed tomography (µ-CT); quantitative measures of the bony fusion were performed. Histomorphometric analyses were also performed in the sagittal plane through the interbody device. Outcome parameters were compared between cage designs and time points.ResultsFlexion-extension range of motion (ROM) was statistically reduced for the PTA group compared with the PEEK cages at 16 weeks (p-value=.02). Only the PTA cages demonstrated a statistically significant decrease in ROM and increase in stiffness across all three loading directions between the 8-week and 16-week sacrifice time points (p-value≤.01). Micro-CT data demonstrated significantly greater total bone volume within the graft window for the PTA cages at both 8 weeks and 16 weeks compared with the PEEK cages (p-value<.01).ConclusionsA direct comparison of interbody implants demonstrates significant and measurable differences in biomechanical, µ-CT, and histologic performance in an ovine model. The 3D-printed porous titanium interbody cage resulted in statistically significant reductions in ROM, increases in the bone ingrowth profile, as well as average construct stiffness compared with PEEK and PSP

Disaster Operations Management: an Empirical Study from Thailand

Disasters have unpredictable and deleterious impacts on modern societies. While recent operations management research has increasingly focused on disaster operations, only a few studies have examined the recovery phase of post-disaster operations. This research presents an overview of Disaster Operations Management as well as an empirical study using econometrics analysis to examine the recovery phase of post-disaster operations. The results suggest that when resources are scarce, at a strategic level we need to understand where to begin when planning the recovery process. This study is an exploratory analysis of the question of how flooding affects per capita income in areas with different levels of industrialization. We developed multiple regression models using panel data from Thailand to examine this effect, finding that flooding in a previous year has a positive effect on areas with a low level of industrialization, but a negative one on highly industrialized areas, meaning the residents of the latter are affected differently. Our results suggest the level of industrialization impacts the effectiveness of the recovery process. Finally, we discuss the implications of the study as well as suggestions for future research