This paper assesses inequality in longevity across education and gender groups in 23 OECD countries around 2011. Data on mortality rates by age, gender, educational attainment, and, for 17 countries, cause of death were collected from national sources, with similar treatment applied to all countries in order to derive comparable measures of longevity at age 25 and 65 by gender and education. These estimates show that, on average, the gap in life expectancy between high and low-educated people is 7.6 years for men and 4.8 years for women at age 25 years, and 3.6 years for men and 2.6 years for women at age 65. At the age of 25, the gap in life expectancy between high and low-educated people varies between 4.1 years (in Canada) and 13.9 years (in Hungary) for men, and between 2.5 years (in Italy) and 8.3 years (in Latvia) for women; in the United States, the gap is 10.0 years for men and 7.0 years for women. Cardiovascular diseases are the first cause of death for all gender and education groups after age 65 years, and the first cause of mortality inequality between the high and low-education elderly.

Advanced economies undergo three transitions during their development: (1) transition from a rural to an urban economy, (2) transition from low-income growth to high-income growth, (3) transition from high fertility and mortality rates to low modern levels. The timings of these transitions are correlated in the historical development of most advanced economies. I consider a nonlinear model of endogenous long-run economic and demographic change, in which child quantity-quality substitution is driven by declining child mortality. Because the model captures the interactions between all three transitions, it is able to explain three additional empirical patterns: a declining urban-rural wage gap, a declining rural-urban family size ratio, and most surprisingly, that early urbanization slows development. This third prediction distinguishes the model from other theories of long-run growth, and I document evidence for it in cross-country data.

In this study, we produce a valid and consistent variable for socioeconomic status (SES) at the household level with census microdata from ten developing countries available from the Integrated Public Use Microdata Series—International (IPUMS-I), the world's largest census database. We use principal components analysis to compute a wealth index based on asset ownership, utilities, and dwelling characteristics. We validate the index by verifying socioeconomic gradients on school enrollment and educational attainment. Given that the availability of socioeconomic indicators varies considerably across samples of census microdata, we implement a stepwise elimination procedure on the wealth index to identify the conditions that produce an internally consistent index. Using the results of the stepwise methodology, we propose which indicators are most important in measuring household SES. The development of the asset index for such a large archive of international census microdata is a very useful public resource for researchers.

The twentieth century has seen a phenomenal decline in mortality and an increase in productivity level. These two important events likely affect people's choices of schooling years and retirement age. We first show that in a standard life-cycle model, positive feedback exists between optimal schooling years and retirement age choices. We then evaluate the impact of a mortality or productivity shock on an endogenous variable (schooling years or retirement age) by decomposing it into the direct and indirect effects, where the indirect effect arises from feedback from the other endogenous variable. Finally, we extend the model by including the utility benefit of schooling and show that a negative correlation of schooling years and retirement age is possible. Apart from clarifying the apparently similar concepts of positive co-movement and positive feedback, our results have implications relevant to the economic demography literature.