There is increasing evidence supporting the existence of a link between income inequalities and health outcomes. The main purpose of this article is to test whether economic inequalities are associated with poor population health in Latin American countries. Multi-country data from 1970 to 2012 were used to assess this question. The results show that the Gini coefficient has a strong correlation with health outcomes. Moreover, multiple linear regression analysis using fixed effects shows that after controlling for gross national income per capita, literacy rate, and health expenditure, the Gini coefficient is independently negatively associated with health outcomes. In Latin American countries, for every percentage point increase in the Gini coefficient, the infant mortality rate grows by 0.467 deaths per 1,000 live births, holding all other variables constant. Additionally, an ordinary least squares estimation model suggests that countries that do not use International Monetary Fund loans perform better on health outcomes. These findings should alert policymakers, elected officials, and the public of the need to fight income inequalities and rethink the role of international financial institutions that dictate state policies.

Latin American countries saw an important expansion in social policy in the first two decades of the 21st century. Along with this increased inclusion, however, social policy remains segmented. Using recent data from ECLAC, World Bank, and other sources, this paper offers a comprehensive analysis of trends in social policy for the period 2000–2020 for 17 countries in Latin America. Four areas of social policy are assessed in longitudinal and comparative perspectives: transfers, health care, education, and family policies. Conditional cash transfers (CCT) and noncontributory pensions (NCP) are the two main policy innovations that allowed countries in the region to expand social rights to previously excluded populations (outsiders). At the same time, due to their design, these policies have introduced new layers of fragmentation to the welfare mix, without resolving—or even increasing—segmentation in social policy. Segmentation is still the rule for the areas of health care and education, and increasing privatisation went unabated even in the periods of social policy expansion and in the countries governed by left coalitions.

Based on data from Argentina’s Permanent Household Survey, the method of analysis used in this study permits the rate of precarious work in Argentina in 2017 and its trend in 2003–2017 to be determined more accurately than before. The figure in 2017 was 47 percent, and women, younger people, the less educated, and the foreign-born were more likely to have precarious jobs. A separate analysis of the categories that constitute precarious work provides unique insight on the interrelation among employment relations, economic growth, and labor-capital conflict. Lastly, the findings provide support for the existence of a range of productivity levels across firms instead of a sharp distinction between formal and informal sectors of the economy and a continuous inverse relationship with precarious employment. En base a datos de la Encuesta Permanente de Hogares de Argentina, el método de análisis utilizado en este estudio permite determinar la tasa de trabajo precario en Argentina en 2017 y su tendencia en 2003–2017 con mayor precisión que antes. La cifra en 2017 fue del 47 por ciento, y las mujeres, los jóvenes, los menos educados y los nacidos en el extranjero tenían más probabilidades de tener trabajos precarios. Un análisis separado de las categorías que constituyen el trabajo precario proporciona una visión única de la interrelación entre las relaciones laborales, el crecimiento económico y el conflicto laboral-capital. Por último, los hallazgos respaldan la existencia de una gama de niveles de productividad de las empresas del mismo sector en lugar de una distinción clara entre los sectores formales e informales de la economía y una relación inversa continua con el empleo precario.