COVID Health Structure Index: The Vulnerability of Brazilian Microregions

Social Indicators Research - Many developing countries have highly unequal health systems across their regions. The pandemic of COVID-19 brought an additional challenge, as hospital structures...     

Density regression using repulsive distributions

Flexible regression is a traditional motivation for the development of non-parametric Bayesian models. A popular approach for this involves a joint model for responses and covariates, from which the desired result arises by conditioning on the covariates. Many such models involve the convolution of a continuous kernel with some discrete random probability measure defined as an infinite mixture of i.i.d. atoms. Following this strategy, we propose a flexible model that involves the concept of repulsion between atoms. We show that this results in a more parsimonious representation of the regression than the i.i.d. counterpart. The key aspect is that repulsion discourages mixture components that are near each other, thus favouring parsimony. We show that the conditional model retains the repulsive features, thus facilitating interpretation of the resulting flexible regression, and with little or no sacrifice of model fit compared to the infinite mixture case. We show the utility of the methodology by way of a small simulation study and an application to a well-known data set.     

SHOULD I STAY OR SHOULD I GO? CAREER CHOICES FOR YOUNG WORKERS IN LATIN AMERICA

This paper presents the first estimates of the returns to formal labor market experience and tenure in a developing country context. We take advantage of rich matched employer–employee data from Brazil and Chile, exploiting job displacement as a source of identification. We find positive returns to both dimensions in these countries, with larger returns to tenure in Brazil and larger returns to experience in Chile. Our findings suggest the more rigid Brazilian labor legislation may encourage firms to invest in young workers' specific skills. Chile's institutions, on the contrary, might promote the acquisition of general skills. (JEL J24, J31, M50)     

Nonparametric Bayesian inference in applications

Nonparametric Bayesian (BNP) inference is concerned with inference for infinite dimensional parameters, including unknown distributions, families of distributions, random mean functions and more. Better computational resources and increased use of massive automated or semi-automated data collection makes BNP models more and more common. We briefly review some of the main classes of models, with an emphasis on how they arise from applied research questions, and focus in more depth only on BNP models for spatial inference as a good example of a class of inference problems where BNP models can successfully address limitations of parametric inference.     

Spatial Disaggregation of Social Indicators: An Info-Metrics Approach

In this paper we propose a methodology to obtain social indicators at a detailed spatial scale by combining the information contained in census and sample surveys. Similarly to previous proposals, the method proposed here estimates a model at the sample level to later project it to the census scale. The main novelties of the technique presented are that (i) the small-scale mapping produced is perfectly consistent with the aggregates -regional or national- observed in the sample, and (ii) it does not require imposing strong distributional assumptions. The methodology suggested here follows the basics presented on Golan (2018) by adapting a cross-moment constrained Generalized Maximum Entropy (GME) estimator to the spatial disaggregation problem. This procedure is compared with the equivalent methodology of Tarozzi and Deaton (2009) by means of numerical experiments, providing a comparatively better performance. Additionally, the practical implementation of the methodology proposed is illustrated by estimating poverty rates for small areas for the region of Andalusia (Spain).

     

Subjectivity in debate: Some reconstructed philosophical premises to advance its discussion in psychology

The topic of subjectivity has been treated peripherally by philosophy. It has appeared in philosophy not as a specific human phenomenon, but attached to other concepts without specifying its ontological definition, such as intersubjectivity, the place of the Other in the emergence of the self, consciousness and so forth. This paper reconstructs some of the overlooked moments and ideas of several classical philosophers, such as Marx, Dewey, Merleau Ponty, Cassirer and Foucault, in order to identify in their works important antecedents to advance a different concept of subjectivity. The concepts and questions which are raised by those philosophers and which are revived in this paper have remained overlooked both by philosophy and psychology because of the lack of any representation of subjectivity capable of making them more visible. The ontological monopoly of language and discourse in explaining all human phenomena, taken together with the critique of theoretical systems and of epistemology, has found in social constructionism its strongest expression in psychology. The value of theoretical systems in generating intelligibility about complex and configurational phenomena is recovered, along with the need to develop new epistemologies capable of generating intelligibility on such systems. Finally, I argue that a new theoretical and epistemological avenue is opened up for the development of psychological thought.     

Comparative analysis of aging policy reforms in Argentina,Chile, Costa Rica,and Mexico

This investigation uses case studies and comparative analysis to review and analyze aging policy in Argentina, Chile, Costa Rica, and Mexico and uncovers similarities and relevant trends in the substance of historical and current aging policy across countries. Initial charity-based approaches to poverty and illness have been gradually replaced by a rights-based approach considering broader notions of well-being, and recent reforms emphasize the need for national, intersectoral, evidence-based policy. The results of this study have implications for understanding aging policy in Latin America from a welfare regime and policy makers’ perspective, identifying priorities for intervention and informing policy reforms in developing countries worldwide.     

Peer Effects and Peer Avoidance: The Diffusion of Behavior in Coevolving Networks

We study the long‐run emergence of behavioral patterns in dynamic complex networks. Individuals can display two kinds of behavior: G (“good”) or B (“bad”). We assume that the exposure of a G agent to bad behavior on the part of peers/neighbors triggers her own switch to B behavior, but only temporarily. We model the implications of such peer effects as an epidemic process in the standard SIS (Susceptible‐Infected‐Susceptible) framework. The key novelty of our model is that, unlike in the received literature, the network is taken to change over time within the same time scale as behavior. Specifically, we posit that links connecting two G agents last longer, reflecting the idea that B agents tend to be avoided. The main concern of the paper is to understand the extent to which such biased network turnover may play a significant role in supporting G behavior in a social system. And indeed we find that network coevolution has nontrivial and interesting effects on long‐run behavior. This yields fresh insights on the role of (endogenous) peer pressure on the diffusion of social behavior and also has some bearing on the traditional study of disease epidemics. (JEL: C71, D83, D85)     

Does Education Affect Happiness? Evidence for Spain

In this paper we study the impact of education on happiness in Spain using individual-level data from the European Social Survey, by means of estimating Ordinal Logit Models. We find both direct and indirect effects of education on happiness. First, we find an indirect effect of education on happiness through income and labour status. That is, we find that people with a higher education level have higher income levels and a higher probability of being employed, and thus, report higher levels of happiness. Second, and after controlling by income, labour status and other socio-economic variables, we find that education has a positive (and direct) impact on happiness. We interpret this result as evidence of a ??self-confidence?? or ??self-estimation?? effect from acquiring knowledge. Finally, we find that the direct impact of education on happiness does not depend of the level of education (primary, secondary or tertiary).