Income inequality and obesity are both widespread socioeconomic issues, particularly salient in middle-income countries. This article seeks to detect the relationship between local income inequality and excess weight in Mexico, using robust municipal income inequality measures generated through small area estimation method and instrumental variable multilevel estimations. Our results emphasize a negative impact of municipal income inequality on individual bodyweight, especially for women. We also explore the potential channels through which income inequality may decrease bodyweight. Three-stage least squares estimations highlight that the social capital pathway, the public policy pathway and the psychological pathway help to explain the negative effect of inequality on excess weight.Our results are fairly robust to alternative inequality measures and nutritional indicators.

SUMMARY This comparative study examines the relationship between excess weight and hourly wages in the unprecedented context of middle‐income countries. We compare three countries that are at different stages of the nutrition transition: India (at an early stage), China (at an intermediate stage) and Mexico (at an advanced stage). To do so, we use three distinct household surveys and combine different estimation procedures. Our results emphasise a wage penalty of underweight together with a wage reward of excess weight in India, pointing towards the persistence of pro‐fat social norms in a country where hunger is still highly prevalent. Conversely, we observe significant overweight and obesity wage penalties in China, especially in non‐manual jobs, probably due to a large diffusion of anti‐fat social norms in a country where hunger is residual and normal weight predominant. In Mexico, we find an overweight wage premium in manual jobs and no effect in non‐manual jobs. We speculate that the large‐scale diffusion of excess weight may lead to its greater social acceptance (i.e. ‘new’ pro‐fat norms). Finally, we explore the potential transmission channels through which bodyweight may affect wages. We provide evidence of potential anti‐fat discrimination in China and pro‐fat‐discrimination in India and Mexico. Our results have important implications in terms of public health policy.

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This study analyzes whether individual skills and personality traits facilitate labor market mobility of disadvantaged groups and rural migrants. We use a panel dataset of individuals in rural South India to explore the relationship between individual cognitive skills, personality traits, and income mobility. We take advantage of intragroup heterogeneity in terms of cognitive skills and personality traits to examine whether these personal characteristics enable individuals to overcome rigid social structures, exploring the role of these skills and traits in migrants’ income mobility. We show that despite strong rigidity in the area’s labor market structure, personality traits are important determinants of labor mobility, enabling individuals to overcome caste and gender discrimination, but that these personality traits do not contribute to increases in migrants’ income mobility.

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À partir de données longitudinales sur la population indienne, nous estimons la façon dont l’accroissement des discriminations envers les femmes affecte leur santé nutritionnelle. Tandis que certaines formes de discriminations en Inde se sont détériorées sur la période étudiée, nous observons systématiquement des effets non linéaires de ces changements sur l’état nutritionnel des femmes, suggérant la concomitance de différents mécanismes ayant des conséquences nutritionnelles diamétralement opposées (prise de poids versus perte de poids). Classification JEL : I14, J16

Finite Mixture Models (FMM) Applied to the Segmentation of the Bogota Labor Market. The purpose of this article is to demonstrate that the semi-parametric approach with Finite Mixture Models (FMM) is a real alternative to clustering procedures to explain social phenomena. We present the general framework of FMM before detailing the three stages of Finite Mixture Regression Models (FMRM). An empirical application of this new method is used to analyze the segmentation between formal and informal economy on the labor market in Bogota.