This paper analyses employment transitions and workers’ skills in Brazil using a random sample from the universe of formal labour contracts covering the period from 2003 to 2018. We develop a novel procedure to derive a measure of occupational distance and internationally comparable skill measures from occupations’ task descriptions in the country under analysis based on machine learning and natural language processing methods, but without usual ad hoc classifications. Our findings confirm that workers who use non-routine cognitive skills intensively experience the highest employment growth rates and wages. Their labour market exit risk is relatively low, occupational and sectoral changes are least common and, in the case of occupational switching, non-routine cognitive workers tend to find occupations that are higher-paid and closer in terms of their task content. Against the same characteristics, routine and non-routine manual workers are worse off in the labour market. Overall, there have been signs of routine-biased technological change and employment polarization since the 2014 Brazilian economic crisis.
PurposeThis article aims to measure inequality of income and opportunities at the national and state levels in Brazil, highlighting their acceptable and unacceptable components.Design/methodology/approachTo this end, a lower-bound estimate of income inequality (MLD) and inequality of opportunity (IOp) was developed using data from the National Household Sample Survey between 2001 and 2014.FindingsIt shows that the disparity of income measured by the MLD decreased 26.7 percent, while IOp measured by the IOp decreased 25.6 percent during that period. The decline in total inequality can be attributed to a 48.5 percent decrease of its unfair component and 51.5 percent decrease of its fair component. The average income of the most disadvantaged group (non-white women working in the informal sector) is shown to be only 29.5 percent of the income of the most advantaged group (formally employed white men). The groups at the greatest disadvantage were most benefited by the increase in income.Originality/valueBeyond comparisons among countries, analysis at the subnational level make it possible to identify how the process that generates inequality acts in each state, revealing patterns undetected in the aggregate analysis. Its decomposition generates two products that are useful to policy-makers. The first is a base estimate of the degree of IOp present in society, which may be expressed as an indicator of the degree of IOp. The second examines the portion of total inequality attributable to IOp.
Este é um artigo de acesso aberto, licenciado por Creative Commons Atribuição 4.0 International (CC-BY 4.0), sendo permitida reprodução, adaptação e distribuição desde que o autor e a fonte originais sejam creditados.Resumo. O estudo objetiva verificar os padrões de dependência espacial de fatores socioeconômicos e demográficos explicativos para o registro de casos de dengue nos municípios do Rio Grande do Sul entre os anos de 2009 a 2015. Para isso, é estabelecida uma ponte interdisciplinar entre as áreas da epidemiologia e economia. Através de um modelo econométrico Logit estimado via GMM espacial de Conley (1999), verificamos que o Índice de Desenvolvimento Humano Municipal (IDH-M), Índice de Gini para desigualdade de renda a densidade populacional mostram-se parcialmente explicativos, complementando-se a análise através de considerações acerca das condições climáticas específicas a cada região. Palavras-chave:Dengue, análise espacial, economia da saúde, mapeamento geográfico.Abstract. The present work aims to verify patterns of spatial dependence of socioeconomic and demographic factors that could explain the register of dengue disease in the cities of Rio Grande do Sul between the years of 2009 and 2015. We established an interdisciplinary bridge between epidemiology and economics. Using an econometric Logit model estimated with Conley`s (1999) spatial GMM method, we found that the Municipal Human Development Index (IDH-M), Gini index for income inequality and population density are partial explanations, while we complement the analysis with considerations on specific climatic conditions of each region.
O objetivo é investigar a distribuição espacial das classes criativas nas microrregiões brasileiras e sua relação com o desenvolvimento regional. Para isso, testa-se o poder explicativo da Teoria do Capital Criativo frente ao da Teoria do Capital Humano para as diferenças de renda per capita entre as microrregiões. Os resultados indicam que as microrregiões com maior PIB per capita e boa parte da população com alto índice educacional estão concentradas nas regiões da metade sul do Brasil. O I de Moran indicou que ambas as variáveis estão associadas com o nível de desenvolvimento das microrregiões, porém o capital humano apresentou resultado mais expressivo. O teste de Indicadores de Associação Espacial Local (LISA) revelou a presença de clusters alto-alto para ambas as variáveis na metade sul. O modelo econométrico espacial apontou que o capital humano tem um efeito mais forte que o capital criativo sobre o desenvolvimento econômico das microrregiões brasileiras.
Esta revisão bibliográfica apresenta a evolução dos modelos que explicam os diferentes níveis de redistribuição de renda nos países da OECD e América Latina, considerando o papel das crenças sociais da população. As teorias têm início com a ideia do eleitor decisivo e da regra da maioria, exposto no modelo de Meltzer & Richard (1981), além das explicações políticas, econômicas e comportamentais de Alesina et al. (2001). Desenvolvimentos posteriores de Alesina & Glaeser (2004), Alesina & Angeletos (2005) e Figueiredo (2012) incorporam o papel das crenças sociais na sorte como elemento fundamental da redistribuição de renda e da percepção sobre a desigualdade de oportunidades. Considera-se que as evidências empíricas contrastantes estimulam o desenvolvimento de novos modelos que incorporem as crenças sociais como determinantes para a redistribuição de renda.
Objective of the study: This study aims to identify the relationship between an individual's mood and risk tolerance in organizational decisions.Methodology/approach: It is an applied, quantitative, descriptive and survey research. For data collection, a questionnaire was applied to a sample of 90 academics from higher education courses in the area of management at a Higher Education Institution in the State of Santa Catarina. Data were categorized and analyzed quantitatively using descriptive statistics, correlation analysis and logistic regression analysis.Originality/relevance: Researches relate positive mood and increased risk-taking, however, the results are fragmented and inconclusive as to the influence of negative mood on the tendency to take risks. Thus, this research focuses attention on the asymmetry of influence of both positive and negative mood on risk preferences.Main results: We found that in decisions involving gains, respondents have less tolerance than when they involve losses. Although mood is not related to risk tolerance, when analyzed separately, a relationship was found between the dimensions of mood and the individuals' risk tolerance.Theoretical/methodological contributions: This research adds to the literature, by exploring decision-making and the behavioral line simultaneously, as well as contributing to represent a more comprehensive description regarding the decision process regarding the Prospect Theory, by demonstrating which dimensions of mood have an influence on the risk tolerance of respondents.Social/management contributions: The study contributes to the improvement of decision-making processes in the context of aspects related to risk tolerance. The practical implications refer to the construction of a decision-making process designed in a more assertive way and in line with the losses and gains arising from the inherent risk of this decision-making process.
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