A theoretical connection between inflation and income inequality

This work investigates the effects of inflation on income distribution. We use a dynamic shopping-time model to show that a differentiated access to transacting technologies by poor and rich consumers is enough to generate a positive link between inflation and the Gini coefficient of income distribution.

Income inequality and elderly self-rated health in Sao Paulo, Brazil

Purpose: To test the association between income inequality and elderly self-rated health and to propose a pathway to explain the relationship. Methods: We analyzed a sample of 2143 older individuals (60 years of age and over) from 49 distritos of the Municipality of Sao Paulo, Brazil. Bayesian multilevel logistic models were performed with poor self-rated health as the outcome variable. Results: Income inequality (measured by the Gini coefficient) was found to be associated with poor self-rated health after controlling for age, sex, income and education (odds ratio, 1.19; 95% credible interval, 1.01-1.38). When the practice of physical exercise and homicide rate were added to the model, the Gini coefficient lost its statistical significance (P>.05). We fitted a structural equation model in which income inequality affects elderly health by a pathway mediated by violence and practice of physical exercise. Conclusions: The health of older individuals may be highly susceptible to the socioeconomic environment of residence, specifically to the local distribution of income. We propose that this association may be mediated by fear of violence and lack of physical activity. (C) 2012 Elsevier Inc. All rights reserved.

Cause-specific mortality and income inequality in Sao Paulo, Brazil

OBJECTIVE: To analyze cause-specifi c mortality rates according to the relative income hypothesis. METHODS: All 96 administrative areas of the city of Sao Paulo, southeastern Brazil, were divided into two groups based on the Gini coefficient of income inequality: high (&gt;= 0.25) and low (<0.25). The propensity score matching method was applied to control for confounders associated with socioeconomic differences among areas. RESULTS: The difference between high and low income inequality areas was statistically significant for homicide (8.57 per 10,000; 95% CI: 2.60; 14.53); ischemic heart disease (5.47 per 10,000 [95% CI 0.76; 10.17]); HIV/AIDS (3.58 per 10,000 [95% CI 0.58; 6.57]); and respiratory diseases (3.56 per 10,000 [95% CI 0.18; 6.94]). The ten most common causes of death accounted for 72.30% of the mortality difference. Infant mortality also had signifi cantly higher age-adjusted rates in high inequality areas (2.80 per 10,000 [95% CI 0.86; 4.74]), as well as among males (27.37 per 10,000 [95% CI 6.19; 48.55]) and females (15.07 per 10,000 [95% CI 3.65; 26.48]). CONCLUSIONS: The study results support the relative income hypothesis. After propensity score matching cause-specifi c mortality rates was higher in more unequal areas. Studies on income inequality in smaller areas should take proper accounting of heterogeneity of social and demographic characteristics.

Cause-specific mortality and income inequality in São Paulo, Brazil

OBJECTIVE: To analyze cause-specific mortality rates according to the relative income hypothesis. METHODS: All 96 administrative areas of the city of São Paulo, southeastern Brazil, were divided into two groups based on the Gini coefficient of income inequality: high (&gt;0.25) and low (<0.25). The propensity score matching method was applied to control for confounders associated with socioeconomic differences among areas. RESULTS: The difference between high and low income inequality areas was statistically significant for homicide (8.57 per 10,000; 95%CI: 2.60;14.53); ischemic heart disease (5.47 per 10,000 [95%CI 0.76;10.17]); HIV/AIDS (3.58 per 10,000 [95%CI 0.58;6.57]); and respiratory diseases (3.56 per 10,000 [95%CI 0.18;6.94]). The ten most common causes of death accounted for 72.30% of the mortality difference. Infant mortality also had significantly higher age-adjusted rates in high inequality areas (2.80 per 10,000 [95%CI 0.86;4.74]), as well as among males (27.37 per 10,000 [95%CI 6.19;48.55]) and females (15.07 per 10,000 [95%CI 3.65;26.48]). CONCLUSIONS: The study results support the relative income hypothesis. After propensity score matching cause-specific mortality rates was higher in more unequal areas. Studies on income inequality in smaller areas should take proper accounting of heterogeneity of social and demographic characteristics.

Transmission of Chlamydia trachomatis through sexual partnerships: a comparison between three individual-based models and empirical data

Chlamydia trachomatis is the most common bacterial sexually transmitted infection (STI) in many developed countries. The highest prevalence rates are found among young adults who have frequent partner change rates. Three published individual-based models have incorporated a detailed description of age-specific sexual behaviour in order to quantify the transmission of C. trachomatis in the population and to assess the impact of screening interventions. Owing to varying assumptions about sexual partnership formation and dissolution and the great uncertainty about critical parameters, such models show conflicting results about the impact of preventive interventions. Here, we perform a detailed evaluation of these models by comparing the partnership formation and dissolution dynamics with data from Natsal 2000, a population-based probability sample survey of sexual attitudes and lifestyles in Britain. The data also allow us to describe the dispersion of C. trachomatis infections as a function of sexual behaviour, using the Gini coefficient. We suggest that the Gini coefficient is a useful measure for calibrating infectious disease models that include risk structure and highlight the need to estimate this measure for other STIs.

Morphometric data for Globigerinoides sacculifer and Globorotalia tumida (size and Fourier coefficients) and temperature proxy reconstructions (UK37' and Tex86H) from samples from ODP sites 165-999/165-1000 and 202-1241 spanning the last 10Ma

Sediment samples from both Site 165-999/165-1000 (Atlantic) and Site 202-1241 (Pacific) were chosen at 1Ma intervals over the period 0.3-9.3Ma. Samples were washed and sieved <150µm. Splits of the sediment fraction were picked completely to obtain, where possible, at least 30 specimens each of planktic foraminifer species Globigerinoides sacculifer and Globorotalia tumida, on which outline analysis (Fourier) was performed. Sea surface and thermocline temperatures were reconstructed from palaeoenvironmental proxies (UK37' and Tex86H respectively).

Chapter 6 Economic integration and changes in industrial location in Vietnam

Vietnam has been praised for its achievements in economic growth and success in poverty reduction over the last two decades. The incidence of poverty reportedly fell from 58.1% in 1993 to 19.5% in 2004 (VASS [2006, 13]). The country is also considered to have only a moderate level of aggregate economic inequality by international comparisons. As of the early 2000s, Vietnam’s consumption-based Gini coefficient is found to be comparable to that of other countries with similar levels of per capita GDP. The Gini index did increase between 1993 and 2004, but rather slowly, from 0.34 to 0.37 (VASS [2006, 13]). Yet, as the country moves on with its market oriented reforms, the question of inequality has been highlighted in policy and academic discourses. In particular, it is pointed out that socio-economic inequalities between regions (or provinces) are significant and have been widening behind aggregate figures (NCSSH [2001], Mekong Economics [2005], VASS [2006]). Between 1993 and 2004, while real per capita expenditure increased in all regions, it grew fastest in those regions with the highest per capita expenditures and vice versa, resulting in greater regional disparities (VASS [2006, 37]). A major contributing factor to such regional inequalities is the uneven distribution of industry within the country. According to the Statistical Yearbook of Vietnam, of the country's gross industrial output in 2007, over 50% belongs to the South East region, close to 25% to the Red River Delta, and about 10% to the Mekong River Delta. All remaining regions share some 10% of the country's gross industrial output. At a quick glance, the South East increased its share of the total industrial gross output in the 1990s, while the Red River Delta started to gain ground in more recent years. How can the government deal with regional disparities is a valid question. In order to offer an answer, it is necessary in the first place to grasp the trend of disparities as well as its background. To that end, this paper is a preparatory endeavor. Regional disparities in industrial activities can essentially be seen as a result of the location decisions of enterprises. While the General Statistics Office (GSO) of Vietnam has conducted one enterprise census (followed by annual enterprise surveys) and two stages of establishment censuses since 2000, sectorally and geographically disaggregated data are not readily available. Therefore, for the moment, we will draw on earlier studies of industrial location and the determinants of enterprises’ location decisions in Vietnam. The remainder of this paper is structured as follows. The following two sections deal with the country context. Section 2 will outline some major developments in Vietnam’s international economic relations that may affect sub-national location of industry. According to the theory of spatial economics, economic integration is seen as a major driver of changes in industrial location, both between and within countries (Nishikimi [2008]). Section 3, on the other hand, will consider some possible factors affecting geographic distribution of industry in the domestic sphere. In Section 4, existing literature on industrial and firm location will be examined, and Section 5 will briefly summarize the findings and suggest some areas for future research.

A study the degree of concentration of the Spanish bunkering

This paper shows the Gini Coefficient of the Spanish bunkering, for the Spanish Port System 1960 to the year 2010 with the aim to describe the Spanish bunkering in these periods and propose future strategies. The stage of bunkering must change due to new regulations of marine fuels but to predict the future you must know the past On December 17 came into force on community standard marine fuels. After a complicated negotiation with the industry moves forward a project that is fully compliant with the guidelines of the International Maritime Organization (IMO) and limiting the sulphur and particulate matter of marine fuels used by ships calling or transit through maritime space of the European Union. The impact of a possible extension at European level of the Sulphur Emission Control Areas (SECA) as they are introduced in the Annex VI of the International Convention for the Prevention of Pollution From Ships, 1973 as modified by the Protocol of 1978 (MARPOL) adopted by the International Maritime Organisation (IMO).

Comparison of Airborne Laser Scanning Methods for Estimating Forest Structure Indicators Based on Lorenz Curves

The purpose of this study was to compare a number of state-of-the-art methods in airborne laser scan- ning (ALS) remote sensing with regards to their capacity to describe tree size inequality and other indi- cators related to forest structure. The indicators chosen were based on the analysis of the Lorenz curve: Gini coefficient ( GC ), Lorenz asymmetry ( LA ), the proportions of basal area ( BALM ) and stem density ( NSLM ) stocked above the mean quadratic diameter. Each method belonged to one of these estimation strategies: (A) estimating indicators directly; (B) estimating the whole Lorenz curve; or (C) estimating a complete tree list. Across these strategies, the most popular statistical methods for area-based approach (ABA) were used: regression, random forest (RF), and nearest neighbour imputation. The latter included distance metrics based on either RF (NN–RF) or most similar neighbour (MSN). In the case of tree list esti- mation, methods based on individual tree detection (ITD) and semi-ITD, both combined with MSN impu- tation, were also studied. The most accurate method was direct estimation by best subset regression, which obtained the lowest cross-validated coefficients of variation of their root mean squared error CV(RMSE) for most indicators: GC (16.80%), LA (8.76%), BALM (8.80%) and NSLM (14.60%). Similar figures [CV(RMSE) 16.09%, 10.49%, 10.93% and 14.07%, respectively] were obtained by MSN imputation of tree lists by ABA, a method that also showed a number of additional advantages, such as better distributing the residual variance along the predictive range. In light of our results, ITD approaches may be clearly inferior to ABA with regards to describing the structural properties related to tree size inequality in for- ested areas.

Determinantes sociais da mobilidade funcional e quedas em idosos do município de São Paulo: uma análise multinível

Introdução: Estudos recentes têm mostrado que as quedas são a causa externa de morte mais importante entre idosos, podendo levar a hospitalização, lesões, dependência e aumento nos custos dos serviços sociais e de saúde. O comprometimento da mobilidade funcional é um importante fator de risco para quedas, mas aspectos sociais, ambientais e comportamentais também podem influenciar nesse evento. Objetivo: Identificar os aspectos socioeconômicos e contextuais associados com a mobilidade funcional e quedas em idosos residentes no município de São Paulo. Métodos: Foram utilizados os dados do Estudo Saúde, Bem-Estar e Envelhecimento (SABE), uma amostra representativa para os indivíduos com idade igual ou superior a 60 anos do município de São Paulo, em 2010. As variáveis dependentes do estudo foram a ocorrência de alguma queda no último ano e o comprometimento da mobilidade funcional, mensurada pelo teste Timed Up and Go (TUG). Fatores individuais (estado marital, raça/cor, anos de estudo e percepção de suficiência de renda) e contextuais (Índice de Gini, área verde/ habitante, taxa de homicídio e percentual de domicílios em favelas) foram analisados por modelos logísticos multiníveis. Resultados: De 1.190 idosos inclusos, 29 por cento relataram ter caído no último ano e 46 por cento apresentaram comprometimento da mobilidade funcional. Os fatores individuais socioeconômicos não apresentaram associação com a ocorrência de queda, mas ter 8 anos ou mais de anos de estudo foi um fator protetor para comprometimento da mobilidade em todos os modelos testados (OR: 0,56). Morar em subprefeituras com taxa de homicídio moderada apresentou associação com chance aumentada de cair (OR: 1.51, 95 por cento IC: 1.09-2.07). Moderada área verde se associou com maior chance de cair entre os indivíduos com 80 anos e mais (OR:2,63, 95 por cento IC: 1.23-5.60). Conclusão: Os resultados estão de acordo com a literatura em relação à associação das características do bairro de residência com quedas e mobilidade funcional em idosos. Estratégias voltadas para prevenção de quedas e de dificuldade na mobilidade funcional devem considerar aspectos sociais e ambientais de locais públicos. Este estudo foi financiado pela Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) (nº processo: 2014/06721-4)

MOREMATA: Stata module (Mata) to provide various functions

This package includes various Mata functions. kern(): various kernel functions; kint(): kernel integral functions; kdel0(): canonical bandwidth of kernel; quantile(): quantile function; median(): median; iqrange(): inter-quartile range; ecdf(): cumulative distribution function; relrank(): grade transformation; ranks(): ranks/cumulative frequencies; freq(): compute frequency counts; histogram(): produce histogram data; mgof(): multinomial goodness-of-fit tests; collapse(): summary statistics by subgroups; _collapse(): summary statistics by subgroups; gini(): Gini coefficient; sample(): draw random sample; srswr(): SRS with replacement; srswor(): SRS without replacement; upswr(): UPS with replacement; upswor(): UPS without replacement; bs(): bootstrap estimation; bs2(): bootstrap estimation; bs_report(): report bootstrap results; jk(): jackknife estimation; jk_report(): report jackknife results; subset(): obtain subsets, one at a time; composition(): obtain compositions, one by one; ncompositions(): determine number of compositions; partition(): obtain partitions, one at a time; npartitionss(): determine number of partitions; rsubset(): draw random subset; rcomposition(): draw random composition; colvar(): variance, by column; meancolvar(): mean and variance, by column; variance0(): population variance; meanvariance0(): mean and population variance; mse(): mean squared error; colmse(): mean squared error, by column; sse(): sum of squared errors; colsse(): sum of squared errors, by column; benford(): Benford distribution; cauchy(): cumulative Cauchy-Lorentz dist.; cauchyden(): Cauchy-Lorentz density; cauchytail(): reverse cumulative Cauchy-Lorentz; invcauchy(): inverse cumulative Cauchy-Lorentz; rbinomial(): generate binomial random numbers; cebinomial(): cond. expect. of binomial r.v.; root(): Brent's univariate zero finder; nrroot(): Newton-Raphson zero finder; finvert(): univariate function inverter; integrate_sr(): univariate function integration (Simpson's rule); integrate_38(): univariate function integration (Simpson's 3/8 rule); ipolate(): linear interpolation; polint(): polynomial inter-/extrapolation; plot(): Draw twoway plot; _plot(): Draw twoway plot; panels(): identify nested panel structure; _panels(): identify panel sizes; npanels(): identify number of panels; nunique(): count number of distinct values; nuniqrows(): count number of unique rows; isconstant(): whether matrix is constant; nobs(): number of observations; colrunsum(): running sum of each column; linbin(): linear binning; fastlinbin(): fast linear binning; exactbin(): exact binning; makegrid(): equally spaced grid points; cut(): categorize data vector; posof(): find element in vector; which(): positions of nonzero elements; locate(): search an ordered vector; hunt(): consecutive search; cond(): matrix conditional operator; expand(): duplicate single rows/columns; _expand(): duplicate rows/columns in place; repeat(): duplicate contents as a whole; _repeat(): duplicate contents in place; unorder2(): stable version of unorder(); jumble2(): stable version of jumble(); _jumble2(): stable version of _jumble(); pieces(): break string into pieces; npieces(): count number of pieces; _npieces(): count number of pieces; invtokens(): reverse of tokens(); realofstr(): convert string into real; strexpand(): expand string argument; matlist(): display a (real) matrix; insheet(): read spreadsheet file; infile(): read free-format file; outsheet(): write spreadsheet file; callf(): pass optional args to function; callf_setup(): setup for mm_callf().

Essays on economics of marriage

A sociedade mudou nas últimas décadas abrindo a possibilidade para cientistas sociais estudarem essas mudanças e analisar os seus impactos na unidade familiar. Nesta tese pretendemos analisar como as decisões dos agentes com relação a decisão de casar e estudar pode estar conectado considerando que homens e mulheres têm preferências pelo casamento intragrupo. No modelo estudado encontramos que as preferências para o casamento intragrupo podem aumentar a proporção de homens e mulheres que decidem se casar e estudar. Mostramos também que empiricamente há um positive assortative mating entre pessoas com as mesmas características, tais como, educação, religião ou raça. Além disso, a probabilidade de casais casados na mesma religião aumenta a probabilidade dos casais estarem casados dentro do mesmo nível de escolaridade. Considerando as mudanças em como os casais se formam, a composição educacional e os retornos da educação que aconteceram no Brasil nos últimos anos, investiga-se os impactos dessas mudanças na desigualdade de renda dos casais. Calculamos cenários contrafactuais para o Coeficiente de Gini mantendo uma dessas três variáveis fixas em um determinado ano, comparando o contrafactual estimado com o Gini real. Se o casamento for formado aleatoriamente com relação à educação, o Coeficiente de Gini seria menor do que o real. Mantendo os retornos da educação fixos no ano de 2014 encontramos um Gini contrafactual menor do que o real.

Null Condition for Semilinear Wave Equation with Variable Coefficients

∗The author was partially supported by M.U.R.S.T. Progr. Nazionale “Problemi Non Lineari...”

Emancipações municipais:uma análise de aspectos econômicos e distribuição orçamentária para o estado do Rio Grande do Sul

Este trabalho visa analisar as características dos municípios que se emanciparam no Rio Grande do Sul, analisando diversos aspectos econômicos entre os anos de 1997 e 2005, comparando com os municípios que deram origem a eles. Utilizando o Coeficiente de Gini, em uma análise que utiliza o orçamento municipal per capita, um instrumento muito importante para comparação da capacidade fiscal dos municípios, busca-se observar se as emancipações contribuíram para uma melhor distribuição orçamentária no Estado. As análises indicaram que os municípios emancipados obtiveram um avanço nos indicadores estudados no período de 15 anos, inclusive com uma diminuição da dependência frente aos repasses da União e uma melhora significativa na capacidade de arrecadação própria. Também se verificou que num primeiro momento houve uma melhora na distribuição orçamentária, mas analisando o longo prazo a curva se inverte, concluindo que as emancipações não resultaram em uma melhor distribuição.

Análise comportamental : um estudo por análise de sobrevivência, aplicada a cartões de crédito

A capacidade de adaptação e rapidez de decisão, distinguem as empresas que melhor conseguem competir e crescer no mercado global. Para atuar rapidamente, as organizações precisam de sistemas de informação cada vez mais eficazes, surgindo recentemente uma nova função considerada fundamental para as empresas, que é a de Cientista de Dados. É neste contexto e para responder aos desafios atuais e futuros, que surgem sistemas de informação cada vez mais avançados, suportados por modelos de análise e visualização estatística. Este trabalho consiste em criar uma metodologia de desenvolvimento de modelos de previsão de incumprimento e perfil do consumidor, aplicado a cartões de crédito, com base numa exposição de análise comportamental, utilizando técnicas de análise de sobrevivência. São definidas técnicas de tratamento dos dados recolhidos, estimado modelo não-paramétrico de Kaplan-Meier e vários modelos de Cox de riscos proporcionais. Com recurso à curva ROC, dependente do tempo, à AUC e ao índice de Gini, conclui-se que o modelo final apresenta um desempenho positivo para identificar os clientes em situação de incumprimento ou com propensão a incumprir.