Relationship between Event Prevalence Rate and Gini Coefficient of Predictive Model

Predictive models are currently used for early intervention to help identify patients with a high risk of adverse events. Assessing the accuracy of such models is a crucial part of the development process. To measure the predictive performance of a scoring model, quantitative indices such as the K-S statistic and C-statistic are used. This paper discusses the relationship between Gini coefficients and event prevalence rates. The main contribution of the paper is the theoretical proof of the relationship between the Gini coefficient and event prevalence rate.

Crisis propagation in a heterogeneous self-reflexive DSGE model

We study a self-reflexive DSGE model with heterogeneous households, aimed at characterising the impact of economic recessions on the different strata of the society. Our framework allows to analyse the combined effect of income inequalities and confidence feedback mediated by heterogeneous social networks. By varying the parameters of the model, we find different crisis typologies: loss of confidence may propagate mostly within high income households, or mostly within low income households, with a rather sharp transition between the two. We find that crises are more severe for segregated networks (where confidence feedback is essentially mediated between agents of the same social class), for which cascading contagion effects are stronger. For the same reason, larger income inequalities tend to reduce, in our model, the probability of global crises. Finally, we are able to reproduce a perhaps counter-intuitive empirical finding: in countries with higher Gini coefficients, the consumption of the lowest income households tends to drop less than that of the highest incomes in crisis times.

The Booming Number of Museums and Their Inequality Changes in China

As the spaces for dialogue between the past and the future, museums are essential to human well-being and social sustainability. Here, we collected data from 328 cities in 31 provinces of mainland China from 1980 to 2019 to investigate the changes in number and spatial inequalities of museums. The results showed that: (1) in mainland China, there were only 137 museums in 1980, and while this increased to 5626 in 2019, China still possessed only four museums per million people; (2) the increasing number of museums lagged behind the growth rate of both the population and economy at both the province and city level; (3) the Gini coefficient of museums per million people was only 0.27 in 2019, indicating relative equality of visiting opportunities among the provinces of China; (4) the Gini coefficients of per capita museums in some provinces were higher than that of the whole nation, with the highest ~0.6 in 2010 and 0.4 in 2017; (5) the economic competitiveness and human well-being of a city were promoted by an increased number of museums. We suggest that the central government of China should increase the number of museums in all provinces, while some provinces should pay more attention to the inequality in the distribution of cultural facilities among cities.

Inequality trends in the distribution of healthcare human resources in eastern Iran

Background Inequitable distribution of human resources in healthcare is one of the main obstacles to improve any health system. This study aimed to evaluate inequalities in the distribution of human resources in healthcare in South Khorasan Province, Iran. Methods We have investigated three types of health staff (i.e. nurses, general practitioners, and specialists) from 2013 to 2018. Data were collected from the annual reports of the Statistical Centre of Iran. The Gini coefficient and time trend regression were applied to measure the inequality. Results The distribution of specialists and general practitioners were the highest and lowest inequality, respectively. Inequalities in the distribution of nurses and specialists have decreased from 2013 to 2018, while the Gini coefficients of the general practitioners have increased from 0.31 to 0.38. According to the regression analysis, inequality in the distribution of nurses and specialists was decreasing over the time; however, the decline was only significant for specialists. While the coefficient B for general practitioners is positive, this indicates raised inequality, but the observed increase was not significant. Conclusions This study revealed that Iran, similar to several other low- and middle-income countries, is with faced the challenge of inequitable distribution of human resources in healthcare, which in turn indicates the necessity of reforms at national and regional levels to address inequalities in the distribution of healthcare human resources, particularly in South Khorasan Province. Hence, the main policy recommendation is to focus on continuous monitoring and evaluation of resource allocation in South Khorasan Province to reduce inequalities.

Opportunity and inequality in the emerging esports labor market

Esports is often described as a growing industry ripe with financial opportunities for young professional, competitive gamers. However, these claims rarely consider how income is distributed amongst players. This study uses prize earnings data from 2005 to 2019 to examine labor market inequality and related social inequalities and social stratifications. Lorenz curves and Gini coefficients show that inequality has increased in the labor market overall and the labor markets for the five top games based on total prizes awarded ( Dota 2, Counter-Strike: Global Offensive, Fortnite, League of Legends, StarCraft II). Competitors can expect to earn more today than in 2005, but median incomes have shown sporadic and inconsistent growth compared with top incomes. Moreover, most competitors earn less than the US poverty threshold. Comparing the earnings of the top female players to the whole labor market shows that gender inequalities exist in median incomes and the likelihood of earning more than the poverty threshold. The esports labor market is an engine of inequality that provides opportunities for a few (primarily male) competitors while building a growing class of lowly paid players who support the interests of game designers and event organizers.

COVID-19 Cases Among Facility-Staff by Neighbourhood of Residence and Social and Structural Determinants: An Observational Study (Preprint)

BACKGROUND Disproportionate risks of COVID-19 in congregate settings including long-term care homes, retirement homes, and shelters both affect and are affected by SARS-CoV-2 infections among facility-staff. In cities across Canada, there has been a consistent trend of geographic clustering of COVID-19 cases. However, there remain limited data on how COVID-19 among facility-staff reflect urban neighbourhood disparities, particularly stratified by the social and structural determinants of community-level transmission. OBJECTIVE To compare the concentration of cumulative cases by geography and social/structural determinants across three mutually exclusive subgroups in the Greater Toronto Area (population 7.1 million): community, facility-staff, and healthcare workers (HCW) in other settings. METHODS We conducted a retrospective, observational study using surveillance data on laboratory-confirmed COVID-19 cases (January 23 to December 13, 2020; prior to vaccination roll-out). We derived neighbourhood-level social/structural determinants from census data, and generated Lorenz curves and Gini coefficients to visualize and quantify inequalities in cases. RESULTS The hardest-hit neighbourhoods (comprising 20% of the population) accounted for 53.4% of community cases, 48.6% of facility-staff cases, and 42.3% of other HCW cases. Compared with other HCW, cases in facility-staff more closely reflected the distribution of community cases. Cases in facility-staff reflected greater social and structural inequalities (larger Gini coefficients) than other HCW across all determinants. Facility-staff cases were also more likely than community cases to be concentrated in lower income neighbourhoods (Gini 0.24[0.15-0.38] vs 0.14[0.08-0.21] with lower household density (Gini 0.23[0.17-0.29] vs 0.17[0.12-0.22]) and with a greater proportion working in other essential services (Gini 0.29 [0.21-0.40], 0.22[0.17-0.28]). CONCLUSIONS COVID-19 cases among facility-staff largely reflects neighbourhood-level heterogeneity and disparities; even more so than cases in other HCW. Findings signal the importance of interventions prioritized and tailored to home geographies of facility-staff in addition to workplace measures, including prioritization and reach of vaccination at home (neighbourhood-level) and at work.

Inter-market Variability of Smallholder Beef Cattle Farming in East Java Indonesia

Indonesia has failed to achieve meat self-sufficiency; meanwhile, East Java is among the centers of beef cattle with a relatively high contribution in terms of GDP and employment. Therefore, this study aims to identify and analyze the market structure of the beef cattle commodity chain by considering the concentration ratio, Gini Index, as well as barriers to exit and entry. The study was conducted in Malang Regency and Sapudi Island, with 164 respondents, which consisted of calf suppliers, farmers, traders, and slaughterhouses. Furthermore, the analytical tools used include descriptive, concentration ratio, Gini Coefficient, and analysis of barriers to entry and exit. Based on the results, the market structures in the beef cattle commodity chain in terms of its input market was perfect competition, while the intermediate and output market was oligopoly. These results were confirmed by the concentration ratios of calf suppliers and farmers, which were lower than the ratios of traders and slaughterhouses. Although the market structures were different, their Gini Coefficients are almost similar because a value of 0.2 showed an equitable distribution. Additionally, the barriers to entry into the market were high investment with a large number of import and market problems. Meanwhile, the barriers to exit the market were a large number of potential demands, high investment, and a source of income.

High-end luxury wine demand and income inequality

Purpose The purpose of this study is to explore the relationship between income inequality and the demand for high-end luxury wine. The consumption of luxury goods has experienced dramatic growth since 2000 but inequality has been neglected by scholars working on luxury consumption. The exploratory research focuses on wine demand between 2000 and 2019 and analyzes the impact of income inequality among other factors, including gross domestic product (GDP) per capita and GDP growth. The authors want to discern whether highly unequal countries import more expensive wine when compared to countries with lower inequality. Design/methodology/approach The authors prepared different data sets based on the year and the trade value of each country to compare the differences and commonalities. The regression models incorporate particular foreign trade statistics (average unit price of wine) as an objective variable and the Gini coefficients to measure the relation between the demand for high-end luxury wines and inequality as an explanatory variable. The models also incorporate other control variables such as economic and institutional conditions. Findings The analysis demonstrates a positive relationship between the unit price of imported wine and the level of income inequality of the importers. This research suggests that conspicuous consumption, as a means of social distinction, is a major driver of the luxury wine market. Other significant factors include GDP per capita and geographic proximity. However, countries with a high power distance and bad governance do not purchase more luxury wines than others. Hence, rather than the social acceptation of wealth and corruption, the consumption of luxury wines is driven by the levels of economic development and inequality. Originality/value This paper is exploratory research that discusses an underexplored issue: the impact of income inequality on the consumption of luxury goods such as high-end luxury wines. It contributes to the literature on wine consumption, luxury business and income and wealth inequalities. These fields are rarely approached together and the research emphasizes the potential offered by such a perspective.

The Impact of Educational Assortative Mating on Income Inequality: Evidence from Argentina

This paper seeks to quantify the impact of educational assortative mating on income inequality among households in Argentina. We use microdata from two household surveys conducted by the National Institute of Statistics and Census: The Permanent Household Survey and the National Survey of Risk Factors. We construct contingency tables and perform a regression analysis to study the existence of educational assortative mating. We also present counterfactual simulations of random re-matching of observations. The results show that a sizeable proportion of couples are educationally homogamous (45%). Comparing the Gini coefficients calculated in the real matching and the simulated scenarios, we observe a reduction of up to 4 points. Thus, the educational assortative mating represents a relevant dimension to explain income inequality. Our results recommend considering this matching pattern when defining optimal income taxes; this is, if there is a high positive covariance between the income of both members of the couple, it seems appropriate, from a redistributive point of view, to define income taxes at the household level and not at the individual level (as is currently the case in most countries, including Argentina).