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Equality of opportunity is about leveling the playing field so that circumstances such as gender, ethnicity, place of birth, or family background do not influence a person's life chances. Success in life should depend on people's choices, effort and talents, not to their circumstances at birth. 'Measuring Inequality of Opportunities in Latin America and the Caribbean' introduces new methods for measuring inequality of opportunities and makes an assessment of its evolution in Latin America over a decade. An innovative Human Opportunity Index and other parametric and non-parametric techniques are presented for quantifying inequality based on circumstances exogenous to individual efforts. These methods are applied to gauge inequality of opportunities in access to basic services for children, learning achievement for youth, and income and consumption for adults.

We evaluate the impact of access to credit on rural households' per capita annual income using an endogenous switching regression approach, an increasingly popular method of tackling the selection bias issue in impact analyses. Using a large survey of rural households in eastern India, we find that access to credit is strongly associated with rural households' socioeconomic and demographic characteristics. Additionally, access to credit increases rural households' economic well-being; nonborrower rural households would benefit the most from access to credit. Access to credit affects recipients heterogeneously, implying that credit policies should be adaptable to different rural household groups.

Purpose Homeownership provides shelter and is a vital component of wealth, and house purchase signifies a lifetime achievement for many households. For South Africa confronted with social and structural challenges, homeownership by the low and lower middle-income household is pivotal for its structural transformation process. In spite of these potential benefits, research on the affordable housing market in the context of South Africa is limited. This study aims to contribute to this knowledge gap by answering the question “do changes in household income per capita have a symmetric or asymmetric effect on affordable house prices?” Design/methodology/approach A survey of the international literature on house prices and income revealed that linear modelling that assumes symmetric reaction of macroeconomic variables dominates the empirical strategy. This linearity assumption is restrictive and fails to capture possible asymmetric dynamics inherent in the housing market. The authors address this empirical limitation by using asymmetric non-linear autoregressive distributed lag models that can test and detect the existence of asymmetry in both the long and short run using data from 1985Q1 to 2016Q3. Findings The results revealed the presence of an asymmetric long-run relationship between affordable house prices and household income per capita. The estimated asymmetric long-run coefficients of logIncome[+] and logIncome[−] are 1.080 and −4.354, respectively, implying that a 1% increase/decrease in household income per capita induces a 1.08% rise/4.35% decline in affordable house prices everything being equal. The positive increase in affordable house prices creates wealth, helps low and middle-income household climb the property ladder and can reduce inequality, which provides support for the country’s structural transformation process. Conversely, a decline in affordable house prices tends to reduce wealth and widen inequality. Practical implications This paper recommends both supply- and demand-side policies to support affordable housing development. Supply-side stimulants should include incentives to attract developers to affordable markets such as municipal serviced land and tax credit. Demand-side policy should focus on asset-based welfare policy; for example, the current Finance Linked Income Subsidy Programme (FLISP). Efficient management and coordination of the FLISP are essential to enhance the affordability of first-time buyers. Given the enormous size of the affordable property market, the practice of mortgage securitization by financial institutions should be monitored, as a persistent decline in income can trigger a systemic risk to the economy. Social implications The study results illustrate the importance of homeownership by low- and middle-income households and that the development of the affordable market segment can boost wealth creation and reduce residential segregation. This, in turn, provides support to the country’s structural transformation process. Originality/value The affordable housing market in South Africa is of strategic importance to the economy, accounting for 71.4% of all residential properties. Homeownership by low and lower middle-income households creates wealth, reduces wealth inequality and improves revenue collection for local governments. This paper contributes to the empirical literature by modelling the asymmetric behaviour of affordable house prices to changes in household income per capita and other macroeconomic fundamentals. Based on available evidence, this is the first attempt to examine the dynamic asymmetry between affordable house prices and household income per capita in South Africa.

The problem of income inequality is globally relevant, receiving the attention of both scientists and politicians. Lithuania as a small country has made significant progress in approaching the standard of living in Western Europe. However, there are still differences in economic growth between separate population groups. Thus, the problem of income inequality remains very acute. Currently, researchers are widely discussing the risk of income inequality to the country’s society by analysing its causes and proposing various solutions. Although scientific debates address income inequality across regions, such studies are often limited to examples of large countries. Meanwhile, there is a lack of studies on regional income inequality in small countries, so the question of whether a small country is characterised by regional income inequality remains open. This research aims to examine the level of regional income inequality in Lithuania. We hypothesised that Lithuania has a high level of regional income inequality and this is one of the causes of the high income inequality in the whole country. To estimate regional income inequality, we used the most common measures: Gini coefficient, decile ratio, and the coefficient of variation. The analysis was performed at level 3 of the Nomenclature of Territorial Units for Statistics (NUTS), according to which Lithuania is divided into 10 administrative counties. For this research, we chose the indicators illustrating income per capita on various levels, i.e., gross domestic product (GDP) per capita, average disposable household income per capita, and gross hourly wages, as the various types of income can be used. For the estimation of GDP per capita and average disposable household income, we analysed the data provided by the Lithuanian Departmen tof Statistics (Statistics Lithuania) for 2014–2017. Due to a lack of data to estimate gross hourly wages, we examined the statistical data from the Lithuanian Department of Statistics for 2014. The results show that the hypothesis has not been confirmed. According to the research results, there is a small distribution of income between different regions of a small economy, although the level of economic development of different regions differs. The study findings are important not only from an academic perspective for identifying the causes of income inequality and raising questions for further research, but also for regional economic policymakers. The obtained results show that decisions related to a more equal distribution of income in Lithuania as a small country are determined not only by the specificity of its regions but also by the general trends of the country.

Promoting the transfer of rural residential land is paramount in enhancing the efficiency of its utilization. The willingness of farmers to transfer rural residential land is influenced by the number of permanent residents. Existing research has drawn different conclusions about the relationship between these two factors, but the differences have not been analyzed. This study is based on survey data collected from our field research in Deqing County, Zhejiang Province, and utilizes the Probit model and threshold effect model to investigate the role of per capita net income in the relationship between the number of permanent residents and the willingness to transfer rural residential land. The results indicate: (1) There is a non-linear impact of the number of permanent residents on the willingness of farmers who are willing to live in rural areas to transfer to their rural residential land with an income threshold. There is a non-linear impact of the number of permanent residents on the willingness of farmers who are willing to live in city areas to transfer out of their rural residential land, with two income thresholds. By comparing with the actual situation, the size and order of the thresholds are scientifically established. (2) The transfer of rural residential land can serve as a supplementary solution to individual household applications for rural residential land, addressing China’s historical legacy issues concerning rural residential land. Considering these findings, policymakers should first actively promote the reform of the rural residential land system while ensuring safeguards for farmers and then work to increase the value of rural residential land. Additionally, they should implement differentiated policies to promote rural residential land transfer. This study can provide a valuable reference for effectively revitalizing idle rural residential land.

Background This study investigated the trends, motivations and preferences of rhinoplasty in China. Methods Data on rhinoplasty were collected from Xiaohongshu and analyzed for trends. Text analysis and word frequency statistics were performed on the notes and comments using Python modules. Results We obtained 1065 notes with 102,153 comments, 239,383 collections and 640,579 likes. The number of rhinoplasty-related publications increased annually, correlating with per capita disposable income of households (DI) growth ( r 2  = 0.609, P  = 0.041 < 0.05). In the Southern provinces, there was a notably higher volume of publications compared to the Northern provinces ( P  = 0.001). Furthermore, a significant correlation was observed between publication data, population size, and the DI ( r 2  = 0.786, P  < 0.001). The nasal tip (3197) and nasion (1409) were the most mentioned nasal subunits. “Good-looking” (9672) and “natural” (2811) were the most used words to describe the nose shape. The “doctor” (4377), the “hospital” (2182) and “hyaluronic acid” (2106) were the most mentioned rhinoplasty procedure related vocabulary. Conclusions Discussions about rhinoplasty in China are increasing, and more people express their desire for rhinoplasty on social networks, related to China’s DI growth. The Southern provinces show a higher inclination toward these discussions, a trend that correlates with our findings of a positive association between NOPs and both DI and population size. Netizens pay more attention to the shape of nasal tip and nasion, and prefer the good-looking and natural appearance. Most people consider autologous cartilage or hyaluronic acid injection for rhinoplasty. Doctors are the primary consideration for patients. Level of Evidence V This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Understanding Changes in Poverty brings together different methods to decompose the contributions to poverty reduction. A simple approach quantifies the contribution of changes in demographics, employment, earnings, public transfers, and remittances to poverty reduction. A more complex approach quantifies the contributions to poverty reduction from changes in individual and household characteristics, including changes in the sectoral, occupational, and educational structure of the workforce, as well as changes in the returns to individual and household characteristics. Understanding Changes in Poverty implements these approaches and finds that labor income growththat is, growth in income per worker rather than an increase in the number of employed workerswas the largest contributor to moderate poverty reduction in 21 countries experiencing substantial reductions in poverty over the past decade. Changes in demographics, public transfers, and remittances helped, but made relatively smaller contributions to poverty reduction. Further decompositions in three countries find that labor income grew mainly because of higher returns to human capital endowments, signaling increases in productivity, higher relative price of labor, or both. Understanding Changes in Poverty will be of particular relevance to development practitioners interested in better understanding distributional changes over time. The methods and tools presented in this book can also be applied to better understand changes in inequality or any other distributional change.

Should income inequality be of concern in developing countries? New data reveal less income inequality in the developing world than 30 years ago. However, this is due to falling inequality between countries. Average inequality within developing countries has been slowly rising, though staying fairly flat since 2000. As a rule, higher rates of growth in average incomes have not put upward pressure on inequality within countries. Growth has generally helped reduce the incidence of absolute poverty, but less so in more unequal countries. High inequality also threatens to stall future progress against poverty by attenuating growth prospects. Perceptions of rising absolute gaps in living standards between the rich and the poor in growing economies are also consistent with the evidence.

The double burden of malnutrition (DBM), defined as the simultaneous manifestation of both undernutrition and overweight and obesity, affects most low-income and middle-income countries (LMICs). This Series paper describes the dynamics of the DBM in LMICs and how it differs by socioeconomic level. This Series paper shows that the DBM has increased in the poorest LMICs, mainly due to overweight and obesity increases. Indonesia is the largest country with a severe DBM, but many other Asian and sub-Saharan African countries also face this problem. We also discuss that overweight increases are mainly due to very rapid changes in the food system, particularly the availability of cheap ultra-processed food and beverages in LMICs, and major reductions in physical activity at work, transportation, home, and even leisure due to introductions of activity-saving technologies. Understanding that the lowest income LMICs face severe levels of the DBM and that the major direct cause is rapid increases in overweight allows identifying selected crucial drivers and possible options for addressing the DBM at all levels.

This paper reports an experiment in 640 Indonesian villages on three approaches to target the poor: proxy means tests (PMT), where assets are used to predict consumption; community targeting, where villagers rank everyone from richest to poorest; and a hybrid. Defining poverty based on PPP$2 per capita consumption, community targeting and the hybrid perform somewhat worse in identifying the poor than PMT, though not by enough to significantly affect poverty outcomes for a typical program. Elite capture does not explain these results. Instead, communities appear to apply a different concept of poverty. Consistent with this finding, community targeting results in higher satisfaction.