Estimating Income Inequality in China Using Grouped Data and the Generalized Beta Distribution

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy.

Income Ranking and convergence with physical and human capital and income equality

This paper presents an overlapping generations model with physical and human capital and income inequality. It shows that inequality impedes output growth by directly harming capital accumulation and indirectly raising the ratio of physical to human capital. The convergence speed of output growth equals the lower of the convergence speeds of the relative capital ratio and inequality, and varies with initial states. Among economies with the same balanced growth rate but different initial income levels, the ranking of income can switch in favor of those starting from low inequality and a low ratio of physical to human capital, particularly if the growth rate converges slowly. (C) 2004 Elsevier B.V. All rights reserved.

Education's role in economic development and in assisting the poor

Much faith has been put in the increased supply of education as a means to promote national economic development and as a way to assist the poor and the disadvantaged. However, the benefits that nations can obtain by increasing the level of education of their workforce depends on the availability of other forms of capital to complement the use of its educated workforce in production. Generally, less developed nations are lacking in complementary capital compared to more developed ones and it is appropriate for less developed countries to spend relatively less on education. The contribution of education to economic growth depends on a nation’s stage of economic development. It is only when a nation becomes relatively developed that education becomes a major contributor to economic growth. It is possible for less developed nations to retard their economic growth by favouring investment in educational capital rather than other forms of capital. Easy access to education is often portrayed as a powerful force for assisting the poor and the disadvantaged. Several reasons are given here as to why it may not be so effective in assisting the poor and in promoting greater income equality even though the aim is a worthy one. Also, an economic argument is presented in favour of special education for the physically and mentally handicapped. This paper is not intended to belittle the contribution of education to economic development nor to devalue the ideal of making basic education available to all. Instead, it is intended as an antidote to inflated claims about the ability of greater investment in education to promote economic growth and about the ability of more widespread access to education to reduce poverty and decrease income inequality.

Gender inequality, poverty and human development in Kenya: Main indicators, trends and limitations

Indicators of gender inequality, poverty and human development in Kenya are examined. Significant and rising incidence of absolute poverty occurs in Kenya and women are more likely to be in poverty than men. Female/male ratios in Kenyan decision-making institutions are highly skewed against women and they experience unfavourable enrolment ratios in primary, secondary and tertiary institutions. The share of income earned by women is much lower than men's share. General Kenyan indicators highlight declining GDP per capita, increased poverty rates especially for women, reduced life expectancy, a narrowing of the difference in female/male life expectancy rates, increased child mortality rates and an increase in the female child mortality rates. This deterioration results in an increased socio-economic burden on women, not adequately captured in the HPI, HDI, GDI and GEM. This paper advocates the use of household level gender disaggregated data because much gender inequality occurs in and emanates from the household level where culture plays a very important role in allocation of resources and decision-making. Because most human development indicators are aggregates or averages, they can be misleading. They need to be supplemented by distributional and disaggregated data as demonstrated in the Kenyan case. The importance is emphasised of studying coping mechanisms of household/families for dealing with economic hardship and other misfortunes, such AIDS.

Reconciling Globalisation and Technological Change: Growing Income Inequalities and Remedial Policies

From the mid-1970s through the 1980s and into the 1990s, wage inequality and skill differentials in earnings and employment increased sharply in OECD countries. After 1973 and especially in the 1980s, the US experienced a dismal real wage performance for the less skilled. Among the factors singled out by economists as possible major contributors to this development are economic globalisation processes and skill-biased technological change. Although these are most commonly considered as independent influences, after critically outlining views about these factors, this article argues that strong interdependence exists between them. The article then examines potential policy responses to this growing inequality.

Spatial inequality in the Australian youth labour market: The role of neighbourhood composition

Australia has experienced a polarization of income and labour market outcomes over the past 20 years (GREGORY and HUNTER, 1995; HARDING, 1996). This has taken an increasingly spatial dimension (HUNTER. 1995a, 1995b), giving rise to concerns that the spatial pooling of disadvantage may hamper the labour market outcomes of youth growing up in poorer residential areas. This paper explores the role that the differential neighbourhood 'quality' of an individual's residential area at age 16 has on their labour market outcomes at age 18 and age 21. Evidence is found that youth who live in poorer quality neighbourhoods face an increased likelihood of being unemployed at both the age of 18 and 21, even after controlling for personal and family characteristics.

A note on the decomposition of the health concentration index

In recent work, the concentration index has been widely used as a measure of income-related health inequality. The purpose of this note is to illustrate two different methods for decomposing the overall health concentration index using data collected from a Short Form (SF-36) survey of the general Australian population conducted in 1995. For simplicity, we focus on the physical functioning scale of the SF-36. Firstly we examine decomposition 'by component' by separating the concentration index for the physical functioning scale into the ten items on which it is based. The results show that the items contribute differently to the overall inequality measure, i.e. two of the items contributed 13% and 5%, respectively, to the overall measure. Second, to illustrate the 'by subgroup' method we decompose the concentration index by employment status. This involves separating the population into two groups: individuals currently in employment; and individuals not currently employed. We find that the inequality between these groups is about five times greater than the inequality within each group. These methods provide insights into the nature of inequality that can be used to inform policy design to reduce income related health inequalities. Copyright (C) 2002 John Wiley Sons, Ltd.

Property crime and income generation by heroin users

This paper provides a detailed analysis of patterns of income generation among 202 active heroin users in South West Sydney. We explore both sources of income and the relative contribution of different types of income generating activities, including drug sales and related activities, property crime, prostitution, legitimate income and avoided expenditures. Despite claims that heroin use leads inevitably to property crime, drug market activities accounted for a greater proportion of drug user income in this sample. Results indicate that law enforcement crackdowns that reduce opportunities for generating income from the drug market may increase property crime by heroin users.