Closing the gender gap in Bangladesh: Inequality in education, employment and earnings

Assesses the status of women in Bangladesh by analysing the dynamics of female participation in labour force and education as well as gender earnings differentials at the macro level. The study finds evidence of growing commercialisation of women’s work in Bangladesh. Although the bulk of the female labour force is engaged in self-employment activities in the rural area or in low-skilled textile and readymade garment industries in the urban area, women’s participation in high-skill and entrepreneurial jobs as well as various decision-making bodies is also on the rise. While the gender wage differentials have been considerably reduced in many industries, in general women tend to be paid less than men. There have been remarkable improvements in women’s educational attainments compared to men. Further, female access to education is found to be highly correlated with overall female labour force participation, and relative to male participation. The overall results are suggestive of an improvement in the status of women in Bangladesh.

Rural community pharmacists integrating care for people with complex health needs

The project involves rural/regional community pharmacists integrating care for complex needs patients and delivering a range of services, based on a care plan developed collaboratively with the GP and the consumer. The pharmacist will coordinate other services based on the multidisciplinary care plan. This research follows a successful pilot project and offers an opportunity to investigate new health service delivery in rural areas for patients at greater health related risk. Care integration will be compared to usual care, with outcomes relating to medication and health service usage, as well as clinical and quality of life outcomes being compared

Does workforce participation empower women? Micro-level evidence from urban Bangladesh

Empirical studies on the impact of women’s paid jobs on their empowerment and welfare in the Bangladesh context are rare. The few studies on the issue to date have all been confined to the garment workers only although studies indicate that women’s workforce participation in Bangladesh has increased across-the-board. Besides, none of these studies has made an attempt to control for the non-working women and/or applied any statistical technique to control for the effects of other pertinent determinants of women’s empowerment and welfare such as education, age, religion and place of living. This study overcomes these drawbacks and presents alternative assessments of the link between women’s workforce participation and empowerment on the basis of survey data from the two largest cities in Bangladesh. While the generic assessment indicates that women’s paid jobs have positive implications for women’s participation in decisions on fertility, children’s education and healthcare as well as their possession and control of resources, the econometric assessment negates most of these observations. Women’s education, on the other hand, appears to be more important than their participation in the labour force. The study underlines the fact that by omitting other relevant explanatory variables from the analysis, the previous studies might have overestimated the impact of women’s paid work on their empowerment. Among other things, the paper also highlights the importance of women’s job category, religion and regional differences for women’s empowerment.

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.

Domestic violence in the urban fringe

Police call data for domestic violence incidents in the city of Brisbane were used to further explore the locational disadvantage thesis. It was hypothesised that the supposed additional burdens and stresses on disadvantaged families living in the outer suburbs may be reflected in significantly higher rates of reported domestic violence. Using an index of relative socioeconomic disadvantage and employing Analysis of Variance (ANOVA), this research shows that significantly higher rates of reported domestic violence occur in the inner suburbs relative to the middle or outer suburbs of Brisbane. This finding adds further doubt as to the magnitude of locational disadvantage impacts on outer suburban low income family households.