On the Robustness of Multidimensional Counting Poverty Orderings

Counting poverty measures have gained prominence in the analysis of multidimensional poverty in recent decades. Poverty orderings based on these measures typically depend on methodological choices regarding individual poverty functions, poverty cut-offs, and dimensional weights whose impact on poverty rankings is often not well understood. In this paper we propose new dominance conditions that allow the analyst to evaluate the robustness of poverty comparisons to those choices. These conditions provide an approach to evaluating the sensitivity of poverty orderings superior to the common approach of considering a restricted and arbitrary set of indices, cut-offs, and weights. The new criteria apply to a broad class of counting poverty measures widely used in empirical analysis of poverty in developed and developing countries including the multidimensional headcount and the adjusted headcount ratios. We illustrate these methods with an application to time-trends in poverty in Australia and cross-regional poverty in Peru. Our results highlight the potentially large sensitivity of poverty orderings based on counting measures and the importance of evaluating the robustness of results when performing poverty comparisons across time and regions

Driving precision policy responses to child health and developmental inequities

The growing evidence base on the extent of and opportunities to reduce inequities in children’s health and development still lacks the specificity to inform clear policy decisions. A new phase of research is needed that builds on contemporary directions in precision medicine to develop precision policy making; with the aim to redress child inequities. This would include identifying effective interventions and their ideal time point(s), duration, and intensity to maximise impact. Drawing on existing data sources and innovations in epidemiology and biostatistics would be key. The economic and social gains that could be achieved from reducing child inequities are immense. <br

Understanding Changes in the Distribution and Redistribution of Income: A Unifying Decomposition Framework

In recent decades income inequality has increased in many developed countries but the role of tax and transfer reforms is often poorly understood. We propose a new method allowing for the decomposition of historical changes in income distribution and redistribution measures into: (i) the immediate effect of tax-transfer policy reforms in the absence of behavioral responses; (ii) the effect of labor supply responses induced by these reforms; and (iii) a third component allowing us to explore the effect of changes in the distribution of a wide range of determinants, including the effect of employment changes not induced by policy reforms. The application of the decomposition to Australia reveals that the direct effect of tax-transfer policy reforms accounts for half of the observed increase in income inequality between 1999 and 2008, while the increased dispersion of wages and capital incomes also played an important role

Modelling income data using two extensions of the exponential distribution

In this paper we propose two extensions of the Exponential model to describe income distributions. The Exponential ArcTan (EAT) and the composite EAT–Lognormal models discussed in this paper preserve key properties of the Exponential model including its capacity to model distributions with zero incomes. This is an important feature as the presence of zeros conditions the modelling of income distributions as it rules out the possibility of using many parametric models commonly used in the literature. Many researchers opt for excluding the zeros from the analysis, however, this may not be a sensible approach especially when the number of zeros is large or if one is interested in accurately describing the lower part of the distribution. We apply the EAT and the EAT–Lognormal models to study the distribution of incomes in Australia for the period 2001–2012. We find that these models in general outperform the Gamma and Exponential models while preserving the capacity of the latter to model zeros

Childcare Use and Its Role in Indigenous Child Development: Evidence from the Longitudinal Study of Indigenous Children in Australia

We investigate patterns of childcare use and its influence on the cognitive development of Indigenous children. The influence of childcare on Indigenous children's cognitive outcomes is less well understood than for non-Indigenous children due to a lack of appropriate data. We focus on a cohort of Indigenous children in Australia who have been followed from infancy and for whom rich information on childcare use and cognitive outcomes is observed. Compared to Indigenous children who never participated in childcare, Indigenous children who participated in childcare performed better on several early cognitive outcomes. Using regression and propensity score matching, we show that this difference is driven by selection into childcare, with children from more advantaged families being more likely to attend formal childcare. However, matching analysis results suggest that relatively disadvantaged children might benefit more from attending childcare, as indicated by the positive estimated effects found for those who never attended childcare

Socio-economic groups moving apart: An analysis of recent trends in residential segregation in Australia's main capital cities

© 2021 The Authors. Population, Space and Place published by John Wiley & Sons Ltd. We study changes in the spatial distribution and segregation of socio-economic groups in Australia using a new data set with harmonised census data for 1991 and 2011. We find a general increase in residential segregation by education and occupation groups across the major capital cities in Australia. Importantly, these trends cannot be explained in general by changes in the demographic structure of groups and areas but rather by the rise in the over and underrepresentation of groups across areas. In particular, our analysis reveals clear diverging trends in the spatial configuration of high and low socio-economic groups as measured by their occupation and education. Whereas high-skilled groups became more concentrated in the inner parts of cities, the low-educated and those working in low-status occupations became increasingly overrepresented in outer areas. This pattern is observed in all five major capital cities, but it is especially marked in Sydney, Melbourne and Brisbane