TY - JOUR TI - Measuring small area inequality using spatial microsimulation: Lessons learned from Australia AU - Miranti, Riyana AU - Cassells, Rebecca AU - Vidyattama, Yogi AU - McNamara, Justine VL - 8 IS - 2 PY - 2015 DA - 2015/08/31 SP - 152-175 C1 - IJM 2015;8(2):152-175 DO - 10.34196/ijm.00118 UR - https://doi.org/10.34196/ijm.00118 AB - Measuring income inequality has long been of interest in applied social and economic research in the OECD countries including Australia. This includes measuring income inequality at the regional level. In this article, we have used spatial microsimulation techniques to calculate small area inequality in Australia using disposable income data which are not available at a small area level, drawing together data from the Australian Census and survey data. Using disposable income data increases the strength of the results, as a more accurate measure of income distribution is able to be obtained. We estimate inequality at a small area level for the two most populous states in Australia – New South Wales and Victoria using conventional Gini coefficient methodology. We also examine the differences in inequality between the densely populated capital cities of each state and the balance of these states or rural areas. The results show that there are marked variations in inequality with distinct pockets of small areas with high income inequality in both states and their capital cities. The small area inequality estimation enables the policy maker to pinpoint pockets of inequality. This will be useful to identify regions that need better targeting/interventions. KW - income inequality KW - spatial microsimulation KW - small area JF - IJM SN - 1747-5864 PB - International Journal of Microsimulation ER -