Old, Single and Poor: Using Microsimulation and Microdata to Analyse Poverty and the Impact of Policy Change among Older Australians*

Abstract

In recent months in Australia there has been extended debate about whether the age pension, particularly with regard to single pensioners, is sufficiently high to allow older Australians to attain an acceptable standard of living. This is an important policy consideration given Australia’s rapidly ageing population. By using microdata and microsimulation models, this paper examines the national and spatial impacts on the distribution of poverty among older single people of an increase in the single age‐pension rate. This paper shows that the cost of increasing the single age‐pension to 66 per cent of the couple‐age pension rate would be about $A1.3 billion and would benefit about 824,000 single age‐pensioners. Further, it is estimated that such an increase would reduce poverty rates for lone older persons from 46.5 per cent to 36.5 per cent, a 10‐percentage point reduction. Looking at the spatial distribution of such benefits, the effect of the policy change seems to be generally stronger in capital cities, and in bands of rural areas in New South Wales and Victoria.

Poverty at the Local Level: National and Small Area Poverty Estimates by Family Type for Australia in 2006

“…By knowing where concentrations of disadvantage are located, policy makers and service providers can allocate resources and target policies better. Recent applications of this spatial microsimulation technique to modelled policy changes can be found in Harding et al (2009b) and Tanton et al (2009a), an approach which allows policy makers to see the spatial effect of proposed policies.…”

The Challenges of Combining Two Databases in Small-Area Estimation: An Example Using Spatial Microsimulation of Child Poverty

“…Examples of this work include simulating the small-area impact of changes in income taxes and cash transfers (Chin et al, 2005;Harding et al, 2009;Tanton et al, 2009); development of small-area measures of housing stress ; the need for different types of aged care (Lymer et al, 2008;; and the retirement saving by gender of those who have just retired .…”

“…One crucial indicator that has often been produced and updated for various different population groups is poverty rates, as this measure is not otherwise available at a small-area level in Australia (Chin and Harding, 2007;Miranti et al, 2011 ;Tanton et al, 2009). The primary reason why spatial microsimulation has been used to estimate small-area poverty in Australia is because the income variable from the Australian Census of Population and Housing (hereafter, census) is a measure of equivalised gross household income (variable HIED in the 2006 Census data) which is available only in income ranges.…”

Spatial microsimulation as a method for estimating different poverty rates in Australia

“…Advances in spatial microsimulation have meant that the ability to see the effect of policy changes for small areas is now possible (Ballas et al , 2003; Harding et al , 2008; Tanton et al , 2008). Further, using the spatial microsimulation approach, estimates of poverty for subgroups of the population can easily be calculated (Anderson, 2007a; Ballas et al , 2007; Miranti et al , 2008b; Tanton et al , 2008; Brewer et al , 2009).…”