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Understanding the Drivers of Poverty Dynamics in Australian Households


  • Buddelmeyer, Hielke

    () (Melbourne Institute of Applied Economic and Social Research)

  • Verick, Sher

    () (ILO International Labour Organization)


Using longitudinal household data and an econometric model of conditional poverty transitions, this paper contributes to the growing literature on poverty dynamics in Australian households. The results reveal that a range of household head, partner and demographic characteristics in addition to life-changing events have an impact on both the likelihood of remaining poor and slipping into poverty. These findings have important implications for Australian policymakers: tertiary education and employment are key factors in keeping households out of poverty; having a disability increases the probability of becoming poor and remaining in such a situation; households in outer-regional or remote areas are more likely to become poor and continue to live under such hardship; and finally, life-changing events, especially becoming separated, can lead households into persistent poverty. These results are robust to a range of poverty definitions. By drawing on research that utilizes such longitudinal data, policymakers will be much better informed about the drivers of material deprivation in Australia and subsequently how best to design policies that target and support the most vulnerable households.

Suggested Citation

  • Buddelmeyer, Hielke & Verick, Sher, 2007. "Understanding the Drivers of Poverty Dynamics in Australian Households," IZA Discussion Papers 2827, Institute for the Study of Labor (IZA).
  • Handle: RePEc:iza:izadps:dp2827

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    References listed on IDEAS

    1. Lorenzo Cappellari & Stephen P. Jenkins, 2004. "Modelling low income transitions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 19(5), pages 593-610.
    2. Ann Huff Stevens, 1999. "Climbing out of Poverty, Falling Back in: Measuring the Persistence of Poverty Over Multiple Spells," Journal of Human Resources, University of Wisconsin Press, vol. 34(3), pages 557-588.
    3. Peter Saunders & Bruce Bradbury, 2006. "Monitoring Trends in Poverty and Income Distribution: Data, Methodology and Measurement," The Economic Record, The Economic Society of Australia, vol. 82(258), pages 341-364, September.
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    Cited by:

    1. Alexander Ahammer & Stefan Kranzinger, 2017. "Poverty in Times of Crisis," Economics working papers 2017-03, Department of Economics, Johannes Kepler University Linz, Austria.
    2. FUSCO Alessio & ISLAM Nizamul, 2012. "Understanding the drivers of low income transitions in Luxembourg," LISER Working Paper Series 2012-31, LISER.
    3. Aysenur Acar & Cem Baslevent, 2014. "Examination of the Transitions of Households into and out of Poverty in Turkey," Working Papers 015, Bahcesehir University, Betam.
    4. Elliott Fan & Chris Ryan, 2011. "Reconciling income mobility and welfare persistence," CEPR Discussion Papers 651, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    5. REINSTADLER Anne & RAY Jean-Claude, 2010. "Macro Determinants of Individual Income Poverty in 93 Regions of Europe," LISER Working Paper Series 2010-13, LISER.
    6. Ayşenur Acar & Cem Baslevent, 2013. "Examination of the transition of Turkish households into and out of poverty between 2007-2010," EcoMod2013 5779, EcoMod.
    7. Sara Ayllón, 2013. "Understanding poverty persistence in Spain," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 4(2), pages 201-233, June.
    8. Mitra, Sophie & Posarac, Aleksandra & Vick, Brandon, 2011. "Disability and poverty in developing countries : a snapshot from the world health survey," Social Protection and Labor Policy and Technical Notes 62564, The World Bank.
    9. Birhanu, Mulugeta Y. & Ambaw, Birhanu & Mulu, Yohannis, 2017. "Dynamics of multidimensional child poverty and its triggers: Evidence from Ethiopia using Multilevel Mixed Effect Model," MPRA Paper 79377, University Library of Munich, Germany.

    More about this item


    household panel data; poverty dynamics; state dependence; attrition;

    JEL classification:

    • D31 - Microeconomics - - Distribution - - - Personal Income and Wealth Distribution
    • I32 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Measurement and Analysis of Poverty
    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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