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Lifecycle Earnings Risk and Insurance: New Evidence from Australia


Darapheak Tin and Chung Tran

Abstract: We study the nature of lifecycle earnings dynamics by documenting higher-order moments of earnings shocks over the lifecycle, using the Household, Income and Labour Dynamics in Australia (HILDA) Survey 2001-2020. Similar to other countries (e.g. see Guvenen et al. (2021) and De Nardi et al. (2021)), the distribution of earnings shocks in Australia displays negative skewness and excess kurtosis, deviating from the conventional linearity and normality assumptions. However, the sources of fluctuations and the role of family and government insurance are quite different. Wages account more for the dispersion of earnings shocks (second-order risk), while hours drive the negative skewness and excess kurtosis (third- and fourth-order risks, respectively). Wage changes are strongly associated with earnings changes, whereas hour changes are largely absent in upward movement and relatively small in downward movement of earnings changes. Family insurance via pooling income of family members and adjusting labor market activities of secondary earners, and government insurance embedded in the progressive tax and transfer system play distinct roles in reducing risks over age and by income group. Government insurance is more important in mitigating the dispersion of earnings shocks; meanwhile, family insurance is more dominant in mitigating the magnitude and likelihood of extreme and rare shocks. Family insurance interacts with government insurance; however, their joint forces fail to eliminate the non-Gaussian and non-linear features. Furthermore, comparison between groups reveals: (i) the risk equalizing effect of government insurance, and (ii) the persistent nature of risks for certain demographics such as female heads of household and non-parents. Hence, our findings shed new insights into the complexity of earnings dynamics and the importance of family and government insurance.

Keywords: Income dynamics; Earnings risk; Higher-order moments; Non-Gaussian shocks; Family insurance; Government insurance; Inequality.


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