No abstract

I use variation in the age at which children move to show that where an Australian child grows up has a causal effect on their adult income, education, marriage, and fertility. In doing so, I replicate the findings of Chetty and Hendren (2018a) in a country with less inequality, more social mobility, and different institutions. Across all outcomes, place typically matters most during the teenage years. Finally, I provide suggestive evidence of peer effects using cross-cohort variation in the peers of permanent postcode residents: those born into a richer cohort for their postcode tend to end up with higher incomes themselves. (JEL D63, J13, J62, R23, Z13)

We use the 1 July 2004 introduction of the Australian Baby Bonus to identify the effect of family income on child test scores at grade three. Using a difference‐in‐differences design, we find no evidence that the Baby Bonus improved child outcomes in aggregate, but some evidence of a modest effect for children from disadvantaged backgrounds. We examine whether birth shifting associated with the Baby Bonus and two other Australian maternity payments had negative long‐term effects on children. Despite widespread concerns about this unintended treatment, regression discontinuity estimates provide no clear evidence of lasting health or educational consequences.

We examine the relationship between immigration to Australia and the labour market outcomes of Australian‐born workers. We use immigrant supply changes in skill groups, defined by education and experience, to identify the impact of immigration on the labour market. We find that immigration flows into those skill groups that have the highest earnings and lowest unemployment. Once we control for the impact of experience and education on labour market outcomes, we find almost no evidence that immigration harms the labour market outcomes of those born in Australia.

The literature on intergenerational income mobility uses a diverse set of measures and there is limited knowledge about whether these measures provide similar information and yield similar conclusions. We provide a framework to highlight the key concepts and properties of the different estimators. We then show how these measures relate to one another empirically. Our main analysis uses income tax data from Australia to produce a comprehensive set of empirical estimates for each of 19 different mobility measures at both the national and regional level. We supplement this analysis with other data that uses either within or between country variation in mobility measures. A key finding is that there is a clear distinction between relative and absolute measures both conceptually and empirically. A region may be high with respect to absolute mobility but could be low with respect to relative mobility. However, within broad categories, the different mobility measures tend to be highly correlated. For rank-based estimators, we highlight the importance of how the choice of the distribution used for calculating ranks can play a critical role in determining its properties as well as affect empirical findings. These patterns of results are important for policy makers whose local economy might fare well according to some mobility indicators but not others. * This article was prepared for the Journal of Economic Literature and is under review. We thank Steven Durlauf for helpful guidance and anonymous reviewers for their comments. We also thank Francisco Ferreira and Markus Jäntti for helpful comments and participants at the workshop on Aging, Family and Social Insurance in Solstrand, Norway and the ZEW Workshop on Social Mobility and Economic Performance for their feedback, and Aastha Rajan for excellent research assistance. This research uses data from the Australian Taxation Office. All findings, opinions and conclusions are those of the authors and do not necessarily represent the views of the Australian Government or any of its agencies. The views expressed here do not reflect those of the Federal Reserve Bank of Chicago or the Federal Reserve system or the Australian Treasury. The research plan was approved by the Australian National University Human Ethics Committee, protocol number 2017/832.