How female participation has effected QLD’s regions

A few weeks ago we wrote a post on some work we had done breaking down changes in Participation Rates in QLD regions to discover the impact that changes to the age profile of the working population had (you can read that here). That post attracted some interest and one comment made quite strongly was a desire to see a similar analysis done to consider the impact of changes in the Participation Rates across the sexes. We have now completed that work and the results, along with the similar results from the age related analysis, are tabled below. In both cases we are considering the changes in participation from October 1998 (start of the regional level data set) and January 2019 across the SA4 regions of QLD.

When considering the effects of changes within the sexes we have split out the Propensity effect for both male and female. The Demographic effect, in this case, relates to changes in the male/female make-up of the working population, which in general are small. For details as to what the Propensity and Demographic effects are, and how they are calculated, please refer to our earlier post.

There is a lot to take in here, and analysis of individual regions would take some time, however we can see some overriding conclusions that are worth highlighting.

  • The effect of age demographic changes (in general an ageing of the working population) has been almost universally negative on total Participation Rates.
  • The effect of an ageing population has had a far greater effect in the Rest of QLD than in Greater Brisbane.
  • The effect of demographic changes between male and female are small (except in a few specific instances where shifts in the male/female split has been great)
  • The change in female participation has had an almost universally positive effect on total Participation Rates across the regions. Where the effect has been negative it has been far less so than the negative effect of male participation declines.

Changes can be considered over different time periods, as we did in our earlier post, but we have tried to keep things relatively simple in this post. Anyone wishing to have access to the data behind these conclusions, or the underlying data, are welcome to contact Pete Faulkner at pete@conus.com.au to discuss.

 

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