🎙Steve Austin interviews John Black, Founder of Education Geographics.
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John discusses with Steve the role of aspirational parents and a stronger labour market in driving the long-term growth of Non-Government schools.
The discussion covers the medium-term impact on Non-Government school enrolments of the Covid lockdowns and the Government Stimulus.
Also covered is the long-term impact of a drop in Australia’s population, compared to pre-Covid projections, and the areas which have been the most impacted during the pandemic lockdowns and for the 20 years after it.
When it comes to their new Weekly Payroll Jobs and Wages series, the ABS this week agreed with our ADS post of October 6, 2020: Newer isn’t always better (reproduced below.)
With their latest payroll data release this week, the ABS announced it would extend the time between the final payroll period and the release date, by around 9 days. The ABS says this will improve the quality of estimates, through reducing the level of imputation (by more than half) and revisions in the most recent weeks of data.
For our explanation from last October, you can read our original post below.
Newer isn’t always Better – Covid Jobs update from John Black, CEO of Education Geographics, October 6, 2020.
A week or so back we provided a profile of how the broader Australian stereotypes were faring under Covid jobs lockdowns and today we’re urging a bit of caution when it comes to rushing to judgement on the latest payroll stats – because newer isn’t always better.
Although they don’t quite put it like this, the Australian Bureau of Statistics and I both agree the payroll stats are like a fine bottle of red … you’re well advised to let them age a little after opening, before taking the first sip and rushing to judgement.
The official explanation is contained in the recent ABS release on the weekly payroll data for the week ending September 5, where you can see a section called data limitations and revisions. You can find the technical explanations through this link.
In this section, the bureau stressed that they were trying to help policy makers during these extraordinary times, by releasing data as close as possible to the period when the activity occurred and then make the data as accurate as possible over time, but incorporating new data when it was received.
This means that the latest data is only about 75 percent to 80 percent complete and can take several months to be fully complete and so the final figures look a lot more attractive after ageing than they do when they’re brand new, as you can see below. Even two weeks of waiting can add one point to the index number for the same release.
So far, so good. But what happens when we check out the profile of the 20 to 25 percent of jobs which come late to the party? Let’s check out our two Stereotype Charts for August 8, with the top one based on the original data and the second one also showing the revised data in yellow bars.
The central thrust of the original data profiles shows the big urban and provincial city Working Families and the younger and more aspirational, outer suburban Swinging Voters both faring relatively well from the impact of the Covid jobs lockdown. By relatively well, we mean relative to a (non-Victorian) Australian average jobs loss of about three percent from mid-March to August 8.
When we take a close look at the changes in index numbers for individual occupations and the suburb profiles for where they tend to live, we see that the industries which tend to improve after revision include the better-paid ones we often find in the Goat Cheese Circle inner suburbs, such as professional consulting, finance, media and real estate.
This means our maps for the loss of jobs across inner suburbs tend to look a lot greener after a month or so, after new employer data has been reported from those employers reporting less frequently than every week.
So, until the ABS has amassed enough single touch payroll data over a few years of relatively stable labour markets, to make regular seasonal adjustments, treat the latest weekly data releases with caution, as the revised data a month or so older, is often more accurate.
Just like an old vine Barossa Shiraz, big data often improves with ageing.
Next update, we’ll take a look at the impact of the Federal Budget on those industries most impacted by jobs lockdowns. Talk to you then.
Covid Jobs update from John Black, CEO of Education Geographics, October 6, 2020.
A week or so back we provided a profile of how the broader Australian stereotypes were faring under Covid jobs lockdowns and today we’re urging a bit of caution when it comes to rushing to judgement on the latest payroll stats – because newer isn’t always better.
Although they don’t quite put it like this, the Australian Bureau of Statistics and I both agree the payroll stats are like a fine bottle of red … you’re well advised to let them age a little after opening, before taking the first sip and rushing to judgement.
The official explanation is contained in the recent ABS release on the weekly payroll data for the week ending September 5, where you can see a section called data limitations and revisions. You can find the technical explanations through this link.
In this section, the bureau stressed that they were trying to help policy makers during these extraordinary times, by releasing data as close as possible to the period when the activity occurred and then make the data as accurate as possible over time, but incorporating new data when it was received.
This means that the latest data is only about 75 percent to 80 percent complete and can take several months to be fully complete and so the final figures look a lot more attractive after ageing than they do when they’re brand new, as you can see below. Even two weeks of waiting can add one point to the index number for the same release.
So far, so good. But what happens when we check out the profile of the 20 to 25 percent of jobs which come late to the party? Let’s check out our two Stereotype Charts for August 8, with the top one based on the original data and the second one also showing the revised data in yellow bars.
The central thrust of the original data profiles shows the big urban and provincial city Working Families and the younger and more aspirational, outer suburban Swinging Voters both faring relatively well from the impact of the Covid jobs lockdown. By relatively well, we mean relative to a (non-Victorian) Australian average jobs loss of about three percent from mid-March to August 8.
When we take a close look at the changes in index numbers for individual occupations and the suburb profiles for where they tend to live, we see that the industries which tend to improve after revision include the better-paid ones we often find in the Goat Cheese Circle inner suburbs, such as professional consulting, finance, media and real estate.
This means our maps for the loss of jobs across inner suburbs tend to look a lot greener after a month or so, after new employer data has been reported from those employers reporting less frequently than every week.
So, until the ABS has amassed enough single touch payroll data over a few years of relatively stable labour markets, to make regular seasonal adjustments, treat the latest weekly data releases with caution, as the revised data a month or so older, is often more accurate.
Just like an old vine Barossa Shiraz, big data often improves with ageing.
Next update, we’ll take a look at the impact of the Federal Budget on those industries most impacted by jobs lockdowns. Talk to you then.
The recovery in many jobs was well under way in May. It’s been most pronounced in those hit first in March/April, working in hospitality, young home buyers, young casual workers also studying at TAFE and this is all to the good.
The downturn however continued in May among farming and rural communities, especially fishing (think lobsters in cargo holds of international tourist flights). This has impacted coastal and many rural communities.
The overall picture from March to the end of May shows mainstream suburban families (married, middle aged, with a mortgage and kids at school, two jobs that they really need, and going to church occasionally) to have been much less affected by Covid or by the follow-up lockdowns – down about five percent. These are the groups which weren’t picked up in the polls before the last election and which re-elected Scott Morrison as PM. Â
The groups in deepest trouble (ten percent plus loss over jobs) over the period March to May were – despite a recovery in May – still the workers in casual hospitality and arts & rec jobs (agnostics, twenty somethings, living in small rental units, single, agnostics, no kids, Green voters).
So, good is down only five percent and getting better slowly. Bad is ten percent and getting worse slowly. Spatially, Tasmania looks pretty awful, as do many rural and coastal communities, but the really horrible bits on the map are the inner-city suburbs, particularly in Melbourne and Sydney, where Covid cases have been most concentrated.
Because the jobs lost in many cases have been second or third casual jobs and less well paid, the impact of jobs lost to the economy has been a bit overstated and has actually increased average incomes per job in many suburban areas, especially with large public sector payrolls.
This is, however, pretty cold comfort, for those relying on Government handouts and counting down to the end of September.
What was the real rate of unemployment in May? The short answer is 11.5 percent. This is obtained by maintaining the pre-Covid lockdown participation rate at the March level of 66.2 percent and applying this to the Civilian population 15 years and over, producing a potential workforce of up to 13, 770,061 in May. The combined numbers of officially unemployed and those who dropped out was 1,579,639. We used original or unadjusted figures as seasonal adjustments have become overwhelmed by Covid lockdowns and only original figures are used spatially for smaller areas. The original unemployment figure was marginally higher at 11.7 percent and 12.1 percent respectively in January and February 1993.
The figure of 11.5 percent also resonates with the new and more immediate ABS series on Weekly Payroll Jobs and Wages, which shows 5.6 percent of main jobs were lost between March 14 and the end of May and the official March unemployment rate was 5.6 percent in March. The two figures sum to 11.2 percent.
This means the current unemployment rate is as bad now as it was during the worst of the recession in the early 1990’s. The unemployment figure then was marginally higher at 11.7 percent and 12.1 percent respectively in January and February 1993.
The current figures for the one touch payroll data have been recovering slowly from the initial impact of the Covid jobs lockdown in early April, and this 11.2 percent hybrid figure is likely to continue (barring a second wave starting off from Victoria) at least until the Government begins to wind back JobKeeper and JobSeeker in September.
The realistic figure for unemployment rates at that time will be determined by whether the rate of recovery exceeds the rate at which those now on JobKeeper or JobSeeker join the ranks of those actively seeking work and satisfying the ABS definition of being unemployed.
The official ABS labour market unemployment rate is now pretty meaningless, as participation rates will tend to decline with relatively older and younger workers dropping out of the labour market.
In fact, the first sign of a recovery in a recessed regional labour market can be an interim increase in the local unemployment rate, as formerly discouraged workers are encouraged to seek work by becoming officially unemployed on a temporary basis, while actively hunting for a job and hence immediately boosting participation rates and then growing employment in the longer term.
So the most useful indicators you should be watching for in coming months are total jobs lost and gained by region and accompanying movements to participation rates.
Text by John Black, founder of ADS and EGS. Maps by Dr. Jeanine McMullan, CEO of Health Geographics.
We trace the jobs impact of the Covid-19 labour market shutdown in a news article and a linked online story map published in The Australian today.
The story outlines the evidence that the jobs downturn impacts announced by the Prime Minister in late March were sudden and deep and that since then, there have already been some tentative signs of a small jobs recovery in those states with lower levels of new Covid-19 cases, in apparent anticipation of an easing of social distancing and travel restrictions. However, in those states with continuing cases of new community transmission the downturn in higher SES professional jobs has deepened.
The article is available only to The Australian readers and subscribers and covers the new payroll data provided to the public by the Australian Bureau of Statistics, as a public service, while the data is still being developed.
A co-operative venture between Australian Development Strategies, Health Geographics and Education Geographics has set out to regularly monitor, profile and map big data on jobs and wages from 10,000,000 Australians during the Covid recession.
The jobs data is now being collected weekly via the Tax Office one touch payroll system and published fortnightly by the Australian Bureau of Statistics.
The first of a series of maps has been published today on the three web sites via the following link https://arcg.is/1HeD5n. It will allow readers to see the impact of the Covid restrictions and monitor changes as they are withdrawn in stages over coming months.
More detailed maps and profiling will be made available to clients of the three companies ADS, HGS and EGS.
The first maps published today show most jobs and wages lost by suburb have been close to capital city CBDs, coming as a direct result of the closure of gyms, personal training groups and theatrical productions.
The biggest per capita loss of jobs has occurred across smaller suburbs in rural and tourist regions like Mount Beauty in Victoria or Port Douglas in far north Queensland.
Suburbs across Australia relatively unaffected by jobs loss or per capita jobs loss have dominated by public sector jobs, such as Duntroon, Macarthur or Barton in the ACT, in remote indigenous communities like the APY lands in South Australia or Arnhem Land in the NT, or in mining towns like Mount Isa or Weipa in Queensland or Roxby Downs in SA.
As schools progressively re-open and restrictions are lifted on travel, hospitality and public gatherings, we will monitor the changes in jobs and wages for our readers and clients.
A demographic profile of Covid-19 begins to emerge from the chaos of the first wave of tests.
Dear Colleagues, this is our second update on Covid-19, based on the data we’ve been able to assemble so far, compiled from spatial profiles of LGA testing results in New South Wales and Victoria. More states providing this LGA data to the public would be greatly appreciated.
It’s important to acknowledge that what we’re looking at with this data is the result of the first wave of testing, mainly centred on Australians returning from overseas holidays.
Many of the older members of this group returned on cruise ships, so much so, that cruise ships have been identified by the Commonwealth as a country in their own right, when it comes to overseas sources of the virus.
The layperson’s profile of this group would say it’s the 60 years and over group, wealthier, retired and the layperson would be pretty right. I guess we all know a bit more about this group, because it’s the one at most risk from serious illness and this justifiably gets the most attention.
Dear Colleagues, due to the changing environment and our response to COVID-19, I will be posting a series of updates on the current research being undertaken by Education Geographics, which may assist Australian Non-Government schools with their 2021 planning. You are welcome to distribute these updates to your school boards and risk assessment committees and your feedback would be appreciated.
At Education Geographics and Australian Development Strategies, we’ve been modelling Non-Government schools and their interaction with the Labour market since 2004.
We’ve noticed that the growth or decline in the number of jobs in a school catchment in the second half of the year tends to drive enrolments up or down in the following year (as you can see in the national chart on Australian Participation rates and Non-Government Market Share from 1998 to 2019).
