Tag Archives: covid19australia

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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?

Big Data Improves with Age

Category:Labour MarketTags : 

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.

https://www.abs.gov.au/methodologies/weekly-payroll-jobs-and-wages-australia-methodology/week-ending-5-september-2020#data-limitations-and-revisions

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.

Covid Jobs update from John Black, CEO of Education Geographics, October 6, 2020.

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.

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?

 

Suburban Stereotypes - 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?

 

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.


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Covid Jobs update from John Black, CEO of Education Geographics, October 6, 2020.

Newer Isn’t Always Better

Category:Labour MarketTags : 

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.

https://www.abs.gov.au/methodologies/weekly-payroll-jobs-and-wages-australia-methodology/week-ending-5-september-2020#data-limitations-and-revisions

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.

Covid Jobs update from John Black, CEO of Education Geographics, October 6, 2020.

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.

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?

 

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?

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.

 


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Watching The Watchers

Category:Labour MarketTags : 

Covid Jobs update from John Black, CEO of Education Geographics, September 23, 2020.

So which groups and regions have been losing jobs under the Covid-19 job lockdowns? Not necessarily who you’d have thought, as it turns out.

And what impact is losing your job likely to have on your vote? Frankly, the polls seem to show the voters distinguishing between the political management of Covid lockdowns and their future voting intention.

It seems that inspirational leadership at times of great stress doesn’t necessary get you re-elected – as Winston Churchill discovered after World War 2.

I think the safest bet at the moment is to look at winners and losers from the lockdown and check out their most recent voting intention. Actual jobs held or lost and actual votes cast. A lifetime in journalism has taught me that evidence and truth are always handy friends to fall back on.

On that note, we’ve been monitoring the ABS experimental estimates on the impact of COVID-19 job lockdowns on payroll jobs and wages, since mid-March. There’s been a fair bit of retrospective adjustments by the ABS to the data, particularly that for wages, but there are some useful insights to be gained from the data for our clients across the country.

For example, we have been able to make reasonable estimates of SA2 suburb jobs data from the demographic profiles in the ABS regular releases and the SA4 spatial data released by the ABS. Being able to rely on fortnightly national jobs data for 10 million income earners is a lot more spatially powerful than trying to leverage up a sample of 25,000 from 88 national regions.

It all sounds a bit dry, until you start to profile these relatively fine-grained spatial results against our big education database or map them across regions.

We’re going to share some of these over the coming few months, as time permits. The data in these charts is from the period up to early August and we’ll release more in the coming month, from payroll data released this week.

The charts shown here are based on all Australian suburbs outside of Victoria. We left Victoria out of this profile as the results were so negative, relative to the other states (2.9 percent of jobs lost outside Victoria, compared to 6.4 percent lost in Victoria) that it hopelessly distorted the national profiles.

The patterns in Victoria were reasonably similar however, just a lot more emphatic in terms of winners and losers, with a lot more of the latter than the former.

One exception here was miners and the longer term unemployed. In other states where Governments have been able to control Covid outbreaks more effectively, these two demographics live in suburbs which have fared a lot better. This may have something to do with FIFO miners in Melbourne not being able to get to work in other states, due to their state-wide lockdowns – we just don’t know. Some more mining jobs in Victoria in future would certainly assist here.

First we take a closer look at our traditional stereotypes, to see how they’ve fared.

The above profile chart shows suburb-level jobs gained, for the gold bars above the line and jobs lost, below the line. We’re talking here about jobs gained or lost by suburbs, relative to a (non-Victorian) Australian average jobs loss of about three percent to early August. So those stereotypes above the line are a bit like boats rowing home hard against an outgoing tide. They have to be doing pretty well against the current, just to make it back to the jetty.

The green bars (RHS) show the national means for each of the stereotypes. The five on the right are scores standardised to 100 while the activist pro-Rudd refers to a smaller group of families typically found in semi-rural areas – the sort of families who voted Kevin Rudd into office in 2007 at the expense of John Howard, but who also put Scott Morrison into office in 2019. This smaller group has a lot of clout in Queensland marginal seats and it is now doing ok. Not spectacular, but ok.

The other demographics who re-elected the Coalition are doing even better, relatively speaking, under Covid job lockdowns.

We’re looking here at Working Families (Tradie Dad, Mum in a Clerical job and two kids at home) whose jobs are holding, at least outside Victoria. These are big urban and provincial city groups in many marginal Labor or Coalition seats, and this infers Scott Morrison is on his way to growing his own version of the old Howard Battlers in Queensland and western Sydney.

Other groups doing well include the big outer suburban stereotype volatile group of Swinging Voters (young marrieds, with kids and a mortgage and very tight budgets), which seems to explain why support for the Federal Coalition is fluctuating, but also generally on or above 50 percent.

Finally, we have the Digitally Disrupted, a big urban stereotype of machine operators and unskilled blue-collar workers, often found in manufacturing industry jobs – another big group to swing away from Bill Shorten at the last Federal election in many safe or marginal Labor seats.

Guess which of the boats aren’t making it back to the jetty tonight? The Goat Cheese Circle and the inner urban twenty-something students we called the Coming of Age stereotype. The Goat Cheese Circle group are high-income, professional couples living within an easy commute of the CBD and Coming of Age kids can be found in the CBD or in University suburbs or regional centres, chasing hospitality jobs which no longer exist.

These stereotypes are found in the suburbs faring the worst in what is already a pretty bleak jobs market.

To help you gauge the political significance of these labour market changes, we show the vote profiles from the 2019 election for the 2PP vote and swing and for the Green primary vote.

The actual vote profile for Labor or for the Coalition isn’t significant. The Green voter profile however is certainly showing that the (young) Green 2019 voters are more likely to be found in suburbs losing the most jobs. This isn’t surprising when we look at the number of students now out of work and the dominant role students play in the Coming of Age stereotype.

The really significant swings are found among the Goat Cheese Circle suburbs where we find both well paid professionals and University students. These are the groups which swung heavily against the Coalition in Victoria in recent State and Federal elections in previously safe Coalition seats.

If you put both of these demographics in the same tinny, well then, they’re rowing in the wrong direction to make it back to the jetty tonight.

These are the major demographic foundations which will determine the outcome of the next elections.

Are they going to blame the Federal Coalition Government for their lost jobs? Or are they looking for some leadership from the Labor Party, after swinging their vote behind Labor, many for the first time, in 2019.

And how is the upcoming Budget likely to play out with these groups?

We’ll keep you posted.