Politics, elections and piffle plinking

The 2012 State of Play

   

As we all get reacquainted with the madness that is the first week of the new political season, the time is ripe to do a bit of a comprehensive rundown about the actual state of play of  our political polling. We’ll start off looking at the trends and finish with an election simulation for the December quarter.

First up, the two party preferred trend might surprise a few folks that take their media polling commentary too seriously – it reminds me of a line from Chicken Run, “the polling flashed before my eyes, and it was really boring”.

Over the 3 months from mid November, nothing has changed at all in the two party preferred status – zip, zilch, nadda. Federal politics has been glued to a 54/46 split for nearly 90 days straight.

The primary votes however are a little more interesting, with some compositional change occurring underneath that rather dull looking straight line.

 

 

While the Labor primary continues to recover from its July tanking – albeit at a pace not dissimilar to continental drift over the last few months – Coalition primary support fell to 46% at the end of last year, before bouncing back slightly post Christmas. It’s interesting to ponder whether that is an effective Coalition vote floor under the prevailing dynamics.

Meanwhile, the Greens continued their year long voyage of exploring political life between 11 and 12% public support and the broad “Others”  - apart from pollsters having considerable variation in their vote estimates for this rag tag group – appeared to show a continuation of the slow fade that started after their June 2011 highs.

As of last weekend, the actual point estimates of the trends and the changes from the last election look like this:

The government has a 5.4% swing away from them on the primary vote, washing out to a slightly smaller 4.3% swing away from them on the two party preferred. The Coalition has picked up 3.1 points on their primary while the Greens have lost 0.4 points. The broad “Others” have picked up 2.7 since the 2010 election.

Moving on now to December quarter’s election simulation. For those not familiar with it, we grab three months worth of polling from the major pollsters and a few bits of unpublished stuff (usually giving us a pooled sample of around the 13 to 15 thousand mark), break it down by geography (by state first and foremost, but also by region when possible), turn the derived swings from those polling results into probability distributions for each seat (taking account of their sub-state geography)  –then test those swings against the current seat margins about a million times with a monte carlo simulation and aggregate the results. We end up with a simulated election that shows us how many seats would have changed were an election held during that period and the results of the election closely resembled the polling.

First up, the state based swings the government found themselves facing in the December quarter:

The Coalition was experiencing a two party preferred swing towards them in all states and territories, and in both capital cities and regional areas. Seeing how that plays out in seat terms with our simulation, we get:

During the December quarter, the polling had the government facing an election outcome of 53 seats in the 150 seat House of Representatives. Zooming in to the tasty bit:

The ALP had a 65% implied probability of winning at least 52 seats, dropping down to 53.1% for winning 53 seats (the most likely outcome) before dropping further to a 42% implied probability of winning at least 54 seats.

While that is pretty dismal for the government by just about any yardstick – it was actually a significant improvement over the September quarter results. It’s worth comparing the two (you’ll have to click to expand this one):

In the September quarter simulation, the government was looking at only 43 seats, while the December quarter showed a 10 seat improvement across the probability spectrum for Labor. We can see where the improvement came from by looking at how the State breakdowns changed over the period.

While the two party preferred only increased by 2.1% nationally for the ALP, they made 3.1% gains in Qld, 3.7% gains in regional Australia and 5.2% gains in South Australia. On the other hand, Victoria was flat and the capital cities only moved by 1.2% over the September quarter to December quarter period.

Worth mentioning is that the ALP is currently sitting 1.1% higher on the two party preferred than they experienced in the December quarter (currently 45.8% as opposed to the 44.7% achieved over the October to December period) – mostly because of the relatively poor October results. So the current trend polling would have them somewhere around 5 or 6 seats better off at the moment than they were during the final 3 months of last year.

But the story at the moment is not so much the relatively poor state of Labor’s electoral prospects based on current polling, but the fact that the two party preferred trend line has been unmoved for around 90 days. I can’t find another example of 90 days of nothing in federal polling going back to the mid 1980’s, even over a Christmas break. Usually you get some movement – a bit here, a bit there. This one – flat as a tack.

 

Australian Exceptionalism

   

Australian Exceptionalism”…. let that phrase roll off your tongue.

Now stop laughing for a moment if you can!

There’s something about that phrase that just doesn’t sit right with us. We’re not only unaccustomed to thinking about ourselves that way, but for many it’s a concept that is one part distasteful to three parts utterly ridiculous – try mentioning it in polite company sometime. Bring a helmet.

We’ll often laugh at the cognitive dissonance displayed by our American cousins when they start banging on about American Exceptionalism – waxing lyrical about  the assumed ascendancy of their national exploits while they’re forced to take out a second mortgage to pay for a run of the mill medical procedure. That talk of exceptionalism has become little more than an exceptional disregard for the truth of their own comparative circumstances.

But in truth, we both share that common ignorance  – we share a common state of denial about the hard realities of our own accomplishments compared to those of the rest of the world. While the Americans so often manifest it as a belief that they and they alone are the global benchmark for all human achievement,  we simply refuse to acknowledge our own affluence and privilege – denialists of own hard won triumphs, often hysterically so.

Never before has there been a nation so completely oblivious to not just their own successes, but the sheer enormity of them, than Australia today.

In some respects, we have a long standing cultural disposition towards playing down any national accomplishment not achieved on a sporting field – one of the more bizarre national psychopathologies in the global pantheon of odd cultural behaviours – but to such an extreme have we taken this, we are no longer capable of seeing an honest reflection of ourselves in the mirror.

We see instead a distorted, self absorbed cliché of ourselves bordering on parody – struggling victims of tough social and economic circumstances that are not just entirely fictional, but comically separated from the reality of the world around us.

So preoccupied have we become with our own imagined hardships, so oblivious are we to the reality of our privileged circumstances, that when households earning  over $150,000 a year complain about having government welfare payments scaled back, many of us treat it as a legitimate grievance.

Somewhere along the highway to prosperity – and an eight lane highway it has been – far too many of us somehow managed to confuse Cost Of Lifestyle with Cost Of Living. We managed to confuse government assistance as a means to enable the less well off to achieve a better standard of living and greater opportunity, with government assistance being a god given right to fund the self indulgences of an aspirational lifestyle choice beyond our income means. Too many of us have demanded our dreams be handed to us on a plate, and if our income couldn’t provide for them, we demanded that government should give us handouts to make up the difference.

So let us take a hard look at our economic reality.

Over the medium term, our broader economic performance has been nothing short of astonishing. Before the resources boom was even a twinkle in the eye of Chinese poverty alleviation, our performance was world beating – that is worth keeping in your thought orbit. Big Dirt has a bad habit of propagandising about their own contributions and the Australian public has a bad habit of believing them when it comes to our own national development of late.

Imagine if, in 1985, all OECD economies had exactly 100 units of GDP each. If we then tracked the growth of that GDP (using OECD data) over time with the actual growth rates achieved during that period (creating a basic index) – this is how economies changed (click to expand the charts)

Only Turkey, Israel, Ireland and Korea have experienced more growth – with Turkey and Korea pursuing the change from developing to developed status, Israel partially so as well and Ireland recovering from the economic lethargy of civil war, we are the highest growing country that can be remotely called a developed country with no unusual circumstances. Putting this into context, let’s trace that growth over the last 25 odd years with some of the countries we are often compared to.

It’s kind of mind blowing – we grew faster, significantly faster, than all of the countries we are usually compared to, including over the period before the resources boom. But you ain’t seen nothing yet.

What about the distribution of that growth”, I hear you ask. “The poor missed out” you might also be tempted to add.

Using data from the freshly minted OECD report on international comparisons of income distribution and inequality, where the average income growth per year was measured among countries between the mid 1980’s and the late 2000’s, what we find is that Australia left just about everyone else for dead. Not just at the average, or total household income level, but also with the size of the income growth among the poorest  10% of our households *and* the richest 10% of our households.

First up, total population income growth in blue, bottom decile income growth (the poorest 10% of households) in red and the top decile income growth (the wealthiest 10%) in green for all OECD countries.

       

 It’s interesting to note that the only countries where the poorest  10% of households experienced faster income growth than Australia was 4 of the five PIIGS countries – the current basket cases of Europe. Something might be said there about false growth and swings and roundabouts.

Looking at how our growth here compared to the usual suspects:

And for direct comparison:

It is true that the income of the wealthiest 10% of households in Australia grew faster than the income of the poorest 10% of households – the income of Australia’s wealthiest 10% of households grew faster than any other cohort in the OECD. But it’s also true that our poorest 10% of households experienced faster income growth than any country other than Spain and Ireland (who are now quickly reversing that growth with their economic woes) , and faster income growth than the top 10% of wealthiest households in *every other country*.

The income of our poor grew faster than the income of everyone else’s rich. Just chew on that reality for a bit. Let it roll around in your head.

While you’re chewing on that, let’s take a quick squiz at minimum wages. Again, using OECD data, if we turn hourly minimum wages into US dollar equivalents using purchasing power parity adjustments (so we can compare like with like), we can see how the real hourly minimum wage has operated in Australia compared to the nations we’re usually put in the same bucket with.

We have the highest minimum wages in the OECD.  Worth noting too that despite the incessant whinging from the usual business lobbies in Australia, it hasn’t done our economic activity any harm. Now if we compare the ratio of these minimum wages to the average wage for each country, giving us a simple glance at the distribution of wages for each country (which the OECD also fortuitously provides, saving us time), what we find is that Australia, again, sits on top.

Our minimum wage is a lot closer to our average wage than comparable nations.

So our economy has grown faster than nearly all others, our household income has grown faster than nearly all others (including our poor having income growth higher than everyone else’s rich) and we have the highest minimum wages in the world. But wait, there’s more! Read More »

How Australian Pollsters lean

   

One of the questions that often gets asked is whether a given pollster generally delivers a higher vote estimate for a party than other pollsters – basically, whether a polling firm such as, say, Newspoll (to choose a random polling organisation), leans towards one party or the other.

We can never really tell if any pollster delivers results that are actually higher or lower for a party than other pollsters, because we just don’t have elections every week to determine the true state of public opinion with which to judge them against. However, we can look at relative leans – how pollsters lean for or against a party on the vote estimates compared to what other pollsters are doing at the same time.

It doesn’t tell us who is more accurate – and that’s an important factoid to keep in your thought orbit here – but rather, it tells us how pollsters behave comparatively to each other.

To get us into the groove – and something you may not have seen in a while – this is how the primary vote estimates and the two party preferred vote estimates look like since September 2010  for the four public pollsters we regularly track. Click to expand each chart

 

   

  

These charts are interesting enough – you can sort of see the way some polling firms look like they produce results often more favourable to one party than the other. However, to really examine any relative lean, we need to go a little deeper.

The first thing we need to do is have a yardstick from which to compare the pollsters against. Thankfully, we already have a perfect tool for this – our Pollytrend estimates. Just to refresh, our Pollytrend estimates are based on an aggregation of the most recent poll from all pollsters we track, weighted by both sample size and time. So the older a poll is, the less weight it has in our trend and similarly, the smaller the sample size, the less weight it has in our trend. As a new poll gets released by a pollster, that new poll replaces the previous poll of that pollster in the algorithm. As far as I can see, there isn’t a more theoretically accurate estimate of the true state of political public opinion in Australia than our Pollytrend series – which makes it kind of handy for what we want to do.

The other thing we need to be mindful of here is to only compare temporal like-with-like in the polling results. Not all pollsters produce the same amount of polls, so we have to take that into consideration. Essential Report comes out every week, Newspoll once a fortnight, Nielsen once a month and Morgan’s Phone Poll (we don’t use their face to face results here) gets produced whenever it gets produced.

To control for the different quantities of polls for each of the pollsters, we’ll compare their poll results to the Pollytrend result that occurred on the last date that a given poll was in the field. So each pollster gets each of their polls compared to the Pollytrend result that existed at the time each poll was undertaken. Rather than do it for the primary votes and the two party preferred, we’ll just use the two party preferred results – and we’ll use ALP two party preferred results as our reference.

Once we separate the pollsters and look at how their results compared with the Pollytrend results occurring at the same time, this is what it all looks like. Just click on each chart to expand.

 

   

    

 

You can start to get a feel for the way each pollster leans relative to what the pollsters were saying collectively. To make it more interesting,  we can take the difference between each pollster’s ALP two party preferred result and the equivalent Pollytrend – again, click to expand the charts

   

    

 

Taking the Essential Media chart– the producer of Essential Report – to use as an example, what we see is that after March this year, Essential Report consistently produced ALP Two Party Preferred results that were a point or two higher than our Pollytrend. At the other end, Nielsen up until July this year produced ALP two party preferred results that were consistently a few points lower for Labor than what our trend measures were showing at the time.

If we average these differences out, we find that two pollsters lean towards Labor (in that they produce results usually more favourable for Labor compared to Pollytrend) and two lean away from Labor (producing results generally more favourable for the Coalition)…. which makes sense considering.

All our pollsters here have relative leans under 1%, so it’s hardly earthshaking stuff –  and it certainly isn’t “bias” in any respectable sense of the word. Rather, Nielsen and Morgan tend to be more favourable to the Coalition by a small margin while EMC and Newspoll tend to be more favourable to Labor by a small margin – at least compared to what the aggregated results of all the pollsters together were saying at any given time.

So yes – our pollsters do lean relative to each other, but not by much, and at varying levels of consistency.

Trend Updates for November

   

Updating our Pollytrend estimates for the last month’s worth of polling shows a substantial move back to Labor of around 3 points of two party preferred, all coming directly from a 3 point boost to their primary vote over the same period.

Looking first at the primary vote trends, we have (click to expand)

   

 

The Coalition peaked in July with a primary vote of 50 – losing 4 points since, all of which moved across to Labor in net terms. That’s lifted Labor’s primary vote from the low of 28 in July up to 32 today. Meanwhile, the Greens continue to hang  around the 12% mark.

In two party preferred terms, we have (click to expand)

There’s been around a 4 and a half point gain to Labor since the lows of July, with 3 of those points coming in over the last 4 to 5 weeks. As you can see from the individual polls, the change hasn’t been some overnight leap, but a much more gradual trend growth in support.

Comparing the current state of play to the last election, we can see that the ALP faces a 4.4% swing against them as of this week – but a much larger 6.2% primary vote swing against them.

Only 2 and half points of that primary vote swing have been picked up by the Coalition, a third of a point by the Greens, with the remainder boosting the broad “Others” vote by around 3 points.

So we currently have the Coalition leading Labor on the primaries by around 46 to 32, with the Greens on 12 and a two party preferred of just over 54/46 to the Opposition.

Wipeout

   

With a bag of polling data bursting at the seams, it’s that time of year again where we not only update our Pollytrend metrics, but run some election simulation goodness to see how the polling data for the last three months would have played out if it was reflected in any hypothetical election.

We have the usual Newspoll and Nielsen polls for the simulations, plus a Galaxy for Qld, a couple of unpublished national polls  and unpublished NSW and Victorian polls – giving us an aggregated sample size just shy of 15,000 over the quarterly period from July 1st through to last Tuesday. (made up of around 11,900 from the published and 4000 odd from the others – where there’s nothing significantly  different in those unpublished jobbies that we aren’t seeing in Newspoll, Nielsen and Galaxy anyway, it just tightens up our uncertainty a bit)

First up,  the trend measures.

Last month’s Pollytrend update saw a small movement back to Labor – small, but the largest movement towards them that they had experienced since the election last year. Suffice to say, that movement back to the ALP troughed out and is now in slight reverse.

The current point estimates on the trend have the Coalition sitting on 57.3% to Labor’s 42.7% on the two party preferred.

On the primary vote trends (conveniently available on the sidebar to your right) we have Labor bouncing around in palliative care on 28.3, the Coalition hanging around 48.7 and the Greens moving up a point or so over the last month to come in at 12.3. This gives us a whopping 9.7% primary vote swing against the government, washing  out into a 7.5% two party preferred swing towards the Coalition (off the back of a 5.1% primary vote swing towards the Opposition). The Greens meanwhile are slightly ahead of their 2010 election results by 0.6%.

Looking at the longer term primary vote trends, we get:

Nothing particularly exciting there (especially if you happen to be the ALP!), except to note that the big ALP crunch on the primary vote came back in the May to July period and has been pretty much faffing about ever since. That primary vote level is roughly what we saw Labor achieve at the last NSW State election and, barring Campbell Newman getting caught riding a Citycycle naked through Queen Street Mall in the middle of a crack bender, it’s similar to what we’ll also see Labor achieve at the upcoming Qld state election

Next up – the election simulations. Monte Carlo based, state swing focused simulations using our quasi-event dependence framework etc etc.. you’ve heard the spiel before. This time we’re updating the system to incorporate the new electoral redistributions as outlined by Antony Green over at his place.

If you’re an ALP member – probably best to look away about now. If you thought those trends were bad, you ain’t seen nothing yet.

If you’re a Coalition member, well then – break out the popcorn!

The raw state swing data from the aggregated polling looks like this:

The whole country has moved blue since the election, with SA and NSW leading the charge against Labor. WA (the home of Stephen Smith – being spruiked as a possible Gillard replacement by the very people that caused this mess in the first place) comes in showing the smallest swing against the government.

Starting with the basic distribution of the results  of a hypothetical federal election held during the last 3 months (usual caveats of the election results matching the polling data etc – the simulations stabilised out around the 20,000 iteration mark for those in to such nerdery), looking at the number of seats won by the ALP, we have (click to expand)

It’s showing us a result clustered around the 41 to 44 seats won mark in a Parliament of 150 – between 27% and 29% of the seats available. That would give the Coalition around 103 to 107 seats, depending on how they fared against the Indies.

Changing the format of the charts, so it tells us the implied probability of the ALP winning *at least* any given number of seats, starting with the full distribution, we get:

The ALP is rock solid up to winning at least 38 seats, before the distribution starts falling away.

Zooming in to the key results to have a closer look:

The most likely result is the ALP winning at least 42 seats, with an implied probability of 61%. The 43rd seat mark was sitting just under the 50% threshold at 49.5% implied probability. The implied probabilities then start to fall off a cliff, with only a 38% likelihood of getting that 44th seat.

Now here’s where the ouch factor comes in. Comparing the September simulation with the June and March simulations, we can see how the likely number of seats that the ALP would have won have dramatically reduced as the months have rolled on. We’ll run that chart above (giving us the implied probabilities of the ALP winning at least X number of seats) overlayed with the same charts from the last two quarterly simulations (click to expand)

To use an example to explain it – in the March quarter, there was a 60% implied probability of the ALP winning at least 68 seats. By June, that 60% implied probability level had reduced to 52 seats. Now in September, it’s sitting on 42 seats – a full 26 seat contraction over the year from an already election- losing position.

At the critical 50% threshold level, it went from 69 seats in March, to 53 seats in June, down to 42 seats now (as the 43rd seat is just below the 50% implied probability mark) – a 27 seat contraction at the critical 50% threshold.

So what seats would be lost?

I’m going to do something I rarely do and post the individual seat baseline implied probabilities from the simulation. The reason I rarely do this is because it gets taken out of context too often. So to hopefully reduce the likelihood of that happening, it’s best to give a long explanation of what it means.

The simulation results are based on the statistical sledgehammer of monte carlo simulations applied to state swings (with a quasi-event dependency framework so that individual seats aren’t treated as independent events, but are semi dependent on clusters of seats within each state that exhibit historical correlation from the mean state swing, as well as an overarching state swing quasi-event dependence). We need a quasi-event dependence with simulations like this to reflect observable reality and to prevent our results from becoming what is a technical term known as “horseshit

The reason we use the swing of federal polling in each state as the main driver for the simulations, is simply because the best predictor of the result of any given seat at any given Federal election, is the swing at the state level of that federal election that such an “any given seat” happens to reside in.

Seats swing together more at the state level than at the national level – where a perfect example is the 2010 Federal election. Victoria, South Australia and Tasmania had a swing towards the ALP, while the rest of the States had a swing towards the Coalition.

It’s this state based nature of the simulation, as well as its accommodation of uncertainty (both the standard deviations of the swing within each state and the uncertainty of the polling ) and the quasi-event dependency framework (that allows seats to move together on the basis of both history *and* any localised, regional polling results within a state) that makes it at least as accurate as a standard pendulum approach, usually more accurate (sometimes much more) – but never in the last 20 years of elections I’ve retrospectively applied it to for testing, has it been less accurate than a standard pendulum approach.

The ordinary election pendulum has the property where a swing of 5% doesn’t mean that every seat under a margin of 5% will change. What it means is that the average swing would be 5% and that for every seat under a 5% margin that doesn’t change hands, some seat above the margin will swing by more to make up the weight.

The simulations exhibit this same property, but at a state level.

Using an example – let’s say the South Australian seat of Adelaide held by Kate Ellis. Adelaide sits on a margin of 6.1% and South Australia is facing a swing of 8.8% against the Labor Party, meaning that a uniform swing would see this seat fall to the Coalition and be held by them on a margin of 1.3% . If Kate Ellis managed to hold the seat, then some other seat or groups of seats would need to swing more to make up the weight to give us the average swing.

This seat currently has an implied probability of ALP victory of 36.7% based on this quarter’s polling results.  That doesn’t mean that the actual, real life probability of Kate Ellis winning her seat is exactly 36.7%. What the 36.7% implied probability represents is the generic starting probability based on the state swing, the historical variance of the seat of Adelaide in terms of the state swing and geographical factors (in this case, being a capital city seat) with all else being equal.

Of course, not all things are equal.

Most seats have varying numbers of local issues running at various strengths, which will impact the swing in a given seat. Occasionally that impact is large, but often it’s either not very large, or different local issues end up cancelling each other out in net terms as candidates stake out their local issue grounds and it becomes a game of swings and roundabouts, pardon the pun.

Sometimes, opposition candidates end up being complete duds that act to reduce the swing in a particular seat.

Sometimes, some local members are strong local members.

Going back to our example of Adelaide,  Kate Ellis is a strong local member, so that would increase her actual probability of holding the seat beyond the generic probability. By how much? Maybe 10 to 15% – looking back at previous elections, strong local members seem to have around a 10-15% boost in implied probabilities of holding their seats.

However, in any given election, for any given seat, the state swing  – particularly a big state swing – will generally take out those before it in a manner highly correlated to their generic, seat based, implied probability.

The implied probability of winning is effectively a measure of the *distance* between a given seat’s margin and the swing we are seeing, controlling for what we know (geography, historical variance and historical behaviour) and what we think we know (the actual state swing itself). What it doesn’t take into consideration is local and seat dependent issues at the individual seat level.

Anyone using the results below inappropriately, without taking all that rant into consideration, will now be sent to the naughty corner :-P

So, this is what the implied probability of the ALP winning the seats they currently hold looks like if an election were held during the last three months. I’ve only listed ALP/Coalition head to head seats for the mainland states, and no Coalition held seats are listed because the ALP would only pick any of them up on these polling results through some black swan event.

All up – 14 kinds of gruesome for Labor.

BTW – dealing with a spam problem, so some of the comments from new posters might be held up from appearing for a small amount of time.

Polling trends – Spring Session Edition

   

With the Parliament set to start its Spring sitting session today, it might be worth taking a look at the current state of play on the polling trends using our Pollytrend system. Over the six week period from the beginning of June, we saw the Coalition pick up 4 points of two party preferred in what was their strongest public support push since the 2010 election – lifting their vote from around 54.5 up to 58.5 by mid July.

Over the past 4 weeks however, the ALP has actually clawed back a point and a half to give them – and I’m not joking here – their largest increase in the vote share over any arbitrary period since the last election. Millions of words have been written about the current state of ALP support, but that pretty much says it all right there.

The two party preferred chart tells the story:

As we would expect, this generally reflects the behaviour in the primary votes of all concerned – detailed charts of which you can find in the sidebar on the right.  Currently, the ALP is facing a 9.1% swing against them from the last election on the primary vote with the LNP picking up 5.2% and the Greens losing about half a percent – all washing out into a current 7.2% swing to the Coalition in two party preferred terms.

The broader “Others” have actually jumped 4.3% in the primary vote since the election – nearly all of which came in net terms from the ALP (though, that doesn’t mean the Others growth has all been actual ALP voters – there would have been an unknown amount of churn between all parties to deliver this result). It’s worth mentioning, but probably not worth thinking too much about – as that broad “Others” group historically gets a bit all over the place.

Looking at the longer term trends in the primary vote, we have:

It’s been a rather smooth ride for all concerned, with only a few bumps along the way. The Coalition has consistently gained primary voteshare, the ALP has consistently lost it by a greater amount and the Greens slightly faded. More detailed versions of each party’s primary vote behavior can be seen over in the sidebar on the right.

As we enter the Spring Parliamentary session, the Coalition is ahead by miles, the long term momentum is with them, but they’ve have come off their peak of 6 weeks ago – with the ALP having gained their largest increase in public support this term (all 1.5% of it).

Pollytrend, Election Sims and Labor’s worst month in government

   

Being the end of June, it’s time to crank up the stats and run our quarterly election simulations based on polling aggregates of the last 3 months from all the pollsters that provide state level breakdowns. However, before we do, it’s worth updating our Pollytrend measures as the month of June turned out to be quite the mover and shaker – delivering the ALP its largest voter alienation in the history of the Rudd/Gillard government.

First up, the primary vote trends for the majors (the Greens are pretty flat – you can see them in the sidebar on the right)

While the ALP primary didn’t quite fall off a cliff, it certainly stumbled without grace or poise down a rather steep hill. The June period saw the Gillard government drop 4 points of primary vote – from 33% down to 29% (give or take a couple of tenths of a percent) in around 30 days. This flowed through into the two party preferred estimates as a slightly smaller loss of 3%. The two party preferred chart is starting to look a little horrific for the Labor side.

Again we see the same pattern emerge where the ALP vote flattens off at some level for a while before taking a hit and flattening off at a new, lower level of support – rinse and repeat.

The simulations don’t look much better – especially considering that a full two thirds of the sample period we’re using here – April through June – had the government in a much better position than they face right now. First up, the broad results where we look at the probability of the ALP winning at least X number of seats.

And a close up of the threshold 50% area:

The most likely result were an election held over the last three months and where the outcomes of the election matched the polling, would have had the ALP winning 53 seats. To give an idea of how far the government has slipped over the last 3 months, it’s worth comparing this election simulation to the last set we ran for the first quarter of 2011. If we look at the same cumulative probability distribution above with last quarter’s, we get: Read More »

New Trends and Gender Shifts

   

Plugging all the new polling data of late into our trend system, we find that the medium term deterioration in the Labor government’s two party preferred vote has stabilised out around the 46% mark over the last 6 weeks. A lot of day to day stuff came and went, from budgets to boat people, from carbon pricing to the usual day to day gibberish – none of it made a jot of difference.

An interesting pattern that has developed this year is how the Coalition has increased their lead over the ALP in relatively short bursts, followed by a small contraction or consolidation in the Coalition vote, before going on to enjoy another burst of support. It’s almost as if each time the government loses some political “event”, a chunk of their support moves across to the Coalition – but without the opposite ever occurring –  where government “wins” fail to achieve any growth in their political standing.

In one respect, it’s as if the government has been saddled with all downside risk in the electorate and no corresponding upside. Lose an event and their support shrinks – win an event and their support doesn’t move in any significantly beneficial manner for them.

On the primary vote trends, the same basic pattern has been occurring as with the two party preferred, but with the added component of a slightly fading Greens vote (click to expand the charts).

Finally, the net approval ratings of Gillard and Abbott by gender make for some interesting food for thought. Here we’ll use Nielsen data.

Back when Gillard became PM, she held high approval ratings and high voting intention numbers among women, while Abbott held moderate approval ratings among men and enjoyed a relatively small but significant lead on voting intention among men. Over the last year, Abbott has increased his male voting intention figures while his male net approval rates split fairly evenly. However, Gillard’s support among women has dropped significantly in both voting intention and net approval – effectively creating the difference between the ~53/47 two party preferred lead to Labor we saw back in July last year vs. the 54/46 results favouring the Coalition we see today. If we compare the aggregate poll results between July 2010 and May of this year, they tell the story.

Gillard lost her strong gender advantage among women while Abbott’s gender advantage among men grew significantly.

The CSIRO gets HIP to debunking media hysteria

   

The CSIRO last week released what was effectively a statistical analysis of the reality surrounding large parts of the infamous Home Insulation Program – or for those of you not familiar with this particular policy, you may have heard about it via it’s common alternative name in the mainstream media, the “OMG, PETER GARRETT IS BURNING DOWN OUR FUCKING HOUSES!” policy.

As we here have long known and talked about, the reality of the Home Insulation Program was always vastly different to its hysterical media portrayal – driven as it was by naive and innumerate journalists looking for easy sensational headlines, and partisan hacks prostituting their cheap wares before a gullible public. Having a cowardly government lacking the plums to tell them all where to stick it was another unfortunate sub-plot in this tale of public deception about the reality of a substantial piece of public policy.

The CSIRO report covers three large areas – analysis of fire related incidents, broader safety risk issues relating to the insulation program and the development of a risk profiling tool. Today, we’ll just focus on the fire related incidents component, as we’ve long been following this particular issue in depth and it’s nice to be able to bring it to a close, flip the bird at our detractors and exit the battlefield under a big banner saying “We told you so” :-P

The first thing that needs to be done is explain what the CSIRO *didn’t* do. They *didn’t* answer the elephant in the room question: “In the 12 month period after having insulation installed, was there a difference between pre-program and in-program probability of having an insulation related fire incident?”. They provided all the data we need to get an estimate of it, they made a sort of assumption about it, but didn’t actually attempt to tackle that important question head on.

We will.

This question is important because it tells us whether the Home Insulation Program was safer or more dangerous in terms of fires than what existed before it over the short term – over the first 12 months of having insulation installed.

The second thing the CSIRO didn’t do was provide long term background fire rates (the number of fires we should expect to see every year from all houses that have had insulation installed for longer than 12 months) that allow us to answer the questions *we’ve* been asking. They’ve provided background rates that answer a lot of different questions, that answer a lot of questions other people may have been asking, but not the ones we have. This is a simple methodology issue which we can easily deal with since the CSIRO kindly provided in the report all the data we need.

To get a feel for what actually happened, it’s worth looking at the strong relationship between when the fire incidents under the program occurred (defined as houses which had the fire services called out to them over what turned out to be an insulation related fire) and when insulations were actually installed. This data comes from Table 5.1 on page 30 of the report (click to expand)

As the number of installations increased during the program, the number of fire incidents increased with it, before those fire incidents trailed off on an 8 to 12 month tail after the installations had ceased. This is important because it shows us straight away that most fires happened relatively quickly after insulation was installed. To really highlight this relationship further, if we change this data from a chronological month by month representation into one where we measure how many days insulation had been installed, for every fire incident under the program, this is what we get: Read More »

First Election Simulation for 2011

   

With the Newspoll quarterly release this week, we now have enough data to aggregate the pollsters together, break the aggregated sample down into state based components and run our first election simulation for 2011.

Before we start though, it’s worth running though an updated Pollytrend to show how the polls have moved over the January to March period.

As we can see, things were pretty calm over the first 6 to 7 weeks of the year in terms of the two party preferred national results. Over the last 5 weeks however, a fairly large chunk of us went a bit berko over the carbon tax, boat people and other topical favourites of the hyperventilating classes.

What this means in practical terms is that the Labor party are today sitting a little above their aggregate support level of the last 3 months that we use for the simulations – by about half a percentage point of two party preferred thereabouts. Not a massive difference, but worth noting since someone would have in comments anyway.

At the state level breakdown, this is what the last 3 months of aggregated polling suggested in terms of the swings operating since the last election.

The government has boosted its stocks in WA, but have lost ground to the Coalition in NSW, Vic and SA – where most of that lost ground is occurring in the capital cities.

As always, we’re running our quasi-dependency Monte Carlo based simulation method which treats individual seat results as neither dependent nor independent events, imitating the real world effects we see operating in elections  where seats “move together” at the state level of aggregation. After 20,000 iterations, the simulation stabilised giving us the following results in terms of the number of seats the ALP would have been likely to win (click to expand). Read More »