I’ve completely rewritten this article to make it more coherent and reflective of what I was trying to say rather than making it look like the government was going to be nailed with a 70 seat loss. Yesterdays attempt was appalling gibberish that confused everyone including myself.So if you’ve read this before – it’s now all new and improved!
If you havent, welcome aboard to a long argument
As many of you know, the ALP primary vote projections based on the combination of the recent quarterly demographic and Marginal/Safe seat Newspolls showed what can only be described as horrific results for the Coalition.
Well let me say from the outset, what you are about to witness cannot be described as anything other than absolute devastation. Coalition supporters might want to remove any sharp objects from their vicinity before reading on.
The previous projections were rough, they didn’t take into account the redistributions since the last election, and they didn’t take into account capital vs. non capital breakdowns which is really, really important in some States. But most importantly, as I stated at the beginning of that article, it didn’t include the most recent quarterly Newspoll because, frankly, I didn’t believe it’s contents. Not that it was wrong, but just that I COULD NOT BELIEVE what it was saying and what I was seeing.
You see, the data from the last quarterly Newspoll is even worse for the Coalition than the Q1 Newspoll. Much, much worse as the results in the states with the most Coalition seats, like NSW, tanked in the last quarter whereas the ground the Coalition made up were in States like WA ands SA where the seats they hold are relatively few.
This is the real danger that these latest Newspoll numbers hint at.
What we are going to do is create a set of weighted ratios out of that quarterly Newspoll data and apply them to Coalition seats – not to tell us what the vote necessarily is in those seats, but to highlight the Coalition seats that are in danger because of the way the vote is swinging.
To start with, we’ll use a breakdown of the redistributed two party preferred results since the last election based on the Mackerras Pendulum for the initial redistribution, and make experimental TPP projections and swing projections based on the last quarterly Newspoll, March to July 2007 including State, Capital City vs. Non Capital City and Marginal vs Safe swings.
I took the State based Newspoll figures and determined the TPP swing for the ALP since the last election by State. I then took the national TPP swing for the ALP since the last election from that same Newspoll.
I then divided each State swing by the national swing to give me a state weight. Let’s use NSW as an example. The NSW swing to the ALP was 12.2, and the national swing was 9.8.The state swing divided by the national swing is 1.245.
That means in NSW the swing towards the ALP is 1.245 times the national swing.
I then took the national capital city swing towards the ALP (9.5) and divided it by the national swing (9.8) to give me a capital city weight of 0.969.This means that the capital cities are swinging 0.969 times the national swing. I repeated this process for the non-capital cities to arrive at a non-capital city weight of 1.245 (Yes it is the same as the NSW State weight as both had a TPP swing to the ALP of 12.2).
Next I took the national marginal seat TPP swing to the ALP (9.3) and divided it by the national swing (9.8) to get a marginal seat weight of 0.949.I repeated this process to get a safe government seat weight of 1.4898. That, by the way, is huge.
To get an idea of how these weights stack up on a seat by seat basis is simple and best explained with an example. Let’s take the NSW seat of Bennelong (every psephs favourite seat)
At the 2004 election the TPP result was 54.33% Coalition and 45.67% ALP.
The effect of the 2006 redistribution on Bennelong was to reduce that TPP down to a notional Coalition 54% and ALP 46%.
Bennelong is a NSW, capital city, marginal seat. Hence, the estimated TPP vote for Bennelong based on the Newspoll quarterly breakdown, using the weights described above is:
Estimated Bennelong TPP for the ALP = Redistributed ALP TPP + (state weight * capital city weight * marginal seat weight * national swing).
Hence, the estimated ALP TPP for Bennelong = 46 +(1.245 * 0.969 * 0.949 *9.8)
= 46 + 11.22
= 57.22
These are the ALP swings and the ALP swing weights as determined by the Newspoll data for the March-July 2007 results.
The National Swing is 9.8
NSW, swing 12.2, weight 1.245
Vic , swing 9, weight 0.918
Qld, swing 11.1, weight 1.133
SA , swing 10.4, weight 1.061
WA, swing 5.4, weight 0.55
Marginal Seat swing = 9.3 weight = 0.949
Safe Government Seat swing = 14.6 weight = 1.490
Capital City swing = 9.5 weight = 0.969
Non Capital City swing = 12.2 weight = 1.245
However, we have a problem. There will be feedback between some of the weights, for instance if there is a large swing in non-capital city NSW, that will inflate both the non-capital city ALP swing AND the NSW ALP swing AND most likely the swing against the government safe seats. If we apply that weighted swing to most seats it will produce an inflated TPP result.
But it’s also a good thing.
The feedback built into the weights also allows us to identify the seats that are most likely to be suffering swings against them simply because of where those big swings broadly identified by Newspoll are occurring.
For instance, we know NSW has a 12.2% swing to the ALP, we know that there is a swing against the government of 14.6% in their safe seats and we know that non-capital city seats are swinging slightly more than capital city seats. So its probably a fair assumption to make that there are a number of NSW non capital city seats, that are considered safe government seats and which are experiencing very large swings.
What the following table attempts to do is to identify those seats by using an experimental, weighted TPP projection and a nominal swing projection for each seat derived from that TPP. These are based on the 2006 redistribution as the underlying, pre-existing TPP vote for the last election.All seats are nominally (as in post 2006 redistribution) Coalition held seats.
| Seat |
State |
ALP TPP |
|
Experimental ALP |
Experimental ALP |
| |
|
2006 Redistribution |
|
TPP |
Swing |
| Cowper |
NSW |
43.4
|
|
66
|
22.6
|
| Paterson |
NSW |
43.2
|
|
65.8
|
22.6
|
| Gilmore |
NSW |
40.5
|
|
63.1
|
22.6
|
| Hume |
NSW |
37.1
|
|
59.7
|
22.6
|
| Lyne |
NSW |
35.9
|
|
58.5
|
22.6
|
| Farrer |
NSW |
34.6
|
|
57.2
|
22.6
|
| Parkes |
NSW |
31.2
|
|
53.8
|
22.6
|
| Riverina |
NSW |
29.3
|
|
51.9
|
22.6
|
| Blair |
QLD |
44.3
|
|
64.9
|
20.6
|
| Herbert |
QLD |
43.9
|
|
64.5
|
20.6
|
| Longman |
QLD |
43.4
|
|
64
|
20.6
|
| FLYNN |
QLD |
42.2
|
|
62.8
|
20.6
|
| Petrie |
QLD |
42.1
|
|
62.7
|
20.6
|
| Dickson |
QLD |
40.9
|
|
61.5
|
20.6
|
| Dawson |
QLD |
39.8
|
|
60.4
|
20.6
|
| Leichhardt |
QLD |
39.7
|
|
60.3
|
20.6
|
| Wide Bay |
QLD |
37.8
|
|
58.4
|
20.6
|
| Fisher |
QLD |
37
|
|
57.6
|
20.6
|
| Forde |
QLD |
37
|
|
57.6
|
20.6
|
| Fairfax |
QLD |
36.7
|
|
57.3
|
20.6
|
| McPherson |
QLD |
36
|
|
56.6
|
20.6
|
| Fadden |
QLD |
34.7
|
|
55.3
|
20.6
|
| Groom |
QLD |
31
|
|
51.6
|
20.6
|
| Moncrieff |
QLD |
30.1
|
|
50.7
|
20.6
|
| Maranoa |
QLD |
29
|
|
49.6
|
20.6
|
| Mayo |
SA |
36.4
|
|
55.7
|
19.3
|
| Grey |
SA |
36.1
|
|
55.4
|
19.3
|
| Barker |
SA |
30.1
|
|
49.4
|
19.3
|
| Macquarie |
NSW |
50.5
|
|
68.1
|
17.6
|
| Robertson |
NSW |
43.1
|
|
60.7
|
17.6
|
| Hughes |
NSW |
41.2
|
|
58.8
|
17.6
|
| North Sydney |
NSW |
39.9
|
|
57.5
|
17.6
|
| Macarthur |
NSW |
38.9
|
|
56.5
|
17.6
|
| Warringah |
NSW |
38.7
|
|
56.3
|
17.6
|
| Berowra |
NSW |
36.9
|
|
54.5
|
17.6
|
| Cook |
NSW |
36.3
|
|
53.9
|
17.6
|
| Mackellar |
NSW |
34.5
|
|
52.1
|
17.6
|
| Bradfield |
NSW |
32.5
|
|
50.1
|
17.6
|
| Mitchell |
NSW |
29.3
|
|
46.9
|
17.6
|
| McEwen |
VIC |
43.5
|
|
60.2
|
16.7
|
| Gippsland |
VIC |
42.2
|
|
58.9
|
16.7
|
| Flinders |
VIC |
38.8
|
|
55.5
|
16.7
|
| Wannon |
VIC |
37.6
|
|
54.3
|
16.7
|
| Indi |
VIC |
33.7
|
|
50.4
|
16.7
|
| Murray |
VIC |
25.9
|
|
42.6
|
16.7
|
| Mallee |
VIC |
25.2
|
|
41.9
|
16.7
|
| Bowman |
QLD |
41.1
|
|
57.1
|
16
|
| Ryan |
QLD |
39.5
|
|
55.5
|
16
|
| Sturt |
SA |
43.2
|
|
58.2
|
15
|
| Eden-Monaro |
NSW |
46.7
|
|
61.1
|
14.4
|
| Page |
NSW |
44.5
|
|
58.9
|
14.4
|
| Hinkler |
QLD |
41.2
|
|
54.3
|
13.1
|
| Higgins |
VIC |
41.2
|
|
54.2
|
13
|
| Dunkley |
VIC |
40.6
|
|
53.6
|
13
|
| Kooyong |
VIC |
40.4
|
|
53.4
|
13
|
| Goldstein |
VIC |
39.9
|
|
52.9
|
13
|
| Menzies |
VIC |
39.3
|
|
52.3
|
13
|
| Casey |
VIC |
38.6
|
|
51.6
|
13
|
| Aston |
VIC |
36.8
|
|
49.8
|
13
|
| Wakefield |
SA |
49.3
|
|
61.6
|
12.3
|
| Wentworth |
NSW |
47.4
|
|
58.6
|
11.2
|
| Lindsay |
NSW |
47.1
|
|
58.3
|
11.2
|
| Bennelong |
NSW |
46
|
|
57.2
|
11.2
|
| Dobell |
NSW |
45.2
|
|
56.4
|
11.2
|
| Greenway |
NSW |
39
|
|
50.2
|
11.2
|
| McMillan |
VIC |
45
|
|
55.6
|
10.6
|
| Corangamite |
VIC |
44.6
|
|
55.2
|
10.6
|
| Bonner |
QLD |
49.4
|
|
59.6
|
10.2
|
| Moreton |
QLD |
47.2
|
|
57.4
|
10.2
|
| Kalgoorlie |
WA |
43.6
|
|
53.6
|
10
|
| Canning |
WA |
40.4
|
|
50.4
|
10
|
| Forrest |
WA |
39.5
|
|
49.5
|
10
|
| Pearce |
WA |
37
|
|
47
|
10
|
| O’Connor |
WA |
29.6
|
|
39.6
|
10
|
| Kingston |
SA |
49.9
|
|
59.5
|
9.6
|
| Makin |
SA |
49
|
|
58.6
|
9.6
|
| Boothby |
SA |
44.6
|
|
54.2
|
9.6
|
| Deakin |
VIC |
45
|
|
53.3
|
8.3
|
| La Trobe |
VIC |
44.1
|
|
52.4
|
8.3
|
| Moore |
WA |
39.1
|
|
46.9
|
7.8
|
| Tangney |
WA |
38.2
|
|
46
|
7.8
|
| Curtin |
WA |
35.3
|
|
43.1
|
7.8
|
| Hasluck |
WA |
48.1
|
|
53.1
|
5
|
| Stirling |
WA |
47.9
|
|
52.9
|
5
|
Please note, this too is rough, and could be cleaned up even further with more time and more data. But that clean up process wouldn’t dramatically alter the nature of what is going on.
What the above table tells us is that the seats with the highest experimental swing are the best candidates to actually be experiencing swings against them that are necessary to balance out the Newspoll data.
The problem for the government comes from the 14.6% swing against their safe seats being an average swing. Now clearly some coalition safe seats wont be swinging much at all, which makes other safe coalition seats having larger than 14.6% swings against them to balance out the numbers. Some probably having much larger swings against them.
For the Newspoll figures to be right means that a lot of these seats will have fallen if an election were held in July. They wouldn’t have fallen with those margins (because, remember they are inflated), but still would have gone.I’ll put some more realistic numbers to these swings in Part 2.
The danger for the government here is if the swing against their safe seats is uniform. The more uniform it is, the most seats they will lose.The government holds 49 seats that are considered safe (i.e. are held with a buffer of more than 6%) but are held with a margin of less than this 14.6% swing against them.
This is why uniformity in this swing would wipe them out. When I was playing around with this a few days ago, I couldn’t believe what I was seeing – we all talk about elections being won or lost in the marginals, but if the polls hold, the marginals will be irrelevant. Not that the Coalition is doing particularly well in that area either, with a 9.3% swing against them there.
And nor can they be satisfied of the usual saviour of anti-government swings – the swings in the opposition safe seats. The ALP is only picking up an average of a 4.1% swing in their own safe seats. That too is extremely surprising.
In part 2, I’ll use some linear programming (or what the more pure end of mathematics calls matrix algebra) to whittle down the size of these swings to be consistent with the national, state, capital city vs. non capital city and safe vs. marginal seats swings.Then we might get a better idea of how an election may have looked like were it held in July.
One thing is clear however, these results are catastrophic for the government, suggesting that only a handful of seats are truly safe and that there will be massive swings against them in many seats they thought were untouchable. That simply has to be the case for the size of the swings to balance out.
CONTINUE on to Part 2 where some realistic numbers are produced to reflect the actual swings
