Possums Pollytics

Politics, elections and piffle plinking

Regression model for the coming election

Posted by Possum Comitatus on May 16, 2007

 

 

After gathering together the newspoll data from 1985 to the present and aggregating those into a monthly series, I thought I’d build a quick election model regression.The series used are a mix of newspoll series and economic series sourced from the RBA.These were:

GOVPRIMARY: The primary vote for the government according to the newspoll.

OPPRIMARY: The primary vote for the Opposition according to newspoll

PMDISAT:The dissatisfaction rating for the Prime Minister

PMDISAT(-1):The dissatisfaction rating for the Prime Minister lagged by one period.

OPSAT: The satisfaction rating of the Leader of the Opposition

GST: A dummy variable for the GST where it equals 1 for the period it has been operating and zero for the periods before it was introduced.

CAMP: A campaign dummy variable which equals 1 the month before the election and zero otherwise.

INT: The standard bank variable home loan interest rate.

AR(1):A first order serial correlation termm

MA(1):A first order moving average error component.

The model became:

GOVPRIMARY = 64.8207675 + 1.374899313*INT – 0.565567558*OPPRIMARY – 0.128756676*PMDISAT + 0.05746403116*OPSAT – 0.1212621617*PMDISAT(-1) – 1.720345869*GST + 2.518176146*CAMP + [AR(1)=0.8682231246,MA(1)=-0.6409529542,BACKCAST=1996:03]

Using the quaint little Eviews, the more important technical bits were:

 

Dependent Variable: GOVPRIMARY
Method: Least Squares
Date: 05/17/07 Time: 00:40
Sample: 1996:03 2007:05
Included observations: 135
Convergence achieved after 36 iterations
Backcast: 1996:02
Variable Coefficient Std. Error t-Statistic Prob.
C 64.82077 3.467005 18.69647 0.0000
INT 1.374899 0.470391 2.922884 0.0041
OPPRIMARY -0.565568 0.075075 -7.533329 0.0000
PMDISAT -0.128757 0.028567 -4.507237 0.0000
OPSAT 0.057464 0.024617 2.334312 0.0212
PMDISAT(-1) -0.121262 0.027496 -4.410223 0.0000
GST -1.720346 0.743948 -2.312453 0.0224
CAMP 2.518176 0.735535 3.423599 0.0008
AR(1) 0.868223 0.067859 12.79458 0.0000
MA(1) -0.640953 0.115439 -5.552327 0.0000
R-squared 0.818619 Mean dependent var 43.11037
Adjusted R-squared 0.805559 S.D. dependent var 3.360798
S.E. of regression 1.481958 Akaike info criterion 3.695793
Sum squared resid 274.5250 Schwarz criterion 3.910998
Log likelihood -239.4660 F-statistic 62.68402
Durbin-Watson stat 1.847315 Prob(F-statistic) 0.000000

I spent alot of time checking for all sorts of relationships, but what was interesting was the CAMP result.The Coalition get a 2.5% boost to their primary vote in the month before the election and the GST hurt there primary vote and it has not yet recovered.

Another interesting phenomena that I came across was that the Coalition appears to get a boost in their primary vote when economic bad news is occurring, and a decline in their primary vote when the economic sunshine comes around.When the Coalition is in government:
– a 1% increase in unemployment has walked hand in hand with a 0.96% increase in their primary vote.Likewise a 1% decrease in unemployment has walked hand in hand with a 0.96% decrease in their primary vote.

– a 1% increase in the interest rate level has walked hand in hand with 1.3% increase in their primary vote.Likewise a 1% decrease in the interest rate level has walked hand in hand with 1.3% decrease in their primary vote.

When the Coalition is in opposition:

– a 1% increase in unemployment has walked hand in hand with a 1.6% increase in their primary vote.Likewise a 1% decrease in unemployment has walked hand in hand with a 1.6% decrease in their primary vote.

– a 1% increase in the interest rate level has walked hand in hand with 0.4% increase in their primary vote.Likewise a 1% decrease in the interest rate level has walked hand in hand with 0.4% decrease in their primary vote.

When times are tough, the people run to the Coalition and economic sunshine kills them.See for yourself:

 

Dependent Variable: COALITION
Method: Least Squares
Date: 05/17/07 Time: 01:03
Sample(adjusted): 1986:01 2007:05
Included observations: 257 after adjusting endpoints
Convergence achieved after 8 iterations
Variable Coefficient Std. Error t-Statistic Prob.
C 27.46739 3.446556 7.969518 0.0000
DGOVLIB*UNEMP 0.960052 0.419546 2.288308 0.0230
DGOVLIB*INT 1.325942 0.437369 3.031630 0.0027
DGOVALP*UNEMP 1.562745 0.296463 5.271298 0.0000
DGOVALP*INT 0.385121 0.166081 2.318868 0.0212
AR(1) 0.671602 0.047794 14.05187 0.0000
R-squared 0.600228 Mean dependent var 44.33366
Adjusted R-squared 0.592265 S.D. dependent var 3.318514
S.E. of regression 2.119009 Akaike info criterion 4.362844
Sum squared resid 1127.040 Schwarz criterion 4.445702
Log likelihood -554.6254 F-statistic 75.37167
Durbin-Watson stat 2.145189 Prob(F-statistic) 0.000000

I bet the government is praying for a recession.

 

 

7 Responses to “Regression model for the coming election”

  1. Steve said

    Does the government do these kinds of analysis or do you think they just look at raw poll data and think “Oh F**K”?

  2. possumcomitatus said

    I’m sure the governments pollsters like Crosby-Textor do analysis like that all the time, probably a lot more sophisticated to boot.As for the “Oh Fuck” – I think that’s happening no matter which type of polling analysis the government looks at😉

  3. netvegetable said

    Are you saying that a tory government is less likely to win an election when the economy is doing well?

  4. possumcomitatus said

    That’s exactly right netveggie! But its not only Coalition governments, coalition oppositions also suffer from the same allergy to economic sunshine.

    The evidence seems to fly in the face of alot of political mythology to the contrary.

  5. Albert F said

    Thanks Possum – great work.

    I think that govts can use bad economic news to their advantage. I’m not sure its purely a Coalition thing. Keating won the ’93 election and had the first million plus unemployment rate in history in (I think) the final week of the campain. It seemed to help him as voters were scared of Hewson’s radical reform agenda.

  6. Possum Comitatus said

    Hi Albert,
    I agree.Historically at least, interest rate levels have walked hand in hand with the Coalitions primary vote with a high degree of statistical significance, although only contributing a small amount of explanatory power in the Coalitions primary vote (between 5-10% depending how you measure it).Historically, bad economic news is good political news for the Coalition particularly.Whether this time that effect will be overpowered by the “Keeping interest rates low” fallout is something that time will tell.

  7. Ash said

    “Tory” is a description or label I *&^%ing hate. I am a rusted on Coalition voter and there is nothing Tory about me. I have worked battler jobs, I have put myself through two degrees. I send my kids to public schools. I could say a lot more. Tory is a word that belongs in the class warfare of Britain prior to the 1950s and not in Australia in the 21st century.

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