First let's look at the polls over the period: we will focus on Coalition two-party preferred voting intention. In the next two charts these results are first presented as a scatter plot and then a line plot.
The simplest way to aggregate these results is through a localised regression.
But this does not adjust for the house effects (systemic biases) from individual polling houses. Nor does it factor in the sample size for the individual polls. We can do both of these with a hierarchical Bayesian model. [This is pretty much the same model as I used in the lead up to last year's Federal election (except, I have dropped the rounding effects from the model). It still assumes that the house effects sum to zero].
We will apply a smoother (using a 61-term Henderson moving average) to remove the kinks but retain the broad shape of the curve.
We can compare the smoothed Bayes model (which adjusts for house effects) with the earlier LOESS model (that does not). While the trajectories are similar, the specific results can vary from time to time.
From these charts, and focusing on the broad trajectories, I think there has been five distinct periods in the polling fortunes of the Abbott Government.
- First a short honeymoon, that had ended by early December 2013
- We then see a four month period of stability from December 2013 to March 2014.
- The period immediately prior to and including the Federal Budget in April and May 2014 saw a four to five point decline in the polls.
- This was followed by period of rebuilding from late June 2014 to mid October 2014. Much of the ground that had been lost with the budget was recovered during this period.
- Finally, we see a second phase of rapid decline, from mid October to mid December, where that previous gain has been all but lost.
The key message here is that the 2016 Federal Election is too early to call. This is not the dead-cat bounce of the final Keating, Howard or Gillard years. The late June 2014 to mid October 2014 rebound shows that a sustained recovery is not beyond the realms of possibility. But, nor is it clear sailing for the government. It has suffered three periods of decline over the past 15 months and it is currently in a difficult position from which it needs to extract itself.
A quick word on house effects (largely for completeness): The Bayesian model estimated the house effects for each polling house as follows (relative to each other and subject to a "sum to zero constraint").
We can consolidate the above charts, adjust poll results for house effects and overlay the smoothed trajectory.
Updates
- 21 December 2014, 8.30am - updated to include ReachTEL data
- 10 January 2015 - consolidated chart added
- 7 February 2015 - updated to include maxima, minima and endpoint statistics
wonderful stuff Mark.
ReplyDeleteGreat work Mark. a question how come you don't use Essential polls?
ReplyDeleteThe short answer is that I don't understand this series sufficiently. It does not always behave in a manner I would expect from independent fortnightly samples. The series appears a touch under-dispersed and a touch more auto correlated than I would expect. It also has a slight tendency to a random walk around the central tendency of the other polls over time.
ReplyDeleteBecause I don't understand the series, I find it challenging to include it in a model. If I could express algebraically why it behaves a little differently, I would be more comfortable including it in a model.
Please note: I am not suggesting there is anything wrong with the Essential poll series. All I am saying is that I do not understand it fully.
Thank Mark :-)
ReplyDelete