April 2018 - poll update

Before we get to the aggregation at the start of April 2018, in March we had a newcomer. Roy Morgan joined the pollsters publishing polls in the lead up to the 2019 Australian Federal Election. To the best of my knowledge, prior to the two Morgan polls in March 2018, the previous Morgan poll was about a month before the 2016 Federal Election.  

The new polls from March 2018 were:

	MidDate	Firm	L/NP	ALP	GRN	ONP	OTH	TPP L/NP	TPP ALP
0	2018-03-28	ReachTEL	34.0	36.0	10.0	7.0	13.0	46.0	54.0
1	2018-03-23	Essential	38.0	36.0	9.0	8.0	9.0	48.0	52.0
2	2018-03-23	Newspoll	37.0	39.0	9.0	7.0	8.0	47.0	53.0
3	2018-03-21	Roy Morgan	40.0	35.0	12.0	3.5	9.5	49.0	51.0
4	2018-03-09	Essential	36.0	38.0	9.0	8.0	9.0	46.0	54.0
5	2018-03-07	Roy Morgan	36.0	36.0	13.5	3.0	11.5	46.0	54.0
6	2018-03-02	Newspoll	37.0	38.0	9.0	7.0	9.0	47.0	53.0

All of these polls have Labor in the box seat, with two-party preferred (TPP) estimates ranging from 51 to 54 per cent for Labor. The Coalition ranges from 46 to 49 per cent.

The TPP poll aggregate is improving (albeit slowly) for the Coalition from its low-point in December 2017. Nonetheless, if an election were held today, Labor would win with a healthy majority in the House of Representatives. The latest aggregate has Labor on 52.6 and the Coalition on 47.4 per cent.

Note: for the above charts I have included all six pollsters in the core set of pollsters for the purposes of locating the position of the aggregated TPP estimate.

Moving to the primary vote estimates, I am using a Gaussian auto-regressive model where the primary votes share is estimated as centred logits (also known as: centred log ratios).

With house effects summed to zero across pollsters and parties as follows.

From the primary votes aggregations we can estimate the TPP vote. As with the direct TPP aggregation, all of these models suggest the Coalition has been improving its position since December 2017. However, if a poll was called at the moment, the most likely outcome is a sizable Labor win.

Acknowledgement: I source the data for this analysis from Wikipedia.