1. How Have The Polls Changed Since 2015?
John Curtice
British Polling Council

2. Performance of Final Polls
Based on 10 polls whose fieldwork did not end before 5.5; Polls by Opinium; YouGov; Survation; ComRes; Populus; Ashcroft, Ipsos MORI: BMG Research, Panelbase; ICM Research

3. Inquiry’s Key Recommendations
Turnout
ascertain who has voted by post;
identify better ways of who is more likely to vote
Don’t Knows
review ways of imputing likely voting behaviour
Sampling/Representativeness
improve representativeness of who is interviewed;
in setting quotas and weighting targets investigate use new variables associated with responding to polls and vote choice
benchmark against random probability surveys

4. Overview
Nearly every company has made at least some change to their methods.
Most have addressed to some extent all of the principal recommendations in the Sturgis Report, albeit not necessarily in the same way
Some have also made changes that do not flow directly from the report

5. Age Gap in Turnout

6. Anticipated Age Gap in Turnout
* vs 60+

7. The Widened Age Gap in Party Support
Source: BES 2010 and 2015

8. Sampling/Representativeness - 1
Secure greater inclusion of those who are less engaged in politics (YouGov)
Changes of mode
ICM from phone to online
ComRes all polls online
Quota/Weight data by (BES) interest in politics (ICM; YouGov) or overall estimated turnout (Kantar) or newspaper readership (Ipsos MORI)
Weight data so that % in each demographic (esp. age) group represents % of voters (BES) rather than % population (ORB; Panelbase?)

9. Sampling/Representativeness - 2
Quotas/weighting by education (Ipsos MORI; Kantar; ORB)
Change quota/weighting age bands to secure more older voters (Kantar; YouGov)
Changes to quotas/weighting by past vote/party identification etc. (ICM; Opinium; YouGov)
Weighting by 2016 EU Referendum vote (Opinium, Panelbase; YouGov)

10. Identifying Who Will Vote - 1
Weight data so that estimated turnout in different demographic groups is in line with modelling of turnout in 2015; drop asking people how likely they are to vote (ComRes)
Use reported likelihood to vote in a model of the relationship between likelihood and turnout in (Kantar)
Weight data so that estimated turnout in each demographic group matches a variety of estimates for 2015 (ICM)

11. Identifying Who Will Vote - 2
Ask/use additional questions apart from reported likelihood of voting (ICM, Ipsos MORI; YouGov)
Change use/wording of likelihood of voting question (Ipsos MORI; Opinium)
Not ask postal voters likelihood of voting (Kantar)

12. Shy Voters? Introduce ‘squeeze’ question (Kantar)
Introduce/extend imputation of Don’t Knows etc (ICM; Kantar?)

13. Conclusion - 1
Biggest change is the application of greater effort to ensuring a more accurate estimate of key differences in turnout
Some effort to contact the less politically engaged
Much greater attention to weighting/modelling data to reflect patterns of turnout/engagement at previous elections, sometimes with reference to the random probability BES
Somewhat less reliance on a likelihood to vote question alone

14. Conclusion - 2
Also some changes designed (inter alia) to improve representativeness of those who do vote
Greater use of past vote weighting
Some use of weighting by education and EU referendum vote
Many of the changes clearly informed by an understanding of what went wrong in 2015 (thanks, not least, to the Sturgis report)
But inevitably whether they will prove sufficient will only be known on June 9!