*By Stephen Fisher, John Kenny and Rosalind Shorrocks.*

This is our first post since the Manchester bombing. We would like to take this opportunity to extend our sympathy to all those affected, directly and indirectly. Now that the political parties are campaigning again we hope that it is not insensitive of us to update our forecasts.

In truth, because of Monday’s terrible events it is not clear how our forecast should be interpreted. Only one poll conducted since the attacks has been published, so most of the changes in the opinion poll data, and the models that are built on them, reflect polls conducted late last week; shortly after the Conservative manifesto launch and mostly before Theresa May’s announcement of a cap on social care funding. Those polls showed a considerable tightening of the Conservative lead and so a reduction in the predicted Tory majority.

Overall, our combined forecast of the Conservative majority has dropped to 100, down from 123 last week and from 132 two weeks ago.

Seats | Betting Markets | Complex models | Simple model | Volunteered | Average |

Con | 380 | 382 | 356 | 381 | 375 |

Lab | 181 | 189 | 210 | 173 | 188 |

LD | 15 | 8 | 6 | 10 | |

UKIP | 0 | 0 | 0 | 0 | |

Green | 1 | 1 | 1 | 1 | |

SNP | 46 | 48 | 55 | 50 | |

PC | 3 | 3 | 3 | ||

Con majority | 110 | 114 | 62 | 112 | 100 |

The combined probability of a Conservative majority, at 87% has correspondingly taken a small dip from 91% last week. More strikingly the probability of a Conservative landslide (a 100+ seat majority) has fallen from 64% (and 71% two weeks ago) to just 34% this week. The citizen forecast component of this average has not changed due to lack of new data. Previously that component was pulling down the average. Now it is pushing up. The markets and our pseudo-probability from the polls are both around 30%. Intriguing there is some inconsistency between the PredictIt market suggesting a 27% probability of a 100+ majority and the spread-betting markets pointing to a 110 seat majority.

Betting markets | Models | Polls | Citizen forecast | Average | |

Con majority | 0.87 | 0.87 | 0.94 | 0.79 | 0.87 |

Con landslide | 0.27 | 0.31 | 0.43 | 0.34 |

Last week we pondered whether the narrowing of the Conservative lead in the predicted share of the vote would be a temporary phenomenon due to the polls showing the smallest leads having been held between the launches of the Labour and Conservative manifestos. But the vote share lead has narrowed further this week, from 18.5 to 14.2 points, apparently as a result of the controversial nature of some of the Conservative manifesto promises.

Poll aggregates | Betting markets | Models | Average | |

Con | 45.4 | 47.6 | 45.3 | 46.1 |

Lab | 33.9 | 31.7 | 30.1 | 31.9 |

Lib Dem | 8.2 | 11.0 | 9.6 | |

UKIP | 4.1 | 4.0 | 4.6 | 4.2 |

Green | 2.1 | 2.0 | 2.0 | |

SNP | 4.0 | 4.0 | 4.0 | |

PC | 0.6 | 0.6 | 0.6 | |

Con-Lab | 11.5 | 15.9 | 15.3 | 14.2 |

The betting markets expect the Conservative vote share to recover and Labour to drop back, if not in the polls then at least in the actual election result. But they are expecting a narrower eventual lead than they were last week.

**Methodology**

The main changes in method this week are: there are three additional complex models from Nigel Marriot (one replacing his simple model), and Lord Ashcroft now has just one published average forecast instead of three separate forecasts. These changes have probably not made much difference to our seats average. We have dropped polling averages and the simple forecasting models from both Principalfish and Adrian Kavanagh because they appeared to be out of date at the time of writing. This means that the simple seats projection is just based on figures from Electionpolling.

The rest of what follows is basically the same detailed description of our method than we wrote last week.

The basic approach is to combine forecasts by averaging them within each category and then taking the average across categories. Since the different sources do not all present equally clear figures that can be averaged on a like for like basis we have made various judgement calls on how to treat the data.

Historically the idea of combining forecasts from different sources has had a good track record, though it has to be admitted that our attempt to do one for the EU referendum did not work out well. Most recently the pollyvote.com combined forecast of the US presidential election last year was 2 points out on the share of the vote.

*Polls*

For vote shares, we use the various available polling averages, or ‘polls of polls’, and take their average. We exclude polling averages for whom the most recently published polling average is more than a week old. There are seven different polling averages. They are in truth nowcasts rather than forecasts, but we are in effect treating them as forecasts. There are seven different polling averages. Some admittedly are quite sophisticated, allowing for pollster (aka house) effects, but they are nonetheless estimates of current public opinion and not future votes.

We do not attempt to say what seats outcome is implied by polls (that is the job of the modellers). However, since statistical models are rarely if ever clear about the probabilities their models place on key events like a Conservative majority and a 100+ majority, we have included in the probabilities table some pseudo-probabilities from the polls. Taking the two most recent polls published by each pollster in the last two weeks we calculate the proportion showing a Conservative lead over Labour of 6 points or more as the pseudo-probability of a Conservative majority. Using the same polls, we use the proportion showing a Conservative lead over Labour of 16 points or more as the pseudo-probability of a Conservative landslide. These thresholds of 6 and 16 points are based on what would be required under uniform swing assumptions for the Conservatives to win a bare majority and a 100+ majority respectively.

*Betting markets*

There are numerous betting markets for the various outcomes in the election. We have taken those that are most helpful for the four forecasts we want to produce. For seat shares, we take the mid-point of the spread as the seat share, and average these mid-points between different sources. Note that the markets imply fewer seats forecast than there are actually are in the House of Commons. This is because the markets are separate for each party and do not need to be consistent collectively.

For vote share, we use betting markets for the Conservatives, Labour and UKIP. (Vote share markets for other parties are unavailable on the betting market aggregation site Oddschecker.) Odds are given for 5-point ranges of vote share. We take a weighted sum of the mid-points of these ranges where the weights are the implied probabilities. For the top and bottom options we use 2.5% above/below the upper/lower bound (e.g. 52.5 for “Above 50” and 27.5 for “Below 30”). The weighted sum is calculated just using the three categories with the largest implied probabilities, because the probabilities for other categories are so small and unstable. For UKIP we use just the two most likely categories.

For the probability of a Conservative majority we give an average of the implied probability from sites offering this market. For the probability of a Conservative landslide, we use the combined prices PredictIt that the Conservatives will win 370-379 seats, 380-389 seats, and 390 or more seats. This really represents a majority of 90 or more but that was as close as we could get to 100.

*Statistical models*

There are numerous statistical forecasting models this year (and more to come). We have divided them into two categories: simple (poll average plus uniform swing seats projection) and complex (anything more elaborate than the simple models, although they are not necessarily particularly complex). Some make adjustments for long run differences between pollsters, for constituency variation, and some estimate by how much things will differ between current polls and the eventual result. Chris Hanretty’s forecast at electionforecast.co.uk does all of these things. Within these categories we simply average the available estimates of seats and shares.

We should note that not all of the models are the modellers’ favourite. Some are counterpoints to their main models for comparison. We have included these on the basis that they are still talked of and expected to be reasonable estimates, for example, at Electoral Calculus, Martin Baxter has a local election results based model. We have not excluded any models based on our judgement of quality, but they do have to be statistical models as opposed to personal guesses.

*Volunteered forecasts*

These come from the Times Red Box sweepstake, where both podcast contributors and members of the public can make predictions about seats for the Conservatives and Labour.

*Citizen forecasts*

Some polls ask people what they think that the outcome will be on June 8^{th}. Different pollsters use different survey questions but they can be combined to generate pseudo-probabilities. We use the proportion of poll respondents who think the Conservatives will win/there will be a Conservative majority, excluding don’t knows and re-percentaging, as the pseudo-probability of a Conservative majority. We similarly use the proportion of poll respondents who think that there will be a Conservative landslide/the Conservatives will win more than 100 seats, for the probability of a Conservative landslide. Due to the limited number of polls these questions are asked in, we take results from the last two months.

Note: Estimates come from around lunchtime on 26^{th} May 2017. In all seat estimates, the Speaker’s seat is counted as Conservative.

**Sources**

There sources we used are listed below in no particular order. Please let us know of any that you think we have missed or misclassified. Some polling averages we know of were not included because they were more than a week old.

*Prediction markets:
*IG

Predictit

Sporting index

Oddschecker

Betfair Predicts

*Complex Forecasting Models:
*ElectionForecast.co.uk (Chris Hanretty)

Electoral Calculus (main and local election forecast)

Forecast UK

UK-Elect

PME Politics (Patrick English)

Nigel Marriot (Four separate models)

Chris Prosser (GE vote shares from Local elections vote shares)

Lord Ashcroft

*Simple forecasting models (polling average + uniform swing):*

Electionpolling

*Polling Averages (less than a week old):
*Telegraph

FT

Britain Elects

Electionforecast.co.uk

NewStatesman

Electionpolling

Principalfish

The CrossTab

*Volunteered forecasts:
*The Times Red Box Sweepstake

*Citizen forecasts:
*YouGov (here)

ICM (here and here)

ComRes (here)

The three authors are equal contributors and our names are in alphabetical order.