House effects in Danish opinion polls #2

A year ago, Zoltán Fazekas and I looked into house effects in Danish opinion polls on the support for political parties. In brief, we found some interesting differences in the house effects among different polling firms (do read the post from last year if you are unfamiliar with the concept of house effects).

However, with the upcoming Danish general election in 2019, we found it necessary to update the results. You can read a lot more about the method and results here. Below you can find one of the figures from the analysis.

Unsurprisingly, the polling firms have a hard time polling the new right-wing political party, Nye Borgerlige, and there is no agreement among the firms (for my previous posts in Danish on this, look here, here, here, here and here). As the figure shows, YouGov believes the party is doing better than what other firms predict, whereas Voxmeter is less optimistic about the prospects for the party.

Last, Hans Redder from TV 2 uses our results in his new and interesting piece on what you need to be aware of when you see a new opinion poll. It is great to see how these aspects of the polling coverage are getting more and more attention, and I do hope that more journalists will show awareness of this in their coverage when we get closer to the election. To be continued…

House effects in Danish opinion polls

While opinion polls are great they are also subject to a multitude of potential systematic errors. Some of these errors are related to the fact that polling firms rely on specific methods that might shape the results (so-called ‘house effects’). Some firms, for example, rely on internet panels when they recruit respondents, whereas other firms call people on their phones. Such differences might affect the results in opinion polls.

In an analysis of all Danish opinion polls on the public support for political parties from 2010 to 2017 (n=1,062), Zoltán Fazekas and I examined whether such house effects are present for the national political parties. In doing this, we relied on the Bayesian approach described in Jackman (2005) to estimate house effects for each of the 10 parties (90 estimates in total given the 9 polling firms).

Figure 1: House effects in Danish opinion polls, 2010-2017

Figure 1 presents the results with the 10 parties on the vertical axis and the nine polling firms on the horizontal. If there are no house effects in the polls for a party, we will see no circles on the horizontal line next to a party. The greater a house effect is for a party in the polls from a specific polling firm, the greater the circle will be (the size of the circle is proportional to the magnitude of the house effect). When the house effect is negative, i.e. the polling firm estimate a lower support for a party, the circle is red. The blue circles are for positive deviations. The gray color is for effects where 0 falls within the 95% credible interval.

TV 2 covered the analysis (in Danish) with additional interpretations of the results. Subsequently, the analysis was also covered by Mandag Morgen (also in Danish).