Brazilian latest polls and house effects

October 25, 2014
By

(This article was first published on » R, and kindly contributed to R-bloggers)

The latest polls just released tonight are suggesting a numerical tie between Dilma Rousseff (PT) and Aecio Neves (PSDB) considering the limit of the margin of error. Actually, these polls fired up a possible game-changing for the opposition over the government as some of the polls did capture any impact stimulated by the televised debate on Friday night.

There is still a lot of uncertainty around; roughly 5% of the electorate were reported to be undecided still. Nonetheless, by the time I run my model today, it turned Aecio ahead of Dilma for a little margin (< 1%). These numbers also account for Wasting votes, so it will typically diverge from the official results.

House Effects

Although the machinery behind the model I’m running allows for drawing several elections from data, it’s too risky to call one side or the other given the pollster’s credibility, which was certainly aggravated by the poor performance 3 weeks ago. Meanwhile, I’ve been trying to learn the pollsters’ random walk in the Brazilian campaigns, but given the small range of observations this will take a while to produce robust measures.

The following chart shows the house effects considering those polls released over the runoff campaign. Ideally, a poster would have its effect equally distributed between positive and negative bands. Like a drunkard’s walk a pollster could stagger left and right near each party or candidate. Not surprisingly, however, the picture shows two blocks of bias. While the first 4 pollsters typically fielded more positive numbers of the Government, the last 3 did so for the opposition. In addition, the house effects found for Datafolha, Veritá, and Sensus are statistically different than zero.

houseeffects

To leave a comment for the author, please follow the link and comment on their blog: » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)