A two-stage model to forecast elections in new democracies

Bunker, Kenneth

doi:10.1016/j.ijforecast.2020.02.004

Cited by 4 publications

(9 citation statements)

References 87 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…So, let us begin with the former: is the forecast of the TSM for the first question of the plebiscite in line with the TSM forecast for other types of elections? In its application to twenty six first round presidential elections in eleven countries, Bunker (2021) shows that the mean absolute error of the TSM is significantly lower than the mean absolute error of the polls. More specifically, it shows that while the model erred by an average of 4.1 percent, the polls erred by an average of 5.2 percent.…”

Section: Resultsmentioning

confidence: 97%

“…It is in this context that the TSM was developed. The TSM (see Bunker, 2021) essentially uses a poll aggregation method but adds the complexity of space state DLMs (West & Harrison, 1997). Its main objective is to estimate latent trends of support for parties (or candidates) and extrapolate them into the future (Bodell, 2016).…”

Section: The Two-stage Modelmentioning

confidence: 99%

“…When it comes to electoral forecasting there is a remarkable lack of research stemming from new democracies in general (Lewis-Beck & Bélanger, 2012;Lewis-Beck & Stegmaier, 2008) and from Latin America in particular (Bunker, 2021;Cantú et al, 2016;Turgeon & Rennó, 2012). While some research has been conducted in the region, it has all focused on presidential elections, leaving both more frequent elections (such as those held at the legislative and municipal levels) and less frequent ones (such as regional referendums and national plebiscites) significantly understudied.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Forecasting two-horse races in new democracies: Accuracy, precision and error

Bunker

2022

Rev. Lat. Op. Pub.

Self Cite

View full text Add to dashboard Cite

The purpose of this article is to explore electoral forecasting in two-horse races in new democracies. Specifically, it applies a Bayesian dynamic linear model (coined the Two-Stage Model, TSM) to look at the 2020 Chilean two-question national plebiscite. The ultimate objective is to test the TSM in terms of accuracy (how close the forecast is to the election results), precision (how close the forecast is to other methods of prediction) and error (how the forecast deviates from perfect accuracy/precision). The article finds that while the TSM does appear to be a stable estimator, its accuracy and precision is affected under certain conditions. Using the difference in the results for each of the two questions, the article discusses how sharp and unexpected shifts in electoral preferences can affect forecasts.

show abstract

Section: Resultsmentioning

confidence: 97%

Section: The Two-stage Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Forecasting two-horse races in new democracies: Accuracy, precision and error

Bunker

2022

Rev. Lat. Op. Pub.

Self Cite

View full text Add to dashboard Cite

show abstract

“…In our 9. As Bunker (2020Bunker ( , 1409 put it "it is likely that the average of the two polls will be a better estimator of the parameter of interest than any poll chosen at random." 10.…”

Section: Dependent Variablementioning

confidence: 99%

“…Forecasting models draw on theories of voting behavior and empirical evidence about what matters to voters when they cast their ballots (Lewis-Beck and Tien, 2012;Stegmaier and Norpoth, 2013). Building on these models, and forecasting literature in Latin America (Bunker and Bauchowitz, 2016;Turgeon and Rennó, 2012;Bunker, 2020), we seek to add some degree of certainty in an area of Peruvian politics that has remained largely unexplored.…”

Section: Introductionmentioning

confidence: 99%

Choosing the Lesser Evil: Forecasting Presidential Elections in Peru

Arce

Vera

2022

Rev. Lat. Op. Pub.

View full text Add to dashboard Cite

The Peruvian political landscape is dominated by the weakness of party organizations, the continuous rotation of political personalities, and, in turn, high electoral volatility and uncertainty. Nevertheless, we observe patterns of electoral competition that suggest candidates learn to capture the political center and compete over the continuation of an economic model that has sustained growth. We use this information to record the vote intention for the candidate viewed as the lesser evil. Our forecasting results predict a good share of the variation in political support for this candidate. The out-of-sample prediction also comes fairly close to the real electoral results. These findings provide some degree of electoral certainty in an area that, to date, remains understudied.

show abstract