Project Details
Description
This research aims to introduce a new election prediction method which is called “spatial signals approach”. The spatial signals approach is a direct extension of the KLR signals approach of Kaminsky et al. (1998), which is developed for early warning system of crisis prediction. There are two research purposes of this research, the first is to examine the neighborhood effect of presidential elections in Taiwan, and the second is to verify the effectiveness of prediction of the presidential elections in Taiwan by spatial signals approach. Our empirical data comprised of the result of the 10th, 11th, 12th and 13th presidential election in 2000 to 2012. The spatial units of spatial signals approach are villages. We find that the spatial signals approach is better fitting for the outcome of presidential election. The findings also reveal that the forecast accuracy are almost up to 90 percent, and 70 percent on average. This study concludes that the prediction accuracy of spatial signals approach is well for the outcome of presidential election in Taiwan, and show that the presidential elections in Taiwan indeed exhibit neighborhood effect.
| Status | Finished |
|---|---|
| Effective start/end date | 2013/08/01 → 2016/07/31 |
Keywords
- presidential election
- election forecast
- spatial signals approach
- noise to signal ratio
- classification and regression tree
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