Prediction of Exit Polls for the Presidential Election in 2007 and 2013 by Using Nonresponse ModelsPrediction of Exit Polls for the Presidential Election in 2007 and 2013 by Using Nonresponse Models
- Other Titles
- Prediction of Exit Polls for the Presidential Election in 2007 and 2013 by Using Nonresponse Models
- Authors
- 최보승; 김성용
- Issue Date
- 2017
- Publisher
- 한국자료분석학회
- Keywords
- contingency table; nonresponse mechanism; boundary solution; exit poll.
- Citation
- Journal of The Korean Data Analysis Society, v.19, no.1, pp.1 - 9
- Indexed
- KCI
- Journal Title
- Journal of The Korean Data Analysis Society
- Volume
- 19
- Number
- 1
- Start Page
- 1
- End Page
- 9
- URI
- https://scholar.korea.ac.kr/handle/2021.sw.korea/85342
- DOI
- 10.37727/jkdas.2017.19.1.1
- ISSN
- 1229-2354
- Abstract
- Estimation of nonresponses in exit polls frequently produces inaccurate election results. Since estimates of nonresponses differ depending on the assumed mechanism, nonresponse mechanism should be determined prior to the analysis. However, nonresponse mechanism is not testable. From this problem, estimates from all possible models need to be provided. Along with the selection of nonresponse mechanism, ML (maximum likelihood) estimates under NMAR (not missing at random) have a boundary solution problem which is that cell expectations of more than one columns are estimated as zeros. To overcome the boundary solution problem, various Bayesian models have been suggested. In this paper, ML estimation under MAR (missing at random) and NMAR as well as Bayesian estimation under NMAR are applied to the two exit polls for 2007 and 2013 Korean presidential elections with 53 contingency tables. In comparing ML and Bayesian estimates, we also consider weighting methods to reduce biases. As results, ML estimates under MAR produce more accurate election results and better than the Bayesian approaches under NMAR.
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Collections - Graduate School > Department of Economics and Statistics > 1. Journal Articles
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