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http://dx.doi.org/10.7465/jkdi.2013.24.2.321

Time series regression model for forecasting the number of elementary school teachers  

Ryu, Soo Rack (Department Computing.Statistics, Daegu University)
Kim, Jong Tae (Department Computing.Statistics, Daegu University)
Publication Information
Journal of the Korean Data and Information Science Society / v.24, no.2, 2013 , pp. 321-332 More about this Journal
Abstract
Because of the continuous low birthrates, the number of the elementary students will decrease by 17% in 2020 compared to 2011. The purpose of this study is to forecast the number of elementary school teachers until 2020. We used the data in education statistical year books from 1970 to 2010. We used the time-series regression model, time series grouped regression model and exponential smoothing model to predict the number of teachers for the next ten years. Consequently time-series grouped regression model is a better model for forecasting the number of elementary school teachers than other models.
Keywords
Exponential smoothing; group-specific time series regression analysis; time serise regression;
Citations & Related Records
Times Cited By KSCI : 3  (Citation Analysis)
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