Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1017819 | Journal of Business Research | 2014 | 6 Pages |
Abstract
Quantile regression is popular because it provides more information as well as comprehensive interpretations. To improve forecasting performance, this study proposes a new quantile information criterion (NQIC), on the basis of the coefficient of variation, and expects the NQIC to reflect whether a variable is predictable. The health care expenditure data determine the thresholds for the NQICs. The thresholds assist in forecasting the development of information and communication technology. From the empirical analyses, the NQICs and thresholds greatly improve the forecasting performance.
Related Topics
Social Sciences and Humanities
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Authors
Kun-Huang Huarng, Tiffany Hui-Kuang Yu,