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A quantile regression forecasting model for ICT development
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Purpose
– Because quantile regression gets more popular and provides more comprehensive interpretations, it is important to advance quantile regression for forecasting. By extending the convention quantile regression, the purpose of this paper is to propose a quantile regression-forecasting model to forecast information and communication technology (ICT) development.
Design/methodology/approach
– This paper proposes an approach to forecasting based on quantile regression method.
Findings
– Via quantile information criterion, the proposed approach can identify whether the independent variables are predictable. For those which are predictable, the proposed approach can be used to forecast these variables.
Practical implications
– The proposed approach is used to forecast ICT development. It can also be used to forecast other problem domains.
Originality/value
– Based on the empirical results, the proposed approach advances the application of quantile regression model to forecast. The applicability of quantile regression model is greatly enhanced.
Title: A quantile regression forecasting model for ICT development
Description:
Purpose
– Because quantile regression gets more popular and provides more comprehensive interpretations, it is important to advance quantile regression for forecasting.
By extending the convention quantile regression, the purpose of this paper is to propose a quantile regression-forecasting model to forecast information and communication technology (ICT) development.
Design/methodology/approach
– This paper proposes an approach to forecasting based on quantile regression method.
Findings
– Via quantile information criterion, the proposed approach can identify whether the independent variables are predictable.
For those which are predictable, the proposed approach can be used to forecast these variables.
Practical implications
– The proposed approach is used to forecast ICT development.
It can also be used to forecast other problem domains.
Originality/value
– Based on the empirical results, the proposed approach advances the application of quantile regression model to forecast.
The applicability of quantile regression model is greatly enhanced.
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