TITLE:
A Survey of Selected Grey Forecasting Models with Application to Medical Tourism Forecasting
AUTHORS:
Althea Dianne La Foucade, Samuel Gabriel, Ewan Scott, Karl Theodore, Charmaine Metivier
KEYWORDS:
Medical Tourism, Medical Tourism Demand, Grey Forecasting and Parameter Optimization
JOURNAL NAME:
Theoretical Economics Letters,
Vol.9 No.4,
April
26,
2019
ABSTRACT: This paper examines the
predictive capacity of two Grey Systems Forecasting models. The original Grey
GM(1,1) Forecasting model, introduced by Deng [1] [2] together
with an improved Grey GM(1,1) model proposed by Ji et al. [3] are used to forecast medical tourism demand for
Bermuda. The paper also introduces a quasi-optimization method for the
optimization of the alpha (weight) parameter. Five steps ahead out-of-sample
forecasts are produced after estimating the models using four data points. The
results indicate that the optimization of the alpha parameter substantially
improves the predictive accuracy of the models; reducing the five steps ahead
out-of-sample Mean Absolute Percentage Error from roughly 7% to roughly 3.80%
across the two models. Largely, the forecasting approaches demonstrate
significant potential for use as an
alternative to the traditional forecasting methods in circumstances
where substantial amounts of high-quality data are not available.