Abstract
In this study, we compare the performance between three leading indicators, namely, export, unemployment rate, and SET index in forecasting QGDP growth in Thailand using the mixed-frequency data sampling (MIDAS) approach. The MIDAS approach allows us to use monthly information of leading indicators to forecast QGDP growth without transforming them into quarterly frequency. The basic MIDAS model and the U-MIDAS model are considered. Our findings show that unemployment rate is the best leading indicator for forecasting QGDP growth for both MIDAS settings. In addition, we investigate the forecast performance between the basic MIDAS model and the U-MIDAS model. The results suggest that the U-MIDAS model can outperform the basic MIDAS model regardless of leading indicators considered in this study.
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Acknowledgements
The authors would like to thank the anonymous reviewer for useful suggestions which have greatly improved the quality of this paper. This research is supported by Puay Ungphakorn Centre of Excellence in Econometrics, Faculty of Economics, Chiang Mai University.
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Kingnetr, N., Tungtrakul, T., Sriboonchitta, S. (2017). Forecasting GDP Growth in Thailand with Different Leading Indicators Using MIDAS Regression Models. In: Kreinovich, V., Sriboonchitta, S., Huynh, VN. (eds) Robustness in Econometrics. Studies in Computational Intelligence, vol 692. Springer, Cham. https://doi.org/10.1007/978-3-319-50742-2_31
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DOI: https://doi.org/10.1007/978-3-319-50742-2_31
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