Economic Forecasting for Thailand using Predictors with Different Frequency
DOI:
https://doi.org/10.14456/mjba.2020.1คำสำคัญ:
Elastic Net Regression JEL Classification Codes: C36, C53, C55, E17, GDP, Growth, MIDASบทคัดย่อ
This study examines economic growth of Thailand using predictor variables with different frequencies (yearly, quarterly, and monthly). Mixed Data Sampling (MIDAS) is approached to combine the enormously different frequency data. Ridge, LASSO, and elastic net regression are also used to specify factors affecting to Thailand economic growth. Data have been carefully collected from January 2000 to December 2019, total 20 years. The empirical results show that variables with positive impact on GDP growth consist of industry value added (INDUSVA), tax revenue (TAXREVEN), electricity consumption (ELECC), and investment growth (INVEST), while negative impact of external debt (EXD) on growth also exists.
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