Forecasting the Philippines’ GDP growth using long short-term memory neural network regression and mixed-data sampling regression models

• Main Authors: Arsua, Andre Millard M, Azucena, Raphael Matthew D
• Format: text
• Language: English
• Published: Animo Repository 2022
• Subjects: Gross domestic product > Philippines; Forecasting; Mathematics
• Online Access: https://animorepository.dlsu.edu.ph/etdb_math/3; https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1003&context=etdb_math
• Institution: De La Salle University

Having better forecasts is crucial in the Philippines’ state of economic recovery. The study intends to forecast the Philippines’ GDP growth rate from 2011 to 2021 using two emerging methods used for mixed-frequency data: Mixed-Data Sampling (MIDAS) Regression and Long Short-Term Memory (LSTM) Neura...