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

• المؤلفون الرئيسيون: Arsua, Andre Millard M, Azucena, Raphael Matthew D
• التنسيق: text
• اللغة: English
• منشور في: Animo Repository 2022
• الموضوعات: Gross domestic product > Philippines; Forecasting; Mathematics
• الوصول للمادة أونلاين: https://animorepository.dlsu.edu.ph/etdb_math/3; https://animorepository.dlsu.edu.ph/cgi/viewcontent.cgi?article=1003&context=etdb_math
• المؤسسة: 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...