Nowcasting Vietnam's Export Growth with Mixed Frequency Data

Abstract

Purpose: The primary objective of this study is to investigate and employ a practical and meaningful nowcasting model to predict Vietnam's export growth based on factors of export supply and demand alongside relevant financial indicators.   Theoretical Framework: This study employs the concepts and theories of nowcasting model with mixed frequency data to create the conceptual framework.   Methodology: This study employs four commonly-used models in nowcasting: the bridge equation model (BEQ), Bayesian VAR model (BVAR), mixed frequency vector autoregressive model (MFVAR), and mixed data sampling regression (MIDAS).   Findings: According to the experimental findings, the mixed frequency data models outperformed the models utilizing the same frequency data in nowcasting Vietnam's export growth. Additionally, this model demonstrated effectiveness in instantaneous and short-term forecasting. MIDAS emerged as the most suitable choice for nowcasting Vietnam's export growth among the models examined.   Implication of Research: using data with mixed frequency along with corrresponding methods is the good way for nowcasting.   Originality/Value: This study used macroeconomics factors to nowcast the export growth in Vietnam. It applied four different models including BEQ, BVAR, MFVAR, and MIDAS. The study reveals the roles of data and the potential capability in nowcasting of MIDAS model.