VAR Model Estimation And Application Of IRF And FEVD On Currency Exchange Rates, COVID-19 Cases, And WHO Twitter Information In Southeast Asia

Abstract

This paper examines the impact of the COVID-19 pandemic and World Health Organization (WHO) information dissemination through Twitter on the exchange rates of Southeast Asian countries. The study utilizes a VAR model for analysis, incorporating daily positive cases and the percentage of tweets with positive sentiment as proxies for the pandemic and WHO information, respectively. The VAR models are employed for forecasting and estimating impulse response functions (IRF) and forecast error variance decomposition (FEVD). The forecasting performance is evaluated using mean absolute error (MAE), root-mean-square error (RMSE), and R2 metrics, revealing that only Cambodia possesses a reliable forecasting model. The IRF analysis demonstrates varying effects of the pandemic and WHO information across different countries, while the FEVD results indicate distinct contributions of the pandemic and WHO information in each Southeast Asian country. Additionally, the FEVD analysis reveals that exchange rates are mostly influenced by their own past behavior. Overall, this study provides insights into the economic impact of the COVID-19 pandemic and WHO information on exchange rates in Southeast Asia.