Ordinary least square and maximum likelihood estimation of VAR(1) model’s parameters and it’s application on covid-19 in China 2020

Abstract Vector Autoregressive (VAR) is a multivariate time series model for examining objects with two or more variables in which the affect each other under stationarity assumption. This study aims to compare parameter estimation procedure of VAR(1) Ordinary Least Square (OLS) and Maximum Likelihood Estimation (MLE) methods. The comparison investigated by both theoretical empirical approaches. uses daily data number positive cases deaths caused covid-19 China. Result shows that theoretically, OLS MLE give same results. Empirically, it proven done methods provide results either presence absence intercept. For intercept, influenced itself from preceding period. Meanwhile, only explained previous there significant effect period toward cases, but not significant. Hence, no interaction between vice versa.