The comparition of Maximum Likelihood Estimator with other ones about variance

In the field of statistics, Maximum Likelihood Estimator is a method to estimate the parameters of an econometric model. When an operation is applied on a set of values, one statistical model is achieved. Then, Maximum Likelihood Estimator could generate the estimation of the parameters of the model. This method is similar to many well-known statistical estimation approaches. Generally, this approach for a certain amount of data is assigning values to the parameters of the model so that one distribution is generated, which is most likely related to population data. Hence, this research compares the Maximum Likelihood Estimator with other estimation methods using computer programming and computer simulation in Eviews softeware. The results showed that
Variance of Maximum Likelihood Estimator is lower but it is bias. Then, according to the
struggle between Maximum Likelihood Estimator and other estimators, we can find an
estimator which possesses the minimum mean square error.