Jurnal Agro Ekonomi, JAE, Vol. 26, Nomor 2, Oktober 2008, ABSTRAK : This paper primarily attempts to detect the in the present upshots of global warming temperature data. It has been done through the estimation of the long memory fractional parameter using a simulation technique in the presence of additive outliers which stands as wild observations generated in the atmosphere due to global warming. The, the study investigates emprirically the impact of global warming on the particular aspect of global agricultural production. Based on monte Carlo simulations, a data generating process is applied where additive outliers are generated in a discrete way. Observed facts reveal that additeve outilers affect the bias and the MSE of the estimated fractional parameter. The size of the additive outliers in data generating process has also important effects on the estimated fractional parameter depending on the value of true fractional parameter....