Samaneh Negarchi - Department of Agricultural Economics, ShahidBahonar University of Kerman, Kerman, I. R. Iran.
M.R. Zare Mehrjerdi - Department of Agricultural Economics, ShahidBahonar University of Kerman, Kerman, I. R. Iran.
H. Mehrabi Boshrabadi - Department of Agricultural Economics, ShahidBahonar University of Kerman, Kerman, I. R. Iran.
H. Nezamabadi Pour - Department of Electrical Engineering, ShahidBahonar University of Kerman, Kerman, I. R. Iran.

ABSTRACT-Due to the important role productivity plays in future decision making and programming, the productivity indexes should have accurate quantities. In this study, Auto-Regressive Distributed Lag (ARDL) and Genetic Algorithm (GA) methods are applied to time series of ۱۹۷۸-۲۰۰۸ to accurately measure total factor productivity (TFP) in the agricultural sector of Iran. The comparison of these two methods shows that GA method is more efficient than ARDL model. Also, the growth of TFP in the agricultural sector of Iran has had high fluctuations and annual average of productivity growth in this sector has been -۰.۱۶ during the period of the study. Therefore, it is necessary to emphasize the optimum use of available inputs, their appropriate combinations and increasing productivity in the agricultural sector of Iran.

Genetic Algorithm, Auto-Regressive Distributed Lag Total Factors Productivity Agriculture, Iran