ESTIMATING CO-INTEGRATING REGRESSION IN TIME SERIES
Abstract: The study investigated the equilibrium relation, on the long run, between the local production (GDP) and the index number for the wholesale prices during the period 1986-2016 and identifying their integration degree so that some methods could be used to estimate and compare the regression of co-integration to create accurate estimations with a high degree of confidence. Prediction of greater precision and the study of the unit root test for the stability of time series show that the time series for both the index number of wholesale prices and the local production (GDP) are unstable at its level at the first difference while it was stable at the second difference. The latent root maximization test showed that there was at least one vector of co-integration. Three methods of joint integration were used in comparison with the ordinary least squares method namely: the modified least squares method, the method of regression of the common integers and the lower dynamic squares method. The method of dynamic least squares was the best way to estimate the regression of co-integration since it gave the best results in interpreting the relationship between the two variables.
Publication year 2019
Organization Name
serial title مجلة الفيوم للبحوث والتنمية الزراعية، كلية الزراعة، جامعة الفيوم
Author(s) from ARC
Publication Type Journal
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