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Abstract

Gross Domestic Product (GDP) is the total pecuniary or mart value of all final commodity and services that are produced within country's borders in a given time. We choose GDP to predict in Iraq since 2000 to 2018.The state and governments rely on GDP to help shape policy or decide how much public spending is affordable. Combining grey regression is a modern statistical technique of modeling, using this type of model is related to its highly accuracy therefor, in this study we used combined grey regression model to predict the gross domestic production of Iraq because it gives less Mse than grey or regression models alone which is equal to 1.3165 and estimated parameter of grey C1, regression C2 are equals to (2.9 and 0.205) respectively and the intercept C3 is equal to 1.8569 the outcome showed that the new model could attain preferable predicting result contrasted with different predicting methods.

Vector Autoregressive Integrating Moving Average (Varima) Model of COVID-19 Pandemic and Oil Price

“…The current study used the Extended Cross Correlation Matrix (ECCM) to determine the model order. The test hypothesis is as follows (Asraa et al, 2018;Rahim et al, 2020):…”

“…The quantity of parameters makes the selection of p and q crucial, (p + q + 3) d 2 , where d is the number of the series, grew dramatically with p and q, causing statistical difficulties. The estimation of the parameters will be inconsistent if orders below the true orders of the VARMA (p, q) models are chosen, and it is likely to be inaccurate if orders above the true orders are chosen (Mainassara, 2010;Nasser et al, 2009;Rahim et al, 2020).…”