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  • 1.  ARIMAX MODEL IN SPSS

    Posted Thu January 04, 2024 09:56 AM

    Dear IBM professionals

    As we stand on the threshold of a new year, I want to extend my warmest wishes to the entire IBM family. May the coming year be filled with prosperity, innovation, and success for every member of this incredible team.

    I have a question regarding ARIMAX MODEL IN SPSS. I'm doing a Master's Thesis Project in the field of economics. I'm studying Agricultural productivity in 4 different economic phases. Thus, I have 4 dependent variables (=4 different economic phases). I took Population Growth Rate (%) and Average Annual Temperature (°C) as independent variables. I have a mean for them for each 4 economic phases. Overall my formula looks as follows:

    Y_t = a + β1 * Y_{t-1} + β2 * PopulationGrowthRate _t + β3 * AverageAnnualTemperature _t + ε_t                                                                                                                             Formula (1)

    Where:

    Yt - value of agricultural productivity at period t

    a - constant term

    β1 - autoregressive coefficient

    β2 - coefficient for the Annual Population Growth Rate (%) variable

    β3 - coefficient for the Annual Temperature (°C) variable

    εt - error term at period t.

    According to formula (1):

    ·     β1>0, indicates that agricultural productivity in the previous period has a positive impact on agricultural productivity in the current period.

    ·      β1<0, indicates that agricultural productivity in the previous period has a negative impact on agricultural productivity in the current period.

    ·     β2>0, indicates that Population Growth Rate (%) has a positive impact on agricultural productivity.

    ·     β2<0, indicates that Population Growth Rate (%) has a negative impact on agricultural productivity.

    ·     β3>0, indicates that Average Annual Temperature (°C) has a positive impact on agricultural productivity.

    ·     β3<0, indicates that Average Annual Temperature (°C) has a negative impact on agricultural productivity.

    The autoregressive coefficient (β1) measures the impact of agricultural productivity in the previous period on agricultural productivity in the current period. 

    The coefficients for the exogenous variables (β2 and β3) measure the impact of Population Growth Rate (%) and Average Annual Temperature (°C) on agricultural productivity.

    In the IBM SPSS program dialogs, I selected Analyze>Forecasting>Create Models, specified my 2 independent variables, selected ARIMA from the Method dropdown menu, and clicked on the Criteria button... what shall I insert further to run the model? 



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    Rustam Usmanov.
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