Hi,
I want to see how sensitive of each variable to a response variable in percentage for a time series model generated by an ARIMA procedure in SAS/ETS, for instance, I have a model as follows:
Y(1) = AR(1) + MA(1) + aX + bZ + cR,
where Y(1) is a first-order difference term of the response variable, AR(1) is a first-order autocorrelation term, MA(1) is a first-order moving average term, and X, Z, R are the predictor variables in the model.
Each of them has its own coefficient, and I want to see the percentage change of the response variable while each predictor variable changes for 1%, for instance,
Variable Sensitivity- Impact of One Point Change on Y(1)
Predictor Variable | Sensitivity |
| ||
AR(1) | 30% | |||
MA(1) | 1.5% | |||
X | -19% | |||
Z | -11% | |||
R | -30% |
How can I generate this kind of table for a time series model in SAS/ETS?
Thank you for your help!
Lawrence
Not sure, if I understood you correctly:
ODS Output ParameterEstimates=Est;
Proc ARIMA Data=A;
Identify Var=x CrossCorr=(y z r);
Estimate p=1 q=1 Input=(y z r);
Run;
ODS Output Close;
Data Sensitivity1Pct (Keep=Parameter Variable Sensitivity);
Set Est;
Sensitivity=Estimate*0.01;
Run;
Not sure, if I understood you correctly:
ODS Output ParameterEstimates=Est;
Proc ARIMA Data=A;
Identify Var=x CrossCorr=(y z r);
Estimate p=1 q=1 Input=(y z r);
Run;
ODS Output Close;
Data Sensitivity1Pct (Keep=Parameter Variable Sensitivity);
Set Est;
Sensitivity=Estimate*0.01;
Run;
Thank you!
After you got the data set Sensitivity1Pct how do you estimate the effect of a change of an independent variable on the dependent variable while keeping all the other terms fixed?
Thank you for your help!
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