When you specify the IDENTIFY statement cross correlation with prewhitening, proc arima will print out the following information:   a plot of the sample cross-correlation function for each series specified in the CROSSCORR= option. If a model was previously estimated for a variable in the CROSSCORR= list, the cross-correlations for that series are computed for the prewhitened input and response series. For each input variable with a prewhitening filter, the cross-correlation report for the input series includes the following: a table of test statistics for the hypothesis of no cross-correlation between the input and response series the prewhitening filter used for the prewhitening transformation of the predictor and response variables More details can be found in http://support.sas.com/documentation/cdl/en/etsug/63939/HTML/default/viewer.htm#etsug_arima_sect051.htm.   Hope this helps.   ... View more

Hi Maria. Sorry if I miss-understood you question. The way to produce pre-whitened CCF plots in Proc ARIMA is to: 1) identify the input or X variable. 2) Estimate a model for X that results in white noise residuals. This model is the pre-whitening filter. 3) Identify the Y variable and list the X variable in a crosscorr=(X) option.   Modifying the code sent earlier;     proc  arima  data=in;    identify var=x;    estimate p=(1)(6) q=(6) ml;;    identify var=y crosscorr=(x);    run;   Hope this helps. Chip ... View more

You can capture any statistics shown in a table or graph by using the ODS statements.    https://blogs.sas.com/content/iml/2017/01/09/ods-output-any-statistic.html ... View more