difference in difference with control variables

[skclHA]

I am currently running a DID analysis to examine the effects of policy interventions.

I have a few questions about the control variables.

The current data format (example) is as follows.

I know that the time-invariant control variables (sex, age) have the same value at both time points, but how should I handle the time-varying variables (income, work) in the DID regression?

pid	sex	age	income	work
1	1	50	200	1
1	1	50	300	1
2	0	30	500	1
2	0	30	400	0
3	0	20	600	0
3	0	20	900	1
4	1	40	800	0
4	1	40	400	0

1. Can I put the INCOME and WORK variables into the model together like the command below? If that's true, what is the interpretation of the results?

PROC MIXED DATA = LONG;

CLASS POST POLICY SEX AGE;

MODEL DEPENDENT=POST|POLICY SEX AGE INCOME WORK / SOLUTION;

LSMEANS POST|EXPOSED / DIFF;

ESTIMATE 'D-I-D' EXPOSED*POST 1 -1 -1 1;

RANDOM Int/SUBJECT=PID TYPE=UN ;

RUN;

2. How would I write the command if I want to control for changes in the control variable (incom, work) over time?

[Ksharp]

https://communities.sas.com/t5/Statistical-Procedures/Covariate-values-in-ESTIMATE-statements-when-u...

https://communities.sas.com/t5/Statistical-Procedures/Difference-in-Difference-analysis-for-longitud...

[skclHA]

Thank you for the valuable information. However, it's a bit challenging for me. Could you please provide simpler information regarding continuous variables as the dependent variable? I apologize in advance if it's a difficult request.

[Ksharp · Accepted solution]

You could use AT to control variables  whether it is category or continuous.

Here is some example:

24447 - Examples of writing CONTRAST and ESTIMATE statements (sas.com)

Sure. Also @SteveDenham  could you an answer .