I have a panel dataset of n communities (i), observed at a given time (t), where we observe (y_t) and some IVs (x1_t), (x2_t).
Data would look like
I am interested in how x moderates the effects of shocks to y.
That is: Are communities who are currently higher in x more protected against shocks to y such that a shock is less likely to persist in the time series?
How would I go about modeling this?
Data would look like
| i | t | y | x |
| community_1 | 1 | 10 | 2 |
| community_2 | 2 | 11 | 4 |
That is: Are communities who are currently higher in x more protected against shocks to y such that a shock is less likely to persist in the time series?
How would I go about modeling this?
