I have an unbalanced panel data and I want to run an ARDL model. The longest time-span is from 1950m1 to 2019m12. I have 100 individuals.
The dependent variable is inflation volatility (the standard deviation of a 60-month overlapping-rolling-window of inflation). Among the explanatory variables I have the Lag1 of inflation volatility, inflation in levels, effective real exchange rate volatility, ...
I use the following regression:

areg sd60_inf_m L1sd60_inf_m mean_tr_hpinf_m Qadj sd60_hpEERm shelter1983 crisis, absorb(SeriesIdCode) vce(cluster SeriesIdCode)

Could I test for dynamic stability of the coefficients? I had in mind the cusum6 test, but for panel data. Does it exist?

I get the following:

PHP Code:
. areg sd60_inf_m L1sd60_inf_m mean_tr_hpinf_m Qadj sd60_hpEERm shelter1983 crisis, abso
> rb(SeriesIdCode) vce(cluster SeriesIdCode)

Linear regression, absorbing indicators         Number of obs     =     43,497
                                                F(   5,     99)   =          .
                                                Prob > F          =          .
                                                R-squared         =     0.9980
                                                Adj R-squared     =     0.9980
                                                Root MSE          =     0.0006

                            (Std. Err. adjusted for 100 clusters in SeriesIdCode)
---------------------------------------------------------------------------------
                |               Robust
     sd60_inf_m |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
----------------+----------------------------------------------------------------
   L1sd60_inf_m |   .9961985   .0008042  1238.80   0.000     .9946029    .9977941
mean_tr_hpinf_m |   .0057533   .0030959     1.86   0.066    -.0003896    .0118962
           Qadj |    .000056   .0000197     2.84   0.005     .0000169     .000095
    sd60_hpEERm |  -.0020381   .0013724    -1.49   0.141    -.0047613     .000685
    shelter1983 |   -.000031   .0000141    -2.19   0.031     -.000059   -2.93e-06
         crisis |  -.0000117   7.99e-06    -1.47   0.145    -.0000276    4.13e-06
          _cons |   .0000634   .0000182     3.47   0.001     .0000272    .0000996
----------------+----------------------------------------------------------------
   SeriesIdCode |   absorbed                                     (100 categories) 
Thank you so much for your help.