Estimating Dynamic Panel Data with different time periods in DV and EV's

[fabian maendli]

Dear Statalist,

I have dynamic panel data with N = 30 over 192 months (16 years), which means small N and large T. I would like to estimate a DV that is monthly, using three annual lags of the DV (and the same for all other explanatory and control variables). The reason is that if I use monthly lags of the DV spanning three years, I would have to estimate models with very large numbers of regressors - on the other hand if the DV is annual too, then the number of observations is not large enough and I do not realize the full potential of the data, which is monthly.

1) Is this feasible from an econometrical perspective?
2) What kinds of models would be suitable?

Thanks in advance for any help or advice,
Fabian

[fabian maendli]

Dynamic panel-data estimation                   Number of obs     =      3,663
Group variable: cat_company                     Number of groups  =         30
Time variable: cat_year_m~h
                                                Obs per group:
                                                              min =          6
                                                              avg =      122.1
                                                              max =        158

Number of instruments =    185                  Wald chi2(65)     =    1451.67
                                                Prob > chi2       =     0.0000
One-step results
------------------------------------------------------------------------------------------------
                      freq_neg | Coefficient  Std. err.      z    P>|z|     [95% conf. interval]
-------------------------------+----------------------------------------------------------------
                      freq_neg |
                           L1. |  -.0538829   .0259616    -2.08   0.038    -.1047668    -.002999
                           L2. |  -.3202612    .025061   -12.78   0.000    -.3693799   -.2711426
                           L3. |   -.356995   .0290229   -12.30   0.000     -.413879   -.3001111
                           L4. |  -.5712165    .031787   -17.97   0.000    -.6335179   -.5089151
                           L5. |  -.2679029   .0313788    -8.54   0.000    -.3294043   -.2064016
                           L6. |  -.3501498   .0299518   -11.69   0.000    -.4088543   -.2914454
                           L7. |  -.3858191   .0288397   -13.38   0.000    -.4423438   -.3292944
                           L8. |  -.1949953   .0314511    -6.20   0.000    -.2566384   -.1333523
                           L9. |  -.2165878   .0306888    -7.06   0.000    -.2767367   -.1564389
                          L10. |   -.254612   .0308063    -8.26   0.000    -.3149913   -.1942327
                          L11. |  -.1505806    .038828    -3.88   0.000    -.2266822   -.0744791
                          L12. |  -.2738982   .0356228    -7.69   0.000    -.3437177   -.2040788
                          L13. |   3.437116   .5935349     5.79   0.000     2.273809    4.600423
                          L14. |   3.365919   .5935252     5.67   0.000     2.202631    4.529207
                          L15. |   3.530314   .5940444     5.94   0.000     2.366008    4.694619
                          L16. |   3.517882    .592144     5.94   0.000     2.357301    4.678462
                          L17. |   3.471721   .5912702     5.87   0.000     2.312853    4.630589
                          L18. |   3.520242   .5936442     5.93   0.000     2.356721    4.683764
                          L19. |   3.383958   .5930395     5.71   0.000     2.221622    4.546294
                          L20. |   3.410956   .5942216     5.74   0.000     2.246303    4.575609
                          L21. |    3.48619   .5903409     5.91   0.000     2.329143    4.643237
                          L22. |   3.349951   .5928484     5.65   0.000      2.18799    4.511913
                          L23. |   3.515272   .5916337     5.94   0.000     2.355691    4.674852
                          L24. |   3.525092   .5970339     5.90   0.000     2.354928    4.695257
                          L25. |    2.00257   .5885878     3.40   0.001     .8489592    3.156181
                          L26. |   1.740636   .5879331     2.96   0.003     .5883078    2.892963
                          L27. |   1.886602   .5894676     3.20   0.001     .7312669    3.041938
                          L28. |   1.907984   .5870581     3.25   0.001      .757371    3.058596
                          L29. |   1.944944   .5871373     3.31   0.001     .7941764    3.095712
                          L30. |   1.801181   .5879795     3.06   0.002     .6487626      2.9536
                          L31. |   1.793904   .5832464     3.08   0.002     .6507618    2.937046
                          L32. |   1.915111   .5814324     3.29   0.001     .7755241    3.054697
                          L33. |   1.806886   .5795266     3.12   0.002     .6710343    2.942737
                          L34. |   1.965477    .582878     3.37   0.001     .8230569    3.107897
                          L35. |   1.829791   .5806689     3.15   0.002     .6917013    2.967881
                          L36. |   1.789048   .5852408     3.06   0.002      .641997    2.936099
                               |
freq_neg_13_to_24_months_prior |  -3.406737   .5916904    -5.76   0.000    -4.566429   -2.247045
freq_neg_25_to_36_months_prior |  -1.775813   .5794399    -3.06   0.002    -2.911494   -.6401313
           freq_pos_tot_4_1_12 |   .0043417   .0200124     0.22   0.828    -.0348819    .0435652
          freq_pos_tot_4_13_24 |  -.0295224   .0204835    -1.44   0.150    -.0696692    .0106245
          freq_pos_tot_4_25_36 |  -.0348383   .0211783    -1.64   0.100     -.076347    .0066705
          freq_neut_tot_4_1_12 |   .1696598   .0769817     2.20   0.028     .0187784    .3205411
         freq_neut_tot_4_13_24 |  -.1639081   .0857059    -1.91   0.056    -.3318885    .0040723
         freq_neut_tot_4_25_36 |   .0303198   .0738768     0.41   0.682    -.1144761    .1751158
                     PR_Comp_1 |   .2281865   .0554336     4.12   0.000     .1195387    .3368344
                     PR_Comp_2 |    .142109   .0592998     2.40   0.017     .0258836    .2583344
                     PR_Comp_3 |    .065443   .0638567     1.02   0.305    -.0597138    .1905998
                MSCI_ESG_ENV_1 |   .0053786   .2036366     0.03   0.979    -.3937419     .404499
                MSCI_ESG_ENV_2 |   .1874652   .1861139     1.01   0.314    -.1773114    .5522417
                MSCI_ESG_ENV_3 |   .1916222   .2348751     0.82   0.415    -.2687247     .651969
         assets_total_usd_cs_s |  -.0063877   .0037729    -1.69   0.090    -.0137824     .001007
      assets_total_usd_cs_2y_s |   .0050705   .0040571     1.25   0.211    -.0028813    .0130223
      assets_total_usd_cs_3y_s |  -.0119312   .0037577    -3.18   0.001    -.0192961   -.0045664
                net_sales_cs_s |   .0949077   .0163251     5.81   0.000     .0629111    .1269042
             net_sales_cs_2y_s |  -.2047092   .0167555   -12.22   0.000    -.2375494   -.1718691
             net_sales_cs_3y_s |   .2728473   .0236579    11.53   0.000     .2264787    .3192158
                cash_flow_cs_s |   .0112143   .1306158     0.09   0.932     -.244788    .2672165
             cash_flow_cs_2y_s |  -.0188446   .1583632    -0.12   0.905    -.3292309    .2915417
             cash_flow_cs_3y_s |  -.0679756   .1560878    -0.44   0.663    -.3739021    .2379509
                      roa_cs_s |  -.1232024   .3560136    -0.35   0.729    -.8209763    .5745715
                   roa_cs_2y_s |   .1283978   .3431579     0.37   0.708    -.5441793    .8009748
                   roa_cs_3y_s |   .1253875   .2146592     0.58   0.559    -.2953367    .5461118
      tot_debt_tot_assets_cs_s |  -.0890765   .0888833    -1.00   0.316    -.2632844    .0851315
   tot_debt_tot_assets_cs_2y_s |    -.00432   .0916886    -0.05   0.962    -.1840263    .1753864
   tot_debt_tot_assets_cs_3y_s |    .029038   .0755197     0.38   0.701    -.1189778    .1770538
                         _cons |  -4.573229   3.787587    -1.21   0.227    -11.99676    2.850306
------------------------------------------------------------------------------------------------
Instruments for differenced equation
        GMM-type: L(2/2).freq_neg
        Standard: D.freq_pos_tot_4_1_12 D.freq_pos_tot_4_13_24 D.freq_pos_tot_4_25_36
                  D.freq_neut_tot_4_1_12 D.freq_neut_tot_4_13_24 D.freq_neut_tot_4_25_36
                  D.PR_Comp_1 D.PR_Comp_2 D.PR_Comp_3 D.MSCI_ESG_ENV_1 D.MSCI_ESG_ENV_2
                  D.MSCI_ESG_ENV_3 D.assets_total_usd_cs_s D.assets_total_usd_cs_2y_s
                  D.assets_total_usd_cs_3y_s D.net_sales_cs_s D.net_sales_cs_2y_s
                  D.net_sales_cs_3y_s D.cash_flow_cs_s D.cash_flow_cs_2y_s D.cash_flow_cs_3y_s
                  D.roa_cs_s D.roa_cs_2y_s D.roa_cs_3y_s D.tot_debt_tot_assets_cs_s
                  D.tot_debt_tot_assets_cs_2y_s D.tot_debt_tot_assets_cs_3y_s
Instruments for level equation
        Standard: _cons

. estat sargan
Sargan test of overidentifying restrictions
H0: Overidentifying restrictions are valid

        chi2(119)    =  1057.944
        Prob > chi2  =    0.0000