How to do bys regression using ASDOCX in Stata 16 or stata 17

[Aduba Joseph]

#15885

Hello,
It is possible to do a nested bys regression with asdocx in state 16 or state 17?
For example, I have panel data of n-industry and t year. Now within the n-industry, I have four classifications: high tech, medium high tech, medium low tech and low tech. I want to estimate many panel data regressions for each industrial group using the nested function such that all regressions be nested in one table for each industrial group.
e.g.

bys group, sort : asdocx xtreg lnCt1 $xvar1, fe robust replace save(electricity) dec(4) stat(p, rmse) fs(8) font(Times New Roman) nest table_layout(autofit) 
bys group, sort : asdocx xtreg lnCt1 $xvar2, fe robust save(electricity) dec(4) stat(p, rmse) fs(8) font(Times New Roman) nest 
bys group, sort : asdocx xtreg lnCt1 $xvar3, fe robust save(electricity) dec(4) stat(p, rmse) fs(8) font(Times New Roman) nest
bys group, sort : asdocx xtreg lnCt1 $xvar4, fe robust save(electricity) dec(4) stat(p, rmse) fs(8) font(Times New Roman) nest
bys group, sort : asdocx xtreg lnCt1 $xvar5, fe robust save(electricity) dec(4) stat(p, rmse) fs(8) font(Times New Roman) nest
bys group, sort : asdocx xtreg lnCt1 $xvar6, fe robust save(electricity) dec(4) stat(p, rmse) fs(8) font(Times New Roman) nest
bys group, sort : asdocx xtreg lnCt1 $xvar7, fe robust save(electricity) dec(4) stat(p, rmse) fs(8) font(Times New Roman) nest
bys group, sort : asdocx xtreg lnCt1 $xvar8, fe robust save(electricity) dec(4) stat(p, rmse) fs(8) font(Times New Roman) nest

I expect each of the codes above to produce neatly nested Tables by industrial category (group). But this is not the case. I know there is a way to get this done but I simply don’t know how to figure it out. Any help?

[Dr. Attaullah Shah]

#15886

I have added the bysort and by options for nested regressions. First update asdocx. One example is presented below:

asdocx_update

* Use grunfeld dataset
webuse grunfeld

* Just keep 5 companies in the dataset and then estimate regression for each company
keep if company < 6

* Note the bys company
bys company : asdocx reg invest mvalue kstock, nest replace
                         

                                          Table: Regression results
  0 |1                                   2                3                4                5                6 
----+----------------------------------------------------------------------------------------------------------
  1 |                                  (1)              (2)              (3)              (4)              (5) 
----+----------------------------------------------------------------------------------------------------------
  2 |                                    1                2                3                4                5 
  3 |mvalue                       0.118***         0.118***         0.118***         0.118***         0.118*** 
  4 |                              (0.009)          (0.009)          (0.009)          (0.009)          (0.009) 
  5 |kstock                       0.256***         0.256***         0.256***         0.256***         0.256*** 
  6 |                              (0.039)          (0.039)          (0.039)          (0.039)          (0.039) 
  7 |_cons                      -63.611***       -63.611***       -63.611***       -63.611***       -63.611*** 
  8 |                             (22.376)         (22.376)         (22.376)         (22.376)         (22.376) 
  9 |Observations                      100              100              100              100              100 
 10 |R-squared                       0.761            0.761            0.761            0.761            0.761 
---------------------------------------------------------------------------------------------------------------

[Bijaya Kumar Padhi]

#16159

Do the same code will work for logistic regressions for nested tables?

[Dr. Attaullah Shah]

#16164

Hello Prof. Bijaya Kumar
Yes, nested regression tables can be created for all regression commands. See this example

webuse lbw
asdocx logistic low age lwt i.race smoke ptl ht ui, replace nest
asdocx logistic low age lwt i.race  ptl ht ui,  nest
asdocx logistic low age lwt i.race smoke ,  nest

                           Table: Regression results
  0 |1                                  2               3               4 
----+-----------------------------------------------------------------------------
  1 |                                 (1)             (2)             (3) 
  2 |                                 low             low             low 
----+-----------------------------------------------------------------------------
  3 |age                           -0.027          -0.032          -0.023 
  4 |                             (0.036)         (0.035)         (0.034) 
  5 |lwt                         -0.015**        -0.017**         -0.013* 
  6 |                             (0.007)         (0.007)         (0.006) 
  7 |1bn.race                                                             
  8 |                                                                     
  9 |2.race                       1.263**         1.042**         1.231** 
 10 |                             (0.526)         (0.508)         (0.517) 
 11 |3.race                       0.862**            0.41         0.944** 
 12 |                             (0.439)          (0.38)         (0.416) 
 13 |smoke                        0.923**                        1.054*** 
 14 |                             (0.401)                          (0.38) 
 15 |ptl                            0.542         0.679**                 
 16 |                             (0.346)         (0.341)                 
 17 |ht                          1.833***        1.896***                 
 18 |                             (0.692)         (0.709)                 
 19 |ui                            0.759*          0.767*                 
 20 |                             (0.459)         (0.446)                 
 21 |_cons                          0.461           1.308            0.33 
 22 |                             (1.205)          (1.15)         (1.108) 
 23 |Observations                     189             189             189 
 24 |Pseudo R2                      0.142           0.118           0.086 
----------------------------------------------------------------------------------

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