asdocx: Export from Stata to Word, Excel, LaTeX & HTML › Forums › asdocx Forum › How to do bys regression using ASDOCX in Stata 16 or stata 17
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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?
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 ---------------------------------------------------------------------------------------------------------------
Do the same code will work for logistic regressions for nested tables?
Hello Prof. Bijaya Kumar
Yes, nested regression tables can be created for all regression commands. See this examplewebuse 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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