Figure for panel quantile regression

[River Huang]

Dear All, I know that we can obtain figures of coefficients estimates of quantile regression by using -grqreg- (please ssc install grqreg) after the -qreg- command. An example is

webuse grunfeld, clear

// please ssc install grqreg
// without fixed effects
qreg invest mvalue kstock
grqreg, ci ols olsci

Thanks to Machado, J.A.F. and Santos Silva, J.M.C. (2018), Quantiles via Moments, Journal of Econometrics, forthcoming, now we can use -xtqreg- (please ssc install xtqreg) command to estimate quantile regressions with fixed effects. An example is

xtset company year

// please ssc install xtqreg
// with fixed effects
forvalues q = 10(10)90 {
    xtqreg invest mvalue kstock, q(0.`q')
}

with results as

. // please ssc install xtqreg
. // with fixed effects
. forvalues q = 10(10)90 {
  2.     xtqreg invest mvalue kstock, q(0.`q')
  3. }      



                              MM-QR regression results
Number of obs = 200
.1 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |    .084099    .029583     2.84   0.004     .0261174    .1420805
      kstock |   .2646024   .0552066     4.79   0.000     .1563994    .3728054
------------------------------------------------------------------------------




                              MM-QR regression results
Number of obs = 200
.2 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |   .0915338   .0237915     3.85   0.000     .0449033    .1381644
      kstock |   .2775904   .0444176     6.25   0.000     .1905334    .3646474
------------------------------------------------------------------------------




                              MM-QR regression results
Number of obs = 200
.3 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |   .0978504   .0224984     4.35   0.000     .0537543    .1419465
      kstock |   .2886248     .04201     6.87   0.000     .2062867    .3709629
------------------------------------------------------------------------------




                              MM-QR regression results
Number of obs = 200
.4 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |   .1031741   .0244971     4.21   0.000     .0551607    .1511875
      kstock |   .2979249   .0457377     6.51   0.000     .2082807    .3875691
------------------------------------------------------------------------------




                              MM-QR regression results
Number of obs = 200
.5 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |    .112539   .0329018     3.42   0.001     .0480526    .1770254
      kstock |   .3142844   .0614081     5.12   0.000     .1939268     .434642
------------------------------------------------------------------------------




                              MM-QR regression results
Number of obs = 200
.6 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |   .1164492   .0373915     3.11   0.002     .0431631    .1897353
      kstock |   .3211153   .0697806     4.60   0.000     .1843478    .4578827
------------------------------------------------------------------------------




                              MM-QR regression results
Number of obs = 200
.7 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |   .1249394   .0484885     2.58   0.010     .0299037    .2199751
      kstock |   .3359468   .0904895     3.71   0.000     .1585906    .5133029
------------------------------------------------------------------------------




                              MM-QR regression results
Number of obs = 200
.8 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |   .1335321   .0603947     2.21   0.027     .0151606    .2519036
      kstock |   .3509575   .1127063     3.11   0.002     .1300572    .5718578
------------------------------------------------------------------------------




                              MM-QR regression results
Number of obs = 200
.9 Quantile regression
------------------------------------------------------------------------------
             |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
      mvalue |    .149272   .0832815     1.79   0.073    -.0139567    .3125008
      kstock |   .3784536   .1554208     2.44   0.015     .0738345    .6830727
------------------------------------------------------------------------------

My question is: How can I draw a figure (like the one above) in this situation? Thanks.

[Lisanne Stolte]

Any update on this?

[Joao Santos Silva]

For the moment, this has to be done manually. That is, we need to save the estimates and standard errors for the different quantiles and then use them to construct the plot.

Best wishes,

Joao

[Lisanne Stolte]

Okay too bad. But will give it a try

Thanks João!

[setareh amd]

For the moment, this has to be done manually. That is, we need to save the estimates and standard errors for the different quantiles and then use them to construct the plot.

Best wishes,

Joao

hi,
is there any code to plot a graph for quantile panel regression due to compare with ols?

[Joao Santos Silva]

I believe FernandoRios created a command for that.

[FernandoRios]

Thanks for the tag Joao,
and yes, you could do it using qregplot command:
Here an example:

webuse nlswork , clear
xtqreg ln_wage age nev_mar union wks_ue ttl_exp, i(idcode)
qregplot, ols olsopt(abs(idcode) robust)

[setareh amd]

Thanks for the tag Joao,
and yes, you could do it using qregplot command:
Here an example:

webuse nlswork , clear
xtqreg ln_wage age nev_mar union wks_ue ttl_exp, i(idcode)
qregplot, ols olsopt(abs(idcode) robust)

hi,
i really appreciate you.
how can i define time in quantile panel and is there any code for 9 decile?

[FernandoRios]

Not really sure what you are asking. For the time component, you can add it as a dummy variable:

webuse nlswork , clear
xtqreg ln_wage age nev_mar union wks_ue ttl_exp i.time, i(idcode)
qregplot, ols olsopt(abs(idcode) robust)
** and if you want to plot specific quantiles , you can do:
qregplot, ols olsopt(abs(idcode) robust) q( 10 15 20 (10) 90)

[setareh amd]

Not really sure what you are asking. For the time component, you can add it as a dummy variable:

webuse nlswork , clear
xtqreg ln_wage age nev_mar union wks_ue ttl_exp i.time, i(idcode)
qregplot, ols olsopt(abs(idcode) robust)
** and if you want to plot specific quantiles , you can do:
qregplot, ols olsopt(abs(idcode) robust) q( 10 15 20 (10) 90)

thank you, how can i specify time here? for example time is year and id is code
and i have error that should use quantile between 0 and 1

[setareh amd]

FernandoRios

thank you, how can i specify time here? for example time is year and id is code
and i have error that should use quantile between 0 and 1

[setareh amd]

FernandoRios @Joao Santos Silva


Hello,

I want to regress a quantile panel data which section is code and time is year, with also 9 deciles from 10 to 90.

Would you help me with the syntax?

I also want to plot the panel data quantile and compare it with ols.

I really appreciate that.

[setareh amd]

For the moment, this has to be done manually. That is, we need to save the estimates and standard errors for the different quantiles and then use them to construct the plot.

Best wishes,

Joao

Hello,

I want to regress a quantile panel data which section is code and time is year, with also 9 deciles from 10 to 90.

Would you help me with the syntax?

I also want to plot the panel data quantile and compare it with ols.

I really appreciate that.

[River Huang]

Is this waht you wanted?

webuse nlswork , clear
xtqreg ln_wage age nev_mar union wks_ue ttl_exp i.year, i(idcode)
qregplot age nev_mar union wks_ue ttl_exp, ols olsopt(abs(idcode) robust) q(10(10)90) raopt(color(gs14))

[setareh amd]

Is this waht you wanted?

webuse nlswork , clear
xtqreg ln_wage age nev_mar union wks_ue ttl_exp i.year, i(idcode)
qregplot age nev_mar union wks_ue ttl_exp, ols olsopt(abs(idcode) robust) q(10(10)90) raopt(color(gs14))

[ATTACH=CONFIG]n1620434[/ATTACH]

hello,
thank you. Is my regression correct?
it has shown the years seperately. i want specify years from 1386 to 1396