[R] equivalent of stata command in R

From: mike mick <saint-filth_at_hotmail.com>
Date: Wed, 09 Jun 2010 09:28:20 +0000

Dear all,

I need to use R for one estimation, and i have readily available stata command, but i need also the R version of the same command. the estimation in stata is as following:

  1. Compute mean values of relevant variables

. sum inno lnE lnM

    Variable | Obs Mean Std. Dev. Min Max

-------------+--------------------------------------------------------

        inno |    146574    .0880374    .2833503          0          1

         lnE |    146353    .9256239    1.732912  -4.473922   10.51298

         lnM |    146209    4.281903    1.862192  -4.847253   13.71969



        2. Estimate model



. xi: xtreg lnLP lnC lnL lnE lnM eco inno eco_inno eco_lnE eco_lnM i.year, fe i(stno)

i.year _Iyear_1997-1999 (naturally coded; _Iyear_1997 omitted)

Fixed-effects (within) regression Number of obs = 146167

Group variable (i): stno                        Number of groups   =     48855



R-sq:  within  = 0.9908                         Obs per group: min =         1

       between = 0.9122                                        avg =       3.0

       overall = 0.9635                                        max =         3



                                                F(11,97301)        = 949024.29

corr(u_i, Xb)  = 0.2166                         Prob > F           =    0.0000




------------------------------------------------------------------------------
lnLP | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- lnC | .0304896 .0009509 32.06 0.000 .0286258 .0323533 lnL | -.9835998 .0006899 -1425.74 0.000 -.984952 -.9822476 lnE | .0652658 .0009439 69.14 0.000 .0634158 .0671159 lnM | .6729931 .0012158 553.53 0.000 .67061 .6753761 eco | .0610348 .0177048 3.45 0.001 .0263336 .095736 inno | .0173824 .0058224 2.99 0.003 .0059706 .0287943 eco_inno | .0080325 .0110815 0.72 0.469 -.0136872 .0297522 eco_lnE | .0276226 .004059 6.81 0.000 .019667 .0355781 eco_lnM | -.0214237 .0039927 -5.37 0.000 -.0292494 -.0135981 _Iyear_1998 | -.0317684 .0013978 -22.73 0.000 -.034508 -.0290287

 _Iyear_1999 | -.0647261 .0027674 -23.39 0.000 -.0701501 -.0593021

       _cons | 1.802112 .009304 193.69 0.000 1.783876 1.820348

-------------+----------------------------------------------------------------

     sigma_u |  .38142386

     sigma_e |   .2173114

         rho |  .75494455   (fraction of variance due to u_i)


------------------------------------------------------------------------------
F test that all u_i=0: F(48854, 97301) = 3.30 Prob > F = 0.0000 3. Compute marginal effect of eco at sample mean

. nlcom (_b[eco]+_b[inno]*.0880374+_b[eco_lnE]*.9256239+_b[eco_lnM]*4.281903)

       _nl_1: _b[eco]+_b[inno]*.0880374+_b[eco_lnE]*.9256239+_b[eco_lnM]*4.281903


        lnLP | Coef. Std. Err. t P>|t| [95% Conf. Interval]

-------------+----------------------------------------------------------------

       _nl_1 |  -.0036011    .008167    -0.44   0.659    -.0196084    .0124061


------------------------------------------------------------------------------

in fact i can find the mean of the variables ( step 1) and extimate the model (step 2) but i couldnt find the equivalent of step 3 (compute marginal effect of eco at sample mean). Can someone help me for this issue?

Cheers!                                                


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