Re: Re: st: Time demean panel variables using -center command

[Vaidyanathan Ganapathy <vaidyang@usc.edu>]

Hi Nick,

Sorry if my question was not clear. To clarify -

My goal is to use -Oaxaca to decompose differences in ln(healthcare
costs) between two groups - term born infants and pre-term infants. I
want to specify fixed effect models for the healthcare costs,
separately for the term and preterm cohorts. Dependent variable is
ln(healthcare costs) and independent variables that change over time
are - income eligibility category, number of chronic conditions and
each chronic diagnosis (Yes/No).

The issue is, Oaxaca doesn't support xtreg, fe. If I try using xtreg,
fe with Oaxaca I get an error message "suest doesn't support xtreg
fe". So I decided to demean the variables in my specification and just
use -regress, which, I believe, is equivalent to running a fixed
effects specification. I am able to use Oaxaca with the time demeaned
variables but the outputs, including the predicted values and the
explained and unexplained differences are not making sense.
Specifically, as you can see from the output, the predicted values are
too small and hence the explained difference is not perceptible at
all. Is this expected if you use demean natural log of a continuous
variable such as costs or wages? I wanted to know if it is meaningful
at all to demean ln(healthcare costs)? I tried, demeaning the
healthcare costs (in raw scale) first, and then take natural log and
it seems to work somehow. But I am not sure if this is a right
approach.

Please let me know if you need further clarification/outputs etc.

Thanks,

Vicky

//De-mean the ln(dependent) and the indendent variables -

by pcn: center lnallhccx2 tpcat2-tpcat6 bpdx2 chdx2 asthbrdx2 cnsdx2
motordx2 physdevdx2 nddx2 chrnic1, casewise

//Run OLS regression with cluster robust errors of the dependent
variable on set of predictors for two groups (premie_cat=0 and
premie_cat==2)

oaxaca c_lnallhccx2  c_tpcat2- c_tpcat6 c_bpdx2 c_chdx2 c_asthbrdx2
c_cnsdx2 c_motordx2 c_physdevdx2 c_nddx2 c_chrnic1 c_period if
premie_cat==0|premie_cat==2, by(premie_cat) weight(0 1) cluster(pcn)


Blinder-Oaxaca decomposition                      Number of obs   =     137972

          1: premie_cat = 0
          2: premie_cat = 2

                                (Std. Err. adjusted for 68994 clusters in pcn)
-------------------------------------------------------------------------------
             |               Robust
c_lnallhccx2 |      Coef.   Std. Err.      z    P>|z|     [95% Conf. Interval]
--------------+----------------------------------------------------------------
Differential  |
Prediction_1 |   4.73e-10   6.22e-10     0.76   0.447    -7.46e-10    1.69e-09
Prediction_2 |   1.19e-08   9.81e-09     1.21   0.227    -7.36e-09    3.11e-08
  Difference |  -1.14e-08   9.83e-09    -1.16   0.247    -3.07e-08    7.88e-09
--------------+----------------------------------------------------------------
Decomposition |
   Explained |          0  (omitted)
 Unexplained |  -1.14e-08   9.83e-09    -1.16   0.247    -3.07e-08    7.88e-09
-------------------------------------------------------------------------------


Thanks !
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