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st: Regression based Shapley Value Decomposition rbdineq
From
Ruchika <[email protected]>
To
[email protected]
Subject
st: Regression based Shapley Value Decomposition rbdineq
Date
Mon, 26 Mar 2012 16:42:55 +0530
Dear Statalisters
I am running a regression based decomposition by using command
rbdineq. i have installed the DASP V2.1 in stata 10. when i use this
command with 3, 4 independent variables then i get the results as
given below but i actually need more independent variables then i
donot get the results even after 3-4 hours. it just get one line
repeatedly saying 6094missing values generated as i have mentioned
below the these results. Can anyone have any idea why i am not getting
results even after such a long time. how many maximum independent
variables this command can process? Is there any other way of doing
this regression based shapley value based decomposition?
rbdineq sector sex_head hh_size, dep(real_mpce_mrp) model(semilog)
hsize(per_wht) dregres(0)
Regression-based inequality decomposition by predicted income
components(using the Shapley value).
Execution time : 86.86 second(s)
Inequality index : Gini index
Estimated inequality : 0.350435
Household size : per_wht
+---------------------------------------------------------------------+
| Sources | Income Absolute Relative |
| | Share Contribution Contribution |
|--------------------+------------------------------------------------|
|1: _p_cons | . 0.000000 0.000000|
|2: _p_sector | . 0.064459 0.183941|
|3: _p_sex_head | . 0.000016 0.000046|
|4: _p_hh_size | . 0.041701 0.118997|
|5: _p_resi | . 0.244259 0.697016|
|--------------------+------------------------------------------------|
| Total | . 0.350435 1.000000|
+---------------------------------------------------------------------+
Marginal contributions:
---------------------------------------------------------------------------
Source | level_1 level_2 level_3 level_4 level_5
---------------+-----------------------------------------------------------
1: _p_cons | 0.000000 0.000000 0.000000 0.000000 0.000000
2: _p_sector | 0.020474 0.015706 0.011915 0.009101 0.007264
3: _p_sex_head | 0.000009 0.000004 0.000002 0.000001 0.000001
4: _p_hh_size | 0.014967 0.010676 0.007363 0.005027 0.003667
5: _p_resi | 0.059700 0.053299 0.047875 0.043428 0.039958
---------------------------------------------------------------------------
rbdineq social_group nic3grp_hh eduheadcate ageheadcate religioncode
state_club sector sex_head hh_size hhtype, dep(real_mpce_mrp)
model(semilog) hsize(per_wht) dregres(0)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
(6094 missing values generated)
and so on...............
Thanks & Regards
Ruchika
PhD Research Scholar
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