Example: wage inequality
------------------------

ge_entr.ado


- German Socio-Economic Panel (GSOEP)
- wave 1996
- strictly positive wages

- STATA-Output:


. ge_entr  weight96 wage95

----------------------------------------------------------------
Generalized entropy measures with bootstrap confidence intervals
----------------------------------------------------------------
Confidence level = 0.95,              100 bootstrap replications
----------------------------------------------------------------
GE^-1 = 0.334055,      confidence interval [0.304113 ; 0.368023]
MLD   = 0.200512,      confidence interval [0.183040 ; 0.217421]
THEIL = 0.170764,      confidence interval [0.147927 ; 0.189413]
GE^2  = 0.206883,      confidence interval [0.099874 ; 0.256426]
----------------------------------------------------------------




Example: wage inequality difference
-----------------------------------

diff_ge.ado


- German Socio-Economic Panel (GSOEP)
- waves 1996 and 1986
- only strictly positive wages count

- STATA-Output:


. diff_ge  weight86  wage85  c86 weight96 wage95 c96

------------------------------------------------------------------
Generalized entropy differences and bootstrap confidence intervals
------------------------------------------------------------------
Confidence level = 0.95,                100 bootstrap replications
------------------------------------------------------------------
GE^-1 = -0.023410,     confidence interval [-0.062718 ; 0.022843]
MLD   = -0.013676,     confidence interval [-0.031238 ; 0.012549]
THEIL = -0.013886,     confidence interval [-0.048052 ; 0.031287]
GE^2  = -0.024116,     confidence interval [-0.151645 ; 0.121033]
------------------------------------------------------------------




Example: subgroup decomposition of wage inequality
--------------------------------------------------

sub_dec.ado


- German Socio-Economic Panel (GSOEP)
- wave 1996
- subgroup 1 = natives, subgroup 2 = foreigners
- strictly positive wages

- STATA-Output:


. sub_dec  weight96 wage95 df96


Subgroup decomposition with bootstrap confidence intervals
----------------------------------------------------------
Confidence level = 0.95,        100 bootstrap replications
----------------------------------------------------------


Contributions to overall inequality measured by MLD
---------------------------------------------------


Total
-----
MLD          = 0.200512, confidence interval [0.180616 ; 0.217859]


Within-group: absolute contributions
------------------------------------
subgroup 1   = 0.186745, confidence interval [0.167548 ; 0.203651]
subgroup 2   = 0.012550, confidence interval [0.009742 ; 0.015203]


Within-group: relative contributions
------------------------------------
subgroup 1   = 0.931337, confidence interval [0.917095 ; 0.950596]
subgroup 2   = 0.062589, confidence interval [0.047448 ; 0.076688]


Between-group: absolute contribution
------------------------------------
MLDB         = 0.001218, confidence interval [0.000130 ; 0.001893]


Between-group: relative contribution
------------------------------------
MLDB         = 0.006074, confidence interval [0.001082 ; 0.009352]


Within-group MLD
-----------------------
subgroup 1   = 0.201577, confidence interval [0.179612 ; 0.220917]
subgroup 2   = 0.170554, confidence interval [0.142482 ; 0.201566]


Population shares
-----------------
subgroup 1   = 0.926417, confidence interval [0.918377 ; 0.935736]
subgroup 2   = 0.073583, confidence interval [0.065322 ; 0.081696]




Contributions to overall inequality measured by THEIL
-----------------------------------------------------


Total
-----
THEIL        = 0.170764, confidence interval [0.146156 ; 0.189939]


Within-group: absolute contributions
------------------------------------
subgroup 1   = 0.161042, confidence interval [0.137997 ; 0.181576]
subgroup 2   = 0.008571, confidence interval [0.006556 ; 0.010893]


Within-group: relative contributions
------------------------------------
subgroup 1   = 0.943065, confidence interval [0.932124 ; 0.959447]
subgroup 2   = 0.050192, confidence interval [0.034516 ; 0.063181]


Between-group: absolute contribution
------------------------------------
THEILB       = 0.001152, confidence interval [0.000176 ; 0.001781]


Between-group: relative contribution
------------------------------------
THEILB       = 0.006743, confidence interval [0.001261 ; 0.010470]


Within-group THEIL
-----------------------
subgroup 1   = 0.171574, confidence interval [0.146337 ; 0.192979]
subgroup 2   = 0.139622, confidence interval [0.120459 ; 0.166902]


Income shares
-------------
subgroup 1   = 0.938613, confidence interval [0.931090 ; 0.949598]
subgroup 2   = 0.061387, confidence interval [0.051975 ; 0.070205]





Example: interquartile transitions of equivalent income
-------------------------------------------------------

mob.ado


- German Socio-Economic Panel (GSOEP)
- waves 1996 and 1997
- state 1 = 1. quartile, state 2 = 2. quartile etc.
- no weights (i.e. all weights = 1)

- STATA-Output:


. gen w=1

. mob w  d961 d962 d963 d964 d971 d972 d973 d974

------------------------------------------------------------------
Prais mobility index,   estimate and bootstrap confidence interval
------------------------------------------------------------------
Confidence level = 0.95,                100 bootstrap replications
------------------------------------------------------------------
Prais index = 0.451590, confidence interval [0.432648 ; 0.484881]
------------------------------------------------------------------



Example: mobility index difference
----------------------------------

diff_m.ado


- two states
- artificial data:

w   d11 d12 d21 d22 d31 d32 d41 d42
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   1   0   0   1   0   1   1   0
1   0   1   1   0   1   0   1   0
1   0   1   1   0   1   0   0   1
1   0   1   1   0   1   0   0   1
1   0   1   1   0   1   0   0   1
1   0   1   1   0   1   0   0   1
1   0   1   1   0   1   0   0   1
1   0   1   1   0   1   0   0   1
1   0   1   1   0   1   0   0   1
1   0   1   1   0   1   0   0   1
1   0   1   1   0   1   0   0   1



- STATA-Output:


. diff_m  w d11 d12 d21 d22 d31 d32 d41 d42

------------------------------------------------------------------------
Prais mobility difference,    estimate and bootstrap confidence interval
------------------------------------------------------------------------
Confidence level = 0.95,                      100 bootstrap replications
------------------------------------------------------------------------
Prais difference = -0.100000, confidence interval [-0.200000 ; 0.175000]
------------------------------------------------------------------------

.
