help for apcgo

Calculates age-period-cohort effects for the gap between two groups (based on a Blinder-Oaxaca decomposition), including trends for each parameter

Syntax

apcgo depvar [indepvars]
[if exp] [in range] [weight]
,
age(varname)
period(varname) gap(varname) [rep(real)]

apcgo allows all varlists & weights that oaxaca accepts, and some options (see below).

Description

apcgo The procedure calculates the blinder-oaxaca decomposition for each periodXage group context and
estimates age-period-cohort APC-T (trended) models for the explained and unexplained gap. It provides trended
parameters of age, period and cohort effects (The trend in age is set to be the average effect of ageing
of cohorts observed in the window of observation); appropriate constraints offer a unique solution & solve the traditional
APC identification problem. The user provides a dependent variable, a binary gruop varaible (gap), age and period, and controls from
a microdata series of crossectional surveys. It is possible to obtain confidence intervals using bootstrap,
by providing the number of repetitions (the rep argument). The data must be a complete rectangle (age x period)
and the pace between periods must be fix and equal to the distance between age groups. If not, the procedure
will fail.

This ado file quotes fractions of the Yang & colleagues (2006)
apc_ie.ado file (ssc install apc) and chauvel (2012) apcd.ado

Options

age(string) and period(string)
specify the names of age and period variables. They must be given by the user.

gap(string)
The independent dichotomous variable. Must be provided by the user.

rep(real)
Number of repetitions for bootstrap. When set to zero (default), no confidence interval will be provided.

logit
logit decomposition

probit
probit decomposition

Since apcgo makes use of constraints, this package should be
processed on STATA 11.0 or higher.

example

use "http://www.louischauvel.org/apcgoex.dta", clear

* race / 1=caucasian AA=2

* a5 / age

* y5 / year

* labincome / medianized labor personal income

* pweight / sampling weight

* vet / 1=veteran 0=no veteran satus

* ED / level of education 6=drop out 7=ged 8=comunity coll ... 11=Ba 12=Ma+

* female / male=0 female = 1

* lnlab / ln of labincome

keep if female==0 & a5<65

* how the veteran premium changed?

apcgo lnlab [w=pweight], gap(vet) age(a5) period(y5)

* what is the role of education in the veteran premium change?

xi: apcgo lnlab i.ED if fem==0 [w=pwei], gap(vet) age(a5) period(y5) rep(1)

References

Chauvel, L., Hartung, A., & Bar-Haim, E. 2016. Closing or Persisting Gender Gap? A Cohort Analysis of Education and Wages in the US and Europe.

see Yang, Y., Fu, W., and Land, K. 2006. apc_ie and apc_cglm
STATA packages.

Author

Louis Chauvel,
louis.chauvel@uni.lu
Anne Hartung
anne.hartung@uni.lu
Eyal Bar-Haim
eyal.bar-haim@uni.lu
PEARL Institute for Research on Socio-Economic Inequality (IRSEI), University of Luxembourg

Also see

Online: help for glm.

Online: help for oaxaca.

Online: help for apctlag.

Online: help for apcd.