help for apch

Generalized linear models for age-period-cohort effects with hysteresis

Syntax

apch depvar [indepvars]
[if exp] [in range] [weight]
, [
age(string)
period(string)
glm_options ]

apch allows all varlists & weights that glm considers.

Description

apch estimates age-period-cohort APC-D (detrended) models and provides
detrended (0 sum and 0 slope) parameters of age, period and cohort effects;
appropriate constraints offer a unique solution & solve the traditional APC
identification problem.
We focus on cohort parameters (DCE=detrended cohort effect) that should be tested
to be non-zeros across cohort span.
Their "hysteresis" (durability) over life course is assessed & tested by a coefficient
h (hysteresis) that is 0 in case of linear stability of cohort effect, -1 in case of vanishing
of the cohort effect over life span, equal to 1 in case of development from 0 of the cohort effect
over life course.
Since the cohort parameters and the hysteresis parameter can not be assessed simultaneously,
the package proposes an iterative strategy that converges to a single stable solution.
The apch provides Raftery's bics able to assess the interest of cohort effect
and then of hysteresis effect.

The user provides a dependant variable, age and period, and controls from a microdata
series of crossectional surveys.
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.

The procedure delivers :
(1) An APC-Detrended model with controls, including zero-sum/zero-slope parameters of
age, period & cohort effects.
(2) An APC-Hysteresis model with controls, delivering the h-hysteresis parameter of
linear stability of the DCE.
(3) Delta BICs are provided to measure
(a) dbic_cohort : the interest of including cohort effects after a AP model and
(b) dbic_hyster : the interest of including hysteresis effects to the APC model

Options

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

Any glm_options can be valid options for apch.

Many types of model can be handled by apch :

* the user must call "family(bin) link(logit)" for a logit regression

* the user must call "family(poisson) link(log) exposure(pop)",
where pop is the population at risk, for a poisson model

* the default "family(gauss) link(id)" will provide a linear regression.

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

example

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

apch mf2 , age(age) period(year)

References

see http://www.louischauvel.org/apchex.htm for working paper and examples on apch.

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

Author

Louis Chauvel
Sciences Po Paris
During the completion of the v1.0
Louis Chauvel was also invited Pr at Columbia U
Dpt of sociology, Knox Hall
chauvel@louischauvel.org

Also see

Online: help for glm.