st: Error component models

[Dimitris Pavlopoulos <Dimitris.Pavlopoulos@soc.kuleuven.be>]

Dear statalisters,

I want to run an error component model for earnings in the framework  
of Ramos (2003), Cappellari (2004), Dickens (2000). These models  
extend the typical random effects model

y_it = m_i + e_it

by applying several specifications to the individual effects m_i  
(random walk, random growth) and to the error term e_it (AR(1) or ARMA  
models). An example is the following model of Ramos (2003):

y_icat = g_c * a_t [m_i + h_i * a_it + u_iat] + z_c * v_it

where
u_iat = u_i(a-1)(t-1) + p_iat
v_it = r * v_it + l_t * e_it

and i stands for the individual, c for cohort, a for age, t for time.  
g_c and a_t are shifters for cohort and time respectively.

These models are estimated with the use of minimum distance  
estimation. Estimation of some these models is possible in SAS. Does  
anyone know how to estimate them in STATA? Is there any module for  
them? I have found references to an old module from L. Cappellari  
(mindist) that was presented in one Stata meeting but it does not  
appear anywhere. Moreover, from what I understand it does not cover  
all the usual specifications that are used in the literature.

I would very much appreciate your help.

Best regards,
Dimitris


References:

Cappellari, L. (2004). The dynamics and inequality of Italian men?s  
earnings. long-term changes or transitory fluctuations. Journal of  
Human Resources, 39 (2), 475-499.

Dickens, R. (2000b). The evolution of individual male earnings in  
Great Britain: 1975-95. Economic Journal, 110, 27-49.

Ramos, X. (2003). The covariance structure of earnings in Great  
Britain, 1991-1999. Economica, 70, 353-374.


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