help cquadequralso see: clogit, cquadbasicr, cquadextr

Title

cquadequr -- Conditional maximum likelihood estimation for the modified
version of the quadratic exponential model proposed by Bartolucci, Nigro & Pigini (2013)

Syntax

cquadequr id depvar [indepvars]

Description

Fit by conditional maximum likelihood a modified version of the model for binary logitudinal
data proposed by Bartolucci & Nigro (2010), in which the interaction terms have an extended
form. This modified version is used to test for state dependence as described in Bartolucci
et al. (2013).

For a vector y_i of T observations (y_,...,y_) for unit i, the model is based on the assumption:

p(y_i) exp[(y_x_ + ... + y_x_)'beta + (1 + ... + 1)gamma]

where x_ is a column vector of covariates and the first observation is taken as initial condition
and 1{.} is the indicator function. The function can be also used with unbalanced panel data.

id (compulsory) is the list of the reference unit of each observation

Examples

Setup

. webuse union

Fit (modified) quadratic exponential model

. cquadequr idcode union age grade

Saved results

cquadequr saves the following in matrix list return matrix list:

Matrices

matrix list r(coefficients) coefficient vector

matrix list r(ser) standard errors

matrix list r(serr) robust standard errors

matrix list r(He) Hessian matrix of the conditional likelihood function

matrix list r(vcov) coefficients covariance matrix

Authors

Francesco Bartolucci

Department of Economics, University of Perugia

Perugia, Italy

francesco.bartolucci@unipg.it

Claudia Pigini

Department of Economics and Social Science, Marche Polytechnic University

Ancona, Italy

c.pigini@univpm.it

Francesco Valentini

Department of Economics and Social Science, Marche Polytechnic University

Ancona, Italy

f.valentini@pm.univpm.it

References

Bartolucci, F. & Nigro, V. (2010). A dynamic model for binary panel data with unobserved heterogeneity admitting a root-n consistent conditional estimator. Econometrica, 78, pp. 719-733.

Bartolucci, F., Nigro, V. & Pigini, C. (2013). Testing for state dependence in binary panel data with individual covariates, MPRA Paper 48233, University Library of Munich, Germany.

cquadr User guide. https://github.com/fravale/cquadr/blob/master/cquadr-guide.pdf