cquad_equ {cquad}

Conditional maximum likelihood estimation for the modified version of the quadratic exponential model (to test for state dependence)

Description

Fit by conditional maximum likelihood a modified version of the model for binary longitudinal 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. (2018).

Usage

cquad_equ(id, yv, X = NULL, be = NULL, w = rep(1, n), Ttol=10)

Arguments

id

list of the reference unit of each observation

yv

corresponding vector of response variables

X

corresponding matrix of covariates (optional)

be

initial vector of parameters (optional)

w

vector of weights (optional)

Ttol

Threshold individual observations that activates the recursive algorithm (default=10)

Value

formula

formula defining the model

lk

conditional log-likelihood value

coefficients

estimate of the regression parameters (including for the lag-response)

vcov

asymptotic variance-covariance matrix for the parameter estimates

scv

matrix of individual scores

J

Hessian of the log-likelihood function

se

standard errors

ser

robust standard errors

Tv

number of time occasions for each unit

Author(s)

Francesco Bartolucci (University of Perugia), Claudia Pigini (University of Perugia), Francesco Valentini (University of Ancona "Politecnica delle Marche")

References

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

Bartolucci, F., Nigro, V., & Pigini, C. (2018). Testing for state dependence in binary panel data with individual covariates by a modified quadratic exponential model. Econometric Reviews, 37(1), 61-88.

Examples

# example based on simulated data
data(data_sim)
data_sim = data_sim[1:500,]   # to speed up the example, remove otherwise
id = data_sim$id; yv = data_sim$y; X = cbind(X1=data_sim$X1,X2=data_sim$X2)

out = cquad_equ(id,yv,X,Ttol=10)