{smcl} {cmd:help cquadpseudor}{right:also see: {help clogit}, {help cquadbasicr}, {help cquadextr}} {hline} {title:Title} {p2colset 5 17 21 2}{...} {p2col :{hi:cquadpseudor} {hline 2}}Pseudo conditional maximum likelihood estimation of the dynamic logit model (Bartolucci and Nigro, 2012){p_end} {p2colreset}{...} {title:Syntax} {p 8 16 2}{cmd:cquadpseudor} id {depvar} [{indepvars}] {title:Description} {pstd} Estimate the dynamic logit model for binary logitudinal data by the pseudo conditional maximum likelihood method proposed by Bartolucci & Nigro (2012). {pstd} For a vector y_i of T observations (y_{i,1},...,y_{i,T}) for unit i, the model is based on the assumption: {pstd} p(y_{i,t}) {proportional to} exp(y_{i,t}x_{i,t}'beta + y_{i,t-1}y_{i,t}gamma) {pstd} where x_{i,t} is a column vector of covariates and the first observation is taken as initial condition. The function can be also used with unbalanced panel data. {pstd} id (compulsory) is the list of the reference unit of each observation{p_end} {title:Examples} {pstd}Setup{p_end} {phang}{cmd:. webuse union}{p_end} {pstd}PCML estimator for dynamic logit model{p_end} {phang}{cmd:. cquadpseudor idcode union age grade}{p_end} {title:Saved results} {pstd} {cmd:cquadpseudor} saves the following in matrix list {cmd:return matrix list}: {synoptset 20 tabbed}{...} {p2col 5 20 24 2: Matrices}{p_end} {synopt:{cmd:matrix list r(coefficients)}}coefficient vector{p_end} {synopt:{cmd:matrix list r(ser_ps)}}standard errors{p_end} {synopt:{cmd:matrix list r(serr_ps)}}first-step robust standard errors{p_end} {synopt:{cmd:matrix list r(He_ps)}}Hessian matrix of the conditional likelihood function{p_end} {synopt:{cmd:matrix list r(vcov_ps)}}coefficients covariance matrix{p_end} {title:Authors} {pstd}Francesco Bartolucci{p_end} {pstd}Department of Economics, University of Perugia {p_end} {pstd}Perugia, Italy{p_end} {pstd}francesco.bartolucci@unipg.it{p_end} {pstd}Claudia Pigini{p_end} {pstd}Department of Economics and Social Science, Marche Polytechnic University{p_end} {pstd}Ancona, Italy{p_end} {pstd}c.pigini@univpm.it{p_end} {pstd}Francesco Valentini{p_end} {pstd}Department of Economics and Social Science, Marche Polytechnic University{p_end} {pstd}Ancona, Italy{p_end} {pstd}f.valentini@pm.univpm.it{p_end} {title:References} {pstd} 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. {pstd} Bartolucci, F. & Nigro, V. (2012). Pseudo conditional maximum likelihood estimation of the dynamic logit model for binary panel data. Journal of Econometrics, 170, pp. 102-116. {pstd} cquadr User guide. https://github.com/fravale/cquadr/blob/master/cquadr-guide.pdf{p_end}