{smcl} {cmd:help cquadpseudo}{right:also see: {help clogit}, {help cquadbasic}, {help cquadext}} {hline} {title:Title} {p2colset 5 17 21 2}{...} {p2col :{hi:cquadpseudo} {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:cquadpseudo} {depvar} id [{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}Fit (simplified) quadratic exponential model{p_end} {phang}{cmd:. cquadpseudo union idcode age grade}{p_end} {title:Saved results} {pstd} {cmd:cquadpseudo} saves the following in {cmd:e()}: {synoptset 20 tabbed}{...} {p2col 5 20 24 2: Scalars}{p_end} {synopt:{cmd:e(lk)}}final conditional log-likelihood{p_end} {synoptset 20 tabbed}{...} {p2col 5 20 24 2: Macros}{p_end} {synopt:{cmd:e(cmd)}}{cmd:cquadpseudo}{p_end} {synoptset 20 tabbed}{...} {p2col 5 20 24 2: Matrices}{p_end} {synopt:{cmd:e(be)}}coefficient vector{p_end} {synopt:{cmd:e(se)}}standard errors{p_end} {synopt:{cmd:e(ser)}}robust standard errors{p_end} {synopt:{cmd:e(tstat)}}t-statistics based on robust standard errors{p_end} {synopt:{cmd:e(pv)}}p-values{p_end} {title:Author} {pstd}Francesco Bartolucci{p_end} {pstd}Department of Economics, University of Perugia {p_end} {pstd}Perugia, Italy{p_end} {pstd}bart@stat.unipg.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.