Spatial Models for Limited Dependent Variables R package spldv version 0.1.3 The current version of this package estimates spatial autoregressive models for binary dependent variables using GMM estimators <doi:10.18637/jss.v107.i08>. It supports one-step (Pinkse and Slade, 1998) <doi:10.1016/S0304-4076(97)00097-3> and two-step GMM estimator along with the linearized GMM estimator proposed by Klier and McMillen (2008) <doi:10.1198/073500107000000188>. It also allows for either Probit or Logit model and compute the average marginal effects. All these models are presented in Sarrias and Piras (2023) <doi:10.1016/j.jocm.2023.100432>. Software Depends: R (>= 4.0) Imports: Formula, Matrix, maxLik, stats, sphet, memisc, car, methods, numDeriv, MASS, spatialreg Suggests: spdep Mauricio Sarrias <msarrias86@gmail.com> Comprehensive R Archive Network (CRAN) Mauricio Sarrias [aut, cre] (ORCID: <https://orcid.org/0000-0001-5932-4817>), Gianfranco Piras [aut] (ORCID: <https://orcid.org/0000-0003-0225-6061>), Daniel McMillen [ctb] GPL (>= 2) 2023-10-11 application/tgz https://CRAN.R-project.org/package=spldv doi:10.32614/CRAN.package.spldv