Nothing
spldv: Spatial Models for Limited Dependent Variables
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>.
Getting started
Browse package contents
Package details |
|
|---|---|
| Author | Mauricio Sarrias [aut, cre] (<https://orcid.org/0000-0001-5932-4817>), Gianfranco Piras [aut] (<https://orcid.org/0000-0003-0225-6061>), Daniel McMillen [ctb] |
| Maintainer | Mauricio Sarrias <msarrias86@gmail.com> |
| License | GPL (>= 2) |
| Version | 0.1.3 |
| URL | https://github.com/gpiras/spldv |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
|
Try the spldv package in your browser
Any scripts or data that you put into this service are public.
