Bayesian spatial PSM
Version 1.1 (91.8 KB) by
Rolando Gonzales Martinez
Bayesian spatial propensity score matching. This is an update of the original code I made in 2014, now updated to run in MatLab 2020a
Bayesian Spatial Propensity Score Matching (BS-PSM)
Rolando Gonzales Martinez
Updated and tested to run on MatLab 2020a (January 2022)
In order to run the BS-PSM algorithm you will need:
(1) A n x n spatial contiguity matrix (W)
(2) A n x 1 binary treatment vector(y)
(3) A n x p matrix of potential explanatory variables (X)
(4) A n x 1 variable that measures the impact (I) of the treatment
There is a need also to define the parameters of the MCMC simulation:
- ndraws: number of draws (simulations) of the MCMC
- nomit: burn-in
By default, the prior of rho is elicitated in the positive range (0,1]
BS-PSM uses some functions of James LeSage Spatial Econometrics Toolbox
To run an example file check BSPSM_poverty_example.m
Cite As
Rolando Gonzales Martinez (2024). Bayesian spatial PSM (https://github.com/rogon666/Bayesian-spatial-PSM/releases/tag/v1.1), GitHub. Retrieved .
MATLAB Release Compatibility
Created with
R2020a
Compatible with any release
Platform Compatibility
Windows macOS LinuxTags
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Version | Published | Release Notes | |
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1.1 |
To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.