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
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Updated 6 Jan 2022
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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

View Bayesian spatial PSM on File Exchange

Cite As

Rolando Gonzales Martinez (2026). 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 Linux
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Version Published Release Notes
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.