By Rodrigo Chang (rrcp@banguat.gob.gt) at Banco de Guatemala @r2cp
Check out the introductory presentation
This is a toy example of a prototype model that combines a Multilayer Perceptron to estimate the time-varying coefficients of a SVAR.
This is work-in-progress. Inspiration for this work comes from Prof. Phillippe Coulombe's idea of a Macro Neural Network.
flowchart LR
A[Time variaton sources S] --> |Neural network G| B(VAR parameters β)
B --> C(Macro variables y)
D[Lagged values X] --> C
I will upload here the following work:
scripts/nn-svar.jl
: The toy example network estimated with simulated data.scripts/poly-example.jl
: This is an example I worked for understanding how to estimate a neural network with theLux.jl
package in Julia.notebooks\intro.qmd
: This is a Quarto notebook with my elevator-pitch presentation given on Sept. 2.notebooks\final.qmd
: This is the Quarto presentation with my progress at the end of the course.
For this project, I used Julia. Feel free to try out the project by instantiating it:
julia> ]
(DTVP-VAR) pkg>