https://github.com/tpapp/nonhomotheticces.jl

Julia package for calculations with non-homothetic preferences.
https://github.com/tpapp/nonhomotheticces.jl

Last synced: over 1 year ago
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Julia package for calculations with non-homothetic preferences.

• Host: GitHub
• URL: https://github.com/tpapp/nonhomotheticces.jl
• Owner: tpapp
• License: other
• Created: 2021-06-03T15:21:04.000Z (about 5 years ago)
• Default Branch: master
• Last Pushed: 2025-02-26T10:17:37.000Z (over 1 year ago)
• Last Synced: 2025-02-26T10:38:49.023Z (over 1 year ago)
• Language: Julia
• Size: 138 KB
• Stars: 3
• Watchers: 3
• Forks: 0
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE.md

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README

          
# NonhomotheticCES.jl

![lifecycle](https://img.shields.io/badge/lifecycle-experimental-orange.svg)

[![build](https://github.com/tpapp/NonhomotheticCES.jl/workflows/CI/badge.svg)](https://github.com/tpapp/NonhomotheticCES.jl/actions?query=workflow%3ACI)

[![codecov.io](http://codecov.io/github/tpapp/NonhomotheticCES.jl/coverage.svg?branch=master)](http://codecov.io/github/tpapp/NonhomotheticCES.jl?branch=master)

A small package to solve for the consumption aggregator for non-homothetic CES preferences as described in

*Comin, D., Lashkari, D., & Mestieri, Martí (2021). Structural change with long-run income and price effects. Econometrica, 89(1), 311–374.*

## API

```julia

using NonhomotheticCES, StaticArrays

U = NonhomotheticCESUtility(σ,  # σ

                            Ω̂s, # LOG sectoral Ωs

                            ϵs) # sectoral ϵs

Ĉ = log_consumption_aggregator(U,

                               Ê,  # LOG expenditure

                               p̂s) # LOG prices

ĉs = log_sectoral_consumptions(U, Ê, p̂s, Ĉ)

```

## Integrations

Partial derivatives are implemented for AD frameworks:

1. [X] [ForwardDiff.jl](https://github.com/JuliaDiff/ForwardDiff.jl)

2. [ ] [ChainRulesCore.jl](https://github.com/JuliaDiff/ChainRulesCore.jl) **WIP**

## Example

σ = 0.5, Ω̂₁ = 0.0, Ω̂₂ = 0.0, ϵ₁ = 1.0, ϵ₂ = 2.0, p̂₁ = 0.1, p̂₂ = 0.0 (see [script/plot.jl](./script/plot.jl)).