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wbEAWPV/AFW-Micro_Fiscal_Sim

Domaine:

socioeconomic

Type de record:

software
Créateur:
wbE
Hôte:
This repository hosts the AFW Fiscal Simulation Tool, developed under a regional project led by Moritz Meyer, Daniel Valderrama, Andrés Gallegos, Gabriel Lombo, and Madi Magan. # 📘 AFW Fiscal Simulation Tool ## 🧩 Overview The **AFW Fiscal Simulation Tool** is a regional microsimulation platform designed to analyze the distributional and fiscal impacts of tax and transfer policies across the Africa Western and Central region. It provides a harmonized framework for country teams to simulate reform scenarios and assess their effects on poverty, inequality, and fiscal balances. --- ## 🧠 Key Features - Harmonized household surveys to produce a **standardized input** for the simulation exercise. - Developed modules include **direct taxes** (PIT, property taxes, and firm-level taxes), **indirect taxes** (customs, excises, VAT), **cash transfers**, **in-kind transfers**, and **energy subsidies**. - **Pre-simulation** processes are not standardized, but the simulation can be easily translated into **R** and **Python** environments. - Country-specific parameters are saved in the folder named **parameters**, which contains over **440 parameters**, including **product-specific VAT rates**. - The microsimulation model computes the **impact of granular policies** along the welfare distribution, disaggregated by **gender** and **subnational regions** *(ongoing)*. - Produces **standardized outputs** compatible with **CEQ** and **AFWSim** frameworks. --- This work is part of the **AFW Fiscal Simulation Project**, implemented by the World Bank’s Poverty and Equity Global Practice in collaboration with national statistical offices and ministries of finance across the Africa Western and Central region. The tool and its underlying framework were developed by **Moritz Meyer**, **Daniel Valderrama**, **Andrés Gallegos**, **Gabriel Lombo**, and **Madi Magan**, under the leadership of Gabriela Inchauste and Johan Mistien with contributions from multiple country teams and technical experts. We acknowledge the valuable support from country counterparts, data producers, and the broader World Bank team for their guidance and collaboration throughout the project’ …

Visit

github.com

Languages

BariLomboMaMa’di

Licenses

MIT

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