Ev Datasets

Description

This repository contains a fully reproducible analytical environment, raw datasets, processing scripts, empirical outputs, and manuscript-ready figures designed to model Electric Vehicle (EV) adoption, fleet transition dynamics, displacement estimates, and fiscal exposure risks across urban regions in South Asia (with specific modules focusing on Delhi, Pakistan, and Sri Lanka).

Steps to reproduce

To ensure complete transparency, auditability, and absolute reusability of the research findings, the empirical pipeline is structured as an end-to-end reproducible pipeline. All raw indicators, intermediate panel data structures, structural estimation scripts, and plotting assets are packaged within a unified modular framework (`final_pkg`). Executing the computational lifecycle requires a standard Python 3.10+ execution environment and requires following the specific step-by-step protocol

Institutions

• Quaid-i-Azam University

  Islamabad, Islamabad

Categories

Licence