Depreciation Method Based on Information Asymmetry and Adverse Selection

This dataset was developed to analyze the depreciation of electric vehicles (EVs) in the Colombian market, focusing specifically on how perceived information asymmetry affects resale values. Data collection was carried out using web scraping techniques on e-commerce platforms, primarily Mercado Libre and TuCarro, capturing EV sales information between 2019 and 2024.

Key Variables:

Brand: Brand of the electric vehicle (e.g., Audi, BMW, BYD).
Model: Year of the vehicle model.
Initial Price: Launch price of the vehicle at the time of release.
Current Price: Resale price of the vehicle on e-commerce platforms.
Accumulated Kilometers: Total mileage of the vehicle at the time of resale.
This dataset is part of a broader research project funded by Fundación Universitaria Los Libertadores, titled "Depreciation Model for Electric Vehicles in Colombia." This project aims to develop a more accurate depreciation model that considers market dynamics, consumer perceptions, and technological advancements.

本数据集旨在分析哥伦比亚市场上电动汽车（EV）的折旧情况，特别是探讨认知信息不对称如何影响二手车价值。数据收集通过电子商务平台（如Mercado Libre和TuCarro）的网页抓取技术完成，主要捕捉了2019年至2024年间的电动汽车销售信息。

关键变量包括：
品牌：电动汽车品牌（例如，奥迪、宝马、比亚迪）。
型号：车辆型号的年份。
初始价格：车辆发布时的首发价格。
当前价格：车辆在电子商务平台上的二手车价格。
累计里程：车辆在二手车销售时的总行驶里程。
此数据集属于由Fundación Universitaria Los Libertadores资助的更广泛研究项目的一部分，项目名称为“哥伦比亚电动汽车折旧模型”。该项目旨在开发一个更精确的折旧模型，该模型考虑了市场动态、消费者认知和技术进步。” }