Replication Data for: Deputies' assets and their legislative activity (2023-2025)

This dataset provides empirical support for the research paper \"Deputies' assets and their legislative activity (2023-2025)\". The study investigates the relationship between wealth concentration among political elites and their performance in the Brazilian National Congress. All files are written in Brazilian Portuguese, except for the ReadMe. Dataset Content: The repository is organized into subfolders and includes: Raw Data: Original files collected from public sources, such as asset declarations from the Superior Electoral Court (TSE) for federal deputy candidates from 2022, legislative proposal data from the Chamber of Deputies, and other government sources. Processed Data: Consolidated and clean datasets in .csv, .r, .xlsx formats, ready for analysis. They include variables on the legislators' wealth, sociodemographic profile, party affiliation, and legislative activity. Analysis Scripts: R codes used for data processing. Codebook: A document in .pdf format that provides a detailed description of each variable in the processed datasets. ReadMe: A document in .pdf format that provides general information about the dataset. Methodology: Data collection and organization followed a mixed-methods approach, combining the compilation of large-scale electoral data with computational social science techniques for processing and analyzing large volumes of information. The full methodology is described in the paper associated with this dataset.

本数据集为研究论文《议员资产与立法活动（2023-2025）》提供实证支撑。本研究探讨巴西国民议会中政治精英的财富集中度与其履职表现之间的关联。除自述文件（ReadMe）外，所有文件均采用巴西葡萄牙语撰写。

数据集内容：本仓库按子文件夹组织，包含以下部分：
1. 原始数据（Raw Data）：从公开渠道采集的原始文件，包括2022年联邦众议员候选人的巴西高等选举法院（Superior Electoral Court，TSE）资产申报材料、众议院（Chamber of Deputies）立法提案数据及其他政府公开来源信息。
2. 处理后数据（Processed Data）：已完成整合与清洗的数据集，格式涵盖.csv、.r、.xlsx，可直接用于分析，包含议员财富、社会人口学特征、党派归属及立法活动相关变量。
3. 分析脚本（Analysis Scripts）：用于数据处理的R语言代码。
4. 代码手册（Codebook）：.pdf格式文档，详细说明处理后数据集内各变量的具体信息。
5. 自述文件（ReadMe）：.pdf格式文档，提供本数据集的通用说明信息。

研究方法：本数据集的数据采集与组织采用混合研究方法，结合大规模选举数据汇编与计算社会科学技术，以处理和分析海量信息。完整方法论详见本数据集配套的研究论文。