Financial Repression Index for CFA Franc Zones: PCA Construction and Investment - Panel

This dataset accompanies the article “Measuring Financial Repression in CFA Franc Zones: Index Construction and Implications for Investment Activity”, accepted for publication in the International Journal of Financial Studies. It provides the complete empirical foundation for constructing, validating, and applying a composite Financial Repression Index for the 14 member countries of the CEMAC and UEMOA monetary unions. The dataset contains a balanced panel covering 2005–2021, which represents the longest period for which all repression‑related variables are jointly observable across the CFA franc countries. Although the institutional analysis in the article spans 1985–2024, data limitations—especially for interest‑rate series and liquidity ratios—necessitate restricting the empirical sample to this balanced window to ensure comparability and methodological integrity. The repository includes: * Excel dataset containing all macroeconomic variables used in the PCA and fixed‑effects regressions. A Python script that fully reproduce the PCA workflow: * PCA construction script: standardizes the four repression proxies and extracts the first principal component, which serves as the composite Financial Repression Index. The Financial Repression Index is constructed using principal component analysis (PCA) after standardizing all variables to mean zero and unit variance. Higher index values correspond to greater financial repression, reflecting policy‑induced constraints such as interest‑rate rigidities, liquidity mandates, and limited credit allocation. Domestic credit and broad money are treated as repression‑related outcomes rather than development indicators, consistent with the institutional characteristics of the CFA franc zones.本数据集配套发表于《International Journal of Financial Studies》的论文《中非法郎区金融抑制（Financial Repression）测度：指数构建及其对投资活动的启示》，该论文已获正式录用。本数据集为中非经济与货币共同体（CEMAC）与西非经济与货币联盟（UEMOA）两大货币联盟的14个成员国的综合金融抑制指数的构建、验证与应用提供了完整的实证基础。 本数据集包含2005–2021年的平衡面板数据，这是当前中非法郎区各国所有金融抑制相关变量可联合观测的最长时间跨度。尽管论文中的制度分析跨度为1985–2024年，但受限于数据可得性——尤其是利率序列与流动性比率数据——为保证样本可比性与方法学严谨性，实证样本被限定在该平衡窗口内。 本仓库包含以下内容： * 包含主成分分析（Principal Component Analysis, PCA）与固定效应回归所用全部宏观经济变量的Excel数据集； * 可完整复现主成分分析工作流的Python脚本：该脚本对四类金融抑制代理变量进行标准化处理，并提取第一主成分作为综合金融抑制指数。 金融抑制指数通过主成分分析构建，所有变量均先标准化至均值为0、方差为1。指数值越高代表金融抑制程度越深，对应政策引致的约束包括利率刚性、流动性强制要求以及信贷配置受限等。结合中非法郎区的制度特征，国内信贷与广义货币被视为金融抑制的结果变量而非发展指标。