Presentation for 2026 CADSA Symposium

This project applies the Fama-French Three-Factor Model to a simulated Moroccan stock market dataset. The analysis constructs the market, size, and value factors and estimates their impact on portfolio returns using OLS regression. Diagnostic tests and robust (HAC) standard errors are used to ensure reliable inference. Results show that the three factors significantly explain returns, highlighting the relevance of multifactor models in emerging markets.

This notebook explores the time dimension of the statistical capacity dataset, which tracks country-level scores across indicators of data quality and accessibility from 2004 to 2023. The focus here is on how one of those indicators, data_products_score, which measures the quality and availability of statistical outputs produced by a country, has evolved globally over nearly two decades. Because the dataset records one observation per country per year, the analysis works at the level of global yearly averages, which produces a clean annual time series from 2005 to 2023.