Master Econometrie, Statistiques

Master Économétrie, Statistiques at Université Paris 1 - Panthéon Sorbonne in Paris, France is a two-year master's program taught in French. Econometrics and statistics form a field that applies mathematical and statistical methods to economic and social data, aiming to test theories, measure relationships between variables, and support forecasting and policy analysis. Students in this field typically study probability theory, statistical inference, regression analysis, and more advanced econometric techniques for working with time series and panel data, alongside courses in microeconomics and macroeconomics that provide the theoretical grounding for empirical analysis. Coursework generally emphasizes both the mathematical foundations of statistical modeling and practical training in statistical software used to process and analyze large datasets. Many programs include applied projects where students work with real economic or financial data to answer questions about markets, policy effects, or social trends, building skills that combine quantitative rigor with economic interpretation. Some programs also introduce students to machine learning methods as they apply to economic and financial data analysis. Graduates of econometrics and statistics programs commonly pursue careers as data analysts, economists, statisticians, or quantitative researchers, working in banks, insurance companies, government statistical agencies, consulting firms, and international organizations that rely on data-driven analysis. Some continue into doctoral research in economics or statistics. Instruction for this program is delivered in French, so applicants need a solid quantitative background along with the language proficiency to follow coursework and technical material. The program starts in September and runs over two years, leading to a master's degree. Yearly tuition is 250 EUR. Paris offers access to major financial institutions, government agencies, and research centers that employ graduates trained in econometrics and statistics.