Concept

ENSAE Paris

Summary
ENSAE Paris (officially École nationale de la statistique et de l'administration économique Paris) is a university in France, known as Grandes Ecoles and a member of IP Paris (Institut Polytechnique de Paris). ENSAE Paris is known as the specialization school of École polytechnique for economics, finance, applied mathematics, statistics, and data science. It is one of France's top engineering schools and is directly attached to France's Institut national de la statistique et des études économiques (INSEE) and the French Ministry of Economy and Finance. The ENSAE was established in 1942 by the National Statistics Service (ancestor of the INSEE, National Institute of Statistics and Economic Studies) under the name School of Applied Statistics. In 1946, with the creation of INSEE, the school took the name of INSEE Specialization School. At this time, the school led to two types of administrative careers: "administrateur" (the highest managing level of the INSEE administration) and "attaché" (a lower level) civil servant executive. Early promotions included five or six "administrateurs" students and five or six "attachés" students. The decree of 2 November 1960 changed the school's name to the National School of Statistics and Economic Administration. As a result, the number of students grew, and the school opened to graduate students from law schools and universities of economics. Finally, the decree of 15 April 1971 clarified the administrative status and the objective of the school in the academic field, designating the ENSAE a Grande Ecole. In the 1980s, a scholarship system was established to support doctoral studies. In addition, a research laboratory, the CREST (Center for Research in Economics and Statistics), was formed in 1988. In 1994, the Department of training for "attachés" became a full-fledged school, the National School for Statistics and Analysis Areas information (ENSAI, relocated to Rennes). The "administrateurs" training stayed at the ENSAE where increasing numbers of students chose to specialize in financial modeling and other new areas of applied statistics such as biostatistics or marketing.
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