ENSAE Paris - École d'ingénieurs pour l'économie, la data science, la finance et l'actuariat
ENSAE Paris - École d'ingénieurs pour l'économie, la data science, la finance et l'actuariat
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History and identity

History and identity

The origins

Mathematical statistics as we know it today is a recent discipline whose formalization from probability theory dates back to the 1930s. The history of ENSAE is inseparable from this development of statistics as a branch of applied mathematics, but also from its economic and social applications.

In 1942, a School for the Application of the National Statistics Service was created, which in 1946 became the School for the Application of the INSEE when the National Institute of Statistics and Economic Studies was created. The school originally trained executives for the statistical and economic administration, with classes of about ten students, most of whom were graduates of the École Polytechnique. In 1960, the school received its current name of École nationale de la statistique et de l'administration économique. The size of the classes increased and students who were not civil servants quickly became the majority, as the dual training in economics and statistics met a growing demand from businesses.  

The broad lines of ENSAE's educational project were laid out from the outset by its first director, Eugène Morice, who defined its dual field of competence in statistics and economics. However, it was Edmond Malinvaud, who succeeded him in 1962, who gave ENSAE its impetus. Thanks to his action, the school acquired the academic prestige and the image of scientific excellence that its partners recognize today. Under his impetus, economic modeling and econometrics were developed, the latter becoming a key discipline at the school at the interface of mathematical statistics and economic analysis. From the outset, ENSAE's training was original in that it combined courses from disciplines that were compartmentalized at the university, in order to provide coherent skills in the use of data for decision-making. This multidisciplinary positioning has remained remarkably stable over time and is still the hallmark of ENSAE today, along with the requirement for scientific rigor.    

From the outset, the school has relied on a diversified recruitment of Polytechnique students, students from scientific preparatory classes ("mathematics option" and "economics option" competitions), and university students. Since 1985, the pool of students has been expanded to include scientific Khâgnes, at the crossroads of literary and scientific cultures. In 1962, a training center for economists and statisticians from developing countries (CESD) was created within ENSAE to train African students. These training courses were gradually distributed within a network of African statistical schools, which remained closely linked to the school and to INSEE. 

The recent period

The Center for Research in Economics and Statistics (CREST) was created in 1980 within ENSAE. 

Until the end of the 1980s, ENSAE had two divisions dedicated respectively to the training of statisticians-economists and INSEE administrators (SEA division) and statistical management executives and INSEE attachés (CSGA division). In 1994, the Lesourne-Curien report led to the splitting of ENSAE into two schools, the first within the SEA division, which kept the name ENSAE, and the second within the CGSA division, which became the Ecole nationale de la statistique et de l'analyse de l'information (ENSAI) and focused more on statistics, data management, statistical engineering, and computer science. These two schools, along with the CEPE (a continuing education center created in 1957 and attached to ENSAE in 1987) and CREST, form the Groupe des écoles nationales d'économie et statistique (GENES). 

In the 1980s, the demand for ENSAE graduates from banks, insurance companies and the financial services of large corporations exploded. The school adapted to this demand by developing a range of specialization courses in finance and insurance, and by creating a finance laboratory within CREST. 

In the 2000s, ENSAE asserted its identity as a leading engineering school by joining the Mines-Ponts joint competition and the ParisTech network, along with eleven other top Parisian schools (AgroParisTech, Arts et Métiers ParisTech, Chimie ParisTech, École des Ponts ParisTech, École polytechnique, ENSTA ParisTech, ESPCI ParisTech, HEC Paris, Institut d'Optique Graduate School, Mines ParisTech, and Telecom ParisTech). In 2012, GENES was granted the status of a major public institution of higher education and research, and gained autonomy to take part in the reorganization of higher education. CREST became a joint CNRS-GENES-École polytechnique research unit. Cramped in its Malakoff premises, ENSAE decided to move to the Saclay plateau. It became a founding member of the COMUE Université Paris-Saclay and moved in September 2017, along with the Parisian hubs of CREST and GENES, into a new building built near the École polytechnique. ENSAE leaves the ParisTech network and the COMUE in 2019 to build the Institut Polytechnique de Paris (IP Paris), with the École polytechnique, ENSTA Paris, Télécom Paris and Télécom SudParis. It will then change its name from ENSAE ParisTech to ENSAE Paris.

After 80 years, ENSAE entered a new phase in its history. The Institut Polytechnique de Paris is now a reality: an experimental higher education and research institution, accredited to award master's and doctoral degrees, it will begin its first academic year in September 2019. ENSAE and CREST provide expertise in statistics and machine learning, quantitative economics and sociology, finance and actuarial science. While the institutional environment of the school has undergone profound changes, the school's pedagogical project is, on the other hand, very much in line with continuity: mastery of mathematical tools remains the foundation of the dual competence in statistics and economics, the basis from which students then choose to specialize in actuarial science, data science, finance, actuarial science, economics or quantitative sociology.