Since the late 1980s, international institutions have been using economic models and quantitative assessments to inform policymakers about the potential costs, benefits and trade-offs of environmental policies and climate change mitigation scenarios. This mainly concerns the costs of environmental inaction, as well as the benefits of policy action on issues such as climate change, air pollution and resource use.

More recently, modelling issues have also become financial and accounting issues: by calling on the mathematicians, economists and accounting researchers in its network, the Cournot Foundation is helping to enrich the debate by recalling the underlying theoretical foundations and promoting modelling that takes account of the turbulence affecting economies, crises or wars.

The first step was to develop and promote a specific model for estimating the climate risk embedded in a bank loan portfolio ("The Climate Extended Risk Model", 2020), a model that continues to drive financial debate. For some months now, these debates have focused on accounting issues, the main stakes of which also feed into the most fundamental debates between accounting theory and corporate law theory. The Cournot Foundation brings to these debates the original contribution of its theorists.

In 2021, Josselin Garnier, member of the scientific committee, built a model that was a direct extension of the models used in current regulation. The Cournot Foundation brings the original contribution of its theorists to these debates.


The pandemic has had a severe impact on the most vulnerable workers, particularly women and precarious workers, as well as on developing countries. In response to the crisis, economists promoted measures to preserve jobs through retention programs, and to support household income through cash transfers and extended unemployment benefits.

Almost all countries have introduced at least one type of active labour market policy (training, employment incentives, direct job creation, business start-up incentives, public employment services and administration, sheltered and supported employment and rehabilitation) to cope with the negative effects of the pandemic.

What assessment can be made today, more specifically, for women? The Cournot Foundation proposes to take stock of these measures and to draw lessons from their consequences for the crises that have followed. Particular attention will be paid to tax policies and parental leave policies.


Work carried out as part of an initial Alfred P. Sloan Foundation project has demonstrated the analytical power of multifractal methods for understanding financial market mechanisms. These methods seem suitable for qualifying the changes in the International Monetary System (IMS), which have led to significant ruptures with the rise of cryptoassets.

Monetary relations are classically analysed by economists based on classifications of exchange rate regimes, first official (de jure), then observed (de facto), but the new classifications do not take into account all the dimensions of the transformations. Is the traditional notion of exchange rate regimes still relevant in the emerging IMS? The interrelations between currencies and cryptoassets require the establishment of a common analytical framework.

The Cournot Foundation’s approach is based on statistical methods, implemented to quantify the proximity between the different assets.
The project focuses simultaneously on the comparison of the fluctuation regimes of cryptocurrencies, currencies, and commodities, to determine the differences and similarities both from a mathematical and an economic point of view. Can similar behaviours be detected in a set of different cryptoassets? Do crypto-market dynamics lead to greater efficiency over time? Do political tensions between the main market players strongly influence these dynamics?

This quantitative and analytical base serves as a starting point for reflection on the economic nature of these assets and for a new look at the oil market and the classification of exchange regimes based on a mathematical categorization. It also makes it possible to confirm the methodological interest of the analysis of persistence regimes established during the previous Sloan project, to make it a systematizable tool.


The Cournot Foundation has a unique transdisciplinary approach as both an observer and a promoter of the probabilization of science. With a scientific team of probability theorists and practitioners, the Foundation brings together researchers to explore historical and contemporary issues from a theoretical perspective. The multidisciplinary conferences and seminars highlight how the mathematics of randomness has been changing concepts and methods. Mathematicians, historians, economists, philosophers and other scholars contribute to these events with the aim of broadening their audience. For younger audiences, an initiation program introduces probability theory to middle school students in Educational Priority Areas.

Health Crisis and Economic Crisis: Have Large Cities Been the Most Affected by the Pandemic?

The Cournot Centre proposes to measure the impact of the crisis on the basis of local corporate taxation: the level of analysis is therefore that of the municipalities. At this level, an assessment of the state of economic activity can be compared with the national framework data. The economic-activity-based approach (DGCL, INSEE and DGFIP data [2020]) provides a detailed picture of the depth of the crisis for each sector, and, in particular, for the presential economy. The aggregation of data makes it possible to establish a diagnosis at the level of inter-municipalities, employment zones, and urban areas.

The objective of the project will be to measure the intensity of public policies according to territories (employment, companies) and to propose a typology of the most affected areas by sectors and professions.

The data used will be drawn from the Census of Local Direct Taxation (REI) from 2019 and 2020, as well as from criteria for the distribution of state allocations for fiscal years 2019 through 2021. The data on the Cotisation sur la Valeur Ajoutée des Entreprises (Company Value Added Contribution) (CVAE) reflect the evolution of economic activity in the territories. The data on the tax on commercial surface areas (TASCOM), or on the flat-rate distribution network tax (IFER) can be used to confirm or qualify the diagnosis. It is also possible to apply to these data the deformations in accordance with INSEE's framing data. The reports will present a statistical overview and an assessment of the indicators of the crisis, and finally an attempt at categorization, based on the most relevant criteria for differentiating the territories, and, in particular, those that discriminate against the presential economy.


Since the publications of Kolmogorov in the 1940s, the dominant approach has been to model turbulence using fractional or multi-fractional processes. The experimental confirmation of the predictions made possible by the models has always, however, been a delicate matter. Recently, the observation of time series taken from commodities or currency markets has made it possible to demonstrate in a direct way such multi-fractional behaviour.

The Cournot Centre’s Probabilism research programme for 2020 is organized around two questions stemming from these results:

  • On what kind of data is this type of behaviour observable?
  • Which micro-models are capable of taking into account these macroscopic processes?

The first results were based on data from human interactions. Can the methods developed for commodities or currencies be used on other types of data? Fields as varied as wave propagation in the atmosphere, the dynamics of animal populations, intracellular transport in systems biology, imaging of human tissue by elastography, communication networks and internet traffic are all areas in which the multi-fractional approach has been tested.

In all of these fields of study, the nature of the data conditions the development of the models to be estimated. They have to be sampled correctly, in order to allow for time-frequency analysis, and must not be filtered or pretreated. The fact that the processes are of a fractional or multi-fractional nature is fundamental. If modelling Markov processes has been the standard stochastic approach, the multiplication of available data confirms that it is not only possible, but necessary to go beyond this framework and develop new tools and non-Markovian models.

There are important challenges associated with modelling, simulation and analysis of non-Markovian phenomena when trying to understand them through comparison with experimental data. Non-Markovian models may, in particular, be important for modelling what results from human intervention; that may mean that there is “memory” in the process leading to a non-Markovian behaviour as, for instance, recently seen in price processes.