A people-centric view of your email life
Center for Collective Learning

  About CCLThe Center for Collective Learning (CCL) studies how knowledge moves, grows, and decays, from teams to nations, and from the past to the future.We are a multidisciplinary team of researchers based in Toulouse, France, and at the Corvinus University of Budapest.Our research informs sustainable economic development strategies, and has led to the creation of dozens of public data observatories. We are pioneers in economic complexity methods, which involve the application of machine learning techniques to questions of economic development.CCL is supported by a European Research Executive Agency (ERA) Chair, and two Horizon consortia projects: the European Lighthouse of AI for Sustainability (ELIAS), and the Observatory for the Sea.



  Featured project: Rankless





















  
  





Rankless is a data exploration platform that allows you to explore the impact of universities without the need for rankings. All universities make impact that is specific to the the topics they specialize in and the geographies they inhabit. If you want to understand academic impact, you need to explore more and rank less.




















  
  






  Grant announcement: ERC Synergy Award





















  
  





      

      
        
          
        
        

        
          
            
          
            

            
          
        
          
        

        
      
        
      

    
  We are proud to announce that Professor César Hidalgo, director of CCL, together with his colleagues, Professor Umberto Grandi, Professor Ulle Endriss and Professor Maija Setälä, won a prestigious ERC-synergy award for ADDI: Advancing Digital Democratic Innovations. Their goal is to to study digitally augmented forms of civic participation. 

  Featured paper: Augmenting the availability of historical GDP per capita estimates through machine learningPhilipp Koch, Viktor Stojkoski, César A. Hidalgo PNAS (2024)





  


  We introduce a machine learning method to estimate the GDP per capita of dozens of countries and hundreds of regions in Europe and North America for the past 700 years using data on hundreds of thousands of historical figures. We find that our model generates accurate out-of-sample estimates that correlate with other proxies of economic output such as urbanization, body height, wellbeing, and church building activity. Additionally, we show our estimates reproduce the well-known reversal of fortune between southwestern and northwestern Europe between 1300 and 1800 and find this is largely driven by countries and regions engaged in Atlantic trade. These findings showcase the use of granular biographical data to estimate historical income levels and augment the availability of historical GDP per capita data.Full paper



  Conference on Economic Complexity (CEC)Highlights from the event





















  
  






  Flagship CollaborationsThe Observatory of Economic Complexity (OEC)





















  
  





      

      
        
          
        
        

        
          
            
          
            

            
          
        
          
        

        
      
        
      

    
  The Observatory of Economic Complexity is a leading international trade data distribution platform. It was begotten at MIT’s Collective Learning group in 2011, and after being open-sourced, it was professionalized at Datawheel (a company that spun out of the CCL in 2013). Today the OEC has dozens of proprietary data pipelines and receives 800k+ monthly users. The CCL is an active partner and collaborator with the OEC. The OEC is updated monthly and has been used by over 5,000 academic publications according to Google Scholar.  Pantheon 


      

      
        
          
        
        

        
          
            
          
            

            
          
        
          
        

        
      
        
      

    
  Pantheon is an observatory of human collective memory. It contains structured data on the biographies of more than 80k notable individuals. Pantheon was created at MIT’s Collective Learning in 2013. Its current development is now performed by Datawheel. The Center for Collective Learning continues to participate in the Pantheon project by performing academic research on collective memory and by exploring the design of new features that could enhance our understanding of human collective memory.Explore more projects
