Project Description
International economic law increasingly has to confront problems of a “big data” nature. Faced with a proliferation of thousands of bilateral investment treaties (BITs), hundreds of free trade agreements (FTA) and an ever-growing body of case law rendered by WTO panels or investment arbitrators, it becomes exceedingly important to find new ways to organize and analyze this complex and atomized structure of international economic law.
While in the past it was either prohibitively costly or simply impossible to investigate thousands of treaties or hundreds of awards, the advance of technology and, in particular, of big-data analytics provides new tools to conduct innovative and insightful legal empirical analysis with a view to revealing yet undiscovered structures running through international economic law.
This project employs state-of-the-art text as data analytics and network analysis tools to investigate patterns of convergence and divergence in two areas of international economic law, examining trade and investment: (1) the universe of free trade and investment protection agreements and (2) the network of investment awards and trade panel/Appellate Body reports. This project will make a novel contribution to these efforts by providing big data solutions to big data problems. Revealing the structures of convergence and divergence in both areas of international law using text-as-data analytics and network analysis tools will help policy-makers and negotiators, in particular in developing countries, to better understand the current structures of international economic law and to help evaluate its need for reform.