This paper proposes a new method to predict the impact of preferential trade agreements (PTAs) on trade and welfare taking the Trans-Pacific Partnership (TPP) agreement as a case study. Relying on a novel dataset of treaty texts covering all trade agreements notified to the WTO, we first...

Preferential trade agreements (PTAs) form an intricate web that connects countries across the globe. In this article, we introduce a PTA text corpus and research tools for its fine-grained, automated analysis. Recent computational advances allow for efficient and effective content analysis by...

This paper constructs a legal text generation and assembly system in the domain of international investment law. We rely on a corpus of 1600 bilateral investment treaties split into 22 600 articles to train a character-level recurrent neural network (char-RNN). Prior work has shown that while...

Traditional means of content analysis are ill-equipped to deal with the vast universe of international investment agreements (IIAs). In this article, we propose a novel approach to efficiently investigate over 2,100 IIAs and their 24,000 articles in unprecedented detail by treating treaty text...

Through the lens of state-of-the-art text-as-data techniques, this article examines the bilateral investment treaty (BIT) practice of the member states of the Gulf Cooperation Council (GCC). The analysis unveils two critical trends. First, GCC states are global champions of investment...