PITIIA · Promoting Investment for Sustainable Development through International Investment Agreements (PITIIA)

The PITIIA project investigates how the design of International Investment Agreements (IIAs) shapes foreign direct investment (FDI) in developing economies. It delivers three integrated objectives. First (Measurement): construct treaty-level indices and archetypes from full agreement texts using natural language processing (NLP) and unsupervised machine learning (ML) to capture “strength,” “complexity,” and scope. Second (Causality): estimate the effect of IIA design on FDI with a structural gravity framework using Poisson pseudo-maximum likelihood (PPML), complemented by modern causal methods—double/debiased machine learning (DML) and Bayesian Additive Regression Trees (BART)—to map where impacts vary with governance and legal quality. Third (Synthesis and Policy): translate findings into actionable guidance through policy briefs and an International Investment Agreement Effectiveness Dashboard v1.0, a public, open-data tool for ‘what-if’ simulations that help policymakers design agreements that foster investment while safeguarding policy autonomy. PITIIA treats investment treaties as credible signalling instruments whose effects depend on content and context, raising standards for measurement, identification, and reproducibility. Key outputs include open datasets and code, a containerised reproducibility bundle, two conference papers, one book chapter, and two journal submissions, ensuring both scientific contribution and practical uptake for sustainable-development-aligned investment policy.