3 citations · 3 across the 7 of their papers we have counts for
11 papers
Bias-robust causal inference for panel data
Angelos Alexopoulos
We develop a bias-robust causal inference method for observational panel data settings. Such methods typically impute untreated outcomes, so counterfactual error passes straight in…
Exchangeable Gaussian Processes for Staggered-Adoption Policy Evaluation
Hayk Gevorgyan, Konstantinos Kalogeropoulos, Angelos Alexopoulos
We study the use of exchangeable multi-task Gaussian processes (GPs) for causal inference in panel data, applying the framework to two settings: one with a single treated unit subj…
On robust Bayesian causal inference
Angelos Alexopoulos, Nikolaos Demiris
This paper develops a Bayesian framework for robust causal inference from longitudinal observational data. Many contemporary methods rely on structural assumptions, such as factor…
Gaussian Invariant Markov Chain Monte Carlo
Michalis K. Titsias, Angelos Alexopoulos, Siran Liu +1
We develop sampling methods, which consist of Gaussian invariant versions of random walk Metropolis (RWM), Metropolis adjusted Langevin algorithm (MALA) and second order Hessian or…
A computationally efficient framework for realistic epidemic modelling through Gaussian Markov random fields
Angelos Alexopoulos, Paul Birrell, Daniela De Angelis
We tackle limitations of ordinary differential equation-driven Susceptible-Infections-Removed (SIR) models and their extensions that have recently be employed for epidemic nowcasti…
The heterogeneous causal effects of the EU's Cohesion Fund
Angelos Alexopoulos, Ilias Kostarakos, Christos Mylonakis +1
This paper estimates the causal effect of EU cohesion policy on regional output and investment, focusing on the Cohesion Fund (CF), a comparatively understudied instrument. Departi…