4 papers
The heterogeneous impact of the EU-Canada agreement with causal machine learning
Lionel Fontagné, Francesca Micocci, Armando Rungi
This paper introduces a causal machine learning approach to investigate the effects of free trade agreements and applies it to the EU-Canada Comprehensive Economic and Trade Agreem…
The Network Effects of the EU Carbon Border Adjustment Mechanism with a Quantitative Trade Model
Noemi Walczak, Kenan HuremoviÄ, Armando Rungi
We investigate the economic and environmental impacts of the European Carbon Border Adjustment Mechanism (CBAM) using a multi-country, multi-sector general equilibrium model with i…
Learning by exporting with a dose-response function
Francesca Micocci, Armando Rungi, Giovanni Cerulli
This paper investigates the causal effect of export intensity on productivity and other firm-level outcomes with a dose-response function. After positing that export intensity acts…
Non-linear dependence and Granger causality: A vine copula approach
Roberto Fuentes-MartÃnez, Irene Crimaldi, Armando Rungi
Inspired by Jang et al. (2022), we propose a Granger causality-in-the-mean test for bivariate Markov stationary processes based on a recently introduced class of non-linear mod…