skip to content
Matteo Pograxha
Matteo Pograxha

About

I am a Research Fellow at the University of Nottingham and a PhD Candidate in Economics at Trinity College Dublin. I am currently visiting Harvard Government hosted by Professor James Snyder.

My research interests lie in empirical Political Economy with a specific focus on Media Economics. I employ advanced text analysis techniques, including BERT-based models and large language models (LLMs).

You can find my CV here. Email: matteopograxha@gmail.com

Research

Working Papers

  • Man Bites Dog: Editorial Choices and Biases in the Reporting of Weather Events - with Nicola Mastrorocco, Arianna Ornaghi, and Stephane Wolton CEPR Discussion Paper (2023)

    Every day, editors of media outlets decide what is news and what is not. We unpack the process of news production by looking at the share of newscasts devoted to weather events by local TV stations in the United States. We document that coverage increases with the severity of the weather event that day. We also uncover that stations operating in Democratic-leaning markets devote more time to extreme weather events and mention climate change more than outlets in Republican-leaning markets. We make sense of these publication and presentation biases with a stylised model of news production and consumption.

Work in Progress

Research & Training

  • Oct 2024 – Sept 2025
    UN Research Consultant — Text Analytics & Legal Digitization

    Led large-scale digitization and variable extraction of South African Government Gazettes using advanced layout detection and Named Entity Recognition (NER).

  • Sept 2025
    Guest Instructor — National Treasury (Pretoria), South Africa

    Delivered a two-day seminar on text analysis for policy and research teams, covering NLP pipelines, document layout parsing, and practical use cases with legal and administrative texts.

Teaching

  • Spring 2022
    Introduction to Macroeconomics - Undergraduate
  • Fall 2022
    Introduction to Microeconomics - Undergraduate
  • Spring 2024
    Statistics - Undergraduate