Green Conditionality in Industrial Policy: Certified Energy Savings, Threshold Incentives, and Rationing in Italy’s Transizione 5.0
Italy’s Transizione 5.0 tax credit (2024–2025) paid for digital and energy investment only if
a certifier attested a minimum reduction in energy consumption, with higher rates for higher certified
savings. I study whether this conditionality led to additional investment and real energy savings, or
mainly to strategic certification around the thresholds. I plan to compare ex ante and ex post certified
savings near each threshold, look at differences across certifiers, and use the moment the budget ran
out to measure the cost of rationing for firms. Currently at the design and data access stage.
Lobbying and Industry Concentration in the European Union
I study how concentrated lobbying of the EU institutions is across firms, and how this compares with
the concentration of sales within industries. I measure the political activity of companies with three
public sources: the EU Transparency Register, the Have Your Say consultation portal, and the European
Commission’s records of its meetings with interest representatives. I plan to link these records
to firm-level financial data. The project builds on the lobbying records I collected for earlier work on
EU public consultations; the next step is building the firm-level data.
A Monetary Model of Money Laundering
Joint work with Fabrizio Mattesini. We are developing a theoretical model of money laundering with the
goal of linking the model to moments drawn from the Financial Intelligence Unit datasets of the Bank of
Italy.
Urban Mobility, with a Focus on the City of Rome
Like many first-year PhD students, I started a scraper before having a research question, as a
backup. It is still running. It collects the positions of shared bikes and e-scooters in Rome,
together with the city’s public transport feeds, and is slowly turning into a project.
Currently at the data collection stage.
Digital Democracy and Gender Equality
ENGAGE.EU Research Label collaboration. With my co-authors I drafted a critical framework for
understanding gender bias in AI across data and model levels, arguing these biases are structural
externalities for governance and regulation.
Event page →