Carbon Tax, Labour Market Segregation, and Inequality, with Flavio Contrada and Alessandro Spiganti (December 2025)
A rapid transition to low-carbon production is essential for climate mitigation, but its economic costs and benefits are not evenly shared. This paper studies how carbon pricing affects workers of different skills when clean and dirty energy sectors differ in their skill intensity. We extend a dynamic multi-sector environmental growth model in the spirit of Golosov et al. (2014) by introducing high-and low-skill households and a production structure in which clean energy is relatively high-skill intensive and dirty energy relatively low-skill intensive. We show that a Pigouvian carbon tax decentralizes the first-best allocation by internalizing the external cost of emissions, yet it is not distributionally neutral: the induced reallocation of capital and labour toward clean production raises the skill premium and can reduce welfare for the low-skill household. Numerical simulations calibrated to the U.S. economy confirm that aggregate welfare gains coexist with significant welfare losses for low-skill households, raising concerns about the political acceptability of such policies.
Learning Models from Prices, with Filippo Massari (September 2025)
We study a dynamic financial economy with complete markets in which agents
hold heterogeneous beliefs about dividends. Beliefs combine an exogenous agent-
specific model, possibly misspecified, and an endogenous market-based model de-
rived from state prices. We show that using prices to learn improves prediction and
offers a hedge against model misspecification. With Bayesian learning, agents up-
date model weights and survive on all paths. Market beliefs converge almost surely
to the most accurate exogenous model, despite heterogeneity and misspecification,
and so do individual beliefs of any agent who assigns positive prior weight to it.
With non-Bayesian learning, where the weight on the market model is fixed, sur-
vival is not guaranteed. Yet market accuracy weakly improves, and can exceed that
of any individual model when beliefs are diverse. In such cases, relying on prices
helps approximate the truth, while ignoring the market leads to vanishing. Our
results characterize how endogenous use of prices shapes learning, survival, and the
predictive power of markets.
An Economic Model of Acculturation under Strategic Complements and Substitutes, with Sebastiano della Lena (March 2025)
We propose a cultural transmission model based on the co-evolution of cultural traits, behaviors, and socialization levels. Cultural traits affect agents’ behavior during their interaction in a strategic environment. In turn, behaviors affect both how much parents directly socialize their children and the traits they decide to transmit. We describe the co-evolution of cultural traits and behaviors, and their long-run outcomes, in terms of well-established acculturation processes: assimilation, integration, marginalization, and separation. We characterize how the occurrence of each process depends on the nature of the strategic environment (complements or substitutes), the cost of transmitting traits, and the size of the majority.
Work in Progress (preliminary titles)
On the Accuracy of Prediction Markets, with Pablo Beker
Long-run Effect of a Transaction Tax in Speculative Markets, with Filippo Massari and Arianna Traini