2025
Demand, wealth inequality and the business cycle
Journal of Macroeconomics
We consider a flexible price continuous-time DSGE model of a closed economy populated by heterogeneous households subject to uninsurable idiosyncratic income risk and aggregate TFP shocks. The economy produces a variety of imperfectly substitutable final goods. Our main innovation is a rich representation of household consumption and saving behavior allowing for a time-varying elasticity of substitution across varieties. Specifically, we consider a utility function displaying Increasing Elasticity of Substitution (IES). We provide a convenient approach to handle the complex dynamic programming problem implied by income heterogeneity, aggregate shocks and non-homothetic preferences. We show that IES preferences help to replicate important features of the wealth distribution observed in the data together with a plausible macroeconomic dynamics.
2024
We investigate the impact of platform-based accommodations in the real estate market on socio-economically relevant indicators. Using a city-specific dataset from 2017 to 2019 we studied the effect of Airbnb density on rental prices, residential population, and non-local undergraduate enrollments in the municipality of Bologna. Leveraging rental estimates from the Real Estate Market Observatory, as well as data on Airbnb listings, we employed three longitudinal estimations with zone-fixed effects and various demographic and economic controls. Our analysis reveals a significant positive association between Airbnb and rental prices. Moreover, Airbnb presence seems to have a negative impact on non-resident undergraduate enrollments in the subsequent year. These findings support existing literature on the impact of platform-based accommodations on rent and underscore its potential role in producing tourist-led gentrification within urban areas.
2023
Nonparametric estimates of option prices via Hermite basis functions
Annals of Finance
We extensively investigate the empirical performance of approximate pricing formulas for European options based on approximating the logarithmic return’s density of the underlying by a linear combination of rescaled Hermite polynomials. Empirical results suggest that such approximate pricing formulas, when compared with simple nonparametric estimates based on interpolation and extrapolation on the implied volatility curve, perform reasonably well only for options with strike price not too far apart from the strike prices of the observed sample.
2022
Estimating tail-risk using semiparametric conditional variance with an application to meme stocks
International Review of Economics & Finance
Machine Learning-Driven Credit Risk: a Systemic Review
Neural Computing and Application