Research

In this paper, we aim at disentangling the various forces that contributed to shape the housing market dynamics during 2020. While a large shock in household income should have put a downward pressure on house prices, due to low demand, this is not what we have observed in reality. Other factors, such as a change in preferences toward housing or speculative motives following expansionary monetary and regulatory policy may have been the cause of the house price soar. To disentangle all these mechanisms, we estimate a structural DSGE model, which features a housing market, to assess the various driving forces on housing markets during the COVID-19 crisis. In this framework, we consider several shocks that may have had an influence on the housing market during the pandemic to identify their relative importance . Preliminary results confirm the interpretation that households' demand for residential services has proven to be the most important factor in mitigating the negative oscillations in prices and quantities in this market.

This work studies the turbulent confluence of two major events - the COVID-19 pandemic and the Russian invasion of Ukraine - both of which caused significant disruptions in global energy demand and macroeconomic variables. We propose and estimate a two-sector Dynamic Stochastic General Equilibrium model that incorporates both crude and refined energy sources, thus combining together the multifaceted dynamics of the energy sector, where crude elements like oil, coal, and gas are intertwined with other production components. The model describes the transmission of energy shocks through complementarities in production and consumption, as a mechanism that amplifies the fluctuations of the business cycle. We find that the impact of price shocks on oil, coal, and gas accounts for 32% of the increase in the general price level between 2021:Q1 and 2022:Q4, and that oil and gas price shocks contributed most significantly. Finally, we discuss the case in which energy shocks can be Keynesian supply shocks.

Recent studies suggest that space activities generate significant economic benefits. This paper attempts to quantify these effects by modeling both business cycle and long-run effects driven by space sector activities. We develop a model in which technologies are shaped by both a dedicated R&D sector and spillovers from space-sector innovations. Using U.S. data from the 1960s to the present day, we analyze patent grants to distinguish between space and core sector technologies. By leveraging the network of patent citations, we further examine the evolving dependence between space and core technologies over time. Our findings highlight the positive impact of the aerospace sector on technological innovation and economic growth, particularly during the 1960s and 1970s.

We develop a unified framework for integrating asynchronous analyst forecasts, firm fundamentals, and realized earnings into real-time cross-sectional signals. The approach combines a dynamic state-space representation of firm-level earnings with a reduced-rank structure that captures information propagation across firms. By accounting explicitly for irregular forecast timing and announcement schedules, the model generates expected-surprise measures that update continuously as new information arrives. The motivation follows the idea that effective forecasting and trading arise from exploiting overlooked information, combining heterogeneous data sources, and reacting before such information is fully incorporated into prices. Empirical results using I/B/E/S forecasts show that even a parsimonious specification delivers accurate real-time expectations and informative daily cross-sectional signals.

The EU has set ambitious targets to replace fossil fuels with renewable energy, aiming for 42.5% penetration by 2030. Bioenergy can be a significant contributor, especially in mountain areas with abundant residual biomass. However, regional planning for bioenergy adoption requires careful evaluation of levelized costs and key techno-economic risks. This study focuses on bioenergy from biomass gasification and combined heat and power (CHP) in South Tyrol. It uses techno-economic modeling to assess key factors affecting bioenergy LCOE, the impact of future renewable energy market conditions on competitiveness, and necessary subsidies to achieve price parity over the plant's lifetime. 

This chapter reviews and contextualizes the economic effects of US space activities from the 1960s Space Race to the 2020s. Initially driven by Cold War geopolitics, early space efforts led to significant advancements like the Apollo missions and satellite technology. Today, the focus has shifted to sustainable space economy initiatives, where private companies take on more risks and receive more rewards, promising substantial commercial and scientific benefits. First, this chapter provides examples of how space investments have contributed to technological progress and economic growth. The chapter then analyzes the microeconomic and macroeconomic effects of space activities, outlining key contributions in both areas. The chapter concludes by highlighting new research directions to study the peculiarities of the emerging New Space Economy.