(with Andrea Fronzetti Colladon, Barbara Guardabascio, Ludovica Segneri,  Alessandro Sterlacchini)

We investigate the dynamic effects of radical innovation on firm labour productivity growth and identify its main transmission channels. Radical innovation is defined in terms of novelties relative to the Italian technology market. Using panel data on over 28,500 Italian firms from 2012 to 2020, and analysing the text of their patents, we examine how firm labour productivity growth responds to the launch of a novelty, distinguishing whether the effect is driven by product or process innovation and whether it transmits through output or employment dynamics. We find that output per worker growth initially slows down but accelerates in subsequent years. The cumulative effect of novelties over time is positive and economically significant: firms that introduce these new technologies experience, on average, an 8\% faster rate of labour productivity growth than firms that do not. This effect is primarily driven by employment adjustments, particularly among small firms, which respond significantly to product novelties. We show that the effect of novelties is causal, using a difference-in-differences approach that treats the arrival of novelties as an event of technological discontinuity, and, alternatively, an instrumental variable strategy that exploits variation in firms' access to local public knowledge for identification.


(with Larissa Marioni, Ana Rincon-Aznar)

Using novel data on UK businesses, we identify the key factors that influence firms' propensity to invest in data assets and assess how these investments relate to productivity outcomes. We find that businesses investing in digitised information and in targeted training are 20–40\% more likely to use data for external and scientific purposes, as well as to perform skill-intensive data tasks. Labour productivity levels in data-investing firms are 1.4 to 1.5 times higher compared to firms not engaged in such activities. 


(with Andrea Fronzetti Colladon, Antonio Minnti, Carmelo Parello)

This paper examines the impact of technological interdependence on economic growth in an increasingly integrated world. We construct a Schumpeterian growth model that highlights how innovation not only propels the expansion of leading economies but also facilitates the transfer of knowledge to developing nations. The ability of follower countries to effectively utilize technology transfers depends on their proximity to the technological leader. By catalyzing the technology catch-up of the followers, technological interdependence diminishes the innovation growth potential for the frontier economy. Subsequently, using half-century data from a global sample of countries, we evaluate the predictions of the model by measuring international technology interdependence based on the textual similarity of over 7 million patent applications. Our empirical findings underscore the significance of technological interdependence as a growth driver for technology leaders and, notably, for countries below the frontier. Furthermore, our data reveals a shift in technological interdependence over time, with China emerging as a dominant player in the world's technology market, replacing the United States


     (with Andrea Bacchiocchi, Germana Giombini, Ludovica Segneri)

Does financial risk affect firms’ decisions to develop new technologies? We address this question in the context of the rise of Artificial Intelligence (AI). Using data on 28,020 Italian firms observed between 2012 and 2019 and matched with patent records, we find that firms more exposed to financial risk, proxied by cash-flow volatility, are more likely to innovate in AI. The result is robust to financial, economic, market-uncertainty and technological controls. By contrast, financial risk has significantly weaker effects on innovation in more mature technologies. Our findings suggest that financially risk-exposed firms are more willing to invest in high-uncertainty/high-reward innovation domains, possibly to reduce future financial distress.


    (with Andrea Bacchiocchi, Germana Giombini, Ludovica Segneri)

Using a panel sample of innovating firms in Italy during the early (pre-LLM) phase of AI development (2012–2021), we examine how financial conditions affect firms’ patenting in new digital fields and, through an event analysis, we assess how these factors influence firm economic performance by shaping AI innovation. Our findings show that higher leverage and larger cash holdings significantly constrain firms’ ability to succeed in new digital fields. Through this channel, productivity is between 1% lower for each additional percentage point in these financial conditions.