Endogenous Financial Constraints and Innovation

We investigate which indicators of a firm’s innovation activities are associated with financial constraints and analyse the nature and direction of causal links between innovation and financial constraints. By estimating simultaneous bivariate probit models on data from the UK Innovation Surveys, we show that among innovation inputs, R&D activity increases the likelihood that firms face financial constraints while innovation outputs in the form of new-to-market products seem to generate financial constraints. Reverse effects on innovation appear limited to external R&D

Innovation, asymmetric information and the capital structure of new firms

Start-ups are essential contributors to economic development, but they often face several barriers to growth, including access to finance. We study their capital structure in their early years of operation through the lens of Pecking Order Theory, exploring how the pursuit of innovation influences firms’ reliance on different types of finance. Panel analyses of 8273 German start-ups show that innovation activities are relevant predict start-ups’ revealed preferences for finance. Effects on the type and order of financing sources depend on the degree of information asymmetries specific to research and development activities, human capital endowments, and the market introduction of new products and processes. New firms focused on research and development activities and with better human capital are less likely to receive informationally complex finance such as debt and will rely relatively more on owner and equity finance. Mixed evidence is found, instead, on the role of new products or processes. Our results suggest that the traditional pecking order theory does not hold for new firms, implying that owner and external equity play a much more prominent role for such firms. Then, managers and entrepreneurs should consider specific sources of finance and financial instruments in light of their innovative activities

Upgrading Italy's Industrial Capacity: Industry 4.0 across Regions and Sectors

How are Industry 4.0 investments distributed across Italian regions and sectors? Which are the main drivers of diffusion? To address these questions, in this study we exploit rich firm survey data on the adoption of the new digital technologies and examine their adoption patterns. On the one hand, we produce novel insights into the drivers of structural change in the Italian economy, and on the other, we provide evidence on the technological upgrading of Italy's production capacity that is relevant for policy. The results of econometric tests on region-sector pairs indicate that corporate governance characteristics, innovation patterns and type of industrial relations are significant predictors of the uneven regional and sectoral distribution of Industry 4.0 investments

The direction of technical change in AI and the trajectory effects of government funding

Government funding of innovation can have a significant impact not only on the rate of technical change, but also on its direction. In this paper, we examine the role that government grants and government departments played in the development of artificial intelligence (AI), an emergent general purpose technology with the potential to revolutionize many aspects of the economy and society. We analyze all AI patents filed at the US Patent and Trademark Office and develop network measures that capture each patent’s influence on all possible sequences of follow-on innovation. By identifying the effect of patents on technological trajectories, we are able to account for the long-term cumulative impact of new knowledge that is not captured by standard patent citation measures. We show that patents funded by government grants, but above all patents filed by federal agencies and state departments, profoundly influenced the development of AI. These long-term effects were especially significant in early phases, and weakened over time as private incentives took over. These results are robust to alternative specifications and controlling for endogeneity