Abstract: Contributing to the fast-growing Economics of Artificial Intelligence (AI), this paper examines the close relationship between university and industry for what concerns to the research and development of AI technologies in the USA. Recalling the history of the university-industry relationships in the several phases of the US national system of innovation (NSI), we argue that current collaborations resemble in some respects what happened during the prewar NSI. Yet, the AI R&D presents some peculiarities. Universities are changing their positioning in the innovation process and turning to a research-based training model in the domains concerned by AI. This could potentially change the trajectory of university-industry links, since it is very much in line with the typical Humboldtian perspective that was at work in some European institutes in XVIII century up to US early XX century. At the same time, if the way in which the production of knowledge and the training of the workforce envisages a return to the origins, differences arise in the definition of the main goals—e.g., Sustainable Development Goals—and in the role of stakeholders. The overall discussion also bears some implications for the link between division of knowledge and division of labour.

Abstract: This paper contributes to the understanding of the emergence of biotechnology as the outcome of a co-evolutionary process that necessitated simultaneous innovations in four core domains: law, government policy and university-industry links, molecular biology, and finance. The institutional changes that resulted had profound implications for the division of labour and the division of knowledge that characterised the early biotechnology industry.  The Smithian interpretation, which suggests that the division of labour precedes and shapes the division of knowledge through learning by doing, may be challenged in conditions of economic uncertainty. From this perspective, we argue that the division of knowledge can precede the division of labour, with organisations making deliberate decisions about the allocation of resources to core and non-core competences. The varied distribution of roles and institutions influenced the trajectories of early biotechnology start-ups. These trajectories manifested in two theoretical models, wherein differing emphases on scientific research and commercialisation coexisted to varying degrees, thereby influencing long-term profitability and growth.

Abstract: This paper offers a contribution to the literature on science policies and on the possible trade-off between broad science-technology policies and mission-oriented programs. We develop a multi-country, multi-sectoral agentbased model that represents a small-scale monetary union. Findings are threefold. Firstly, symmetric science policies from governments significantly reduce cross-country growth divergence. Secondly, even if economic growth is largely driven by the sectors with absolute advantages, having some flow of open science investments is sufficient for the other industries to survive and innovate. Thirdly, science policy limits monopolistic tendencies and reduces income inequality. Yet, the working of the model suggests that supply-side science policies should be paired with demand-side policies to meet grand societal challenges. 

Abstract: This paper contributes to the understanding of the relationship between the nature of data and the artificial intelligence (AI) technological trajectories, on the one hand, and on the dynamic processes triggered by demand during the evolution of an industry, on the other hand. We develop an agent-based model in which firms are data producers that compete on the markets for data and AI. The model is enriched by a public sector that fuels the purchase of data and trains the scientists that will populate firms as workforce. Through several simulation experiments, we analyze the determinants of each market structure, the corresponding relationships with innovation attainments, the pattern followed by labor and data productivity, the quality of data traded in the economy, and in which forms demand does affect innovation and the dynamics of industries. We question the established view in the literature of industrial organization according to which technological imperatives are enough to experience divergent industrial dynamics on both the markets for data and AI blueprints. Although technical change behooves if any industry pattern is to emerge, the actual unfolding is not the outcome of a specific technological trajectory, but the result of the interplay between technology-related factors and the availability of data-complementary inputs such as labor and AI capital, the market size, preferences, and public policies. 

Abstract: This paper contributes to the literature around the Kaldor–Verdoorn law and analyses the impact of robotisation on the channels through which the law shapes labour-productivity growth. We start with a simple evolutionary reinterpretation of the law that combines Kaldorian and neo-Schumpeterian arguments. We then apply a GMM estimator to a panel of 17 industries in 25 OECD capitalist economies for the period 1990–2018. After elaborating on the general evidence of the evolutionary interpretation of the law, the estimates suggest a positive influence from robotisation: a higher robot density strengthens both the channel that ties labour productivity dynamics with mechanisation, and the one connected with the general advancement of science and technology which joins productivity to aggregate demand. This overall result is robust to several specifications of the underlying econometric model. Moreover, we find some evidence of technological unemployment out of the macroeconomic factor. Results agree with the empirical literature that suggests different impacts from robotisation on the basis of the level of economic activity considered. 

Abstract: This paper focusses on Secular Stagnation in the United States. It answers to two research questions. First: is Secular Stagnation a fact? Second: conditional to the previous reply, how does the literature meet the qualitative and quantitative evidence? I focus on historical annual data related to the USA from 1870 onwards. The contribution to the debate is manifold. Firstly, I provide a careful systematization of the concept and explain why this definition is crucial for the topic analysis. Secondly, I talk about Secular Stagnation in terms of labor and multifactor productivity growth: their decline since the 1970s is not comparable to any previous shortfall. Thirdly, the definition allows to evaluate whether present-day debates on the phenomenon are supported by data, but it also lets to disentangle the most relevant channels through which Secular Stagnation emerges. Therefore, I carry out a comparative validation exercise on the different lines of thought. Finally, as long as Secular Stagnation is confirmed as empirical evidence, also policy implications can be drawn from the different theoretical frameworks. Despite the several contrasting approaches and viewpoints, I trace out a complementary in policy implications. 

Abstract: This paper deals with the Secular Stagnation in productivity growth that marks the US economy since the end of the Golden Age. I contribute to the understanding of this phenomenon proposing a theoretical and empirical analysis. On the theoretical side, I develop an agent-based, stock-flow consistent model to investigate the deep relationship between functional income distribution and productivity through the channel of innovation. Findings suggest that the continuous shift of income from wages to profits may have resulted in a smaller incentive to invest on R&D, with the corresponding decline in productivity growth that characterizes US Secular Stagnation. In this respect, a social compromise between workers and capitalists in terms of higher wages helps foster innovation and economic growth, but it does not necessarily entail significant improvements in terms of income concentration, because of higher unemployment rates. Additionally, I question the neoclassical belief on the negative interest-elasticity of investments, since decreases in the rate of interest are not associated with increases in capital accumulation, but they decrease income inequality through higher employment rates. On the empirical side, this paper presents a panel cointegration analysis on US manufacturing industries for the period 1958–2011. If, on the one hand, the linkage between R&D and wages is corroborated, on the other hand, I find the lack of any long-run relationship between innovative search and the rate of interest, which does not necessarily conflict with theoretical predictions. 

Abstract: The dissertation analyzes the phenomenon of Secular Stagnation with respect to the United States and consists of three essays. In the first chapter I take a historical view to see which characteristics the literature associates with Secular Stagnation find support in the data. I focus on US macroeconomic data since 1870. The very simple setting allows me to grasp that it is apt to talk about Secular Stagnation in terms of productivity growth, since the decline is greater than any previous shortfall. Findings cast some doubt on Summers's hypothesis of negative natural rates and offer some evidence supporting Gordon's and Hein's stands. The second chapter starts by noticing as the debate on Secular Stagnation paid little attention to the profound interplay between income distribution, innovation, and productivity. I scrutinize US capitalistic evolution of last fifty years and inspect the way the distribution of income between wages and profits can determine the rate of innovative activity and then further attainments in productivity through an Agent-based SFC model. I advance the idea that the continuous shrinkage of the labour share may have resulted in a smaller incentive to invest in R&D activity, entailing the evident decline in productivity performances that marks US Secular Stagnation. In the third chapter, I extend the argument started with the second chapter and I also undertake an econometric analysis to test some predictions from the model to the empirical ground. I gather a panel of US manufacturing industries with data on total R&D expenditures, hourly wage rates, productivity levels and values of shipments from 1958 to 2011. I figure out that my series of interest are cointegrated, and I am then able to detect positive and long-lasting evidences, confirming the main theoretical results. 

Abstract: Si Nicholas Kaldor n’est pas un théoricien de l’innovation à proprement parler, ses travaux sur la croissance économique n’en sont pas pour autant moins notables pour l’étude de l’innovation, tant au niveau théorique que méthodologique. Ainsi, Kaldor est l’un des premiers à laisser une place croissante aux faits, à l’histoire et à une démarche inductive, démarche méthodologique étant depuis largement adoptée dans les travaux portant sur l’innovation. Du point de vue théorique, avec l’introduction de sa « fonction de progrès technique » dès la fin des années 1950 et le développement de sa théorie de la « croissance cumulative » à partir de la deuxième moitié des années 1960, Kaldor propose une approche où le changement technique, au-delà des seules innovations, n’est plus un facteur exogène et où la croissance est auto-entretenue. Les travaux de Kaldor mettent en lumière les mécanismes qui seront au cœur de la théorie de la croissance endogène, mais près d’un quart de siècle avant l’avènement de cette dernière. L’apport de Kaldor aux théories de la croissance est double, à la fois théorique et méthodologique. Le cheminement et la portée de son apport théorique sont intimement liés à l’originalité méthodologique de son approche. Les théoriciens de la croissance, contemporains de Kaldor comme Harrod, Hicks ou Solow, ont une démarche purement déductive. Leurs théories sont construites autours d’axiomes théoriques. Kaldor, dont les premiers travaux s’inscrivent dans cette même approche méthodologique, ouvre graduellement sa théorie de la croissance aux faits empiriques…