Back to the past: the historical roots of labor-saving automation

AbstractThis paper, relying on a still relatively unexplored long-term dataset on U.S. patenting activity, provides empirical evidence on the history of labor-saving innovations back to early nineteenth century. The identification of mechanization/automation heuristics, retrieved via textual content analysis on current robotic technologies by Montobbio et al. (Robots and the origin of their labour-saving impact, LEM Working Paper Series 2020/03), allows to focus on a limited set of CPC codes where mechanization and automation technologies are more prevalent. We track their time evolution, clustering, eventual emergence of wavy behavior, and their comovements with long-term GDP growth. Our results challenge both the general-purpose technology approach and the strict 50-year Kondratiev cycle, while they provide evidence of the emergence of erratic constellations of heterogeneous technological artefacts, in line with the development-block approach enabled by autocatalytic systems

Bubble-and-bust dynamics under walrasian asset pricing and heterogeneous traders

Mainstream economic theory is hardly capable to explain some of the stylised facts that are normally observed in actual financial time series. Rather, phenomena like volatility clustering and excess comovement of prices have been successfully investigated in frameworks featuring heterogeneous agents and bounded rationality. Our model inherits some of the assumptions common to the Heterogeneous Agents stream of research, and develops an Agent-Based numerical simulation able to study the whole transitional price dynamics of the risky security, and the evolution of portfolio choices and wealth distribution among the traders. Adopting this methodology, we are able to show the emergence of transient bubble-and-bust dynamics, intended as sharp decoupling of the asset price from underlying fundamentals, and to replicate recent findings in financial literature about the asymptotic wealth dominance of the least-risk-averse trader, under quite general assumptions

Labour‐saving automation: A direct measure of occupational exposure

This article represents one of the first attempts at building a direct measure of occupational exposure to robotic labour-saving technologies. After identifying robotic and labour-saving robotic patents, the underlying 4-digit CPC (Cooperative Patent Classification) code definitions, together with O*NET (Occupational Information Network) task descriptions, are employed to detect functions and operations which are more directed to substituting the labour input and their exposure to labour-saving automation. This measure allows us to obtain fine-grained information on tasks and occupations according to their text similarity ranking. Occupational exposure by wage and employment dynamics in the United States is then studied, and complemented by investigating industry and geographical penetration rates

Trade unions’ responses to Industry 4.0 amid corporatism and resistance

The aim of this paper is to shed light on the paths, directions, and ensuing degrees of technological adoption fostered by trade unions or, alternatively, forms of resistance thereof, in the so called ‘Italian Motor-Valley’, a distinctive technological district located in the outskirts of Bologna, Italy, specialised in the engineering and automotive industry. We find that the introduction of Industry 4.0 technology opens up a new space of action for trade unions in influencing firms’ decisions on technological adoption. However, this new scope can have ambiguous effects, depending on how the process is governed. On the one hand, trade unions’ involvement in said decisions might end up fostering corporatist tendencies, favouring the alignment of workers’ and managers’ objectives. On the other hand, such a major involvement can help both recomposing old forms of dualism and revitalising workers’ role in the crucial issue of work organisation

An agent-based model of intra-day financialmarkets dynamics

We build an agent-based model of a financial market that is able to jointly reproduce many of the stylized facts at different time-scales. These include properties related to returns (leptokurtosis, absence of linear autocorrelation, volatility clustering), trading volumes (volume clustering, correlation between volume and volatility), and timing of trades (number of price changes, autocorrelation of durations between subsequent trades, heavy tail in their distribution, order-side clustering). With respect to previous contributions we introduce a strict event scheduling borrowed from the EURONEXT exchange, and an endogenous rule for traders participation. We show that such a rule is crucial to match stylized facts

The present, past, and future of labor-saving technologies

The present chapter provides a historical reappraisal of labor-saving technologies. It reviews and systematizes theoretical contributions and empirical findings documenting the presence of labor- and time-saving heuristics in innovative efforts back since the First Industrial Revolution. More in detail, with the help of various patent analyses, the chapter documents the presence of labor-saving heuristics in the latest wave of technological innovation, detecting the human functions substituted by the underlying technologies. Against a reductionist approach conceiving robots as the only threat for labor displacement, it shall be argued that labor-saving technologies consist of a complex and heterogeneous bundle of innovations uncovering a much wider set of artifacts and functions. Motivated by the recurrent debate on the threats of automation occurring in the last couple of centuries, evidence is provided on the existence of long waves and clusters in relevant innovations, discussing how the overall cluster of labor-saving technologies consists of heterogeneous and often independent innovations following remarkably different time-trajectories. The chapter closes with an outline of potential future trends in labor-saving technologies and room for policy actions

Robots, AI, and related technologies: A mapping of the new knowledge base

Using the entire population of USPTO patent applications published between 2002 and 2019, and leveraging on both patent classification and semantic analysis, this papers aims to map the current knowledge base centred on robotics and AI technologies. These technologies will be investigated both as a whole and distinguishing core and related innovations, along a 4-level core-periphery architecture. Merging patent applications with the Orbis IP firm-level database will allow us to put forward a threefold analysis based on industry of activity, geographic location, and firm productivity. In a nutshell, results show that: (i) rather than representing a technological revolution, the new knowledge base is strictly linked to the previous technological paradigm; (ii) the new knowledge base is characterised by a considerable - but not impressively widespread - degree of pervasiveness; (iii) robotics and AI are strictly related, converging (particularly among the related technologies) and jointly shaping a new knowledge base that should be considered as a whole, rather than consisting of two separate GPTs; (iv) the U.S. technological leadership turns out to be confirmed