In the context of the Covid-19 pandemic, we evaluate the effects of vaccines and virus variants on epidemiological and macroeconomic outcomes by means of Monte Carlo simulations of a macroeconomic-epidemiological agent-based model calibrated using data from the Lombardy region of Italy. From simulations we infer that vaccination plays the role of a , reducing the frequency and the amplitude of contagion waves and significantly improving macroeconomic performance with respect to a scenario without vaccination. The emergence of a variant, on the other hand, plays the role of an , leading to a deterioration of both epidemiological and macroeconomic outcomes and partly negating the beneficial impacts of the vaccine. A new and improved vaccine in turn can redress the situation. Vaccinations and variants, therefore, can be conceived of as drivers of an intertwined cycle impacting both epidemiological and macroeconomic developments.

This work correlates the impact of robotization on employment and households' income at the regional scale with the level of investment in R&D and education policies. This kind of policy, by raising the qualitative and quantitative levels of human capital, contributes to improving the complementarity effect between humans and robots, thus mitigating the substitution effect. To this end, we compute the Adjusted Penetration of Robots (APR) (a metric used to measure the extent to which robots are being used in a particular industry or sector) at the sectoral level, combining the International Federation of Robotics database for the stock of robots, EUROSTAT Regional database, and the STructural ANalysis database on 150 NUTS-2 regions of the Euro area. We then perform a spatial stacked-panel analysis on the investment in R&D and education level. Results supports the idea that regions that invest more in R&D and have higher levels of human capital can turn the risk of robotization into an increase in both income and "quantity of work," by enhancing complementarity between robots and the labor force. On the contrary, regions investing less in R&D and having lower levels of human capital may suffer a reduction in households' disposable income.

The causes of the 2007-8 subprime crisis continue to be the subject of much debate, with explanations ranging from de-regulation and fraudulent behavior to global imbalances and rising inequality. However, a comprehensive analysis of the endogenous forces that made the crisis inevitable has yet to be presented. This paper offers a 'structural' interpretation of the crisis by synthesising insights from conventional financial economics and the Minskyian and Schumpeterian literature. While highlighting the innovative character of US financial firms evolving from credit providers to of financial commodities, we stress the key features of their path towards financial fragility.  We contend that financial institutions were able to achieve progressively unsustainable positions due to the 'enforced indebtedness' of US households, which played a functional, albeit secondary, role in the development of the crisis.

AI is transforming labor markets around the world. Existing research has focused on advanced economies but has neglected developing economies. Different impacts of AI on labor markets in different countries arise not only from heterogeneous occupational structures, but also from the fact that occupations vary across countries in their composition of tasks. We propose a new methodology to translate existing measures of AI impacts that were developed for the US to countries at various levels of economic development. Our method assesses semantic similarities between textual descriptions of work activities in the US and workers' skills elicited in surveys for other countries. We implement the approach using the measure of suitability of work activities for machine learning provided by Brynjolfsson et al. (Am Econ Assoc Pap Proc 108:43-47, 2018) for the US and the World Bank's STEP survey for Lao PDR and Viet Nam. Our approach allows characterizing the extent to which workers and occupations in a given country are subject to destructive digitalization, which puts workers at risk of being displaced, in contrast to transformative digitalization, which tends to benefit workers. We find that workers in urban Viet Nam, in comparison to Lao PDR, are more concentrated in occupations affected by AI, which requires them to adapt or puts them at risk of being partially displaced. Our method based on semantic textual similarities using SBERT is advantageous compared to approaches transferring AI impact scores across countries using crosswalks of occupational codes.

We study the evolutionary selection of conjectures in duopoly games when players have other regarding preferences, i.e. preferences over payoff distributions. In both the Cournot and Bertrand duopoly games, the consistent conjectures are independent of other regarding preferences. Both duopoly games have evolutionarily stable conjectures that depend on other regarding preferences but that do not coincide with the consistent conjectures. For increasingly spiteful preferences, the evolutionarily stable conjectures implicate low quantities in the Cournot game and high prices in the Bertrand game, whereas the inverse relationships hold for the consistent conjectures. We discuss our findings in the context of ultimate and proximate causation.

The emergence of profit-based online platforms related to the Sharing Economy, such as BlaBlaCar and Airbnb, provides new means for end users to create an income from their possessions. With this opportunity, participants have to make strategic economic decisions despite limited formal expertise and information. Decentralization (using digital technologies) and reputation (using user reviews) are the core mechanisms chosen by these platforms to mitigate these limitations and to work efficiently as online matchmakers. We test the performance of these two mechanisms by studying the allocative efficiency (in terms of value and volume of transactions) of simulated marketplaces under different types of motivation from the participants and control from the platforms. As a result, we find an inverted-U relationship between the decision-making leeway available to the participants and the platform's allocative efficiency. From the participants' perspectives, too much freedom or too many barriers lead to market failures affecting specific participants: low-end consumers are banned from the marketplace while high-end providers experience lower levels of activity. As governance advice for these platforms, we show the limitations of promoting these platforms on the sole motive of monetary rewards.

This article conceptualizes innovation as a process, where the scientific and industrial application of technological knowledge nurtures new routines and institutions, in order to relate changing business model innovations to innovation cascades. Innovation in science-based, high-tech sectors is changing its tempo, from the evolutionary pace of incremental novelties punctuated by occasional radical novelties, to innovation cascades. These cascades involve a long series of interlinked radical innovations, which can be traced through various scientific and technological indicators like patents and publications. Innovation cascades are relevant to industry, because they make the future less predictable. They are particularly interesting because these changes also enable the testing an abundance of new business models. Innovation cascades have a major impact on the number and sustainability of business models and on strategy. Business model innovations are visible not only in the existing organizations that undergo change, but also new organizational models appear. The case of biotechnology after the 1980s is used to illustrate our conceptualization.

In this article, we develop a new way to capture knowledge diffusion and assimilation in innovation networks by means of an agent-based simulation model. The model incorporates three essential characteristics of knowledge that have not been covered entirely by previous diffusion models: the network character of knowledge, compatibility of new knowledge with already existing knowledge, and the fact that transmission of knowledge requires some form of attention. We employ a network-of- networks approach, where agents are located within an innovation network and each agent itself contains another network composed of knowledge units (KUs). Since social learning is a path-dependent process, in our model, KUs are exchanged among agents and integrated into their respective knowledge networks depending on the received KUs' compatibility with the currently focused ones. Thereby, we are also able to endogenize attributes such as absorptive capacity that have been treated as an exogenous parameter in some of the previous diffusion models. We use our model to simulate and analyze various scenarios, including cases for different degrees of knowledge diversity and cognitive distance among agents as well as knowledge exploitation vs. exploration strategies. Here, the model is able to distinguish between two levels of knowledge diversity: heterogeneity within and between agents. Additionally, our simulation results give fresh impetus to debates about the interplay of innovation network structure and knowledge diffusion. In summary, our article proposes a novel way of modeling knowledge diffusion, thereby contributing to an advancement of the economics of innovation and knowledge.

This study builds on the economics and organization literatures to explore whether and how institutions and organizational structure complement or substitute each other to create specific spaces of alignment where specific individual actors' motivations co-exist. Focusing on university-industry collaborations, the study examines whether and how different axes of alignment of university and industry motivations are integrated in projects with specific technological objectives and organizational structures, benefitting from the presence of specific institutions designed to facilitate collaboration. Empirically, the study relies on in-depth data on 30 university-industry collaborations in the Netherlands, and provides preliminary evidence that the technological objective and organizational structure of collaboration are malleable variables allowing the integration of both partners' objectives and expectations. Different institutional incentives for university-industry collaboration favor specific axes of alignment of motivations and certain types of collaborative projects' design. Hence, our exploratory results suggest that specific organizational and technological structures tend to prevail in the presence of specific institutions.

In order to understand heterogeneous behavior amongst agents, empirical data from Learning-to-Forecast (LtF) experiments can be used to construct learning models. This paper follows up on Assenza et al. (2013) by using a Genetic Algorithms (GA) model to replicate the results from their LtF experiment. In this GA model, individuals optimize an adaptive, a trend following and an anchor coefficient in a population of general prediction heuristics. We replicate experimental treatments in a New-Keynesian environment with increasing complexity and use Monte Carlo simulations to investigate how well the model explains the experimental data. We find that the evolutionary learning model is able to replicate the three different types of behavior, i.e. convergence to steady state, stable oscillations and dampened oscillations in the treatments using one GA model. Heterogeneous behavior can thus be explained by an adaptive, anchor and trend extrapolating component and the GA model can be used to explain heterogeneous behavior in LtF experiments with different types of complexity.

Low inflation was once welcomed by both policymakers and the public. However, Japan's experience during the 1990s changed the consensus of economists and central banks around the world regarding prices. Facing deflation and the zero-interest bound at the same time, the Bank of Japan had difficulty conducting an effective monetary policy, making Japan's stagnation unusually prolonged. The too-low inflation that concerns central banks today translates into the "Phillips curve puzzle." In the United States and Japan, in the course of the recovery from the Great Recession after the 2008 Global Financial Crisis, the unemployment rate had steadily declined to a level commonly regarded as lower than the natural rate or NAIRU. However, inflation remained low. In this paper, we consider a minimal model of the dual labor market to jointly investigate how the different factors affecting the structural evolution of the labor market have contributed to the observed flattening of the Phillips curve. We find that the level of bargaining power of workers, elasticity of the supply of labor to wage in the secondary market, and composition of the workforce are the main factors jointly explaining the evidence for Japan.

This paper aims to investigate the relationship between external imbalances and poverty in the Eurozone. The former are registered through the Target2 (T2) settlement mechanism and can be assimilated into changes in official reserves to cover the balance of payments disequilibrium in a fixed exchange rate regime. The presence of T2 discrepancies has led to differences in interest rates and increased distances in general living conditions inside the Eurozone. An empirical investigation implemented in 11 Eurozone countries reveals that T2 is negatively correlated with poverty, therefore allowing for an interpretation that approximates balance of payment crisis models. Results that appear to be robust to several control variables suggest that the policy framework of the Eurozone-in the absence of a compensatory mechanism-should be revised towards centralised fiscal instruments and anti-speculative monetary interventions.

This paper analyses medium-term labour market trends from 1983 to 2018 in Italy relying on the "Rilevazione dei contratti di lavoro" from INPS archive which provides information on average salaries by professional category, age, gender, and geographical origin. Within an overall pattern of exacerbated wage inequalities, documented by means of different indicators, the empirical analysis highlights how the -component of the wage variation prevails in the gender, age and geographical dimensions. By contrast, the component in terms of professional categories (trainees, blue-collar jobs, white-collar jobs, middle managers, executives) is the only between-variation attribute to prevail, corroborating the role played by a reduced class schema, excluding capitalists and the self-employed, in explaining wage inequality. Regression-based inequality estimations confirm the role played by managerial remuneration, the contradictory located class, in driving divergent patterns. Stratification of wage losses is recorded to be largely concentrated among blue-collar professional categories, women, youth, and in Southern regions.

The paper investigates the cognitive determinants of routinization and creativity by means of a lab-in-the-field experiment run at the 20th edition of a mass gathering festival in Italy ("La Notte della Taranta"). Subjects play repeatedly the puzzle version of the Target-The-Two game (32 hands). In hands 1-16, the strategy that is optimal given the card distribution is always the same and it is the easiest to be discovered. Conversely, in hands 17-32, subjects are exposed to games where the optimal contextual strategy may differ from the one with which they have been made familiar. We investigate whether and how, in hands 17-32, subjects remain routinized on the familiar strategy, or creatively choose a different one. We define as "experts" those subjects who played the optimal contextual strategy in the overwhelming majority of hands 1-16. In hands 17-32, we find several subjects playing the familiar strategy even when it is not the optimal one, regardless of whether they are experts or not. This shows that routinization is deep-rooted in the cognitive individual process. Furthermore, routinization pays off only for inexpert subjects: creative inexpert subjects are slower and they fail to find the optimal contextual strategy in several hands. Among expert subjects instead, creative subjects, although still slower, need less moves than routinized ones to find the optimal contextual strategy.

The literature on employee spinoffs has, for a long time, stressed the importance of industry-specific skills and experiences in explaining the success of new firms. We argue that employees also develop skills that are associated with their occupation within an industry, and that success as an entrepreneur, therefore, is also contingent on the relation between the entrepreneurs' previous occupation and the industry in which they operate as self-employed. Using matched employer-employee data, we develop a measure, occupational spin-offs, that accounts for this relation. An occupational spin-off is defined as a start-up in the most common industry, given the previous occupation of the founder. We then show that entrepreneurs starting occupational spinoffs enjoy above average income from self-employment and have longer spells as business owners.

The theory of firm growth is in a rather unsatisfactory state. However, the analysis of large firm-level datasets which have become available in recent years allows us to begin building an evidence base which can, in turn, be used to underpin the development of more satisfactory theory. Here we study the 239 thousand UK private sector firms born in 1998 over their first 15 years of life. A first, and quite striking, finding is the extraordinary force of mortality. By age 15, 90% of the UK firms born in 1998 are dead, and, for those surviving to age 15, the hazard of death is still about 10% a year. The chance of death is related to the size and growth of firms in an interesting way. Whilst the hazard rate after 15 years is largely independent of size at birth, it is strongly affected by the current (age 14) size. In particular, firms with more than five employees are half as likely to die in the next year as firms with less than five employees. A second important finding is that most firms, even those which survive to age 15, do not grow very much. By age 15 more than half the 26,000 survivors still have less than five jobs. In other words, the growth paths - what we call the 'growth trajectories' - of most of the 26,000 survivors are pretty flat. However, of the firms that do grow, firms born smaller grow faster than those born larger. Another striking finding is that growth is heavily concentrated in the first five years. Whilst growth does continue, even up to age 15, each year after age five it involves only a relatively small proportion of firms. Finally, there are two groups of survivors which contribute importantly to job creation. Some are those born relatively large (with more than 20 jobs) although their growth rate is quite modest. More striking though, is a very small group of firms born very small with less than five jobs (about 5% of all survivors) which contribute a substantial proportion (more than one third) of the jobs added to the cohort total by age 15.

This paper studiesthe relevance of productheterogeneity and relatedness for the accumulation ofcapabilities in firms, as well as their implications for innovation dynamics. The existing literature has produced extensive evidence on the relevance of capability accumulation for innovation processes. Yet, an assessment of prior attempts to model these processes indicates that when it comes to the final consumption good sector, the evolutionary macroeconomic literature has focused on process rather than product innovation. To facilitate the consideration of empirical and microeconomic insights on product innovation in these models, this paper introduces a simple agent-based model, which may later serve as an innovation module in macroeconomic models. In the model, firms accumulate capabilities to produce final consumption goods that are heterogeneous in terms of their complexity and differ in their relatedness to each other. The model is used to study theoretical implications of different topological structures underlying product relatedness by conducting simulations with different 'product spaces'. The analysis suggests that the topological structure of the product space, the assumed relationship between product complexity and centrality, as well as the relevance of product complexity in price setting dynamics have significant but nontrivial implications and deserve further attention in evolutionary macroeconomics.

The notion of development blocks (Dahmén, 1950, 1991) suggests the co-evolution of technologies and industries through complementarities and the overcoming of imbalances. This study proposes and applies a methodology to analyse development blocks empirically. To assess the extent and character of innovational interdependencies between industries the study combines analysis of innovation biographies and statistical network analysis. This is made possible by using data from a newly constructed innovation output database for Sweden. The study finds ten communities of closely related industries in which innovation activity has been prompted by the emergence of technological imbalances or by the exploitation of new technological opportunities. The communities found in the Swedish network of innovation are shown to be stable over time and often characterized by strong user-supplier interdependencies. These findings serve to stress how historical imbalances and opportunities are key to understanding the dynamics of the long-run development of industries and new technologies.

In this paper the evolution of consumption is explained on the basis of a theory that connects preferences over actions to the motivational forces driving actions. More specifically, the hypotheses about what motivates consumption activities draw on insights from biology, behavioral science, and psychology. With secularly rising income, the growing consumption opportunities and the expanding consumption alter the underlying motivational forces and induce a change of preferences. As a consequence, the structure of consumption expenditures is systematically transformed. In the light of this explanation, the paper analyzes the effects of the growth and transformation of consumption on individual welfare. As turns out, the motivations driving the growth of consumption do not necessarily imply that this growth indeed results in welfare increases, particularly when the ability to spend on consumption is already high. Moreover, when preferences change, the measurement of the welfare effects of the growth and transformation of consumption depends on the arbitrary choice of a reference point. This implies an ambiguity that raises further queries about the normative foundations of the ubiquitous calls for continued consumption growth.

In recent years, a debate on the technological sources of the next long wave of growth has emerged. In this context, some authors consider that health-related industries will be more likely to generate new technological systems than defense-related industries, which have entered a stage of technological maturity (Ruttan 2006; Steinbock 2014; among others). Based on evolutionary works, in this paper we state that technological systems are characterized by a high degree of technological relatedness, which is positively associated with the possibility of a system to generate variety through the recombination of knowledge from a common base. Following this statement, this work aims to analyze technological relatedness between defense (and health) technological system(s) and other groups of products to compare their variety patterns. Based on international trade data (a panel for 60 countries and 17 years), and different measures of proximity and relatedness (e.g. sectoral competitiveness of countries), we compare defense and health technological systems regarding their potential of generating related variety through two main methods: network analysis and econometrical analysis. The main results support Ruttan's hypothesis. The network analysis shows the potential for both systems to generate related variety, but higher centrality indicators for health products. In line with that, competitiveness in health products presents a stronger correlation with competitiveness in other groups of products, both related and high and medium technology. This suggests that an improvement in countries' competitiveness in health sectors can generate spillovers on other related sectors, which can strengthen structural competitiveness and sustain long-term growth.