Journal of Evolutionary Economics最新文献

This paper proposes an empirical test to identify possible endogenous cycles within heterogeneous agent models (HAMs). We consider a two-type HAM into a standard small-scale dynamic asset pricing framework. Fundamentalists base their expectations on the fundamental value, while chartists consider the level of past prices. Because these strategies, by their nature, cannot be directly observed but can cause the response of the observed data, we construct a state-space model where agents’ beliefs are considered the unobserved state components and from which the heterogeneity of fundamentalist-chartist trader cycles can be mathematically derived and empirically tested. The model is estimated using the S&P500 index for the period 1990–2020 at different time scales, specifically, quarterly, monthly, and daily. We find empirical evidence of endogenous damped fluctuations with a higher probability of chartist behavior in the short-term horizon. In addition, the model exhibits better long-run out-of-sample forecasting accuracy compared to the benchmark random walk model.

This paper discussed how green technological domains are inserted into the Brazilian knowledge space. We investigated whether the insertion of technologies into the Brazilian knowledge space is affected by the fact that these technologies are green or non-green, the potential moderating effect of the industry knowledge bases with which technologies are associated, and the differences regarding the insertion of green and non-green technology domains across industries. We considered Brazilian patent and industry data from 1997 to 2020 and a multilevel analysis to answer these questions. Our results indicated that green technological domains are intensely combined with other domains, but their structural embeddedness is still low. The characteristics of sectoral knowledge bases influenced the insertion of green technologies into the national knowledge space since these technologies are more deeply embedded in the knowledge space when associated with less mature knowledge bases.

For several decades, OECD countries have been experiencing a shift towards services, on the one hand, and, on the other hand, they are still emitting large amounts of greenhouse gas emissions. To tackle greenhouse gas emissions, policymakers often design appropriate strategies to promote investment and innovation in renewable energy sources. However, some important drivers of renewable energy (especially environmental regulations and environmental innovation) are much less common in the services sector than in other sectors (especially manufacturing). Based on this fact, this article aims to examine how services affect renewable energy deployment in OECD countries. Our analysis of the implementation of both environmental regulations and environmental innovation in services suggests that the shift towards services may dampen renewable energy deployment. Additionally, we employ the generalized quantile regression (GQR) estimator on panel data from OECD countries over the period 1991–2018 to investigate the relationship between the shift towards services and renewable energy consumption. The results reveal that the shift towards services tends to negatively affect renewable energy deployment in OECD countries. More precisely, the findings show that the share of services in the economy has a negative and significant impact on renewable energy consumption per capita in OECD countries. On the basis of these findings, policy implications are drawn.

The challenge of pursuing sustainable development highlights the relevance of the complex mechanisms through which natural and social selection processes affect and are affected by the economic system. Current economic development is unsustainable because it fails to generate long-term systemic compatibility between firms and their natural and social environment. This paper evaluates the issue from an evolutionary perspective by conceptualising unsustainability as the emergence of negative macro-selection effects, arising from both the natural and social domains, and argues for a methodological need for closer integration of system dynamics modelling within the evolutionary field. The Earth4All model is then used to illustrate the complex interactions between economic, social, and natural selection processes. The model results illustrate that the current global development trajectory is strongly unsustainable from both a natural and a social perspective, leading to the emergence of relevant natural and social macro-selection mechanisms, whose systemic interactions bring further complex adverse effects.

An economic interpretation of Epictetus’s precept of ‘Taking away aversion from all things not in our power’ consists of extending the symmetric factor of the preference relation beyond its boundaries under non-ethical preferences, so as to yield indifference between outcomes differing only on things outside one’s control. This paper examines the evolutionary dynamics of a population composed of Nash agents and Epictetusian agents matched randomly and interacting in the prisoner’s dilemma game. It is shown that when the evolutionary dynamics is driven by material pay-offs, the Nash type is an ESS under perfect random matching, whereas either the Nash or the Epictetusian type can be an ESS under imperfect random matching. However, when selection is driven by utility pay-offs, the Nash type can never be an ESS, and the Epictetusian type is an ESS if the matching process exhibits a sufficiently high degree of assortativity.

Artificial intelligence (AI) is anticipated to reshape the economy by revolutionizing human interaction with technology. Despite its significance, research endeavors in the field of economics remain relatively limited. In this editorial, we outline the articles featured in a Virtual Special Issue designed to expand the scope of inquiry for economists examining AI and its implications. We position these articles within the current economic literature and propose an agenda for further research aimed at fostering a more varied understanding of the impacts, implications, and challenges of AI technologies at the intersection with economic activity.

The purpose of this work is to study the joint interaction of three founding elements of modern capitalism, namely endogenous technical change, income distribution, and labor markets, within a low-dimensional nonlinear dynamic setup extending the Goodwin model. Going beyond the conservative structure typical of the predator–prey model, we insert an endogenous source of energy, namely a Kaldor–Verdoorn (KV) increasing returns specification, that feeds the dynamics of the system over the long run and in that incorporates a transition to an (anti)-dissipative framework. The qualitatively dynamics and ample array of topological structures reflect a wide range of Kaldorian stylized facts, as steady productivity growth and constant shares of income distribution. The intensity of learning regimes and wage sensitivity to unemployment allow to mimic some typical traits of both Competitive and Fordist regimes of accumulation, showing the relevance of the demand-side engine, represented by the KV law, within an overall supply-side framework. High degrees of learning regimes stabilize the system and bring it out of an oscillatory trap. Even under regimes characterized by low degrees of learning, wage rigidity is able to stabilize the business cycle fluctuations and exert a positive effect on productivity growth.

This book briefly outlines the project of a future economic system in which energy is predominantly derived from the sun and from hydrogen. Hydrogen is generated by the electrolysis of water, the energy for which comes from the sun. Hydrogen is then combined with oxygen to produce energy and water. The solar hydrogen economy is then a circular economy which, according to the author, can generate unlimited amounts of energy in a sustainable way. It is quite likely that the solar hydrogen economy will be an important component of a sustainable economic system. The book, although quite synthetic, is written with clarity and passion, perhaps underestimating the barriers to the construction of such an economic system and the presence of possible alternatives. However, it provides a quick introduction to a subject the importance of which is likely to grow considerably in the near future.

Many social scientists still resist Darwinian insights. A possible reason for this is a fear of being associated with Social Darwinism. This article updates a 2002 search for appearances of Social Darwinism in articles and reviews on the JSTOR database. This database has since increased substantially in size, and it now includes far more publications in languages other than English. Use of the term Social Darwinism was rare before the 1940s. Talcott Parsons used it in 1932 to criticise the analytic use of the core Darwinian concepts in social science. Subsequently, and for the first time, Herbert Spencer and Willam Graham Sumner were described as Social Darwinists. This led to a major change of meaning of the term, where it was associated more, but not entirely, with free market individualism. With this reconstructed meaning, a 1944 bestselling book by Richard Hofstadter provoked an explosion of usage of the term in postwar years. The continuing use of the term is partly ideologically motivated and has served to deter consideration of Darwinian ideas in social science.

The characteristics of the financial arrangements established to finance startups affect the fate of startups. Among these features, we particularly focus on the proximities and differences between venture capital (VC) investors in syndicated investments. We consider the proximities between investors in a startup and between investors and the startup. Against the background of the theoretical literature dealing with proximity relations, we distinguish five types of proximities between VC investors and between VC investors and the startups they finance: geographic, institutional, organizational, social, and cognitive. We then test six hypotheses regarding the impacts of these proximities on the likelihood of three events occurring in VC-backed startups: obtaining a later-stage round of funding, going public, and being merged or acquired. We implement these tests on a 33-year-long, 68-country sample using survival models adapted to account for tied failures and competing events. We find that the five forms of proximity relations are influential but have distinct roles. We also find that the impacts of these proximities are nonlinear in the sense that too much proximity/distance always ends up reverting the effects of proximity/distance. Finally, we observe that as the theoretical literature predicts, cognitive proximity is positively correlated with the probability of a merger and acquisition (M&A) but negatively correlated with the likelihood of an initial public offering (IPO).