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Despite the growing interest in basic income (BI) in recent years, the existing research has mainly focused on its impact on household finances. However, changes in household behavior may affect the actions of other decision makers, such as businesses and governments, leading to unanticipated outcomes. Therefore, any analysis of BI must use a model with multilayered feedback from the actions of individual decision makers. To actualize such a model, household budgets, firms, and other entities must autonomously determine production levels, prices, and other factors, thereby encompassing a complete circulation of funds. This study constructs a macroeconomic model using agent-based modeling as a basic framework to achieve these goals, and it analyzes the emergent behaviors generated by BI and the labor supply in the economic system. The results show that although BI brings about more equitable consumption by households, it also creates a unique phenomenon wherein Gross Domestic Product increases but economic activity in terms of capital investment stagnates. Upon examining the impact of BI, the results of this study present the need to examine the multilayered feedback influencing mutual decision makers, which arises from the behavioral changes of individual decision makers caused by BI.

La economía artificial es uno de los métodos o enfoques de investigación para el estudio de sistemas socioeconómicos complejos con mayor crecimiento durante los últimos años. Este artículo presenta una visión crítica sobre sus características, su potencial y los riesgos relativos al uso de esta metodología. Para ello, encontramos útil relacionar y comparar a la economía artificial con la economía teórica más tradicional. Desde nuestro análisis, la economía teórica y la economía artificial comparten los mismos objetivos, presentan menos diferencias metodológicas de las que a primera vista pudiera parecer, y sus aproximaciones son sin duda complementarias. --- Artificial Economics is one of the fastest growing approaches to analyse complex socio-economic systems. In this paper we present our views on the distinguishing features of Artificial Economics and on its relation with Theoretical Economics — the field that in our opinion lies closest to Artificial Economics. In this context, we discuss various reasons why conducting research on Artificial Economics may be worthwhile, and provide general guidelines on how to go about it. Our view is that Artificial Economics and Theoretical Economics share the same goals, do not differ conceptually as much as it is sometimes perceived, and their approaches are certainly complementary.

To reach the “30·60” decarbonization target (where carbon emissions start declining in 2030 and reach net zero in 2060), China is restructuring its power system to a new energy-based one. Given this new situation, this paper reviews previous studies on the power market and highlights key issues for future research as we seek to adapt to the new power system (NPS). Based on a systematic literature review, papers on the operational efficiency of the power market, participants’ bidding strategies and market supervision were identified. In a further step, papers with high relevance were analyzed in more detail. Then, key studies that focused on market trading under China’s new power system were picked out for further discussion. New studies were searched for that pertained to new energy mechanisms and bidding, the transition from coal-fired power, flexible resources and the technical applications of simulations. The quantitative analysis supports the construction of a basic paradigm for the study of power markets that is suitable for the new power system. Finally, the theoretical basis and application suggestions for power market simulations are introduced. This study summarized the existing research on the power market and further explored the key issues relating to the power market as it adapts to the NPS, hoping to inspire better research into China’s power sector, and promote safe, low-carbon, and sustainable development in China’s power industry.

We study mechanisms leading to wealth condensation. As a natural starting point, our model adopts a neoclassical point of view, i.e., we completely ignore work, production, and productive relations, and focus only on bilateral link between two randomly selected agents. We propose a simple matching process with deterministic trading rules and random selection of trading agents. Furthermore, we also neglect the internal characteristic of traded goods and analyse only the relative wealth changes of each agent. This is often the case in financial markets, where a traded good is money itself in various forms and various maturities. We assume that agents trade according to the rules of utility and decision theories. Agents possess incomplete knowledge about market conditions, but the market is in equilibrium. We show that these relatively frugal assumptions naturally lead to a wealth condensation. Moreover, we discuss the role of wealth redistribution in such a model.

Credibly representing category-of-goods mental accounting in an intertemporal optimisation framework is notoriously difficult, as this modelling approach imposes interrelations between the demand for different categories through first-order conditions. This breaks the principle of nonfungibility, contrary to the rationale of mental-accounting theory. Proofs that using intertemporal optimisation is futile in modelling this kind of behaviour are provided, and an alternative is developed: a procedural-behavioural merger of mental accounting and categorisation theories. The merger is necessary to enhance mental-accounting theory, which by itself does not inform about how mental budgets are formed, what they include and how money is spent from various accounts. A classification of six basic consumer types was devised, basing on the differences between their mental-accounting systems and variations of changes of expenditure in response to fluctuations of net disposable income and other possible stimuli. Representing the consumer problem as a behavioural procedure including spending on nondurable and frequently-bought durable goods as well as decisions whether or not to purchase very expensive durable goods, such as houses and flats, allows to model real-world features such as infrequent purchases and rare debt-taking. The devised working-life cycle models of consumer behaviour are consistent with microeconomic evidence on consumption, including those features that are not accounted for by various versions of the permanent income or buffer-stock models.

This paper addresses the methodological problems of empirical validation in agent-based (AB) models in economics and how these are currently being tackled. We first identify a set of issues that are common to all modelers engaged in empirical validation. We then propose a novel taxonomy, which captures the relevant dimensions along which AB economics models differ. We argue that these dimensions affect the way in which empirical validation is carried out by AB modelers and we critically discuss the main alternative approaches to empirical validation being developed in AB economics. We conclude by focusing on a set of (as yet) unresolved issues for empirical validation that require future research. [PUBLICATION ABSTRACT]

The recent financial crises pointed out the central role of public and private debt in modern economies. However, even if debt is a recurring topic in discussions about the current economic situation, economic modeling does not take into account debt as one of the crucial determinants of economic dynamics. The authors' contribution, in this paper, is to investigate the issues of borrowing and debt load by means of computational experiments, performed in the environment of the agent-based Eurace simulator. The authors aim to shed some light on the relation between debt and main economic indicators. Their results clearly confirm that the amount of credit in the economy is a very important variable, which can affect economic performance in a twofold way: fostering growth or pushing the economy into recession or crisis. The outcomes of their computational experiments show a rich scenario of interactions between real and financial variables in the economy, and therefore represent a truly innovative tool for the study of economics.

We focus on the complementarity between original institutional economics, Mario Bunge's framework of systemism, and the formal tools developed by complexity economists, especially in the context of agent-based modeling. We assert that original institutional economics might profit from exploiting this complementarity.

This paper introduces an agent-based computational economic modeling approach into an input–output analytical framework and proposes diffusion of technological innovation behavior into the simulation models. A large number of heterogeneous firms with macro-regional economic frameworks are included to perform policy simulation scenarios to investigate the impact of diffusing technological innovations on the dynamic changes in the regional economic structures of major global economies (i.e., China, Japan, the United States, Russia, India, and the European Union). This study reveals that process innovation may be more conducive to promoting the transfer of resource elements between regions for China, the EU, Japan, India, and Russia. However, for the U.S., product innovation may facilitate upgrading its industrial structure. Furthermore, from 2012 to 2030, for these six economies, the output share of the primary industry will likely decline by varying degrees, while the output share of the tertiary industry will show an uptrend. The employment share in the tertiary industry in these six economies decreased. Another important finding is that differentiated technological innovation-driven policies must be adopted within the context of global economic governance. Moreover, each economy should choose a technological innovation mode that is suitable for its economic development. Thus, these findings provide an important theoretical basis for formulating global economic governance policies in the future.

This paper investigates the interplay between monetary aggregates and the dynamics and variability of output and prices by considering both the money supplied by commercial banks as credit to firms and the fiat money created by the central bank through the quantitative easing monetary policy. The authors address this problem by means of an agent-based model and simulator, called Eurace, which is characterized by a complete set of interrelated markets and different types of interacting agents, modeled according to a rigorous balance-sheet approach. The dynamics of credit money is endogenous and depends on the supply of credit from the banking system, which is constrained by its equity base, and the demand of credit from firms in order to finance their production activity. Alternative dynamic paths for credit money have been produced by setting different firms' dividend policies. Results point out the strict dependence of output and prices dynamics on monetary aggregates, and show the emergence of endogenous business cycles which are mainly due to the interplay between the real economic activity and its financing through the credit market. In particular, the amplitude of the business cycles strongly rises when the fraction of earnings paid out by firms as dividends is higher, that is when firms are more constrained to borrow credit money to fund their activity. This interesting evidence can be explained by the fact that the level of firms leverage, defined as the debt-equity ratio, can be considered ad a proxy of the likelihood of bankruptcy, an event which causes mass layoffs and supply decrease.