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This study aims to provide a manageable symmetric two-players conflict model in which, defining measures for polarization and hostility, we investigate the effects of spillovers into the properties of the sets of equilibria, into the intensity of conflict, and into the endogenous changes in polarization and hostility. We show that, without spillovers, the equilibrium efforts’ intensity is uniquely connected to the ratio of the marginal productivity of effort to (ex ante) polarization. Conversely, we show that negative spillovers in conflict technology can imply the non-existence of equilibria. Then, introducing spillovers in the possible outcomes of the conflict, we connect the existence of multiple symmetric and asymmetric equilibria to the intensity of growing polarization and hostility. We then investigate the different effects of marginal productivity of effort, (ex ante) polarization and rates of growth of polarization and hostility on the intensity of conflict as well as on polarization and hostility at equilibrium. The results show the crucial role played by hostility, a factor disregarded in many conflict models. Finally, we show how the results obtained by considering partial spillover effects are confirmed when the general case is taken into account.

We propose a model with economic and environmental domains that interact with each other. The economic sphere is described by a Solow growth model, in which productivity is not exogenous but negatively affected by the stock of pollution that stems from the production process. A regulator can charge a tax on production, and the resources collected from taxation are used to reduce pollution. The resulting model consists of a two dimensional discrete dynamical system, and we study the role of taxation from both a static and a dynamical point of view. The focus is on the determination of the conditions under which taxation has a positive effect on the environment and leads to economic growth. Moreover, we show that a suitable environmental policy can allow recovering both local and global stability of the steady states. On the contrary, we show that, if the policy is not adequate, the system can exhibit endogenous oscillating and chaotic behavior and multistability phenomena.

We study the static and dynamical properties of a model that describes the interaction between the economic and epidemiological domains. The epidemiological sphere is represented by a susceptible–infected–susceptible model, while the economic domain consists of an overlapping generations model in which the workers correspond to the non-infected population of adults. The productivity of the firms and the propensity to save for retirement of the households are negatively affected by the disease spread. A capital tax is levied and the collected resources are used to curb the spread of the outbreak. We show that multiple endemic steady states can arise from the interaction between the two domains, and different stable endemic attractors can coexist with the stable disease free steady state. We study analytically and numerically the complex dynamics and the evolution of the basins of attraction in the case of multistability. We show that the effect of taxation can be beneficial from both the epidemiological and the economic points of view, as it can give rise to new steady states characterized by reduced shares of infected people and increased capital level, it can simplify the dynamical behaviors and reduce the size of the basins of attraction of those outcomes in which large shares of infected people and low capital levels are observed.

We propose a model for exploring the feasibility and effectiveness of a green transition from dirty to clean technologies. It relies on an evolutionary framework for the technology selection that accounts for the environmental domain dynamics, in terms of pollution evolution. A regulator charges an environmental tax to the producers, and the agents can choose between the less profitable clean technology and the more profitable dirty one, which, however, is taxed to a greater extent with respect to the clean one. The environmental tax depends endogenously on the level of pollution, which rises because of the producers’ emissions. The pollution stock also naturally decays, and can be abated by involving the resources collected from the taxation. We analytically study the resulting two-dimensional model from both statically and dynamically, to understand under what conditions the green transition can take place and results in an improvement for the environmental quality. We show that excessive over-taxation of the dirty technology may be not beneficial, as steady state pollution level can increase above a certain taxation threshold and multiple steady states can emerge. Moreover, dynamics can result in persistent endogenous oscillations that systematically lead to a significant increase in pollution levels. Finally, we discuss the economic rationale for the results also in the light of possible policy suggestions.

Outcomes observed in laboratory experiments on contests are often not consistent with the results expected by theoretical models, with phenomena that frequently occur like overbidding and, less frequently, underbidding, and persisting oscillations in strategic choices. Several explanations have been suggested to understand such phenomena, dealing primarily with equilibrium analysis. We propose a dynamical model based on the coevolution of strategic choices and agent preferences. Each agent can have non self-interested preferences, which influence strategic choices and in turn evolve according to them. We show that multiple coexisting steady states characterized by non self-interested preferences can exist, and they lose stability as the prize increases, leading to endogenous oscillating dynamics. Finally, with an emphasis on two specific kinds of agents, we explain how overbidding can emerge. The numerical results show a good qualitative agreement with the experimental data. The model and the analysis of this paper are interesting not only to explain real life phenomena observed in experimental settings, but also as a methodological contribution to analyze the interplay between preferences and choices in conflict situations.

We propose a model economy consisting of interdependent real, monetary and stock markets. The money market is influenced by the real one through a standard LM equation. Private expenditures depend on stock prices, which in turn are affected by interest rates and real profits, as these contribute to determine the participation level in the stock market. An evolutionary mechanism regulates agents’ participation in the stock market on the basis of a fitness measure that depends on the comparison between the stock return and the interest rate. Relying on analytical investigations complemented by numerical simulations, we study the economically relevant static and dynamic properties of the equilibrium, identifying the possible sources of instabilities and the channels through which they spread across markets. We aim at understanding what micro- and macro-factors affect the dynamics and, at the same time, how the dynamics of asset prices, which are ultimately influenced by the money market, behave over the business cycle. Starting from isolated markets, we show the effect of increasing the market interdependence on the national income, the stock price and the share of agents that participate in the stock market at the equilibrium. Moreover, we investigate the stabilizing/destabilizing role of market integration and the possible emergence of out-of-equilibrium dynamics.

The way agents form their expectations, and which equilibria are consequently selected, are issues that come over macroeconomic growth models that study the transition between states characterized by different levels of capital. Existing theoretical works in this area have been mostly dominated by perfect foresight models although alternative expectations schemes have been proposed in the last decades. In the present paper we propose an OLG model with capital accumulation assuming that agents employ simple yet heterogeneous rules to forecast the future course of the interest rate and the real wage. The forecasting rules are selected according to an evolutionary mechanism that, on the basis of a fitness measure, evaluates the performance of the heuristics agents are currently adopting. We analytically show that, in the heterogeneous setting we consider, multiple equilibria are possible, but the evolutionary heuristic switching allows for a decrease in the number of possible steady states, drives their selection, and reduces the actual possibility that the economy might be locked into a poverty trap. (c) 2022 Elsevier B.V. All rights reserved.

We study a financial market populated by heterogeneous agents, whose decisions are driven by “animal spirits”. Each agent may have either correct, optimistic or pessimistic beliefs about the fundamental value, which can change from time to time based on an evolutionary mechanism. The evolutionary selection of beliefs depends on a weighted evaluation of the general market sentiment perceived by the agents and on a profitability measure of the existent strategies. As the relevance given to the sentiment index increases, a herding phenomenon in agent behavior may occur and animal spirits can drive the market toward polarized economic regimes, which coexist and are characterized by persistent high or low levels of optimism and pessimism. This conduct is detectable from agents polarized shares and beliefs, which in turn influence the price level. Such polarized regimes can consist in stable steady states or can be characterized by endogenous dynamics, generating persistent alternating waves of optimism and pessimism, as well as return distributions displaying the typical features of financial time series, such as fat tails, excess volatility and multifractality. Moreover, we show that if the sentiment has no or low relevance on belief selection, those stylized facts are abated or are missing from the simulated time series.

In this paper, we study a class of markets, among which we can mention agricultural and energy markets, characterized by seasonality, i.e., in which demand and/or supply conditions cyclically alternate with a precise and known periodicity. We propose a new theoretical framework based on a cobweb model with adaptive expectations, accordingly modified to be consistent with market’s seasonality. The model, consisting in a second-order non-autonomous difference equation, is investigated with the aim of understanding how the periodical nature of the market together with the agents’ expectation formation mechanism affects the resulting dynamics. We analytically prove the emergence of dynamical scenarios that are missing in the classic cobweb model for non-seasonal markets, such as quasi-periodic dynamics and an ambiguous role on stability of the expectation weight. Finally, we discuss their economic rationale with the help of numerical simulations. In such a peculiar economic framework, agents’ learning plays a key role to explain the dynamical properties of economic observables.

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