Journal of Economic Interaction and Coordination最新文献

Most of the theoretical contributions on the relationship between economy and environment assume the environment as a good distributed homogeneously among agents. The aim of this work is to relax this hypothesis and to consider that the environment can have a local character even if conditioned through externalities by the choices made at the global level. In this article, we adapt the classical framework introduced in John and Pecchenino (Econ J 104(427):1393-1410, 1994) to analyze the dynamic relationship between environment and economic process, and we propose an OLG agent-based model where each agent perceives her own level of environmental quality determined by her own decisions, and by the decisions of those living around her. Despite the attention devoted to local environmental aspects, network externalities (determined through the scheme of Moore neighborhoods) play a fundamental role in defining environmental dynamics and they may induce the emergence of cyclical dynamics. The occurrence of oscillations in the local environmental quality is partially mitigated by the presence of heterogeneity in individuals' preferences. Finally, when a centralized planner is introduced, the dynamics converge to stationary values regardless of the assumption on heterogeneity of agents.

We develop an agent-based simulation of the catastrophe insurance and reinsurance industry and use it to study the problem of risk model homogeneity. The model simulates the balance sheets of insurance firms, who collect premiums from clients in return for insuring them against intermittent, heavy-tailed risks. Firms manage their capital and pay dividends to their investors and use either reinsurance contracts or cat bonds to hedge their tail risk. The model generates plausible time series of profits and losses and recovers stylized facts, such as the insurance cycle and the emergence of asymmetric firm size distributions. We use the model to investigate the problem of risk model homogeneity. Under the European regulatory framework Solvency II, insurance companies are required to use only certified risk models. This has led to a situation in which only a few firms provide risk models, creating a systemic fragility to the errors in these models. We demonstrate that using too few models increases the risk of nonpayment and default while lowering profits for the industry as a whole. The presence of the reinsurance industry ameliorates the problem but does not remove it. Our results suggest that it would be valuable for regulators to incentivize model diversity. The framework we develop here provides a first step toward a simulation model of the insurance industry, which could be used to test policies and strategies for capital management.

Overtourism is an increasingly relevant problem for tourist destinations, and some cities are starting to take extreme measures to counter it. In this paper, we introduce a simple mathematical model that analyzes the dynamics of the populations of residents and tourists when there is a competition for the access to local services and resources, since the needs of the two populations are partly mutually incompatible. We study under what conditions a stable equilibrium where residents and tourists coexist is reached, and what are the conditions for tourists to take over the city and to expel residents, among others. Even small changes in key parameters may bring about very different outcomes. Policymakers should be aware that a sound knowledge of the structural properties of the dynamics is important when taking measures, whose effect could otherwise be different than expected and even counterproductive.

How will the novel coronavirus evolve? I study a simple epidemiological model, in which mutations may change the properties of the virus and its associated disease stochastically and antigenic drifts allow new variants to partially evade immunity. I show analytically that variants with higher infectiousness, longer disease duration, and shorter latent period prove to be fitter. "Smart" containment policies targeting symptomatic individuals may redirect the evolution of the virus, as they give an edge to variants with a longer incubation period and a higher share of asymptomatic infections. Reduced mortality, on the other hand, does not per se prove to be an evolutionary advantage. I then implement this model as an agent-based simulation model in order to explore its aggregate dynamics. Monte Carlo simulations show that a) containment policy design has an impact on both speed and direction of viral evolution, b) the virus may circulate in the population indefinitely, provided that containment efforts are too relaxed and the propensity of the virus to escape immunity is high enough, and crucially c) that it may not be possible to distinguish between a slowly and a rapidly evolving virus by looking only at short-term epidemiological outcomes. Thus, what looks like a successful mitigation strategy in the short run, may prove to have devastating long-run effects. These results suggest that optimal containment policy must take the propensity of the virus to mutate and escape immunity into account, strengthening the case for genetic and antigenic surveillance even in the early stages of an epidemic.

We study the dynamic behavior of heterogeneous markets with many types of agents. In particular this paper aims at studying the effects of a change in the number n of agents, who are possibly different in terms of the rule they employ to forecast, on the long-run value of a relevant state variable. On the one hand we show that a heterogeneous agents model cannot be by and large traced back to an equivalent average representative-agent model. This complicates the possibility of easily reducing large and complex models to simpler and analytically tractable ones. On the other hand, under fairly general conditions, we characterize a class of models in which the probability of convergence to the steady state becomes either one or zero as n grows. This fact has positive implications for a policy maker committed to the goal of stabilizing the economy.