A comparison of economic agent-based model calibration methods

Platt, Donovan

doi:10.1016/j.jedc.2020.103859

Cited by 58 publications

(31 citation statements)

References 38 publications

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“…Agent-based model calibration remains a very active field of research; sufficiently flexible and computationally feasible methods are recent and still under development(Lamperti et al 2017;Fagiolo et al 2017;Barde and van der Hoog 2017;Platt 2019). …”

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confidence: 99%

A simulation of the insurance industry: the problem of risk model homogeneity

Heinrich

Sabuco

Farmer

2021

J Econ Interact Coord

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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.

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confidence: 99%

A simulation of the insurance industry: the problem of risk model homogeneity

Heinrich

Sabuco

Farmer

2021

J Econ Interact Coord

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“…In recent years agent-based technology has increased in popularity across a variety of domains ranging from epidemiology [42] to economics [43]. Meanwhile, significant advances in software testing have revolutionised the way we test complex systems, such as the emergence of fuzzing techniques to enhance the automatic discovery of security vulnerabilities [44].…”

Section: Methodsmentioning

confidence: 99%

Test case generation for agent-based models: A systematic literature review

Clark

Walkinshaw

Hierons

2021

Information and Software Technology

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Context: Agent-based models play an important role in simulating complex emergent phenomena and supporting critical decisions. In this context, a software fault may result in poorly informed decisions that lead to disastrous consequences. The ability to rigorously test these models is therefore essential.Objective: Our objective is to summarise the state-of-the-art techniques for test case generation in agent-based models and identify future research directions. Method:We have conducted a systematic literature review in which we pose five research questions related to the key aspects of test case generation in agent-based models: What are the information artifacts used to generate tests? How are these tests generated? How is a verdict assigned to a generated test? How is the adequacy of a generated test suite measured? What level of abstraction of an agent-based model is targeted by a generated test?Results: Out of the 464 initial search results, we identified 24 primary publications. Based on these primary publications, we formed a taxonomy to summarise the state-of-the-art techniques for test case generation in agentbased models. Our results show that whilst the majority of techniques are effective for testing functional requirements at the agent and integration levels of abstraction, there are comparatively few techniques capable of testing society-level behaviour. Furthermore, the majority of techniques cannot test non-functional requirements or "soft goals".Conclusions: This paper reports insights into the key developments and open challenges concerning test case generation in agent-based models that may be of interest to both researchers and practitioners. In particular, we identify the need for test case generation techniques that focus on societal and non-functional behaviour, and a more thorough evaluation using realistic case studies that feature challenging properties associated with a typical agent-based model.

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“…For further details about the validation and calibration of the model, see Teglio et al (2019). As pointed out by Platt (2019), further developments of agent-based model calibration techniques are required in order to definitively calibrate large-scale models, like Eurace; however, future research will explore the feasibility of a full calibration of the model or of part of it, by resorting to Bayesian inference.…”

Section: Policy Makersmentioning

confidence: 99%

The complexity of the intangible digital economy: an agent-based model

Bertani

Ponta

Raberto

et al. 2021

Journal of Business Research

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During the last decades, we have witnessed a strong development of intangible digital technologies. Software, artificial intelligence and algorithms are increasingly affecting both production systems and our lives; economists have started to figure out the long-run complex economic implications of this new technological wave. In this paper, we address this question through the agent-based modelling approach. In particular, we enrich the macroeconomic model Eurace with the concept of intangible digital technology and investigate its effects both at the micro and macro level. Results show the emergence of the relevant stylized facts observed in the business domain, such as increasing returns, winner-take-most phenomena and market lock-in. At the macro level, our main finding is an increasing unemployment level, since the sizeable decrease of the employment rate in the mass-production system, provided by the higher productivity of digital assets, is usually not counterbalanced by the new jobs created in the digital sector.

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A comparison of economic agent-based model calibration methods

Cited by 58 publications

References 38 publications

A simulation of the insurance industry: the problem of risk model homogeneity

A simulation of the insurance industry: the problem of risk model homogeneity

Test case generation for agent-based models: A systematic literature review

The complexity of the intangible digital economy: an agent-based model

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