Dynamic bank runs: an agent-based approach

Journal of Economic Interaction and Coordination - This paper simulates bank runs by using an agent-based approach to assess the depositors’ behavior under various scenarios in a...     

Capability-based governance patterns over the product life-cycle: an agent-based model

In recent literature, there is disagreement over the temporal pattern of vertical governance of firms over the product life-cycle. We use a novel neo-Schumpeterian agent-based simulation model to investigate emerging patterns of vertical governance for different levels of imitability and substitutability of capabilities. We find that, in the mature phase of the product life-cycle, firms generally prefer vertical specialization. However, in the early phase, imitability and substitutability, in interplay, determine the governance form preferred. High imitability frustrates appropriation and thereby discourages integration for synergistic advantages. However, firms need not vertically specialize: under low substitutability, incompatibilities reduce the advantages of specialization. When both substitutability and imitability are low, firms can appropriate the value of their inventions and there is no combinatorial advantage of specialization, so firms predominantly integrate. If substitutability is high and imitability is low, the combinatorial advantage of specialization balances with the synergistic advantage of integration.     

A network agent-based model of ethnocentrism and intergroup cooperation

Quality & Quantity - We present a network agent-based model of ethnocentrism and intergroup cooperation in which agents from two groups (majority and minority) change their communality (feeling...     

Convex incentives in financial markets: an agent-based analysis

We investigate whether convex incentive contracts are a source of instability of financial markets as indicated by the results of a continuous double-auction asset market experiment performed by Holmen et al. (J Econ Dyn Control 40:179–194, 2014). We develop a model to replicate the setting of the experiment and perform an agent-based simulation where agents have linear or convex incentives. Extending the simulation by varying features of actual asset markets that were not studied in the experiment, our main results show that increasing the number of convex incentive contracts increases prices and volatility and decreases market liquidity, measured both as bid–ask spreads and volumes. We also observe that the influence of risk aversion on traders’ decisions decreases when there are convex contracts and that increasing the differences in initial wealth among the traders has similar effects as increasing number of convex incentive contracts.     

Macroeconomic implications of mortgage loan requirements: an agent-based approach

It is a well-known fact that the housing market, with its associated mortgage securities, plays a crucial role in modern economies. The recent crisis of 2007, triggered by the U.S. real estate bubble, confirms this key role and suggests the importance of regulating mortgage lending. This paper investigates these issues by designing a housing market with a linked mortgage lending instrument in the Eurace agent-based model. Our results show that the presence of a housing market in the model has relevant macroeconomic implications, driven mainly by the additional amount of endogenous money injected into the economy by new mortgages. This additional money generally helps to support and stabilize aggregated demand, thus improving the main economic indicators. However, if the regulation of mortgage lending is too lax, involving an increase in the debt-service-to-income ratio (DSTI), then the additional supply of mortgages no longer enhances macroeconomic performance, and the stability of the economic system is undermined. Based on a number of recent discussions, a regulation of stock control that targets households’ net wealth (a stock), rather than income (a flow) is designed and analyzed. The results show that regulation of stock control can be combined effectively with DSTI to increase the stability of the housing market and the economy as a whole. Interestingly, the regulation based on stock control also directly affects mortgage distribution among households, avoiding excessive concentration. From a policy perspective, our results suggest that the use of a mild flow control regulation, coupled with a stricter stock control measure, fosters sustainable growth and eases first-time buyers access to the housing market, encouraging homeownership.

     

Information dissemination in an experimentally based agent-based stock market

This paper builds an agent-based model to reproduce the results of an experimental stock market that studies how the market aggregates private information. The aim is to use experiments and agent-based modeling to analyze the trading behavior in experimental stock markets. Using the experimental environment and results, it is possible to formulate a hypothesis about the subjects’ behavior and thereby formalize (algorithmically) the trading behavior in an agent-based model. This may lead to a better understanding of how the market converges to an equilibrium and of the mechanism that allows dissemination of private information in the market.     

Innovation,finance, and economic growth: an agent-based approach

This paper extends the endogenous growth agent-based model in Fagiolo and Dosi (Struct Change Econ Dyn 14(3):237–273, 2003) to study the finance–growth nexus. We explore industries where firms produce a homogeneous good using existing technologies, perform R&D activities to introduce new techniques, and imitate the most productive practices. Unlike the original model, we assume that both exploration and imitation require resources provided by banks, which pool agent savings and finance new projects via loans. We find that banking activity has a positive impact on growth. However, excessive financialization can hamper growth. Indeed, we find a significant and robust inverted U-shaped relation between financial depth and growth. Overall, our results stress the fundamental (and still poorly understood) role played by innovation in the finance–growth nexus.

     

Systemic financial risk indicators and securitised assets: an agent-based framework

The paper presents an agent-based model of a credit economy which includes a securitisation process and a bailout mechanism for bank bankruptcies. Within this framework, banks are able to sell mortgages to a financial vehicle corporation, which finances its activity by creating mortgage-backed securities and selling them to a mutual fund. In turn, the mutual fund collects liquidity by selling shares to households and remunerates them with a monthly interest. The impact of this mechanism is analysed by means of computational experiments for different levels of banks’ securitisation propensity. Furthermore, we study a set of systemic risk indicators which have the aim of assessing the imbalances in the financial system. Two of them are the mortgage-to-GDP ratio and the capital adequacy ratio, which are constructed to detect only the on-balance sheet changes in banks’ credit exposure. We consider two additional indicators, similar to the previous ones with the only difference that they are also able to account for the off-balance sheet items. Moreover, we adopt an indicator, the so-called “virtuous–unvirtuous cycle” indicator, which, besides off-balance assets, targets also the GDP. The results show that higher securitisation propensity weakens the financial stability of banks with relevant effects on different sectors of the economy. Most importantly, the analysis of systemic risk reveals the important issue of designing suitable systemic risk indicators for predicting incoming financial crises, finding that an essential feature of these indicators should be to integrate banks’ off-balance sheet assets.

     

Combining monetary policy and prudential regulation: an agent-based modeling approach

This paper explores the interaction between monetary policy and prudential regulation in an agent-based modeling framework. Firms borrow funds from the banking system in an economy regulated by a central bank. The central bank carries out monetary policy, by setting the interest rate, and prudential regulation, by establishing the banking capital requirement. Different combinations of interest rate rule and capital requirement rule are evaluated with respect to both macroeconomic and financial stability. Several relevant policy implications were drawn. First, the efficacy of a given capital requirement rule or interest rate rule depends on the specification of the rule of the other type it is combined with. More precisely, less aggressive interest rate rules perform better when the range of variation of the capital requirement is narrower. Second, interest rate smoothing is more effective than the other interest rate rules assessed, as it outperforms those other rules with respect to financial stability and macroeconomic stability. Third, there is no tradeoff between financial and macroeconomic stability associated with a variation of either the capital requirement or the smoothing interest rate parameter. Finally, our results reinforce the cautionary finding of other studies regarding how output can be ravaged by a low inflation targeting.

     

Learning to save in a voluntary pension system: toward an agent-based model

Mandatory pension systems partially replace old-age income, therefore the government matches additional life-cycle savings in a voluntary pension system. Though the individual saving decisions are apparently independent, the earmarked taxes (paid to finance the matching) connect them. Previous models either neglected the endogenous tax expenditures (e.g. Choi et al., in: Wise (ed) Perspectives in the economics of aging, University of Chicago Press, Chicago, pp 81–121, 2004) or assumed very sophisticated saving strategies (e.g. Fehr et al. in FinanzArchiv Pub Finance Anal 64:171–198, 2008). We create twin models: myopic workers learn (i) from farsighted workers using public information (analytic model) and (ii) also from each other (agent-based model). These models provide more realistic results on saving behavior and the impact of matching on the income redistribution than the earlier models.

     

A comparison of different trading protocols in an agent-based market

We compare price dynamics of different market protocols (batch auction, continuous double auction and dealership) in an agent-based artificial exchange. In order to distinguish the effects of market architectures alone, we use a controlled environment where allocative and informational issues are neglected and agents do not optimize or learn. Hence, we rule out the possibility that the behavior of traders drives the price dynamics. Aiming to compare price stability and execution quality in broad sense, we analyze standard deviation, excess kurtosis, tail exponent of returns, volume, perceived gain by traders and bid-ask spread. Overall, a dealership market appears to be the best candidate, generating low volume and volatility, virtually no excess kurtosis and high perceived gain.     

Itchy feet vs cool heads: Flow of funds in an agent-based financial market

Investors tend to move funds when they are unhappy with their current portfolio managers׳ performance. We study the effect of the size of this flow of funds in an agent-based model of the financial market. The model combines the discrete choice approach from agent-based modelling, where all capital is mobile, with the evolutionary finance framework where all growth is endogenous. Our results show that, if investors exhibit recency bias in evaluating portfolio managers׳ performance, even a small amount of freely flowing capital has a huge impact on the market dynamics and the survival of noise traders. We also find that investors׳ intensity of choice is a driving force for excess volatility and extreme price movements when the size of the flow of funds is large.     

Varieties of agents in agent-based computational economics: A historical and an interdisciplinary perspective

In this paper, we trace four origins of agent-based computational economics (ACE), namely, the markets origin, the cellular-automata origin, the tournaments origin, and the experiments origin. Along with this trace, we examine how these origins have motivated different concepts and designs of agents in ACE, which starts from the early work on simple programmed agents, randomly behaving agents, zero-intelligence agents, human-written programmed agents, autonomous agents, and empirically calibrated agents, and extends to the newly developing cognitive agents, psychological agents, and culturally sensitive agents. The review also shows that the intellectual ideas underlying these varieties of agents cross several disciplines, which may be considered as a part of a general attempt to study humans (and their behavior) with an integrated interdisciplinary foundation.     

Buying cooperation in an asymmetric environmental differential game

We consider a two-player asymmetric differential game of pollution control. One player is non-vulnerable to pollution, or unwilling to consider damages when choosing her production policy in a non-cooperative game. We characterize the feedback-Nash equilibrium and the cooperative solution. We establish conditions under which the vulnerable player can buy the cooperation of the non-vulnerable player to control her emissions. We further use the Nash bargaining solution to allocate the total cooperative dividend between the two players and propose a time-consistent decomposition overtime of the total payoff.     

Training provision and workplace institutions: an investigation

The training debate has suffered from a preoccupation with macro institutions and regulatory frameworks. This has resulted in a neglect of workplace industrial relations issues. Using case study data from three private sector engineering companies, this article highlights the importance of workplace institutions in explaining training outcomes.     

Complex agent-based macroeconomics: a manifesto for a new paradigm

This article discusses some issues and challenges facing modern macroeconomics. We argue for the necessity to replace the reductionist approach at the heart of mainstream DSGE models with an approach rooted on the science of complexity and agent-based modelling. To strengthen and exemplify our position, we show a simple example and introduce several items for a research agenda along these lines.     

Social networks and labour productivity in Europe: an empirical investigation

This paper uses firm-level data recorded in the Amadeus database to investigate the distribution of labour productivity in different European countries. We find that the upper tail of the empirical productivity distributions follows a decaying power-law, whose exponent α is obtained by a semi-parametric estimation technique recently developed by Clementi et al. [Physica A 370(1):49–53, 2006]. The emergence of “fat tails” in productivity distribution has already been detected in Di Matteo et al. [Eur Phys J B 47(3):459–466, 2005] and explained by means of a model of social network. Here we show that this model is tested on a broader sample of countries having different patterns of social network structure. These different social attitudes, measured using a social capital indicator, reflect in the power-law exponent estimates, verifying in this way the existence of linkages among firms’ productivity performance and social network.