Effects of financial instability on subjective well-being: a preference-based approach

Abstract

PurposeThe purpose of this paper is to examine the link between banking crises and the subjective well-being of individuals. In addition, the authors examine the transmission of crises from the banking sector to well-being and show that negative financial shocks have significant adverse effects.Design/methodology/approachThe authors employ agent-based modeling to test for the direct and indirect welfare effects of banking crises. The model includes a support vector machine (SVM) optimized subjective well-being function. The existing literature suggests that this is influenced by both the negative psychological effects of recessions and the adverse economic effects of income loss and increased unemployment.FindingsThe authors show that the different choices of policy response to a banking crisis carry different opportunity costs in terms of welfare and that societal preferences should be taken into account. The authors demonstrate that these effects influence different population classes in an asymmetric manner. Finally, the results demonstrate that the welfare loss of a bank failure is much higher than the cost of a bailout.Practical implicationsThe authors are able to propose to the authorities the best policy mix in order to handle banking crises in the most adequate manner, according to society's preferences between financial stability and public goods.Social implicationsThe findings extend the existing literature on subjective well-being, by quantifying the welfare cost of banking crises and showing that authorities should reconsider bank bailouts as a policy solution to bank distress.Originality/valueThe originality of this article lies in the use of an agent-based model to model the relationship between societal well-being and financial stability. Also, the authors extend existing agent-based methodologies to include machine learning optimization techniques.

Islamic banking, efficiency and societal welfare: a machine-learning, agent-based study

“…Existing studies mainly use conceptual approaches (AbdulKareem et al, 2021;Oshodi, 2016;Tabash and Dhankar, 2014), with few implementing an empirical methodology. Secondly, we extend an existing agent-based model (Polyzos et al, 2021a), to include a machine-optimised happiness function, developing a modelling process that uses banking data from both Islamic economies and conventional economies. Thirdly, we demonstrate that despite the fact that Islamic banking promotes financial stability, it can hinder economic growth and increase unemployment.…”

“…In this paper, we have used the agent-based system of Polyzos et al (2021a) and Polyzos and Samitas (2015), which we extended with the happiness component presented in subsection 3.2 to calculate individual happiness functions. In this section, we will describe the model in brief.…”

“…In this section, we will describe the model in brief. Readers can refer to Polyzos et al (2021a) and Samitas et al (2018) for the formal model definition and for detailed algorithmic steps. Our approach is similar to the modelling approach of Azmat et al (2021b) and Azmat et al (2020), with two main differences: firstly, our approach implements multiple periods and multiple heterogeneous agents, and secondly, the agent-based model describes the non-linear outcomes on the underlying economic environment where the impact of economic activity is asymmetric across different agent groups.…”

“…To examine the efficiency of Islamic banking systems, we use an agent-based model (Polyzos et al , 2021a), which includes a machine-trained happiness function (based on a naïve Bayes classifier and an artificial neural network [ANN]), to examine the benefits of the PLS paradigm over conventional banking. This modelling methodology is an implementation of agent-based economics (Tesfatsion, 2006), where the economy is described as a constant interaction between heterogeneous agents, with differing (and often clashing) rational objectives.…”

The perfect bail‐in: Financing without banks using peer‐to‐peer lending

“…In this paper, we attempt to address this lacuna by simulating a banking system that combines conventional and P2P lenders, using agent‐based modelling (Polyzos, Abdulrahman, & Dandu, 2021; Schubring et al, 2016). We attempt to examine the effects of various degrees of adoption of P2P lending practices on financial stability and economic performance.…”