House-Price Crash and Macroeconomic Crisis: A Hong Kong Case Study

House prices crash has become an important feature of macroeconomic crisis. We argue that house prices crash driven by contractionary monetary policy is not only a reaction to crisis, but also accelerates and amplifies the fluctuations of major macroeconomic variable. In this paper, we conduct a case study of Hong Kong in the 1997-1998 financial crisis and quantitatively analyze the mechanism by developing a general equilibrium model incorporating financial accelerator mechanism into both household and entrepreneur sectors. After estimating and simulating the model, impulse response results imply that our model can explain the co-movement of house prices, consumption, and investment better than the alternative models.house prices, fianncial accelerator, consumption, investment, Hong Kong

Simulating supervision: how do managers respond to a crisis?

Supervision is fundamental to child and family social work practice, in England as elsewhere, yet there is little research regarding what managers and social workers do when they meet to discuss the families they are working with. Recent years have seen a growing interest in the use of simulated clients and Objective Structured Clinical Exams to help develop and evaluate the abilities of social workers and students. This paper describes a study of 30 simulated supervision sessions between English social work managers and an actor playing the role of a student social worker in need of support. The simulation concerns a referral regarding an incident of domestic abuse. During the simulations, managers typically asked closed questions to obtain more information before providing solutions for the supervisee in the form of advice and direction. There was little evidence of emotional support for the social worker, nor empathy with the family. Managers typically acted as expert problem-solvers. The implications of this are discussed in relation to current theoretical models of supervision for child and family social work and in relation to how Children’s Services responds to domestic abuse

Financial contagion: Evolutionary optimisation of a multinational agent-based model

Over the past two decades, financial market crises with similar features have occurred in different regions of the world. Unstable cross-market linkages during a crisis are referred to as financial contagion. We simulate crisis transmission in the context of a model of market participants adopting various strategies; this allows testing for financial contagion under alternative scenarios. Using a minority game approach, we develop an agent-based multinational model and investigate the reasons for contagion. Although the phenomenon has been extensively investigated in the financial literature, it has not been studied through computational intelligence techniques. Our simulations shed light on parameter values and characteristics which can be exploited to detect contagion at an earlier stage, hence recognising financial crises with the potential to destabilise cross-market linkages. In the real world, such information would be extremely valuable in developing appropriate risk management strategies

The Variable Scale Evacuation Model (VSEM): a new tool for simulating massive evacuation processes during volcanic crises

Volcanic eruptions are among the most awesome and powerful displays of nature's force, constituting a major natural hazard for society (a single eruption can claim thousands of lives in an instant). Consequently, assessment and management of volcanic risk have become critically important goals of modern volcanology. Over recent years, numerous tools have been developed to evaluate volcanic risk and support volcanic crisis management: probabilistic analysis of future eruptions, hazard and risk maps, event trees, etc. However, there has been little improvement in the tools that may help Civil Defense officials to prepare Emergency Plans. Here we present a new tool for simulating massive evacuation processes during volcanic crisis: the Variable Scale Evacuation Model (VSEM). The main objective of the VSEM software is to optimize the evacuation process of Emergency Plans during volcanic crisis. For this, the VSEM allows the simulation of an evacuation considering different strategies depending on diverse impact scenarios. VSEM is able to calculate the required time for the complete evacuation taking into account diverse evacuation scenarios (number and type of population, infrastructure, road network, etc.) and to detect high-risk or "blackspots" of the road network. The program is versatile and can work at different scales, thus being capable of simulating the evacuation of small villages as well as huge cities

A mixed-game agent-based model of financial contagion

Over the past two decades, financial market crises with similar features have occurred in different regions of the world. Unstable cross-market linkages during financial crises are referred to as financial contagion. We simulate the transmission of financial crises in the context of a model of market participants adopting various strategies; this allows testing for financial contagion under alternative scenarios. Using a minority game approach, we develop an agent-based multinational model and investigate the reasons for contagion. Although contagion has been extensively investigated in the financial literature, it has not been studied yet through computational intelligence techniques. Our simulations shed light on parameter values and characteristics which can be exploited to detect contagion at an earlier stage, hence recognising financial crises with the potential to destabilise cross-market linkages. In the real world, such information would be extremely valuable to develop appropriate risk management strategies

Classical mechanics of economic networks

Financial networks are dynamic. To assess their systemic importance to the world-wide economic network and avert losses we need models that take the time variations of the links and nodes into account. Using the methodology of classical mechanics and Laplacian determinism we develop a model that can predict the response of the financial network to a shock. We also propose a way of measuring the systemic importance of the banks, which we call BankRank. Using European Bank Authority 2011 stress test exposure data, we apply our model to the bipartite network connecting the largest institutional debt holders of the troubled European countries (Greece, Italy, Portugal, Spain, and Ireland). From simulating our model we can determine whether a network is in a "stable" state in which shocks do not cause major losses, or a "unstable" state in which devastating damages occur. Fitting the parameters of the model, which play the role of physical coupling constants, to Eurozone crisis data shows that before the Eurozone crisis the system was mostly in a "stable" regime, and that during the crisis it transitioned into an "unstable" regime. The numerical solutions produced by our model match closely the actual time-line of events of the crisis. We also find that, while the largest holders are usually more important, in the unstable regime smaller holders also exhibit systemic importance. Our model also proves useful for determining the vulnerability of banks and assets to shocks. This suggests that our model may be a useful tool for simulating the response dynamics of shared portfolio networks