Systemic risk governance in a dynamical model of a banking system with stochastic assets and liabilities

We consider the problem of governing systemic risk in an assets–liabilities dynamical model of a banking system. In the model considered, each bank is represented by its assets and liabilities. The net worth of a bank is the difference between its assets and liabilities and bank is solvent when its net worth is greater than or equal to zero; otherwise, the bank has failed. The banking system dynamics is defined by an initial value problem for a system of stochastic differential equations whose independent variable is time and whose dependent variables are the assets and liabilities of the banks. The banking system model presented generalizes those discussed in Fouque and Sun (in: Fouque, Langsam (eds) Handbook of systemic risk, Cambridge University Press, Cambridge, pp 444–452, 2013) and Fatone and Mariani (J Glob Optim 75(3):851–883, 2019) and describes a homogeneous population of banks. The main features of the model are a cooperation mechanism among banks and the possibility of the (direct) intervention of the monetary authority in the banking system dynamics. By “systemic risk” or “systemic event” in a bounded time interval, we mean that in that time interval at least a given fraction of banks have failed. The probability of systemic risk in a bounded time interval is evaluated via statistical simulation. Systemic risk governance aims to maintain the probability of systemic risk in a bounded time interval between two given thresholds. The monetary authority is responsible for systemic risk governance. The governance consists in the choice of assets and liabilities of a kind of “ideal bank” as functions of time and in the choice of the rules for the cooperation mechanism among banks. These rules are obtained by solving an optimal control problem for the pseudo mean field approximation of the banking system model. Governance induces banks in the system to behave like the “ideal bank”. Shocks acting on the banks’ assets or liabilities are simulated. Numerical examples of systemic risk governance in the presence and absence of shocks acting on the banking system are studied.

     

Value creation by knowledge‐based ecosystems: evidence from a field study

A growing number of research and development‐driven companies are located in knowledge‐based ecosystems. Value creation by these ecosystems draws on the dynamics of single firms (interacting and partnering) as well as the ecosystem at large. Drawing on a field study of a Dutch high‐tech campus, two key sources of value creation are identified: (1) facilitation of the innovation process for individual companies and (2) creation of an innovation community. Furthermore, the coevolution of the ecosystem's business model with firm‐level business models explains why technology‐based firms join, stay in, or leave the ecosystem at a certain point in time. A remarkable finding is that ecosystem managers have to deliberately facilitate exit routes for companies that no longer fit the ecosystem in order to enhance and reinforce its business model. As such, this study suggests a dynamic capability perspective on knowledge‐based ecosystems that need to develop a business model at the ecosystem level to create sufficient innovative capacity and entrepreneurial fitness.     

The evaluation of East Asian banks by considering economic and political conditions as well as country risk

This paper evaluates the performance of East Asian banks during the period of 2000–2010 by controlling country-specific conditions comprehensively. Particularly, it seeks to show that country-specific conditions are significant factors in estimating the common frontier by which the performance of all banks are compared. Thus, disregarding political conditions, regulatory environments, and country risk would lead to inaccurate efficiency scores because of the inaccurate common frontier. Following this further, an inaccurate measure of bank performance can hardly reveal bank problems before turning into a crisis. Our results confirm the significant impact of country-specific conditions on the common frontier, and hence bank efficiencies. The findings suggest that researchers, bank managers, and regulators also consider other factors other than economic conditions in their evaluations and decisions.     

Robust control and central banking behaviour

This paper seeks to explain the recent behaviour of the two main central banks in the recent financial crisis, applying a robust control tool through a Neo-Keynesian monetary policy model. The direct forbearer of this paper is the Giordani and Söderlind (2004) study. It begins with the origin, purpose and theoretical grounds of robust control, indicating that it is one way to face model uncertainty, as an alternative to the Bayesian approach. In the middle section, we seek to obtain the course of the model's main variables: interest rates, inflation and output. The model constructor also wants the participating agents to have the same doubts that he has regarding its validity; therefore, robust control is considered as a “fine-tuning” of the rational expectations approach. The impulse-response functions are obtained, with the monetary authority acting as a Stackelberg-type leader, affected by a perturbation on the supply side. The two relevant equilibria are obtained and compared in robust control with dynamic economy (the reference equilibrium and the worst possible case equilibrium) with that obtained when operating with rational expectations. The alternative course for the reference model set forth in the paper by Dennis (2008) is also analysed. We mainly find that the different results depend on the behaviour of the law of motion of the state variables, specifically the shadow prices that influence the private sector's expectations. Lastly, the paper relates the recent monetary policy performance when facing the financial crisis that began in the summer of 2007.     

Business at the fingertips of consumers: a scale for measuring resale motivations in online settings

Our current understanding of what motivates consumers to resell second-hand products online is limited. This article lays out the development and validation of an online resale motivation (ORM) scale based on three studies involving 1119 respondents. Study 1 presents the ORM scale development process and the resulting multidimensional construct, including the protester, economic, generative, recreational, practical and social facets of motivation. Study 2 replicates the scale and investigates its predictive value, demonstrating that the ORM scale successfully predicts online resale frequency. Study 3 examines the mediating role of ORM on the relationship between planned resale intentions and online resale behaviour. The findings show that there is no direct link between a consumer’s intention to resell an item prior to its purchase and the frequency with which they resell online. Rather, consumers who more frequently resell online items that they acquired with the intention of reselling do so because they perceive positive economic, practical and recreational outcomes associated with online reselling.     

The role of entrepreneurship education as a predictor of university students’ entrepreneurial intention

Using Ajzen’s theory of planned behavior and Shapero’s entrepreneurial event model as well as entrepreneurial cognition theory, we attempt to identify the relationship between entrepreneurship education, prior entrepreneurial exposure, perceived desirability and feasibility, and entrepreneurial intentions (EI) for university students. The data were collected from a survey of ten universities; we received 494 effective responses. We used probit estimation to show that perceived desirability significantly impacts EI whereas there is no significant impact from perceived feasibility. There is a significant negative impact from exposure (which is surprising) and a significant positive impact from entrepreneurship education. Males and people from technological universities and/or backgrounds have higher EI than females and people from other universities and backgrounds. There are also significant positive interactive effects by gender, university type, and study major on the relationship between entrepreneurship education and EI.     

Migration as an antidote to rent-seeking?

We develop a new mechanism through which skilled migration may influence economic performance in the sending country. If agents can choose between acting as rent-seekers and engaging in productive activities, and only productive skills are exportable, a positive probability of migration (to a more secure economy) reduces the relative expected returns from rent-seeking, thus decreasing the proportion of skilled workers who opt for “parasitic” activities. Such an improvement in the allocation of talent may prevail over the loss of skilled workers due to outmigration. However, we show that this result is not robust to the introduction of endogenous protection. If productive workers share their resources between accumulation of productive capital and investment in security, prospective migration may induce a weaker protection against rent-seeking, which in turn might depress average income in the source economy.     

Productivity and profitability analysis of large Italian companies: 1998–2002

The determinants of profitability and productivity for large Italian companies operating in industrial sectors are investigated in this paper. Data were taken from one of the most important Italian business surveys, and furthermore two cross-section surveys for the years 1998 and 2002 are compared. The results highlight the importance of financial management and organisational complexity in order to explain the development of profitability and productivity ranking during 1998–2002. This paper identifies the important enterprise behaviour in terms of the variables considered. Large Italian companies remain competitive in the more traditional sectors (e.g. mechanics, textiles, etc.). In general, the Italian enterprises are not dynamic enough to compete in the most technological and innovative sectors. Moreover, there is the necessity for greater investments in order to foster the national economy.