A dual approach to ambiguity aversion

In the present paper, the assumption of monotonicity of Anscombe and Aumann (1963) is replaced by an assumption of monotonicity with respect to first-order stochastic dominance. This yields a representation result where ambiguous distributions of objective beliefs are first aggregated into “equivalent unambiguous beliefs” and then risk preferences are used to compute the utility of these equivalent unambiguous beliefs. Such an approach makes it possible to disentangle uncertainty aversion, related to the processing of information, from risk aversion, related to the evaluation of the equivalent unambiguous beliefs. An application to portfolio choice shows the tractability of the framework and its intuitive appeal.     

A dual approach for matrix-derivatives

Summary A dual approach for matrix by matrix derivatives is proposed, based on the work ofBalestra and the idea ofDwyer/MacPhail. The two derivative concepts are calledB-type derivative for the form B/A = (b _kl /A), because it was studied fully inBalestra, andA-type derivative for the form B/ /A = (B/a _ij ). Both derivative concepts are linked by permutation matrices, which also reveil the duality aspect more clearly, and can be transformed to each other very easily. The derivatives are applied to least squares estimates and posterior means in the general regression model and the seemingly unrelated regression (SUR)-system, introduced byZellner. The derivatives with respect to the covariance matrix is related to the local sensitivity concept ofLeamer [1978], while the derivatives with respect to the data-matrix, also called local resistance, is linked with the robustness concept ofTukey. The newly definedB-derivative enables an easier interpretation of the results.     

On the determinants of foreign ownership shares: Evidence from US firms' joint ventures in Japan

It is often argued that firms' foreign expansion is motivated by economies of scale in information-based intangible assets. Since these assets are combined with local factors in real production, their owner often has to deal with local factor owners' opportunistic behavior such as siphoning of skills which reduces the return on intangibles to the original owner. Local factor owners' agency behavior can also reduce a subsidiary's profit. Maintaining ownership mitigates the former type of opportunistic behavior, while ceding ownership reduces the latter type. Hence there is a non-linear relationship between ownership and the cost of control. In this paper we present a model that incorporates these aspects of a joint venture ownership. In our model the share in a joint venture of a foreign parent firm with a superior technology is determined such that its marginal cost of control is set equal to the marginal benefit it derives from a joint venture. We assume that, because of the uniqueness and mobility of its intangible factor, the foreign partner has more bargaining power than its local counterpart regarding the ownership of their joint venture and that the local partner is less concerned than its foreign counterpart about the problems of agency and property rights protection because of its geographic and cultural proximity to the joint venture. As a consequence, the foreign partner is able to exert its preference for its ownership share in the joint venture. Our theoretical results allow a decomposition of ownership share into components explained by the cost of control and by the profitability of a joint venture. Our empirical results using data on technology-based US firms' subsidiaries in Japan are consistent with our model predictions. In particular, the fraction of ownership share explained by the cost of control relative to the fraction explained by intrinsic profitability is higher for industries that rely more heavily on intangible assets, as expected from the model.     

A disaggregated approach to test the J-Curve phenomenon: Japan versus her major trading partners

A limited number of studies have tested the J-Curve phenomenon using bilateral trade data between the United States and its major trading partners. In this paper, we test the J-Curve hypothesis by using quarterly bilateral data over the 1973–98 period between Japan and its nine major trading partners. We demonstrate that when aggregate data are used, there is no evidence of the J-Curve in the short run or any significant relation between trade balance and effective exchange rate in the long run. However, when bilateral data are employed, we find evidence of the J-Curve between Japan and Germany as well as between Japan and Italy. We also find that real depreciation of the yen has favorable long-run effects in the cases of Canada, the United Kingdom, and the United States.     

A cross-country panel approach to exploring the determinants of educational equity through PISA data

The main aim of the paper is to analyse the effect of country and school factors on a new measure of educational equity defined as the country proportion of resilient students, i.e. those who, despite their disadvantaged socioeconomic background, are able to obtain good educational results. We construct a cross country panel dataset by merging the five editions of OECD PISA (Programme for International Student Assessment). The panel analysis allows to exploit country and time level variation in the proportion of resilient students controlling for systematic and institutional differences. Our findings suggest that educational funding can help disadvantaged students to obtain the opportunities that they are otherwise lacking. In addition, this effect seems to be heterogeneous, and particularly driven by those countries whose economic development (in terms of per capita GDP) is lower.     

Credit risk and asymmetric information: A simplified approach

We present a simple model for risky, corporate debt. Debtholders and equityholders have incomplete information about the financial state of the debt issuing company. Information is incomplete because it is delayed for all agents, and it is asymmetrically distributed between debtholders and equityholders. We solve for the equityholders' optimal default policy and for the credit spreads required by debtholders. Delayed information accelerates the equityholders' optimal decision to default. Interestingly, this effect is small, implying only a small impact on credit spreads. Asymmetric information, however, has a major impact on credit spreads. Our model predicts high credit spreads for short-term debt, as observed empirically in credit markets.     

Valuing the option to purchase an asset at a proportional discount: A correction

Gu [Gu, Y. A. (2002). Valuing the option to purchase an asset at a proportional discount. The Journal of Financial Research, 25 (1), 99–109] introduces proportional-strike options to study a residential real estate program in China. Under this program, a state employee can buy her house at a fraction of the market price. The employee can also qualify for a subsidized mortgage. Given that the homeowner has the option, but not the obligation, of taking the subsidy, we show that the solution of the housing problem derived by Gu can be wrong. We provide a numerical example to illustrate the point.     

Precautionary behavior and consumer information: A Markov process approach

This paper explores the role of consumer confidence in the equilibrium of a dynamic macroeconomic growth model with rational expectations. Consumers face an uncertain future income stream due to a Markov stochastic process that affects production. Changes in the properties of this process change consumer information sets and optimal policies in the rational expectations format. Increases in “persistence” in the shock process are considered; this is identified with the consumer's subjective assessment of future economic conditions. Two cases are considered: where either good or bad states of the process are more likely to persist into the future, and where bad states persist unconditionally at the expense of good. Consistent with earlier treatments of savings under uncertainty (Barsky, Mankiw and Zeldes 1986, and Skinner 1988), the consumer's response to increased income uncertainty is to exhibit precautionary saving behavior. The infinite-horizon growth model format used offers significant improvement over other finite-horizon life cycle models. Specifically, the model is a full general equilibrium model and the solutions are rational expectations solutions. The technique also is easily adapted to other recursive decision problems under uncertainty.     

An input-output approach to the measurement of the information economy

This study presents a set of methods based on input-output analysis to measure the size and structure of a country's information economy. Published current national data bases do not identify even the broad contours of a country's information economy. The methodology which is stylised algebraically using input-output modelling unravels the latent information economy. Both the primary or marketed information activities and the non-marketed or secondary information activities are measured. The interdependencies of the primary and secondary information sectors with the non-information sectors such as agriculture and manufacturing are examined. Linkages and multipliers are also calculated using consistent approaches. Finally, the methodology is empirically validated using Australia as a case-study and the results are discussed.The author acknowledges with thanks useful comments by referees of the journal on an earlier draft of this paper. The author is also grateful to Professor D.Mc Lamberton of the University of Queensland and Professor M. Jussawalla of the East-West Center, Hawaii, for their encouragement and support given to this study.     

Understanding the economic determinants of the severity of operational losses: A regularized generalized Pareto regression approach

We investigate a novel database of 10,217 extreme operational losses from the Italian bank UniCredit. Our goal is to shed light on the dependence between the severity distribution of these losses and a set of macroeconomic, financial, and firm‐specific factors. To do so, we use generalized Pareto regression techniques, where both the scale and shape parameters are assumed to be functions of these explanatory variables. We perform the selection of the relevant covariates with a state‐of‐the‐art penalized‐likelihood estimation procedure relying on L₁‐penalty terms. A simulation study indicates that this approach efficiently selects covariates of interest and tackles spurious regression issues encountered when dealing with integrated time series. Lastly, we illustrate the impact of different economic scenarios on the requested capital for operational risk. Our results have important implications in terms of risk management and regulatory policy.     

A social information processing approach to job attitudes and task design.

This article outlines a social information processing approach to explain job attitudes. In comparison with need-satisfaction and expectancy models to job attitudes and motivation, the social information processing perspective emphasizes the effects of context and the consequences of past choices, rather than individual predispositions and rational decision-making processes. When an individual develops statements about attitude or needs, he or she uses social information--information about past behavior and about what others think. The process of attributing attitudes or needs from behavior is itself affected by commitment processes, by the saliency and relevance of information, and by the need to develop socially acceptable and legitimate rationalizations for actions. Both attitudes and need statements, as well as characterizations of jobs, are affected by informational social influence. The implications of the social information processing perspective for organization development efforts and programs of job redesign are discussed.     

Modelling international sovereign risk information spillovers: A multilayer network approach

Applying the TVP-VAR model, we creatively construct multilayer information spillover networks containing return spillover layer, volatility spillover layer and extreme risk spillover layer among 23 countries in the G20 to explore international sovereign risk spillovers. From the perspective of system-level and country-level measures, this article explores the topological structures of static and dynamic multilayer networks. We observe that (i) at the system-level, multilayer measures containing uniqueness edge ratio and average edge overlap show each layer has unique network structures and spillover evolution behavior, especially for dynamic networks. Average connectedness strength shows volatility and extreme risk spillover layers are more sensitive to extreme events. Meanwhile, three layers have highly intertwined and interrelated relations. Notably, their spillovers all show a great upsurge during the crisis (financial and European debt crisis) and the COVID-19 pandemic period. (ii) At the country-level, average overlapping net-strength shows that countries’ roles are different during distinct periods. Multiplex participation coefficient on out-strength indicates we’ll focus on countries with highly heterogeneous connectedness among three layers during the stable period since their underestimated spillovers soar in extreme events or crises. Multilayer networks supply comprehensive information that cannot obtain by single-layer.     

A computational intelligent approach to multi-factor analysis of violent crime information system

Various scientific studies have explored the causes of violent behaviour from different perspectives, with psychological tests, in particular, applied to the analysis of crime factors. The relationship between bi-factors has also been extensively studied including the link between age and crime. In reality, many factors interact to contribute to criminal behaviour and as such there is a need to have a greater level of insight into its complex nature. In this article we analyse violent crime information systems containing data on psychological, environmental and genetic factors. Our approach combines elements of rough set theory with fuzzy logic and particle swarm optimisation to yield an algorithm and methodology that can effectively extract multi-knowledge from information systems. The experimental results show that our approach outperforms alternative genetic algorithm and dynamic reduct-based techniques for reduct identification and has the added advantage of identifying multiple reducts and hence multi-knowledge (rules). Identified rules are consistent with classical statistical analysis of violent crime data and also reveal new insights into the interaction between several factors. As such, the results are helpful in improving our understanding of the factors contributing to violent crime and in highlighting the existence of hidden and intangible relationships between crime factors.     

The characteristics of technically orientated firms: Evidence from the unlisted securities market

The results of a survey of the research, design and development activity of firms listed on the UK Unlisted Securities Market are reported. The significance of different corporate objectives, types of market structure, forms of rivalry, different groups as project initiators, and techniques of project evaluation, is reported. Technically progressive firms could not be distinguished from less technically progressive firms using univariate tests. Multiple discriminant analyses indicated that technically progressive firms operate in markets where products characteristics and advertising are significant forms of rivalry, the growth rate of profits is more important as a corporate objective and the significance of interdepartmental committees as an initiating group is higher than for less technically progressive firms. The latter firms judged price competition and the objective of achieving a target level of units sold as more significant than the former group.     

An empirical approach to the organisational determinants of spin-off creation in European universities

Given the importance in recent years of the phenomenon of academic entrepreneurship in European universities, knowledge about determinants and performance of this technology transfer mechanism may have important managerial and policy implications. Applying the resource-based view at universities, we have tested the influence of five bundles of resources and capabilities on spin-off activity rates as well as on the performance of new spin-offs in a sample of seven European universities. These five bundles are: technology transfer policies and strategies; human capital; stock of technology; resources and capabilities of technology transfer offices; and support measures for academic entrepreneurship. Our results show that excellence of human capital and the presence of university-based financial support measures are strongly associated with both spin-off activity and performance. Another interesting finding is related to the availability of university-based non-economic support measures (training, counselling, etc.), which have no influence on spin-off activity but are significantly associated with performance of new spin-offs. We also discuss some interesting relationships between explanatory variables.     

Socio-institutional determinants of educational resource efficiency according to the capability approach: An endogenous stochastic frontier analysis

We investigate the role of private and public resources in educational attainments and the socio-institutional determinants of educational resource efficiency in Italy. Following the Sen's capability approach, we consider social capital and the quality of government part of the social conversion factors through which resources can be converted into human capabilities, such as education. We analyze the case of Italy by constructing a new longitudinal dataset from 1993 to 2012, using repeated cross sections from the main social survey of the Italian Statistical Institute and a panel stochastic frontier model that takes into account endogeneity. The results show the relative importance of private resources (measured by an ad hoc constructed wealth index), the complementarity between private wealth and public expenditures on education, and the positive impact of social capital and the quality of government on educational resource efficiency.     

Credit risk pricing and the rationality of lending decision-making within dual banking systems: A parametric approach

The reduction of non-performing loans, and making correct provisions for them, plays a primary role in the management and minimization of banking credit risk. However, these actions depend primarily upon the cost at which banks may dispose of these bad loans. Hence, this study aims to perceive the price of banks’ credit risk via estimating the shadow price of non-performing loans. We assess and compare the perceived price of the credit risk of Islamic and conventional banks operating in 9 countries from the Middle East and Asia, using a quadratic directional distance function. Following this, we evaluate the impact of different settings of directional vectors on shadow prices by conducting a risk-sensitivity analysis. Applying bootstrap regression, the factors affecting NPLs’ prices are further investigated. The paper concludes that the estimation of the shadow prices of bad loans can provide important elements in favor of credit risk management and, therefore, credit risk mitigation.     

Concept-based query language approach to enterprise information systems

In enterprise information systems (EISs) it is necessary to model, integrate and compute very diverse data. In advanced EISs the stored data often are based both on structured (e.g. relational) and semi-structured (e.g. XML) data models. In addition, the ad hoc information needs of end-users may require the manipulation of data-oriented (structural), behavioural and deductive aspects of data. Contemporary languages capable of treating this kind of diversity suit only persons with good programming skills. In this paper we present a concept-oriented query language approach to manipulate this diversity so that the programming skill requirements are considerably reduced. In our query language, the features which need technical knowledge are hidden in application-specific concepts and structures. Therefore, users need not be aware of the underlying technology. Application-specific concepts and structures are represented by the modelling primitives of the extended RDOOM (relational deductive object-oriented modelling) which contains primitives for all crucial real world relationships (is-a relationship, part-of relationship, association), XML documents and views. Our query language also supports intensional and extensional–intensional queries, in addition to conventional extensional queries. In its query formulation, the end-user combines available application-specific concepts and structures through shared variables.