Predicting sovereign debt crises using artificial neural networks: A comparative approach

Recent episodes of financial crisis have revived interest in developing models able to signal their occurrence in timely manner. The literature has developed both parametric and non-parametric models, the so-called Early Warning Systems, to predict these crises. Using data related to sovereign debt crises which occurred in developing countries from 1980 to 2004, this paper shows that further progress can be achieved by applying a less developed non-parametric method based on artificial neural networks (ANN). Thanks to the high flexibility of neural networks and their ability to approximate non-linear relationship, an ANN-based early warning system can, under certain conditions, outperform more consolidated methods.     

On the distributional properties of size, profit and growth of Icelandic firms

In this paper, we analyze the distributional properties of the balance sheets of Icelandic firms by performing an empirical analysis of total assets, profit rates and growth rates using a data set of 2,818 Icelandic firms during the period 2000–2009. We find that the firms size measure, i.e. total assets, have the same heavy tail characteristics as various studies have shown, e.g. for US and Italian firms. The heavy tail nature of the total assets distribution seems to be robust w.r.t. a boom-bust cycle of the economy as well as special characteristics of Icelandic firms, e.g. their relatively small size and private ownership. Another important finding is that the profit rates, or return on assets, of Icelandic firms follow a Laplace like distribution similar to US firms. Additionally, we identified deviations from the distributional regularities, namely the power law behavior of firms’ size and Laplacian distributions of growth and profit rates, during the booming period of the economy 2005–2007.     

Feeling lonely at work: investigating the consequences of unsatisfactory workplace relationships

Although prior literature reveals that loneliness is a pervasive problem among adults, little research has evaluated the impact of loneliness in the workplace. Given that workplace relationships underlie many important organizational phenomena, it is important to understand whether and how workplace loneliness affects employee behavior. Based on the social exchange model, we hypothesize that in comparison with their non-lonely counterparts, lonely employees will experience lower quality leader‐member and organization‐member exchanges at work such that they will tend to be worse at in-role and extra-role workplace functions. Drawing on the results of our survey of schoolteachers, we present findings to support our hypotheses.     

Effective teamwork at the top: the evidence from China

Effective teamwork is an important topic of human resource management, and how top-level managers work effectively as a team is critical to business success. Prior research indicates that the diverse background of top managers influences the effectiveness of their teamwork, and the effects of top management team (TMT) diversity on organizational innovation varies. In this study, we propose that functional team dynamics plays a crucial role in facilitating TMT effectiveness. On the basis of a sample of Chinese firms, our findings support the distinction between demographic and network diversities and the moderating effect of functional team dynamics on TMT diversity–firm innovation relationships.     

Socio-Economic Impact of Super Typhoon Harurot in San Mariano, Isabela, the Philippines

This paper reports on the socio-economic effects and coping mechanisms of farm households affected by super typhoon Imbudo in San Mariano, Isabela, the Philippines. Estimations of economic losses are given based on 150 interviews among the rural population. The relative loss per crop as part of the annual household income for yellow corn, banana, and rice were 64%, 24%, and 27%, respectively. Unexpectedly, most farm households did not change their agricultural strategies and continued with “business as usual” (78%). The main explanation for this lack of adaptation is found in the cultural and societal structure of farm households and their traders. This paper concludes with a short-term and long-term vulnerability and resilience analysis for the households, the socio-agricultural system, and the ecological system.     

RISK MEASURES AND CAPITAL REQUIREMENTS FOR PROCESSES

In this paper we propose a generalization of the concepts of convex and coherent risk measures to a multiperiod setting, in which payoffs are spread over different dates. To this end, a careful examination of the axiom of translation invariance and the related concept of capital requirement in the one-period model is performed. These two issues are then suitably extended to the multiperiod case, in a way that makes their operative financial meaning clear. A characterization in terms of expected values is derived for this class of risk measures and some examples are presented.     

A stochastic programming model to analyze ordinal preference data

Many marketing situations require analysis of ordinal preference data. Existing analysis methods include OLS, variations of the logit model and methods such as LINMAP. An alternative method is proposed that has the following features: 1) Tie rankings are allowed; 2) all rank order information is incorporated into the estimation — not just first preferences; 3) the procedure is formulated as a L.P. model, which is easily implemented with existing software; 4) statistical inference is supported by the underlying stochastic model; and 5) it supports estimation of individual and group preferences.