Review Essay

Sen's capability approach has a culturally specific side, with capabilities influenced by social structures and institutions. Although Sen acknowledges this, he expresses his theory in individualistic terms and makes little allowance for culture or social structure. The present paper draws from recent social theory to discuss how the capability approach could be developed to give an explicit treatment of cultural and structural matters. Capabilities depend not only on entitlements but on institutional roles and personal relations: these can be represented openly if capabilities are disaggregated into individual, social and structural capacities. The three layers interact, and a full analysis of capabilities should consider them all. A stratified method implies that raising entitlements will not on its own be enough to enhance capabilities and that cultural and structural changes will be needed.     

International network extension processes to institutionally different markets: Entry nodes and processes of exporting SMEs

This article is about how SMEs reduce their liability of network outsidership in the process of establishing a network insider position in foreign business networks. By examining how SMEs establish insidership positions in institutionally different business networks, the authors contributes to the network approach to firm internationalization. From a detailed longitudinal and retrospective case study of four SMEs from mature market entering emerging country markets and four SMEs from such immature markets entering mature markets, the authors develop propositions based on intra-group and inter-group analysis. The propositions concern the parties to which the exporter initiates and develops relationships when plugging into the foreign network (the entry node), and how the firm reaches an insider position in this network (the entry process). Three distinct network types are identified along this entry process: the exposure network, the formation network and the sustenance network.     

A preference foundation for constant loss aversion

Following prospect theory and in particular the concept of loss aversion, introduced by Kahneman and Tversky (1979), we consider decision making under risk in which the decision maker’s preferences depend on a reference outcome. An outcome below this reference outcome is regarded as resulting from a loss: a loss decreases the decision maker’s basic utility more than a comparable gain increases this utility. An elegant and simple way to model this phenomenon was proposed by Shalev (2002): the utility of an outcome below the reference outcome is obtained from the basic utility by subtracting a multiple of the loss in basic utility: this multiple, the loss aversion coefficient, is constant across different reference outcomes. We provide a preference foundation for this loss aversion model.     

The relevance of irrelevance in brand communication

Brand managers strive to achieve an outstanding position in the psyche of the user by differentiating the product and service. In order to do so, brands are now often promoted by communications that focus on a trivial attribute difference. The current study tests both how the use of such an irrelevant attribute affects the perceptions of the consumer and how they rate the brand when the irrelevance of the attribute is previously revealed. The results of a controlled experiment (n = 894) show that the use of irrelevant attributes generally has a positive effect on buying behavior and that this effect is obtained even when the actual irrelevance is previously proven to the consumer. Further, the results are consistent across a variety of outcome variables, including attention, perceived uniqueness, price fairness, attitude toward the brand, and intention to buy the brand. © 2010 Wiley Periodicals, Inc.     

A constraint-free approach to optimal reinsurance

Reinsurance is available for a reinsurance premium that is determined according to a convex premium principle H. The first insurer selects the reinsurance coverage that maximizes its expected utility. No conditions are imposed on the reinsurer's payment. The optimality condition involves the gradient of H. For several combinations of H and the first insurer's utility function, closed-form formulas for the optimal reinsurance are given. If H is a zero utility principle (for example, an exponential principle or an expectile principle), it is shown, by means of Borch's Theorem, that the optimal reinsurer's payment is a function of the total claim amount and that this function satisfies the so-called 1-Lipschitz condition. Frequently, authors impose these two conclusions as hypotheses at the outset.     

Spatial propagation of macroeconomic shocks in Europe

This paper implements a spatial vector autoregressive model that takes into account both the time and the spatial dimensions of economic shocks. We apply this framework to analyze the propagation through space and time of macroeconomic (inflation, output gap and interest rate) shocks in Europe. The empirical analysis identifies an economically and statistically significant spatial component in the transmission of macroeconomic shocks in Europe.     

Comparing spatial concentration and assessing relative market structure in air traffic

Traffic distributions of air traffic and their concentration have been measured through Gini, an index that contrasts in many ways with other more established ones, such as Herfindahl's. This research is extended in the sense that it perceives spatial concentration in air transport as an aggregate of complex networks that are subject to multiple constraints, such as geopolitics or technology. We propose a multi-layered analytic approach where network operators are economic agents that behave in strategic ways. It allows for comparing air traffic between airports in Europe with that of the US and, in particular, introduces a normative component by isolating patterns in airlines' strategies that coincide with more or less welfare-oriented degrees of spatial concentration in light of the above constraints.     

On forecasting cointegrated seasonal time series

We analyze periodic and seasonal cointegration models for bivariate quarterly observed time series in an empirical forecasting study. We include both single equation and multiple equation methods for those two classes of models. A VAR model in first differences, with and without cointegration restrictions, and a VAR model in annual differences are also included in the analysis, where they serve as benchmark models. Our empirical results indicate that the VAR model in first differences without cointegration is best if one-step ahead forecasts are considered. For longer forecast horizons however, the VAR model in annual differences is better. When comparing periodic versus seasonal cointegration models, we find that the seasonal cointegration models tend to yield better forecasts. Finally, there is no clear indication that multiple equations methods improve on single equation methods.