Structural comparisons of networks and model-based detection of small-worldness

In this paper, we consider the problem of assessing the “level of small-worldness” of a graph and of detecting small-worldness features in real networks. After discussing the limitations of classical approaches, based on the computation of network indicators, we propose a new procedure, which involves the comparison of network structures at different “observation scales”. This allows small-world features to be caught, even if “hidden” deeply into the network structure. Applications of the procedure to both simulated and real data show the effectiveness of the proposal, also in distinguishing between different small-world models and in detecting emerging small-worldness in dynamical networks.     

Modeling node heterogeneity in latent space models for multidimensional networks

Multidimensional network data can have different levels of complexity, as nodes may be characterized by heterogeneous individual-specific features, which may vary across the networks. This article introduces a class of models for multidimensional network data, where different levels of heterogeneity within and between networks can be considered. The proposed framework is developed in the family of latent space models, and it aims to distinguish symmetric relations between the nodes and node-specific features. Model parameters are estimated via a Markov Chain Monte Carlo algorithm. Simulated data and an application to a real example, on fruits import/export data, are used to illustrate and comment on the performance of the proposed models.     

Wage bargaining as an optimal control problem: a dynamic version of the efficient bargaining model

Decisions in Economics and Finance - In this paper, I develop a dynamic version of the efficient bargaining model grounded on optimal control in which a firm and a union bargain over the wage in a...     

A unified approach to systemic risk measures via acceptance sets

We specify a general methodological framework for systemic risk measures via multidimensional acceptance sets and aggregation functions. Existing systemic risk measures can usually be interpreted as the minimal amount of cash needed to secure the system after aggregating individual risks. In contrast, our approach also includes systemic risk measures that can be interpreted as the minimal amount of cash that secures the aggregated system by allocating capital to the single institutions before aggregating the individual risks. An important feature of our approach is the possibility of allocating cash according to the future state of the system (scenario‐dependent allocation). We also provide conditions that ensure monotonicity, convexity, or quasi‐convexity of our systemic risk measures.     

On the determinants of data breaches: A cointegration analysis

Decisions in Economics and Finance - Cyber risks and particularly data breaches constitute one of the new frontiers of risk modeling for insurers across the world. We use the cointegration...     

Business investment in euro area countries: the role of institutions and debt overhang

The recovery of business investment in the euro area has been sluggish, thereby hampering aggregate demand in the short term and potential growth in the long run. While we show that business investment can be associated to cost and supply of credit, cyclical demand conditions and economic uncertainty. But we also find evidence of additional factors. We suggest that there exists a link between excess leverage and weak economic institutions on the one hand and subdued investment growth on the other hand. Moreover, in euro area countries with both larger excess leverage and weaker economic institutions, the link with business investment is found to be stronger. The link between investment and weak institutions or excess leverage highlights the importance of structural reforms aimed at easing business regulations, reducing administrative burdens and increasing the efficiency of insolvency frameworks. These reforms are thus expected to reduce distortions in the allocation of resources and be supportive of a smoother deleveraging process, hence fostering business investment.     

Information Asymmetry in Consumer Perceptions of Quality‐Differentiated Food Products

Increasing consumer demand for quality‐differentiated food products has given rise to a large quantity of food product classifications related to production practices and locations. Some food product claims such as native have no clear definitions and may have ambiguous connotations for different consumers. We analyze whether asymmetry in information affects consumer preferences and willingness to pay for ambiguous claims using the native attribute. An empirical application of pecans is used in the analysis to compare native and improved pecan varieties. With no evidence in the literature of additional benefits of native varieties, the results showed that consumers preferred native varieties. Furthermore tastes and preferences for all product attributes were heterogeneous; heterogeneity in preference for the native attribute was only significant at the 10% level.     

The impact of peer ratings on cooperation: The role of information and cost of rating

In this study, we experimentally analyze the effectiveness of payoff‐irrelevant peer‐to‐peer ratings as a cooperation enforcement device in a finitely repeated public goods game setting. We run two treatments that differ in the amount of information on own and others' received rating points provided to the players, whereas, in a third treatment, we analyze peer approval when assigning ratings to others is costly. In particular, we wonder whether, even under anonymity and in the absence of reputational concerns, (a) players rate others' contribution decisions in the expected direction and (b) the peer rating mechanisms under study foster cooperation and welfare. Our findings reveal that, in the two costless rating treatments, peer rating concerns lead to higher contributions and efficiency, compared to our control. Introducing a small fixed cost for assigning rating points results in a very high percentage of subjects deciding not to rate others' behavior, so that cooperation cannot be enforced.     

Higher education and stakeholders’ donations: successful civic crowdfunding in an Italian university

Can civic crowdfunding be used to improve the structures and services offered by public universities? Are stakeholders willing to make donations to such projects? This paper answers these questions by analysing a successful civic crowdfunding project in an Italian university. Stakeholders were found to be willing to engage in crowdfunding and make donations. The key to success is to ensure effective communication and to draw on feelings of belonging to the institution.