On the value of participation: endogenous emergence of social norms in a three-player ultimatum game experiment

We report results from two different settings of a three-player ultimatum game. Under the “Monocratic” rule, a player is randomly selected to make an offer to two receivers. Under the “Democratic” rule, all three players make a proposal, and one proposal is then randomly selected. A majority vote is required to implement the proposal in either setting. Although the two rules are strategically equivalent, different patterns of behaviour emerge as the number of interactions increase. Under the “Monocratic” rule, proposers seem to be entitled to claim a larger share of the pie, and receivers are more likely to accept, than in the “Democratic” rule. We speculate that institutions allowing more participation in the process of collective choice lead to a more socially responsible behaviour in individuals.     

Using artificial neural network and multivariate analysis techniques to evaluate road operating conditions

Regional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1).     

Measuring the relative development and integration of EU countries’ capital markets using composite indicators and cluster analysis

Review of World Economics - The paper proposes a set of metrics and a methodology to measure the progress that European Union Member States are making towards the development and integration of...     

Are valuation effects desirable from a global perspective?

Recent studies have emphasized the role of valuation effects due to exchange rate movements in easing the process of adjustment of the external balance of a country. This paper asks to what extent valuation effects are desirable from a global perspective as a mean to achieve an efficient allocation of resources. In a frictionless world, it is desirable to have large movements in prices and exchange rates. But once a small degree of price rigidity is introduced not only should prices be stabilized but also the response of the exchange rate should be muted. There is a minor role for valuation effects that depends both on the size and composition of assets and liabilities.     

Urban Economic Openness and IPO Underpricing

This paper represents a first attempt to employ a macroeconomic approach to explain the high and varying IPO underpricing within a single emerging market. We examine the empirical impact of trade openness on the short-run underpricing of initial public offerings (IPOs) using city-level data. Particularly, we argue that urban economic openness (UEO) has a significant impact on the productivity and on prices of both direct and indirect real estate due to productivity gains of companies in more open areas. This in turn positively affects the firm’s profitability, enhancing the confidence in local real estate markets and future company performance, hence decreasing the uncertainty of the IPO valuation. As a result, issuers have less incentive to underprice IPO shares. We use a sample of Chinese real estate IPOs, which offer a suitable laboratory thanks to their strong geographic investment patterns focused locally and a country with a highly heterogeneous openness across regions. Controlling for traditional firm- and issuing-specific characteristics of IPOs that are used for developed markets and Chinese-related features (i.e. listing location and state ownership), we find the evidence that companies investing in economically more open areas experience less IPO underpricing. Our results show great explanatory power and are robust to different specifications.