Financial Literacy: The Role of the Local Context

In this article, we investigate the role of local factors associated with the financial literacy of Italian adults (no. 945). Using a multilevel regression model, together with the common socioeconomic and sociodemographic variables already used in previous studies, we also add certain environmental variables at the local level. We separately analyze the three indexes that define the OECD financial literacy index—Financial Attitude Index (FAI), Financial Knowledge Index (FKI), and Financial Behavior Index (FBI)—because they show a dynamic of their own in each region. Our findings confirm that the FKI and the FAI are associated to some extent with environmental traits, while the FBI is not. We conclude that not only the sociodemographic and socioeconomic conditions of individuals but also certain features of the regional context where they live have an impact on their financial literacy. Consequences for financial education programs are highlighted.     

Modelling tourism flows through gravity models: a quantile regression approach

Gravity models are widely used to study tourism flows. The peculiarities of the segmented international demand for agritourism in Italy are examined by means of a novel approach: a panel data quantile regression. We characterize the international demand for Italian agritourism with a large data set, by considering data of 33 countries of origin, from 1998 to 2010. Distance and income are the major determinants, but we also found that mutual agreements and high urbanization rates in countries of origin are associated with larger flows of incoming tourists.     

Fiscal rule compliance,poverty and social exclusion in the Eurozone

This paper develops a simple model of the effects of fiscal adjustments on poverty. Our theory suggests that in richer countries the effects of fiscal adjustment are stronger the more complex is the poverty measure. By examining a panel of 16 EU countries in the period 2005–2015, the paper finds that structural public balance adjustments may harm the welfare of poorer individuals. The empirical estimation hinges on a comprehensive index of poverty and social exclusion, the AROPE index. The results suggest that rigid fiscal rules require specific alternative policies to sustain the welfare of poorer individuals during downturns.     

Karl Pearson and the Origin of Kurtosis

Although the kurtosis index proposed by Karl Pearson in 1905 is introduced in statistical textbooks at all levels, the measure is not easily interpreted and has been a subject of considerable debate. In this study, the theoretical development of kurtosis is surveyed from a historical perspective of Pearson's work on evolution. It surprisingly emerges that there was no emphasis in Pearson's papers on kurtosis as measuring (in part) tail heaviness. However, it is found that Pearson used to frequently adjust the formalisation of kurtosis depending on his changing needs. This complex development partly explains the confusion that would surround kurtosis in subsequent literature. Our conclusion is that most misunderstandings arise from improper use of the kurtosis coefficient outside the Pearson system of frequency curves.     

“To Own or Not to Own?” A Study on the Determinants and Consequences of Alternative Intellectual Property Rights Arrangements in Crowdsourcing for Innovation Contests

Firms are increasingly engaging in crowdsourcing for innovation to access new knowledge beyond their boundaries; however, scholars are no closer to understanding what guides seeker firms in deciding the level at which to acquire rights from solvers and the effect that this decision has on the performance of crowdsourcing contests. Integrating property rights theory and the problem‐solving perspective while leveraging exploratory interviews and observations, we build a theoretical framework to examine how specific attributes of the technical problem broadcast by firms affect the seekers’ choice between alternative intellectual property rights (IPR) arrangements that call for acquiring or licensing‐in IPR from external solvers (i.e., with high and low degrees of ownership, respectively). Each technical problem differs in the knowledge required to be solved as well as in the stage of development of the innovation process and seeker firms pay great attention to such characteristics when deciding about the IPR arrangement they choose for their contests. In addition, we analyze how this choice between acquiring and licensing‐in IPR, in turn, influences the performance of the contest. We empirically test our hypotheses analyzing a unique dataset of 729 challenges broadcast on the InnoCentive platform from 2010 to 2016. Our results indicate that challenges related to technical problems in later stages of the innovation process are positively related to the seekers’ preference toward IPR arrangements with a high level of ownership, while technical problems involving a higher number of knowledge domains are not. Moreover, we found that IPR arrangements with a high level of ownership negatively affect solvers’ participation and that IPR arrangement play a mediating role between the attributes of the technical problem and the solvers’ self‐selection process. Our paper contributes to the open innovation and crowdsourcing literature and provides practical implications for both managers and contest organizers.     

A latent class conjoint analysis for the Administrative Clerk figure: insights from ELECTUS

Quality & Quantity - ELECTUS is a multi-centre research project with the aim to stabilize the relationship between universities and companies. Through this project, it is possible to acquire...     

Bank loan recovery rates: Measuring and nonparametric density estimation

In this paper we analyse a comprehensive database of 149,378 recovery rates on Italian bank loans. We investigate a new methodology to compute the recovery percentage that we suggest to consider as a mixed random variable. To estimate the probability density function of such a mixture, we propose the mixture of beta kernels estimator and we analyse its performance by Monte Carlo simulations. The application of these proposals to the Bank of Italy’s data shows that, even if we remove the endpoints from the support of the recovery rate, the density function estimate is far from being a beta function.     

Cross-country diffusion of photovoltaic systems: Modelling choices and forecasts for national adoption patterns

In this paper we propose an innovation diffusion framework based on well-known Bass models to analyze and forecast national adoption patterns of photovoltaic installed capacity. This allows for interesting comparisons among several countries and in many cases highlights the positive effect of incentive policies in stimulating the diffusion of such a technology. In this sense, the Generalized Bass Model proves to be essential for modelling and forecasting. On this basis, we observe important differences in the investments made by countries in the PV sector and we are able to identify whether and when these investments obtained the expected results. In particular, from our analysis it turns out that in some cases incentive measures have been certainly effective in facilitating adoption, while in some others these have not been able to produce real feed-back. Moreover, our cross-country approach is able to forecast different stages in PV evolution: whereas some countries have already entered the mature stage of diffusion, others have just begun. This result may suggest various considerations about the competitive advantage of those countries that invested in alternative energy provisions. In spite of a very diversified scenario in terms of historical patterns of diffusion, we may report, as a general result, the fragile role of innovators for this special market and the dominance of imitative behaviour in adoptions.     

Market potential dynamics in innovation diffusion: Modelling the synergy between two driving forces

The presence of a slowdown in new product life cycles has recently received notable attention from many innovation diffusion scholars, who have tried to explain and model it on a dual-market hypothesis (early market-main market). In this paper we propose an alternative explanation for the slowdown pattern, a dual-effect hypothesis, based on a recent co-evolutionary model, where diffusion results from the synergy between two driving forces: communication and adoption. An analysis of the synergistic interaction between communication and adoption, based on the likelihood ratio order or on a weak stochastic order, can inform us of which of the two had a driving role in early diffusion. We test the model on the sales data of two pharmaceutical drugs presenting a slowdown in their life cycle and observe that this is identified almost perfectly by the model in both cases. Contrary to the general expectation, according to which communication should precede adoption, our findings show that adoptions may be the main driver in early life cycle; this may be related to the drug's specific nature.