Background: Several studies have demonstrated that self-rated health status is affected by socioeconomic variables. However, there is little knowledge about whether perceived economic resources affect people’s health. The purpose of this study is to examine the relationship between self-rated health status and different measures of income. Specifically, the effect of both objective income and perceived economic resources are estimated for a very large sample of households in Italy. By estimating this relationship, this paper aims at filling the previously mentioned gap. Methods: The data used are from the 2015 European Health Interview Survey and were collected using information from approximately 16,000 households in 562 Italian municipalities. Ordinary and generalized ordered probit models were used in estimating the effects of a set of covariates, among others measures of income, on the self-rated health status. Results: The results suggest that the subjective income, measured by the perceived economic resources, affects the probability of reporting a higher self-rate health status more than objective income. The results also indicate that other variables, such as age, educational level, presence/absence of chronic disease, and employment status, affect self-rated health more significantly than objective income. It is also found that males report more frequently higher rating than females. Conclusions: Our analysis demonstrates that perceived income affects significantly self-rated health. While self-perceived economic resources have been used to assess economic well-being and satisfaction, they can also be used to assess stress levels and related health outcomes. Our findings suggest that low subjective income adversely affects subjective health. Therefore, it is important to distinguish between effects of income and individuals’ perceptions of their economic resources or overall financial situation on their health. From a gender perspective, our results show that females are less likely to have high rating than males. However, as females perceive an improved economic situation, on the margin, the likelihood of a higher self-rated health increases compared to males.

Greenhouse gas emissions, produced by various sectors, including transportation, are significantly impairing the environment and drive climate change. Battery electric vehicles are increasingly seen as a way to alleviate these problems, but they must be charged with electricity produced through environmentally friendly methods. This paper investigates a possible relationship between battery electric vehicles and solar photovoltaic panels using ENABLE.EU household survey data from ten European countries in autumn 2017–spring 2018. Based on the estimates from a recursive bivariate probit model, it is found that the probability that a household owns a battery electric vehicle increases significantly if said household owns solar photovoltaic panels. This suggests that a policy encouraging the home charging of battery electric vehicles using solar photovoltaic panels that includes an energy storage facility could speed up the transition to the use of these vehicles.

The aim of this study is to explore the factors that influence the material footprint (MF), which represents the total amount of raw materials used in the production of goods and services. MF provides a more comprehensive measure of resource use across supply chains, capturing aspects of environmental degradation not addressed by conventional indicators. MF serves as a measure of material consumption across global supply-chain networks that connect production and consumption. Moreover, reducing the MF can promote efficient resource use and encourage sustainable production and consumption patterns. In this study, we explore what socioeconomic determinants affect MF in the European Union. We have utilized a dataset comprising observations from unbalanced panel data of 27 European countries spanning the period from 2000 to 2021. The main findings suggest that GDP (Gross Domestic Product) per capita, the industry share, fertility rate, and taxes contribute to an increase in MF, while the degree of urbanization, research and development (R&D), and resource productivity rate reduce MF. Our findings have policy relevance within the EU’s sustainability goals, providing insights into the factors that can drive resource efficiency as outlined in the Circular Economy (CE) Action Plan.

This study concerns factors influencing international tourists’ length of overnight stay in Venice. The data are from a survey conducted by the Bank of Italy on international tourism. Both zero-truncated negative binomial (ZTNB) and ordinary least squares (OLS) regressions are estimated. In general, the estimates from ZTNB and OLS regressions are similar. The results suggest that age, returning directly to the country of residence and the summer season have a positive influence on the length of stay. On the other hand, international tourist expenditure and visiting other places than Venice have a negative impact on the length of stay. Moreover, the average length of overnight stays differs among nationalities and those who have visited Venice previously tend, on average, to stay longer. One finding is that visitors from North America and Australia stay longer and spend more than visitors coming from neighbouring countries.

Visitors to big tourist cities are very likely heterogeneous and can be classified into different segments, for example, low and high spenders. Previous studies on visitor expenditure-based segmentation seem to have only taken into account observed heterogeneity, usually segmenting tourists based on observed characteristics. In the present study, however, the visitors to Venice, Italy, are segmented with respect to their spending into different groups based on both observed and unobserved heterogeneity using a finite mixture model. The results indicate that the visitors belong to three latent classes with respect to their expenditure. Interestingly, different variables affect expenditure differently depending on the latent class belonging. The overall conclusion is that segmenting tourists into different classes based on unobserved heterogeneity with respect to their spending is preferable and more informative than treating the visitors as one homogeneous group. The approach is also more useful for different types of policymaking.