Search

Spatial data are becoming increasingly accessible to urban scientists, but these data are often prone to measurement error. Motivated by the analysis of the Milan (Italy) apartment market heterogeneity, we propose a semiparametric approach to adjust for the presence of measurement error in the covariates when estimating M-quantile regression. The M-quantile approach helps explain the heterogeneity across individual units, preserving robustness and efficiency in the estimates. The model’s parameters are estimated within a penalised likelihood framework and an analytical expression is proposed to estimate standard errors. Asymptotic properties of estimates are also provided.

Is actual income inequality accurately translated into people's perceptions, and what are the genuine hopes of citizens? Our contribution offers insights into how the reality and two subjective dimensions of income inequality, namely perceptions, and desires, interact. Using data from the Eurobarometer, we study the main patterns of different ‘types’ of inequality (measured by S80/S20 ratio) in the regions of the EU Member States. Considering the role of attitudes and beliefs, the residents of the same region are typically found to hold a similar perception of how unequal their society is. Moreover, and somewhat surprisingly, the reality is contrary to people's perception since low (high) actual income inequality in the region is often reflected in its overestimated (underestimated) perception. We also show that perceived, and desired inequality are distinct metrics as commonly applied determinants of perceptions are rather weakly associated with desired inequality, probably due to the normative nature of the latter. The evidence presented here implies that objective measures of income inequality should be used in conjunction with subjective ones to gain a complete picture of the phenomenon. Our findings may assist policy-makers and other interested stakeholders in designing dedicated policies to counteract inequality in all its forms.

This paper provides a comprehensive overview of intergenerational income mobility in Sweden. Intergenerational income mobility is considered in both relative and absolute terms, and the analysis is carried out at the individual and municipality level. We use multilevel models to explore the correlation between upward mobility and social, economic and demographic characteristics of cities. We account for a wider set of local characteristics, such as the spatial distribution of income inequality within city and housing affordability that have not been considered by previous studies analysing social mobility in the United States or other European countries. The analyses are carried out on three subpopulations: offspring who live in a different municipality than their parents (spatial mobile population); offspring who live in the municipality where they grew up (spatial immobile population); offspring belonging to visible minority groups. Our results show substantial differences across municipalities, meaning that the particular combination of municipality attributes contributes to shaping the chance of status attainment among young generations. Highly mobile municipalities have more significant human capital, more residential segregation by income, more local levels of income inequality, and greater accessibility to jobs. The results indicate that dependence on parents’ support and network for upward mobility is of less importance, and that spatial mobility (regardless of background) especially to larger urban areas is associated with upward mobility for the children.

Worldwide thousands of people die annually in highway-related crashes and millions are injured. By 2030 highway-related crashes will be the 5-th leading cause of death in the world according to the WHO (Mannering and Bhat, 2014). The statistical analysis of accident data has historically been fundamental to develop road-safety policies aiming at saving lives and reducing injuries severity. In the absence of detailed driving-related data (such as acceleration and braking) and crash-related data (such as those made available from vehicle black-boxes) that would help improve the identification of cause and effect relationships, a large majority of research has addressed the problem in terms of understanding the factors that affect the frequency of crashes, i.e. the number of crashes occurring in some geographical space over some specified time periods.[...]

This contribution deals with a quite common but relevant issue in insurance. Suppose to be interested in covering a risk (e.g. motor accident, life/health risks, risk of disability, adverse weather events, etc...) and that you want to stipulate a contract to protect yourself against the loss of economic resources in case that the event occurs. In such circumstances any insurer will ask you to pay an amount (called premium) that approximately equals the pure premium (i.e. the amount that corresponds to the expected loss times the odds of the event) plus the so called loadings (i.e. the amount of money that consider both the gain of the contractor and administrative/process costs). The challenging point is: how to compute the odds? In particular, how to compute the probability of an adverse event given covariates that should be considered explanatory of the risk? [...]

We propose an innovative methodology to measure inequality between cities. If an even distribution of amenities across cities is assumed to increase the average well-being in a given country, inequality between cities can be evaluated through a multidimensional index of the Atkinson (1970) type. This index is shown to be decomposabe into the sum of inequality indices computed on the marginal distributions of the amenities across cities, plus a residual term accounting for their correlation. We apply this methodology to assess inequality between Italian cities in terms of the distribution of public infrastructures, local services, economic and environmental conditions.

The effects of fiscal decentralization on economic growth are analyzed. A theoretical framework is developed that builds on the relationships between government size and growth and between decentralization and government size. The framework is tested empirically on a panel of 25 European countries observed between 1995 and 2015. The econometric results show that the relationship between expenditure decentralization and growth is bell shaped. The paper also focuses on expenditure composition. In this respect, the relationship between investment decentralization and growth is an inverted bell-shaped curve: there is a critical mass of decentralized investments beyond which it is possible to enhance growth.

In this paper we exploit data at regional level on decentralized public expenditure provided by Conti pubblici territoriali from 1996 to 2014 and we decompose decentralized public expenditure into current and capital spending. The aim is to disentangle their specific effect on economic growth. Since literature does not provide unanimous indication about the effect of different component of expenditure on growth, we consider a generalized additive model, which is a semi-parametric estimation method that allows more flexibility than conventional estimation techniques. Our findings show a non-linear effect, that is different according to categories of expenditure. More specifically, the effect of capital expenditure is positive, while, decentralized current expenditure tends to have a negative effect on the rate of economic growth.