Rebecca Graziani

Stochastic population forecasts based on conditional expert opinions.

The paper develops and applies an expert-based stochastic population forecasting method, which can also be used to obtain a probabilistic version of scenario-based official forecasts. The full probability distribution of population forecasts is specified by starting from expert opinions on the future development of demographic components. Expert opinions are elicited as conditional on the realization of scenarios, in a two-step (or multiple-step) fashion. The method is applied to develop a stochastic forecast for the Italian population, starting from official scenarios from the Italian National Statistical Office.

How to Compute a Mean? The Chisini Approach and Its Applications

Scholars often consider the arithmetic mean as the only mean available. This gives rise to several mistakes. Thus, in a first course in statistics, it is necessary to introduce them to a more general concept of mean. In this work we present the notion of mean suggested by Oscar Chisini in 1929, which has a double advantage. It focuses students minds on the substance of the problem for which a mean is required, thus discouraging any automatic procedure, and it does not require a preliminary list of the different mean formulas. Advantages and limits of the Chisini mean are discussed by means of examples.

Stochastic Population Forecasting Based on Combinations of Expert Evaluations Within the Bayesian Paradigm

This article suggests a procedure to derive stochastic population forecasts adopting an expert-based approach. As in previous work by Billari et al. (2012), experts are required to provide evaluations, in the form of conditional and unconditional scenarios, on summary indicators of the demographic components determining the population evolution: that is, fertility, mortality, and migration. Here, two main purposes are pursued. First, the demographic components are allowed to have some kind of dependence. Second, as a result of the existence of a body of shared information, possible correlations among experts are taken into account. In both cases, the dependence structure is not imposed by the researcher but rather is indirectly derived through the scenarios elicited from the experts. To address these issues, the method is based on a mixture model, within the so-called Supra-Bayesian approach, according to which expert evaluations are treated as data. The derived posterior distribution for the demographic indicators of interest is used as forecasting distribution, and a Markov chain Monte Carlo algorithm is designed to approximate this posterior. This article provides the questionnaire designed by the authors to collect expert opinions. Finally, an application to the forecast of the Italian population from 2010 to 2065 is proposed.

Variations and Determinants of Mortality and Length of Stay of Very Low Birth Weight and Very Low for Gestational Age Infants in Seven European Countries

The EuroHOPE very low birth weight and very low for gestational age infants study aimed to measure and explain variation in mortality and length of stay (LoS) in the populations of seven European nations (Finland, Hungary, Italy (only the province of Rome), the Netherlands, Norway, Scotland and Sweden). Data were linked from birth, hospital discharge and mortality registries. For each infant basic clinical and demographic information, infant mortality and LoS at 1 year were retrieved. In addition, socio-economic variables at the regional level were used. Results based on 16,087 infants confirm that gestational age and Apgar score at 5 min are important determinants of both mortality and LoS. In most countries, infants admitted or transferred to third-level hospitals showed lower probability of death and longer LoS. In the meta-analyses, the combined estimates show that being male, multiple births, presence of malformations, per capita income and low population density are significant risk factors for death. It is essential that national policies improve the quality of administrative datasets and address systemic problems in assigning identification numbers at birth. European policy should aim at improving the comparability of data across jurisdictions.