activity
20132021
most citedMeasurement error induced by locational uncertainty when estimating discrete choice models with a distance as a regressor

1 citations · 2 across the 4 of their papers we have counts for

collaborators

8 papers

stat.ME2021

Spatial sampling design to improve the efficiency of the estimation of the critical parameters of the SARS-CoV-2 epidemic

Giorgio Alleva, Giuseppe Arbia, Piero Demetrio Falorsi +2

The pandemic linked to COVID-19 infection represents an unprecedented clinical and healthcare challenge for many medical researchers attempting to prevent its worldwide spread. Thi…

q-bio.QM20201 cited

Observed and estimated prevalence of Covid-19 in Italy: Is it possible to estimate the total cases from medical swabs data?

Francesca Bassi, Giuseppe Arbia, Pietro Demetrio Falorsi

During the current Covid-19 pandemic in Italy, official data are collected with medical swabs following a pure convenience criterion which, at least in an early phase, has privileg…

stat.AP2020

A sample approach to the estimation of the critical parameters of the SARS-CoV-2 epidemics: an operational design

Giorgio Alleva, Giuseppe Arbia, Piero Demetrio Falorsi +2

Given the urgent informational needs connected with the diffusion of infection with regard to the COVID-19 pandemic, in this paper, we propose a sampling design for building a cont…

stat.ME2020

Post-sampling crowdsourced data to allow reliable statistical inference: the case of food price indices in Nigeria

Giuseppe Arbia, Gloria Solano-Hermosilla, Fabio Micale +2

Sound policy and decision making in developing countries is often limited by the lack of timely and reliable data. Crowdsourced data may provide a valuable alternative for data col…

stat.AP2020

A Note on Early Epidemiological Analysis of Coronavirus Disease 2019 Outbreak using Crowdsourced Data

Giuseppe Arbia

Crowdsourcing data can prove of paramount importance in monitoring and controlling the spread of infectious diseases. The recent paper by Sun, Chen and Viboud (2020) is important b…

stat.ME2019

Reduced-bias estimation of spatial econometric models with incompletely geocoded data

Giuseppe Arbia, Maria Michela Dickson, Giuseppe Espa +2

The application of state-of-the-art spatial econometric models requires that the information about the spatial coordinates of statistical units is completely accurate, which is usu…