New perspectives for the quality of sub-municipal data with the Italian permanent population and housing census

Author:

Carbonetti Giancarlo1ORCID,Daddi Stefano1,De Matteis Giampaolo1,Di Zio Marco1ORCID,Fardelli Davide1,Ferrara Raffaele1ORCID,Lipizzi Fabio1,Orsini Enrico1ORCID

Affiliation:

1. ISTAT, Italian National Institute of Statistics, IT

Abstract

Over the years, official statistics have shown increasing attention to the territory in providing detailed and quality information and, in this sense, the Population and Housing Census has always guaranteed the availability of sub-municipal data useful for decision-making processes in the social, economic and environmental fields. The Istat modernization programme introduced the Permanent Census that, differently from the traditional decennial census essentially drew on collecting data from people, is strongly based on the integration of administrative and sample data, and planned for providing yearly statistical figures. This change requires new methodological and IT architectures. It is a revolution that – on the medium term – is expected to provide more stable and coherent figures at various territorial levels.In this framework, sub-municipal data derives from the integration of the Basic Register of Individuals and the Basic Register of Places. The quality of data depends on the quality of the Registers and the procedures adopted to integrate and elaborate input data. In this regard, Istat is working to improve the geocoding information and linkage procedures. One of the problem encountered is that of non-geocoded units. These are units without an allocation into an enumeration area because of problems in administrative data. Istat has studied a procedure integrating deterministic and probabilistic approaches for assigning the enumeration area to those critical units. An experimental study is carried out to evaluate the quality of the imputation procedure. In this paper, we discuss the approach adopted, the evaluation process, the results obtained and the impact on the quality of the data and the spatial analyses that can be carried out.

Publisher

Firenze University Press and Genova University Press

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3