Longitudinal business data construction and quality: Two different approaches
Silvia Biffignandi and
Alessandro Zeli
Statistica Neerlandica, 2021, vol. 75, issue 2, 92-114
Abstract:
Reducing the response burden and widening available statistical information necessitate new approaches in the National Statistical Institutes production process. Our article focuses on longitudinal data needs. Two approaches for building business longitudinal data in a context of cross‐section surveys and administrative sources information are considered. The article describes construction approaches and evaluates the quality of two data bases obtained through multisources integration. The computed databases aim to represent the target population of Italian firms with 20 persons employed and over. The similarity of the distribution of the main economic variables between the target population and the computed databases is considered a basic criterion in evaluating the quality of the created databases. To this end, rank correlation, and the Fligner–Policello test are applied. In addition, representativeness R indicators are computed. No differences are found between distributions.
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)
Downloads: (external link)
https://doi.org/10.1111/stan.12228
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:stanee:v:75:y:2021:i:2:p:92-114
Ordering information: This journal article can be ordered from
http://www.blackwell ... bs.asp?ref=0039-0402
Access Statistics for this article
Statistica Neerlandica is currently edited by Miroslav Ristic, Marijtje van Duijn and Nan van Geloven
More articles in Statistica Neerlandica from Netherlands Society for Statistics and Operations Research
Bibliographic data for series maintained by Wiley Content Delivery ().