A Business Survey on Job Vacancies: Integration with Other Sources and Calibration

Diego Bellisai (), Stefania Fivizzani () and Marina Sorrentino ()
Additional contact information
Diego Bellisai: Istat
Stefania Fivizzani: Istat
Marina Sorrentino: Istat

A chapter in Survey Data Collection and Integration, 2013, pp 139-152 from Springer

Abstract: Abstract Statistical sources on the demand side of the labour market have been historically developed later than those on the supply side. A quarterly business survey was set up by ISTAT in 2003 to contribute to fill in some of these gaps, in particular, those on job vacancies and hours worked. Attention has been paid, when designing the survey and especially for the processing procedures, to the already existing sources, in order to fully exploit the available information in the editing and imputation and grossing up phases, and to ensure consistency among aggregate data produced by different sources. In this paper, it is discussed how the integration between the data collected by the job vacancy and hours worked and two other Istat business surveys has shaped the data processing methods which are used to produce the quarterly job vacancy indicators and differentiated them from others used in short-term business statistics.

Keywords: Local Unit; Target Parameter; Imputation Procedure; Data Processing Method; Social Contribution (search for similar items in EconPapers)
Date: 2013
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

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:spr:sprchp:978-3-642-21308-3_9

Ordering information: This item can be ordered from
http://www.springer.com/9783642213083

DOI: 10.1007/978-3-642-21308-3_9

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().