Estimation of standard error of the parameter of change using simulations
Djordje Petkovic
Additional contact information
Djordje Petkovic: Statistical Office of the Republic of Serbia
Romanian Statistical Review, 2015, vol. 63, issue 2, 90-95
Abstract:
The main objective of this paper is to present the procedure for estimating standard error of parameter of change (index) of turnover in R software (R core team, 2014) when samples are coordinated. The problem of estimating standard error is dealt with in the statistical literature by various types of approximations. In my paper I start from the method presented at the Consultation on Survey Methodology between Statistics Sweden and Statistical Office of the Republic of Serbia (SERSTAT 2013:22), make simulations and calculate estimate of the correlation and true value of standard error of change between turnovers from two years. I use two consecutive sampling frames of quarterly Structural Business Survey (SBS). These frames are updated with turnover from corresponding balance sheets. Important assumption is that annual turnover is highly correlated with quarterly turnover and that computed correlation can be referred to when comparing methods of estimation of correlation on the sample data.
Keywords: coordinated samples with permanent random numbers; correlation of totals; quarterly SBS; R; simulations; standard error of index (search for similar items in EconPapers)
Date: 2015
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.revistadestatistica.ro/wp-content/uploads/2015/04/RRS2_2015_A09.pdf (application/pdf)
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:rsr:journl:v:63:y:2015:i:2:p:90-95
Access Statistics for this article
More articles in Romanian Statistical Review from Romanian Statistical Review Contact information at EDIRC.
Bibliographic data for series maintained by Adrian Visoiu ().