EconPapers    
Economics at your fingertips  
 

A formal framework for hedonic elementary price indices

Hans Wolfgang Brachinger, Michael Beer and Olivier Schöni ()
Additional contact information
Olivier Schöni: University of Bern

AStA Advances in Statistical Analysis, 2018, vol. 102, issue 1, 67-93

Abstract: Abstract Hedonic methods are considered state of the art for handling quality changes when compiling consumer price indices. The present article proposes first a mathematical description of characteristics and of elementary aggregates. In a following step, a hedonic econometric model is formulated and hedonic elementary population indices are defined. We emphasise that population indices are unobservable economic parameters that need to be estimated by suitable sample indices. It is shown that within the framework developed here, many of the hedonic index formulae used in practice are identified as sample versions corresponding to particular hedonic elementary population indices. The article closes with an empirical part on quarterly housing data where the considered hedonic indices are estimated along with their bootstrapped confidence intervals. It is shown that the computed confidence intervals together with the results from theory suggest a particular answer to the price index problem.

Keywords: Consumer price index; Hedonic regression; Elementary aggregate; Hedonic elementary price index; Wild bootstrap; Price index problem; Elementary index bias (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1) Track citations by RSS feed

Downloads: (external link)
http://link.springer.com/10.1007/s10182-017-0293-4 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

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:alstar:v:102:y:2018:i:1:d:10.1007_s10182-017-0293-4

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/10182/PS2

Access Statistics for this article

AStA Advances in Statistical Analysis is currently edited by Göran Kauermann and Yarema Okhrin

More articles in AStA Advances in Statistical Analysis from Springer, German Statistical Society
Bibliographic data for series maintained by Sonal Shukla ().

 
Page updated 2019-04-22
Handle: RePEc:spr:alstar:v:102:y:2018:i:1:d:10.1007_s10182-017-0293-4