Estimating the percentage of food expenditure in small areas using bias-corrected P-spline based estimators
AbstractSmall area estimators based on a penalized spline regression model approximating a non-linear but smooth relationship between a response and a given covariate are obtained. In each small area, individual curves are fitted using penalized splines with B-spline bases, exploiting the mixed model representation of the P-splines for inferential purposes. To account for possible bias, a design-oriented bootstrap correction is proposed. The mean squared error of the bias-corrected estimator is also provided. The methods are used to estimate the percentage of food expenditure for alternative household sizes at provincial level in Spain using the 2006 Spanish Household Budget Survey.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Elsevier in its journal Computational Statistics & Data Analysis.
Volume (Year): 56 (2012)
Issue (Month): 10 ()
Contact details of provider:
Web page: http://www.elsevier.com/locate/csda
P-spline models; Design oriented bootstrap bias correction; MSE; Spanish Household Budget Survey;
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.