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Combining data national surveys with composite calibration to improve the precision of estimates from the UK’s Living Costs and Food Survey

Combining data national surveys with composite calibration to improve the precision of estimates from the UK’s Living Costs and Food Survey
Combining data national surveys with composite calibration to improve the precision of estimates from the UK’s Living Costs and Food Survey

The United Kingdom's Living Costs and Food (LCF) Survey has a relatively small sample size but produces estimates which are widely used, notably as a key input to the calculation of weights for consumer price indices. There has been a recent call for the use of additional data sources to improve the estimates from the LCF. Since some LCF variables are shared with the much larger Labour Force Survey (LFS), we investigate combining data from these surveys using composite calibration to improve the precision of estimates from the LCF. We undertake model selection to choose a suitable set of common variables for the composite calibration using the effect on the estimated variances for national and regional totals of important LCF variables. The variances of estimates for common variables are reduced to around 5 percent of their original size. Variances of national estimates are reduced (across several quarters) by around 10 percent for expenditure and 25 percent for income; these are the variables of primary interest in the LCF. Reductions in the variances of regional estimates vary more but are mostly large when using common variables at the regional level in the composite calibration. The composite calibration also makes the LCF estimates for employment status almost consistent with the outputs of the LFS, which is an important property for users of the statistics. A novel alternative method for variance estimation, using stored information produced by the composite calibration, is also presented.

composite estimation, data harmonisation, data integration, household expenditure survey, linearised jackknife, Data integration, Linearized jackknife, Data harmonization, Household expenditure survey, Composite estimation
2325-0984
713-741
Merkouris, Takis
86d9af6f-9357-402f-af4c-e48f1f8f00ed
Smith, Paul A.
a2548525-4f99-4baf-a4d0-2b216cce059c
Fallows, Andy
f028737a-dfb1-4ec2-9eb7-250a447f39e7
Merkouris, Takis
86d9af6f-9357-402f-af4c-e48f1f8f00ed
Smith, Paul A.
a2548525-4f99-4baf-a4d0-2b216cce059c
Fallows, Andy
f028737a-dfb1-4ec2-9eb7-250a447f39e7

Merkouris, Takis, Smith, Paul A. and Fallows, Andy (2023) Combining data national surveys with composite calibration to improve the precision of estimates from the UK’s Living Costs and Food Survey. Journal of Survey Statistics and Methodology, 11 (3), 713-741. (doi:10.1093/jssam/smad001).

Record type: Article

Abstract

The United Kingdom's Living Costs and Food (LCF) Survey has a relatively small sample size but produces estimates which are widely used, notably as a key input to the calculation of weights for consumer price indices. There has been a recent call for the use of additional data sources to improve the estimates from the LCF. Since some LCF variables are shared with the much larger Labour Force Survey (LFS), we investigate combining data from these surveys using composite calibration to improve the precision of estimates from the LCF. We undertake model selection to choose a suitable set of common variables for the composite calibration using the effect on the estimated variances for national and regional totals of important LCF variables. The variances of estimates for common variables are reduced to around 5 percent of their original size. Variances of national estimates are reduced (across several quarters) by around 10 percent for expenditure and 25 percent for income; these are the variables of primary interest in the LCF. Reductions in the variances of regional estimates vary more but are mostly large when using common variables at the regional level in the composite calibration. The composite calibration also makes the LCF estimates for employment status almost consistent with the outputs of the LFS, which is an important property for users of the statistics. A novel alternative method for variance estimation, using stored information produced by the composite calibration, is also presented.

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LCFpaper v5 AAM - Accepted Manuscript
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Accepted/In Press date: 21 December 2022
e-pub ahead of print date: 8 March 2023
Published date: 1 June 2023
Additional Information: Funding Information: The work of Takis Merkouris and Paul Smith was supported by ONS under contract PU-16- 0031-6.009. We are grateful to Jo Bulman and Steve Martin-Drury who were involved in an earlier phase of this project. The views expressed in this article are those of the authors, and do not necessarily reflect those of the ONS or their respective organisations. Publisher Copyright: © 2023 Crown copyright.
Keywords: composite estimation, data harmonisation, data integration, household expenditure survey, linearised jackknife, Data integration, Linearized jackknife, Data harmonization, Household expenditure survey, Composite estimation

Identifiers

Local EPrints ID: 473776
URI: http://eprints.soton.ac.uk/id/eprint/473776
ISSN: 2325-0984
PURE UUID: 27d7e59c-5ca4-497c-8207-38d576fb3604
ORCID for Paul A. Smith: ORCID iD orcid.org/0000-0001-5337-2746

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Date deposited: 31 Jan 2023 17:44
Last modified: 17 Mar 2024 07:38

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Contributors

Author: Takis Merkouris
Author: Paul A. Smith ORCID iD
Author: Andy Fallows

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