Abstract
Equitable and sustainable well-being (in Italian, “BES”) has become an integral part of the decision-making process of economic and financial planning. By now, the needs of up-to-date and accurate measures of BES at local level is certain. Among BES indicators, several are obtained from Labour Force Survey (LFS) data. LFS provided estimates keeping with the highest quality and methodology standards required by the new Integrated European Social Statistics (IESS) framework regulation. The aim of this paper is to extend recent improvements in LFS variance estimation methodology also to BES indicators computed on LFS data. The direct consequence is that, besides estimates, accuracy measures can be provided. This can help researchers and decision makers to analyze the performance among the Italian regions and their evolution over time.
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Source: our elaboration on Italian Labour force Survey data
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Notes
The description of the dimensions and a list of the 130 indicators is available in English at the link https://www.istat.it/en/well-being-and-sustainability/the-measurement-of-well-being/indicators (last access 9th August, 2020).
Population by gender and 14 5-years age groups at NUTS2 level; Population by gender and 5 age groups at NUTS3 level and for the 13 biggest municipalities; monthly population by gender at NUTS2 level; number of households by wave at NUTS2 level; foreigner population (Male, Female, EU and Not EU) at NUTS2 level.
See, e.g., Berger and Priam (2016) for the estimator for the correlation in rotating repeated surveys.
Because \({}_{q}\widehat{Y}\) is obtained with the calibrated estimator \(\widehat{\mathrm{var}}\left({}_{q}\widehat{Y}\right)\) is estimated with expression (3.4) in Deville and Särndal (1992, p. 380).
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The authors would like to thank the editor, the guest editors and three anonymous referees who kindly review this manuscript and provided valuable suggestions and comments for improving it.
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Ceccarelli, C., Guandalini, A., Martini, A. et al. Accuracy Evaluation of LFS-BES Indicators: A Regional Assessment. Soc Indic Res 161, 989–1002 (2022). https://doi.org/10.1007/s11205-020-02532-3
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DOI: https://doi.org/10.1007/s11205-020-02532-3