- Author
- Luna Angela (University of Southampton), Zhang Li-Chun (University of Southampton), Whitworth Alison (Office for National Statistics ONS-UK), Piller Kirsten (Office for National Statistics ONS-UK)
- Title
- Small Area Estimates of the Population Distribution by Ethnic Group in England : a Proposal Using Structure Preserving Estimators
- Source
- Statistics in Transition, 2015, vol. 16, nr 4, s. 585-602, rys., tab., bibliogr. s. 602
- Issue title
- The Measurement of Subjective Well-Being in Survey Research
- Keyword
- Metody samowsporne, Statystyka małych obszarów, Estymatory, Teoria estymacji
Bootstrap, Small area estimates, Estimators, Estimation theory - Note
- Materiały z międzynarodowej konferencji Small Area Estimation (SAE 2014), Poznań.
summ. - Country
- Wielka Brytania
United Kingdom - Abstract
- This paper addresses the problem of producing small area estimates of Ethnicity by Local Authority in England. A Structure Preserving approach is proposed, making use of the Generalized Structure Preserving Estimator. In order to identify the best way to use the available aggregate information, three fixed effects models with increasing levels of complexity were tested. Finite Population Mean Square Errors were estimated using a bootstrap approach. However, more complex models did not perform substantially better than simpler ones. A mixed-effects approach does not seem suitable for this particular application because of the very small sample sizes observed in many areas. Further research on a more flexible fixed-effects estimator is proposed. (original abstract)
- Accessibility
- The Main Library of the Cracow University of Economics
The Library of Warsaw School of Economics
The Library of University of Economics in Katowice
The Main Library of the Wroclaw University of Economics - Full text
- Show
- Bibliography
- AGRESTI, A., (2013). Categorical Data Analysis. John Wiley & Sons.
- BERG, E. J., FULLER,W. A., (2014). Small Area Prediction of Proportions with Applications to the Canadian Labour Force Survey. Journal of Survey Statistics and Methodology, 2 (3), 227-56.
- CINCO, M., (2010). Intercensal Updating of Small Area Estimates. Unpublished PhD thesis. Massey University.
- LIANG, K-Y., ZEGER, S. L., (1986). Longitudinal data analysis using generalized linear models. Biometrika, 73, 13-22.
- MOLINA, I., AYOUB S., LOMBARDIA, M. J., (2007). Small Area Estimates of Labour Force Participation under a Multinomial Logit Mixed Model. Journal of the Royal Statistical Society: Series A (Statistics in Society), 170 (4), 9751000.
- NOBLE, A., HASETT, S., ARNOLD, G., (2002). Small Area Estimation via Generalized Linear Models. Journal of Official Statistics, 18(1):45-68.
- PFEFFERMANN, D., (2013). New Important Developments in Small Area Estimation. Statistical Science, 28 (1), 40-68.
- PURCELL, N., KISH, L., (1980). Postcensal estimates for local areas (or domains). International Statistical Review, 48(1), 3-18.
- RAO, J. N. K., (2003). Small Area Estimation. John Wiley & Sons.
- SCEALY, J., (2010). Small Area Estimation Using a Multinomial Logit Mixed Model with Category Specific Random Effects. Research paper, Australian Bureau of Statistics.
- UPTON, G., COOK, I., (2008). A Dictionary of Statistics. Oxford University Press.
- ZHANG, L. C., CHAMBERS, R., (2004). Small area estimates for cross-classifications, Journal of the Royal Statistical Society: Series B (Statistical Methodology), 66(2), 479-496.
- Cited by
- ISSN
- 1234-7655
- Language
- eng