Grażyna Dehnel , Elżbieta Gołata
ARTICLE

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ABSTRACT

The paper presents attempts to use administrative data and non-standard techniques to estimate basic economic information about small business in the joint cross-section of Polish Classification of Economic Activities and regions. Due to many outliers and significant fraction of entities for which many variables are equal to zero, the considered distributions are heterogeneous. Therefore, Horvitz-Thompson estimates are compared with the robust ones: modified GREG, Winsor and local regression. Results obtained in the study present practical possibilities of adopting robust estimation techniques to small business data in Poland. Properties of the estimators are discussed.

KEYWORDS

Domain estimation, Robust estimators, Small business statistics.

REFERENCES

BREIDT, F.J., OPSOMER, J.D. (2000) Local Polynomial Regression Estimation in Survey Sampling. The Annals of Statistics, 28, 1026–1053.

CHAMBERS, R.L. (1996) Robust case-weighting for multipurpose establishment Surveys, Journal of Official Statistics, Vol.12, No.1, 3–32.

CHAMBERS, R., DORFMAN, A.H., WEHRLY, T.E. (1993) Bias Robust Estimation in Finite Populations Using Nonparametric Calibration. Journal of the American Statistical Association, 88, 268–277.

CHAMBERS, R., KOKIC, P., SMITH, P. and CRUDDAS, M. (2000) Winsorization for Identifying and Treating Outliers in Business Surveys, Proceedings of the Second International Conference on Establishment Surveys (ICES II), 687–696.

CHAMBERS R., BROWN G., HEADY P., HEASMAN D. (2001) Evaluation of Small Area Estimation Methods – an Application to Unemployment Estimates from the UK LFS, Proceedings of Statistics Canada Symposium 2001, Achieving Data Quality in a Statistical Agency: a Methodological Perspective.

CHAMBERS, R.L, FALVEY, H., HEDLIN, D., KOKIC P. (2001a) Does the Model Matter for GREG Estimation? A Business Survey Example, Journal of Official Statistics, Vol.17, No.4, 527–544.

DEHNEL G. (2008) Estymator GREG a estymacja typu Winsora w badaniach mikroprzedsiębiorstw (GREG and Winsor estimation in small business survey), [in:] Statystyka wczoraj, dziś i jutro (Statistics yesterday, today and tomorrow), Warszawa, Główny Urząd Statystyczny i Polskie Towarzystwo Statystyczne (Central Statistical Office and Polish Statistical Association), 58–71, Summ. - Bibliogr. ISBN 978-83-7027-431-3 (in Polish).

DORFMAN, A.H. (2000) Non-Parametric Regression for Estimating Totals in Finite Populations. Proceedings of the Survey Research Methods. American Statistical Association, 47–54.

EFRON, B. (1979) Bootstrap methods: Another look at the jackknife, [in:] Annals of Statistics 7, 1979, 1–26.

FALORSI P. D., FALORSI S., RUSSO A., PALLARA S. (2000) Small Domain Estimation Methods For Business Surveys, Statistics in Transition, June 2000, Vol. 4, No.5, 745–751.

HEDLIN D. (2004) Business Survey Estimation, R&D, Sweden.

HIDIROGLOU, M.H., SRINATH, K.P. (1981) Some estimators of population total from simple random samples containing large units, JASA, 76, 690–695.

KIM, J.Y., BREIDT, F.J. and OPSOMER, J.D. (2001) Local polynomial regression estimation in two-stage sampling. Proceedings of the Section on Survey Research Methods, American Statistical Association, 55–61.

KISH L. (1965) Survey Sampling, Wiley.

KISH L. (1995) Methods for design effects, Journal Official Statistics, 11, 55–77.

KLIMANEK T., PARADYSZ J. (2006) Adaptation of EURAREA experience in business statistics, ”Statistics in Transition”, Vol.7, No. 4.

KOKIC, P.N., BELL, P.A. (1994) Optimal winsorizing cutoffs for a stratified finite population estimator, Journal of Official Statistics, 10, 419–435.

MACKIN, C., PRESTON J. (2002) Winsorization for Generalised Regression Estimation, Australian Bureau of Statistics.

PAWLOWSKA Z. (2005) Role of small and medium enterprises in creating a demand on work, [in:] “Wiadomosci Statystyczne”, No.2, 34–46 (in Polish).

SÄRNDAL C.E., SWENSSON B., WRETMAN J. (1992) Model Assisted Survey Sampling, Springer Verlag, New York.

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