Model Selection and the GREG Estimator Bias in a Small Business Survey
DOI:
https://doi.org/10.15678/ZNUEK.2017.0971.1101Keywords:
GREG, business statistics, model-assisted estimation, outliersAbstract
Estimation for a very skewed population containing extreme values is problematic, especially at a low level of aggregation. Traditional direct estimation methods do not provide satisfactory results. The growing demand for detailed information and the wider possibility of using data from administration registers has increased the importance of recognising more sophisticated estimation methods. Generalised Regression (GREG) estimation is an example of one such type. The paper examines the importance of the model chosen in GREG estimation in dealing with highly variable and outlier-prone populations. The model-assisted GREG estimator is applied to a real business survey. Lagged variables from administrative registers were used as the auxiliary variables. The variable of interest – mean revenue of small companies – was estimated for provinces cross-classified by categories of economic activity.
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