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Wednesday 15th July, 11:00 - 12:30 Room: HT-101


Advanced survey estimation methods for treatment of non-sampling errors 2

Convenor Dr Alina Matei (University of Neuchatel, Switzerland )
Coordinator 1Professor Giovanna Ranalli (University of Perugia, Italy)

Session Details

Non-sampling errors can be generated by nonresponse, frame imperfections, measurement and data processing errors. We focus here on nonresponse and coverage errors as a possible source of non-negligible bias. Nonresponse is determined by the failure to obtain fully or partially information from the sampled units. Coverage or frame errors are caused by the gap between the target population and the sampling frame.

The proposed session will bring together presentations proposing advanced estimation methods for treatment of these types of non-sampling errors. The presentations will focus on methodologies to deal with nonresponse, frame imperfections or both. Methods using propensity score methods or (generalized) calibration to handle nonresponse, estimation methods for multiple-frame sampling, joint calibration for nonresponse and frame imperfections, calibration in the presence of domain misclassification, etc. are invited to be submitted in this session.

Paper Details

1. Decomposition of wage discrimination through a calibration method
Miss Mihaela Catalina Anastasiade (University of Neuchâtel)
Mr Yves Tillé (University of Neuchâtel)

We propose a new method of wage decomposition, with the intention of going beyond the simple inspection of the difference of average values. The goal is to achieve a deeper level of analysis of the phenomenon of gender wage discrimination. This new method uses calibration to generate a counterfactual distribution of wages, allowing for a proper examination throughout the entire distribution without making any assumptions about the parameters of the underlying model behind the data. We compare our method with the existing methods in the literature.


2. Incorporating spatial and operational constraints in the sampling designs for forest inventories
Miss Audrey-anne Vallée (Université de Neuchâtel)
Mr Bastien Ferland-raymond (Ministère des Forêts, de la Faune et des Parcs )
Professor Louis-paul Rivest (Université Laval)
Professor Yves Tillee (Université de Neuchâtel)

In the province of Quebec, Canada, the forest is examined through regular inventories. Requirements for the spreading and the type of trees and for the cost are difficult to manage. We show that modern and advanced sampling techniques can be used to improve the planning of the forest inventories, even if there are many requirements. Our design includes balanced sampling, highly stratified balanced sampling and sample spreading through a two stage sample. The impact of these techniques on the satisfaction of the requirements and on the precision of survey estimates is investigated using field data from a Quebec inventory.


3. Ratio type estimators for the estimation of population coefficient of variation under two-stage sampling
Mr Muhammad Jabbar (The University of Lahore)

In this paper we propose two ratio and ratio type exponential estimator for the estimation of population coefficient of variation using the auxiliary information in two-stage sampling. The properties of these estimators are derived up to first order of approximation. The efficiency conditions under which suggested estimator are more efficient, are obtained. Numerical and simulated studies are conducted to support the superiority of the estimators. Theoretically and numerically, we have found that our proposed estimator is always more efficient as compared to its competitor estimator.