Hulliger, Beat

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Hulliger, Beat

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  • Publikation
    On Model-Representativeness
    (Eurostat, 21.08.2015) Hulliger, Beat [in: Proceedings of the NTTS2015 Conference]
    04B - Beitrag Konferenzschrift
  • Publikation
    Technical Workshop Report
    (Eurostat, 2014) Cervera, José Luis; Hulliger, Beat; Falorsi, Stefano; Votta, Paola
    04B - Beitrag Konferenzschrift
  • Publikation
    Robust Multivariate Methods for Income Data
    (26.08.2011) Hulliger, Beat; Schoch, Tobias
    With the EU Statistics on Income and Living Conditions (EU-SILC), the European Union established a coordinated survey and adopted a set of indicators (Laeken indicators) to monitor poverty and social cohesion. In particular, the monetary Laeken indicators are based on the equivalized disposable income per person, an aggregation and redistribution of person- and household-specific income components (e.g., income from employment and capital; unemployment-, old-age-, survivors'-, and disability benefits, etc.). To understand this highly complex data the components that are exclusively measured at household-level are distributed among the household members while the individual components are investigated before they are aggregated and redistributed to all household members. The personal income components show the following characteristics: the marginal distribution of each component is heavily skewed and has a remarkable point mass at zero, the joint distribution of the components is far from being elliptically contoured (even after appropriate transformation), an overwhelming majority of observations lies on subspaces i.e., exhibits structural zeros on certain dimension (e.g., individuals on working age with a positive employee-cash income do neither receive old-age nor unemployment benefits, and vice versa), within subspaces the observations are clustered with respect to non-monetary, socio-economic characteristics, many components have missing values, and finally there are outliers in many components but in addition there are genuinely multivariate outliers. The influence of outliers and outlier treatments on the components and on the equivalized disposable income and the Laeken indicators are investigated. In particular the outliers may have a considerable effect on the the Laeken indicators. The presentation shows the development of outlier detection and imputation methods which are capable to treat the structural zeros appropriately, which work with missing values, which cope with the complex nature of the data, which take the sampling design into account, and which are still computationally feasible.
    04B - Beitrag Konferenzschrift
  • Publikation
    Robust Multivariate Methods for Income Data
    (Eurostat, 01.02.2011) Hulliger, Beat; Schoch, Tobias
    Income inequality and poverty measures are central to the analysis of social welfare. However, recording and measurement errors, outlying observations exert strong influence on non-robust estimators of these measures. If the data cannot be purged of these, welfare conclusions drawn from the data can be seriously misleading. Moreover, these measures are computed on the basis of a univariate income variable, which is an aggregation of several distinct income sources or components. Notably outliers in several income components may severely affect the univariate income variable and thus the estimates. In addition, the aggregation process may propagate or mask outliers in the components. Therefore, instead of focusing on univariate robust estimators, propose to adopt truly multivariate outlier-detection and robust imputation methods. Both, outlier-detection- and imputation methods are adapted for the finite population sampling context and can cope with missing values and the multiple zero-inflation structure of income data. This kind of data.
    04B - Beitrag Konferenzschrift
  • Publikation
    Robust Estimation for Poverty- and Inequality-Indicators
    (01.10.2010) Hulliger, Beat; Schoch, Tobias
    04B - Beitrag Konferenzschrift
  • Publikation
    Robust Multivariate Imputation for Income Data
    (04.05.2010) Hulliger, Beat; Schoch, Tobias
    04B - Beitrag Konferenzschrift
  • Publikation
    Robust Multivariate Imputation with Survey Data
    (16.08.2009) Hulliger, Beat; Schoch, Tobias
    04B - Beitrag Konferenzschrift
  • Publikation
    Robustification of the Quintile Share Ratio
    (18.02.2009) Hulliger, Beat; Schoch, Tobias
    04B - Beitrag Konferenzschrift
  • Publikation
    Multivariate Outlier Detection and Treatment in Business Surveys
    (2007) Hulliger, Beat [in: Proceedings of the III International Conference on Establishment Surveys]
    04B - Beitrag Konferenzschrift
  • Publikation
    04B - Beitrag Konferenzschrift