Cost Impact of Changing the Funding Mechanisms for Deposit-Guarantee

Directive 94/19/EC on Deposit Guarantee Schemes (DGS) requires EU Member States to have DGS in place, which protect depositors to a certain extent in cases of default. The Directive leaves many structural aspects of DGS to the discretion of MS, including the way DGS are financed. As a result, the DGS funding mechanisms are very heterogeneous among MS. Some MS finance their scheme by means of regular contributions, whereas others levy contributions only in the event of a crisis. In between, there are a wide variety of schemes which collect both ex-ante contributions and ex-post levies. This study aims at investigating the effects of harmonising the mechanisms for funding DGS across the EU with the aid of a scenario analysis which applies three different ex-ante scenarios across the EU MS.JRC.G.9-Econometrics and statistical support to antifrau

Robust methods for high-dimensional data, and a theoretical study of depth-related estimators.

Deel I Principale Componenten Analyse (PCA) is een methode om hoogdimensionale gegevens om te zetten in laagdimensionale gegevens via de bepaling van e en kleinere deelruimte die goed bij de data aansluit. De berekening van deze PCA-deelruimte wordt echter sterk beïnvloed door de aanwezighe id van abnormale waarden. Daarom stellen we een robuuste PCA methode ROB PCA voor die een combinatie inhoudt van enkele welbekende technieken bin nen robuuste PCA. Deze methode kan gebruikt worden als een stand-alone f unctie, maar in vele situaties dient deze schatter echter als een soort van preprocessing. Ik heb twee zo n toepassingen van PCA bestudeerd in h et gebied van classificatie en PLS regressie. Deel II In Portnoy (2003) is de standaardmethode voor het schatten van regressie kwantielen voor een bepaalde gegevensset uitgebreid naar gecensureerde g egevens via een herwegingschema. We hebben aangetoond dat deze nieuwe sc hatter consistent is. Het breekpunt van deze schatter is echter 0 aangez ien ze gebaseerd is op L1-technieken. We introduceren daarom reeds kort een nieuwe robuuste schatter gebaseerd op regresiediepte voor het p robleem van het schatten van regressiekwantielen bij gecensureerde data. Tenslotte bekijken we nog een nieuwe schatter voor locatie en schaal va n univariate data. Deze schatter, voorgesteld in Mizera en Müller (2004) , is gebaseerd op het concept van regressiediepte. We tonen aan dat deze een begrensde invloedsfunctie heeft, en een breekpunt van ongeveer 30%. Referenties: Mizera, I. and Müller, C.H., Location-scale depth. Journal of th e American Statistical Association, 99:949-966, 2004. Portnoy, S., Censored regression quantiles. Journal of the Ameri can Statistical Association, 98:1001-1012, 2003.status: publishe

Robust Data Imputation

Single imputation methods have been wide-discussed topics among researchers in the field of bioinformatics. One major shortcoming of methods proposed until now is the lack of robustness considerations. Like all data, gene expression data can possess outlying values. The presence of these outliers could have negative effects on the imputated values for the missing values. Afterwards, the outcome of any statistical analysis on the completed data could lead to incorrect conclusions. Therefore it is important to consider the possibility of outliers in the data set, and to evaluate how imputation techniques will handle these values. In this paper, a simulation study is performed to test existing techniques for data imputation in case outlying values arepresent in the data. To overcomesomeshortcomings of the existingimputation techniques, a new robust imputation method that can deal with the presence of outliers in the data is introduced. In addition, the robust imputation procedure cleans the data for further statistical analysis. Moreover, this method can be easily extended towards a multiple imputation approach by which the uncertainty of the imputed values is emphasised. Finally, a classification example illustrates the lack of robustness of some existing imputation methods and shows the advantage of the multiple imputation approach of the new robust imputation technique.JRC.G.9-Econometrics and applied statistic

ROBPCA: a New Approach to Robust Principal Component Analysis

In this paper we introduce a new method for robust principal component analysis. Classical PCA is based on the empirical covariance matrix of the data and hence it is highly sensitive to outlying observations. In the past, two robust approaches have been developed. The first is based on the eigenvectors of a robust scatter matrix such as the MCD or an S-estimator, and is limited to relatively low-dimensional data. The second approach is based on projection pursuit and can handle high-dimensional data. Here, we propose the ROBPCA approach which combines projection pursuit ideas with robust scatter matrix estimation. It yields more accurate estimates at non-contaminated data sets and more robust estimates at contaminated data. ROBPCA can be computed fast, and is able to detect exact fit situations. As a byproduct, ROBPCA produces a diagnostic plot which displays and classifies the outliers. The algorithm is applied to several data sets from chemometrics and engineering

Deposit Protection in the EU: State of Play and Future Prospects

More than ten years have passed since the European Commission adopted Directive 94/19/EC on deposit-guarantee schemes. The Directive laid the foundations for general harmonisation of deposit insurance across the European Union Member States, requiring them to legally set up deposit-guarantee schemes by a specified deadline. Based on minimum harmonisation, the Directive left it to Member States to develop their own deposit insurance systems in terms of e.g. definition of eligible deposits, level of cover, types of funding mechanism, and calculation of members’ contributions. This autonomy has resulted in quite divergent evolution of deposit-guarantee schemes and gives rise to a series of possible problems, which were the subject of the European Commission’s review of the Directive in 2006. This paper overviews the current state of deposit insurance across the European Union, highlights the main controversial issues which cause disparities in the implementation of deposit insurance between Member States (e.g. the definition of eligible deposits, the level of cover applied, the implementation of topping-up arrangements, the types of funding mechanism), and discusses the pros and cons of further harmonisation.JRC.G.9-Econometrics and statistical support to antifrau