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A problem statistical offices are increasingly faced with is guaranteeing confidentiality when releasing microdata sets. One method to provide safe microdata is to reduce the information content of a data set by means of masking procedures. A widely discussed masking procedure is...
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This paper grew out of a lecture presented at the 54th Session of the International Statistical Institute in Berlin, August 13 - 20, 2003, Schneeweiss (2003). It intends not only to outline the eventful life of Abraham Wald (1902 - 1950) in Austria and in the United States but also to present...
Persistent link: https://www.econbiz.de/10010269718
Various estimators of the reduced form of a block recursive model are investigated and compared to each other. In particular it is shown that the structural reduced form estimator, which results from estimating separately each block of the block recursive model by some efficient method and then...
Persistent link: https://www.econbiz.de/10010276588
If rounded data are used in estimating moments and regression coffiecients, the estimates are typically more or less biased. The purpose of the paper is to study the bias inducing effect of rounding, which is also seen when population moments intstead of their estimates are considered. Under...
Persistent link: https://www.econbiz.de/10010276631
The present article considers the problem of consistent estimation in measurement error models. A linear relation with not necessarily normally distributed measurement errors is considered. Three possible estimators which are constructed as different combinations of the estimators arising from...
Persistent link: https://www.econbiz.de/10010276632
A measurement error model is a regression model with (substantial) measurement errors in the variables. Disregarding these measurement errors in estimating the regression parameters results in asymptotically biased estimators. Several methods have been proposed to eliminate, or at least to...
Persistent link: https://www.econbiz.de/10010332971
Summary Microaggregation is a set of procedures that distort empirical data in order to guarantee their factual anonymity. At the same time the information content of data sets should not be reduced too much and should still be useful for scientific research. This paper investigates the effect...
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