Showing 1 - 10 of 12
From the literature on decentralization, it appears that the fiscal vertical imbalance is somehow inherent to multi-level governments. Using a stylized model we show that this leads to a reduction in the extent of redistributive fiscal policies if the maximal tolerable size of government has...
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The Sign Covariance Matrix is an orthogonal equivariant estimator of multivariate scale. It is often used as an easy-to-compute and highly robust estimator. In this paper we propose a k-step version of the Sign Covariance Matrix, which improves its efficiency while keeping the maximal breakdown...
Persistent link: https://www.econbiz.de/10013145137
In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses - conclusions based on a sample with and without these units...
Persistent link: https://www.econbiz.de/10010269751
In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses - conclusions based on a sample with and without these units...
Persistent link: https://www.econbiz.de/10010286574
In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses – conclusions based on a sample with and without these...
Persistent link: https://www.econbiz.de/10003958692
In empirical studies it often happens that some variables for some units are far away from the other observations in the sample. These extreme observations, or outliers, often have a large impact on the results of statistical analyses – conclusions based on a sample with and without these...
Persistent link: https://www.econbiz.de/10003962105
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