The impact of participation in sports on educational attainment—New evidence from Germany

We analyze the impact of exercising sports during childhood and adolescence on educational attainment. The theoretical framework is based on models of allocation of time and educational productivity. Using the rich information from the German Socio-Economic Panel (GSOEP), we apply generalized ordered probit models to estimate the effect of participation in sport activities on secondary school degrees and professional degrees. Even after controlling for important variables and selection into sport, we find strong evidence that the effect of sport on educational attainment is statistically significant and positive.     

Efficient reverse k-nearest neighbor estimation

The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, has received increasing attention recently. Many industrial and scientific applications call for solutions of the RkNN problem in arbitrary metric spaces where the data objects are not Euclidean and only a metric distance function is given for specifying object similarity. Usually, these applications need a solution for the generalized problem where the value of k is not known in advance and may change from query to query. In addition, many applications require a fast approximate answer of RkNN-queries. For these scenarios, it is important to generate a fast answer with high recall. In this paper, we propose the first approach for efficient approximative RkNN search in arbitrary metric spaces where the value of k is specified at query time. Our approach uses the advantages of existing metric index structures but proposes to use an approximation of the nearest-neighbor-distances in order to prune the search space. We show that our method scales significantly better than existing non-approximative approaches while producing an approximation of the true query result with a high recall.