Fiscal incidence Fiscal incidence Fiscal incidence is a concept within public finance, a sub-discipline within economics, that refers to the combined overall economic impact of both government taxation and expenditures on the real economic income of individuals. While taxation reduces the economic well-being of individuals, government expenditures raise their economic well-being. Fiscal incidence is the term for the overall impact of government taxing and spending considered together. In theory, governments withdraw resources from society in the form of taxation, and contribute resources back into society in the form of expenditures. However, the burdens of taxation are not borne equally by individuals, and
Word-sense induction on the identification of hubs in co-occurrence graphs, which have to cope with the need to tune a large number of parameters. To deal with this issue several graph-based algorithms have been proposed, which are based on simple graph patterns, namely Curvature Clustering, Squares, Triangles and Diamonds (SquaT++), and Balanced Maximum Spanning Tree Clustering (B-MST). The patterns aim at identifying meanings using the local structural properties of the co-occurrence graph. A randomized algorithm which partitions the graph vertices by iteratively transferring the mainstream message (i.e. word sense) to neighboring vertices is Chinese Whispers. By applying co-occurrence graphs approaches have been