14,362 research outputs found

    The First Differential of the Functor "Algebraic K-Theory of Spaces"

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    In his "Algebraic K-theory of topological spaces II" Waldhausen proved that his functor A(X) splits: There is a canonical map from the stable homotopy of X which has a retraction up to weak equivalence. We adapt Waldhausen's proof to obtain a calculation of the Differential (in the sense of Goodwillie's "Calculus I") of A(X) at any path-connected base space.Comment: The calculation of the differential in Section 7 contains a mistake and it is not clear if the statement hold

    Note on the injectivity of the Loday assembly map

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    Comparing Direct and Indirect Taxation: The Influence of Framing on Tax Compliance

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    Standard theory of the optimal mix of direct and indirect taxation implicitly assumes that compliance is not influenced by the framing of the taxes. According to our findings, this is not the case. Using an experimental approach, we examine whether framing the tax payment decision as income tax or consumption tax influences compliance. We find that median compliance is 10.2 percentage points higher in the income tax framing. Further, we find that subjects' reaction to a change in tax rates is comparable, but reaction towards a change in detection rates is higher in the consumption tax scheme. We conclude that behavioral patterns should be taken into account when drawing conclusions about the direct-indirect tax mixComparative analysis of tax systems ; behavioral public finance ; optimal tax mix ; noncompliance ; framing

    A Bramble-Pasciak conjugate gradient method for discrete Stokes equations with random viscosity

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    We study the iterative solution of linear systems of equations arising from stochastic Galerkin finite element discretizations of saddle point problems. We focus on the Stokes model with random data parametrized by uniformly distributed random variables and discuss well-posedness of the variational formulations. We introduce a Bramble-Pasciak conjugate gradient method as a linear solver. It builds on a non-standard inner product associated with a block triangular preconditioner. The block triangular structure enables more sophisticated preconditioners than the block diagonal structure usually applied in MINRES methods. We show how the existence requirements of a conjugate gradient method can be met in our setting. We analyze the performance of the solvers depending on relevant physical and numerical parameters by means of eigenvalue estimates. For this purpose, we derive bounds for the eigenvalues of the relevant preconditioned sub-matrices. We illustrate our findings using the flow in a driven cavity as a numerical test case, where the viscosity is given by a truncated Karhunen-Lo\`eve expansion of a random field. In this example, a Bramble-Pasciak conjugate gradient method with block triangular preconditioner outperforms a MINRES method with block diagonal preconditioner in terms of iteration numbers.Comment: 19 pages, 1 figure, submitted to SIAM JU
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