In the paper we propose a model of tax incentives optimization for inve- ment projects with a help of the mechanism of accelerated depreciation. Unlike the tax holidays which influence on effective income tax rate, accelerated - preciation affects on taxable income. In modern economic practice the state actively use for an attraction of - vestment into the creation of new enterprises such mechanisms as accelerated depreciation and tax holidays. The problem under our consideration is the following. Assume that the state (region) is interested in realization of a certain investment project, for ex- ple, the creation of a new enterprise. In order to attract a potential investor the state decides to use a mechanism of accelerated tax depreciation. The foll- ing question arise. What is a reasonable principle for choosing depreciation rate? From the state's point of view the future investor's behavior will be rat- nal. It means that while looking at economic environment the investor choose such a moment for investment which maximizes his expected net present value (NPV) from the given project. For this case both criteria and "investment rule" depend on proposed (by the state) depreciation policy. For the simplicity we will suppose that the purpose of the state for a given project is a maximi- tion of a discounted tax payments into the budget from the enterprise after its creation. Of course, these payments depend on the moment of investor's entry and, therefore, on the depreciation policy established by the state.

Inhalt

The Jubilee of Prof. dr. Habil. Jonas Mockus. 1. Topographical Differential Evolution Using Pre-calculated Differentials; M.M. Ali, A. Törn. 2. Optimal Tax Depreciation in Stochastic Investment Model; V.I. Arkin, A.D. Slastnikov. 3. Global Optimisation of Chemical Process Flowsheets; I.D.L. Bogle, R.P. Byrne. 4. One-dimensional Global Optimization Based on Statistical Models; J.M. Calvin, A. Zilinskas. 5. Animated Visual Analysis of Extremal Problems; G. Dzemyda. 6. Test Problems for Lipschitz Univariate Global Optimization with Multiextremal Constraints; D. Famularo, P. Pugliese, Y.D. Sergeyev. 7. Numerical Techniques in Applied Multistage Stochastic Programming; K. Frauendorfer, G. Haarbrücker. 8. On the Efficiency and Effectiveness of Controlled Random Search; E.M.T. Hendrix, P.M. Ortigosa, I. García. 9. Discrete Backtracking Adaptive Search for Global Optimization; B.P. Kristinsdottir, Z.B. Zabinsky, G.R. Wood. 10. Parallel Branch-and-bound Attraction Based Methods for Global Optimization; K. Madsen, J. Zilinskas. 11. On Solution of Stochastic Linear Programs by Discretization Methods; K. Marti. 12. The Structure of Multivariate Models and the Range of Definition; V. Saltenis, V. Tiesis. 13. Optimality Criteria for Investment Projects Under Uncertainty; S.A. Smolyak.