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Optimal Nonlinear Income Taxation with a Two-Dimensional Population; A Computational Approach

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  • Tarkiainen, Ritva
  • Tuomala, Matti

Abstract

We consider the optimal income tax problem when income differences are due to differences in abilities and in preferences between consumption and leisure among individuals. We model this problem as an optimal control problem and develop a numerical method for solving it. The method is based on the expansion of state and control variables in Lagrange series and on a spectral collocation method for approximating state equations. In this way the optimal control problem is reduced to a parameter optimization problem. The problem is difficult to solve, but we managed to do so with some limitations. On the basis of our calculations we conclude that the tax system in the two-dimensional case is more redistributive compared to that obtained from the one-dimensional model. Citation Copyright 1999 by Kluwer Academic Publishers.

Suggested Citation

  • Tarkiainen, Ritva & Tuomala, Matti, 1999. "Optimal Nonlinear Income Taxation with a Two-Dimensional Population; A Computational Approach," Computational Economics, Springer;Society for Computational Economics, vol. 13(1), pages 1-16, February.
  • Handle: RePEc:kap:compec:v:13:y:1999:i:1:p:1-16
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    Cited by:

    1. Jukka Pirttilä & Sanna Tenhunen, 2005. "Pawns and Queens Revisited: Public Provision of Private Goods When Individuals Make Mistakes Abstract: This paper analyses the optimal tax policy and public provision of private goods when individuals," Working Papers 212, Työn ja talouden tutkimus LABORE, The Labour Institute for Economic Research LABORE.
    2. Sören Blomquist & Vidar Christiansen, 2008. "Taxation and Heterogeneous Preferences," FinanzArchiv: Public Finance Analysis, Mohr Siebeck, Tübingen, vol. 64(2), pages 218-244, June.
    3. Terhi Ravaska & Sanna Tenhunen & Matti Tuomala, 2016. "On the optimal lifetime redistribution and equality of opportunities," Working Papers 1600, Tampere University, Faculty of Management and Business, Economics.
    4. Braulio Calagua, 2023. "Reducing incentive constraints in bidimensional screening," The Journal of Mechanism and Institution Design, Society for the Promotion of Mechanism and Institution Design, University of York, vol. 8(1), pages 107-150, December.
    5. Henrik Jordahl & Luca Micheletto, 2005. "Optimal Utilitarian Taxation and Horizontal Equity," Journal of Public Economic Theory, Association for Public Economic Theory, vol. 7(4), pages 681-708, October.
    6. Bastani, Spencer & Blomquist, Sören & Micheletto, Luca, 2010. "Public Provision of Private Goods, Tagging and Optimal Income Taxation with Heterogeneity in Needs," Working Paper Series, Center for Fiscal Studies 2010:14, Uppsala University, Department of Economics.
    7. Kaplow Louis, 2008. "Optimal Policy with Heterogeneous Preferences," The B.E. Journal of Economic Analysis & Policy, De Gruyter, vol. 8(1), pages 1-30, September.
    8. Terhi Ravaska & Sanna Tenhunen & Matti Tuomala, 2018. "On the optimal lifetime redistribution and social objectives: a multidimensional approach," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 25(3), pages 631-653, June.
    9. Jukka Pirttilä & Sanna Tenhunen, 2008. "Pawns and queens revisited: public provision of private goods when individuals make mistakes," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 15(5), pages 599-619, October.
    10. Matti Tuomala & Sanna Tenhunen, 2013. "On the design of an optimal non-linear tax/pension system with habit formation," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 20(3), pages 485-512, June.
    11. Yukihiro Nishimura, 2008. "Envy Minimization In The Optimal Tax Context," Working Paper 1178, Economics Department, Queen's University.
    12. Blomquist, Sören & Christiansen, Vidar, 2004. "Welfare Enhancing Marginal Tax Rates: The Case of Publicly Provided Day Care," Arbetsrapport 2004:6, Institute for Futures Studies.

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