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Algorithm for calculating corporate marginal tax rate using Monte Carlo simulation


  • Sinha, Pankaj
  • Bansal, Vishakha


Simulated marginal tax rates involve complex calculations of simulating future (uncertain) incomes and mimicking corporate tax code. This paper develops two algorithms to calculate simulated marginal tax rate. The codes have been developed to forecast future taxable income of Indian companies and their Marginal Tax Rates (MTR) using Monte Carlo simulation in MATLAB. Loss carry forward and minimum alternate tax rules have been incorporated in both the algorithms. Further, a change is made in both the algorithms to incorporate loss carry backward feature to suit the needs of the country where such laws are applicable. The 10000 simulations in MATLAB suggest that MTR is company specific and it is dependent on the income pattern of the company. The MTR increases when loss carry backward rule is applied. In cases where the company actually pays zero tax in a year due to incurred losses, it is found that even in such cases MTR may be non zero. It is found that there is enough cross sectional and time series variations in MTR, therefore, the effect of tax rates on various policy issues of government and companies can be studied by taking MTR as an effective proxy for tax rates.

Suggested Citation

  • Sinha, Pankaj & Bansal, Vishakha, 2012. "Algorithm for calculating corporate marginal tax rate using Monte Carlo simulation," MPRA Paper 40811, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:40811

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    References listed on IDEAS

    1. Julian Alworth & Giampaolo Arachi, 2001. "The Effect of Taxes on Corporate Financing Decisions: Evidence from a Panel of Italian Firms," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 8(4), pages 353-376, August.
    2. Plesko, George A., 2003. "An evaluation of alternative measures of corporate tax rates," Journal of Accounting and Economics, Elsevier, vol. 35(2), pages 201-226, June.
    3. Shackelford, Douglas A. & Shevlin, Terry, 2001. "Empirical tax research in accounting," Journal of Accounting and Economics, Elsevier, vol. 31(1-3), pages 321-387, September.
    4. Laurence J. Kotlikoff & David Rapson, 2005. "Comparing Average and Marginal Tax Rates Under the FairTax and the Current System of Federal Taxation," NBER Working Papers 11831, National Bureau of Economic Research, Inc.
    5. John R. Graham & Michael L. Lemmon, 1998. "Measuring Corporate Tax Rates And Tax Incentives: A New Approach," Journal of Applied Corporate Finance, Morgan Stanley, vol. 11(1), pages 54-65.
    6. Graham, John R., 1996. "Debt and the marginal tax rate," Journal of Financial Economics, Elsevier, vol. 41(1), pages 41-73, May.
    7. Grady, Patrick, 1986. "The Recent Corporate Income Tax Reform Proposals in Canada and the United States," MPRA Paper 18749, University Library of Munich, Germany.
    8. Padovano, Fabio & Galli, Emma, 2002. "Comparing the growth effects of marginal vs. average tax rates and progressivity," European Journal of Political Economy, Elsevier, vol. 18(3), pages 529-544, September.
    9. Gogas, Periklis, 1997. "On the construction of cersonal, corporate and effective overall marginal tax rates for Canada (1977-1992)," MPRA Paper 1465, University Library of Munich, Germany.
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    Cited by:

    1. José A. Clemente-Almendros & Francisco Sogorb-Mira, 2016. "The effect of taxes on the debt policy of spanish listed companies," SERIEs: Journal of the Spanish Economic Association, Springer;Spanish Economic Association, vol. 7(3), pages 359-391, August.
    2. Sinha, Pankaj & Bansal, Vishakha, 2013. "Capital structure puzzle: the interrelationship between leverage, taxes and other micro economic factors," MPRA Paper 49878, University Library of Munich, Germany, revised 17 Sep 2013.

    More about this item


    Marginal tax Rate; Corporate taxes; Loss carry forward; Alternate minimum tax; Loss carry backward; Tax code;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • G38 - Financial Economics - - Corporate Finance and Governance - - - Government Policy and Regulation
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • K34 - Law and Economics - - Other Substantive Areas of Law - - - Tax Law

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