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A more accurate measurement of tax effort

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  • Sangheon Kim

Abstract

Even though it is commonplace in many countries for federal governments to give fiscal support to local governments, this may work as a deterrent in providing incentives to local governments to increase their own revenue. To address this problem of moral hazard, various techniques of measuring the local governments' tax effort have been suggested in the literature. However, all of these techniques share a drawback: 'biasedness'. To solve this problem, this article presents an unbiased estimator, which is the Kalman filter estimator. A Monte Carlo simulation shows evidence that the Kalman filter estimator is more accurate than other methods suggested in the literature.

Suggested Citation

  • Sangheon Kim, 2007. "A more accurate measurement of tax effort," Applied Economics Letters, Taylor & Francis Journals, vol. 14(7), pages 539-543.
    • Handle: RePEc:taf:apeclt:v:14:y:2007:i:7:p:539-543
    DOI: 10.1080/13504850500425345
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    References listed on IDEAS

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    1. Leuthold, Jane H., 1991. "Tax shares in developing economies A panel study," Journal of Development Economics, Elsevier, vol. 35(1), pages 173-185, January.
    2. Burmeister, Edwin & Wall, Kent D., 1982. "Kalman filtering estimation of unobserved rational expectations with an application to the German hyperinflation," Journal of Econometrics, Elsevier, vol. 20(2), pages 255-284, November.
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    Cited by:

    1. Basil Dalamagas & Panagiotis Palaios & Stefanos Tantos, 2019. "A New Approach to Measuring Tax Effort," Economies, MDPI, vol. 7(3), pages 1-25, August.
    2. Mustafa Kiziltan & Ahmet Burcin Yereli, 2023. "Evaluating local fiscal capacity and fiscal effort of Turkish local governments: Evidence from spatial panel data analysis," Economic Change and Restructuring, Springer, vol. 56(1), pages 441-472, February.
    3. Yongzheng Liu & Jianmei Zhao, 2011. "Intergovernmental fiscal transfers and local tax efforts: evidence from provinces in China," Journal of Economic Policy Reform, Taylor & Francis Journals, vol. 14(4), pages 295-300, December.

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