IDEAS home Printed from https://ideas.repec.org/p/aer/rpaper/rp_131.html
   My bibliography  Save this paper

Tax reforms and revenue mobilization in Kenya

Author

Listed:
  • Moses Kinyanjui Muriithi
  • Eliud Dismas Moyi

Abstract

One of the key objectives of tax reforms in Kenya was to ensure that the tax system could be harnessed to mitigate the perpetual fiscal imbalances. This would be achieved through tax policies intended to make the yield of individual taxes responsive to changes in national income. In addition, it was expected that the predominant taxes in the revenue would be those with highly elastic yields with respect to national income (or proxy bases). This study applies the concepts of elasticity and buoyancy to determine whether tax reforms in Kenya achieved these objectives. Elasticities and buoyancies are computed for the pre-reform period as well as the post-reform period. Evidence suggests that reforms had a positive impact on the overall tax structure and on the individual tax handles. In fact, the elasticity of indirect taxes was low and that of direct taxes was high, especially after the reforms. Despite this positive impact, the reforms failed to make VAT responsive to changes in income, although VAT was predominant in the tax structure.

Suggested Citation

  • Moses Kinyanjui Muriithi & Eliud Dismas Moyi, 2003. "Tax reforms and revenue mobilization in Kenya," Research Papers RP_131, African Economic Research Consortium.
  • Handle: RePEc:aer:rpaper:rp_131
    as

    Download full text from publisher

    File URL: http://www.aercafrica.org/documents/rp131.pdf
    Download Restriction: no

    References listed on IDEAS

    as
    1. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    2. Seyoum, E.T. & Battese, George E. & Fleming, E.M., 1998. "Technical efficiency and productivity of maize producers in eastern Ethiopia: a study of farmers within and outside the Sasakawa-Global 2000 project," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 19(3), December.
    3. Hung-Jen Wang, 2002. "Heteroscedasticity and Non-Monotonic Efficiency Effects of a Stochastic Frontier Model," Journal of Productivity Analysis, Springer, vol. 18(3), pages 241-253, November.
    4. Fulginiti, Lilyan E. & Perrin, Richard K., 1998. "Agricultural productivity in developing countries," Agricultural Economics of Agricultural Economists, International Association of Agricultural Economists, vol. 19(1-2), September.
    5. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    6. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    7. Nin, Alejandro & Arndt, Channing & Preckel, Paul V., 2003. "Is agricultural productivity in developing countries really shrinking? New evidence using a modified nonparametric approach," Journal of Development Economics, Elsevier, vol. 71(2), pages 395-415, August.
    8. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    9. Ashok Parikh & Farman Ali & Mir Kalan Shah, 1995. "Measurement of Economic Efficiency in Pakistani Agriculture," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 77(3), pages 675-685.
    10. Greene, William H., 1990. "A Gamma-distributed stochastic frontier model," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 141-163.
    11. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "Multilateral Comparisons of Output, Input, and Productivity Using Superlative Index Numbers," Economic Journal, Royal Economic Society, vol. 92(365), pages 73-86, March.
    12. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    13. Fulginiti, Lilyan E. & Perrin, Richard K., 1997. "LDC agriculture: Nonparametric Malmquist productivity indexes," Journal of Development Economics, Elsevier, vol. 53(2), pages 373-390, August.
    14. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    15. Bauer, Paul W., 1990. "Recent developments in the econometric estimation of frontiers," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 39-56.
    16. Seyoum, E. T. & Battese, G. E. & Fleming, E. M., 1998. "Technical efficiency and productivity of maize producers in eastern Ethiopia: a study of farmers within and outside the Sasakawa-Global 2000 project," Agricultural Economics, Blackwell, vol. 19(3), pages 341-348, December.
    17. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    18. Almas Heshmati & Yilma Mulugeta, 1996. "Technical efficiency of the Ugandan matoke farms," Applied Economics Letters, Taylor & Francis Journals, vol. 3(7), pages 491-494.
    19. Reifschneider, David & Stevenson, Rodney, 1991. "Systematic Departures from the Frontier: A Framework for the Analysis of Firm Inefficiency," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 32(3), pages 715-723, August.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:aer:rpaper:rp_131. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Steven Kinuthia). General contact details of provider: http://edirc.repec.org/data/aerccke.html .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.