IDEAS home Printed from
   My bibliography  Save this paper

Confidence Intervals for Policy Reforms in Behavioural Tax Microsimulation Modelling


  • John Creedy
  • Guyonne Kalb
  • Hsein Kew


This paper addresses the need for a measure of the uncertainty that is associated with the results calculated through tax policy behavioural microsimulation modelling. Deriving the analytical measure would be extremely complicated, therefore, a simulated approach is proposed which generates a pseudo sampling distribution of aggregate measures based on the sampling distribution of the estimated labour supply parameters. This approach, which is very computer intensive, is compared to a more time-efficient approach where the functional form of the sampling distribution is assumed to be normal. The results show that in many instances the results from the two approaches are quite similar. The exception is when aggregate measures for minor types of payments, involving relatively small groups of the population, are examined.

Suggested Citation

  • John Creedy & Guyonne Kalb & Hsein Kew, 2005. "Confidence Intervals for Policy Reforms in Behavioural Tax Microsimulation Modelling," Department of Economics - Working Papers Series 936, The University of Melbourne.
  • Handle: RePEc:mlb:wpaper:936
    Note: This paper is forthcoming (2006) in the Bulletin of Economic Research.

    Download full text from publisher

    File URL:
    Download Restriction: no

    Other versions of this item:

    References listed on IDEAS

    1. Keane, Michael & Moffitt, Robert, 1998. "A Structural Model of Multiple Welfare Program Participation and Labor Supply," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 39(3), pages 553-589, August.
    2. John Creedy & Guyonne Kalb, 2005. "Discrete Hours Labour Supply Modelling: Specification, Estimation and Simulation," Journal of Economic Surveys, Wiley Blackwell, vol. 19(5), pages 697-734, December.
    3. John Creedy & Guyonne Kalb & Hsein Kew, 2003. "Flattening the Effective Marginal Tax Rate Structure in Australia: Policy Simulations Using the Melbourne Institute Tax and Transfer Simulator," Australian Economic Review, The University of Melbourne, Melbourne Institute of Applied Economic and Social Research, vol. 36(2), pages 156-172.
    4. John Creedy & Alan S. Duncan & Mark Harris & Rosanna Scutella, 2002. "Microsimulation Modelling of Taxation and the Labour Market," Books, Edward Elgar Publishing, number 2796.
    5. Arthur van Soest, 1995. "Structural Models of Family Labor Supply: A Discrete Choice Approach," Journal of Human Resources, University of Wisconsin Press, vol. 30(1), pages 63-88.
    6. Guyonne Kalb, 2002. "Estimation of Labour Supply Models for Four Separate Groups in the Australian Population," Melbourne Institute Working Paper Series wp2002n24, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    7. Pudney, Stephen & Sutherland, Holly, 1994. "How reliable are microsimulation results? : An analysis of the role of sampling error in a U.K. tax-benefit model," Journal of Public Economics, Elsevier, vol. 53(3), pages 327-365, March.
    Full references (including those not matched with items on IDEAS)


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. François Bourguignon & Amedeo Spadaro, 2006. "Microsimulation as a tool for evaluating redistribution policies," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 4(1), pages 77-106, April.
    2. repec:ijm:journl:v10:y:2017:i:1:p:106-134 is not listed on IDEAS
    3. Denis Beninger & Holger Bonin & Julia Horstschräer & Grit Mühler, 2010. "Wirkungen eines Betreuungsgeldes bei bedarfsgerechtem Ausbau frühkindlicher Kindertagesbetreuung: eine Mikrosimulationsstudie," Vierteljahrshefte zur Wirtschaftsforschung / Quarterly Journal of Economic Research, DIW Berlin, German Institute for Economic Research, vol. 79(3), pages 147-168.
    4. Tim Goedemé & Karel Van den Bosch & Lina Salanauskaite & Gerlinde Verbist, 2013. "Testing the Statistical Significance of Microsimulation Results: A Plea," International Journal of Microsimulation, International Microsimulation Association, vol. 6(3), pages 50-77.
    5. Matteo Richiardi & Ross E. Richardson, 2017. "JAS-mine: A new platform for microsimulation and agent-based modelling," International Journal of Microsimulation, International Microsimulation Association, vol. 10(1), pages 106-134.
    6. Figari, Francesco & Paulus, Alari & Sutherland, Holly, 2014. "Microsimulation and policy analysis," ISER Working Paper Series 2014-23, Institute for Social and Economic Research.
    7. John Creedy & Guyonne Kalb, 2005. "Behavioural Microsimulation Modelling With the Melbourne Institute Tax and Transfer Simulator(MITTS) : Uses and Extensions," Department of Economics - Working Papers Series 932, The University of Melbourne.
    8. Goedemé, Tim & Van den Bosch, Karel & Salanauskaite, Lina & Verbist, Gerlinde, 2013. "Testing the statistical significance of microsimulation results: often easier than you think. A technical note," EUROMOD Working Papers EM18/13, EUROMOD at the Institute for Social and Economic Research.
    9. John Creedy & Penny Mok, 2017. "Labour supply in New Zealand and the 2010 tax and transfer changes," New Zealand Economic Papers, Taylor & Francis Journals, vol. 51(1), pages 60-78, January.
    10. repec:ijm:journl:v109:y:2017:i:1:p:106-134 is not listed on IDEAS
    11. John Creedy & Guyonne Kalb, 2005. "Behavioural Microsimulation Modelling for Tax Policy Analysis in Australia: Experience and Prospects," Australian Journal of Labour Economics (AJLE), Bankwest Curtin Economics Centre (BCEC), Curtin Business School, vol. 8(1), pages 73-110, March.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:


    Access and download statistics


    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:mlb:wpaper:936. 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: (Dandapani Lokanathan). General contact details of provider: .

    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.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with 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.