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Confidence Intervals for Policy Reforms in Behavioural Tax Microsimulation Modelling

Author

Listed:
  • John Creedy

    () (Department of Economics, The University of Melbourne)

  • Guyonne Kalb

    () (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne)

  • Hsein Kew

    () (Department of Economics, The University of Melbourne)

Abstract

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, 2004. "Confidence Intervals for Policy Reforms in Behavioural Tax Microsimulation Modelling," Melbourne Institute Working Paper Series wp2004n32, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  • Handle: RePEc:iae:iaewps:wp2004n32
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    File URL: http://melbourneinstitute.unimelb.edu.au/downloads/working_paper_series/wp2004n32.pdf
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    References listed on IDEAS

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    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. 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.
    4. 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.
    5. 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.
    6. John Creedy & Alan S. Duncan & Mark Harris & Rosanna Scutella, 2002. "Microsimulation Modelling of Taxation and the Labour Market," Books, Edward Elgar Publishing, number 2796.
    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.
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    Citations

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    Cited by:

    1. Figari, Francesco & Paulus, Alari & Sutherland, Holly, 2014. "Microsimulation and policy analysis," ISER Working Paper Series 2014-23, Institute for Social and Economic Research.
    2. 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.
    3. repec:taf:nzecpp:v:51:y:2017:i:1:p:60-78 is not listed on IDEAS
    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. repec:ijm:journl:v109:y:2017:i:1:p:106-134 is not listed on IDEAS
    6. 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.
    7. 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.
    8. 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.
    9. 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.
    10. 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.
    11. Tim Goedemé & Karel Van den Bosch & Lina Salanauskaite & Gerlinde Verbist, 2013. "Testing the Statistical Significance of Microsimulation Results: Often Easier than You Think. A Technical Note," ImPRovE Working Papers 13/10, Herman Deleeck Centre for Social Policy, University of Antwerp.

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