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Confidence Intervals for Policy Reforms in Behavioural Tax Microsimulation Modelling

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  • 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.

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Bibliographic Info

Paper provided by Melbourne Institute of Applied Economic and Social Research, The University of Melbourne in its series Melbourne Institute Working Paper Series with number wp2004n32.

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Length: 45 pages
Date of creation: Dec 2004
Date of revision:
Handle: RePEc:iae:iaewps:wp2004n32

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  1. Michael P. Keane & Robert Moffitt, 1995. "A structural model of multiple welfare program participation and labor supply," Working Papers 557, Federal Reserve Bank of Minneapolis.
  2. John Creedy & Guyonne Kalb, 2003. "Discrete Hours Labour Supply Modelling: Specification, Estimation and Simulation," Treasury Working Paper Series 03/20, New Zealand Treasury.
  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. 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.
  5. 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.
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Cited by:
  1. Denis Beninger & Holger Bonin & Julia Horstschräer & Grit Mühler, 2010. "Wirkungen eines Betreuungsgeldes bei bedarfsgerechtem Ausbau frühkindlicher Kindertagesbetreuung: eine Mikrosimulationsstudie," SOEPpapers on Multidisciplinary Panel Data Research 316, DIW Berlin, The German Socio-Economic Panel (SOEP).
  2. François Bourguignon & Amedeo Spadaro, 2006. "Microsimulation as a Tool for Evaluating Redistribution Policies," Working Papers 20, ECINEQ, Society for the Study of Economic Inequality.
  3. 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.
  4. John Creedy & Guyonne Kalb, 2005. "Behavioural Microsimulation Modelling for Tax Policy Analysis in Australia: Experience and Prospects," Melbourne Institute Working Paper Series wp2005n02, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  5. 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.
  6. Tim Goedemé & Karel Van den Bosch & Lina Salanauskaite & Gerlinde Verbist, 2013. "Testing the Statistical Significance of Microsimulation Results: A Plea," International Journal of Microsimulation, Interational Microsimulation Association, vol. 6(3), pages 50-77.

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