Confidence Intervals for Policy Reforms in Behavioural Tax Microsimulation Modelling

This paper addresses the need for a measure of the uncertainty that is associated with the results calculated using tax policy behavioural microsimulation models. Deriving the analytical measure would be extremely complicated. Therefore, a simulated approach is proposed, which approximates the 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 with 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.

[1]  Guyonne Kalb,et al.  Flattening the effective marginal tax rate structure in Australia: Policy simulations using the Melbourne Institute Tax and Transfer Simulator , 2003 .

[2]  John Creedy,et al.  Microsimulation modelling of taxation and the labour market : the Melbourne Institute Tax and Transfer Simulator , 2002 .

[3]  Holly Sutherland,et al.  How reliable are microsimulation results?: An analysis of the role of sampling error in a U.K. tax-benefit model , 1994 .

[4]  J. Creedy,et al.  Discrete Hours Labour Supply Modelling: Specification, Estimation and Simulation , 2005 .

[5]  G. Kalb.  Estimation of Labour Supply Models for Four Separate Groups in the Australian Population , 2002 .

[6]  Arthur van Soest,et al.  Structural models of family labor supply: a discrete choice approach. , 1995 .

[7]  Robert A. Moffitt,et al.  Institute for Research on Poverty Discussion Paper no. 1080-96 A Structural Model of Multiple Welfare Program Participation and Labor Supply , 1996 .

[8]  C. Särndal,et al.  Calibration Estimators in Survey Sampling , 1992 .

[9]  Anil Gupta,et al.  Microsimulation in Government Policy and Forecasting , 2000 .

[10]  G. Maddala.  Limited-dependent and qualitative variables in econometrics: Introduction , 1983 .

[11]  N. Anders Klevmarken,et al.  Statistical inference in micro-simulation models: incorporating external information , 2002, Math. Comput. Simul..

[12]  P. Schmidt,et al.  Limited-Dependent and Qualitative Variables in Econometrics. , 1984 .