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Discrete Hours Labour Supply Modelling: Specification, Estimation and Simulation

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  • John Creedy

    (The Treasury, Wellington, New Zealand)

  • Guyonne Kalb

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

  • Rosanna Scutella

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

Abstract

Recent studies have examined tax policy issues using labour supply models characterised by a discretised budget set. Microsimulation modelling using a discrete hours approach is probabilistic. This makes analysis of the distribution of income difficult as even for a small sample with a modest range of labour supply points the range of possible labour supply combinations over the sample is extremely large. This paper proposes a method of approximating measures of income distribution and compares the performance of this method to alternative approaches in a microsimulation context. In this approach a pseudo income distribution is constructed, which uses the probability of a particular labour supply value occurring (standardised by the population size) to refer to a particular position in the pseudo income distribution. This approach is compared to using an expected income level for each individual and to a simulated approach, in which labour supply values are drawn from each individual’s hours distribution and summary statistics of the distribution of income are calculated by taking the average over each set of draws. The paper shows that the outcomes of various distributional measures using the pseudo method converge quickly to their true values as the sample size increases. The expected income approach results in a less accurate approximation. To illustrate the method, we simulate the distributional implications of a tax reform using the Melbourne Institute Tax and Transfer Simulator.

Suggested Citation

  • John Creedy & Guyonne Kalb & Rosanna Scutella, 2003. "Discrete Hours Labour Supply Modelling: Specification, Estimation and Simulation," Melbourne Institute Working Paper Series wp2003n21, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  • Handle: RePEc:iae:iaewps:wp2003n21
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    More about this item

    JEL classification:

    • D10 - Microeconomics - - Household Behavior - - - General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General
    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General

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