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Labour Supply and Income Taxation: Estimation and Simulation Exercise for Finland

Author

Listed:
  • Mika Kuismanen

    (European Central Bank, Research Department, Germany)

Abstract

It is well known that the estimation of a labour supply function is complicated because of the non-linear budget constraint an individual faces. This non-linearity may arise from a variety of reasons - the structure of the tax/benefit scheme, overtime rates etc. Non-linearities also cause problems when it comes to interpreting the policy implications of the estimates. In this study we first estimate two well-structured econometric labour supply models which mimic the actual budget constraints as closely as possible. Utilising estimation results we construct a microsimulation model to analyse different income tax regimes and systems to the labour supply. Our simulation results show that none of the proposed reforms are self-financing. A revenue neutral proportional tax system does not have major effects on labour supply. The biggest behavioural responses are achieved if we reduce the marginal tax rates from the lower end of the state income tax schedule.

Suggested Citation

  • Mika Kuismanen, 2005. "Labour Supply and Income Taxation: Estimation and Simulation Exercise for Finland," Finnish Economic Papers, Finnish Economic Association, vol. 18(1), pages 16-18, Spring.
    • Handle: RePEc:fep:journl:v:18:y:2005:i:1:p:16-18
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    Cited by:

    1. Anne-Célia Disdier & Keith Head, 2008. "The Puzzling Persistence of the Distance Effect on Bilateral Trade," The Review of Economics and Statistics, MIT Press, vol. 90(1), pages 37-48, February.

    More about this item

    JEL classification:

    • H24 - Public Economics - - Taxation, Subsidies, and Revenue - - - Personal Income and Other Nonbusiness Taxes and Subsidies
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models

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