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A Fuzzy Logic Approach to Modelling the Underground Economy

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  • Robert Draeseke

    ()

  • David E. A. Giles

    ()

Abstract

The availability of data for the size of the "Underground Economy" is important for macroeconomic policy. We use fuzzy set theory and fuzzy logic to construct an annual time-series for the (unobservable) New Zealand underground economy over the period 1968 to 1994. Two input variables are used - the effective tax rate and an index of the degree of regulation. The resulting underground economy time-series is compared with one previously constructed by the second author using a structural "Multiple Indicators, Multiple Causes" (MIMIC) model. The two approaches each yield sensible, but somewhat different, pictures of the New Zealand underground economy over this period. The fuzzy logic approach to this measurement problem involves several subjective judgements, but our results are quite robust to these choices.

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Bibliographic Info

Paper provided by Department of Economics, University of Victoria in its series Econometrics Working Papers with number 9909.

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Length: 6 pages
Date of creation: 23 Jul 1999
Date of revision:
Handle: RePEc:vic:vicewp:9909

Note: ISSN 1485-6441
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Related research

Keywords: underground economy; tax evasion; fuzzy logic; fuzzy sets;

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References

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  1. David Giles & Patrick Caragata, 2001. "The learning path of the hidden economy: the tax burden and tax evasion in New Zealand," Applied Economics, Taylor & Francis Journals, Taylor & Francis Journals, vol. 33(14), pages 1857-1867.
  2. David E. A. Giles, 1999. "Modelling the hidden economy and the tax-gap in New Zealand," Empirical Economics, Springer, Springer, vol. 24(4), pages 621-640.
  3. Gregory Richardson, 1998. "The structure of fuzzy preferences: Social choice implications," Social Choice and Welfare, Springer, Springer, vol. 15(3), pages 359-369.
  4. Patrick J. Caragata, & David E. A. Giles, 1998. "Simulating the Relationship Between the Hidden Economy and the Tax Level and Tax Mix in New Zealand," Econometrics Working Papers, Department of Economics, University of Victoria 9804, Department of Economics, University of Victoria.
  5. Lindstrom, Tomas, 1998. "A fuzzy design of the willingness to invest in Sweden," Journal of Economic Behavior & Organization, Elsevier, Elsevier, vol. 36(1), pages 1-17, July.
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Cited by:
  1. David E. A. Giles & Robert Draeseke, 2001. "Econometric Modelling based on Pattern recognition via the Fuzzy c-Means Clustering Algorithm," Econometrics Working Papers, Department of Economics, University of Victoria 0101, Department of Economics, University of Victoria.

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