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Die relative Steuerbelastung mittelständischer Kapitalgesellschaften: Evidenz von handelsbilanziellen Mikrodaten

Author

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  • Gebhardt Heinz

    (RWI – Leibniz-Institut für Wirtschaftsforschung, Hohenzollernstraße 1–3, 45128EssenGermany.)

  • Siemers Lars-H. R.

    (Universität Siegen, Lehrstuhl für Europäische Wirtschaftspolitik und Forschungskolleg (FoKoS), Unteres Schloß 3, 57072SiegenGermany, Tel.: (0271) 740 3193)

Abstract

Official tax statistics do not provide sufficient disaggregated data to determine the effective relative tax burden of SMEs. Due to secrecy of tax matters, there are also no tax microdata. The only available data are commercial balance sheets and profit-and-loss statements. We discuss the issues of measuring effective tax rates derived from these commercial financial statements and estimate the relative effective tax burden of SME and large corporations in Germany. We use a backward-looking measure via bootstrapped trimmed quantile regression, to guarantee robust results. Backward-looking average tax rates derived from corporate data on actual tax payments can be robust indicators of the corporate tax burden. In contrast to forward-looking measures, our approach controls for the firm-specific tax optimisation strategy, the quality of the tax administration and potentially different degrees of leniency of tax audits. We find evidence for an inverted U-shaped pattern of burden: small enterprises face a significantly lower tax burden than medium-sized enterprises, and medium-sized enterprises face a significantly higher tax burden than large companies. That is, taxation is not size-neutral and medium-sized enterprises face a tax disadvantage. Given the evidence that SMEs represent employment and growth engines, taxation of SMEs in Germany may hamper growth and employment. We also provide empirical evidence that the big German tax reform at the beginning of this millennium („Steuerreform 2000“) did significantly reduce the effective tax burden. Again, the tax relief was different for small, medium and large corporations.

Suggested Citation

  • Gebhardt Heinz & Siemers Lars-H. R., 2017. "Die relative Steuerbelastung mittelständischer Kapitalgesellschaften: Evidenz von handelsbilanziellen Mikrodaten," Zeitschrift für Wirtschaftspolitik, De Gruyter, vol. 66(1), pages 1-35, April.
  • Handle: RePEc:lus:zwipol:v:66:y:2017:i:1:p:1-35:n:3
    DOI: 10.1515/zfwp-2017-0003
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    Cited by:

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    2. Gebhardt Heinz & Siemers Lars-H. R., 2017. "Die relative Steuerbelastung mittelständischer Kapitalgesellschaften: Evidenz von handelsbilanziellen Mikrodaten," Zeitschrift für Wirtschaftspolitik, De Gruyter, vol. 66(1), pages 1-35, April.
    3. Ademmer, Martin & Boysen-Hogrefe, Jens & Fiedler, Salomon & Groll, Dominik & Jannsen, Nils & Kooths, Stefan & Potjagailo, Galina, 2017. "Deutsche Konjunktur im Sommer 2017 - Deutsche Wirtschaft mit überhöhter Drehzahl [German Economy Summer 2017 - German economy heating up]," Kieler Konjunkturberichte 32, Kiel Institute for the World Economy (IfW Kiel).

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    More about this item

    Keywords

    backward-looking tax burden measurement; SMEs; financial-statement data; corporate income taxation; base eroding and profit shifting; effektive Unternehmenssteuerbelastung; KMU; Handelsbilanzdaten; vergangenheitsorientierte Steuerlastmessung; Steuerreform 2000; backward-looking tax burden measurement; SMEs; financial-statement data; corporate income taxation; base eroding and profit shifting;
    All these keywords.

    JEL classification:

    • H22 - Public Economics - - Taxation, Subsidies, and Revenue - - - Incidence
    • H25 - Public Economics - - Taxation, Subsidies, and Revenue - - - Business Taxes and Subsidies
    • H26 - Public Economics - - Taxation, Subsidies, and Revenue - - - Tax Evasion and Avoidance
    • C00 - Mathematical and Quantitative Methods - - General - - - General
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access

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