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A Dynamic Panel Analysis of the Profitability of Australian Tax Entities

Author

Listed:
  • Simon Feeny

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

  • Mark N. Harris

    (Melbourne Institute of Applied Economic and Social Research, The University of Melbourne and Central European University, Budapest, Hungary)

  • Joanne Loundes

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

Abstract

This paper investigates the determinants of profitability of Australian tax entities over the period 1993/94 to 1996/97 for each of 91 three-digit ANZSIC industries. The theoretical model is based on that of Cowling and Waterson (1976). However, it is augmented by the inclusion of lagged profitability to allow for habit persistence in entity profitability. The so-called operational Wansbeek-Bekker estimator is used to control for endogeneity of this lagged dependent variable, whilst simultaneously controlling for observed and unobserved entity heterogeneity. Aggregate results suggest that profitability in the previous year, entity capital intensity, and barriers to entry have the expected positive association with current profitability measured by the price-cost margin. Entity market share-and to a lesser extent concentration-are found to have a U shaped relationship with profitability.

Suggested Citation

  • Simon Feeny & Mark N. Harris & Joanne Loundes, 2000. "A Dynamic Panel Analysis of the Profitability of Australian Tax Entities," Melbourne Institute Working Paper Series wp2000n22, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
  • Handle: RePEc:iae:iaewps:wp2000n22
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    File URL: http://melbourneinstitute.unimelb.edu.au/downloads/working_paper_series/wp2000n22.pdf
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    References listed on IDEAS

    as
    1. Ian Domowitz & R. Glenn Hubbard & Bruce C. Petersen, 1986. "Business Cycles and the Relationship Between Concentration and Price-Cost Margins," RAND Journal of Economics, The RAND Corporation, vol. 17(1), pages 1-17, Spring.
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    4. Simon Feeny, 2000. "Determinants of Profitability: An Empirical Investigation Using Australian Tax Entities," Melbourne Institute Working Paper Series wp2000n01, Melbourne Institute of Applied Economic and Social Research, The University of Melbourne.
    5. Demsetz, Harold, 1973. "Industry Structure, Market Rivalry, and Public Policy," Journal of Law and Economics, University of Chicago Press, vol. 16(1), pages 1-9, April.
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    Cited by:

    1. Ashwin Madhou & Imad Moosa & Vikash Ramiah, 2015. "Working Capital as a Determinant of Corporate Profitability," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 18(04), pages 1-17, December.
    2. Kounetas, Kostas & Alexopoulos, Elias & Tzelepis, Dimitris, 2016. "Environmental and Financial Performance. Is there a win-win or a win-loss situation? Evidence from the Greek manufacturing," MPRA Paper 80906, University Library of Munich, Germany, revised 19 Jul 2017.
    3. Kounetas, Kostas & Tsekouras, Kostas, 2008. "The energy efficiency paradox revisited through a partial observability approach," Energy Economics, Elsevier, vol. 30(5), pages 2517-2536, September.
    4. Nina Ponikvar & Maks Tajnikar, 2011. "Are the Determinants of Markup Size Industry-Specific? The Case of Slovenian Manufacturing Firms," Panoeconomicus, Savez ekonomista Vojvodine, Novi Sad, Serbia, vol. 58(2), pages 229-244, June.
    5. Sonia Baños-Caballero & Pedro García-Teruel & Pedro Martínez-Solano, 2012. "How does working capital management affect the profitability of Spanish SMEs?," Small Business Economics, Springer, vol. 39(2), pages 517-529, September.
    6. Tamminen, Saara & Chang, Han-Hsin, 2012. "Company heterogeneity and mark-up variability," Working Papers 32, VATT Institute for Economic Research.
    7. Huang, Bwo-Nung & Hwang, M.J. & Yang, C.W., 2008. "Causal relationship between energy consumption and GDP growth revisited: A dynamic panel data approach," Ecological Economics, Elsevier, vol. 67(1), pages 41-54, August.

    More about this item

    JEL classification:

    • C23 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Models with Panel Data; Spatio-temporal Models
    • F18 - International Economics - - Trade - - - Trade and Environment

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