IDEAS home Printed from https://ideas.repec.org/a/bla/ecorec/v57y1981i2p128-139.html
   My bibliography  Save this article

Profits, Variability of Profits and the Prices Justification Tribunal

Author

Listed:
  • D. R. CHAPMAN
  • C. W. JUNOR

Abstract

In 1973 the Prices Justification Tribunal was established and given certain powers over the price‐setting practices of large firms in Australia. This paper addresses itself to the impact of that body on firms' markup. Using a large sample of Australian firms observed from 1969 to 1978, this paper establishes evidence that although a statistically significant downward effect on firms' markup can be attributed to the tribunal, in numerical terms the effect has been very small.

Suggested Citation

  • D. R. Chapman & C. W. Junor, 1981. "Profits, Variability of Profits and the Prices Justification Tribunal," The Economic Record, The Economic Society of Australia, vol. 57(2), pages 128-139, June.
  • Handle: RePEc:bla:ecorec:v:57:y:1981:i:2:p:128-139
    DOI: 10.1111/j.1475-4932.1981.tb01045.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1475-4932.1981.tb01045.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1475-4932.1981.tb01045.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Hersh, Larry & Sundararajan, V, 1979. "Heteroscedasticity: Sampling Experiments on Weighted Least Squares Using MINQU Estimates of Variances and Other Variance Estimates," Australian Economic Papers, Wiley Blackwell, vol. 18(33), pages 351-361, December.
    2. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Montgomery, D. & Swinnen, G. & Vanhoof, K., 1997. "Comparison of some AI and statistical classification methods for a marketing case," European Journal of Operational Research, Elsevier, vol. 103(2), pages 312-325, December.
    2. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.
    3. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2020. "Application of Discriminant Analysis for Avoiding the Risk of Quarry Operation Failure," JRFM, MDPI, vol. 13(10), pages 1-14, September.
    4. Dean Fantazzini & Silvia Figini, 2009. "Random Survival Forests Models for SME Credit Risk Measurement," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 29-45, March.
    5. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
    6. Larry G. Perry & Glenn V. Henderson Jr. & Timothy P. Cronan, 1984. "Multivariate Analysis Of Corporate Bond Ratings And Industry Classifications," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 7(1), pages 27-36, March.
    7. Premachandra, I.M. & Chen, Yao & Watson, John, 2011. "DEA as a tool for predicting corporate failure and success: A case of bankruptcy assessment," Omega, Elsevier, vol. 39(6), pages 620-626, December.
    8. Paul G. Farnham & George S. Cluff, 1982. "Municipal Bond Ratings: New Results, New Directions," Public Finance Review, , vol. 10(4), pages 427-455, October.
    9. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
    10. Serrano Cinca, C. & Mar Molinero, C. & Gallizo Larraz, J.L., 2005. "Country and size effects in financial ratios: A European perspective," Global Finance Journal, Elsevier, vol. 16(1), pages 26-47, August.
    11. Martin Vojtek & Evžen Koèenda, 2006. "Credit-Scoring Methods (in English)," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 56(3-4), pages 152-167, March.
    12. Poon, Winnie P. H. & Firth, Michael & Fung, Hung-Gay, 1999. "A multivariate analysis of the determinants of Moody's bank financial strength ratings," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 9(3), pages 267-283, August.
    13. Tony R. Wingler & James M. Watts, 1982. "Electric Utility Bond Rating Changes: Methodological Issues And Evidence," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 5(3), pages 221-235, September.
    14. En-Der Su & Shih-Ming Huang, 2010. "Comparing Firm Failure Predictions Between Logit, KMV, and ZPP Models: Evidence from Taiwan’s Electronics Industry," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 17(3), pages 209-239, September.
    15. Chrysovalantis Gaganis & Fotios Pasiouras & Charalambos Spathis & Constantin Zopounidis, 2007. "A comparison of nearest neighbours, discriminant and logit models for auditing decisions," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 15(1‐2), pages 23-40, January.
    16. Laitinen, Erkki K., 2007. "Classification accuracy and correlation: LDA in failure prediction," European Journal of Operational Research, Elsevier, vol. 183(1), pages 210-225, November.
    17. Ha-Thu Nguyen, 2016. "Reject inference in application scorecards: evidence from France," EconomiX Working Papers 2016-10, University of Paris Nanterre, EconomiX.
    18. Harper, Susan D. & Wharton, B. Robert & Traylor, Harlon D., 1985. "A Prediction Of Grain Elevator Bankruptcies Using Linear Discriminant Analysis," 1985 Annual Meeting, August 4-7, Ames, Iowa 278559, American Agricultural Economics Association (New Name 2008: Agricultural and Applied Economics Association).
    19. Yufei Xia & Xinyi Guo & Yinguo Li & Lingyun He & Xueyuan Chen, 2022. "Deep learning meets decision trees: An application of a heterogeneous deep forest approach in credit scoring for online consumer lending," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1669-1690, December.
    20. Ibtissem Baklouti, 2014. "A Psychological Approach To Microfinance Credit Scoring Via A Classification And Regression Tree," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(4), pages 193-208, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bla:ecorec:v:57:y:1981:i:2:p:128-139. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/esausea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.