IDEAS home Printed from https://ideas.repec.org/a/hyp/journl/v3y2015i1p20-28.html
   My bibliography  Save this article

The Determinants of Gini Coefficient in Iran Based on Bayesian Model Averaging

Author

Listed:
  • Mohsen Mehrara

    (Faculty of Economics, University of Tehran, Tehran, Iran)

  • Mojtaba Mohammadian

    (University of Tehran, Tehran, Iran)

Abstract

This paper has tried to apply BMA approach in order to investigate important influential variables on Gini coefficient in Iran over the period 1976-2010. The results indicate that the GDP growth is the most important variable affecting the Gini coefficient and has a positive influence on it. Also the second and third effective variables on Gini coefficient are respectively the ratio of government current expenditure to GDP and the ratio of oil revenue to GDP which lead to an increase in inequality. This result is corresponding with rentier state theory in Iran economy. Injection of massive oil revenue to Iran's economy and its high share of the state budget leads to inefficient government spending and an increase in rent-seeking activities in the country. Economic growth is possibly a result of oil revenue in Iran economy which has caused inequality in distribution of income.

Suggested Citation

  • Mohsen Mehrara & Mojtaba Mohammadian, 2015. "The Determinants of Gini Coefficient in Iran Based on Bayesian Model Averaging," Hyperion Economic Journal, Faculty of Economic Sciences, Hyperion University of Bucharest, Romania, vol. 3(1), pages 20-28, March.
    • Handle: RePEc:hyp:journl:v:3:y:2015:i:1:p:20-28
    as

    Download full text from publisher

    File URL: http://hej.hyperion.ro/articles/1(3)_2015/HEJ%20nr1(3)_2015_A2Mehrara.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Zubair Chishti & Hafiz Syed Muhammad Azeem & Muhammad Kamran Khan, 2023. "Asymmetric nexus between commercial policies and consumption-based carbon emissions: new evidence from Pakistan," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 9(1), pages 1-24, December.
    2. Tessa Conroy & Steven Deller & Philip Watson, 2021. "Regional income inequality: a link to women-owned businesses," Small Business Economics, Springer, vol. 56(1), pages 189-207, January.

    More about this item

    Keywords

    Gini coefficient; Bayesian Model Averaging (BMA);

    JEL classification:

    • H53 - Public Economics - - National Government Expenditures and Related Policies - - - Government Expenditures and Welfare Programs
    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • I38 - Health, Education, and Welfare - - Welfare, Well-Being, and Poverty - - - Government Programs; Provision and Effects of Welfare Programs

    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:hyp:journl:v:3:y:2015:i:1:p:20-28. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Iulian Panait (email available below). General contact details of provider: https://edirc.repec.org/data/fehypro.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.