IDEAS home Printed from https://ideas.repec.org/a/ris/qjatoe/0295.html
   My bibliography  Save this article

ANALYSIS of OVERTIME BEHAVIOR IN THE iRANIAN LABOR MARKET WITH DECISION-TREE APPROACH

Author

Listed:
  • Naghavi, Somayeh Sadat

    (Ph.D. Candidate in Economics, Ferdowsi University of Mashhad)

  • Hooshmand, Mahmoud

    (Professor of Economics, Ferdowsi University of Mashhad)

  • Malek Sadati, Seyed Saeed

    (Assistant Professor of Economics, Ferdowsi University of Mashhad)

Abstract

Understanding the behavior of the workforce in cases involving individuals' decision to work overtime, is crucial to accurately assessing the effects of employment policies; Given that the issue of overtime in the analysis of human resources and the labor market system in macroeconomics, has been somewhat ignored, and on the other hand, changing the approach to the use and management of overtime in certain circumstances can be an unavoidable option in the labor market, this article examines the feasibility of this issue by analyzing the behavior of the Iranian labor force using the cost and income statistics of urban households for the period 2005-2020 and the factors that influence the individual's decision regarding Examines effective overtime. The technique used is one of the data mining techniques, and in particular, the Decision Tree algorithm, which allows us to study their behavior by realizing the underlying distribution of the data obtained from the set of subjects under study. The results suggest that overtime is difficult to define by individual-level characteristics such as age, education, gender, work attitudes, or any other invisible factor represented by these variables, but it can be defined as job attribute, the structural features of the labor market, as well as the cost decile in which the household is located, so that if these results are further supported, there will be significant consequences for both individuals and policymakers for workforce optimal allocation

Suggested Citation

  • Naghavi, Somayeh Sadat & Hooshmand, Mahmoud & Malek Sadati, Seyed Saeed, 2023. "ANALYSIS of OVERTIME BEHAVIOR IN THE iRANIAN LABOR MARKET WITH DECISION-TREE APPROACH," Quarterly Journal of Applied Theories of Economics, Faculty of Economics, Management and Business, University of Tabriz, vol. 9(4), pages 277-306, March.
  • Handle: RePEc:ris:qjatoe:0295
    as

    Download full text from publisher

    File URL: https://ecoj.tabrizu.ac.ir/article_16005_da4f38ee94d39d414810876fde4429a1.pdf
    File Function: Full text
    Download Restriction: no
    ---><---

    More about this item

    Keywords

    Overtime Working; Labor Market; Labor Behavior; Machine Learning Model (ML); Decision Tree;
    All these keywords.

    JEL classification:

    • J21 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Labor Force and Employment, Size, and Structure
    • J22 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Time Allocation and Labor Supply
    • J30 - Labor and Demographic Economics - - Wages, Compensation, and Labor Costs - - - General
    • J82 - Labor and Demographic Economics - - Labor Standards - - - Labor Force Composition
    • M54 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Management

    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:ris:qjatoe:0295. 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: Sakineh Sojoodi (email available below). General contact details of provider: https://edirc.repec.org/data/fetabir.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.