IDEAS home Printed from https://ideas.repec.org/a/wsi/serxxx/v65y2020isupp01ns021759081944003x.html
   My bibliography  Save this article

Employment Discrimination In Indian Manufacturing Industries: A Logit Analysis

Author

Listed:
  • ARUN KUMAR BAIRWA

    (School of Humanities and Social Sciences, Indian Institute of Technology Indore, Madhya Pradesh, India)

  • JADHAV CHAKRADHAR

    (#x2020;Centre for Economic and Social Studies (CESS), Hyderabad, Telangana, India)

  • PRITEE SHARMA

    (School of Humanities and Social Sciences, Indian Institute of Technology Indore, Madhya Pradesh, India)

Abstract

Persistent socioeconomic inequalities in a society reduce the chances of employment for its weaker sections. In India, those most affected by inequality and discrimination are women, people of lower castes, rural households and illiterate people. This necessitates an analysis of the levels of discrimination and favoritism working against female, lower caste, rural and illiterate individuals in different manufacturing industries. This study presents an in-depth picture of employment in each industry with regard to the four variables selected — gender, caste, location and education. Fourth (2013–2014) and fifth (2015–2016) annual Employment and Unemployment Surveys have been used for the analysis.

Suggested Citation

  • Arun Kumar Bairwa & Jadhav Chakradhar & Pritee Sharma, 2020. "Employment Discrimination In Indian Manufacturing Industries: A Logit Analysis," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 65(supp01), pages 233-259, December.
  • Handle: RePEc:wsi:serxxx:v:65:y:2020:i:supp01:n:s021759081944003x
    DOI: 10.1142/S021759081944003X
    as

    Download full text from publisher

    File URL: http://www.worldscientific.com/doi/abs/10.1142/S021759081944003X
    Download Restriction: Access to full text is restricted to subscribers

    File URL: https://libkey.io/10.1142/S021759081944003X?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Jadhav Chakradhar & Arun Kumar Bairwa, 2020. "Employment Probabilities And Workforce Distribution In The Indian Manufacturing Sector: A State-Level Analysis," Bulletin of Monetary Economics and Banking, Bank Indonesia, vol. 23(1), pages 55-82.

    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:wsi:serxxx:v:65:y:2020:i:supp01:n:s021759081944003x. 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: Tai Tone Lim (email available below). General contact details of provider: http://www.worldscinet.com/ser/ser.shtml .

    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.