IDEAS home Printed from https://ideas.repec.org/p/cde/cdewps/185.html
   My bibliography  Save this paper

Does Affirmative Action Affect Productivity In The Indian Railways?

Author

Listed:
  • Ashwini Deshpande

    (Department of Economics, Delhi School of Economics, Delhi, India)

  • Thomas E. Weisskopf

    (University of Michigan, Ann Arbor)

Abstract

Our objective in this paper is to shed some empirical light on a claim often made by critics of affirmative action policies: that increasing the representation of members of marginalized communities in jobs – and especially in relatively skilled positions – comes at a cost of reduced efficiency. We undertake a systematic empirical analysis of productivity in the Indian Railways in order to determine whether increasing proportions of Scheduled Castes and Scheduled Tribes in railway employment – largely a consequence of India's affirmative action policies – have actually reduced productive efficiency in the railway system. We find no evidence that higher percentages of Scheduled Castes and Scheduled Tribes in the railway labour force have reduced productivity. Indeed, some of our results suggest that the opposite is true, providing tentative support for the claim that greater labour force diversity boosts productivity.

Suggested Citation

  • Ashwini Deshpande & Thomas E. Weisskopf, 2010. "Does Affirmative Action Affect Productivity In The Indian Railways?," Working papers 185, Centre for Development Economics, Delhi School of Economics.
  • Handle: RePEc:cde:cdewps:185
    as

    Download full text from publisher

    File URL: http://www.cdedse.org/pdf/work185.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Baltagi, Badi H. & Li, Qi, 1991. "A joint test for serial correlation and random individual effects," Statistics & Probability Letters, Elsevier, vol. 11(3), pages 277-280, March.
    2. T. S. Breusch & A. R. Pagan, 1980. "The Lagrange Multiplier Test and its Applications to Model Specification in Econometrics," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 47(1), pages 239-253.
    3. Ray,Subhash C., 2012. "Data Envelopment Analysis," Cambridge Books, Cambridge University Press, number 9781107405264.
    4. Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
    5. David Neumark & Harry Holzer, 2000. "Assessing Affirmative Action," Journal of Economic Literature, American Economic Association, vol. 38(3), pages 483-568, September.
    6. James Levinsohn & Amil Petrin, 2003. "Estimating Production Functions Using Inputs to Control for Unobservables," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 70(2), pages 317-341.
    7. Jerry Coakley & Ana-Maria Fuertes & Ron Smith, 2002. "A Principal Components Approach to Cross-Section Dependence in Panels," 10th International Conference on Panel Data, Berlin, July 5-6, 2002 B5-3, International Conferences on Panel Data.
    8. Baltagi, Badi H. & Griffin, James M., 1997. "Pooled estimators vs. their heterogeneous counterparts in the context of dynamic demand for gasoline," Journal of Econometrics, Elsevier, vol. 77(2), pages 303-327, April.
    9. Alivelu, G., 2008. "Analysis of Productivity Trends on Indian Railways," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 47(1).
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Elaine McCrate, 2013. "Screening for honesty and motivation in the workplace: what can affirmative action do?," Chapters, in: Jeannette Wicks-Lim & Robert Pollin (ed.), Capitalism on Trial, chapter 15, Edward Elgar Publishing.
    2. Borooah, Vani, 2019. "Discrimination and Jobs Reservation in India," MPRA Paper 101671, University Library of Munich, Germany.

    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. Hasan Vergil & Fuat Sekmen & Haşmet Gökirmak & Sukru Apaydin, 2022. "2008 financial crisis and income distribution in Turkey," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2627-2643, August.
    2. Bera, Anil K. & Sosa-Escudero, Walter & Yoon, Mann, 2001. "Tests for the error component model in the presence of local misspecification," Journal of Econometrics, Elsevier, vol. 101(1), pages 1-23, March.
    3. Croissant, Yves & Millo, Giovanni, 2008. "Panel Data Econometrics in R: The plm Package," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 27(i02).
    4. Wu, Jianhong & Zhu, Lixing, 2011. "Testing for serial correlation and random effects in a two-way error component regression model," Economic Modelling, Elsevier, vol. 28(6), pages 2377-2386.
    5. Gilberto Fraga & Carlos Bacha, 2011. "The Non-linearity of the Relationship between Human Capital and Exports in Brazil – evidences of regional differences," ERSA conference papers ersa11p1016, European Regional Science Association.
    6. Ball, V. Eldon & San Juan, Carlos & Ulloa, Camilo, 2012. "State Productivity Growth: Catching Up and the Business Cycle," 2012 Annual Meeting, August 12-14, 2012, Seattle, Washington 123334, Agricultural and Applied Economics Association.
    7. Deshpande, Ashwini & Weisskopf, Thomas E., 2014. "Does Affirmative Action Reduce Productivity? A Case Study of the Indian Railways," World Development, Elsevier, vol. 64(C), pages 169-180.
    8. Serap Bedir Kara & Aysegul Coskun, 2020. "The Impact of Gender Inequalities in Education on Income Corporate Social Responsibility (CSR)," Eurasian Journal of Social Sciences, Eurasian Publications, vol. 8(4), pages 148-162.
    9. Yushu Li & Fredrik N. G. Andersson, 2021. "A simple wavelet-based test for serial correlation in panel data models," Empirical Economics, Springer, vol. 60(5), pages 2351-2363, May.
    10. Baltagi, Badi H. & Jung, Byoung Cheol & Song, Seuck Heun, 2010. "Testing for heteroskedasticity and serial correlation in a random effects panel data model," Journal of Econometrics, Elsevier, vol. 154(2), pages 122-124, February.
    11. Federico Zincenko & Walter Sosa-Escudero & Gabriel Montes-Rojas, 2014. "Robust tests for time-invariant individual heterogeneity versus dynamic state dependence," Empirical Economics, Springer, vol. 47(4), pages 1365-1387, December.
    12. Coakley, Jerry & Fuertes, Ana-Maria & Smith, Ron, 2006. "Unobserved heterogeneity in panel time series models," Computational Statistics & Data Analysis, Elsevier, vol. 50(9), pages 2361-2380, May.
    13. Chen, Kevin Z. & D. Meilke, Karl & Turvey, Calum, 1999. "Income risk and farm consumption behavior," Agricultural Economics, Blackwell, vol. 20(2), pages 173-183, March.
    14. Vasilis Sarafidis & Tom Wansbeek, 2012. "Cross-Sectional Dependence in Panel Data Analysis," Econometric Reviews, Taylor & Francis Journals, vol. 31(5), pages 483-531, September.
    15. Baltagi, Badi H. & Li, Qi, 1995. "Testing AR(1) against MA(1) disturbances in an error component model," Journal of Econometrics, Elsevier, vol. 68(1), pages 133-151, July.
    16. Emir Malikov & Gudbrand Lien, 2021. "Proxy Variable Estimation of Multiproduct Production Functions," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(5), pages 1878-1902, October.
    17. Eshagh Mansourkiaee, 2023. "Estimating energy demand elasticities for gas exporting countries: a dynamic panel data approach," SN Business & Economics, Springer, vol. 3(1), pages 1-28, January.
    18. repec:jss:jstsof:27:i02 is not listed on IDEAS
    19. Alexander Chudik & M. Hashem Pesaran, 2013. "Large panel data models with cross-sectional dependence: a survey," Globalization Institute Working Papers 153, Federal Reserve Bank of Dallas.
    20. Won Koh & Byoung Cheol Jung & Badi H. Baltagi & Seuck Heun Song, 2004. "Testing for Serial Correlation, Spatial Autocorrelation and Random Effects," Econometric Society 2004 Australasian Meetings 338, Econometric Society.
    21. Walter Sosa Escudero & Anil K. Bera, 2008. "Tests for Unbalanced Error Component Models Under Local Misspecication," CEDLAS, Working Papers 0065, CEDLAS, Universidad Nacional de La Plata.

    More about this item

    Keywords

    affirmative action; labour force; productivity; Indian railways;
    All these keywords.

    JEL classification:

    • J - Labor and Demographic Economics
    • L - Industrial Organization

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:cde:cdewps:185. 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: Sanjeev Sharma (email available below). General contact details of provider: https://edirc.repec.org/data/cdudein.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.