IDEAS home Printed from https://ideas.repec.org/p/icr/wpicer/19-2002.html
   My bibliography  Save this paper

A Duration-Sensitive Measure of the Unemployment Rate: Theory and Application

Author

Listed:
  • Vani K. Borooah

Abstract

The measurement of unemployment, like that of poverty, involves two distict steps: identification and aggregation. In this two-step process, the issue of identifying the unemployed has received considerable attention but, once the unemployed have been identiified, the aggregation issue has been addressed by simply "counting heads": the unemployment rate is conventionally defined as the proportion of the labour force that, on a given date, is unemployed. This, in particular, leads to differences between individuals, in their unemployment experiences being ignored when the unemployment rate is being computed. This paper - predicated on the proposition that what matters to a person is not just the fact of unemployment but also its duration - proposes a methodology, derived from the measurement of income inequality, for adjusting unemployment rates so as to make them "duration-sensitive". In consequence, different values of the "duration-sensitive" rate will, depending upon the degree of inequality in the distribution of unemployment duration, and upon the extent to which society is averse to such inequality, be associated with the same value of the conventionally defined unemployment rate. A numerical example, based on published data for seven major OECD countries, illustrates the methodology.

Suggested Citation

  • Vani K. Borooah, 2002. "A Duration-Sensitive Measure of the Unemployment Rate: Theory and Application," ICER Working Papers 19-2002, ICER - International Centre for Economic Research.
  • Handle: RePEc:icr:wpicer:19-2002
    as

    Download full text from publisher

    File URL: http://www.bemservizi.unito.it/repec/icr/wp2002/borooah19-02.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. C. M. Beach & S. F. Kaliski, 1986. "Lorenz Curve Inference with Sample Weights: An Application to the Distribution of Unemployment Experience," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 35(1), pages 38-45, March.
    2. Sen, Amartya K, 1976. "Poverty: An Ordinal Approach to Measurement," Econometrica, Econometric Society, vol. 44(2), pages 219-231, March.
    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. Basu, Kaushik & Nolen, Patrick, 2004. "Vulnerability, Unemployment and Poverty: A New Class of Measures, Its Axiomatic Properties and Application," Working Papers 04-07, Cornell University, Center for Analytic Economics.
    2. Naschold, Felix, 2016. "Measuring Poverty Over Time - Accounting for the intertemporal distribution of poverty," 2016 Annual Meeting, July 31-August 2, Boston, Massachusetts 235722, Agricultural and Applied Economics Association.
    3. García, A., 2016. "Oaxaca-Blinder Type Counterfactual Decomposition Methods for Duration Outcomes," Documentos de Trabajo 014186, Universidad del Rosario.
    4. Carlos Gradín & Olga Cantó & Coral del Río, 2015. "Unemployment and spell duration during the Great Recession in the EU," International Journal of Manpower, Emerald Group Publishing, vol. 36(2), pages 216-235, May.
    5. Sripad Motiram & Karthikeya Naraparaju, 2014. "Unemployment burden and its distribution: Theory and evidence from India," Working Papers 341, ECINEQ, Society for the Study of Economic Inequality.
    6. Stephen Bazen & Xavier Joutard & Mouhamadou M. Niang, 2012. "The Duration-Based Measurement of Unemployment: Estimation Issues and an Application to Male-Female Unemployment Differences in France," Working Papers halshs-00793056, HAL.
    7. Carlos Gradín & Coral Del Río & Olga Cantó, 2012. "Measuring Poverty Accounting For Time," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 58(2), pages 330-354, June.
    8. Stephen Bazen & Xavier Joutard & Mouhamadou Niang, 2014. "The measurement of unemployment using completed durations: evidence on the gender gap in unemployment in France," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 12(4), pages 517-534, December.
    9. Peter Lambert, 2009. "Mini-symposium: The 1990, 1992 and 1993 papers on distributionally sensitive measures of unemployment by Manimay Sengupta and Anthony Shorrocks," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 7(3), pages 269-271, September.
    10. Carlos Gradín & Olga Cantó & Coral Río, 2017. "Measuring employment deprivation in the EU using a household-level index," Review of Economics of the Household, Springer, vol. 15(2), pages 639-667, June.
    11. Sripad Motiram & Karthikeya Naraparaju, 2014. "Unemployment Burden and its Distribution: Theory and Evidence from India," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2014-026, Indira Gandhi Institute of Development Research, Mumbai, India.
    12. Sripad Motiram & Karthikeya Naraparaju, 2014. "Unemployment Burden and its Distribution: Theory and Evidence from India," Working Papers id:6066, eSocialSciences.
    13. Carlos Gradin & Olga Canto & Coral del Rio, 2012. "Measuring employment deprivation among households in the EU," Working Papers 247, ECINEQ, Society for the Study of Economic Inequality.
    14. Basu, K & Nolen, PJ, 2006. "Vulnerability, Unemployment and Poverty: A Class of Distribution and Sensitive Measures, Its Axiomatic Properties and Applications," Economics Discussion Papers 2911, University of Essex, Department of Economics.

    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. Edwin Fourrier-Nicolaï & Michel Lubrano, 2020. "Bayesian inference for TIP curves: an application to child poverty in Germany," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 18(1), pages 91-111, March.
    2. Coral del Río & Javier Ruiz-Castillo, 2001. "TIPs for poverty analysis. The case of Spain, 1980-81 to 1990-91," Investigaciones Economicas, Fundación SEPI, vol. 25(1), pages 63-91, January.
    3. Chakravarty, Satya R. & Deutsch, Joseph & Silber, Jacques, 2008. "On the Watts Multidimensional Poverty Index and its Decomposition," World Development, Elsevier, vol. 36(6), pages 1067-1077, June.
    4. Borooah, Vani, 2007. "Measuring economic inequality: deprivation, economising and possessing," MPRA Paper 19422, University Library of Munich, Germany.
    5. Belhadj, Besma & Limam, Mohamed, 2012. "Unidimensional and multidimensional fuzzy poverty measures: New approach," Economic Modelling, Elsevier, vol. 29(4), pages 995-1002.
    6. Julie Litchfield & Patricia Justino, 2004. "Welfare in Vietnam during the 1990s: Poverty, inequality and poverty dynamics," Journal of the Asia Pacific Economy, Taylor & Francis Journals, vol. 9(2), pages 145-169.
    7. Duclos, Jean-Yves & Araar, Abdelkrim & Giles, John, 2010. "Chronic and transient poverty: Measurement and estimation, with evidence from China," Journal of Development Economics, Elsevier, vol. 91(2), pages 266-277, March.
    8. Russell Davidson & Jean-Yves Duclos, 2000. "Statistical Inference for Stochastic Dominance and for the Measurement of Poverty and Inequality," Econometrica, Econometric Society, vol. 68(6), pages 1435-1464, November.
    9. Temple, Jonathan & Ying, Huikang, 2014. "Life During Structural Transformation," CEPR Discussion Papers 10297, C.E.P.R. Discussion Papers.
    10. Gaurav Datt & Martin Ravallion, 1998. "Farm productivity and rural poverty in India," Journal of Development Studies, Taylor & Francis Journals, vol. 34(4), pages 62-85.
    11. Vito Peragine & Ernesto Savaglio & Stefano Vannucci, 2008. "Poverty Rankings of Opportunity Profiles," Department of Economics University of Siena 548, Department of Economics, University of Siena.
    12. Ravallion, Martin & Chen, Shaohua, 2003. "Measuring pro-poor growth," Economics Letters, Elsevier, vol. 78(1), pages 93-99, January.
    13. Chattopadhyay, Amit K. & Mallick, Sushanta K., 2007. "Income distribution dependence of poverty measure: A theoretical analysis," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 377(1), pages 241-252.
    14. Constantine Angyridis & Brennan Scott Thompson, 2016. "Negative income taxes, inequality and poverty," Canadian Journal of Economics, Canadian Economics Association, vol. 49(3), pages 1016-1034, August.
    15. Davidson, Russell, 2009. "Reliable inference for the Gini index," Journal of Econometrics, Elsevier, vol. 150(1), pages 30-40, May.
    16. Bossert, Walter & D’Ambrosio, Conchita, 2014. "Proximity-sensitive individual deprivation measures," Economics Letters, Elsevier, vol. 122(2), pages 125-128.
    17. Hippu Salk Kristle Nathan & Srijit Mishra, 2008. "On Measuring Group Differential - Some Further Results," Development Economics Working Papers 22343, East Asian Bureau of Economic Research.
    18. Boyd H. Hunter & Steven Kennedy & Nicholas Biddle, 2004. "Indigenous and Other Australian Poverty: Revisiting the Importance of Equivalence Scales," The Economic Record, The Economic Society of Australia, vol. 80(251), pages 411-422, December.
    19. Carlisle Ford Runge, 1984. "Strategic Interdependence in Models of Property Rights," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 66(5), pages 807-813.
    20. Benoit Decerf, 2021. "Combining absolute and relative poverty: income poverty measurement with two poverty lines," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 56(2), pages 325-362, February.

    More about this item

    JEL classification:

    • J64 - Labor and Demographic Economics - - Mobility, Unemployment, Vacancies, and Immigrant Workers - - - Unemployment: Models, Duration, Incidence, and Job Search

    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:icr:wpicer:19-2002. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/icerrit.html .

    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: Simone Pellegrino (email available below). General contact details of provider: https://edirc.repec.org/data/icerrit.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.