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How Long is a Spell of Unemployment?: Illusions and Biases in the Use of CPS Data

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  • Nicholas M. Kiefer
  • Shelly J. Lundberg
  • George R. Neumann

Abstract

Most data used to study the durations of unemployment spells come from the Current Population Survey, which is a point-in-time survey and gives an incomplete picture of the underlying duration distribution. We introduce a new sample of completed unemployment spells obtained from panel data and apply CPS sampling and reporting techniques to replicate the type of data used by other researchers. Predicted duration distributions derived from this CPS-like data are then compared to the actual distribution. We conclude that the best inferences that can be made about unemployment durations using CPS-like data are seriously biased.

Suggested Citation

  • Nicholas M. Kiefer & Shelly J. Lundberg & George R. Neumann, 1984. "How Long is a Spell of Unemployment?: Illusions and Biases in the Use of CPS Data," NBER Working Papers 1467, National Bureau of Economic Research, Inc.
    • Handle: RePEc:nbr:nberwo:1467
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    References listed on IDEAS

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    10. repec:bla:econom:v:46:y:1979:i:183:p:239-60 is not listed on IDEAS
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    Cited by:

    1. Jacoby, Sanford M. & Sharma, Sunil, 1992. "Employment Duration and Industrial Labor Mobility in the United States, 1880–1980," The Journal of Economic History, Cambridge University Press, vol. 52(1), pages 161-179, March.
    2. Haroon Bhorat & David Tseng, 2012. "The Newly Unemployed and the UIF Take-up Rate in the South African Labour Market," Working Papers 12147, University of Cape Town, Development Policy Research Unit.
    3. Francisco J. Gil & Maria Jesus Martin & Angel Serrat, 1994. "Movilidad en el mercado de trabajo en España: un análisis econométrico de duración con riesgos en competencia," Investigaciones Economicas, Fundación SEPI, vol. 18(3), pages 517-537, September.
    4. Villagarcía, Teresa, 1992. "Measuring the effects of covariates on duration data through completely censored and lengith biased cps-like data," UC3M Working papers. Economics 2840, Universidad Carlos III de Madrid. Departamento de Economía.
    5. Bowles, Roger Arthur & Florackis, Chrisostomos, 2007. "Duration of the time to reconviction: Evidence from UK prisoner discharge data," Journal of Criminal Justice, Elsevier, vol. 35(4), pages 365-378.
    6. Ignez M. Tristao, 2007. "Occupational Employment Risk and its Consequences for Unemployment Duration and Wages: Working Paper 2007-01," Working Papers 18287, Congressional Budget Office.
    7. Jones, Stephen R G & Riddell, W Craig, 1995. "The Measurement of Labor Force Dynamics with Longitudinal Data: The Labour Market Activity Survey Filter," Journal of Labor Economics, University of Chicago Press, vol. 13(2), pages 351-385, April.
    8. Lester Lusher & Geoffrey C. Schnorr & Rebecca L.C. Taylor, 2022. "Unemployment Insurance as a Worker Indiscipline Device? Evidence from Scanner Data," American Economic Journal: Applied Economics, American Economic Association, vol. 14(2), pages 285-319, April.
    9. Alfred Garloff & Stefan Werth, 2013. "Characterizing unemployment duration data with stock sample measures," ERSA conference papers ersa13p849, European Regional Science Association.
    10. Bindler, Anna, 2016. "Still unemployed, what next? Crime and unemployment duration," Working Papers in Economics 660, University of Gothenburg, Department of Economics.
    11. Yang, Zhenlin & Tsui, Albert K., 2004. "Analytically calibrated Box-Cox percentile limits for duration and event-time models," Insurance: Mathematics and Economics, Elsevier, vol. 35(3), pages 649-677, December.
    12. Anthony Shorrocks, 2009. "Spell incidence, spell duration and the measurement of unemployment," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 7(3), pages 295-310, September.

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