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The Estimation of Frictional Unemployment: A Stochastic Frontier Approach

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  • Warren, Ronald S, Jr

Abstract

This paper reports an estimate of the frictional unemployment rate in U.S. manufacturing that is derived from a parametric, statistical method for estimating stochastic frontiers. The steady-state, perfect-foresight solution to an estimated employment growth frontier provides a locus of technically efficient (frictional) rates of unemployment. The mean frictional unemployment rate during the sample period is estimated to be 3.7 percent of the manufacturing labor force. This estimate conforms closely to an estimate of 3.5 percent that is derived from manufacturing-sector data presented by David M. Lilien (1980) for roughly the same time period. Copyright 1991 by MIT Press.

Suggested Citation

  • Warren, Ronald S, Jr, 1991. "The Estimation of Frictional Unemployment: A Stochastic Frontier Approach," The Review of Economics and Statistics, MIT Press, vol. 73(2), pages 373-377, May.
  • Handle: RePEc:tpr:restat:v:73:y:1991:i:2:p:373-77
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    Cited by:

    1. Aomar Ibourk & Sergio Perelman, 2001. "Frontières d'efficacité et processus d'appariement sur le marché du travail au Maroc," Economie & Prévision, La Documentation Française, vol. 0(4), pages 33-45.
    2. Cahill, Miles B., 2000. "Exploring the interaction between efficiency wages and labor market frictions," The Quarterly Review of Economics and Finance, Elsevier, vol. 40(1), pages 121-137.
    3. Sergio Destefanis & Raquel Fonseca, 2006. "Labour-Market Reforms and the Beveridge Curve. Some Macro Evidence for Italy," CSEF Working Papers 168, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    4. Baños, José F. & Rodríguez-Álvarez, Ana & Suárez, Patricia, 2016. "Matching frontiers: A random parameter model approach," Efficiency Series Papers 2016/07, University of Oviedo, Department of Economics, Oviedo Efficiency Group (OEG).
    5. Carlo Altavilla & Floro Ernesto Caroleo, 2013. "Asymmetric Effects of National-based Active Labour Market Policies," Regional Studies, Taylor & Francis Journals, vol. 47(9), pages 1482-1506, October.
    6. Sergio Destefanis & Raquel Fonseca, 2006. "Labour-Market Reforms and the Beveridge Curve. Some Macro Evidence for Italy," CSEF Working Papers 168, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    7. Iva Tomic, 2012. "The Efficiency of the Matching Process: Exploring the Impact of Regional Employment Offices in Croatia," Working Papers 1204, The Institute of Economics, Zagreb.
    8. Aysun, Uluc & Bouvet, Florence & Hofler, Richard, 2014. "An alternative measure of structural unemployment," Economic Modelling, Elsevier, vol. 38(C), pages 592-603.
    9. Aomar Ibourk & Bénédicte Maillard & Sergio Perelman & Henri Sneessens, 2004. "Aggregate Matching Efficiency: A Stochastic Production Frontier Approach, France 1990–1994," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 31(1), pages 1-25, March.
    10. Altavilla, Carlo & Caroleo, Floro Ernesto, 2009. "Unintended Effects of National-based Active Labour Market Policies," IZA Discussion Papers 4045, Institute for the Study of Labor (IZA).
    11. Cuéllar Martín, Jaime & Martín-Román, Ángel L. & Moral, Alfonso, 2017. "A composed error model decomposition and spatial analysis of local unemployment," MPRA Paper 79783, University Library of Munich, Germany.
    12. Iva Tomić, 2014. "Regional matching (in)efficiency on the Croatian labour market," Acta Oeconomica, Akadémiai Kiadó, Hungary, vol. 64(3), pages 287-312, September.

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