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Is Optimal Matching Suboptimal?

Author

Listed:
  • Matissa Hollister

    (1Dartmouth College, Hanover, MA, USA, mantissa.n.hollister@dartmouth.edu)

Abstract

Optimal matching (OM) is a method for measuring the similarity between pairs of sequences (e.g., work histories). This article discusses two problems with optimal matching. First, the author identifies a flaw in OM ‘‘indel costs’’ and proposes a solution to this flaw. Second, the author discusses the need for benchmarks to measure the added value of OM and to test competing versions. To that end, the author conducts an empirical test of traditional OM, the alternative localized OM, and sequence comparison. The test documents the problem with traditional OM and shows that it is solved by localized OM. The test also demonstrates the value of OM and sequence comparison in examining occupational sequences; both methods capture variation beyond traditional human capital and status attainment measures, although the marginal improvements of OM over sequence comparison may not justify its computational complexity. These results point to the need for more systematic approaches to sequence analysis methods.

Suggested Citation

  • Matissa Hollister, 2009. "Is Optimal Matching Suboptimal?," Sociological Methods & Research, , vol. 38(2), pages 235-264, November.
    • Handle: RePEc:sae:somere:v:38:y:2009:i:2:p:235-264
    DOI: 10.1177/0049124109346164
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    References listed on IDEAS

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    Cited by:

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    2. Mark Hanly & Paul Clarke & Fiona Steele, 2016. "Sequence analysis of call record data: exploring the role of different cost settings," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 179(3), pages 793-808, June.
    3. Raffaella Piccarreta, 2017. "Joint Sequence Analysis," Sociological Methods & Research, , vol. 46(2), pages 252-287, March.
    4. Zhelyazkova, N., 2014. "Discovering and explaining work-family strategies of parents in Luxembourg," MERIT Working Papers 2014-022, United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (MERIT).
    5. Xiangyang Bi & Xueling Liu, 2024. "From “transitions” to “trajectories”: towards a holistic interactionistic analysis of educational inequality in contemporary China," Palgrave Communications, Palgrave Macmillan, vol. 11(1), pages 1-16, December.
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    7. Michael Koch & Bernard Forgues & Vanessa Monties, 2017. "The Way to the Top: Career Patterns of Fortune 100 CEOS," Post-Print hal-02051118, HAL.
    8. Liao, Tim F. & Bolano, Danilo & Brzinsky-Fay, Christian & Cornwell, Benjamin & Fasang, Anette Eva & Helske, Satu & Piccarreta, Raffaella & Raab, Marcel & Ritschard, Gilbert & Struffolino, Emanuela & S, 2022. "Sequence analysis: Its past, present, and future," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 107, pages 1-1.
    9. John Levi Martin & James P. Murphy, 2021. "Some Methods for the Analysis of Event Sequence Data from Multiple Respondents," Sociological Methods & Research, , vol. 50(3), pages 1321-1352, August.
    10. Raffaella Piccarreta, 2012. "Graphical and Smoothing Techniques for Sequence Analysis," Sociological Methods & Research, , vol. 41(2), pages 362-380, May.
    11. Hanly, Mark & Clarke, Paul & Steele, Fiona, 2016. "Sequence analysis of call record data: exploring the role of different cost settings," LSE Research Online Documents on Economics 64896, London School of Economics and Political Science, LSE Library.
    12. Christian Brzinsky-Fay & Ulrich Kohler, 2010. "New Developments in Sequence Analysis," Sociological Methods & Research, , vol. 38(3), pages 359-364, February.
    13. Schoon, Ingrid & Lyons-Amos, Mark, 2016. "Diverse pathways in becoming an adult: The role of structure, agency and context," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 46, pages 11-20.
    14. Thomas King, 2013. "A framework for analysing social sequences," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 167-191, January.
    15. Fasang, Anette Eva & Liao, Tim Futing, 2014. "Visualizing Sequences in the Social Sciences: Relative Frequency Sequence Plots," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 43(4), pages 643-676.
    16. Brian T. Pentland & Thorvald Hærem & Derek Hillison, 2011. "The (N)Ever-Changing World: Stability and Change in Organizational Routines," Organization Science, INFORMS, vol. 22(6), pages 1369-1383, December.
    17. Anette Eva Fasang & Tim Futing Liao, 2014. "Visualizing Sequences in the Social Sciences," Sociological Methods & Research, , vol. 43(4), pages 643-676, November.
    18. Elisabeth Beusch & Arthur Soest, 2020. "Labour Market Trajectories of the Self-employed in the Netherlands," De Economist, Springer, vol. 168(1), pages 109-146, March.
    19. Struffolino, Emanuela & Studer, Matthias & Fasang, Anette Eva, 2016. "Gender, education, and family life courses in East and West Germany: Insights from new sequence analysis techniques," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 29, pages 66-79.
    20. Dirk Witteveen & Johan Westerman, 2023. "Structural Change Shapes Career Mobility Opportunities: An Analysis of Cohorts, Gender and Parental Class," Work, Employment & Society, British Sociological Association, vol. 37(1), pages 97-116, February.

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