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Optimal Matching and Social Sciences

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  • Laurent Lesnard

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Abstract

This working paper is a reflection on the conditions required to use optimalmatching (OM) in social sciences. Despite its striking success in biology, optimalmatching was not invented to solve biological questions but computer science ones:OM is a family of distance concepts originating in information and coding theorywere it is known under various names among which Hamming, and Levenshteindistance. As a consequence, the success of this method in biology has nothing to dowith the alleged similarity of the way it operates with biological processes but withchoices of parameters in accordance with the kind of materials and questionsbiologists are facing. As materials and questions differ in social sciences, it is notpossible to import OM directly from biology. The very basic fact that sequences ofsocial events are not made of biological matter but of events and time is crucial forthe adaptation of OM: insertion and deletion operations warp time and are to beavoided if information regarding the social regulation of the timing of event is to befully recovered. A formulation of substitution costs taking advantage of the socialstructuration of time is proposed for sequences sharing the same calendar: dynamicsubstitution costs can be derived from the series of transition matrices describingsocial sub-rhythms. An application to the question of the scheduling of work isproposed: using data from the 1985-86 and 1998-99 French time-use surveys,twelve types of workdays are uncovered. Their interpretability and quality,assessed visually through aggregate and individual tempograms, and box plots,seem satisfactory.

Suggested Citation

  • Laurent Lesnard, 2006. "Optimal Matching and Social Sciences," Working Papers 2006-01, Center for Research in Economics and Statistics.
    • Handle: RePEc:crs:wpaper:2006-01
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    Cited by:

    1. Paolo Lucchino & Dr Richard Dorsett, 2013. "Visualising the school-to-work transition: an analysis using optimal matching," National Institute of Economic and Social Research (NIESR) Discussion Papers 414, National Institute of Economic and Social Research.
    2. Arnstein Aassve & Francesco C. Billari & Raffaella Piccarreta, 2007. "Strings of Adulthood: A Sequence Analysis of Young British Women’s Work-Family Trajectories," European Journal of Population, Springer;European Association for Population Studies, vol. 23(3), pages 369-388, October.
    3. Luca Maria Pesando & Nicola Barban & Maria Sironi & Frank F. Furstenberg, 2021. "A Sequence‐Analysis Approach to the Study of the Transition to Adulthood in Low‐ and Middle‐Income Countries," Population and Development Review, The Population Council, Inc., vol. 47(3), pages 719-747, September.
    4. Bicaba, Zorobabel, 2011. "Growth and financial reforms trajectory: an optimal matching sequence analysis approach," MPRA Paper 34057, University Library of Munich, Germany.
    5. Vicentini, Francesca & Boccardelli, Paolo, 2016. "Career diversity and project performance in the Italian television industry," Journal of Business Research, Elsevier, vol. 69(7), pages 2380-2387.
    6. H. Corrales-Herrero & B. Rodr z-Prado, 2012. "Characterizing Spanish labour pathways of young people with vocational lower-secondary education," Applied Economics, Taylor & Francis Journals, vol. 44(29), pages 3777-3792, October.
    7. Herrmann & Kim van der Putten, 2014. "Uraveling start-up processes with the help of sequence analyses," Innovation Studies Utrecht (ISU) working paper series 14-02, Utrecht University, Department of Innovation Studies, revised Jun 2014.
    8. Thomas King, 2013. "A framework for analysing social sequences," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 167-191, January.
    9. Paolo Lucchino & Dr Richard Dorsett, 2013. "Visualising the school-to-work transition: an analysis using optimal matching," National Institute of Economic and Social Research (NIESR) Discussion Papers 414, National Institute of Economic and Social Research.
    10. Helena Corrales Herrero & Beatriz Rodríguez Prado, 2011. "Characterizing Spanish Labour Pathways of young people with vocational lower-secondary education," Post-Print hal-00712379, HAL.
    11. Barbara Zimmermann & Simon Seiler, 2019. "The Relationship between Educational Pathways and Occupational Outcomes at the Intersection of Gender and Social Origin," Social Inclusion, Cogitatio Press, vol. 7(3), pages 79-94.
    12. Nicola Barban, 2011. "Family trajectories and health: A life course perspective," Working Papers 039, "Carlo F. Dondena" Centre for Research on Social Dynamics (DONDENA), Università Commerciale Luigi Bocconi.
    13. Pietro Lovaglio & Mario Mezzanzanica, 2013. "Classification of longitudinal career paths," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(2), pages 989-1008, February.
    14. Laurent Lesnard & Thibaut Saint Pol, 2009. "Patterns of Workweek Schedules in France," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 93(1), pages 171-176, August.
    15. Helena Corrales Herrero & Beatriz Rodríguez Prado, 2011. "El empleo a tiempo parcial entre los jóvenes: Puente o trampa," Investigaciones de Economía de la Educación volume 6, in: Antonio Caparrós Ruiz (ed.), Investigaciones de Economía de la Educación 6, edition 1, volume 6, chapter 42, pages 677-692, Asociación de Economía de la Educación.
    16. Madero-Cabib, Ignacio & Fasang, Anette Eva, 2016. "Gendered work-family life courses and financial well-being in retirement," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 27, pages 43-60.
    17. Qianhan Lin, 2013. "Lost in Transformation? The Employment Trajectories of China’s Cultural Revolution Cohort," The ANNALS of the American Academy of Political and Social Science, , vol. 646(1), pages 172-193, March.
    18. Suzana Koelet & Helga de Valk & Ignace Glorieux & Ilse Laurijssen & Didier Willaert, 2015. "The timing of family commitments in the early work career," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 32(22), pages 657-690.
    19. Raffaella Piccarreta & Orna Lior, 2010. "Exploring sequences: a graphical tool based on multi‐dimensional scaling," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 173(1), pages 165-184, January.
    20. Thibault de Saint Pol, 2006. "Dinner in France : An Enduring Dietary Synchronism," Working Papers 2006-13, Center for Research in Economics and Statistics.
    21. Okka Zimmermann & Nicole Hameister, 2019. "Stable cohabitational unions increase quality of life: Retrospective analysis of partnership histories also reveals gender differences," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 40(24), pages 657-692.
    22. Silke Aisenbrey & Anette E. Fasang, 2010. "New Life for Old Ideas: The "Second Wave" of Sequence Analysis Bringing the "Course" Back Into the Life Course," Sociological Methods & Research, , vol. 38(3), pages 420-462, February.
    23. Ignace Glorieux & Ilse Laurijssen & Joeri Minnen & Theun Tienoven, 2010. "In Search of the Harried Leisure Class in Contemporary Society: Time-Use Surveys and Patterns of Leisure Time Consumption," Journal of Consumer Policy, Springer, vol. 33(2), pages 163-181, June.

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