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Optimal Matching and Social Sciences


  • Laurent Lesnard



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.

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  • 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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    References listed on IDEAS

    1. Wil Dijkstra & Toon Taris, 1995. "Measuring the Agreement between Sequences," Sociological Methods & Research, , vol. 24(2), pages 214-231, November.
    2. Daniel S. Hamermesh, 2002. "Timing, togetherness and time windfalls," Journal of Population Economics, Springer;European Society for Population Economics, vol. 15(4), pages 601-623.
    3. Joel H. Levine, 2000. "But What Have You Done for Us Lately?," Sociological Methods & Research, , vol. 29(1), pages 34-40, August.
    4. Andrew Abbott, 2000. "Reply to Levine and Wu," Sociological Methods & Research, , vol. 29(1), pages 65-76, August.
    5. Glenn Milligan, 1980. "An examination of the effect of six types of error perturbation on fifteen clustering algorithms," Psychometrika, Springer;The Psychometric Society, vol. 45(3), pages 325-342, September.
    6. Gershuny, Jonathan, 2000. "Changing Times: Work and Leisure in Postindustrial Society," OUP Catalogue, Oxford University Press, number 9780198287872.
    7. Andrew Abbott, 1998. "The Causal Devolution," Sociological Methods & Research, , vol. 27(2), pages 148-181, November.
    8. Glenn Milligan, 1981. "A monte carlo study of thirty internal criterion measures for cluster analysis," Psychometrika, Springer;The Psychometric Society, vol. 46(2), pages 187-199, June.
    9. Laurent Lesnard, 2004. "Schedules as sequences: a new method to analyze the use of time based on collective rhythm with an application to the work arrangements of French dual-earner couples," electronic International Journal of Time Use Research, Research Institute on Professions (Forschungsinstitut Freie Berufe (FFB)) and The International Association for Time Use Research (IATUR), vol. 1(1), pages 60-84, August.
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    Cited by:

    1. 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.
    2. H. Corrales-Herrero & B. Rodríguez-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.
    3. Thomas King, 2013. "A framework for analysing social sequences," Quality & Quantity: International Journal of Methodology, Springer, vol. 47(1), pages 167-191, January.
    4. 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.
    5. Helena Corrales Herrero & Beatriz Rodríguez Prado, 2011. "Characterizing Spanish Labour Pathways of young people with vocational lower-secondary education," Post-Print hal-00712379, HAL.
    6. 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.
    7. 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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