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Sorting Multidimensional Types: Theory and Application

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  • Ilse Lindenlaub

    (European University Institute)

Abstract

This paper studies multidimensional matching between workers and jobs. Workers differ in manual and cognitive skills and sort into jobs that demand different combinations of these two skills. To study this multidimensional sorting, I develop a theoretical framework that generalizes the unidimensional notion of assortative matching. I derive the equilibrium in closed form and use this explicit solution to study biased technological change. The key finding is that an increase in worker-job complementarities in cognitive relative to manual inputs leads to more pronounced sorting and wage inequality across cognitive relative to manual skills. This can trigger wage polarization and boost aggregate wage dispersion. I then estimate the model for the US and identify sizeable technology shifts: during the 1990s, worker-job complementarities in cognitive inputs increased by 15% whereas complementarities in manual inputs decreased by 41%. In addition to this bias in complementarities, there has also been a strong cognitive skill-bias in production. Counterfactual exercises suggest that these technology shifts can account for observed changes in worker-job sorting, wage polarization and a significant part of the increase in US wage dispersion.

Suggested Citation

  • Ilse Lindenlaub, 2014. "Sorting Multidimensional Types: Theory and Application," 2014 Meeting Papers 979, Society for Economic Dynamics.
    • Handle: RePEc:red:sed014:979
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    Cited by:

    1. Benjamin Lochner & Bastian Schulz, 2016. "Labor Market Sorting in Germany," CESifo Working Paper Series 6066, CESifo.
    2. David J. Deming, 2017. "The Growing Importance of Social Skills in the Labor Market," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 132(4), pages 1593-1640.
    3. Youngmin Park & Youngki Shin & Lance Lochner, 2017. "Earnings Dynamics and Returns to Skills," 2017 Meeting Papers 166, Society for Economic Dynamics.
    4. Douglas W. Allen & Shih En Lu, 2017. "Matching, marriage, and children: differences across sexual orientations," Review of Economics of the Household, Springer, vol. 15(2), pages 527-547, June.
    5. Pierre-Andr'e Chiappori & Robert McCann & Brendan Pass, 2016. "Multidimensional matching," Papers 1604.05771, arXiv.org.
    6. Cristian Bartolucci & Francesco Devicienti & Ignacio Monzón, 2018. "Identifying Sorting in Practice," American Economic Journal: Applied Economics, American Economic Association, vol. 10(4), pages 408-438, October.
    7. Albert Banal-Estañol & Inés Macho-Stadler & David Pérez-Castrillo, 2018. "Endogenous Matching in University-Industry Collaboration: Theory and Empirical Evidence from the United Kingdom," Management Science, INFORMS, vol. 64(4), pages 1591-1608, April.
    8. Ilse Lindenlaub & Fabien Postel-Vinay, 2023. "Multidimensional Sorting under Random Search," Journal of Political Economy, University of Chicago Press, vol. 131(12), pages 3497-3539.
    9. Andreas Gulyas, 2018. "Identifying Labor Market Sorting with Firm Dynamics," 2018 Meeting Papers 856, Society for Economic Dynamics.

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