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Stochastic Monotonicity in Intergenerational Mobility Tables

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Abstract

The aim of this paper is to test for stochastic monotonicity in intergenerational socio-economic mobility tables. In other words we question whether having a parent from a high socio-economic status is never worse than having one with a lower status. We ?rst test a set of 149 intergenerational mobility tables in 35 different countries and ?nd that monotonicity cannot be rejected in hardly any table. We then explain how a number of covariates such as education, cognitive and non-cognitive skills can be used to investigate whether monotonicity still holds after conditioning on these variables. Based on the NCDS cohort data from the UK, our results provide evidence that monotonicity holds even conditionally.

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  • Valentino Dardanoni & Mario Fiorini & Antonio Forcina, 2008. "Stochastic Monotonicity in Intergenerational Mobility Tables," Working Paper Series 156, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    • Handle: RePEc:uts:wpaper:156
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    File URL: http://www.finance.uts.edu.au/research/wpapers/wp156.pdf
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    1. Pirmin Fessler & Peter Mooslechner & Martin Schürz, 2012. "Intergenerational transmission of educational attainment in Austria," Empirica, Springer;Austrian Institute for Economic Research;Austrian Economic Association, vol. 39(1), pages 65-86, February.
    2. Gordon Anderson, 2018. "Measuring Aspects of Mobility, Polarization and Convergence in the Absence of Cardinality: Indices Based Upon Transitional Typology," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 139(3), pages 887-907, October.
    3. Frank T Denton & Byron G Spencer & Terry A Yip, 2019. "Age-Income Dynamics Over The Life Course: Cohort Transition Patterns In Relative Income Based On Canadian Tax Returns," Department of Economics Working Papers 2019-02, McMaster University.
    4. Marcin Wroński, 2024. "Intergenerational Educational Mobility in Poland in the Long Run: Education as a Positional Good," Eastern European Economics, Taylor & Francis Journals, vol. 62(3), pages 317-339, May.
    5. Ravi Kanbur & Joseph E. Stiglitz, 2016. "Dynastic inequality, mobility and equality of opportunity," The Journal of Economic Inequality, Springer;Society for the Study of Economic Inequality, vol. 14(4), pages 419-434, December.
    6. Yoram Amiel & Michele Bernasconi & Frank Cowell & Valentino Dardanoni, 2015. "Do we value mobility?," Social Choice and Welfare, Springer;The Society for Social Choice and Welfare, vol. 44(2), pages 231-255, February.
    7. Evans, R.J. & Forcina, A., 2013. "Two algorithms for fitting constrained marginal models," Computational Statistics & Data Analysis, Elsevier, vol. 66(C), pages 1-7.
    8. Delgado, Miguel A. & Escanciano, Juan Carlos, 2012. "Distribution-free tests of stochastic monotonicity," Journal of Econometrics, Elsevier, vol. 170(1), pages 68-75.
    9. Gordon Anderson & Maria Grazia Pittau & Roberto Zelli, 2020. "Measuring the progress of equality of educational opportunity in absence of cardinal comparability," METRON, Springer;Sapienza Università di Roma, vol. 78(2), pages 155-174, August.
    10. Berrittella, Maria & Dardanoni, Valentino, 2016. "Nonlinearity in intergenerational income transmission: A cross-country analysis," Economic Analysis and Policy, Elsevier, vol. 52(C), pages 1-10.
    11. R. Colombi & A. Forcina, 2016. "Testing order restrictions in contingency tables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 79(1), pages 73-90, January.
    12. Francesco Andreoli & Claudio Zoli, 2014. "Measuring Dissimilarity," Working Papers 23/2014, University of Verona, Department of Economics.
    13. Toru Kitagawa & Martin Nybom & Jan Stuhler, 2018. "Measurement error and rank correlations," CeMMAP working papers CWP28/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.

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