New Directions in Measuring Intergenerational Mobility

Introduction

Bibliographic Data

ID9706839
AuthorsMaia Güell (0000-0003-4701-9887, University of Edinburgh, CEPR, FEDEA and IZA), José V Rodríguez Mora (0000-0002-5776-308X, University of Edinburgh, Alan Turing Institute and CEPR), José V Rodrı́guez Mora (Turing Institute), Gary Solon (University of Arizona and NBER, corresponding author)
Year2018
Volume128
Issue612
PagesF335-F339
Publication date2018-07-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe Economic Journal (JOURNAL)
Journal identifiersISSN: 0013-0133 • E-ISSN: 1468-0297
PublisherOxford University Press (OUP) (PUBLISHER)
DOI10.1111/ecoj.12607
OpenAlexW2789684694
LanguageEN
Citations received9
References cited17

This Feature contains seven new articles that exemplify several of the cutting edges in research on intergenerational transmission of socio‐economic status. Section 1 of this introduction briefly summarises the articles and highlights some cross‐cutting themes. In Section 2, we offer a few suggestions for future research. One of the growth areas in mobility research is the study of 'multi‐generational mobility,' that is, status transmission across three or more generations. The article by Solon (2018) summarises both the theoretical and empirical literatures. One of the greatest challenges in advancing the empirical literature is simply to assemble good data that span at least three generations. The article by Long and Ferrie (2018) develops and analyses three generations of occupational data from Great Britain and the US over the 1850–1910 period. An example of the basis for the title's message that 'grandfathers matter(ed)' is that, when the authors apply least squares to the regression of the log of average earnings in the occupation of British sons on the same variables for both their fathers and grandfathers, the father coefficient estimate is 0.285 (with standard error 0.018) and the grandfather coefficient estimate is 0.051 (0.016). (We will say a bit more about such results in Section 2.) The article by Adermon et al. (2018) reports similar results for intergenerational wealth transmission across three generations from Malmö, Sweden. Continuing on the subject of wealth inequality, the article by Boserup et al. (2018) studies wealth inequality among children in Denmark. The authors find that wealth at age 18 is a significant predictor of adult wealth. They suggest two main reasons: inter vivos transfers at young ages foreshadow additional transfers later in life, and children may inherit saving/investment propensities from their parents

Demographic economics · Earnings · Econometrics · Economics · Empirical research · Inequality · Section (typography · Social mobility · Social science · Sociology · Statistics · Accounting · Computer Science · Health disparities and outcomes · Intergenerational and Educational Inequality Studies · Mathematics · Youth Education and Societal Dynamics

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