Where is the Land of Hope and Glory? The geography of intergenerational mobility in England and Wales*

• Published date: 01 January 2023
• Author: Brian Bell,Jack Blundell,Stephen Machin
• Date: 01 January 2023
• DOI: http://doi.org/10.1111/sjoe.12511

Scand. J. of Economics 125(1), 73– 106, 2023

DOI: 10.1111/sjoe.12511

Where is the Land of Hope and Glory? The

geography of intergenerational mobility in

England and Wales∗

Brian Bell†

King’s Business School, London WC2R 2LS, UK

brian.bell@kcl.ac.uk

Jack Blundell‡

Stanford University, Stanford, CA 94305, USA

Stephen Machin§

London School of Economics and Political Science, London WC2A 2AE, UK

Abstract

We present a new analysis of intergenerational mobility across three cohorts in England

and Wales using linked decennial census microdata, focusing on occupation, homeownership,

and education. Four main results emerge. First, area-level differences in upward occupational

mobility are highly persistent over time. Second, measures of absolute and relative mobility

tend to be spatially positively correlated. Third, there is a robust relationship between upward

educational and upward occupational mobility. Last, there is a small negative relationship

between upward homeownership mobility and upward occupational mobility, revealing that

social mobility comparisons based on different outcomes can have different trends.

Keywords: Intergenerational mobility

JEL classif‌ication:I24; J62; R23; R31

∗We thank three anonymous referees for very helpful comments. This research was partly

funded by the ESRC at the Centre for Economic Performance (CEP) at the London School of

Economics and Political Science (LSE). J. Blundell is grateful for the generous support of the

Europe Center at Stanford University. Permission from the Off‌ice for National Statistics (ONS)

to use the Longitudinal Study is gratefully acknowledged, as is the help provided by staff of

the Centre for Longitudinal Study Informational and User Support (CeLSIUS). CeLSIUS is

supported by the ESRC Census of Population Programme (Award Ref: ES/R00823X/1). The

authors alone are responsible for the interpretation of the data. This work contains statistical data

from ONS that is Crown Copyright. The use of the ONS statistical data in this work does not

imply the endorsement of the ONS in relation to the interpretation or analysis of the statistical

data. This work uses research datasets that may not exactly reproduce ONS aggregates.

†Research Associate at the CEP.

‡Visiting Fellow at the CEP.

§Director of the CEP.

c

2022 The Authors. The Scandinavian Journal of Economics published by John Wiley & Sons Ltd on behalf of F¨

oreningen

f¨

or utgivande av the SJE.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution

and reproduction in any medium, provided the original work is properly cited.

74 The geography of intergenerational mobility in England and Wales

1. Introduction

There is copious evidence showing that life chances are affected by family

background.1Children whose parents went to university are themselves more

likely to do so, and they are more likely to be higher earners if their parents

were; and it is the same story for homeownership. What is far less clear, and

for which there is almost no evidence for England and Wales, is whether

the role of family background is attenuated or enhanced by the place where

children grow up. In other words, is the link between child and parental

university attendance the same in Liverpool as in Lambeth? If your father

was a low-skilled worker, does the probability that you become a high-skilled

professional depend on whether you grew up in Oldham or Oxford? Such

questions are both intrinsically interesting for academic research and at the

same time crucial for policy. England and Wales offer a particularly interesting

setting for looking at spatial mobility patterns and their evolution through

time. There has been immense academic and policy discussion surrounding

intergenerational mobility, with much debate over aggregate patterns. The

countries also exhibit signif‌icant regional imbalances. Akin to the US, there is

a dominant narrative of regions being “left behind”, as other areas excel. For

example, Inner West London is the richest area in Northern Europe, whereas

West Wales is the poorest (Eurostat, 2019).

Much of the existing evidence on intergenerational mobility in the UK

focuses on relatively small samples of individuals in longitudinal studies that

follow a group of people born in the same week in a particular year (Blanden

et al., 2004; Blanden and Machin, 2008). These cohort studies are infrequent,

suffer from signif‌icant attrition over time, and do not provide a large enough

sample to provide estimates at anything other than the national level. The

UK’s Social Mobility Commission (SMC) produces a social mobility index

for areas each year; however, the major components of this index focus on

wages, employment, schooling, occupation, and homeownership for all adults

living in an area, irrespective of background. As acknowledged in Social

Mobility Commission (2017), this is a limited proxy of spatial differences in

intergenerational mobility.

There are two recent survey-based papers investigating regional differences

in intergenerational mobility in the UK. Friedman and Macmillan (2017)

study Understanding Society and the Labour Force Survey to estimate rates

of mobility across 19 areas of the UK. Exploiting the large sample size of

these surveys, they f‌ind substantial differences in mobility across regions.

While a valuable contribution, an important data shortcoming of this work

1For reviews of the economic literature on intergenerational mobility, see Black and

Devereux (2011). The vast sociology literature on the topic is discussed in Bukodi and

Goldthorpe (2018) and a more populist discussion is given in Elliot Major and Machin (2018).

c

2022 The Authors. The Scandinavian Journal of Economics published by John Wiley & Sons Ltd on behalf of F¨

oreningen

f¨

or utgivande av the SJE.

B. Bell, J. Blundell, and S. Machin 75

is that it has to look at individuals’ location as adults, rather than where

they grew up. This makes it less useful for understanding the geographical

origins of differences in rates of mobility. It also uses retrospective reports

of parental status, so it will potentially suffer from recall error. Similarly,

Rohenkohl (2019) uses longitudinal household survey data to estimate regional

intergenerational mobility for 12 regions of the UK. The full length of the panel

is exploited so that recall error is not an issue, and the author is able to explore

pre- and post-transfer household income rather than just individual labour

market earnings. The paper demonstrates a strong North– South divide in

mobility rates. However, the sample sizes available for regional estimates are

limited, forcing a focus on highly aggregated regions. Neither of these studies

is able to investigate changes over time.

In this paper, we signif‌icantly improve on both of these dimensions

by using linked decennial census data contained in the Longitudinal

Study of England and Wales (LS) to study much more disaggregated

geographies and trends of intergenerational mobility.2The LS data are a

1 percent sample from the decennial census and life events data. They

can be structured so as to follow three cohorts of individuals born in

1954– 1963, 1964– 1973, and 1974– 1983 over time. Parental occupation,

education, and homeownership are observed when the individual cohort

members were aged 8– 17 and living with their parents. By f‌irst observing

the cohort members when they are under 18 and living at home allows

us to directly link parent and child. The same outcomes can be looked

at for the cohort members when aged 28– 37 in the 1991, 2001, and

2011 censuses.

A key feature of this paper is that these data offer scope to focus on multiple

measures or dimensions of mobility; see the recent review of Deutscher and

Mazumder (2021) for an extensive discussion of a large number of metrics

of absolute and relative mobility. The LS data make this possible, and

we argue that this is a useful approach for two reasons. First, we might

consider that socio-economic status cannot be reduced to a single measure

such as income. Rather, there exists some latent socio-economic status that

is noisily measured by multiple observables, such as income, wealth, health,

or education. Alternatively, one might argue that there does not exist some

latent status variable, but that there are simply multiple dimensions of welfare,

which cannot be combined without making strong assumptions. We consider

both these justif‌ications to be valid, and present separate results for each

dimension of mobility. One could combine them into an index, but we do not

2As the census is administered separately for Scotland and Northern Ireland, these areas are

excluded from this dataset. As of 2015, these omitted countries constitute approximately 11

percent of the UK population. For brevity, we refer to combined estimates for England and

Wales as “national” results.

c

2022 The Authors. The Scandinavian Journal of Economics published by John Wiley & Sons Ltd on behalf of F¨

oreningen

f¨

or utgivande av the SJE.