Transcript “‘ Everything in Common . . . But the Language’? Mobility in Britain and the U.S.

“‘ Everything in Common . . . But the Language’?
Mobility in Britain and the U.S. Since 1850”
Jason Long
Joseph P. Ferrie
Department of Economics
Colby College
Department of Economics
and
Institute for Policy Research
Northwestern University
and
NBER
“Indeed, in many respects, she was quite English,
and was an excellent example of the fact that
we have really everything in common
with America nowadays, except, of course, language.”
Oscar Wilde, The Canterville Ghost [1891]
A century later, a modern Wilde could say much the same:
Britain and the U.S. have much [if not “everything”] in common:
legal and political heritage
economic system
culture
technology
and [contra Wilde] language
But two things they do not share are
1. their belief in the prospects for economic and social mobility
(either within or across generations)
and
2. their attitudes toward an active state that taxes from the
successful and transfers to the unsuccessful (though this
difference has narrowed since the 1980s)
The U.S. also differs from a number of otherwise similar countries
(France, Germany, Canada) in these respects.
What are the origins of these differences?
II. What’s different now?
• Three things have made linkage easier in just the last several
years:
– Better indexes to and availability of US/British censuses
from 1850-1901
– Complete transcription of 1880/81 censuses
– Public use samples from IPUMS for US, 1850-70 and 190020; for Britain for 1851
Studying Mobility in the 19th Century
Linked Census Data
2% Sample of 1851 Census
168,130 men in England and Wales
+
Complete-Count 1881 Census
All 12,640,000 men in the census
28,474 men in 1851 and 1881
• 16,829 sons in 1851
• 9,477 HH heads in 1851
20,269 sons in 1881
+
Complete-Count 1901 Census
8,677 sons in 1901
Match Criteria
1. First, last name phonetic match (e.g. “John”/“Jon”;
“Aitken”/“Aitkin”). Middle initial match.
2. | Reported Age1881 – (Reported Age1851 + 30) |  5
3. Birth county and parish match.
◦
Approx 16,000 parishes in England and Wales
◦
Size: Median = 405, Mean = 1,842

High-resolution information
4. No duplicate matches.
5. No missing information.
Example: John Jowitt
1851: Fairburn parish, Yorkshire, England
County
York
York
York
York
York
York
Parish
Fairburn
Fairburn
Fairburn
Fairburn
Fairburn
Fairburn
First
Name
Robert
Christiana
John
Mary
Jane
Joseph
Last
Name
Jowitt
Jowitt
Jowitt
Jowitt
Jowitt
Morby
Marital
Relation Status
Head
M
Wife
M
Son
U
Daughter U
Daughter U
Lodger U
Occupation
Farmer Lab
Scholar
Farm Lab
Birth
Sex Age County
M 31 York
F 38 York
M
7 York
F
3 York
F
1 York
M 30 York
Birth
Parish
Brotherton
Brotherton
Brotherton
Brotherton
Ledsham
Brayton
1881: Hornby parish, Lancashire, England
County Parish
First
Name
Last
Marital
Name Relation Status Occupation
Lanc
Lanc
Lanc
John
Mary
Jane
Jowett Head
Jowett Wife
Lea
Visitor
Hornby
Hornby
Hornby
M
M
U
Birth
Birth
Sex Age County Parish
Clerk of Works M
F
No Occupation F
37
34
36
York
Brotherton
Cheshire Holme Chapel
Cheshire Coupleton
Another Example: Alfred H King and Occupational Mobility
1851: Essenden parish, Hertfordshire, England
County
Hertford
Hertford
Hertford
Hertford
Hertford
Parish
Essenden
Essenden
Essenden
Essenden
Essenden
First
Name
Henry
Mary A
Alfred H
Amelia
Gertrude
Last
Name
King
King
King
King
King
Marital
Relation Status Occupation Sex
Head
M
Rat Destroyer M
Wife
M
F
Son
U
Scholar
M
D
U
F
D
U
F
Birth
Age County
48 N K
35 Middlesex
7 Hertford
0 Hertford
0 Hertford
Birth
Parish
NK
Coopers Lane
Essenden
Essenden
Essenden
1881: Essenden parish, Hertfordshire, England
First
County Parish
Name
Hertford Essenden Alfred
Henry
Hertford Essenden Eliza
Last
Marital
Birth
Name Relation Status Occupation Sex Age County
King Head
M
Evangelist/ M 37 Hertford
Missionary
King Wife
F
F 21 Cheshire
Birth
Parish
Essenden
Denton
Long-term goals of the project:
Comparisons of intergenerational mobility between
historical (c. 1880-1900) and modern (c. 1950-70)
populations are possible for 5 countries
U.S.
Britain
France
Norway
Canada
To comprehensively compare mobility between
two tables, we need
• A single metric to summarize mobility
In measuring intergenerational income mobility, this is
straightforward: a regression is estimated relating son’s
income to father’s income:
log(Yison)=α+ δXi+β log(Yifather)+εi
• Test for statistical significance
• Control for different occupational structures
– Do this by adjusting marginal frequencies in
two tables being compared to a common
margin
Father
Son
White Collar
Farmer
Skilled/
Semi
Unskilled
White Collar
X
X
X
X
Farmer
X
X
X
X
Skilled/Semi
X
X
X
X
Unskilled
X
X
X
X
[(Farm-Farm)/(Farm-Unsk)]/[(Unsk-Farm)/(Unsk-Unsk)]
=11.6%
[(WhCol-WhCol)/(WhCol-Unsk)]/[(Unsk-Whcol)/(Unsk-Unsk)]= 9.3%
In 1870, 1890 England lags behind US
Catches up in the 20th century
Comparing Mobility in Two Economies
Simple two-generation human capital model generates clear predictions.
Solon (1999, 2004), Becker and Tomes (1979, 1986):
(1) log yit    phit
(2) hit   log  Ii ,t 1  Gi ,t 1   eit
(3) eit    ei ,t 1  it
(4) Ui  (1   )log Ci ,t 1   log yit
(5) (1   ) yi ,t 1  Ci ,t 1  Ii ,t 1
with the standard earnings
elasticity regression function:
yit   *   yi ,t 1   it
the model above implies
(1   ) p  

1  (1   ) p
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