Many Fourth District cities have experienced relatively weak population growth over the past half century. One possible reason some cities have recently grown more is because they have better educated workforces. Recent research suggests that the educational attainment of residents is critical to population growth, particularly for cities in the Northeast and Midwest.Cities and towns ; Population ; Federal Reserve District, 4th

Tim Dunne

English

Research Papers in Economics

The Growth of Cities in the Fourth District
by Tim Dunne
August 1, 2007
ISSN 0428-1276
When the boundaries of the Fourth 
District were drawn in 1914, three dis-
trict cities—Cleveland, Pittsburgh, and 
Cincinnati—ranked among the top 
20 most populous cities in the United 
States. Today, none of these cities ranks 
in the top 35, and the only district city 
in the top 20 is Columbus. Including the 
surrounding suburban areas along with 
these cities (the so-called metropoli-
tan statistical area, or MSA), doesn’t 
change the picture much: Population 
growth in these areas has also lagged, 
with Pittsburgh, Cleveland, and Cincin-
nati all dropping out of the top 20 larg-
est MSAs over the last half century. 
A number of factors are behind the 
decline. For starters, cities in the Fourth 
District have been affected by the same 
broad trends that have inﬂ  uenced the 
population growth of other large, older 
cities across the United States. Recent 
research also suggests that popula-
tion growth is linked to the educational 
attainment of residents, and this link is 
especially strong for cities located in the 
Northeast and Midwest.
 Trends in Population Growth
The decline in the population of 
many Fourth District cities is part of a 
broader national trend that represents a 
shift in the population from the North-
east and Midwest to the West and the 
South. Figure 1 illustrates this point. 
The ﬁ  gure plots city population growth 
from 1950 to 2005 for the 100 largest 
cities in 1950 against the average Janu-
ary temperature of the city. One can 
think of the January temperature as a 
proxy for the location of the city within 
the United States. The colder cities are 
in the Northeast and upper Midwest. 
The pattern is unmistakable—colder 
cities grew, on average, much more 
slowly than their warmer counterparts 
over the period. Even cities such as 
Minneapolis and Boston experienced 
population declines of almost 30 per-
cent over this period. This pattern is 
true for colder metropolitan areas and 
colder suburban areas, as well. 
The different patterns of population 
growth for warm and cold regions reﬂ  ect 
a long-term trend in the movement of 
the population away from the original 
core population centers in the Northeast 
to the West (see Edward Glaeser and 
Jesse Shapiro, 2003, for a description of 
the basic developments that have inﬂ  u-
enced population growth in U.S. cities 
across regions). When the country was 
expanding into the Midwest, this aided 
Fourth District cities. But as the popu-
lation moved further west, growth in 
Midwest cities slowed. More recently, 
southern cities have experienced higher 
growth, and it is argued that techno-
logical changes, such as the invention 
of air-conditioning and the eradication 
of malaria, allowed for the successful 
expansion of these locales. 
An alternative view is that the eco-
nomic advantages that fostered the 
growth of the older Northern cities 
have waned. In particular, low trans-
portation costs and access to raw mate-
rials offered by proximity to the Great 
Lakes or navigable rivers such as the 
Ohio became less important as truck-
ing became the dominant shipping 
mode. New transportation technologies 
allowed manufacturing and distribu-
tion ﬁ  rms to consider sites away from 
traditional water and rail transportation 
hubs as feasible locations. This is not 
to say that transportation costs have 
become unimportant in determining 
ﬁ  rm location. There are still beneﬁ  ts to 
being near customers, suppliers, and 
other ﬁ  rms in an industry. It is just that 
the particular transportation advan-
tages offered in the Great Lakes region 
have become less important as trans-
portation technology and networks 
have evolved and the economy has 
shifted away from manufactured goods 
that are natural-resource intensive. The 
decline in manufacturing-intensive 
cities is shown in ﬁ  gure 2. Cities that 
had a high share of manufacturing 
employment in 1970 have experienced 
low subsequent population growth. 
Except for Columbus, the other large 
Fourth District cities are found toward 
the lower middle and right-hand cor-
ner of the chart, with Cleveland, Day-
ton, and Youngstown having very high 
manufacturing shares in 1970.
Clearly, all these stories play some 
part in explaining the recent popula-
tion growth histories of Fourth District 
cities, but there is more to the story 
than location or industrial specializa-
tion. Another broad trend inﬂ  uencing 
the growth of older cities is a general 
fall in population densities. In 1950, 
the population density of 13 out of the 
top 20 most populous cities exceeded 
10,000 persons per square mile; this 
list included Cleveland and Pittsburgh. 
Only 5 cities in the top 20 today are 
this dense, and fast growing, large cit-
Many Fourth District cities have expe-
rienced relatively weak population 
growth over the past half century. One 
possible reason some cities have recently 
grown more is because they have better 
educated workforces. Recent research 
suggests that the educational attain-
ment of residents is critical to popula-
tion growth, particularly for cities in the 
Northwest and Midwest. 
Federal Reserve Bank of Clevelandies such as San Antonio and Phoenix 
have densities of about 3,000 persons 
per square mile. The drop in density 
is due to a number of factors. House-
hold size has fallen: In 1950 households 
used to average 3.4 persons; now they 
average 2.6. Access to cars has allowed 
workers and ﬁ  rms to move outside the 
central city. As transportation networks 
evolved, especially ring roads and high-
way systems, the cost of moving people 
within and around most cities fell. 
Moreover, cities experiencing popu-
lation inﬂ  ows in the South and West 
often expanded their borders, lessen-
ing density. This was not the case for 
many of the large Fourth District cities, 
where city boundaries have remained 
relatively ﬁ  xed over the last half cen-
tury. One exception is Columbus, a city 
that has grown from 39.4 square miles 
in 1950 to 210.3 square miles in 2000. 
Although cities such as Cleveland and 
Pittsburgh had relatively ﬁ  xed boundar-
ies, this did not result in above-average 
population growth in the surrounding 
suburbs over the period. Cleveland’s 
suburbs grew weakly compared to other 
major cities, and Pittsburgh’s suburbs 
actually contracted from 1970 to 2000. 
In fact, cities that had relatively high 
population growth rates from 1970 to 
2000 tended to have relatively high sub-
urban population growth rates, as well, 
and cities with low growth rates tended 
to have low suburban growth rates.
 Education and City Growth
Many analysts identify the education 
level of the populace as a key factor 
in city and metropolitan growth. Fig-
ure 3 depicts the relationship between 
city population growth and the share 
of a city’s adult population that had 
four or more years of college educa-
tion in 1970. Two striking patterns 
emerge. Population growth is gen-
erally higher in cities with a greater 
initial share of college-educated resi-
dents, and the college shares of some 
Fourth District cities are extremely 
low. This is especially true for Cleve-
land and Youngstown. College shares 
in these two cities were less than 50 
percent of the average in 1970. In con-
trast, Columbus, with its more highly 
educated workforce, experienced solid 
population growth over the last 30 
years. The patterns observed in ﬁ  gures 
2 and 3 are related—cities that had high 
manufacturing shares in 1970 tended to 
have low college shares, as well.
FIGURE 1  CITY POPULATION GROWTH AND TEMPERATURE,  
 1950–2005
FIGURE 2  CITY GROWTH AND MANUFACTURING, 1970–2005
FIGURE 3  CITY POPULATION GROWTH AND EDUCATION, 
 1970–2005
Phoenix
L.A.
San Diego
San Francisco
San Jose
D.C
Chicago
Minneapolis
St. Louis
N.Y.
Cincinnati
Cleveland
Columbus
Dayton
Toledo
Pittsburgh
Austin
Houston San Antonio
Growth rate
January temperature in city
3
2
1
0
–1
02 0 4 0 7 0 80
Growth rate
Manufacturing’s share of employment in 1970
1.0
0.5
0
–0.5
0 0.1 0.2 0.3 0.4
Phoenix
Tuscon
Fresno
San Diego
San Franciso
San Jose
D.C.
Chicago
Minneapolis
St. Louis
N.Y.
Cincinnati
Cleveland
Columbus
Dayton
Toledo
Youngstown
Pittsburgh
Austin
Houston
San Antonio
Madison
Phoenix
Tuscon
Fresno
L.A.
San Diego
San Francisco
San Jose
D.C.
Chicago Minneapolis
St. Louis
N.Y.
Cincinnati
Cleveland
Columbus
Dayton
Toledo
Youngstown Pittsburgh
Austin
Houston
San Antonio
Madison
Growth rate
Share of adult population with a college degree in 1970
1.0
0.5
0
–0.5
0.05 0.1 0.15 0.2 0.25 0.3However, not all Fourth District cit-
ies ﬁ  t the standard story. In 1970, Pitts-
burgh’s share of college graduates was 
roughly twice that of Cleveland’s, and 
over the last 30 years, it has risen mark-
edly. In 2005, Pittsburgh had the highest 
share of college graduates of any large 
Fourth District city with the exception 
of Lexington, Kentucky. Nonetheless, 
Pittsburgh has had roughly the same 
relative decline in population as Cleve-
land over the past 50 years. One pos-
sible reason for the difference in growth 
patterns between the two cities may 
have to do with the geographical dis-
tribution of educated people within the 
respective metropolitan areas. In the 
Pittsburgh area, the city has a slightly 
greater college share than the suburbs. 
In the Cleveland metropolitan area, the 
opposite is true—the suburbs have a 
much larger college share than the city. 
In fact, the share of college graduates 
in Cleveland’s suburbs exceeded the 
city’s share by 2.4 times in 2000—one 
of the largest differences in the nation, 
and this gap has existed for decades. 
These differences in suburb-city shares 
balance out at the metropolitan level, 
and the Pittsburgh and Cleveland met-
ropolitan areas each had college shares 
of about 27 percent in 2005, which is 
slightly under the national average for 
large metropolitan areas. 
While the overall share of college grad-
uates rises when one incorporates the 
suburbs into the calculations, the same 
general story regarding education and 
growth occurs when the unit of analy-
sis is the metropolitan area. Populations 
grew faster, on average, in more edu-
cated metropolitan areas (see ﬁ  gure 4). 
There are a number of theories as to 
why a city with a more skilled popu-
lace may grow faster than a less skilled 
locale. Robert Lucas argued in 1988 
that cities with high human capital 
generate signiﬁ  cant knowledge spill-
overs. In this theory, cities facilitate 
the interaction of skilled workers, and 
such interactions foster new ideas and 
new innovations, which lead to higher 
growth. The physical proximity of 
skilled individuals to other skilled indi-
viduals is central to this story. Recent 
empirical work by Enrico Moretti sup-
ports this view. He shows that ﬁ  rms 
located in cities with skilled workforces 
have higher productivity, even after 
controlling for the skill level of their 
own workforces, suggesting such spill-
overs exist. However, the overall impor-
tance of such human capital spillovers 
is still an open question. 
Edward Glaeser and Albert Saiz also 
consider the possibility that cities with 
more skilled inhabitants are more ﬂ  ex-
ible and, in their terms, can “reinvent” 
themselves in response to negative 
shocks. They argue that older northern-
city growth is more closely linked to 
education because of a greater need 
to reinvent in these cities. In particu-
lar, these cities and metropolitan areas 
experienced particularly severe shocks 
to their manufacturing sectors begin-
ning in the 1970s. Cities with relatively 
skilled workforces adapted better than 
those with unskilled workforces. This 
point is illustrated in ﬁ  gure 5, which 
plots population growth and educa-
tion separately for warm and cold cities 
(here a cold city is one where the aver-
age January temperature is below freez-
ing). In the case of cold cities, the share 
of college-educated adults is positively 
correlated with growth, and initial edu-
cation explains a signiﬁ  cant share of the 
variation in cold-city growth rates. For 
warm cities, the correlation between 
education and growth is much weaker, 
and education explains little of the dif-
ference in growth rates in the warm-city 
sample. Glaeser and Saiz report that 
the same patterns apply for metropoli-
FIGURE 4  METROPOLITAN POPULATION GROWTH, 1970–2005
FIGURE 5   CITY GROWTH, 1970–2005
Youngstown
Dayton
Madison
Toledo
Cincinnati
Pittsburgh
St. 
Louis
Minneapolis
Cleveland
Columbus
Chicago
N.Y.
Atlanta
Fresno
Tuscon
D.C.
Memphis
Austin
San Francisco
San Jose
San Antonio
San Diego
Phoenix
Houston
L.A.
Growth rate
0 0.1 0.2 0.3
1.0
0.5
–0.5
0
Share of adult population with a college degree in 1970
0 0.1 0.2 0.3
Cold city Warm city
Sources (ﬁ  gures 1–5): U.S. Census Bureau; and State of the Cities (HUD).
Note (ﬁ  gures 1–5): All population growth rates are calculated as log differences.
NY
CHI
BOS
DC
SF
PGH
STL
DAL
CLV
MIN
ATL
SEA
CIN
COL
SJ
SAT
DAY AK
YST
TOL
JVL
AUS
 
Growth rate
Share of adult population with a college degree in 1970
0.05 0.1 0.15 0.2 0.25
1.5
1.0
0
–0.5
0.5Tim Dunne is an economic advisor at the 
Federal Reserve Bank of Cleveland.
The views expressed here are those of the 
author and not necessarily those of the 
Federal Reserve Bank of Cleveland or 
the Board of Governors of the Federal 
Reserve System or its staff. 
Economic Commentary is published by 
the Research Department of the Federal 
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 Recommended Reading
Edward Glaeser and Jesse Shapiro. 
2003. “City Growth: Which Places 
Grew and Why?” in B. Katz and R. 
Lang, eds. Redeﬁ  ning Urban and Sub-
urban America, vol 1. Washington, 
D.C.: Brookings Institution.
Edward Glaeser and Albert Saiz. 2004. 
“The Rise of the Skilled City,” Brook-
ings-Wharton Papers on Urban Affairs, 
5:47–94.
Enrico Moretti. 2004. “Workers’ Edu-
cation, Spillovers, and Productivity: 
Evidence from Plant-level Produc-
tion Functions,” American Economic 
Review, 94(3): 656–90.
Robert Lucas. 1988. “On the Mechan-
ics of Economic Development,” Jour-
nal of Monetary Economics, 22:3-42.
Curtis Simon and Clark Nardinelli. 2002. 
“Human Capital and the Rise of Ameri-
can Cities, 1900–1990.” Regional Sci-
ence and Urban Economics, 32:59–96.
tan areas, as well. The implication for 
Fourth District cities is clear. Fourth 
District cities had few of the growth 
advantages offered by the warmer 
locales but, at the same time, many were 
poorly positioned in terms of workforce 
skills to take advantage of the techno-
logical shifts that occurred in the last 
two decades of the twentieth century. 
Although many analysts believe that a 
highly skilled workforce is an impor-
tant factor in the city-growth equation, 
it may also be the case that cities and 
metropolitan areas on a high growth tra-
jectory or poised to grow simply attract 
more educated workers. That is, the 
causality could be reversed. It is rea-
sonable to think that the relationship 
between city growth and education runs 
both ways. Educated workforces lead 
to higher growth, but high-growth cities 
also attract educated workers. 
Research that attempts to sort out these 
confounding effects ﬁ  nds support for the 
idea that an educated workforce leads 
to higher city growth. It is probably safe 
to conclude that cities and metropolitan 
areas looking to foster long-term growth 
should consider policies that increase 
educational attainment and attract and 
retain educated workers as important 
tools for local economic development.

The growth of cities in the Fourth District

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