Bones, Bombs, and Break Points: The Geography of Economic Activity
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Bones, Bombs, and Break Points:
The Geography of Economic Activity
By DONALD R. DAVIS AND DAVID E. WEINSTEIN*
We consider the distribution of economic activity within a country in light of three
leading theories—increasing returns, random growth, and locational fundamentals.
To do so, we examine the distribution of regional population in Japan from the
Stone Age to the modern era. We also consider the Allied bombing of Japanese cities
in WWII as a shock to relative city sizes. Our results support a hybrid theory in
which locational fundamentals establish the spatial pattern of relative regional
densities, but increasing returns help to determine the degree of spatial differenti-
ation. Long-run city size is robust even to large temporary shocks. (JEL D5, J1, N9, R1)
In the last decade, the field of economic ge- The increasing returns theories posit that ad-
ography has enjoyed a renaissance.1 The central vantages of size may arise from knowledge
question in this literature is how to explain the spillovers, labor-market pooling, or the advan-
distribution of economic activity across space— tages of proximity for both suppliers and de-
across countries of the world, across regions manders in a world of costly trade. In this
within a country, and across cities. Three prin- approach, a distribution of city sizes may arise
cipal theoretical approaches have emerged, from technological characteristics of individual
which may be termed increasing returns, ran- industries (J. V. Henderson, 1974) or from the
dom growth, and locational fundamentals. We tacit competition among locations for mobile
develop stylized facts and empirical tests that factors of production (Krugman, 1991a). Impor-
help to evaluate the theories. tant themes within this work include the possi-
bilities of multiple equilibria, path dependence,
and spatial catastrophes. An outstanding expo-
* Department of Economics, Columbia University, 420
sition of much of the new work is in Masahisa
West 118th Street, New York, NY 10027, and National Fujita et al. (1999).
Bureau of Economic Research (e-mail: DRD28@columbia. The random growth theory (H. Simon, 1955)
edu; and DEW35@columbia.edu). The authors want to es- holds that a distribution of cities of quite differ-
pecially thank Mary Berry, Wayne Farris, and Hiroshi Kito ent sizes emerges from very simple stochastic
who helped us enormously in obtaining and understanding
the historical demographic data. While their help was in- processes. One large advantage of this approach
strumental, any remaining errors are the responsibility of the is that it is able to explain a key empirical
authors. Kazuko Shirono gave us tremendous help with the regularity known as Zipf’s Law regarding the
archival and data construction aspects of the paper. Joshua distribution of city sizes that, to date, the in-
Greenfield also helped input the bombing data. Weinstein
wants to also thank the Japan Society for the Promotion of creasing returns theories cannot explain. A re-
Science for funding part of this research, and Seiichi cent and very interesting development of this
Katayama for providing him with research space and access approach is Xavier Gabaix (1999).
to the Kobe University library. This research was supported What we term the locational fundamentals
by National Science Foundation Grant No. SBR-9810180.
1 theory may be thought of as a variant of the
Paul Krugman has argued that the study of the spatial
location of economic activity should assume a stature in the random growth theory. Instead of city growth
profession equal to one of the flagship fields such as inter- itself being random, it is fundamental economic
national trade (Krugman, 1995). A new Journal of Eco- characteristics of locations that are random. A
nomic Geography has been founded. While demurring from fully specified locational fundamentals model
some of Krugman’s strongest claims, J. Peter Neary, writing
a review article in the Journal of Economic Literature, would incorporate differences in Ricardian
declares “New economic geography has come of age” technological coefficients and Heckscher-Ohlin
(Neary, 2001, p. 536). endowments, with the caveat that the primitive
12691270 THE AMERICAN ECONOMIC REVIEW DECEMBER 2002
endowments of interest would elaborate on the other than increasing returns help to explain the
concept of “land” to include a detailed descrip- variation in the density of economic activity.
tion of location-specific characteristics. A paper Second, there has been a notable rise in concen-
in this spirit is Jordan Rappaport and Jeffrey D. tration in the last century as Japan industrialized
Sachs (2001). Following Krugman (1996), if we and became ever more integrated into the world
posit that these characteristics are distributed economy. This suggests that the increasing re-
according to the same process as in Gabaix turns theories may help to account for the rise in
(1999), then the locational fundamentals theory dispersion.
also can account for Zipf’s Law. However, in The same data set can be employed to address
contrast to the random growth theory, the loca- a second key question. Over tens, hundreds, or
tional fundamentals story predicts that the size thousands of years, how much persistence
of specific locations should be robust even to should we expect in the identity of the most
large temporary shocks.2 densely settled regions? The increasing returns
In this paper, we will examine these three theories do not answer with a single voice.
theories empirically. A few key questions Insofar as the size distribution is tied to techno-
emerge. How important are scale economies in logical characteristics of particular industries,
explaining the degree of spatial concentration of then as we move from hunter-gatherer societies,
economic activity?3 The premise that we work to agriculture-based societies, through feudal-
from is that the forces of increasing returns ism, into and out of autarky, and finally to a
must be vastly stronger in a modern, knowl- modern industrial economy, one might guess
edge-based economy than in more primitive, that there would be radical shifts over time in
agricultural or pre-agricultural, economies. To which are the densely populated regions. On the
investigate this, we employ a unique data set on other hand, an important strand within the in-
Japanese regional population over the past creasing returns theories has stressed the role of
8,000 years. The answer that we provide has path dependence (Krugman, 1991b; Paul A.
two parts. First, for the 8,000 years in our data David, 2000). An early start in one location
set, there has always been a great deal of vari- provides that site with advantages at each suc-
ation in measures of regional population den- ceeding stage of locational competition. The
sity. This alone suggests that important factors random growth theory is likewise consistent
with correlation across long stretches of time in
2
the spatial density of particular locations so long
Physical geography has played a quite limited role in
much of the theoretical literature of the new economic as the variance of growth rates is not too large.
geography. There are exceptions, such as the very nice A clear prediction emerges from the locational
paper of Fujita and Tomova Mori (1996) on the role of fundamentals theory, which would hold that
ports. More typical, though, is a tendency to focus almost many of the crucial characteristics for locations
exclusively on factors with no real geographical counter-
part, as in the survey by Fujita and Jacques Francois Thisse
have changed little over time even if the eco-
(1996, p. 339): “The main reasons for the formation of nomic meaning may have evolved. For exam-
economic clusters involving firms and/or households are ple, there are advantages of being near a river,
analyzed: (i) externalities under perfect competition; (ii) on the coast, on a plain instead of a mountain or
increasing returns under monopolistic competition; and (iii) desert, etc. Our empirical results strongly con-
spatial competition under strategic interaction.”
3
Fujita et al. (1999) argue that, at varied levels of
firm that there is a great deal of persistence
geographical aggregation, the locational fundamentals the- across time in which are the densely settled
ory is of quite limited importance, and instead the key to regions. For the increasing returns theory, this
understanding dispersion is increasing returns: “[T]he dra- would stress the importance of path depen-
matic spatial unevenness of the real economy—the dispar-
ities between densely populated manufacturing belts and
dence. For the random growth theory, this re-
thinly populated farm belts, between congested cities and quires that the variance of growth have not been
desolate rural areas; the spectacular concentration of partic- too high. However, we believe that this persis-
ular industries in Silicon Valleys and Hollywoods—is tence arises most naturally from the locational
surely the result not of inherent differences among locations fundamentals story and suggests this may be an
but of some set of cumulative processes, necessarily involv-
ing some form of increasing returns, whereby geographic important component of a complete answer.
concentration can be self-reinforcing.” (Fujita et al., 1999, Finally, the theories have quite distinct sto-
p. 2). ries to tell about how the distribution of cityVOL. 92 NO. 5 DAVIS AND WEINSTEIN: GEOGRAPHY OF ECONOMIC ACTIVITY 1271
sizes will be affected by a powerful, but tem- porary shocks. For the increasing returns theory,
porary, shock. The increasing returns literature, the message is more nuanced. There has long
as noted earlier, has given a prominent role to been a great deal of spatial dispersion of eco-
path dependence as well as to the possibility nomic activity, so increasing returns is not nec-
of catastrophes in which even small shocks essary to explain this. Nonetheless, in the last
may give rise to large and irreversible struc- century there has been a substantial rise in the
tural changes in relative city sizes.4 By look- degree of spatial dispersion, and this might well
ing at a large shock, one can gauge how be accounted for by increasing returns. The
important these theoretical possibilities of emphasis within the increasing returns literature
catastrophic spatial change are in practice. on the possibility of spatial catastrophes in the
The pure random growth theory predicts that distribution of city sizes seems to be of greater
growth follows a random walk—all shocks interest theoretically than empirically. Finally,
have permanent effects. By contrast, the lo- the locational fundamentals theory fares quite
cational fundamentals story holds that so long well in our empirical investigations. It has an
as the shock is purely temporary, even strong advantage over the increasing returns theory
shocks should shortly be reversed, as the ad- in that it provides a simple account of Zipf’s
vantages of the particular locations reassert Law. It can provide a consistent story about
themselves in relatively rapid growth rates on why there has been a great deal of spatial
the path to recovery. dispersion over long stretches of time. It can
The particular experiment that we consider is explain why there has been a great deal of
the Allied bombing of Japanese cities during persistence in which regions are most densely
World War II. This is one of the most powerful settled. And it can explain why specific loca-
shocks to relative city sizes that the world has tions are highly robust even to temporary
ever experienced. We find that, in the wake of shocks of great magnitude. The one weakness
the destruction, there was an extremely power- is that it does not provide a reason why the
ful recovery. Most cities returned to their rela- degree of concentration in Japan should have
tive position in the distribution of city sizes increased in the last century.
within about 15 years. This strikes most These considerations lead us to believe
strongly at the random growth theory, which that the most promising direction for re-
predicts no reversion to the prior path. For the search is to consider a hybrid theory in which
increasing returns theory, this suggests that locational fundamentals play a key role in
however appealing the theoretical possibility of establishing the basic pattern of relative re-
spatial catastrophes, in practice the distribution gional densities and in which increasing re-
of city sizes seems to be highly robust to tem- turns plays a strong role in determining the
porary shocks even of great magnitude. Finally, degree of concentration.
the reversion to the prior growth path would
seem to be a strong confirmation of a locational I. Bones: Archaeology, History,
fundamentals theory. and Economic Geography
In sum, our experiments are very problematic
for the pure random growth theory. While this A. The Data
theory provides a foundation for understanding
Zipf’s Law, it fails utterly to predict the great In this section, we examine 8,000 years
robustness of particular locations to strong tem- of data on Japanese regions in order to ad-
dress key questions concerning variation and
persistence of regional population densities.
4
For example, Krugman (1998, p. 7) writes: “The new Historically, how large has the variation in
work is highly suggestive, particularly in indicating how regional population density been and are there
historical accident can shape economic geography, and how important changes over time? How persistent
gradual changes in underlying parameters can produce dis- is the identity of the regions that have been
continuous change in spatial structure.” A theoretical exam-
ple can be found in Fujita et al. (1999), Figure 5.3. There a most densely settled? We then discuss the
shock to relative region sizes that is sufficiently large can results in light of the three theories noted
permanently alter the relative size of regions. above.1272 THE AMERICAN ECONOMIC REVIEW DECEMBER 2002
The data that we bring to bear is of two main especially over long stretches of time, the ap-
types.5 As we move back in time two millennia propriate definition of cities changes. For exam-
and more, one has access neither to regional ple, areas that are considered core parts of
accounts nor to population censuses. However, modern Tokyo would not have been thought of
Shuzo Koyama (1978) provides detailed data on as part of historical Tokyo (Edo). It is not at all
the number of archaeological sites, including clear how one should or could deal with such
28,013 from the Jomon period (⫺6,000 to issues. Third, for some of our early periods,
⫺300) and another 10,530 sites from the Yayoi virtually all of the population lived outside of
period (⫺300 to 300). These have been divided anything that in modern terms would be thought
according to the 45 modern prefectures we use.6 of as a city. Taken together, these factors sug-
We take a count of these archaeological sites for gest that the turn to regional data may be a
the respective periods as a proxy for the level of necessity, but it is one with many virtues.
economic activity in the prefectures. By focusing on regional data, one transfor-
The second type of data is population. In mation becomes absolutely essential. Differ-
order to provide a basis for taxation, Japan ences in region sizes are large and the
began censuses of population quite early. This demarcation between regions does not always
was done at a regional level because of the correspond to an obvious economic rationale.
substantial autonomy of local lords. Hiroshi This suggests that we work not with the raw
Kito (1996) provides the best estimates of re- regional population, but instead with the popu-
gional population for 68 provinces (kuni) for the lation deflated by the regional area. This mea-
period beginning in 725 and ending in 1872. In sure of regional population density will be the
1920 regional censuses began using a system unit of analysis for this portion of our study.8
based on 47 prefectures (ken), and this system One of the key reasons for turning to the
continues through our most recent data for the historical data is that economies of the remote
year 1998.7 Often we will find it convenient to past look quite different from the modern econ-
work with data that allows a comparison across omy. By examining such data, we are able to
all of these periods of time. A quite close match abstract from forces that we think are important
between the data sets can be achieved when we today, but much less so in earlier times. Hence
aggregate up to 39 regions. Kito (1996) also it is also important to have in mind the principal
provides estimates of total population of Japan features of the earlier economies (as outlined in
for the Jomon and Yayoi periods. Table 1).
We need to discuss the unit of analysis. A Our earliest data on archaeological sites of
great deal of work on economic geography con- the Jomon period (⫺6,000 to ⫺300) takes us
siders cities rather than regions as the unit of back to the Stone Age. The economy is based
analysis. We do have data on cities, and we will on hunting and gathering. There are no metal
discuss it, but this data extends back only to tools or agriculture, although there is evidence
1925. All of our earlier data concerns regions, of pottery. The Yayoi period (⫺300 to 300) is a
which thus must be the unit of analysis. There revolutionary time, with the introduction of
are, nonetheless, good reasons why one might primitive forms of agriculture, metallurgy, and
prefer the regional data. The first is that since some coins. As yet, there is neither writing nor
the definition of a city always involves a thresh- cloth. Our next stop in history is the year 725. A
old, even purely uniform growth of population feudal regime has risen and we have the first
in all locations may appear nonuniform because population census. Writing is well developed
populations may cross the threshold in some and farming is widespread. The capital is Nara.
locations but not others. A second reason is that, By 800, the capital has moved to Kyoto and
greater protection of peasant property rights has
encouraged more widespread cultivation. The
5
6
Details on data construction are in the Appendix. next century would see more extensive usage of
There are 47 prefectures in Japan, but we were forced
to drop Okinawa and Hokkaido because these prefectures
were not included in early censuses.
7 8
The move to prefectures occurred earlier, but the 1920 Rappaport and Sachs (2001) also focus on regional
census is the first to use these categories. population densities in the United States for similar reasons.VOL. 92 NO. 5 DAVIS AND WEINSTEIN: GEOGRAPHY OF ECONOMIC ACTIVITY 1273
TABLE 1—PRINCIPAL FEATURES OF HISTORICAL ECONOMIES
Share of
Population five Relative var of Raw Rank
in largest log population Zipf correlation correlation
Year thousands regions density coefficient with 1998 with 1998 History
⫺6000 to 125 0.39 2.46 ⫺0.809 0.53 0.31 Hunter-gatherer society, not ethnically
⫺300 (0.217) Japanese, no metal tools or
agriculture.
⫺300 to 595 0.23 0.93 ⫺1.028 0.67 0.50 First appearance of primitive
300 (0.134) agriculture and ethnically Japanese
people. Some metallurgical skills,
some coins, no writing or cloth.
725 4,511 0.20 0.72 ⫺1.207 0.60 0.71 Creation of feudal regime, population
(0.133) censuses begin, writing well
developed, farming is widespread.
Capital is Nara.
800 5,506 0.18 0.75 ⫺1.184 0.57 0.68 Capital moves to Kyoto. Property
(0.152) rights for peasant farmers continue
to improve, leading to greater
cultivation.
900 7,442 0.29 0.68 ⫺1.230 0.48 0.65 Use of metallic farm tools doubles
(0.166) over average for previous 300
years. Improved irrigation and dry-
crop technology.
1150 6,836 0.20 0.66 ⫺1.169 0.53 0.73 Multiple civil wars especially in (rice-
(0.141) rich) northern Japan. General
political instability and rebellions.
1600 12,266 0.30 0.64 ⫺1.192 0.76 0.83 Reunification achieved after bloody
(0.068) war, extensive contact with West.
Japan is a major regional trading
and military power.
1721 31,290 0.21 0.43 ⫺1.582 0.85 0.84 Closure of Japan to trade with minor
(0.113) exceptions around Nagasaki.
Capital moves to Tokyo. Political
stability achieved.
1798 30,531 0.21 0.37 ⫺1.697 0.83 0.81 Population is approximately 80
(0.120) percent farmers, 6 percent nobility.
Population stability attributed to
infanticide, birth control, and
famines.
1872 33,748 0.18 0.30 ⫺1.877 0.76 0.78 Collapse of shogun’s government,
(0.140) civil war, jump to free trade, end
of feudal regime, start subsidized
import of foreign technology.
1920 53,032 0.25 0.43 ⫺1.476 0.94 0.93 Industrialization and militarization in
(0.043) full swing, but still 50 percent of
labor force is farmers. Japan is a
major exporter of silk and textiles.
1998 119,486 0.41 1.00 ⫺0.963 1.00 1.00 Japan is a fully industrialized country.
(0.025) Tokyo, with a population of 12
million, is one of the largest cities
in the world.
Notes: Population for years prior to 725 is based on Koyama (1978). All time periods have 39 regions with Hokkaido and
Okinawa dropped from all years. The relative variance of the log population is the variance of the log of population density
in year t divided by the variance of the log of population density in 1998. The Zipf coefficient is from a regression of log rank
on log population density using 1920 log density as instruments for the years prior to 725 and 1998 data for later years.
Standard errors are in parentheses. The correlation columns indicate the raw and rank correlations between regional density
in a given year and regional density in 1998.1274 THE AMERICAN ECONOMIC REVIEW DECEMBER 2002
metal farm tools, raising productivity. By 1150, ble twice over, rising from 30 to 120 million. In
Japan was racked by instability and civil war, sum, our data covers Japan from the Stone Age
particularly in the North. to the modern era.
By 1600, the reunification of Japan was com-
plete and there is extensive trade and contact B. Variation in Regional Density
with the West. Japan is a major regional power.
By the 1630’s, however, Japan began more than We begin by examining several measures of
two centuries of self-imposed isolation. By variation in regional population density (see
1721, the capital moved to Tokyo and popula- Table 1). A very coarse but simple measure is
tion movement became more restricted. Even as the share of population accounted for by the five
late as 1798, fully 80 percent of the population most populous regions. This concentration was
were farmers, about 6 percent nobility, with quite high, at 39 percent, in the Jomon period.
the remainder merchants and artisans. By the This appears to reflect the fact that without
1870’s, Japan witnessed a civil war, the end agriculture, metal tools, or clothing, major sec-
of the Shogun’s government, a jump from au- tions of Japan were virtually uninhabitable.
tarky to free trade, and the subsidized import From here through the dawn of the twentieth
of Western technology. This can be thought century, the share of the five largest regions
of as the very start of Japan’s industrial revolu- typically hovered around 20 percent, occasion-
tion. By the 1920’s, industrialization and the ally rising toward 30 percent. Remarkably, by
accompanying militarization are in full swing. the end of the twentieth century, the share of the
Japan is a major exporter of silk and textiles. five most populous regions would rise above 40
Nonetheless, approximately 50 percent of the percent.
workforce is still composed of farmers. By A second measure of regional variation is
1998, of course, Japan is a highly industrialized what may be termed the relative variance of log
society, with farmers now comprising only 5 population density, which measures variance in
percent of the population. Tokyo is one of the proportional terms. To get this, first take logs of
world’s great cities with a population of 12 the regional population densities. For each pe-
million. riod, this allows us to compute a variance of the
We conclude our data description by exam- log population densities. If we now normalize
ining the evolution of the total population of this by the same measure of variation for 1998,
Japan. The main features are developed in Table we get a measure that is above unity if the
1. Kito (2000) estimates that the population in variation is greater in the historical period than
Jomon-period Japan would have been approxi- in modern Japan and below unity in the reverse
mately 125,000; by 1998, it would fall just shy case.9
of 120 million. In short, our data encompasses a A first observation is that regional population
period in which Japanese population rises by a variation is substantially higher in the modern
factor of nearly one thousand. If we restrict period than at all prior dates except the Jomon
attention to the period for which we have cen- and Yayoi periods. Again, one reason there is so
suses (i.e., from 725 to 1998), the population much variation in the Jomon and Yayoi periods
rises from 4.5 million to nearly 120 million. is simply that the economies were so primitive
That is, our census data encompasses a period in that major sections of Japan were almost unin-
which total Japanese population rises by a factor habitable. A second observation is that all of the
greater than 25. From the Jomon period through censuses from 700 to 1600 show a great deal
about 1721, the broad trend is substantial pop-
ulation growth. In large measure, this reflects
the development of agriculture and its imple- 9
An advantage of using this measure over simply using
ments, extension of regions of cultivation, and the variance in population density is that the former is
establishment of institutions that encouraged in- invariant to average density while the latter tends to rise
vestments in the land. For the next century and with it. The reason for this is that as population, and hence
average density, rises, the same proportional density differ-
a half, through the 1870’s, there is very little ences produce higher absolute variations in density. Since
population growth. In the next 120 years, we wanted to sweep this effect out of the data, we calculate
through 1998, Japanese population would dou- variance based on log population density.VOL. 92 NO. 5 DAVIS AND WEINSTEIN: GEOGRAPHY OF ECONOMIC ACTIVITY 1275
of variation in regional population density— large. Here we will report Zipf coefficients
typically two-thirds to three-fourths of the mod- computed not on city populations but on re-
ern variation. Indeed an F-test reveals that we gional population densities. As we will see,
cannot reject the hypothesis that variance in this transformation does little to disturb the
regional population density in any year prior to basic relation.
1721 was the same as the modern variance (at One should not directly run Zipf-style regres-
the 5-percent level). Interestingly, the data from sions on historical data since the population data
1721 through 1872 shows that the closure of is surely measured with error. In order to obtain
Japan seems to have been accompanied by a unbiased estimates, we need an instrument cor-
substantial reduction in regional population related with historical population data but not
variation. A plausible reason is that eight out of correlated with the measurement error in that
the 12 densest regions in 1600 comprised port survey. An obvious instrument that fits the need
cities whose share of population declined mark- is modern population density, since it is
edly over this time period.10 Closure to trade strongly correlated with historical density but
probably dramatically reduced the value of lo- not with historical census errors. We therefore
cating in a port relative to remaining in farm- used density in 1998 as an instrument for earlier
ing.11 Finally, the reopening of Japan and the census data. We had a different problem with
development of the modern economy gave rise the Jomon and Yayoi data. Urban density in
to a substantial increase in regional variation in 1998 is not a good instrument, since archaeo-
population density. logical discoveries might be correlated with
We can also examine a third measure of modern construction. However, since most Jap-
variation in regional density, the Zipf coeffi- anese archaeological discoveries of Jomon and
cient. We have already noted, in reference to the Yayoi sites occurred since 1960 [see Koyama
random growth theory, that there is an empirical (1978)], we used 1920 density data as an instru-
regularity known as Zipf’s Law for Cities. To ment for these regressions.
understand this, rank the cities by population Table 1 reports the Zipf coefficient for each
and now take logs of both the rank of the city of our time periods. The broad story that it tells
and of its population. Zipf’s Law for Cities confirms the results from the prior nonparamet-
holds that a regression of the log rank against ric statistics. Dispersion was relatively high in
log population will have a slope of minus unity. the Jomon and Yayoi periods—indeed very
Gabaix (1999) reports a slope of ⫺1.004 for the close to fitting Zipf’s Law. Regional variation in
United States and Kenneth T. Rosen and density declined modestly for the period 725 to
Mitchel Resnick (1980) report slopes for a va- 1600, before declining sharply in the period in
riety of OECD countries, many of which are which Japan was closed to the West. Since
reasonably close to minus unity. Japan reopened and began its industrialization,
In this context, the magnitude of the Zipf regional variation has increased substantially,
coefficient provides information about variation reaching a Zipf coefficient of ⫺0.96 in 1998.12
in regional density. If there were only trivial The coefficients are quite precisely estimated.
variation in regional population density, then With the exception of the Jomon period, which
the Zipf slope would be close to minus infinity. has a standard error of 0.22, our standard errors
If virtually all of the population were clustered on the Zipf coefficient range from 0.03 in 1998
in a single region, the Zipf coefficient would to 0.17 in the year 900. We cannot statistically
be close to zero. Hence when the magnitude
of the Zipf coefficient is small, the variation is 12
On first blush, this might appear to conflict with the
results of Jonathan Eaton and Zvi Eckstein (1997) that
showed the stability of the Zipf coefficients for Japanese
10
These were Chiba, Fukuoka, Kobe, Nagoya, Osaka, cities over the period 1925–1985 (a result that we can
Tokyo, Yokkaichi, and Yokohama. confirm). Here the difference between their use of city data
11
Other policies may also have affected city sizes such and our use of regional data is crucial, since this suggests
as the construction of castle towns, tax evasion in rural that even if there is little change in the distribution of city
areas, and declining finances for samurai [See James Whit- sizes, there may be important spatial correlation among
ney Hall (1968) and Susan B. Hanley and Kozo Yamamura cities that are growing, which could explain the increased
(1977)]. variation in regional densities.1276 THE AMERICAN ECONOMIC REVIEW DECEMBER 2002
distinguish the modern coefficient from that in a factor of 200. If we know the distribution of
1600 or any prior date. the regional density of archaeological sites from
Our examination of 8,000 years of Japanese the Yayoi period, how much information would
regional data reveals three important facts. First, we expect this to provide about the distribution
regional population densities have always var- of modern regional population densities? The
ied greatly in Japan. This is true in the Stone raw and rank correlations are 0.67 and 0.50
Age, at the dawn of the agricultural revolution, respectively. Given that two millennia of Japa-
during the long period of feudalism, and it re- nese history separate these dates, with the ac-
mains true in modern industrial Japan. Indeed, companying economic transformations, we
with the exception of Stone Age Japan, our consider this persistence to be quite remarkable.
spread of Zipf coefficients is well within the In moving to the year 725, we now are able to
range of coefficients that one would find in a work with the first census data and ask the same
sample of OECD countries [cf., Rosen and questions. A feudal regime is in place. The vast
Resnick (1980)].13 Second, the closure of Japan majority of the population is agricultural. None-
to trade for more than two centuries was accom- theless, the raw and rank correlations of re-
panied by a substantial reduction in the varia- gional population densities in 725 and 1998 are
tion of regional population density. Large port- 0.60 and 0.71 respectively. Again, these show a
based regions appear to have lost ground relative remarkable persistence.
to regions directed more exclusively to national We will not discuss every date. Perhaps not
activity. Third, the industrial revolution in Japan, surprisingly, there is a general trend that raw
coming hand in hand with its reopening to inter- and rank correlations with modern regional den-
national trade, does seem to have promoted a very sities rise pretty steadily. We will cite just one
high degree of regional concentration and varia- last date. If we look four centuries back to the
tion in regional population density. year 1600, a time in which Japan had a popu-
lation just over 10 percent of its modern popu-
C. Persistence in Regional Population Densities lation, the raw and rank correlations with the
modern regional densities are 0.76 and 0.83
We now turn to consider persistence in the respectively.
identity of the regions that are densely settled. In sum, it is absolutely striking how much
Table 1 reports both raw and rank correlations persistence there is in the distribution of re-
between the regional population densities in the gional population density throughout Japanese
various periods with those for 1998. Consider history. The high correlations trace back virtu-
first the Jomon data, dating from Japan’s Stone ally to the Stone Age. The correlations between
Age (⫺6,000 to ⫺300). The raw and rank cor- modern regional densities and those of Japan
relations of the density of archaeological sites four centuries ago are remarkably strong. Per-
from this period and 1998 regional population sistence is a very strong feature of the data.14
density are 0.53 and 0.31, respectively. The
higher raw correlation especially captures the
fact that the most densely settled regions are 14
common in the two periods. The lower rank cor- This strong persistence raises an interesting ques-
tion: Is the case of Japan special? One notable topograph-
relation captures the fact that large sections of ical feature of Japan is that it is highly mountainous. Is
Japan were relatively untouched by the Jomon the simple contrast between uninviting mountains and
people and so the rankings among these are weak. inviting valleys the source of the persistence? Would one
Consider next the Yayoi period (⫺300 to find such persistence in a land with less stark contrasts?
We believe that additional research is warranted. None-
300). Agriculture and metallurgy are just being theless, we believe there is suggestive evidence in Rap-
introduced. Writing has not yet appeared. In the paport and Sachs (2001) that the pure role of geography
next two millennia, total population will rise by in determining the spatial distribution of activity is large
even in a country with less apparently stark contrasts,
such as the United States. They consider U.S. counties
13
Rosen and Resnick (1980) estimate the Zipf relation- proximate to an ocean, Great Lake, or navigable river;
ship for a broad set of countries using a comparable number jointly these counties account for 15 percent of the U.S.
of observations. Within the OECD countries in their sample, land mass, but 54 percent of the population and 60
Zipf coefficients range from ⫺0.88 to ⫺1.96. percent of civilian income.VOL. 92 NO. 5 DAVIS AND WEINSTEIN: GEOGRAPHY OF ECONOMIC ACTIVITY 1277
II. Bombs and Break Points data on expenditures from U.S. and Japanese
government sources designated for the recon-
Imagine a calamity destroys a large share of struction of war damage in each prefecture. We
a city’s productive capacity and drastically re- allocate these among the cities within the pre-
duces its population. Will this temporary shock fecture in proportion to the shares of buildings
have permanent effects? Or is there a strong destroyed in that city. These are divided by
tendency for locations to be robust even to large the population in the city in 1947 to create
temporary shocks so that this city will shortly our variable, “government reconstruction ex-
revert to its former place in the constellation of penses,” which is thousands of yen per capita
cities? An ideal experiment would have several spent by the government to reconstruct a city.
key features. The shocks would be large, highly These geographically directed expenditures are
variable, clearly identifiable, and purely tempo- quite small. For example, most food aid, income
rary. In this section, we will consider the Allied assistance, and industrial subsidy programs did
bombing of Japanese cities during World War II not discriminate on the basis of location, and
as precisely such an experiment. therefore do not count as regional subsidies.
Interestingly, rural prefectures, which typically
A. Data sustained less war damage, received significantly
more aid relative to the number of buildings de-
Our data covers 303 Japanese cities with pop- stroyed than more urban areas. This was probably
ulation in excess of 30,000 in 1925. Population due to Japan’s long-term policy of subsidizing
is recorded at five-year intervals between 1925 rural districts at the expense of urban ones.
and 1965, with the exception that the regular
1945 census is delayed until 1947 due to dis- B. Magnitude of the Shocks
ruption from the war. These data allow us to
compute population growth rates for the prewar The Allied strategic bombing of Japan in
period, 1925–1940; the period of the war itself World War II devastated the targeted 66 cities.
and its immediate aftermath, 1940 –1947; and The bombing destroyed almost half of all struc-
two measures of the recovery period, 1947– tures in these cities—a total of 2.2 million
1960 and 1947–1965.15 buildings. Two-thirds of productive capacity
One measure of the intensity of the shocks vanished. Three hundred thousand Japanese
will be the dead and missing city residents due were killed. Forty percent of the population was
to war actions. The missing are included be- rendered homeless. Some cities lost as much as
cause the magnitude of the shocks frequently half of their population owing to deaths, miss-
made recovery of bodies impossible, as for ex- ing, and refugees.16
ample with those vaporized by the Hiroshima The nuclear bombings of Hiroshima and Na-
nuclear blast. In order to have a measure of the gasaki are, of course, well known. The first
intensity of the shocks, the dead and missing atomic weapon was dropped on Hiroshima on
will typically enter deflated by the number of August 6, 1945, and was the equivalent of 12
city residents in 1940. A second measure of the kilotons of TNT. The temperature at the blast
intensity of the shocks will be the number of site is believed to have surpassed one million
buildings destroyed per resident. We also at degrees Celsius. Over two-thirds of the built-up
times report the percentage of the built-up area area of the city was destroyed. The blast may
destroyed for the 66 Japanese cities covered by have killed as many as 80,000 people—more
the United States Strategic Bombing Survey than 20 percent of Hiroshima’s population. The
(USSBS) (1947). second atomic weapon was dropped on Nagasaki
If we are to understand the impact of private on August 9 and had a power nearly twice that of
actions that may lead cities to recover, it is Hiroshima, at 22 kilotons. The hilly topography of
important to control for government actions. Nagasaki and the fact that the bomb missed its
The Japan Statistical Yearbook (1950) provides target by a wide margin kept the destruction of the
15 16
More detail is provided in the Appendix. These numbers are from USSBS (1947).1278 THE AMERICAN ECONOMIC REVIEW DECEMBER 2002
built-up area under 40 percent. Still, more than only amounted to 50.8 percent of its built-up
25,000 were killed or went missing, approxi- area (USSBS, 1947, p. 42). This is actually just
mately 8.5 percent of city residents. under the median percentage of urban destruc-
While the nuclear attacks on Hiroshima and tion of 50.9 percent for the 66 targeted cities. In
Nagasaki are widely known among the public in short, in terms of the destruction of built-up area
the West, the devastation of other Japanese cit- for the targeted cities, the devastation of Tokyo
ies is much less well known. An example of the we described made it just a typical city.17
magnitude of the destruction is a single fire-
bombing raid on Tokyo the night of March 9, C. Variance of the Shocks
1945. United States B-29 Superfortress bomb-
ers, based in the Marianas Islands, flew more While the magnitude of the shocks to city
than 300-strong over Tokyo that night. Under a sizes was large, there was also a great deal of
new strategy devised by General Curtis LeMay, variability in these shocks. In fact, approxi-
the bombers flew with minimal defenses and at mately 80 percent of the 300 cities in our sam-
low altitudes. This allowed them to maximize ple, collectively representing 37 percent of the
the payload of napalm incendiaries and to re- urban population, were virtually untouched by
lease these at precise intervals. The city had the bombings. This includes large cities. Kyoto,
received no rain in a week and the wind that the fifth largest city at the beginning of the war,
night blew at 25 miles per hour. Tokyo—a city was not bombed at all.18 Given the city’s his-
of straw, paper, and wood—lay in wait. The B-29 torical significance, it was believed that its de-
Superfortresses flew over Tokyo for just three struction might strengthen the Japanese will to
hours on March 9, dropping 1.7 kilotons of na- resist. The large cities of Niigata and Kitakyu-
palm incendiaries. This unleashed a firestorm. shu escaped substantial damage because they
Rivers boiled. Asphalt streets liquefied and burst were preserved as potential nuclear bomb tar-
into flame. The results were devastating. Sixteen gets. Cities in the North of Japan, such as Sap-
square miles of Tokyo were reduced to ash. At poro, escaped heavy bombing because they
least 80,000 people were killed in that raid alone were largely out of range of U.S. bomber forces.
(Kenneth P. Werrell, 1996, p. 162– 63). Even among those cities that did suffer fire-
The magnitude of destruction in the March 9 bombing, there is a high degree of variability in
raid on Tokyo was large not only by Japanese the destruction. One reason is learning by doing.
standards; when it happened, it was the deadliest The creation of a firestorm from napalm incen-
single-day air attack in the history of the world. diaries depended on having a sufficient number
The number of people killed was of the same of planes, dropping the incendiaries in precise
order of magnitude as the nuclear bombing of patterns and at relatively close intervals. While
Hiroshima. Japan suffered more civilian casualties some tests of the incendiaries had been con-
in that one raid than Britain suffered in all of ducted on mock Japanese cities at the Dugway
World War II. And this was just the beginning. By Proving Grounds in Utah, it was only as a result
the end of the war, the United States had destroyed of the experience of actual bombing raids that
more square miles of Tokyo than the combined U.S. forces achieved the optimal pattern. More-
destruction in the 15 most heavily bombed Ger- over, cities such as Nagoya, which were fire-
man cities (Werrell, 1996, p. 32).
A major reason why Tokyo stands out in
Japanese data is due to the fact that with a 1940 17
The Allies dropped 17 pounds of incendiaries per
population of 7.3 million it was by far the capita on the median firebombed city, but only four pounds
per capita on Tokyo. Tokyo nonetheless still stands out for
largest target in Japan. Given that Tokyo was 16 the number who died. It seems likely that in smaller cities
times the size of Hiroshima and more than 20 there was greater opportunity to escape the firestorms.
times the size of Nagasaki, even nuclear bombs 18
Our definition of “virtually untouched” is casualties of
could not kill as many people in these smaller under 100. Eric Hammel (1998) reports no air attacks on
cities. This suggests the value of considering Kyoto. Takahide Nakamura and Masayasu Miyazaki (1995)
do report 82 casualties in Kyoto (1940 population 1.1 mil-
destruction in proportional rather than absolute lion) due to the war. Presumably these were due to targeting
terms. Seen this way, the destruction in the errors, strafing, and/or Kyoto residents who were killed in
course of the war of 56 square miles of Tokyo other cities.VOL. 92 NO. 5 DAVIS AND WEINSTEIN: GEOGRAPHY OF ECONOMIC ACTIVITY 1279
bombed early, had as a result of those raids the Let S it be city i’s share of total population at
equivalent of firebreaks within the city. In the time t, and let s it be the natural logarithm of this
subsequent raids, it became nearly impossible to share. Suppose further that each city has an
create highly destructive firestorms. initial size ⍀ i and is buffeted by city-specific
In addition, there were a large number of shocks it . In this case we can write the size of
other factors at work that created variance in the any city at any point in time as,
destruction of cities. These include the steady
growth in the number of B-29s available for (1) s it ⫽ ⍀ i ⫹ it .
service; the evolving defense capabilities of the
Japanese cities (which was important notably We can model the persistence in these shocks to
for Osaka); the topography of specific cities; population shares as:
and sheer fortune, as in the fact that Nagasaki
was bombed only when the primary target, (2) it ⫹ 1 ⫽ it ⫹ it ⫹ 1 .
Kokura (now Kitakyushu), could not be visually
identified due to cloud cover. The parameter 僆 [0, 1], and the innovation,
it , is an independently and identically distrib-
D. Temporary Nature of the Shocks uted error term.
We examine the evolution of this system by
Rarely does one find shocks that can so clearly first-differencing equation (1). This yields
be identified as temporary. For much of World
War II, Japanese cities were simply out of range of (3) s it ⫹ 1 ⫺ s it ⫽ it ⫹ 1 ⫺ it .
U.S. bombers. In the first year of the war, the
United States managed only the single “Doolittle If we substitute equation (2) into equation (3),
raid” on Japan from a U.S. carrier, and this had we then obtain
little more than psychological impact. Later, the
United States tried to use China as a base for (4) s it ⫹ 1 ⫺ s it ⫽ 共 ⫺ 1兲 it
attacks on Japanese cities. But the long flights
required and the difficult supply lines insured that ⫹ 关 it ⫹ 1 ⫹ 共1 ⫺ 兲 it ⫺ 1 兴.
these had only minimal effect. It was only with the
capture of the Marianas Islands as a B-29 base, the The key parameter is , which tells us how
seizure of Iwo Jima (which lay directly between much of a temporary shock is dissipated in one
the Marianas and Japan) as a base for fighter period. If ⫽ 1, then all shocks are permanent
escorts, a rise in the number of planes available, and city size follows a random walk.19 In this
and the introduction of new tactics by General case,
LeMay that the U.S. attacks reached an apogee.
The most powerful attacks were compressed in
the last five months of the war. 19
Equation (5) is identical to the key equation in Gabaix
While the devastation of many of these cities (1999)—what he terms “the basic idea.” We also consider
was powerful, once the flames were out, the one amendment to this basic idea in the empirical section.
geographical characteristics of particular loca- However, it is worth noting that we do not consider all
possible random walk processes. One could imagine a world
tions are affected little or not at all. The one in which shocks come in two parts— one of which is mean
possible exception, of course, is the lingering reverting and the other a random walk. Over a short horizon,
radiation in Hiroshima and Nagasaki. This will we might see very strong mean reversion, even though over
make these particularly interesting cases to see a sufficiently long horizon the structure of city sizes is
determined by the random walk component. If one is willing
whether they were special cases in the period of to believe that the random walk component is quite small,
recovery from the war. then this will be a very difficult hypothesis to reject. The
problem with this explanation of Zipf’s Law is that if this
E. Impact of the Shocks: paper’s restrictions on the size of the permanent component
Temporary or Permanent? of the shock is appropriate, then it would take very long
horizons (possibly in the thousands of years) for the Zipf
distribution to emerge. In any case, over the shorter hori-
We now inquire whether temporary shocks zons of interest, this paper shows that mean reversion to
have permanent effects on relative city sizes. shocks is a superior economic model.1280 THE AMERICAN ECONOMIC REVIEW DECEMBER 2002
(5) s it ⫹ 1 ⫽ s it ⫹ it ⫹ 1 .
If 僆 [0, 1), then city share is stationary and
any shock will dissipate over time. In other
words, these two hypotheses can be distin-
guished by identifying the parameter .
One approach to investigating the magnitude
of is to search for a unit root. It is well known
that unit root tests usually have little power to
separate ⬍ 1 from ⫽ 1. This is due to the
fact that in traditional unit root tests the inno-
vations are not observable and so identify with
very large standard errors. A major advantage
of our data set is that we can easily identify the FIGURE 1. EFFECTS OF BOMBING ON CITIES WITH
MORE THAN 30,000 INHABITANTS
innovations due to bombing. In particular, since
by hypothesis the innovation, it , is uncorre- Note: The figure presents data for cities with positive casu-
alty rates only.
lated with the error term (in square brackets),
then if we can identify the innovation, we can
obtain an unbiased estimate of .
An obvious method of looking at the innova- population growth between 1947 and 1960 with
tion is to use the growth rate from 1940 to 1947. that between 1940 and 1947. The sizes of the
However, this measure of the innovation may circles represent the population of the city in
contain not only information about the bombing 1925. The figure reveals a very clear negative
but also past growth rates. This is a measure- relationship between the two growth rates. This
ment error problem that could bias our estimates indicates that cities that suffered the largest
in either direction depending on . In order to population declines due to bombing tended to
solve this, we instrument the growth rate from have the fastest postwar growth rates, while
1940 –1947 with buildings destroyed per capita cities whose populations boomed conversely
and deaths per capita.20 had much lower growth rates thereafter.
We can obtain a feel for the data by consid- In Table 2, we present a regression showing
ering the impact of bombing on city growth the power of our instruments. Deaths per capita
rates. As we argued earlier, if city growth rates and destruction per capita explain about 41 per-
follow a random walk, then all shocks to cities cent of the variance in population growth of
should be permanent. In this case, one should cities between 1940 and 1947. Interestingly,
expect to see no relationship between historical although both have the expected signs, destruc-
shocks and future growth rates. Moreover, if tion seems to have had a more pronounced
one believes that there is positive serial corre- effect on the populations of cities. Presumably,
lation in the data, then one should expect to see this is because, with a few notable exceptions,
a positive correlation between past and future the number of people killed was only a few
growth rates. By contrast, if one believes that percent of the city’s population.
location-specific factors are crucial in under- We now turn to test whether the temporary
standing the distribution of population, then one shocks give rise to permanent effects. In order
should expect to see a negative relationship to estimate equation (4), we regress the growth
between a historical shock and the subsequent rate of cities between 1947 and 1960 on the
growth rate. In Figure 1 we present a plot of growth rate between 1940 and 1947 using
deaths and destruction per capita as instruments
for the wartime growth rates. The coefficient on
20
The actual estimating equation is s i60 ⫺ s i47 ⫽ ( ⫺ growth between 1940 and 1947 corresponds to
1) 47 ⫹ [ i60 ⫹ ( ⫺ 1) i34 ]. Our measure of the ( ⫺ 1). In addition, we include government
innovation is the growth rate between 1940 and 1947 or
s i47 ⫺ s i40 ⫽ 47 ⫹ [ i34 ⫺ i40 ]. This is clearly subsidies to cities to control for policies de-
correlated with the error term in the estimating equation, signed to rebuild cities.
hence we instrument. If one believes that cities follow a randomVOL. 92 NO. 5 DAVIS AND WEINSTEIN: GEOGRAPHY OF ECONOMIC ACTIVITY 1281
TABLE 2—INSTRUMENTAL VARIABLES EQUATION TABLE 3—TWO-STAGE LEAST-SQUARES ESTIMATES OF
(DEPENDENT VARIABLE ⫽ RATE OF GROWTH IN CITY IMPACT OF BOMBING ON CITIES
POPULATION BETWEEN 1940 AND 1947) (INSTRUMENTS: DEATHS PER CAPITA AND BUILDINGS
DESTROYED PER CAPITA)
Independent variable Coefficient
Dependent Dependent
Constant 0.213 variable ⫽ variable ⫽
(0.006) growth rate growth rate
Deaths per capita ⫺0.665 of population of population
(0.506) between between
Buildings destroyed per capita ⫺2.335 1947 and 1947 and
(0.184) 1960 1965
R 2: 0.409 Independent variable (i) (ii) (iii)
Number of observations: 303
Growth rate of population ⫺1.048 ⫺0.759 ⫺1.027
Note: Standard errors are in parentheses. between 1940 and 1947 (0.097) (0.094) (0.163)
Government reconstruction 1.024 0.628 0.392
expenses (0.387) (0.298) (0.514)
Growth rate of population 0.444 0.617
walk or that catastrophes can permanently alter between 1925 and 1940 (0.054) (0.092)
the size of cities, then one should expect the R2: 0.279 0.566 0.386
coefficient on the 1940 –1947 growth rate, ( ⫺ Number of observations: 303 303 303
1), should be zero. If one believes that the
Note: Standard errors are in parentheses.
temporary shocks have only temporary effects,
then the coefficient on 1940 –1947 growth
should be negative. A coefficient of ⫺1 indi-
cates that all of the shock was dissipated by that cumulative growth in these cities over that
1960. period was between 55 and 96 percent, we
The results are presented in Table 3. The conclude that reconstruction expenses had rela-
coefficient on 1940 –1947 growth is ⫺1.048, tively small impacts. As we noted earlier, a
indicating that at this interval is approximately major reason for this was that reconstruction
zero. This means that the typical city com- policies, like most Japanese regional policies,
pletely recovered its former relative size within disproportionately sent money to rural areas. As
15 years following the end of World War II. a result, the four biggest per capita recipients of
Given the magnitude of the destruction, this is assistance were small northern cities that were
quite surprising. Apparently, U.S. bombing of never targeted by U.S. bombers.
Japanese cities had no impact on the typical One potential problem with these results is
city’s size in 1960. This strongly rejects the that it is possible that the United States inad-
hypothesis that growth in city-size share is a vertently targeted cities based on underlying
random walk. growth rates. While this was not an explicit
As expected, reconstruction subsidies seem strategy, we cannot rule it out. If the United
to have had a positive and statistically signifi- States bombed rapidly growing cities more
cant impact on rebuilding cities. However, the heavily, then we may be biasing our results
economic impact is quite modest. Our estimates downwards. We therefore repeated our exercise
suggest that a one standard deviation increase in adding the growth rate between 1925 and 1940
reconstruction expenses would increase the size to our list of independent variables. This im-
of a city in 1960 by 2.2 percent. Reconstruction proves the fit, but does not qualitatively change
expenses probably had a small effect because the results, although the coefficient on 1940 –
both the sums spent and the variance in the 1947 growth falls to ⫺0.76. This implies that
sums were small. In the cities that suffered the bombed cities had recovered over three-fourths
heaviest destruction—Tokyo, Hiroshima, Na- of their lost growth by 1960. One reasonable
gasaki, and Osaka— our estimates indicate that question to ask, then, is whether these cities
government reconstruction expenses accounted ever returned to their prewar trajectories or not.
for less than one percentage point of their cu- If one believes in the location-specific model,
mulative growth between 1947 and 1960. Given then one should expect that the coefficient on1282 THE AMERICAN ECONOMIC REVIEW DECEMBER 2002
FIGURE 2. POPULATION GROWTH
wartime growth should asymptotically ap- gasaki. In those cities, the number of deaths was
proach unity as the end period increases. In the such that if these cities recovered their popula-
last column of Table 3 we repeat the regression, tions, it could not be because residents who
only now extending the endpoint to 1965 in- temporarily moved out of the city returned in
stead of 1960. The estimated coefficient now subsequent years. We have already noted that
reaches ⫺1.027. That is, after controlling for our data underestimates casualties in these cit-
prewar growth trends, by 1965 cities have en- ies. Even so, our data suggest that the nuclear
tirely reversed the damage due to the war. bombs immediately killed 8.5 percent of Na-
Again, the impact of reconstruction subsidies gasaki’s population and 20.8 percent of Hiro-
also lessens as we move into the future. To- shima’s population. Moreover given that many
gether, these results suggest that the effect of Japanese were worried about radiation poison-
the temporary shocks vanishes completely in ing and actively discriminated against atomic
less than 20 years. bomb victims, it is unlikely that residents felt an
One possible objection to our interpretation is unusually strong attachment to these cities or
that in most cases, the population changes cor- that other Japanese felt a strong desire to move
responded much more to refugees than deaths. there. Another reason why these cities are in-
Of the 144 cities with positive casualties, the teresting to consider is that they were not par-
average number of deaths per capita was only 1 ticularly large or famous cities in Japan. Their
percent. Most of the population movement that 1940 populations made them the 8th and 12th
we observe in our data is due to the fact that the largest cities in Japan. Both cities were close to
vast destruction of buildings forced people to other cities of comparable size so that it would
live elsewhere. However, forcing them to move have been relatively easy for other cities to
out of their cities for a number of years may not absorb the populations of these devastated
have sufficed to overcome the social networks cities.
and other draws of their home cities. Hence it In Figure 2 we plot the population of these
may seem uncertain whether they are moving two cities. What is striking in the graph is that
back to take advantage of particular character- even in these two cities there is a clear indica-
istics of these locations or simply moving back tion that they returned to their prewar growth
to the only real home they have known. trends. This process seems to have taken a little
However, there are two cases in which this longer in Hiroshima than in other cities, but this
argument cannot be made: Hiroshima and Na- is not surprising given the level of destruction.You can also read
