3
What Drives City Growth
in the DevelopingWorld?
Allen C. Kelleyand JeffreyG. Williamson
C
C
ities are capital-intensive,a stylizedfact which has
led many pessimiststo assert that current rates of
city growth in the developingworldcannot be sustained.
To make matters worse, cities are stocked with public
capitalat low or zero user charges,and in that sensethey
are too capital-intensive.Since the social costs of inmigration thus exceed private costs, the number and
sizes of cities turn out to be excessive.Furthermore,the
increasing scarcity of urban land encourages the substitution of capital for land and increasescapital intensity. When the economy can no longer finance such
urban costs-when it fails, for instance, to copewith
socialoverheadand housing requirements-the process
of urbanization is retarded.
No doubt the qualitativeanalysisis correct: cities are
capital-intensiveand have a voraciousappetitefor savings and accumulation.But is the quantitativeemphasis-the idea that cities are "too big"-warranted?
It is also often alleged that rapid city growth in the
developingcountries represents a disequilibrium,that
these countries have"overurbanized," and that a painful
structural adjustment will eventuallybe required.Analysts of urban problems in the developingworld point
out that migrants are attracted to the cities in the hope
that they (or their children)willbe selectedfor training
and employment in protected, high-wage sectors.
Apparently,newin-migrantsarewillingto acceptunderemployment in low-wage traditional service sectors
while waiting. Eventually,however,social discontent is
likelyto erupt. Are labor markets in these citiesreallyin
serious disequilibrium, and is the developingworld
overurbanizedas a consequence?
It is often alleged that the unusually high rates of
developing-countryurbanizationin the recent past can
be traced to the availabilityof cheap energy,technological diffusionthat favors modem urban sectors, heavy
capital inflows,world trade liberalization,a drifttoward
domestic price distortions that favor city output, and
unusually rapid population growth. That these conditions have begun to show signs of changing suggests
that the developingworld may have overurbanizedin
the recent past. Urban growth may be expectedto decelerateover the next two decadesunder certain conditions: a recurrence of fuelscarcity,technologicalregression in modern sectors in the face of a productivity
slowdownin industrial countries, diminished capital
transfers because of economic austerity in industrial
countries, a retreat toward protectionism in industrial
countries, and a decreasein population growth.
In short, the pessimists offer three sources for an
incipient urban crisis in the developingworld:a savings
constraint which will bridle the growth of capitalintensivecities; a labormarket disequilibriumwhichhas
made overurbanizationa temporarybut seriousproblem
of overshoot;and the disappearanceof unusual external
conditionswhichwere favorableto urban growth in the
past. Although the pessimistshave establisheda plausible case,no one to our knowledgehas offereda quantitative assessment of the importance of these forces over
the past two decades.Without such an assessment,debate over future trends in developingcountries will be
dominated by allegation and anecdotal evidence.It is
our view that the debate can be better informedby the
application of a general equilibrium model of development that includes some of the costs of urbanization,
so that "natural limits" to urban growth can be evalu32
WhatDrivesCityGrowthin theDeveloping
World?
ated and the impact of changing economicand demographic conditions assessed(seeKelleyand Williamson
1984a, b).
The Limits on City Growth
The limits on urban growth are set, on the one hand,
by urban costs that affect migration decisionsand, on
the other, byrising urban investmentrequirementsthat
compete with productivecapital accumulation. Urban
land constraints raise rents, increase living costs in
urban areas relative to rural areas, and thus inhibit
migration into cities.To the extentthat rising rents and
urban disamenitiesare causedby high densities,crowding, and other manifestationsof inelastic urban land
supply,city rents reflectthe qualityof urban life as well
as living costs. To evaluate the impact of urban land
constraints on city rents, a generalequilibriummodelis
neededwhich, at the minimum, admits housingservice
activities and confronts equilibrium land use issues.
Furthermore,a varietyofurban land requirementsmust
be included-residential squatter settlements, factory
sites, land use for public social overhead,and luxury
housing sites.
The housing and social overheadinvestment requirements of city growth must also be analyzed.Such "unproductive" urban investment requirements (first analyzedby Coaleand Hoover1958)compete directlywith
"productive"capitalaccumulationand maycheckurban
growth.If such overheadinvestmentis forgone,housing
costs rise, the qualityof urban servicesfalls,and migration to cities is discouraged.Thus, in addition to the
effectof the rise in the relativecost of livingin the city,
the rise in unproductive investment requirements in
cities maylowerthe rate ofproductivecapitalaccumulation and job creation and set a limit to urban growth.
Modemurban sectors also tend to be relativelyintensive in skills, in intermediate inputs, and in such imported inputs as energy. To the extent that cities are
energy-intensive,fuel scarcitycan limit urban growth.If
capital and skills are complements and different labor
skills are poor substitutes for each other, rapid rates of
urban capital accumulation implyincreasing demands
for skilled labor, which can constrain capacityexpansion, retard growth of employment,and limit urban
growth. An effort to relax the labor constraint through
skill accumulation is likelyto competewith productive
urban capital accumulation and itselfconstitutea limit
on urban growth.
This chapter uses a computablegeneral equilibrium
model to analyze past, present, and future growth of
cities in the developingworld. Since the model has
appearedelsewhere(Kelleyand Williamson1980,1982,
33
1984b),only a suggestiveoutline is presentedhere.The
model is in the neoclassicalgeneral equilibriumtradition. Prices of outputs and inputs are completelyflexible, and most are endogenouslydetermined; firms are
drivenby profit maximization;householdsare drivenby
utility maximization;and evengovernment demanddecisions obeywell-definedrules from consumer demand
theory. Mobilityof capital and labor is constrained to
reflect the institutional realities of factor markets in
developingcountries, but economic agents are motivatedto searchfor the optimalsectoraland spatialuse of
resources.
Themodel has eight sectors (table3-1). Tradablesand
nontradables-the latter include various locationspecificservices-are distinguished.This is not the first
multisectoral model to recognizenontradables,but it is
the first spatialdevelopmentmodel to stress the importance of nontradablesas an influenceon spatialcost-oflivingdifferentials,on migration behavior,and thus on
the rate of urban growth.
The model is savings-driven,and the aggregatesavings pool is generatedendogenouslyfromthree sources:
retained after-taxcorporate and enterprise profits, government savings, and household savings.This savings
pool is allocated competitively and endogenouslyto
three uses: investment in physical capital (productive
investment), investment in human capital (training),
and investment in housing (unproductiveinvestment).
It should be emphasizedthat these three modesof accumulation are competitiveandare determinedendogenously;that is, investmentin skills (training)takesplace
up to the point at which rates of return are equated to
the economywiderate on physicalcapitalaccumulation.
Physical capital goods are allocated across the three
capital-usingsectors so as to minimize differentialsin
after-tax rates of return. Dwellinginvestment utilizes
householdsavingsonly up to the point at whichrates of
return equal the economywiderate on physicalcapital
accumulation. Of course, there are institutional and
technologicalfeatureswhich seriouslyrestrict the ability of the economy to equate rates of return at the
margin.Anyof the three dwellingmarkets (rural, urban
squatter settlements,and formalurban housing) maybe
starved for funds, since the absenceof an intersectoral
mortgage market may leave housing investment requirements in excessdemand.The immobilityof sectorspecificcapitalstocksmakesit likelythat current investment allocations are insufficient to equalize sectoral
rates of return. Indeed,the larger are housing requirements, the smaller is the residual pool availablefor
physicalcapital accumulation and the more likely it is
that current investment allocations are insufficientto
equalize sectoral rates of return. Furthermore, firms'
demandsfor skillsmayremain unsatisfiedifthe stockof
Table 3-1. Sector Characteristicsof the Kelley-WilliamsonModel
c,,
Determination
of market price
Location
U.N.ISIC
counterpart
Manufacturingand
mining (M)
Urban
Manufacturing,mining
Exogenous
Modemcapitalintensive services
(KS)
Urban
Endogenous
Informalurban services (US)
Low-quality(squatter)
urban housing
services(H, US)
High-qualityurban
housing services
(H, KS)
Agriculture(A)
Urban
Electricity,water, and
gas, banking, public
administration,trade,
commerce, construction
Personal services,some
trade and commerce
Dwellings(rent and imputed ownership)
Informalrural services
(RS)
Rural housing services
(H, RS)
Rural
Sector
Urban
Urban
Dwellings(rent and imputed ownership)
Rural
Agriculture, livestock,
forestry, fishing,
hunting
Personal services,some
trade and commerce
Dwellings(rent and imputed ownership)
Rural
(1980,1982,1984b).
Sources: Kelleyand Williamson
Tradability
characteristics
Primary
Productioninputs
Intermediate
Production
fimction form
Traded intemationally and interregionally
Traded interregionally
Capital, skills,
labor
NestedCES, constant
Imported raw matereturns
rials and fuels,A,KS
Capital, skills,
labor
Imported raw materials and fuels,A,M
Nested CES, constant
returns
Endogenous
Not traded
Labor
None
Endogenous,
owner-occupier
shadowprice
Endogenous,
owner-occupier
shadowprice
Exogenous
Not traded
Dwellings,land None
Cobb-Douglasdiminishing returns
Cobb-Douglasconstant returns
Not traded
Dwellings,land None
Traded intemationally and interregionally
Not traded
Capital, land,
labor
Labor
Imported raw materials and fuels,M,
KS
None
Not traded
Dwellings
None
Endogenous
Endogenous,
owner-occupier
shadowprice
Cobb-Douglasconstant retums
Cobb-Douglasconstant retums
Cobb-Douglasdiminishing returns
Leontieff
World?
WhatDrivesCity Growthin theDeveloping
potential trainablesis insufficientto meet desiredlevels
of investment in training. In short, capital market disequilibriummaywell be a chronicattribute of the economy.
Finally,some exogenousvariablesthat help drive the
alleged
arever
economyover time
inlueced city
ity
lleed tto have
hae influenced
econmy
imeare
growth.Thesevariablesare the nominalvalueof foreign
capitaland aid (F) availableeachyear to helpfinancethe
developmenteffort and forestall balance of payments
problems; the total unskilled labor force (L), which is
determined by earlier demographicevents; the sectoral
rates of change in total factor productivity,whichfavor
modern sectors and are labor saving;prices of imported
raw materials and fuels (Pz), which are influencedby
actions of OPEC and by other world market conditions;
and the terms of trade betweenprimaryexportables(PA)
and manufacturedimportables(PM),which are twisted
Political economyof
by domesticprice ipolante
protectionist or liberalizationwinds in the industrial
nations.
nations.
permit generalizationabouturbanizationinthe
To permit generalizationabout urbanization in the
developingworld, the representativedevelopingeconomy (RDE) has been employedas the data base on which
the model is estimated and validated.The RDE is a fictional economythat embodiesthe experienceof developing economieson three continents since 1960.Three
criteria were used to select the RDEgroup:availabilityof
data beginningin the early 1960s,low per capitaincome
but somesuccessfulgrowth,and closeconformityto the
model's most important assumptions.(The last-named
criterion impliedthe rejectionof economieswhichhave
been heavilydependenton foreign capitaland on minital
whinbeeralhexports
suchpasnuel) T fore eondoms
eral exports such as fuel.) The forty economieswhich
met the criteria' seem to exhibit the same averageattnbutes as the far larger group analyzedby Chenery and
Syrquin (1975). The RdE group contains eleven of the
world'stwelve largest developingeconomiesand covers
more than 80 percent of the populationof the develop-
35
MacroeconomicIndicators
AggregateGrowth.As set out in table 3-2, the model
generatesan annual averagegrowthrate of grossdomestic product (GDP)in constant prices of 6.26 percent for
GDPper
workeraverages
rateoftrend
andthe
1960-73,
is inacceleration
3.58
percent.
A growth
significant
an acceleratiof 5s92
A gnifrom
dicated;
percent in 1960-65 to 6.60 percent in 1968-73. That
the at
to 6.60
cento
prentins
these predictions conform fairly closely to the actual
pre-oPEchistory of the RDEgroup helps to establishthe
model's plausibilityat the most aggregatelevel.
Unbalanced Growth and Industrialization. The
model alsoreplicatesthe RDEhistory of industrialization
dustheliaton
in
modeclselicateseen
quite closely,as can be seen in table 3-3. The M-goods
sector underwent relatively rapid growth, from 15.9
percent of GDPat factor cost (current prices) in 1960to
20.8 in 1973; the model generates almost identical
trends. The service sector underwent a more modest
rise, from 47.5 to 50.6 percent of GDPat factor cost, and
the modelcaptures these trends too. Therapid declinein
the relative importance of agriculture-from 36.6 to
28.6 percent-is also fithfully replicatedin the simulation. It is satisfyingthat the model so closelyreplicates
that the unbalanced rowtes
tiontitative
the quantitative record of the unbalanced growth of
sectoral output.
InvestmentAllocatsonand Sourcesof inance. Gross
domesticinvestment as a share in GDP increasedmarkedly between 1960and 1973,from 15.59to 19.46percent (Kelleyand Williamson1984b,table 3.10, p. 89).
Total investmentshares, includinginvestment in training, also drift upwardin the model,a predictionwhich
conventional national accounts cannot document.
Althoughthe aggregateinvestmentshare increasedover
the period, the model suggests that the distributionof
investment was remarkablystable. Investment allocation by sector and type is poorly documentedfor the
period, but the model predicts that the dispre-OPEC
tribution of investment by sector and type must have
been quite stable over the thirteen years. Thesources of
Predicting the Past
Table 3-2. Annual Average GrowthRate, 1960-73
Of the about one hundred endogenous variables
generated by the model, three-urbanization, city
growth, and rural-urban migration-form
(percent)
GDP
this chapter. The illustrations below show how the
model replicatespast trends forthese and other selected
variables, both to throw light on past trends and to
validate the use of the model for making predictions.
Much of the initial discussionfocuseson 1960-73, but
the late 1970s are also discussed.
GDPper worker
prices)
(constantprices) (constant
the core of
Model
Actual
Model
Actual
1960-65 5.92
1968-73 6.60
1960-73 6.26
5.78
6.12
5.80
3.19
3.98
3.58
3.24
3.58
3.26
Period
Source: Kelleyand Williamson(1984b),table 3.5, p. 84.
36
AllenC. KelleyandJeffreyG. Williamson
Table 3-3. Output Mix, 1960-73
(percent of CDP)
1960
1970
1973
Model
Actual
Model
Actual
Model
Actual
Agriculture(A)
Manufacturingand mining (M)
36.6
15.9
36.6
15.9
30.4
19.3
30.9
19.2
28.2
20.9
28.6
20.8
Moderncapital-intensive
services(KS)
Informalurbanservices(US)
Informalruralservices(RS)
Housing,all sectors(H)
29.6
6.2
3.2
8.5
29.6
6.2
3.2
8.5
30.4
6.9
3.1
9.9
n.a.
n.a.
n.a.
n.a.
30.8
7.2
2.8
10.1
n.a.
n.a.
n.a.
n.a.
Allservicescombined (KS + US + RS + H)
47.5
47.5
50.3
49.9
50.9
50.6
Sector
n.a. Notavailable.
Source: Kelleyand Williamson(1984b),table 3.7, p. 86.
saving,however,did not showthe same stability(Kelley
and Williamson1984b,table 3.10, p. 89).2The share of
gross domestic investment financed by public saving
rose to 34 percent. The model predictsa comparablerise
to 33.7 percent, with both shares rising by about 5
percentagepoints. The fallin the privateshare of finance
was attributable not so much to lagginghouseholdsaving as to a declinein the share of gross corporatesaving
in gross domesticinvestment,from 31.7to 26.6percent.
UrbanIndicators
Migration, Urbanization, and City Growth. Table
3-4 documents four key aspectsof urban development:
the share of the population that is urban, city growth
rates, net rural out-migration rates, and net urban inmigration rates. The rise in urban shares providessome
evidenceof acceleratingrates of urbanizationand conforms to the pre-inflection-pointphase along logistic
urbanization curvesthat is commonlyfound in develop-
IncomelInequalityand WagePatterns. Sizedistributions forthe model and for an averageof eighteen ofthe
Kelleyand
aredaa
givenin
RoE forwhich dataexist
inKeley
ndWilliamillamRDE
eistaregive
or hic
son (1984b, table 3.12, p. 91). In spite of well-known
limitations,the top 5 percent and the bottom 20 percent
shares of national income exhibitsome striking trends.
Contraryto conventionalwisdom,an unambiguousrise
in inequalityis not confirmed.The bottom 20 percent
sufferedan erosion in income shares during the period,
but the top 5 percent underwentan evenmore dramatic
erosion. Clearly, the middle classes flourished at the
expense of both the very rich and the very poor. Those
are exactlythe conditions under which Lorenz curves
ing-countrytime series (Preston 1979;Ledent 1980).In
the first fiveyearsof the simulation (1960-65)urbanizain the
levels
rise(1968-73)
by 3.18 percentage
tion
by 5.38while
percentage
last five
years
they risepoints,
cont
by 5.38
las.
Similars city growthes rise
intersect. Inequality inferences are then impossible unless value weights are imposed on social classes. The
model exhibits the same behavior: a 3.1 percent fall in
the share in national income of the top 5 percent is
predicted, compared with the RDEhistory of a fall of 2.6
percent. Similarly, while the bottom 20 percent found
its share declining by 0.3 percent, the model predicts a
fall of 0.2 percent. The group in the 60-90 percent range
increased its share by 3.7 percent, which implies that the
source of the inequality lies with increased inequality of
earnings. Those in the 60-90 percent range in the model
are urban skilled and unskilled in the formal sectors. In
short, the model generates wage inequality and skill
scarcity.
Table3-4. Migration, Urbanization,
and City Growth, 1960-73, ModelPredictions
Year
1960
1961
1962
1963
1964
1965
1966
1967
1969
1970
1971
1972
1973
-Not
Percent
urban
City
growth rate
32.60
33.55
34.30
34.73
35.25
35.78
36.49
37.23
38.95
39.93
40.96
42.15
43.45
5.56
4.87
3.85
4.13
4.11
4.60
4.61
4.91
5.15
5.22
5.56
5.72
-
Net rural
out-migration
rate
-
1.41
1.13
0.65
0.81
0.82
1.10
1.16
1.425
1.60
1.71
2.02
2.21
Net urban
in-migration
rate
-
2.91
2.24
1.25
1.51
1.50
1.98
2.01
2.3217
2.51
2.58
2.91
3.07
applicable.
Source: Kelley and Williamson (1984b), table 3.13, p. 93.
WhatDrivesCityGrowthin theDeveloping
World?
37
forming to the trends reported in the World Tables 1976
(World Bank 1976, table 2, "Social Indicators") between
1960 and 1970. Rural-urban migration rates also rise.
Table 3-5 presents model predictions and actual experience. City growth rates in the RDE group were 4.60
percent a year during the 1960s; the model predicts a
rate of 4.67 percent. The model predicts a rural outmigration rate of about 1.1 percent a year, and the
historical rate ranged between 1 and 1.2 percent; the
predicted urban in-migration rate is 2.1 percent a year,
and the historical rate ranged between 1.8 and 2.3 percent. Finally, 45 percent of the increase in city population is accounted for by in-migration in the model; this
figure falls between Preston's (1979) estimate of 39 percent (based on twenty-nine developing countries) and
Keyfitz's regional estimate of 49 percent (1980, p. 151).
It is also close to the 42 percent figure for developing
countries reported by Linn for 1970-75 (1979, p. 73).
Table 3-6. Urban Land Use, Density, and Land
Scarcity, Model Predictions, 1960, 1970, and 1973
Variable
1960
1970
1973
Urban Land Use, Density, and Land Scarcity. Table
3.6 reportsofindicators
urban lad ue an.
3-6 shareportsindicato
of urbandevot
land
qustera scity
struction in the long run can inflate the cost of city life,
as summarized in table 3-7. Excess housing demand
arises because capital market segmentation excludes
rises sharply (Mohan 1979; Beier and others 1975).
Competition for land use generates sharply rising land
scarcity; the shadow site rent on urban land almost
doubles between 1960 and 1970 and in 1973 reaches a
level about 2.3 times that of 1960. Urban land values
(deflated by the general price level) surge; the index rises
from a base of 100 in 1960 to 195.2 in 1970 and 239 7 in
from aTbaseofe100 in1960nto195.2aind1970uan 239.7 in
1973. These tn
i urbantlan
uly
a raid
mtersectoral (mortgage) loans forhousing Investment,
and each socioeconomic class must rely on its own
internally generated saving to meet housing investment.
Table 3-7 reports that the saving constraint is never
binding for rural households or for skilled workers and
higher-income households, but for squatter settlements-the
faster growing sector-the saving constraint is bindingvery early in the period and thus excess
short-run demand for new low-quality dwelling units is
which were singled out at the U.N. Habitat Conference
in 1976 (United Nations 1976). Urban densities rise
everywhere in the model, but they rise most dramatically in "luxury" housing, where the relative scarcity of
land compared with structures rises most sharply, encouraging land saving and greater density.
generated. Excess demand and mcreasmg urban land
scarcity ensure a rapid upward drift in (shadow) rents in
The share of urban land devotedto squattersettlements
annual growth of 7 percent-exactly the sharp rises
Share of urban land in squatter
- settlements (percent)
,rban land density(persons . area)
High-qualityhousing areas
Squatter settlements
Shadowsite rent on urban land
(1960 = 100)
Shadowprice on urban land
(1960 = 100)
(percent)
_________________________________________
Variable
Annual city growth (compounded)
Total increase in urban share of
population
Annual increase in urban share of
population
Net in-migrant share of increase in
urban population
Net in-migration rate
Net out-migration
rate
Predicted
Actual
4.67
4.60
7.33
5.30
0.73
45.0
0.53
39.3-49.0
2.09
1.81-2.26
1.10
0.97-1.21
Source: Kelley and Williamson (1984b), table 3.13, p. 93.
52.2
53.9
100.0 152.0 172.7
100.0 121.4 141.7
100.0 183.3 233.3
100.0 195.2 239.7
Source: Kelley and Williamson (1984b), table 3.14, p. 95.
Housing Scarcity and Gost-of-Living Differentials. In
addition to land scarcity, excess demand for housing
units in the short run and rising costs of housing con-
itretrl(otae
gnrtd
on
xesdmn
o osn
n
netet
nraigubnln
Table 3-7. Housing Scarcity and Cost-of-Living
Differentials, Model Predictions, 1960, 1970,
and 1973
Variable
Table 3-5. Predicted and Actual Migration,
Urbanization, and City Growth, Averages, 1960-70
43.0
1960
1970
1973
Excesshousing investment
Urbanhigh-qualityhousing
-3.77
-2.55
-2.67
Urban squatter settlements
Rural housing
-0.02
-0.29
0.37
-0.58
0.28
-0.88
1.00
1.00
1.00
1.00
1.35
1.46
1.00
Housing rent index
Urban high-quality housing
Urban squatter settlements
Rural housing
Urban squatter . rural
Cost-of-living index
Urban
rural
1.72
1.90
1.38
1.25
1.45
1.31
1.09
1.12
a. [Desired housing investment demand - household saving] desired housing investment demand.
Source: Kelley and Williamson (1984b), table 3.15, p. 96.-
38
Allen C. Kelleyand JeffreyG. Williamson
urban squatter settlements, and the cost-of-livingdifferential rises as a result.
Understanding City Growth:
Some Major Influences
Which exogenousvariableshavehad the greatest impact on city growth in developingcountries?Whichare
least likely to account for future growth? Answersto
these questions can be dividedinto three parts: the size
of the past and future changes in the exogenousvariable
thought to influenceendogenous rates of city growth;
the short-run comparativestatic impact of that exogenous variable;and the long-run forcesset in motion by
the short-run comparativestatic impact. This section
focuseson short-run comparativestatic elasticitiesand
exploresthe impactof some keymacroeconomicevents
on urban growth: unbalanced productivity advance,
world market conditions and price policy, accumulation, demographicchange, and land scarcity.
Each of these short-run elasticitiesreflects the full
generalequilibrium impactof the exogenousvariablein
question, basedon the initial conditionsin 1970.Labor
marketsadjust through migration,and urban land markets seek an optimal land use solution, but capital markets are severelyconstrained in the short-run analysis:
old capital cannot migrate, and new capital goods and
newlytrained skilledworkers are not addedto capacity.
Investmentresponsesare also ignored in the short-run
analysis: recent historical experiencewith sectoral investment allocation is assumedto guide entrepreneurs
who are slow to adjust to the new, unexpected,and
shock-distortedrates of retum.
UnbalancedProductivity Advance
If output demandis relativelyprice inelastic,sectoral
total factor productivitygrowth (TFPG) for a sector tends
to generatea relativepricedeclinerather than an elastic
supplyresponse. Thus,the rise in the marginal physical
productivityof factorsused in a technologicallydynamic
sector will be partially offsetby the decline in price, so
that marginal value products rise by less, and shifts of
resources, including labor, to the technologicallydynamic sector are minimized.If, on average,urban sectors tend to haverelativelyhigh rates of TFPG, and ifthe
demand for urban output is price elastic, final demand
shifts toward the dynamic urban sectors, the derived
demand for urban employmentis augmented, and the
city grows. The higher are price elasticitiesof demand
for urban output, the greater is the city growthattributable to unbalancedproductivityadvancethat favorsthe
modem sectors.
In table 3-8 disembodiedTFPG (the Ajs, in rates of
change)in agriculture and manufacturingexerta much
greater impact on urbanization than do productivity
improvementsin the servicesectors. The pricevariables
PA and Pmare exogenouslydetermined and are fixedby
invokingthe small-countrycase of infiniteprice elasticity. Servicesare nontradableswith price elasticitiesof
demand sufficientlylow that the productivity-induced
declines in servicesector prices (PKs,PUS,and PRS,in
response to AKS, Aus, and ARS, respectively)implystable marginalvalue productsand trivial employmentand
city growth effects. Although productivityadvance in
manufacturing is an important potential determinantof
urbanization, rapid productivityadvancein agriculture
tends to forestallout-migrationto the city.This result is
in contrast to the closeddual economymodel in which
productivityadvancein agriculture meets with demand
absorption problems,decliningfarmterms of trade,and
thus a labor surplus which out-migrates to glut urban
labor markets.
Unbalancedrates ofTFPG that favormanufacturingare
likely to have been a key determinant of rapid inmigrationand city growth since the late 1950s.Not only
are the comparativestatic elasticitiesin table3-8 consistent with that position, but limited evidencesuggests
that annual rates of TFPG in manufacturing have been
relatively high in most successful developing economies.
Although technologicaladvancetends to be lower in
the service sectors, especiallyin the informal service
sectors, table 3-8 suggests that rapid TFPG in those sectors has had little impacton urbanizationexperiencefor
the demand elasticityreasons already offered.If rapid
TFPG matters little to urbanization even in the modem
capital-intensiveand skill-intensiveKS sector, lagging
productivityadvancein the service sectors would also
matter little. It is believedthat urban social overheadis
crucialto the profitabilityandviabilityof urban firms.In
our model, KSactivitiessuch as transport, communications, and electricityhavethat role. Table3-8 confirms
that productivity advance augments KS services supplied in short-run equilibrium (QKs), but because
almost all of these productivitygains are passed on to
users elsewherein the economy (PKSdeclines),employment in KS itself changes little. Final-demandcustomers of KSservices,whotend to be the urban rich, gain.A
major user of KS services as intermediate inputs is
manufacturing, and employment rises there. The net
effecton urbanization is, however, indirect and small.
Short-RunConstraintson City Growth
Productivityadvancesthat favormodern sectors foster urbanization, but in the short run the city growth
World?
WhatDrivesCityGrowthin theDeveloping
39
Table3-8. ComparativeStatic Impacts of UnbalancedProductivityAdvance
on City Growth in DevelopingCountries (1970 Elasticities)
Endogenous variable
City growth attributes
Percent urban
City growth rate
In-migration rate
Squatter house rents
Cost-of-livingdifferential
(urban + rural)
Tradable
commodities
Nontradableservices
AM
AA
AKS
0.50
10.29
20.57
3.57
- 0.26
-5.33
-10.65
-0.73
0.03 -0.01
0.68 -0.26
1.36 -0.52
0.40
0
1.49
-0.80
0.12 -0.11
AUs
ARS
- 0.03
- 0.67
-1.33
-0.14
0.01
Selectedeconomywideattributes
PKS
PUs
0.82
0.22
PRS
1.03
0.02
0.24
1.17
QM
2.34
QKS
0.02
0.23
-0.34
-0.11
1.36
-0.18
0.24
- 0.37
-0.11
Qus
QA
QRS
LM
LKS
Lus
LA
LRS
-0.57
0.17
0
1.31
-0.91
0.03
0.15 -1.09
0.09 -0.01
0
0
-1.03
0.24
0.08
0.99
0.02
0.07
0.01
0
0.75 -0.01
0
0.07
-0.09
0
0.60
-0.84
0.10
0.18
0.15 -0.07
0.11
0
0.02 - 0.26
0.15 -0.02
0.01
-0.09
0
-0.01
0.08
0.32
0.34
-0.01
-0.01
0
- 0.41
Source:KelleyandWilliamson
(1984b),table4.1,p. 103.
Note: Variablesare definedas follows:AM,
total factorproductivitygrowthin the manufacturingsector;AA,total factorproductivitygrowthin the
agriculturalsector;AKs,total factorproductivitygrowth in the modern servicessector;AUS,total factorproductivitygrowthin the informalurban
servicessector;ARs,total factorproductivitygrowthin the informalruralservicessector;PKS,priceper unit ofmodemservices;Pus,priceper unit of
informalurban services;PRS,priceper unit of informalruralservices;QM,output in the manufacturingsector;QKS,output in the modernservices
sector;Qus,output in the informalurban servicessector;QA,outputin the agriculturalsector;QRS,outputin the informalrural servicessector;LM,
unskilledlabor in the manufacturingsector;LKS,unskilledlaborin the modem servicessector;Lus, unskilledlabor in the informalurban services
sector; LA,unskilledlabor in the agricultural sector; LRS, unskilledlabor in the informalrural servicessector.
responseis constrained, partlyby problemswith absorption of output, partly by short-run capacityconstraints
and skill bottlenecks,and partly by a rising supplyprice
of unskilled labor in the cities. Table 3-9 focuses
on the rising supply price of urban labor. Urban job
creation fosters in-migration,but with some limitation.
Although land use shifts to squatter settlements to
accommodaterising density, urban rents nevertheless
rise steeplyin the face of the migrant influx.Since most
new in-migrantsare unskilledand poor, rents in squatter settlements rise more sharply than do rents for
high-qualityhousing. Squatter-settlementrents reflect
excessdemandfor housingand sites; the rents for highquality housingmostly reflectincreasedland scarcityas
the needs of the poor are partially accommodatedby
shifting land use. The cost-of-livingadvantage of the
rural area rises sharply as a result of increasedurban
rents. Allthese factors raise the averageunskilledwage
in the cities and tend to restrict city growthin the short
run. Furthermore, job creation is constrainedby skill
bottlenecks (the skilledwage rises) and capital scarcity
(the return to capitalin manufacturingrises faraboveits
return in other uses), which suggeststhat the long-run
impact of unbalanced productivity advance on city
growth is far greater than these short-run elasticities
imply.
Scarcitiesof Fuel and Imported Raw Materials
Since urban-based manufacturing uses intensively
fuels and raw materials (importableswhich we call Zgoods), any increase in the price of imported Z-goods
penalizesmanufacturingdirectlyand other urban activities indirectlyand thus inhibits urban job creation and
citygrowth. Eventhough the modeladmitsthe possibility of direct and indirect substitution away from the
more expensiveimportedfuelsand raw materials, table
3-10 reports that in-migrationand city growth are still
constrained because urban activities tend to be Zintensive.The elasticityofPz,however,is low compared
40
Allen C. Kelley and Jeffrey C. Williamson
Table 3-9. Short-Run Constraintson the City
Growth Response to UnbalancedProductivity
Advance (1970 Elasticities)
Endogenous
variable
AM
AKS
City growth attributes
Citygrowthrate
10.29 0.68
Congestionindicators
Percenturbanlandin squattersettlements
1.25 0.13
Squatter house rents
3.57
1.16
High-quality house rents
Cost-of-living
differential
s (rural
urban)
0.40
0.15
1.49 0.12
Factormarket disequilibriumindicators
Averageurbanunskilledwage
Ruralunskilledwage
Urbanskilledwage
Returnto capitalin M
Returnto capitalin KS
Returnto capitalin A
1.03
0.02
1.28
2.34
0.80
- 0.30
0.15
0.09
0.13
0.27
0.07
0.06
"unproductive" capital accumulation on employment
demand,urban job creation,and city growth.Accumulation in the urban modem sectors fosters job creation,
and an investmentpolicywhichfavorsmanufacturingat
the expense of agriculture fosters urbanization. It is
surprising,however,that accumulation of urban squatter housing (Hus)has the most potent short-run impact
on urban job creation and city growth. This result
occurs even though the impact multipliers excludethe
employment effects of the formation of the housing
stocks through investment (and investment activities in
squatter
construction
are highly
laborintensive).dwelling
The relatively
large urban
employment
effects associated with the accumulation of squatter
housing are therefore all indirect: housing rents de-
Table 3-10. Factors That Influence City Growth
in DevelopingCountries (1970 Elasticities)
Source:Kelleyand Williamson
(1984b),table4.2,p. 105.
Endogenous
urbanization
variable
with the unbalanced productivity advance indicators
(the Ajs) or with the other two exogenous prices reported in table 3-10.Atfirst glancethis maysuggestthat
the sensitivityof urbanization to scarcity of fuels and
Exogenousvariable
Land and labor
raw materials has been overstated in the literature. In
L
Accumulation
KM
view of the historical record since 1960,however, one
must be cautious.Afterall, Pz soaredin the 1970safter
its recorded stability during the 1960s. Thus, Pz may
have been a dominant source of developing-country
urbanization over the past two decadesin spite of the
modest elasticitiesreported in table 3-10. (The issue is
discussedagain below.)
Percent CitygrowthIn-migration
urban
rate
rate
-0.03
0.04
- 0.69
0.88
-1.38
1.77
-0.57
6.38
12.75
0.09
1.82
3.63
0.02
0.40
-0.03
0.39
-0.13
-0.68
0.07
7.92
-2.75
-1.35
0.15
15.83
-5.50
PZ
PM
-0.04
-0.89
-1.77
PA
- 0.32
-6.51
-13.01
RA
Ru
KKS
KA
HKS
HuS
HRS
0
0.81
Prices
Price Policy and World Market Conditions
Table3-10 presents the short-run impact multipliers
for prices of agriculturaland manufacturedgoods,both
0.54
of which compete in world markets. These prices are
Productivityadvance
AM
usuallyheavilydistorted by external and internal price
policy. The table shows that city growth was far more
AA
AKS
sensitive to PA and PM than to Pz. Any effort to under-
Aus
0.50
- 0.26
0.03
- 0.01
stand the sources of past and future city growth must
therefore carefullysort out these relative price conditions, including the impact of past liberalizationand
future protectionist trends in the industrial countries
ARS
and the influence of price-distorting policy regimes in
developing countries.
developing
countries,
Accumulation, Capacity, and Job Creation
Table 3-10 also summarizes the impacts of "productive" capital accumulation and population-sensitive
11.13
10.29
22.23
0.68
- 0.26
20.57
- 10.65
1.36
- 0.52
- 0.03
- 0.67
-1.33
0.23
6.96
-5.33
Other
Skilledlaborforce (S)
Foreigncapital(F)
13.90
0
- 0.03
- 0.06
Note: Variables,
in additionto thosedefinedin table3-8, are as
follows:RA,agriculturalland stock;Ru, urban landstock;L, total
unskilledlaborforce;KM,physical
(productive)
capitalinthe manufacturingsector;KKS,physicalcapitalin the modemservicessector;KA,
physicalcapitalin the agriculturalsector;HKs,high-quality
urban
housing; Hus, low-quality(squatter)urban housing;HRs, rural
housing;Pz, priceper unit of importedrawmaterials;PM,priceper
unit of manufactured
goods;PA,priceperunit ofagricultural
goods.
Source: Kelleyand Williamson
(1984b),table4.6, p. 111.
WhatDrves City Growthin the DevelopingWorld?
41
crease with the augmentedsupplyof dwellingspace,the
relative costof livingin the cities declines,in-migration
is fostered, nominal wages of the unskilled are lowered
by the temporary labor glut, and employmentexpands
everywherein the city as a result, especiallyin manufacturing. In contrast to Coaleand Hoover's(1958)emphasis on the tension betweenunproductiveand productive
capital accumulationin city growth,table 3-10suggests
no conflict:of the sixalternativemodesof accumulation
Table 3-11. The GrowthEnvironment, Pre-OPEC
and Post-OPEC:Dynamic ParametersAssumed
in the Sinulations
listed, accumulation in HUS has the highest urban job
Price of M-goods(PM)
creationand city growtheffects.Anissuefor futurework
is to assesswhether this conclusionholdsfor the longer
run.
Agricultural
landstock(RA)
Urbanlandstock(Ru)
Totallaborforce(L *S
(percent)
Exogenous variable
(dynamicparameter)
Priceof importedrawmaterials(Pz)
Averageannualgrowth
Pre-OPEC Post-OPEC
(1960-73) (1973-79)
0
5.2
-0.7
- 1.6
1.0
1.0
2.54
0.5
1.0
2.68
Source: Kelleyand Williamson(1984b),table 5.1, p. 126.
Land and Labor
Popular accounts of rapid urbanizationin developing
countries emphasizethe roleof high populationgrowth.
Table 3-10 contradicts this view, although how wrong
the population account is dependson which aspect of
urbanization and city growth is of interest.
Lewis (1977) has stressed the capital intensity of
cities, and the present modelconformswith that reality,
since urban activities are, on average, far less laborintensive than are rural activities. The Rybczynski
theorem in trade theory holds that an increasedendowment of any given factor of production should favorthe
expansion of those sectors which use that factor most
intensively. Thus, whatever its source, populationinduced labor force growthshould foster the expansion
of rural activitiesand suppressurbanization.According
to this analysis, population growth does not offer an
explanationfor urbanization, and the negative impact
multiplier in table 3-10 (percent urban, - 0.57)proves
the point. For in-imigration and city growth, however,
table 3-10 reports a more conventionalresult, since the
impact multipliers are positive and quite large. (The
next section elaborates on this issue.)
What about land endowments?Conventionalwisdom
has argued that scarcityof agriculturalland has tended
to push labor into the cities. Although an extensionof
the arable landstock wouldcertainlyincreasethe retention of labor in rural areas and thus retard urbanization,
the size of the impact reported in table 3-10 is small.
Changesin agriculturalland endowmentare simplynot
an important part of the city growth tale.
The OPEC Watershed and Recent
Growth Trends
The changing growth environment in the aftermath
of the OPECprice shock has been significant.It has been
manifestedmainly in relativeprices,whichare captured
in the modelbyexogenoustrends in PA,PM,andPz (table
3-11). In relation to prices of primary exports from
developing countries, the quality-adjusted price of
manufactured goods declined at an annual rate of 0.7
percent up to 1973.Therate of declineacceleratedafter
1973 and averaged1.6 percent a year to 1979.In contrast, the price of imported raw materials (including
fuels) rose by 5.2 percent a year after 1973 compared
with PA;the same relativeprice exhibitedlong-run stability before 1973. Although these price trends are
affectedby the base periodsselected, the averagingdevices applied,and the underlyingprice series,there can
be no doubtabout the epochalcharacterof the post-OPEc
price trends which developingcountries faced in the
1970s.
Astable 3-11shows,the growth rate of the laborforce
was higher after 1973,although the accelerationwas
quite modest. Table3-11 also documents the assumed
rates of farmlandgrowth,showinga declinewhich captures the apparent rapid exhaustion of possibilitiesfor
augmenting extramarginal land. Clearly, there were
other (perhapsless important) nonprice changesin the
economic and demographic environment that surrounded the RDEgroup after 1973.For that matter, not
all of the epochal price trends were related to OPEC.
Nonetheless,we havelabeledthese two epochspre-oPEc
and post-oPEc.
Evaluatng the OPECWatershed
The world economy has been undergoing painful
adjustments to the price shocks associatedwith shortrun OPECpolicyand long-runscarcitiesof raw materials
and fuels. Since as late as 1979the world economywas
still digesting the impact of these disequilibrating
shocks, it seems clear that a long-run general equilibrium model such as ours cannot be expectedto account
42
Allen C. Kelley and Jeffrey G. Williamson
tions by the model in table 3-13 might suggest that the
OPECprice shocks mattered little to subsequent urban
performance in the late 1970s. The annual rate of city
growth declines only modestly over the period as a whole
(from 4.86 to 4.65 percent); the percent urban continues
its rapid climb; and in-migration rates, although somewhat lower, remain high. Note, however, the unambiguous evidence of retardation in the Actual columns of
table 3-12, in which the rates of in-migration and city
growth lose their steam quite dramatically. More important, in table 3-13 compare the predicted actual postOPEc experience with the counterfactual 1973-79 experience that assumes pre-OPECenvironmental conditions:
while the actual city growth rate for 1973-79 is 4.65
percent a year, the counterfactual rate would have been
6.04 percent. Furthermore, without the shocks of the
late 1970s, the counterfactual rate of in-migration
adequately for the short-run trends that developing
countries have undergone since 1979. Nonetheless we
can use the post-oPEc conditions to illustrate the model's sensitivity to such epochal shocks.
Tables 3-12 and 3-13 summarize the city growth predictions. Table 3-13 offers a 1960-73 prediction, using
the actual pre-OPECeconomic and demographic environment, that has already been compared with actual experience in previous sections; a 1973-79 prediction using the actual post-OPEc economic and demographic
environment documented in table 3-11; and a counterfactual post-OPEC prediction, which simply allows the
pre-OPECenvironmental conditions to continue beyond
1973. The counterfactual experiment makes it possible
to assess what urbanization would have been like without the post-OPEC epochal shocks.
Comparison of the pre-1973 and post-1973 predic-
Table 3-12. Post-OPEC Urban Adjustnents, Model Predictions, 1973-79
Counterfactualenvironment
Actual post-OPECenvironment
Year
Percent
urban
City
growth
Net urban
in-migration
rate
Percent
urban
City
growth
Net urban
in-migration
rate
1973
43.45
5.72
3.07
43.45
5.72
3.07
44.78
5.75
3.10
1974
44.45
5.10
2.32
1975
1976
1977
45.22
46.26
47.05
4.48
5.03
4.52
1.72
2.26
1.76
46.25
47.80
49.46
5.92
6.03
6.14
3.27
3.38
3.47
1978
47.85
4.47
1.71
51.22
6.23
3.56
1979
48.58
4.29
1.53
53.03
6.16
3.49
Note: The counterfactualresults assumethat the 1960-73dynamicparameterspersist after 1973.Thenet urbanin-migrationrate is the ratio of
annual in-migrationto the averageurban population in all previousyears.
Source: Kelleyand Williamson(1984b),table 5.3, pp. 130-31.
Table 3-13. Pre-OPEC and Post-OPEC Urban Adjustments,
Model Predictions, Period Averages
(percent)
Basis for prediction
Variable
Annual city growth
Total increase in share urban for period
Annual increase in share urban
Net in-migration share of urban
population increase
Net in-migration rate
Net out-migration rate
Actual
pre-OPEC
environment,
1960-73
Actual
post-OPEC Counterfactual
environment, environment,
1973-79
1973-79
4.86
10.85
0.83
4.65
5.13
0.86
6.04
9.58
1.60
47.72
2.35
1.37
41.34
1.83
1.60
57.50
3.30
3.13
Note: The 1973-79counterfactualresultsassumethat the 1960-73dynamicparameterspersistafter 1973.Thenet in-migrationrate is the ratio of
annualin-migrationto the averageurban populationin allpreviousyears.Thenet out-migrationrate isthe ratio of annualrural out-migrationto the
averagerural population in all previousyears.
Source: Kelleyand Williamson(1984b),table 5.3, pp. 130-31.
WhatDrives City Crowthin the DevelopingWorld?
wouldhave risen to 3.30 percent rather than fallto 1.83
percent, as in fact happened.
in City Growth
It seems clear that exogenouseconomicand demographic conditions had a powerfulimpact on developing-country urbanizationduring the 1970s.Table3-14
reports an effort to isolate the most important factors.
Nine counterfactualstimulationsare used. Each generates a history in the 1970s (1973-79), but the table
presents only one of the model's predictions-the
annual rate of city growth. Each counterfactual case
should be compared with the actual 1973-79 performance reproduced in column 1 (which repeats table
3-12). The fuel abundance counterfactualin column 3
maintainsall of the exogenousconditionsthat underlie
the actual performance in column 1 except*fuelprice
behavior:while the oPEc-augmentedactual Pz was 5.2
percent a year between 1973and 1979,the counterfactual assumes that Pz = 0, as was indeedthe case up to
1973.
Theurban slowdownhad little to dowith agricultural
land expansionor labor force growth.Rather,it appears
that prices were doing most of the work. Furthermore,
fuel scarcity,in spiteof the attention it has received,was
not nearly as important a source of slowdownin city
growth as was the accelerated decline in the relative
price of manufactures(lowerPM)This findingobviously
supports the viewthat any future trend toward protectionism in industrial countries will play an important
role in shaping city growth in developingcountries in
the next two decades.Thesame mightbe said, of course,
of the mix of internal policies which may twist the
relativeprice of manufactures in the future. This position is reinforced by the counterfactual experiment
under "stable world markets," in which the relative
price of manufactures is held fixed during the 1970s.
Under these more favorableprice conditionsfor manufacturingthe model predictsannual city growth rates of
6.49 percent, in contrast to the actual rate of only 4.65
percent.
Although a sharp decline in the rate of population
growth would certainlyhavediminishedthe rate of city
growth, column 8 in table 3-14 suggests that this influencehas beengrosslyoverdrawnin the popularliterature. The counterfactualexploresthe impact of a spectacular reduction in population pressure from the actual
RDcEaraeduction8iecnt
popuartionrsuefo thee ctualic
a.
RDErate of 2.68 percent a year to the 0.9 percent which
prevailed among industrial countries. Even under this
enormous diminution in population growth, the rate of
city growth would still have reached almost 4 percent a
year for the period 1973-79. Rapid population growth
43
certainly has contributed to spectacular city growth
rates, but the experiments suggest that it is not the
central force that drives urbanization.Table 3-14 also
suggests that a shift to foreigncapital austerity would
not matter much to urbanization.
Urbanization in developing countries is, however,
sensitive to a productivityslowdown.Givena plausible
retardation in the economywiderate of TFPGfrom 1.8to
1 percent a year, city growth rates declinesignificantly,
and the impact seemsto show signs of cumulating over
time.
Conclusion
This chapter has shownthe abilityof the Kelley-Williamson model to adequately replicate growth, accumulation, distribution, and city growth in developing
countries up to the 1973watershed.On that basis it is
concluded that the model can be used to analyze the
sources of urban growth during the 1960s, the early
1970s,and the difficultperiod of structural adjustment
since then and to analyzefuture trends in urban experience undervaryingworld market conditionsand domestic policy regimes.
To summarize,rapid rates of populationgrowth are
not-as a reading of the popular literature would suggest-the central influence that drives rapid urban
growth in developingcountries. Capitaltransfersto developing countries have not played a significant part,
and rural land scarcityhas had only a modest role. The
most potent influenceson city growth appear to have
been the rate and imbalance of sectoral productivity
advances-technological eventswhich havefavoredthe
urban modern sectors-and prices (although oPEcinduced fuel scarcityhas been less important than the
relativepriceof manufactures).Thus,trade policyin the
industrialcountries andprice policyin developingcountries are likelyto have the most important impacts on
city growth in the next two decades.
Notes
1. Algeria,Bangladesh,
Brazil,Cameroon,
Chile,Colombia,
CostaRica,Coted'lvoire,Dominican
Republic,Ecuador,Arab
Republic
of Egypt,ElSalvador,
Ethiopia,TheGambia,Guatemala, Honduras, India, Indonesia, Kenya, Korea, Malaysia,
Mexico,
Morocco,
Nicaragua,
Nigeria,Pakistan,Panama,Paraguay,Peru, Philippines,Portugal,Sri Lanka,Swaziland,Syria,
Taiwan,Thailand,Togo, Turkey,Uganda,and Yugoslavia.
2. The World Bank's World Tables normally report only
total private savingsand do not separate householdsavings
from firm (corporate)reinvestment.Althoughthe distinction
Table 3-14. Sources of a Slowdown in City Growth, 1973-79
(percent)
Othercounterfactuals,1973-79
Technological
OPECwatershedcounterfactuals,1973-79
Actual
Itemn
1973-79
(1)
Fel abundance, Worldmarkets, Land expansion,
Total
pr*e-OPEC,
pre-OPEC
~~~~~~~~~~pe-PE,pre-OPEC,
peOE
pr-PCppre-OPEC,
reOE,*world
environment
Pz = 0 only
PMonly
RAonly
(2)
(3)
(4)
(5)
Population
pressure,
pre-OPEC,
Stable
markets,
L + S only
(6)
PM=
0
(7)
No population
pressure
(developed
slowdown
(decreasein
TFPGfrom
country
l.S to I
rate)
(8)
percent)
(9)
Foreign
capital
austerity,
F= 0
(10)
Year
1973
1974
1975
1976
1977
1978
1979
Average
5.72
5.10
4.48
5.03
4.52
4.47
4.29
4.65
5.72
5.75
5.92
6.03
6.14
6.23
6.16
6.04
Exogenousvariablestaken to be:
PZ
5.2
0
-0.7
PM
-1.6
RA
0.5
1.0
2.48
2.54
L5+
L+S
5.72
5.35
4.91
5.28
5.13
5.05
4.83
5.09
5.72
5.59
5.67
5.90
5.91
5.96
5.79
5.80
5.72
5.09
4.51
4.95
4.47
4.36
4.27
4.61
5.72
5.06
4.50
4.96
4.48
4.36
4.28
4.60
5.72
5.95
6.46
6.51
6.64
6.63
5.76
6.49
0
-1.6
0.5
2.68
5.2
-0.7
0.5
2.68
5.2
-1.6
1.0
2.68
5.2
-1.6
0.5
2.54
5.2
0
0.5
2.68
1.8
1.8
1.8
F such that
TFPC
1.8
1.8
F/GDP=
5.72
4.46
4.03
4.37
3.72
3.68
3.57
3.97
5.2
-1.6
0.5
0.9
5.72
5.10
4.27
4.60
4.22
3.93
3.82
4.32
5.72
5.21
5.66
4.37
4.33
4.21
4.24
4.67
5.2
-1.6
0.5
2.68
5.2
-1.6
0.5
2.68
1.0
1.8
3 percent
1.8
1.8
Note: Variablesare defined as follows:Pz, fuel and raw materials prices;AM,domestic price of manufactures;RA, agricultural land stock; L
capital inflow;TFPc, economywideproductivitygrowth.
Sources: Kelleyand Williamson(1984a),table 5, p. 435; (1984b),table 5.4, p. 133.
1.8
population(or labor force);F, foreign
WhatDrives City Growthin the DevelopingWorld?
maybe fuzzyin the economiesbeinganalyzed,the twosources
of savingsare quite distinct in the modeland are thus reported
separately.Furthermore,what the modelidentifiesas training
investmentis embeddedin privateand governmentconsumption in the RDE national accounts.
Bibliography
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