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The growth of capital citiesin the world economicsystemR. Scott Frey a & Thomas Dietz ba Department of Sociology, Anthropology, andSocial Work , Kansas State University , WatersHall, Manhattan, KS, 66506b George Mason UniversityPublished online: 30 Jul 2010.

To cite this article: R. Scott Frey & Thomas Dietz (1990) The growth ofcapital cities in the world economic system, Sociological Spectrum: Mid-SouthSociological Association, 10:2, 271-281, DOI: 10.1080/02732173.1990.9981925

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THE GROWTH OF CAPITAL CITIESIN THE WORLD ECONOMIC SYSTEM

R. SCOTT FREYKansas State University

THOMAS DIETZGeorge Mason University

In this article we examine several determinants of the popula-tion growth of national capital cities. Two competing explanationsare outlined: The first views state participation in the economy as themajor determinant of capital city population growth, while the sec-ond position views world-system position as the major determinantof capital city growth. Results of three analyses of cross-national datasuggest more support for the world-system position than for thestate intervention position.

Carroll and Meyer (1982) have reported that the popula-tion growth of U.S. state capitals and the national capital hasexceeded the growth of noncapitals since 1930. They argue thatthis pattern is a function of increased state participation in theeconomy. That is, populations of capital cities have expandedin response to "increased employment by the government, in-creasing numbers of persons and groups interacting with thegovernment, and increased demands by these new residentsfor services" (Carroll and Meyer 1982, p. 568). Based on theirfindings and the observation that state expansion has in-creased dramatically worldwide, especially in noncore nations,Carroll and Meyer (1982, pp. 577-578) hypothesized that capitalcities of noncore nations have grown more rapidly than capitalcities of core nations.

Others (e.g., Berry 1973, pp. 78-80; Gilbert and Gugler1982, pp. 44-48) have developed similar arguments to explainthe rapid population growth of capitals in noncore nations.They reason that the efforts of noncore nations to foster eco-nomic growth through increased state intervention in theeconomy have resulted in a disproportionate share of total gov-ernment resources (both financial and administrative) being di-rected to capital cities. In turn, foreign and domestic groupshave responded to increased government concentration by in-vesting in the capital city. One of the cumulative, long-termeffects of increased public and private activity in the capital city

SOCIOLOGICAL SPECTRUM, 10:271-281, 1990Copyright © 1990 by Hemisphere Publishing Corporation 271

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272 R. S. FREY AND T. DIETZ

is rapid population expansion. In sum, the more the state exer-cises control over the economy, the more rapid the capital citypopulation growth.

On the other hand, differences in capital city populationgrowth between core and noncore nations may be a result offactors other than state participation in the economy.Dependency/world-system theorists (e.g., Chase-Dunn andRubinson 1977; Chirot 1977; Frank 1972, 1979; Timberlake1987; Wallerstein 1974, 1980, 1989) and findings of cross-national research (Bollen 1983; Bollen and Jackman 1985; Lon-don 1987; Nolan 1982, 1983a, 1983b; Nolan and White 1983;Snyder and Kick 1979) suggest that nations holding subordi-nate positions in the world economic system have experi-enced patterns of development different from those of corenations. It is possible that capital city populations have grownrapidly in noncore nations not simply as a result of increasedstate expansion in the economy, but as a result of the patternof uneven development that these nations have experiencedat the hands of core nations. For instance, foreign invest-ments in the rural and urban sectors of noncore nations arethought to displace rural populations and pull them to majorcities (see, e.g., Bradshaw 1987; London 1987; Timberlake 1985,1987). If this line of reasoning is correct, we would expectnoncore nations to experience more rapid capital city popula-tion growth than core nations, regardless of the level of stateparticipation in the economy.

In this article we examine these competing explanationsof rapid capital city population growth. Although there aregood reasons to believe that the world-system position has aneffect on capital city growth via its effects on state intervention,we only examine the direct effects of state intervention andworld-system position on capital city growth. Results of threepanel regression analyses of the effects of these two variableson capital city population growth are presented.

DATA AND METHODModel and Estimation Procedures

The previously outlined arguments suggest a model inwhich changes over time in a nation's capital city populationare a function of the population size of the capital city at anearlier date, the nation's level of state involvement in the econ-

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CAPITAL CITIES AND WORLD ECONOMICS 273

omy, and the nation's position in the world economic system.To estimate parameters of the model, we had to make deci-sions regarding the time period and functional form for esti-mates, and the techniques for making estimates.

We chose the time period from 1960 to 1980 to model thepopulation growth of capital cities. A twenty-year lag was usedbecause the effects of state intervention and position in theworld economic system are thought to act slowly. Such reason-ing is consistent with Carroll and Meyer's (1982, p. 567) obser-vation:

. . . the redistribution of resources in an urban system is amassive process that requires many years to reach equilib-rium. Thus, we expect a significant time lag between theperiods of state expansion and the date of rapid capital citygrowth.

We used this particular time period because it is the only long-term period for which reasonably reliable data are available.

We report results of parameter estimates of a linear, addi-tive model using absolute change in capital city population sizebetween 1960 and 1980 as the dependent variable. We also esti-mated models using percentage change in population and thelogarithm of absolute population change as dependent vari-ables, and models that included various multiplicative interac-tion terms (state intervention x world system position, andcapital city size x world-system position). Because results ofthe alternative estimates were similar to results reported be-low, they are not reported.

Models based on cross-national data are usually estimatedwith ordinary least squares regression (OLS). If the disturbanceterms of models are generated by normal, independent, andidentically distributed processes (normal i.i.d.), then estimatesobtained are unbiased and efficient in large and small samples(Goldberger 1964, pp. 161-176). Unfortunately, there is nostrong, a priori reason to believe that disturbance terms ofmodels estimated with cross-national data will be normal i.i.d.In fact, noticeably nonnormal, long-tailed residual distributionsseem to be the rule. Therefore, in addition to OLS, we usedtwo estimation procedures proposed for use with nonnormaldisturbances: biweighted least squares regression and jack-knifed least squares regression.

Biweighted least squares (BLS) regression is a robust esti-

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274 R. S. FREY AND T. DIETZ

mation technique that reduces the influence of outliers on esti-mates and standard errors. For long-tailed distributions, BLShas a smaller mean squared error than OLS and only a slightlyhigher mean squared error for normal distributions where OLSis most efficient (Huber 1973, 1977). The estimates that we re-port are for a BLS analysis in which data points more than 5.0standard errors from the mean were weighted zero. These esti-mates were based on a tuning constant of 5.0 and a residualmean square as a measure of spread (Mosteller and Tukey 1977,pp. 356-358). Experiments with other values for the tuning con-stant, other measures of spread, and least absolute errors re-gression (Taylor 1974) yielded results similar to those that wereport.

Jackknifed least squares (JLS) regression is a nonparamet-ric estimation technique that resamples the available data toconstruct multiple estimates of parameters of interest and usesthem to construct a set of final estimates of parameters andtheir standard errors that do not rely on specific assumptionsabout population distributions (Efron 1982). We broke our sam-ple of 84 cases into 14 subsets, each with 78 cases. The stan-dard errors reported were based on Tukey's approach (Mostel-ler and Tukey 1977), whose use in constructing confidenceintervals is subject to various criticisms (Efron 1982, pp. 13-19,75-90). We view the standard errors reported below for allthree estimation techniques (OLS, BLS, and JLS) as roughguides to uncertainty, not as the basis for formal hypothesistesting.

Sample

Our estimates are based on 84 nations for which datawere available on all variables included in the model. Unfortu-nately, the sample does not include nations identified by theWorld Bank (1976, p. 550) as having centrally planned econo-mies. The sample does include a representative sampling ofnations of the core, semiperiphery, and periphery. Nations in-cluded the sample are presented in the Appendix.

Variables and Measurement

Absolute change in capital city population size betweencirca 1960 and circa 1980 was used to measure populationchange. Capital city population size in circa 1960 was used tomeasure initial population size. Data were collected from sev-

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CAPITAL CITIES AND WORLD ECONOMICS 275

eral secondary sources (Dan Golenpaul Associates 1964; Davis1969, Table E; Information Please Almanac 1982; United Nations1962, Table 10; 1983, Table 8). We were unable to find popula-tion data for the metropolitan areas of capital cities at bothpoints in time for many of the nations included in the sample.As a result, we used population data for politically incorpo-rated capital cities. This strategy probably resulted in an under-estimation of the effects of state intervention and world-systemposition on population growth, because a large proportion ofcapital city population growth has occurred outside of politi-cally incorporated areas.

Total current government expenditure as a percent ofgross domestic product for circa 1960 was used as the measureof state intervention in the economy. Data were obtained fromthe World Bank (1976, pp. 442-446) and represent "all defenseexpenditures and all current expenditures for nondefense pur-poses, including transfers to households, subsidies to pro-ducers, and interest payments on public debt" (World Bank1976, p. 17) at the local, regional, and central government lev-els. We believe that the sum of expenditures for local, regional,and central governments is an appropriate measure of stateintervention because, as Carroll and Meyer (1982, p. 567) note,the national capital acts as a locus of control for regional andlocal governments. Data for twenty-three nations included inthe sample refer only to central government expenditures. Theeffect of this difference in definition appears minimal, forresults of an analysis with these nations excluded did not devi-ate significantly from the results we report.

An adjusted version of Snyder and Kick's (1979, pp. 1110,1114) network-based measure of international transactions forcirca 1965 was used to measure a nation's position (whethercore, semiperiphery, or periphery) in the world-system. Thismeasure is based on a block model analysis of four types ofinternational transactions: trade flows, treaty memberships,military interventions, and diplomatic relations. The measureappears valid, for it has been used in previous cross-nationalresearch with some success (Bollen 1983; Bollen and Jackman1985; London 1987; Nolan 1982, 1983a; Nolan and White 1983;Snyder and Kick 1979). Bollen (1983), however, argues that Sny-der and Kick misclassified six nations (South Africa, Iraq, SaudiArabia, Portugal, Spain, and Taiwan). We recoded four of the sixnations that were included in our sample (South Africa, Iraq,

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276 R. S. FREY AND T. DIETZ

Saudi Arabia, and Portugal) according to Bollen's suggested re-classifications. Following conventional practice (Bollen 1983;Bollen and Jackman 1985; London 1987; Nolan 1983a; Nolanand White 1983), we used dummy variables for semiperipherystatus and periphery status in the analyses reported; the effectof core status was captured by the intercept term.

FINDINGS

Multicollinearity is often a problem with the analysis ofcross-national data. The variance-decompensation measuressuggested by Belsley, Kuh and Welsch (1980, pp. 156-159) wereused to assess the effects of collinearity on estimates. Condi-tion index values were all below Belsley et al.'s suggested crite-rion value of fifteen. Consequently, multicollinearity does notappear to degrade the estimates reported in Table 1.

TABLE 1. Results of Panel Regression of Absolute Change inCapital City Population Between 1960 and 1980 on Capital City Sizein 1960, State Expenditures, Semiperipheral Status, and Peripheral

Status (Standard errors in parentheses)

Regressorvariable

CAP60

STATE

SEMI

PER

Intercept

R2

OLS

0.502c

(0.11)13.8023.1

925.2b

(441)1199.5b

(422)-779.3 a

(660)0.23

Estimation method

BLS

0.275c

(0.09)26.78a

(15.2)558.3a

(290)1011.6e

(272)-820.6a

(427)0.45

ILS

0.254(0.51)22.17(31.9)

1042.3a

(623)1285.4e»(407)

-826.5a

(617)—

N-84.aUnstandard¡zed coefficient as large as its standard error.fcUnstandardized coefficient twice its standard error.cUnstandardized coefficient thrice its standard error.OLS - Ordinary least squares, BLS - Biweighted least squares, JLS - Jackknifed

least squares, CAP60 - Capital City Size, 1960, STATE - State Expenditures,SEMI - Semiperipheral Status, PER - Peripheral Status.

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CAPITAL CITIES AND WORLD ECONOMICS 277

OLS EstimatesResults of the OLS estimates are reported in column 1 of

Table 1. Capital city population size in 1960 has a strong andpositive effect on capital city population growth between 1960and 1980. The coefficient is more than twice the size of itsstandard error. Capitals with large populations in 1960 havegrown most, indicating that saturation effects, in which largecities reach an asymptote and then grow slowly, have not oc-curred during the 1960-1980 period.

As expected, state expenditures as a percent of gross do-mestic product have a positive effect on the capital city popula-tion growth. But the coefficient representing the effect of stateintervention is small, and it is not twice as large as its standarderror. This finding contradicts Carroll and Meyer's (1982) argu-ment that state intervention in the economy is the major deter-minant of rapid capital city population growth.

Coefficients for semiperiphery and periphery status are inthe predicted direction and are more than twice the size oftheir standard errors. Capitals in the periphery grew most rap-idly, those in the semiperiphery grew at intermediate levels,and the core nations grew most slowly. Thus, a nation's posi-tion in the world economic system seems to have a substantialeffect on its capital city growth independent of state participa-tion in the economy. This finding suggests that world-systemposition is the major determinant of capital city populationgrowth.

Robust and Nonparametric EstimatesAn examination of the residuals from the OLS regression

analysis revealed a number of outliers. In particular, the stan-dardized residuals for Columbia, Mexico, Japan, South Korea,and the United Kingdom are greater than 2.0. This suggests along-tailed residual distribution and indicates that the OLS esti-mates are unstable. We respecified the model using robust andnonparametric estimation techniques to gauge the stability ofthe OLS estimates.

Robust estimates, which were based on the BLS estima-tion technique, are presented in column 2 of Table 1. All vari-ables have the expected positive effects on capital city popula-tion growth, but there are several important differencesbetween the OLS and BLS estimates. First, the coefficient ofdetermination increases from .23 for the OLS estimates to .45

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278 R. S. FREY AND T. DIETZ

for the BLS estimates, as can be expected of a procedure thatreduces the influence of outliers. Second, the effect of capitalcity size in 1960 is reduced, suggesting that part of the influ-ence attributed to this variable by the OLS estimates is a resultof outliers. There still appears to be a "growth center" effect,with the largest capitals experiencing the most growth, but thiseffect does not appear as strong when the BLS technique isused. Third, the coefficient for state intervention doubles insize and is almost twice the size of its estimated standard error,a result consistent with Carroll and Meyer's (1982) argument.Although robust estimates indicate that state intervention has asignificant impact on capital city growth, world-system positionremains a better predictor of capital city growth.

Column 3 of Table 1 reports the jackknifing results. Theparameter estimates for all variables are similar to those ob-tained by OLS and BLS estimation techniques. However, theestimated standard errors for all variables except peripheralstatus are larger than those of the OLS and BLS estimates. Thisfinding suggests that the parametric estimation techniques aretoo optimistic in estimating the uncertainty in the data. As wastrue of the OLS and BLS estimates, the JLS estimates indicatethat position in the world economic system has a much greatereffect on capital city population growth than state participationin the economy.

CONCLUSIONS

Findings reported here are consistent with expectationsregarding the direction of the effects of state intervention andposition in the world economic system on capital city popula-tion growth. Results of the OLS, BLS, and JLS estimates indicatethat nations with high levels of state intervention experiencedrapid capital city population growth. The effect of world-systemposition on capital city growth proved to be substantial, withthe pace of growth inversely related to centrality in the worldeconomic system.

Although the effects of state intervention and world-system position on capital city growth are in the predicted di-rection, world-system position has a much stronger effect oncapital city growth than state intervention. This finding sug-gests that the argument presented by Carroll and Meyer (1982,pp. 577-578) and others (Berry 1973, pp. 78-80; Gilbert and

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CAPITAL CITIES AND WORLD ECONOMICS 279

Gugler 1982, pp. 44-48), that noncore nations have experiencedmore rapid capital city population growth than core nationsbecause of higher levels of state intervention, is only partiallycorrect. It is clear that factors other than state economic inter-vention account for differences in capital city growth betweencore and noncore nations.

Further research is needed to determine how position inthe world economic system actually influences capital city pop-ulation growth. A number of causal mechanisms come tomind. Perhaps rapid capital city population growth is a resultof the increasing primacy of capital cities in noncore nations.Or, it may be that the presence of regional headquarters andtransportation facilities of multinational corporations in non-core capitals has influenced their population growth. In thatcase, capital city population growth should be related posi-tively with the extent of multinational penetration.

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Berry, Brian J. L. 1973. The Human Consequences of Urbanization:Divergent Paths in the Urban Experience of the Twentieth Cen-tury. New York: St. Martin's Press.

Bollen, Kenneth A. 1983. "World System Position, Dependency, andDemocracy: The Cross-National Evidence." American Sociologi-cal Review 48:468-479.

Bollen, Kenneth A. and Robert M. Jackman. 1985. "Political Democ-racy and the Size Distribution of Income." American Sociologi-cal Review 50:438-457.

Bradshaw, York W. 1987. "Urbanization and Underdevelopment: AGlobal Study of Modernization, Urban Bias, and Economic De-pendency." American Sociological Review 52:224-239.

Carroll, Glenn R. and John W. Meyer. 1982. "Capital Cities in theAmerican Urban System: The Impact of State Expansion."American Journal of Sociology 88:565-578.

Chase-Dunn, Christopher and Richard Rubinson. 1977. "Toward aStructural Perspective on the World-System." Politics and Soci-ety 7:453-476.

Chirot, Daniel. 1977. Social Change in the Twentieth Century. NewYork: Harcourt Brace Jovanovich.

Dan Golenpaul Associates. 1964. Information Please Almanac Atlasand Yearbook, 1965. New York: Simon and Schuster.

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Davis, Kingsley. 1969. World Urbanization, 1950-1970. Volume I: BasicData for Cities, Countries, and Regions. Berkeley: Institute ofInternational Studies, University of California.

Efron, Bradley. 1982. Robust Statistical Procedures. Philadelphia:Siam.

Frank, Andre G. 1972. "The Development of Underdevelopment."Pp. 3-17 in Dependence and Underdevelopment, edited by J.D. Cockcroft, A. G. Frank and D. K. Johnson. New York: An-chor.

1979. Dependent Accumulation and Underdevelopment.New York: Monthly Review Press.

Gilbert, Alan and Josef Gugler. 1982. Cities, Poverty, and Develop-ment: Urbanization in the Third World. New York: Oxford Uni-versity Press.

Goldberger, Arthur S. 1964. Econometric Theory. New York: Wiley.Huber, Peter J. 1973. "Robust Regression: Asymptotics, Conjectures

and Monte Carlo." Annals of Statistics 1:799-821.1977. Robust Statistical Procedures. Philadelphia: Siam.

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Mosteller, F. H. and J. W. Tukey. 1977. Data Analysis and Regression.Reading, MA: Addison-Wesley.

Nolan, Patrick D. 1982. "Stratification in the World System." CurrentAnthropology 22:193-194.

1983a. "Status in the World System, Income Inequality, andEconomic Growth." American Journal of Sociology 89:410-419.

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Taylor, Lester D. 1974. "Estimation by Minimizing the Sum of Abso-lute Errors." Pp. 169-190 in Frontier of Econometrics, edited byPaul Zarembka. New York: Academic Press.

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turing and Community Politics, edited by M. Smith and J.Feagin. London: Basil and Blackwell.

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1983. Demographic Yearbook, 1981. New York: United Nations.Wallerstein, Immanuel. 1974. The Modern World-System, I. New York:

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APPENDIX: SAMPLE OF NATIONS

AlgeriaArgentinaAustraliaAustriaBelgiumBenin

BoliviaBrazilBurundiCameroonCanadaCentral Africa

RepublicChadChileColombiaCongoCosta RicaCyprusDominican RepublicEcuadorEgyptEl SalvadorEthiopiaFinlandFranceGhanaGreece

GuatemalaGuineaHondurasIndiaIndonesiaIraqIrelandIsraelItalyIvory CoastJamaicaJapanJordanKenyaLebanonLiberiaLibyaLuxembourgMadagascarMaliMauritaniaMexicoMoroccoNepalNetherlandsNew ZealandNicaraguaNiger

NigeriaNorwayPanamaParaguayPeruPhilippinesPortugalRwandaSaudi ArabiaSenegalSierra LeoneSouth AfricaSouth KoreaSouth VietnamSudanSwedenSyriaThailandTogoTrinidad and TobagoTunisiaUgandaUnited KingdomUnited StatesUpper VoltaUruguayVenezuelaWest Germany

Request reprints from R. Scott Frey, Department of Sociology,Anthropology, and Social Work, Kansas State University, WatersHall, Manhattan, KS 66506.

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