28 Te Ope Urba Studies Joural, 2009, 2, 28-42 Drivers of Agglomeratio: Geograpy vs History Fracisco J. Goerlic * ad Matilde Mas Ope Access Uiversidad de Valecia, Departameto de Aálisis Ecoómico, Campus de Tarogers, Avda. de Tarogers s/, 46022- Valecia, Spai; Istituto Valeciao de Ivestigacioes Ecoómicas, C/Guardia Civil, 22, Esc. 2, 1º, 46020 Valecia, Spai Abstract: Tis paper focuses o te ifluece of two classical drivers of populatio agglomeratio: geograpy ad istory. Geograpy is idetified by two co-ordiates: coastal positio ad altitude. Te promiece of istory is also captured by two caracteristics: te iitial size of te muicipalities, ad teir status as te admiistrative cetre of te area. I first istace we examie localizatio patters, at a small geograpical scale, accordig to tese caracteristics ad preset empirical evidece of te progressive populatio cocetratio alog te coast, o te plais ad i te regioal (provicial) capitals; a process tat as ot fiised i te preset days. Next, we sow tat bot drivers of populatio agglomeratio, geograpy ad istory, are relevat for Spai ad tat tey sow a icreasig explaatory power i accoutig for populatio cocetratio. a quatitative poit of view te capital status factor sows te most promiet role. A exercise of coditioal covergece sows tat, eve i te absece of tese factors, we would ave see a sigificat amout of populatio cocetratio but at a smaller rate. Our referece is te cesus populatio data for Spais muicipalities for te period 1900-2001. Give te importat cages i muicipality structure, te eleve cesuses ave bee omogeised accordig to te muicipal structure of te 2001 Cesus. Keywords: Populatio, muicipalities, cesus, agglomeratio. INTRODUCTION Tis paper discusses te importace of two classical drivers of populatio agglomeratio: geograpical determiats versus istorical importace. Te refereces used i tis study are te populatio data for Spais muicipalities gatered over te 20 t cetury. Te two geograpical coditioig factors used i te aalysis refer to: 1. coastal or ilad locatio; ad 2. eigt above sea level, i oter words, weter a muicipality is situated i a moutaious regio or o te plais. Historical importace is also examied troug two variables: 1. size measured by te umber of iabitats- at te start of te period, tat is to say te iitial size of te muicipality; ad 2. weter it as provicial capital status, ad tus represets te politicaladmiistrative cetre of te area. Trougout te 20 t cetury, te Spais populatio became icreasigly cocetrated [1-4]. Te coutry s ueve populatio distributio was already evidet i 1900 ad tis imbalace was acutely itesified by te developmet ad idustrialisatio of Spais society. Ecoomic developmet durig te 20 t cetury did ot create its ow urba system i a vacuum, but rater it operated witi a etwork of existig cities, formed i te 18 t ad 19 t ceturies (or peraps muc earlier). A brief look at te Atlas de la Idustrializació de España, 1750-2000 by Jordi Nadal [5] sows tat, wit some relevat exceptios may of wic are liked to te miig idustry, by its very ature *Address correspodece to tis autor at te Uiversidad de Valecia, Departameto de Aálisis Ecoómico, Campus de Tarogers, Avda. de Tarogers s/, 46022-Valecia, Spai; Tel: 963 82 82 46; Fax: 963 82 82 49; E-mail: Fracisco.J.Goerlic@uv.es based essetially o immobile resources- te populatio as remaied i te same locatios for ceturies. Hece, persistece seems to be a importat caracteristic i te evolutio of te populatio distributio over time [6]. Te Spais experiece is similar to tose of oter large Europea cities [7], altoug wit a certai time lag, ad our calculatios corroborate tose made at a provicial level by Ayuda, Collates, Piilla [8, 9] wit a loger time spa, altoug teir use of a larger geograpical uit of aalysis moderates te process of pysical populatio agglomeratio to a large degree. Martí-Heeberg [10] obtais similar results at a regioal level i Europe. Te process of populatio locatio at a muicipal level durig te 20 t cetury is torougly described i Goerlic, Mas, Azagra, Core [4] ad i Goerlic ad Mas [11]. I tese studies, we detail te varied pace of gradual depopulatio i small tows ad villages (te rural eviromet), as compared to te growt of medium-sized cities ad te burgeoig large cities (te metropolita areas), all of wic followed a marked spatial patter. Wile te ilad areas became icreasigly depopulated, te coastal strip grew more desely populated. Madrid, te coutry s capital, is te most otable exceptio i tis process of populatio dispersio towards te coast, altoug tis is ot i ay way surprisig sice atioal capitals ave always ad teir ow demograpic dyamic [12]. I tis paper, we set out to explore tese geeral patters of populatio agglomeratio i greater dept. We aim to ucover te locatio patters ad te timig of tese patters from te eleve cesuses coducted i te 20 t cetury, altoug we are aware we ave o geeral explaatory model for te origis of populatio agglomeratios i certai 1874-9429/09 2009 Betam Ope
Drivers of Agglomeratio: Geograpy vs History Te Ope Urba Studies Joural, 2009, Volume 2 29 places, ad teir subsequet dyamics. I cotrast to te work of oter scolars ([8, 9, 13, 14] for te Spais case; ad [7, 15-24] for oter coutries), our iterest does ot lie solely i urba agglomeratios or large cities. Rater, our aalysis i tis paper icludes te smaller muicipalities, of limited importace i terms of populatio figures but sigificat i umber ad lad surface area [25]. Te paper is structured as follows. Te ext sectio reviews te iformatio sources used ad te procedures followed i creatig te omogeeous series. Sectio 2 itroduces some metodological issues. Sectio 3 describes two geograpical caracteristics of Spais muicipalities. Sectio 4 presets two potetially determiig istorical features of te curret populatio agglomeratio. Sectio 5 cotrasts geograpical ad istorical factors. Fially, Sectio 6 provides a sytesis of te mai coclusios. STATISTICAL SOURCES Te primary iformatio source for te researc is te residet (de jure) muicipal populatio recorded i te eleve Spais cesuses coducted betwee 1900 ad 2001 (te latest available cesus). Of all te Spais admiistrative divisios, muicipalities are te smallest admiistrative uits wit assiged precise boudaries ad are te base for gaterig iformatio o demograpic effects at differet momets i time. 1 Furtermore, tis iformatio as a log istorical traditio. Te first cesus to cover all te muicipalities i Spai was te 1842 Ceso de la Matrícula Catastral (property register cesus). Tis cesus was coducted usig a imputatio procedure ad, as a result, te figures it provides lack rigour ad reliability. Te 1857 cesus is terefore cosidered to be te first moder cesus. However, oter cesuses of great istorical value go back as far as te 16 t cetury. 2 Te muicipal uit is clearly iadequate to provide a full picture of ow te populatio is distributed across te territory. Neverteless, tere is a subdivisio of Spais muicipalities tat, altoug ot official, is traditioally igly relevat. Tese subdivisios are te collective ad idividual populatio etities ad teir correspodig uclei ad outlyig properties. Tese uits represet te true populatio settlemets. However, iformatio o tese uits, istorically compiled i local records, is eiter cosistet over time or adequately systemised. Moreover, tese uits ave o precise boudaries o wic to calculate, for istace, populatio desities. Te Spais muicipal structure witessed major cages durig te 20 t cetury. Te umber of muicipalities fell cosiderably from 9,267 i 1900 to 8,108 i te 2001 cesus. Numerous modificatios also occurred i te muicipal structure, due to mergers, divisios ad oter 1 Tere is also a furter admiistrative uit below tat of muicipality, amely te Local territorial etity smaller ta a muicipality (smaller local etities), defied as a uit for te maagemet, decetralised admiistratio ad political represetatio witi a muicipality (Law 7/1985, of 2 April, regulatig te bases of local govermet). However, o systematic demograpic statistics exist for tese etities, ad ulike te muicipality, tey do ot ave a delimited pysical surface area. 2 For a istorical view of Spais cesuses (particularly te earliest), see te excellet work of García España [27]. O te cesuses used i tis study, see [4], ad te refereces cited terei. types of alteratios made to existig muicipalities i periods betwee cesuses. Tis is a latet problem i may of te studies o populatio locatio coducted from a muicipal perspective [2, 3], but te complexity of adjustmets as meat tat oly oe autor, 3 García Ferádez [26], aware of te problem, approaced te task of omogeisatio by takig as a referece te muicipal structure of te 1981 cesus, ad usig te de facto populatio as is study variable. Ufortuately, te 2001 cesus did ot iclude tis variable i its aalysis ad cetred oly o te registered or usual residet populatio; moreover, te umber of muicipalities grew betwee 1981 ad 2001 as a result of a certai locally based idepedetist tedecy. Tese two reasos provide sufficiet grouds for udertakig te work of [26] afres, based o te muicipal structure from te most recet cesus, 2001, ad takig te registered populatio as te study variable. As a result, Goerlic, Mas, Azagra, Coré [4] created omogeised muicipal populatios startig from two basic priciples: 1. populatios are defied o te basis of a territorial criterio, te muicipal boudaries, ad 2. te criterio tat determies tese territories is te existig muicipalities recorded i te 2001 cesus. Hece, tis study uses iformatio o te omogeised registered muicipal populatios from te cesuses coducted betwee 1900 ad 2001, were tis omogeeity is based o te muicipal boudaries i existece i te 2001 cesus, wit te registered populatios of te 8,108 muicipalities i te 2001 cesus recostructed ad backdated to 1900. Goerlic, Mas, Azagra y Coré [4] provide a detailed descriptio of te omogeisatio process ad te resultig series. Data o muicipal lad area ad eigt above sea level of te muicipal capital are take from te Istituto Geográfico Nacioal (IGN) (Natioal Geograpical Istitute) muicipal database ad provicial lad area data come from te aggregatio of te muicipal lad area. METHODOLOGICAL CONSIDERATIONS Trougout te paper, we use two relative cocetratio idicators commoly foud i te iequality literature: te Gii idices ad te mea logaritmic deviatio or (secod) Teil idex. Bot ideces are described briefly below, togeter wit te decomposability property of te latter, sice it will be widely applied i te followig sectios. If y i is te populatio of muicipality i, we ca defie te Gii idex, G, as te relative mea differece, G = 1 1 y 2 μ 2 i y j (1) i=1 j=1 were μ is te mea of te distributio, μ = 1, ad i=1 te umber of muicipalities studied. Tus, we measure te 3 Te Miisterio de Fometo (Miistry of Developmet) Atlas estadístico de las áreas urbaas e España [28] carried out some omogeisatio of muicipalities for most recet years wit te 1996 Padró (Register) as its referece date. y i
30 Te Ope Urba Studies Joural, 2009, Volume 2 Goerlic ad Mas distace, i terms of populatio, of eac muicipality from eac of te oters, ad G takes te average of all te distaces. Te Gii idex is bouded betwee zero, if all te muicipalities were of te same size, ad oe, i te case of maximum cocetratio. 4 We also use aoter commo idex, wit a property of particular iterest, amely te (secod) Teil idex [29] or mea logaritmic deviatio, T *, wic ca be writte as T * = 1 were log μ = log μ (2) y i μ μ is te geometric mea of te distributio, i=1 log μ = 1 log y i. Te mea logaritmic deviatio also i=1 takes a value of zero if all te muicipalities were te same size, but i cotrast to G, it is ot bouded above, so tat a iger cocetratio is sow as a iger idex value witout it tedig towards a specific value. Note tat bot G ad T * are relative idices; i oter words, if populatio growt ad bee proportioal i all muicipalities, te dispersio, measured by G or T *, would ave remaied costat. If te observed cocetratio icreases, it is precisely because populatio growt as ot occurred proportioally; some muicipalities ave grow more ta oters, or (as i our case) wile some grow, oters become smaller. Te Teil idex T * presets te additive decomposability property explaied below. Let us assume tat we cosider te total set of Spais muicipalities to cotai te combiatio of H differet groups, all exaustive ad mutually exclusive, deoted by te idex = 1, 2, 3,, H. We desigate te umber of muicipalities from group by, ad its vector of populatios by y = ( y 1, y 2,, y ), so tat y i is te populatio of muicipality i from group. Let μ = (μ 1,μ 2,,μ H ) be te vector of te meas of eac group, were μ is te mea muicipal size of group. Tis otatio eables us to write te overall mea, μ, as a weigted sum of te meas of te differet groups, were te weigtig is give by te importace measured by te umber of muicipalities- of eac group, H H μ = 1 y i = 1 y i=1 i = 1 =1 i=1 μ = =1 μ (3) =1 Now we ca express te overall dispersio, measured by T *, as te sum of two compoets, (i) te existig dispersio witi eac oe of te groups, or itra-group dispersio ad H (ii) te existig dispersio amog te differet groups, iter-group dispersio Moreover, te dispersio witi te groups is obtaied as a weigted average of te dispersio idices applied to eac oe of te groups, were te weigts add up to uity ad reflect te relative weigt (i terms of te umber of muicipalities) of tese groups. O te oter ad, te dispersio amog groups is simply te applicatio of te T * idex to te mea muicipality size of eac group (tus te dispersio witi eac of te groups is ot cosidered i tis calculatio). Specifically, T * = 1 H log μ H 1 = =1 i=1 y i log μ y. μ =1 i=1 i μ H 1 = log μ y + log μ = =1 i=1 i μ H = 1 log μ + log μ =1 i=1 y i μ H = 1 log μ H + log μ =1 i=1 y i =1 μ H = T * + log μ =1 =1 μ Itra-group compoet * T H Iter-group compoet THE IMPORTANCE OF GEOGRAPHICAL LOCATION: FROM THE INLAND AREAS TO THE COAST AND FROM THE MOUNTAINS TO THE PLAINS Spai is clearly a coastal coutry. Of te 47 peisular provices, 19 ave direct sea access ad 13 of teir capitals are located o te coast. 5 Te total legt of te Spais coastlie (icludig te islads, Ceuta ad Melilla) is aroud 8,000 kilometres. Despite tis extesio, oly 460 of Spai s preset 8,108 muicipalities ave direct sea access, a scat 5.7% represetig oly 7.0% of te lad surface area. Additioal iformatio is provided i Table 1. At te same time, compared to its Europea eigbours Spai is a very moutaious coutry. Not oly is te extet of its moutai cais cosiderable, but tey are also relatively ig. Accordig to IGN data, 39.3% of Spai s lad area lies betwee 600 ad 1,000 metres above sea level, ad 18.5% is above tat eigt. Sice te populatio is ot distributed evely across te coutry, but i populatio uclei, we ca, for practical purposes, take te eigt of te muicipal capital (mai ucleus) as te altitude of populatio settlemet. Table 2 sows tat 3,080 muicipalities are located at a altitude of betwee 600 ad 1,000 metres above (4) 4 For discrete distributios, te maximum value of G is give by G = 1, wic teds towards 1 as. 5 Te six exceptios are: Giroa, Graada, Lugo, Murcia, Oviedo ad Bilbao; owever, ote tat te coastal city of Gijó i Asturias is equally or eve more importat ta te capital Oviedo i terms of populatio, ad tat Bilbao, altoug ot o te coast, is located o a avigable estuary. Seville is a similar case, located o te river Guadalquivir, altoug te provice does ot ave its ow coastlie.
Drivers of Agglomeratio: Geograpy vs History Te Ope Urba Studies Joural, 2009, Volume 2 31 Table 1. Legt of Coastlie. Coastal Muicipalities ad teir Surface Area Provice Legt of Coast Islet Coastal Muicipalities Number % Lad Area % 01 Álava - - - - - - - 02 Albacete - - - - - - - 03 Alicate/Alacat 244 3.1% 7 19 13.5% 1,625 27.9% 04 Almería 249 3.1% 2 13 12.7% 2,148 24.5% 05 Ávila - - - - - - - 06 Badajoz - - - - - - - 07 Balears (Illes) 1,428 18.1% - 37 55.2% 3,806 76.2% 08 Barceloa 161 2.0% - 28 9.0% 480 6.2% 09 Burgos - - - - - - - 10 Cáceres - - - - - - - 11 Cádiz 285 3.6% - 16 36.4% 2,389 32.1% 12 Castelló/Castelló 139 1.8% 7 16 11.9% 919 13.9% 13 Ciudad Real - - - - - - - 14 Córdoba - - - - - - - 15 Coruña (A) 956 12.1% 47 41 43.6% 2,726 34.3% 16 Cueca - - - - - - - 17 Giroa 260 3.3% 7 22 10.0% 663 11.2% 18 Graada 81 1.0% - 9 5.4% 448 3.5% 19 Guadalajara - - - - - - - 20 Guipúzcoa 92 1.2% 2 10 11.4% 280 14.7% 21 Huelva 122 1.5% 1 9 11.4% 1,846 18.2% 22 Huesca - - - - - - - 23 Jaé - - - - - - - 24 Leó - - - - - - - 25 Lleida - - - - - - - 26 Rioja (La) - - - - - - - 27 Lugo 144 1.8% 5 8 11.9% 642 6.5% 28 Madrid - - - - - - - 29 Málaga 208 2.6% - 14 14.0% 1,385 18.9% 30 Murcia 274 3.5% 16 8 17.8% 2,946 26.0% 31 Navarra - - - - - - - 32 Ourese - - - - - - - 33 Asturias 401 5.1% 2 19 24.4% 2,053 19.4% 34 Palecia - - - - - - - 35 Palmas (Las) 815 10.3% - 27 79.4% 3,798 93.4% 36 Potevedra 398 5.0% 109 22 35.5% 928 20.6% 37 Salamaca - - - - - - - 38 Sta. Cruz de Teerife 768 9.7% - 49 92.5% 3,139 92.8% 39 Catabria 284 3.6% 7 26 25.5% 875 16.7% 40 Segovia - - - - - - - 41 Sevilla - - - - - - - 42 Soria - - - - - - - 43 Tarragoa 278 3.5% - 21 11.5% 1,018 16.1% 44 Teruel - - - - - - - 45 Toledo - - - - - - - 46 Valecia/Valècia 135 1.7% - 23 8.7% 702 6.5% 47 Valladolid - - - - - - - 48 Vizcaya 154 1.9% 4 21 18.9% 271 12.2% 49 Zamora - - - - - - - 50 Zaragoza - - - - - - - 51 Ceuta 20 0.3% - 1 100.0% 19 100.0% 52 Melilla 9 0.1% - 1 100.0% 13 100.0% España 7,905 100.0% 216 460 5.7% 35,119 7.0% Note: Te coastlie ad isles are measured i Kms. Te coastlie percetage is te vertical percetage of te atioal total. Muicipal lad area i Km 2. Te percetage of coastal muicipalities ad teir lad area is te percetage of te provicial coastlie; i te case of Spai, te percetage is of te atioal total. Source: INE, IGN ad autors' ow calculatios.
32 Te Ope Urba Studies Joural, 2009, Volume 2 Goerlic ad Mas Table 2. Statistics o Heigt Above Sea Level Provice Average Altitude Spai Meters 100 Muicipalities Accordig to Altitude Zoes Up to 200 m. 201 to 600 m 601 to 1,000 m 1,001 to 2,000 m. Muicipalities Accordig to Altitude Zoes (%) Up to 200 m. 201 to 600 m 601 to 1,000 m 1,001 to 2,000 m. Meters Altitude of te Provicial Capital INE Code Name 01 Álava 532 86.5 1 37 13-2.0% 72.5% 25.5% - 540 01059 Vitoria-Gasteiz 02 Albacete 796 129.4-7 69 11-8.0% 79.3% 12.6% 686 02003 Albacete 03 Alicate/Alacat 299 48.6 62 59 20-44.0% 41.8% 14.2% - 8 03014 Alicate/Alacat 04 Almería 561 91.2 20 34 37 11 19.6% 33.3% 36.3% 10.8% 16 04013 Almeria 05 Ávila 1,030 167.5-5 103 140-2.0% 41.5% 56.5% 1,131 05019 Avila 06 Badajoz 422 68.7 7 138 19-4.3% 84.1% 11.6% - 186 06015 Badajoz 07 Balears (Illes) 122 19.9 58 9-86.6% 13.4% - 15 07040 Palma 08 Barceloa 376 61.1 111 131 60 9 35.7% 42.1% 19.3% 2.9% 12 08019 Barceloa 09 Burgos 858 139.5-16 310 45-4.3% 83.6% 12.1% 929 09059 Burgos 10 Cáceres 467 76.0-185 32 2-84.5% 14.6% 0.9% 459 10037 Cáceres 11 Cádiz 246 40.0 25 14 5-56.8% 31.8% 11.4% - 69 11012 Cádiz 12 Castelló/Castelló 478 77.8 27 62 33 13 20.0% 45.9% 24.4% 9.6% 27 12040 Castelló de la Plaa/Castelló de la Plaa 13 Ciudad Real 690 112.2-17 85 - - 16.7% 83.3% - 628 13034 Ciudad Real 14 Córdoba 444 72.2 12 48 15-16.0% 64.0% 20.0% - 106 14021 Córdoba 15 Coruña (A) 168 27.3 59 35 - - 62.8% 37.2% - - 26 15030 A Coruña 16 Cueca 925 150.3 - - 180 58 - - 75.6% 24.4% 999 16078 Cueca 17 Giroa 276 44.9 152 34 16 19 68.8% 15.4% 7.2% 8.6% 70 17079 Giroa 18 Graada 831 135.1 5 20 98 45 3.0% 11.9% 58.3% 26.8% 683 18087 Graada 19 Guadalajara 987 160.6 - - 157 131 - - 54.5% 45.5% 685 19130 Guadalajara 20 Guipúzcoa 188 30.6 49 39 - - 55.7% 44.3% - - 8 20069 Doostia-Sa Sebastiá 21 Huelva 318 51.7 35 30 14-44.3% 38.0% 17.7% - 30 21041 Huelva 22 Huesca 599 97.4 10 106 61 25 5.0% 52.5% 30.2% 12.4% 488 22125 Huesca 23 Jaé 651 105.9-39 53 5-40.2% 54.6% 5.2% 568 23050 Jae 24 Leó 848 137.9-18 158 35-8.5% 74.9% 16.6% 838 24089 Leó 25 Lleida 533 86.7 14 140 54 23 6.1% 60.6% 23.4% 10.0% 182 25120 Lleida 26 Rioja (La) 680 110.5-76 81 17-43.7% 46.6% 9.8% 385 26089 Logroño 27 Lugo 402 65.3 14 42 10 1 20.9% 62.7% 14.9% 1.5% 454 27028 Lugo 28 Madrid 810 131.7-24 115 40-13.4% 64.2% 22.3% 655 28079 Madrid 29 Málaga 444 72.2 19 52 29-19.0% 52.0% 29.0% - 11 29067 Málaga 30 Murcia 218 35.4 29 11 5-64.4% 24.4% 11.1% - 39 30030 Murcia 31 Navarra 503 81.8 13 192 66 1 4.8% 70.6% 24.3% 0.4% 490 31201 Pamploa/Iruña 32 Ourese 519 84.4 11 46 35-12.0% 50.0% 38.0% - 139 32054 Ourese 33 Asturias 243 39.4 36 35 7-46.2% 44.9% 9.0% - 232 33044 Oviedo 34 Palecia 854 138.9 - - 173 18 - - 90.6% 9.4% 734 34120 Palecia 35 Palmas (Las) 376 61.1 12 16 4 2 35.3% 47.1% 11.8% 5.9% 13 35016 Palmas de Gra Caaria (Las) 36 Potevedra 170 27.6 44 15 3-71.0% 24.2% 4.8% - 27 36038 Potevedra 37 Salamaca 825 134.1-4 336 22-1.1% 92.8% 6.1% 800 37274 Salamaca
Drivers of Agglomeratio: Geograpy vs History Te Ope Urba Studies Joural, 2009, Volume 2 33 (Table 2) cotd.. Provice Average Altitude Spai Meters 100 Muicipalities Accordig to Altitude Zoes Up to 200 m. 201 to 600 m 601 to 1,000 m 1,001 to 2,000 m. Muicipalities Accordig to Altitude Zoes (%) Up to 200 m. 201 to 600 m 601 to 1,000 m 1,001 to 2,000 m. Meters Altitude of te Provicial Capital INE Code Name 38 Sta. Cruz de Teerife 396 64.4 13 30 8 2 24.5% 56.6% 15.1% 3.8% 5 38038 Sata Cruz de Teerife 39 Catabria 236 38.4 66 20 16-64.7% 19.6% 15.7% - 11 39075 Satader 40 Segovia 964 156.7 - - 132 77 - - 63.2% 36.8% 1,002 40194 Segovia 41 Sevilla 195 31.8 68 34 3-64.8% 32.4% 2.9% - 11 41091 Sevilla 42 Soria 1,045 169.9 - - 55 128 - - 30.1% 69.9% 1,063 42173 Soria 43 Tarragoa 274 44.5 81 84 18-44.3% 45.9% 9.8% - 69 43148 Tarragoa 44 Teruel 991 161.1-32 83 121-13.6% 35.2% 51.3% 912 44216 Teruel 45 Toledo 583 94.9-114 90 - - 55.9% 44.1% - 529 45168 Toledo 46 Valecia/Valècia 214 34.7 168 69 26 2 63.4% 26.0% 9.8% 0.8% 13 46250 Valecia 47 Valladolid 766 124.6 - - 225 - - - 100.0% - 698 47186 Valladolid 48 Vizcaya 113 18.3 97 14 - - 87.4% 12.6% - - 6 48020 Bilbao 49 Zamora 759 123.4 - - 241 7 - - 97.2% 2.8% 649 49275 Zamora 50 Zaragoza 578 93.9 24 129 127 12 8.2% 44.2% 43.5% 4.1% 199 50297 Zaragoza 51 Ceuta 40 6.5 1 - - - 100.0% - - - 40 51001 Ceuta 52 Melilla 15 2.4 1 - - - 100.0% - - - 15 52001 Melilla España 615 100.0 1.344 2.262 3.480 1.022 16.6% 27.9% 42.9% 12.6% 655 28079 Madrid Note: Te mea altitude is obtaied as te simple average of te altitudes of eac muicipal capital. Muicipality distributio accordig to altitude zoes is based o te altitude of te muicipal capital. Te miimum value of eac provice is sow i italics. Te maximum value of eac provice is sow i bold. For Spai, we take data for te capital, Madrid, as Provicial Capital Altitude data. Source: INE, IGN ad autors ow calculatios. sea level (42.9%) ad 1,022 at over 1,000 metres (12.6%). Te table also sows tat i geeral, te altitude of te capital is lower ta te average altitude of te provice. If we take a (simple) average of muicipal capital altitude as te average altitude of Spai (i terms of populatio settlemet) te average altitude is 615 metres. 6 But, as ca be see i Table 2, tere are uge differeces betwee provices, from a average altitude of 113 metres i Vizcaya, to a average of over 1,000 i Ávila or Soria. It is particularly iterestig to cotrast populatio cocetratio i terms of tese two parameters, proximity to te coast ad altitude. Te geograpical factor clearly as a impact o populatio agglomeratio. We focus o aggregated aspects sice te diversity across provices is suc tat greater detail would etail a excessively log study. te Ilad Areas to te Coast: Coastal Spai Our very restricted defiitio of coastal cosiders oly tose muicipalities wit direct access to te sea. Table 3 6 If, istead of te simple average, we cosider te average weigted by te umber of iabitats i te muicipalities, te altitude would be lower, ad moreover, it would ave falle from 424.6 metres i 1900 to 304.8 metres i 2001. Cosequetly, te average altitude of were te populatio resides fell by more ta 100 metres i 100 years. presets some statistics to illustrate te gradual cocetratio of te populatio o tis very arrow strip of lad. Tis defiitio of coastal esures tat our results will ot be biased towards a iger cocetratio. Hece, wile te populatio multiplied by a factor of 2.2 durig te 20 t cetury, te populatio livig rigt o te coast multiplied by a factor of 3.3 ad te ilad populatio by 1.9. Te proportio of te populatio livig i coastal muicipalities rose by over 10 percetage poits trougout te cetury. However, ote tat te level of cocetratio o te coastlie was already quite ig i 1900, altoug te 460 coastal muicipalities represeted oly 7.0% of te etire Spais lad area (icludig Balearics ad Caary Islads). Cocetratio was lower ilad but icreases steadily alog te period, te ilad Teil idex multiplied by a factor of 2.8 wereas te coastlie by 1.3. Hece, te coast as captured more populatio wile te ilad as icreased is differeces. I te case of te coast, te cocetratio idices sow a icreasig tred util te begiig of te eigties, we a sligt tred towards dispersio bega. Sice tese idices refer oly to coastal muicipalities, wat tey idicate is a certai tedecy towards dispersio witi te coastal strip itself. Tus, i te last quarter of te 20 t cetury, residetial destiatios o te coast appear to diversify (all of wic
34 Te Ope Urba Studies Joural, 2009, Volume 2 Goerlic ad Mas Table 3. Coastal Cocetratio of te Populatio (Spai 1900-2001) Spai Zoe 1900 1910 1920 1930 1940 1950 1960 1970 1981 1991 2001 Populatio Coast 3,954,429 4,372,354 4,828,658 5,473,142 6,324,963 6,991,715 7,953,848 9,640,136 11,441,430 12,109,295 12,934,862 Ilad 14,876,220 15,987,952 17,184,005 18,553,429 20,061,891 21,180,553 22,823,087 24,401,346 26,240,925 26,762,973 27,912,509 Spai 18,830,649 20,360,306 22,012,663 24,026,571 26,386,854 28,172,268 30,776,935 34,041,482 37,682,355 38,872,268 40,847,371 % of total populatio Coast 21.0% 21.5% 21.9% 22.8% 24.0% 24.8% 25.8% 28.3% 30.4% 31.2% 31.7% Ilad 79.0% 78.5% 78.1% 77.2% 76.0% 75.2% 74.2% 71.7% 69.6% 68.8% 68.3% Mea muicipal size Coast 8,597 9,505 10,497 11,898 13,750 15,199 17,291 20,957 24,873 26,325 28,119 Ilad 1,945 2,090 2,247 2,426 2,623 2,769 2,984 3,191 3,431 3,499 3,650 Spai 2,322 2,511 2,715 2,963 3,254 3,475 3,796 4,199 4,648 4,794 5,038 Spai = 100 Coast 370.1 378.5 386.6 401.5 422.5 437.4 455.5 499.1 535.2 549.1 558.2 Ilad 83.8 83.2 82.8 81.9 80.6 79.7 78.6 76.0 73.8 73.0 72.4 Gii idex Coast 0.653 0.654 0.666 0.680 0.701 0.720 0.730 0.747 0.755 0.744 0.722 Ilad 0.599 0.604 0.623 0.640 0.662 0.680 0.715 0.781 0.826 0.840 0.847 Spai 0.637 0.643 0.660 0.678 0.701 0.719 0.750 0.808 0.846 0.857 0.862 Teil idex Coast 0.814 0.816 0.848 0.888 0.958 1.026 1.072 1.148 1.205 1.165 1.088 Ilad 0.652 0.665 0.714 0.763 0.829 0.886 1.012 1.316 1.608 1.724 1.813 Spai 0.754 0.771 0.823 0.880 0.958 1.024 1.156 1.474 1.777 1.893 1.979 Note: Te coast is represeted by muicipalities wit direct access to te sea, a total of 460, represetig 7.0% of te total lad area. Te miimum value is sow i italics. Te maximum value is sow i bold. Source: INE ad autors ow calculatios. occurred witi a cotext of ig saturatio). I fact, tere were may coastal muicipalities i te first decades of te cetury, fisig villages wic at tat time ad o ecoomic future ad lost sigificat umbers of residets, but tat i te secod alf of te cetury became tourist uclei of te first order, wit large demograpic gais ([4], capter 4). Wat ca be clearly see is tat durig te secod alf of te 20 t cetury, te distributio of muicipal sizes is less cocetrated o te coast ta i Spai as a wole, altoug te average size is substatially iger (some five times iger). I te case of ilad muicipalities, dispersio as always bee lower ta tat of te coutry as a wole. over te wole period. Tus, o average, te cotrast betwee te coast ad te ilad areas gradually becomes sarper. Tese two groups of muicipalities sow little omogeeity ad marked iteral differeces. Te process of populatio cocetratio o te coast as teded to geerate a more omogeeous coastal area i a certai sese, 7 as opposed to a eterogeeous ilad area wit a few large uclei (essetially Madrid, its surroudigs ad provicial capitals) ad may less cosequetial muicipalities scattered across te rest of ilad Spai. Tus, wile Spai was already a coastal coutry i 1900, it is ow muc more so at te begiig of te 21 st cetury. Table 4. Decompositio of te Teil Idex (Mea Logaritmic Deviatio). Coastal-Ilad Classificatio (1900 2001) Compoet 1900 1910 1920 1930 1940 1950 1960 1970 1981 1991 2001 Iter-groups (Exteral) 0.093 0.097 0.102 0.110 0.122 0.130 0.141 0.168 0.191 0.200 0.207 % 12.3% 12.6% 12.4% 12.5% 12.7% 12.7% 12.2% 11.4% 10.8% 10.6% 10.4% Itra-groups (Iteral) 0.661 0.673 0.721 0.770 0.837 0.894 1.015 1.307 1.585 1.693 1.772 % 87.7% 87.4% 87.6% 87.5% 87.3% 87.3% 87.8% 88.6% 89.2% 89.4% 89.6% Total 0.754 0.771 0.823 0.880 0.958 1.024 1.156 1.474 1.777 1.893 1.979 % 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Note: Te miimum value is sow i italics. Te maximum value is sow i bold. Source: INE ad autors ow calculatios. Table 4 presets te decompositio of te Teil idex for te coastal ilad divisio. It is iterestig to ote ow bot compoets, iter- ad itra-groups, grow cotiuously 7 We migt call tis omogeously cocetrated. I 2001, 224 of te 460 coastal muicipalities ad over 10,000 iabitats ad were ome to 91.9%
Drivers of Agglomeratio: Geograpy vs History Te Ope Urba Studies Joural, 2009, Volume 2 35 Table 5. Populatio Distributio Accordig to Altitude (Spai 1900 2001) Spai Altitude Zoe 1900 1910 1920 1930 1940 1950 1960 1970 1981 1991 2001 Populatio % of total populatio Mea muicipal size Spai = 100 Gii idex Teil idex Below 200 m. 6,640,844 7,292,811 8,107,283 9,109,359 10,391,336 11,481,940 13,335,042 16,477,811 19,471,384 20,417,731 21,566,916 Betwee 200 ad 600 m Betwee 600 ad 1,000 m 5,655,262 6,101,241 6,477,095 6,860,610 7,289,642 7,545,305 7,827,727 7,675,204 7,969,112 8,133,878 8,568,007 5,588,569 5,981,234 6,428,681 7,034,791 7,682,780 8,108,491 8,625,042 9,116,379 9,603,782 9,720,458 10,118,650 Over 1,000 m 945,974 985,020 999,604 1,021,811 1,023,096 1,036,532 989,124 772,088 638,077 600,201 593,798 Below 200 m. 35.3% 35.8% 36.8% 37.9% 39.4% 40.8% 43.3% 48.4% 51.7% 52.5% 52.8% Betwee 200 ad 600 m Betwee 600 ad 1,000 m 30.0% 30.0% 29.4% 28.6% 27.6% 26.8% 25.4% 22.5% 21.1% 20.9% 21.0% 29.7% 29.4% 29.2% 29.3% 29.1% 28.8% 28.0% 26.8% 25.5% 25.0% 24.8% Over 1,000 m 5.0% 4.8% 4.5% 4.3% 3.9% 3.7% 3.2% 2.3% 1.7% 1.5% 1.5% Below 200 m. 4,941 5,426 6,032 6,778 7,732 8,543 9,922 12,260 14,488 15,192 16,047 Betwee 200 ad 600 m Betwee 600 ad 1,000 m 2,500 2,697 2,863 3,033 3,223 3,336 3,461 3,393 3,523 3,596 3,788 1,606 1,719 1,847 2,021 2,208 2,330 2,478 2,620 2,760 2,793 2,908 Over 1,000 m 926 964 978 1,000 1,001 1,014 968 755 624 587 581 Spai 2,322 2,511 2,715 2,963 3,254 3,475 3,796 4,199 4,648 4,794 5,038 Below 200 m. 212.8 216.1 222.2 228.7 237.6 245.9 261.4 292.0 311.7 316.9 318.5 Betwee 200 ad 600 m Betwee 600 ad 1,000 m 107.6 107.4 105.5 102.4 99.0 96.0 91.2 80.8 75.8 75.0 75.2 69.1 68.4 68.0 68.2 67.8 67.1 65.3 62.4 59.4 58.3 57.7 Over 1,000 m 39.9 38.4 36.0 33.7 30.8 29.2 25.5 18.0 13.4 12.2 11.5 Below 200 m. 0.671 0.672 0.685 0.698 0.720 0.739 0.753 0.776 0.791 0.788 0.777 Betwee 200 ad 600 m Betwee 600 ad 1,000 m 0.556 0.559 0.566 0.576 0.595 0.608 0.633 0.676 0.722 0.740 0.753 0.595 0.601 0.626 0.649 0.673 0.690 0.730 0.808 0.856 0.872 0.884 Over 1,000 m 0.486 0.487 0.499 0.513 0.526 0.544 0.570 0.641 0.710 0.739 0.765 Spai 0.637 0.643 0.660 0.678 0.701 0.719 0.750 0.808 0.846 0.857 0.862 Below 200 m. 0.879 0.889 0.930 0.978 1.058 1.136 1.208 1.338 1.452 1.456 1.414 Betwee 200 ad 600 m Betwee 600 ad 1,000 m 0.567 0.574 0.590 0.617 0.664 0.700 0.772 0.913 1.091 1.170 1.230 0.633 0.646 0.710 0.774 0.847 0.901 1.041 1.402 1.725 1.866 1.988 Over 1,000 m 0.396 0.399 0.420 0.446 0.475 0.513 0.569 0.761 0.995 1.101 1.208 Spai 0.754 0.771 0.823 0.880 0.958 1.024 1.156 1.474 1.777 1.893 1.979 Note: Te four altitude zoes are defied by te altitude of te correspodig muicipal capital. Te miimum value is sow i italics. Te maximum value is sow i bold. Source: INE ad autors ow calculatios. I additio, eormous iteral cages ave take place i te size structure alog te coast. Te Spais case is ot uique owever; te US also sows similar levels of coastal populatio cocetratio [30], ad altoug te istorical of all te populatio residig o te coast. I 1900, te situatio was of 67 muicipalities accommodatig 63.4% of te coastal populatio. processes tat ave led to tis situatio are very differet, te results appear to be quite similar. te Moutais to te Plais: Moutaious Spai We defie 4 altitude zoes: up to 200 metres (te plais, wic icludes muc of te coastal strip, but also te secod lie of coastal developmet ad te sores of may
36 Te Ope Urba Studies Joural, 2009, Volume 2 Goerlic ad Mas importat rivers suc as te Ebro or te Guadalquivir); from 200 to 600 metres; from 600 to 1,000 metres; ad above 1,000 metres (te moutais). Table 5 illustrates te gradual movemet of te populatio from te moutais to te plais. Populatio distributio teds to be polarised betwee te two extremes. O oe ad, te zoe coverig territories up to 200 metres above sea level accommodates a growig percetage of te populatio, exceedig 50% from 1981 owards (despite coverig a limited lad area of 16.6%); o te oter, moutai settlemets (above 1,000 metres) start off wit a very scat populatio i 1900 (5.0%, represetig somewat less ta oe millio iabitats), but after experiecig a sarp declie begiig i 1950 [31, 32] tey fall to a curret miimum bot i relative (1.5% of te populatio) ad absolute terms (below 600 tousad iabitats), despite te fact tat tree provicial capitals, Ávila, Segovia ad Soria, are located over 1,000 metres above sea level. Te two itermediate zoes, coverig 200 to 1,000 metres, begi te period wit very similar populatio figures ad, altoug tey gai umbers i absolute terms, tey lose to te plais i relative terms. O average, tese differeces ted to become accetuated, as sow by te mea muicipality sizes. I fact, from 1940 owards, te oly muicipalities wit mea sizes above te atioal average were tose located i te plais. I additio, a remarkable uiformity ca be observed: te iger above sea level te muicipality, te lower its mea size, a tedecy tat remais costat across all te periods aalysed. Evetually, ote tat te average size of muicipalities above 1.000 mts. are te oly oe tat presets a iverted U-sape, sowig a sligt tedecy to icrease teir populatio durig te first alf of te 20 t cetury, but a abrupt fall i te secod alf. Te last sectio of Table 5 presets te iequality idices for eac of te four altitude zoes. Tere is a clear tedecy towards cocetratio witi eac zoe; symptoms of stability oly emerge i te last decade for te plais muicipalities, altoug muc less perceivably ta te picture give i Table 3 for te coast. At te begiig of te 20 t cetury, te populatio cocetratio appears to be lower ta te atioal average i all zoes except te plais, below 200 metres. Over time, tis situatio cages suc tat by te ed of te cetury, te plais sow a lower cocetratio ta te atioal average. Tis result is similar to wat we ave observed o te coast, te process of displacemet towards te plais as teded to geerate a more omogeeous altitude zoe. Te opposite process ca be observed i te 600 to 1,000 metre zoe, wic appears to be were populatio cocetratio is most acute. Te decompositio of te Teil idex is preseted i Table 6. I additio to te geeralised growt of bot compoets, te iter-group compoet emerges as avig a greater relative importace, ad also sows a sligt tedecy to icrease. Te message is terefore tat classificatio of muicipalities by altitude zoes sows a lower degree of cotrast ta te coastal-ilad classificatio, all, as before, witi te cotext of a ig degree of saturatio i te lowest altitude zoe. THE RELEVANCE OF HISTORY Te importace of istory as a coditioig factor i future evolutio as bee igligted by umerous autors. For istace, Krugma [33] puts forward some very compellig examples. I te preset paper, we idetify two potetially coditioig factors i agglomeratio processes: 1. te selectio, at a certai momet i time, of a muicipality as te seat of political/admiistrative power by desigatig it a territorial capital, ad 2. te muicipality s capacity for agglomeratio i te past, for reasos tat are ot geerally explaied. Te Spais provices were created by te Royal Decree of 30 November 1833. Tis project, led by Javier de Burgos, created a decetralised state divided ito 49 provices. Te provices were kow by te ame of teir capital city (wit te exceptios of te provices of Navarra, Álava, Guipúzcoa ad Vizcaya wose capitals are i Pamploa, Vitoria, Sa Sebastiá ad Bilbao, respectively). Tis project was practically te same as tat of 1822, formulated followig te Riego coup durig te Trieio Liberal or tree years of Liberal rule (1820-1823). Te most substatial cages were te abrogatio of te provices of Calatayud, Villafraca ad Játiva, ad ame cages to oters, followig cages to teir capitals. Some provices appear for te first time i 1833, suc as Almería (separated from te Kigdom of Graada), Huelva (from te Kigdom of Seville), or Logroño, ad oters appear wit ew ames suc as Murcia or te Basque provices. Table 6. Decompositio of te Teil idex (Mea Logaritmic Deviatio). Classificatio by Altitude Zoes (1900 2001) Compoet 1900 1910 1920 1930 1940 1950 1960 1970 1981 1991 2001 Iter-groups (Exteral) 0.129 0.136 0.147 0.157 0.174 0.189 0.222 0.300 0.366 0.386 0.396 % 17.1% 17.6% 17.8% 17.9% 18.2% 18.5% 19.2% 20.4% 20.6% 20.4% 20.0% Itra-groups (Iteral) 0.625 0.635 0.676 0.723 0.784 0.835 0.934 1.174 1.411 1.507 1.583 % 82.9% 82.4% 82.2% 82.1% 81.8% 81.5% 80.8% 79.6% 79.4% 79.6% 80.0% Total 0.754 0.771 0.823 0.880 0.958 1.024 1.156 1.474 1.777 1.893 1.979 % 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Note: Te miimum value is sow i italics. Te maximum value is sow i bold. Source: INE ad autors ow calculatios.
Drivers of Agglomeratio: Geograpy vs History Te Ope Urba Studies Joural, 2009, Volume 2 37 Te provicial divisio proposed by Javier de Burgos was cosolidated ad cotiues today, wit oly a few exceptios of iterest. Te most oteworty is te divisio i 1927 of te provice of Sata Cruz de Teerife ito te two provices it as today, Las Palmas ad Sata Cruz. Te provicial capitals were immediately edowed wit basic govermet istitutios ad political eads were created at te same time. Cosequetly, te preset provicial capitals go back to at least te first tird of te 19 t cetury, ad were selected as suc at tat time because tey were te muicipalities wit te igest umber of iabitats i te provice. I oly seve provices as te capital ot bee te largest muicipality durig cesuses carried out i te 20 t cetury. Te most otable is Potevedra, wose capital, Potevedra, as always falle beid te muicipality of Vigo i terms of populatio 17.3% i 1900 to 34.1% i 2001. Te cocetratio idices reveal a iterestig patter. I relative terms, te cocetratio i te capitals sub-set is fairly stable. A sligt tedecy towards cocetratio persists util 1970, but te idices fall to levels sligtly below tose see at te begiig of te 20 t cetury. I cotrast, te cocetratio i te o-capital muicipalities group icreases trougout te wole period. I bot cases, te cocetratio i te two groups is always lower ta te overall cocetratio, wic is a cosequece of te eormous ad icreasig discrepacies betwee te mea sizes of te muicipalities i te two groups. Table 8 sows te decompositio of te Teil idex. Te iter-group compoet sows a icreasig tred util te seveties, followed by certai stability. Sice tis compoet Table 7. Populatio Cocetratio i Provicial Capitals (Spai 1900 2001) Spai Zoe 1900 1910 1920 1930 1940 1950 1960 1970 1981 1991 2001 Populatio Capitals 3,256,794 3,597,921 4,313,125 5,219,615 6,492,167 7,627,904 9,294,128 12,009,442 13,740,930 13,940,513 13,920,609 No-capitals 15,573,855 16,762,385 17,699,538 18,806,956 19,894,687 20,544,364 21,482,807 22,032,040 23,941,425 24,931,755 26,926,762 % of total populatio Capitals 17.3% 17.7% 19.6% 21.7% 24.6% 27.1% 30.2% 35.3% 36.5% 35.9% 34.1% No-capitals 82.7% 82.3% 80.4% 78.3% 75.4% 72.9% 69.8% 64.7% 63.5% 64.1% 65.9% Mea muicipal size Capitals 62,631 69,191 82,945 100,377 124,849 146,690 178,733 230,951 264,249 268,087 267,704 No-capitals 1,933 2,081 2,197 2,335 2,470 2,550 2,667 2,735 2,972 3,095 3,342 Spai 2,322 2,511 2,715 2,963 3,254 3,475 3,796 4,199 4,648 4,794 5,038 Spai = 100 Capitals 2,696.7 2,755.4 3,055.1 3,387.3 3,836.3 4,221.8 4,708.6 5,500.8 5,685.8 5,591.8 5,313.8 No-capitals 83.2 82.9 80.9 78.8 75.9 73.4 70.3 65.1 63.9 64.6 66.3 Gii idex Capitals 0.581 0.565 0.582 0.599 0.601 0.598 0.613 0.623 0.594 0.573 0.558 No-capitals 0.572 0.577 0.588 0.599 0.615 0.626 0.654 0.715 0.771 0.789 0.802 Spai 0.637 0.643 0.660 0.678 0.701 0.719 0.750 0.808 0.846 0.857 0.862 Teil idex Capitals 0.584 0.551 0.592 0.630 0.636 0.630 0.668 0.697 0.626 0.577 0.541 No-capitals 0.593 0.606 0.635 0.666 0.708 0.742 0.831 1.077 1.363 1.490 1.604 Spai 0.754 0.771 0.823 0.880 0.958 1.024 1.156 1.474 1.777 1.893 1.979 Note: Capitals are te provicial capitals icludig Ceuta ad Melilla, a total of 52 muicipalities represetig 3.1% of te total atioal lad surface area. Te miimum value is sow i italics. Te maximum value is sow i bold. Source: INE ad autors ow calculatios. size. Te oter cases are: Cádiz, wose largest muicipality as bee Jerez de la Frotera sice 1950; Ciudad Real, were te largest muicipality was Valdepeñas betwee 1900 ad 1930, ad Puertollao betwee 1950 ad 1981; Jaé, wose largest muicipality was Liares betwee 1900 ad 1930; Asturias, were Gijó was te largest muicipality i various years (1910, 1930, 1940, 1950, 1970, 1981, 1991 ad 2001); Tarragoa, were Reus was te largest muicipality i 1910 ad 1920; ad fially Toledo, were te capital lost groud to Talavera de la Reia betwee 1970 ad 2001. Table 7 provides te same iformatio as above, but for te divisio betwee provicial capitals ad o-capitals. Te populatio i te capitals more ta quadrupled durig te period aalysed, wic i tur as led te percetage of te populatio residig i provicial capitals to double, from is te idex applied to te mea values of te two groups, its evolutio is due to te growt of te large o-capital cities. However te itra-group compoet reveals a cotiued icreasig tred trougout te etire period, practically i lie wit te evolutio of te overall idex. 8 Te Importace of Iitial Coditios Te story of Caterie Evas, told by Krugma [33], perfectly describes wat for im ad may oter autors illustrates te importace of iitial coditios. I 1895 Caterie Evas was a adolescet livig i te small city of 8 It sould be remembered tat te itra-groups compoet i (4) is a weigted mea of te iequality idices of te differet groups, ad cosequetly, it is domiated by te o-capital group idex.
38 Te Ope Urba Studies Joural, 2009, Volume 2 Goerlic ad Mas Table 8. Decompositio of te Teil Idex (Mea Logaritmic Deviatio). Classificatio by Capitals-No-Capitals (1900 2001) Compoet 1900 1910 1920 1930 1940 1950 1960 1970 1981 1991 2001 Iter-groups (Exteral) 0.161 0.166 0.188 0.214 0.251 0.283 0.326 0.400 0.418 0.409 0.382 % 21.4% 21.5% 22.9% 24.4% 26.2% 27.7% 28.2% 27.1% 23.5% 21.6% 19.3% Itra-groups (Iteral) 0.593 0.605 0.635 0.666 0.707 0.741 0.830 1.074 1.358 1.484 1.597 % 78.6% 78.5% 77.1% 75.6% 73.8% 72.3% 71.8% 72.9% 76.5% 78.4% 80.7% Total 0.754 0.771 0.823 0.880 0.958 1.024 1.156 1.474 1.777 1.893 1.979 % 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% 100.0% Note:.Te miimum value is sow i italics. Te maximum value is sow i bold. Source: INE ad autors ow calculatios. Dalto i te state of Georgia. We Caterie made a rug as a weddig preset, tis apparetly trivial occurrece became te embryo of oe of te most importat carpet ad rug maufacturig cetres i te Uited States after te Secod World War. Tis story, togeter wit oters e relates, leads Krugma to coclude tat we oe tries to uderstad te reasos for tat localizatio, oe fids tat it ca be traced back to some seemigly trivial istorical accidet [33]. Oly troug te study of eac idividual case ca we attempt to idetify tis seemigly trivial istorical accidet. To gai a more aggregate picture, te importace of istory to te subsequet evolutio of a activity ad, ece, te settlemet of te populatio i a certai locatio, ca be approaced from various perspectives. I tis paper, we focus o two approaces. Te first is te calculatio of a simple correlatio coefficiet betwee te situatio i 1900 ad tat i 2001, eiter i absolute populatio figures or i rakigs. Table 9 sows tat for all te muicipalities cosidered, tis correlatio is extremely ig, 0.93 ad 0.80 i te case of levels ad rakigs respectively, eve i tis case wic spas a time iterval of over 100 years. te aggregate poit of view, persistece is terefore extremely marked. Te correlatios at a provicial level reveal tat persistece is geeralised. I terms of levels, correlatio coefficiets below 0.7 oly appear i tree provices, Cáceres, Guadalajara ad Soria. I terms of rakigs, oly four provices preset correlatio coefficiets below 0.6, Madrid, Las Palmas, Sata Cruz de Teerife ad Seville, wit a miimum coefficiet of 0.47. 9 Note tat, wit te exceptio of te two provices i te Caary Islads, oe of tese provices is o te coast. A alterative way of examiig tese results is by meas of a equatio tat relates te iitial populatio wit te subsequet growt rate. Tis is te -covergece (ucoditioal) equatio from te ecoomy of growt literature [34, 35]. A egative relatio betwee iitial size ad subsequet growt idicates covergece i muicipality sizes, i tat te smallest muicipalities ted to grow more ta te largest muicipalities. I cotrast, a positive relatio idicates divergece; te muicipalities tat started out large ted to grow more, o average, ta te 9 a statistical perspective, all tese coefficiets are, witout exceptio, igly sigificat uder te ull ypotesis of idepedece betwee iitial ad fial distributio. Hece, istory is importat, ad would seem to be very muc so. smaller oes, ad cosequetly, we ca observe a tedecy towards populatio cocetratio i a limited umber of localities, tose tat, broadly speakig, ad larger populatios at te begiig of te period. Usig logaritms for te etire period, we obtai, log(pob 2001 ) log(pob 1900 ) = ˆ + 0.3098 log(pob 1900 ) + û = 8,108 (5) (0.0159) R 2 = 0.090 were log(pob 2001 ) log(pob 1900 ) represets te average growt over te etire cetury. Te equatio is estimated by ordiary least squares ad te eteroskedasticity-robust stadard error [36] is give i paretesis. Fig. (1) illustrates regressio (5) ad sows te coefficiet of te iitial populatio to be positive ad igly sigificat (t-ratio 19.47). Tis result cofirms, from a alterative perspective, te tred towards populatio cocetratio i te same places tat were already importat at te begiig of te cetury, ad supports te otio of istory as a importat factor i te way te populatio settles across te territory. Te previous result is robust to various types of weigted least squares to correct te eteroskedasticity preset i te data. 10 GEOGRAPHY VERSUS HISTORY I te previous sectios, we ave reviewed te importace of geograpical ad political-istorical factors i populatio agglomeratio across a territory. As a sytesis, we ow preset two exercises tat illustrate te importace of tese factors. Te first is a aalysis of variace ad te secod, te estimatio of a coditioal covergece equatio. Te aalysis of variace cosiders te two geograpical factors: coast ad altitude, ad provicial capital status. Te followig equatio is estimated for eac cesus year 52 log(pob) = j P j + L + j A j + C + u (6) j=1 3 j=1 10 te time series poit of view, equatio (5) represets a ustable AR(1) process; i tis case te usual estimators do ot ave te appropriate properties to perform stadard iferece. However, te estimatio of (5) oly rests o te cross-sectio dimesio of our data ad is perfectly valid to perform te iferece preseted i te text. Work i progress sows (tetatively) tat te same qualitative results are obtaied we we use more complex dyamic pael teciques. I geeral terms, a tedecy towards divergece or cocetratio is observed.
Drivers of Agglomeratio: Geograpy vs History Te Ope Urba Studies Joural, 2009, Volume 2 39 Table 9. Correlatios Betwee te Muicipal Populatio i 1900 ad 2001 Provice Levels Rakigs 01 Álava 0.987 0.775 02 Albacete 0.800 0.803 03 Alicate/Alacat 0.872 0.845 04 Almería 0.786 0.755 05 Ávila 0.883 0.764 06 Badajoz 0.805 0.809 07 Balears (Illes) 0.960 0.805 08 Barceloa 0.970 0.723 09 Burgos 0.896 0.799 10 Cáceres 0.678 0.681 11 Cádiz 0.905 0.856 12 Castelló/Castelló 0.902 0.807 13 Ciudad Real 0.779 0.858 14 Córdoba 0.893 0.887 15 Coruña (A) 0.932 0.822 16 Cueca 0.822 0.842 17 Giroa 0.885 0.771 18 Graada 0.951 0.605 19 Guadalajara 0.654 0.698 20 Guipúzcoa 0.961 0.852 21 Huelva 0.758 0.799 22 Huesca 0.826 0.765 23 Jaé 0.835 0.887 24 Leó 0.815 0.684 25 Lleida 0.901 0.686 26 Rioja (La) 0.844 0.859 27 Lugo 0.738 0.678 28 Madrid 0.990 0.547 29 Málaga 0.961 0.872 30 Murcia 0.907 0.785 31 Navarra 0.890 0.735 32 Ourese 0.765 0.746 33 Asturias 0.789 0.866 34 Palecia 0.807 0.825 35 Palmas (Las) 0.973 0.555 36 Potevedra 0.835 0.693 37 Salamaca 0.897 0.653 38 Sta. Cruz de Teerife 0.917 0.530 39 Catabria 0.959 0.652 40 Segovia 0.910 0.723 41 Sevilla 0.970 0.468 42 Soria 0.591 0.804 43 Tarragoa 0.905 0.710 44 Teruel 0.831 0.807 45 Toledo 0.800 0.744 46 Valecia/Valècia 0.986 0.786 47 Valladolid 0.986 0.794 48 Vizcaya 0.951 0.678 49 Zamora 0.833 0.758 50 Zaragoza 0.986 0.792 51 Ceuta - - 52 Melilla - - España 0.931 0.804 Note: Te miimum value of eac provice is sow i italics. Te maximum value of eac provice is sow i bold. Source: INE ad autors ow calculatios. were L is a dummy variable tat takes te value of oe if te muicipality as direct sea access ad zero oterwise; A j are dummy variables tat take te value of oe if te muicipal capital as a altitude of 200 metres or below for j = 1, betwee 200 ad 600 metres for j = 2, betwee 600 ad 1,000 metres for j = 3, ad zero oterwise; C is a dummy variable tat takes te value of oe if te muicipality is a provicial capital ad zero oterwise; ad fially P j are dummy variables tat take te value of oe if te muicipality belogs to provice j = 1,2,,52, ad zero oterwise, ad is itroduced to capture eterogeeous beaviours i te differet provices. Tus, te referece category i equatio (6) is, for a give provice, a ilad muicipality, moutaious (te capital of wic lies over 1,000 metres above sea level) ad is ot a provicial capital. Te importace of populatio movemets from te ilad areas to te coast, from te moutais to te plais ad from te rural areas to te cities sould be expressed i positive, statistically sigificat estimates for te parameters, j ad. Furtermore, a icreasig tedecy i te estimates deotes te icreasig importace of tese attributes i te demograpic movemets. Tis sould be see as a average, ad does ot exclude specific cases of particular relevace. 11 Specifically, te cases of te cities of Madrid ad Barceloa sould be aalysed wit cautio. O oe ad, te pysical boudaries of tese muicipalities may be coditioig certai results, ad furtermore, tese cities already appear as exceptioal cases well before te 20 t cetury [7]. Te results of estimatig equatio (6), by ordiary least squares, are sow i Table 10. Te estimatios could ot be more coclusive. As oly dummy variables are used, te R 2 is moderately ig (betwee 42.3% ad 55.2%), but wat is more relevat is tat it sows a clearly icreasig tedecy, ad terefore te coast, low altitude ad status of provicial capital are factors of icreasig importace i explaiig te size of Spais muicipalities. Te results of te estimated coefficiets are also extremely revealig. All of tem are positive ad igly sigificat, 12 ad also sow te correct magitude. Te igest estimated coefficiet i all cases is for te capital status factor, ad te altitude factor coefficiets decrease evely wit icreased eigt above sea level towards te moutais. Moreover, ote tat te magitude of te coefficiets icreases cotiuously over time, ad all tem reac maximum values i 2001. Tis result simply idicates tat wile te tree idetifyig factors altitude, coastal locatio ad capital status- were importat at te begiig of te cetury, tey are eve more so today. Te secod exercise is te estimatio of a covergece equatio similar to (5) but coditioal o te tree compoets cosidered i te aalysis of variace (6). Te 11 I fact, tis type of regressio yields a large umber of wat statisticias call atypical observatios or outliers. However, tere is otig atypical i tis case, as tey are simply muicipalities tat, because of teir ow particular circumstaces, deviate widely from te average beaviour. Tese particular cases are wort studyig i teir ow rigt, but tey are ot cases tat must be statistically corrected to improve te fit of te equatio i questio. Te results of tis type of regressio sould be take as descriptive of average beaviour. 12 Te sigificace, ot sow ere, is obtaied from te eteroskedasticityrobust stadard errors [36]. Tis sigificace icreases over time ad te lowest t-ratio values are obtaied i 1900. Te lowest t-ratio is 5.33.