Market Potential and Distance Decay

Transcription

1 Maket Potential and Distance Decay Gowth and decline of sectos acoss locations in uban egions Johan Klaesson Böje Johansson CESIS and CEnSE Jönköping Intenational Business School and the Royal Institute of Technology Abstact This pape intoduces a model which identifies the economic activity of each local economy (location) and obseves the time distance between each pai of locations as well as the aveage time distance between sub locations in each local economy. The study focuses on five categoies of fims: knowledge-intensive and odinay business sevices, knowledgeintensive and odinay manufactuing, and household sevices. We model how these categoies incease and decease thei employment in each location in esponse to the location s maket potential. We also show how the location patten depends on each locations maket potential. In this endeavo we distinguish between demand and supply potential. In the econometic analysis the maket potential of each location is detemined endogenously, and this also makes it possible to detemine the geogaphic extension of uban egions. This execise also includes an endogenous detemination of secto-specific distance-decay paametes. The model succeeds in depicting the gadual incease of sevice activities in cetain locations and manufactuing activities in othes. Coesponding autho: Associate pofesso Johan Klaesson, Jonkoping Intenational Business School, Box 1026, Jonkoping, Sweden. johan.klaesson@ihh.hj.se JEL: C21, L84, R11, R12, R30

2 1 Intoduction Uban agglomeations diffe in size and follow diffeent pattens of gowth and decline. Agglomeation advantages ae peceived as a popety of uban egions that explains the existence and gowth of such egions. The concept is usually defined to compise both localization and ubanization extenalities, whee the latte signifies a concentation of divesified activities and the fome a cluste of divesified activities within a paticula industy o a naow goup of activities shaing simila inputs and/o outputs. The liteatue ecognizes both static and dynamic agglomeation advantages. The fist aspect efes to moe efficient esouce allocation obtained by a bette match between the skill pofiles of employees and qualification pofiles of job desciptions, and a iche set of oppotunities fo fims to buy inputs fom local supplies (Duanton and Puga, 2004; Rosenthal and Stange, 2004). The dynamic aspect efes to divesity of knowledge flows that can stimulate innovation activities and new fim fomation (Jacobs, 1984; Moetti, 2004). Negative agglomeation economies ae often ecognized as congestion and elevated land values. Following Fujita and Thisse (2002), the effect of inceasing agglomeation economies is pimaily eflected by inceasing land values. The pesence of agglomeation economies in an uban egion veifies itself in seveal attactiveness obsevations such as net in-migation, highe than aveage poductivity and wage levels and above aveage land values. As a ule, agglomeation economies ae assumed to incease as the size of city egion gows. In this pape we obseve that an uban egion (o city egion) has an inne stuctue of nodes and netwoks fo tanspot and contacts. We depict an uban egion as an integated constellation of dense concentations, efeed to as uban aeas o local economies. The typical case is that one of the uban aeas is lage than the othes an plays the ole of ubanegion cente, while being suounded by associated (neighboing) uban aeas of vaying size. The diffeent aeas ae affected by the egion s agglomeation economies in diffeent ways. In view of this, we intoduce the concept maket o agglomeation potential which is sepaated into an aea s demand and supply potential, whee these two potentials ae calculated fo each individual uban aea. We conside the location of five categoies of industies (and fims), subdivided into (i) knowledge-intensive business sevices (KIBS), (ii) odinay business sevices (OBS), (iii) knowledge-intensive manufactuing, (iv) odinay manufactuing, and (v) household sevices. A location is identified as a specific uban aea and the uban egion in which aea is embedded. The demand potential of a location is the distance-discounted demand in the paticula uban aea and in its neighboing uban aeas (local economies). The distancediscounting pocedue helps to sepaate accessible demand fom demand that is satisfied by supplies located in othe egions. In paticula cental-place system models ecognize sevice supply as an activity that has a majo pat of its custome contacts and sales inside the egion whee the supply activity is located (Beckmann, 1968, 1999), wheeas economic-base models assume that manufactuing fims typically have the majo pat of customes spead acoss othe egions (McCann, 2001). In view of this we examine how well the location of ou sectos can be explained by each uban aea s (i) local demand potential, and (ii) its inta-egional demand potential. We 2

3 examine especially the stength of this elation fo knowledge-intensive business sevices. Ou examination elates to obsevations made by Coffey and Polèse (1989), who claim that KIBS fims ae not likely to be located outside an uban egions cental uban aea. Refeing to Johansson and Klaesson (2011) also investigates how the location of jobs in diffeent sectos esponds to each uban aea s local and inta-egional demand potential. The main hypothesis is that KIBS fims have stong esponse of this type, based on the fact that these fims have all fims as customes, and that these fims delive thei sevices with a face-toface technology. Ou second pespective is elated to the ole played KIBS fims as supplies of divesified sevice inputs to all fims and especially to knowledge-intensive custome fims. In this case we detemine fo each uban aea its supply potential in (i) the own local economy and in (ii) the est of the own uban egion. Now the angle is changed such that the supply potential of an uban egion consists of the distance-discounted access to KIBS supply in the own local economy, and in the est of local economies in the own uban egion. With this setting we estimate fo ou diffeent sectos how thei location depends on the supply potential, and how the secto location changes in esponse to the supply potential. This fom of conditioned esponse to the business-sevice supply is analyzed in Andesson (2006), whee the conclusion is that manufactuing jobs ae attacted business-sevice supply potential. The pape is outlined as follows. Section 2 pesents a famewok fo analyzing how a sevice-supplie s demand potential vaies acoss altenative locations in an uban egion, and how a sevice-buying custome s accessible sevice-supply potential vaies ove diffeent locations in an uban egion. In addition the section suggest a method to endogenously detemine the time-distance sensitivity which affects fo each location the size of the petaining demand and supply potential. Section 3 shows how the concepts of demand and supply potential can be elated to dynamics associated with New Economic Geogaphy and its concepts home maket effect and poductivity effects of divesified business sevice inputs (Fujita and Thisse, 2002). Section 4 pesents desciptive statistics and estimation method, followed by econometic esults in Section 5. Section 6 concludes. Outline 2 Reseach Questions and Pevious Studies 2.1 Business and Household Sevices in Uban Agglomeations Following suggestions in Anas, Anott and Small (1998), we conside an uban egion as a complex stuctue with seveal centes of vaying size. This appoach implies that one may identify factal self-similaity between a cente and its sub centes. Howeve, in this study we constain the stuctual decomposition of an uban egion into (i) its lagest uban aea (called cental uban aea), and (ii) its attached uban aeas, whee the time distance between aeas is small enough to allow fo fequent commuting and face-to face contacts. We use two complementay fugal models. In the fist model supplies of sevices in an uban egion make choices about location and output capacity, and those choices depend on each supplie s distance-discounted access to demand (demand accessibility). Inceased access to 3

4 demand stimulates diffeentiation of sevice supply. In the second model all fims make location and output choices that depend on the each fim s distance-discounted access to the supply of business/poduce sevices. With this appoach we ty to shed light on a twoponged eseach question associated with New Economic Geogaphy (NEG). Fist, we povide an explanation of the stuctue of an uban agglomeation, descibing whee fims in diffeent sectos have decided to locate thei activities, anging fom sevice supply to manufactuing poducts. Second, we conside a model fomulation that implies that agglomeation economies ae associated with a dispopotionate expansion of jobs in knowledge-intensive poduce sevices and household sevices. The inceased divesity that follows such an expansion is efeed to in the liteatue as the Jacobs hypothesis (Jacobs, 1984). An extension of Jacobs hypothesis is found in models in which inceasing etuns in an uban egion ae assumed to be geneated by a divesified monopolistic-competition industy in the egion poducing a vaiety of intemediate inputs, whee the multiplicity of diffeentiated inputs aise the poductivity of fims using the inputs. Poponents of this appoach to identify the causes of agglomeation economies ae Matsuyama (1995), Rivea-Batiz (1988), Fujita and Thisse (2002). In the subsequent pesentation we suggest that local business-sevice supplies have the descibed poductivity effect on expot-oiented manufactuing fims in each uban egion. The cucial mechanism is that inceasing sevice supply also implies inceasing diffeentiation of accessible sevices, and boade scope of diffeentiation enables fims to enhance thei poductivity and expand thei output. Fo supplies of business sevices we stess that the petinent fims make location decisions that conside the size of the demand potential associated with thei espective location. A simila agument applies to supplies of household sevices (Fujita and Thisse, 2002). Also fo these supplies the distance-discounted demand affect thei evenues and possibility to suvive. Moeove, as the divesity of household sevices in an agglomeation inceases, new households ae attacted to the agglomeation, which implies that uban agglomeation stimulates expansion of both labo supply and job demand. In view of this, we have stong easons to compae the ole of poduce and consume sevices in the pocess of agglomeation dynamics. In a ecent pape Johansson and Klaesson (2011) pesent a model depicting how the change of business-sevice supply in each uban aea esponds to the aea s maket potential, sub divided into local, inta-egional and exta-egional maket potential. The empiical esult, based on a non-linea specification, indicates that business-sevice supply gows as the local and inta-egional maket potential becomes sufficiently lage. In contadistinction, othe sectos of the economy exhibit a diffeent patten of location change. The ambition in Johansson and Klaesson is to examine how location decisions made by a business-sevice fim ae influenced by the fim s demand potential (access to custome demand). In Johansson, Johansson and Wallin (2013), the second pespective is accentuated by showing that the development of new expot poducts is positively stimulated by knowledge flows associated with the distance-discounted access to supply of knowledgeintensive business sevices. In this pespective the focus is on how knowledge milieu of an uban egion can augment knowledge ceation and innovation, following suggestions in Feldman and Audetsch (1999) and Fujita and Thisse (2002). 4

5 2.2 Accessibility Stuctues of Uban Agglomeations Following the liteatue pesented in the peceding sub section, this pape pesents a model of the stuctue of an uban egion, composed by uban aeas (uban centes o locations), signified by and s as indexes. Conside that is any uban aea in an uban egion R. Then s R() denotes a neighboing uban aea, s, in the same egion as. The inteaction between two uban aeas, and s, is assumed to be influenced by the time distance, t s, between the aeas, while the inteaction inside an uban aea is influenced by the aveage distance, t, between zones inside aea. Conside now the categoy of fims whee each fim pimaily supplies its output to local and inta-egional customes. A majo pat of these fims ae sevice supplies. Fo these fims we may define thei local maket o demand potential, M, and thei inta-egional maket MR potential, R () 1, in the following way: MR exp t W (2.1) MR exp t W (2.2) R( ) 2 s s s R() W s epesents the custome demand in aea s, 2 exp ts s whee is the inta-egional time sensitivity fo supplie-custome inteaction, and whee 2 W is the distance-discounted demand oiginating in aea s. Moeove, 1 is the local time sensitivity fo supplie-custome inteaction inside uban aea. We note that if a fim s sales to customes in aea s ae popotional to exp 2ts W, s the sales will educe as 2 attains highe values and as ts inceases. Pevious studies indicate that 2 1 (Johansson, Klaesson and Olsson, 2003). A simila specification of maket potential as in (2.1) and (2.2) was poposed in Lakshmanan and Hansen (1965). The two fomulas ae intepeted as accessibility measues in Weibull (1976), and seveal scholas have shown that the type of measues given in (2.1) and (2.2) can be deived fom andom choice theoy (e.g. Mattson, 1984; Johansson and Klaesson, 2011). As the next step we tun to individual fims poximity to supplies of local inputs, especially sevice supplies. Thus, we conside how a paticula fim s oppotunities to find a desiable composition of local inputs depend on the distance-discounted supply of input altenatives. To captue how a fim s location in an uban egion affects its poductivity we intoduce the concept of the fim s input-supply potential o just supply potential. In this case we focus on the supply potential associated with business-sevice supply. By analogy with ou discussion of the demand potential, a fim in an uban egion has a local supply potential, S and an inta-egional supply potential, SR () specified in fomulas (2.3) and (2.4). S exp t V (2.3) 1 5

6 S exp t V (2.4) R( ) 2 s s s R() whee V s denotes the supply of business sevices in uban aea s, and whee 1 and 2 denote local and inta-egional time sensitivity, espectively. In view of the theoetical suggestion fom pevious liteatue we may conjectue that fims in uban egion will expeience inceasing etuns fom an expansion of S and S R (). Sub section 2.2 suggests (fo each uban egion) that thee is a coupling between the size of the demand potential of business-sevice fims and the sevice-supply potential diected towads sevice-puchasing fims. Such a coupling indicates the possibility of cumulative dynamics as descibed in Figue 1. Demand potential of sevice supplies in an uban egion Inceasing the poductivity of fims in the egion Attaction of sevice supplies to locate and expand in the egion Supply potential offeed buyes of business sevices in the egion Figue 1: Pesence of cumulative dynamics affecting uban gowth an decline 2.3 Endogenous Detemination of Time Sensitivity In a sequence of papes the authos have pesented and estimated paameteized models using accessibility measues of the kind specified in (2.1)-(2.4) (Johansson, Klaesson and Olsson, 2002 and 2003; Johansson and Klaesson 2011). In these contibutions the -values have been impoted fom estimations based on modes of individuals labo commuting behavio. In the pesent pape the time-sensitivity paamete is detemined endogenously as an integal pat of the egession appoach. We conside five diffeent secto aggegates, and fo each secto we obseve the numbe of jobs, denoted by E. The sectos ae KIBS, OBS, household sevices, knowledge-intensive manufactuing and odinay manufactuing. All these sectos will be compaed with egad to how thei location is explained by (i) thei demand potentials M and M R () and by (ii) thei 6

7 S supply potentials S and R (). In addition, we investigate how the numbe of jobs in each uban aea can be explained by each aea s demand and supply potentials. At this stage we emphasize that each of the fou measues M ( 1) M R ( )( 2), S ( 1) and ae all functions of the diffeent time-sensitivity paametes. At the same time we S ( ) R ( ) 2 want to avoid using exogenous values. Instead we intend to detemine the diffeent values as an integal pat of the entie estimation pocedue. This is done by unning ou egessions fo systematically adjusted values to finally settle with the egession that maximizes R-squae. We fist outline the pocedue fo a egession model in which the dependent vaiable is the numbe of KIBS-jobs, E, in each uban aea. The egession equation is specified to geneate paametes that have the fom of elasticities. When the explanatoy vaiables ae the local and inta-egional demand potentials, the following specification applies: lne ln M ( ) ln M ( ) x (2.5) R( ) 2 whee is an eo tem and whee we note that we can apply the appoach in (2.5) fo all five sectos and then compae the - and - paametes fo all five secto aggegates. The patten of job location can accoding to ou famewok also be influenced by the businesssevice supply potentials, and fo this pupose we estimate the following egession equation fo all secto aggegates except the KIBS-secto: lne ln S ( ) ln S ( ) (2.6) R( ) 2 The egession esults associated with equations (2.5) and (2.6) invites to intepet the estimated x -values as the geneal business-inteaction fiction, wheeas the associated - paametes infom about the stength of each secto s esponse to the fiction patten. The two equations (2.5) and (2.6) efe to the patten job location at paticula points in time and hence the estimates povide a static pictue. Now, ou setting opens the possibility to also depict the change pocess between time t and t +, conditioned values of demand potentials and supply potential at date t. This gives us the following two sets of change-pocess egession equations as specified in (2.7) and (2.8): ln( E / E ) ln M ( ) ln M ( ) (2.7), t, t 1, t 1 2 R( ), t 2 ln( E / E ) ln S ( ) ln S ( ) (2.8), t, t 1, t 1 2 R( ), t 2 The system in (2.5)-(2.8) makes it possible to examine and discuss to what extent the accessibility stuctue of a location affects the location patten in a simila way fo ou diffeent sectos of the economy. In addition, the fou equations can be applied with sepaate egessions fo the 72 cental (lagest) uban aeas and fo the goup of othe aeas. Such an execise can eveal if the cental uban aeas play a diffeent ole in the detemination of secto location. 7

8 3 Refeence Models of Agglomeative Foces In the pevious pesentation we have efeed to two diffeent contibutions of New Economic Geogaphy (NEG). The fist one has become the tade mak of Kugman (1991) and emphasizes the home maket effect, which coesponds to ou concept demandpotential effect. The second contibution addesses the impotance fo a fim (and a secto) to have access of a ich vaiety of diffeentiated sevice inputs. Such divesity is consideed to incease poductivity (Quigley, 1998; Rivea-Batiz, 1988) and coesponds to ou concept supply-potential effect. In this section the two NEG contibutions ae futhe discussed by means of two efeence models one fo the demand potential and the othe fo the supply potential. 3.1 Demand Potential of Locations in an Uban Region We conside a fim in location that supplies local sevices to customes in location and in locations s that ae embedded in the same uban egion as. The sevice fims supply diffeentiated poducts in a monopolistic-competition famewok. Ou stylized model depicts a vaiety goup whee each fim poduces an idiosyncatic vaiety, whee all fims that supply a vaiety belonging to the goup have simila demand and cost conditions. We conside a typical fim in supplying vaiety i, while facing the following demand, x i, as deived in Andesson and Johansson (2012) fom CES demand conditions: x G( M, M ) p (3.1) i i i R() i whee p is the pice chaged, i the vaiety goup, i is the common pice elasticity that applies to all vaieties in is a vaiable that educes as the numbe of vaieties in the vaiety goup M and M ae defined in (2.1)-(2.2). inceases, and whee the two demand potentials R() With the demand function in (3.1), the optimal pice fo all vaieties in the vaiety goup becomes p /( 1) v, whee v is the vaiable cost pe unit output that applies to all vaieties in the same goup. Moeove, each fim has a fixed cost F, which implies that a feasible maket solution p v F / x i (3.2) whee epesents land-value costs pe unit output associated with a location in. Fom (3.1) it is obvious that fo sufficiently small elasticity values, x i will get lage as the pice is inceased. Inspecting (3.2), we can see that as x i gows F/ x i becomes smalle and thus thee exists a feasible solution. The cucial agument now is that as the demand potentials M and MR() gow, Gi ( M, M R() ) will gow and xi can get lage. Howeve, with fee enty, this expansion will mateialize in an inceasing numbe of vaieties that can satisfy the feasibility condition in (3.2). The equilibium numbe of vaieties obtain when (3.2) is satisfied as an equality. We may also obseve that conventional land-value models pedict 8

9 that is a positive function of both M and R (), eflecting that many fims want to locate in places whee Gi ( M, MR() ) is lage. M 3.2 Supply Potential of Locations in an Uban Region In this subsection we outline a pespective in which the location of KIBS fims is taken as given at each point in time. Each such fim has a location o s R() and supplies an intemediay sevice input i. Conside then a secto located in which uses each input in popotion to the accessible supply as given by (2.3)-(2.4). We assume that each sevice fim i poduces the amount q, which means that Vs nsq detemines the numbe of sevice vaieties supplied in location s. Fom this we can detemine the values Si S / n and S S / n and then intoduce the assumption (Fujita and Thisse, 2002) that the jr( ) R( ) R( ) poductivity, Q of the secto in is positively affected by input divesity as expessed in the following fomula: 1/ i jr() i j 1/ Q S S (3.3) Given the poductivity- enhancing mechanism in (3.3) we can also conclude that sectos will be attacted to locate in an aea with high values on the supply potentials S and S R (). This agglomeation foce epesents the second feedback that is illustated in Figuen1. In summay, sectos ae attacted to locate and expand in uban aeas with highe than aveage supply potential, and when such sectos gow they stimulate additional sevice-poducing fims to opeate in the same uban aea. When density gets highe, the accessibility advantage may educe, based on inceased time distances, and in this way gowth in cetain aeas may come to a halt. One may emak that the supply capacity of business sevices is measued empiically by obseving the numbe of jobs which may consideed as a cude measue. An altenative would be to weigh jobs by using infomation about wage levels fo diffeent jobs. 4 Data, Desciptive Statistics and Method 4.1 Geogaphy of Uban Aeas and Regions The empiical analysis is based on obsevations of uban aeas, which coespond to local govenment aeas called municipalities. The time span of obsevations is and the numbe of municipalities is 290. The analysis employs a time distance matix which infoms about the tavel time by ca between each pai of uban aeas. In addition, thee is infomation about the aveage time distance between zones in each uban ae. 9

10 Uban aeas ae gouped into 72 uban egions, which ae delineated on the basis of time distances and commuting flows. Thee uban egions (Stockholm, Gothenbug and Malmö) ae labeled lage, with moe than one million inhabitants. Anothe set of egions ae classified as medium-sized, with moe than and less than inhabitants. The emaining 49 egions ae ecognized as small. Table 1 povides an oveview of population change in the peiod The pictue is clea: Lage (metopolitan) egions have gown by moe than 8 pe cent, medium-sized egions have gown modeately and small egions have as goup declined. Table 1: Development of population between 2000 and 2008 in thee categoies of egions Change Change % Lage Medium Small Total Souce: Statistics Sweden Demand and supply potentials ae both positively elated to the population size of uban egions. In view of this we may emak that uban gowth is clealy coelated as illustated in Figue 2, whee the gowth between 2000 and 2008 is egessed against the population size at the beginning of the peiod. Figue 2: Relationship between egional size and gowth (Souce: Statistics Sweden) 10

11 4.2 Secto Aggegates and Secto Chaacteistics In the empiical study, the economy of each uban aea is divided into five secto aggegates as descibed in Table 2. Ou main focus is on knowledge-intensive business sevices (KIBS) and knowledge-intensive manufactuing, whee KIBS ae assumed to locate and develop in esponse to the size of the demand potentials based on all sectos of the economy, aguing that all fims ae KIBS-secto customes. Knowledge-intensive manufactuing is instead assumed to be dependent on the KIBS-based supply potential, eflection outsoucing of knowledge-based development activities supplied by KIBS-fims. A thid issue is find out similaities between business and household sevices in thei esponse to accessibility stuctues in uban aeas. Table 2: Composition of secto aggegates Secto aggegates Activities Knowledge intensive business Legal activities, Compute and elated activities, Reseach and sevices development, Insuance and banking Less knowledge intensive Renting of machiney, Auxiliay tanspot activities, Wholesale, business sevices Real Estate, Education Household sevices Hotels and estauants, Retail, Health and social wok Knowledge intensive Chemicals, Computes and telecom, Pecision instuments, manufactuing Phamaceuticals Less knowledge intensive manufactuing Rest of the economy Souce: Statistics Sweden Wood, Metal, Food and beveages, Plastics Agicultue, Constuction, Mining, Wate supply Table 3 pesents the elative size of the five secto aggegates in the entie Swedish economy. In sectos that ae classified as knowledge intensive moe than 30 pe cent of the employment have at least thee yeas of univesity studies. Fo household sevices thee is a maked diffeence maximum and minimum values among obsevations. Table 3: Employment shaes fo five sectos of the Swedish economy 2000 and Absolute change Change in % Knowledge intensive business sevices Less knowledge intensive business sevices Household sevices Knowledge intensive manufactuing Less knowledge intensive manufactuing

12 Rest of the economy Total Souce: Statistics Sweden Table 4 pesents the same type of infomation as found in Table 3, but now with obsevations specified fo each type of uban egion. Thee ae thee stuctual changes. Fist, the numbe of pesons employed in manufactuing industies educes in a maked way: Second, the employment in KIBS-fims incease fast, Thid, thee is a consideable incease of jobs in household sevices, whee much of the gowth takes place in the thee lagest uban egions. Table 4: Secto gowth by egional categoy (pecentage gowth in paenthesis) Region type Lage Medium Small Total Knowledge intensive business sevices (24.4) (34.1) 9187 (31.3) (27.4) Less knowledge intensive business sevices (4.0) 3200 (2.0) 1496 (3.5) (3.4) Household sevices (18.3) (11.4) (5.8) (13.8) Knowledge intensive manufactuing (-17.1) (-31.1) (-20.2) (-22.2) Less knowledge intensive manufactuing (-5.0) (-7.5) (-5.5) (-6.4) Rest of the economy 6467 (3.4) Souce: Statistics Sweden (13.2) (14.7) (9.0) 4.3 Specification of Dependent and Independent Vaiables and Intepetations In the empiical analysis a basic distinction is made between the 72 cental and 218 noncental uban aeas, by making sepaate egessions fo these two goups. A stuctual diffeence between the two goups is that fo a cental uban aea M (local demand potential) is lage elative to M R () (inta-egional demand potential), wheeas the opposite applies fo non-cental uban aeas. Fo each of ou two goups of uban aeas we have two sets of dependent vaiables, descibing (i) location patten and (ii) location dynamics, espectively. The fist set contains 12

13 the numbe of jobs in each uban aea with egad to five secto aggegates, epesented by E,, E, whee E is the numbe of secto k jobs in aea and whee k =1 efes to the 1 5 k KIBS secto, and whee all secto numbes ae given in Table 4. The egessions which aim at explaining the E-values ae caied out fo k = 1,,5. Regession equations have lne k as dependent vaiable. The second set of dependent vaiables contains indicatos intended to depict the location k k dynamics. These indicatos ae epesented by ln( E ( t )/ E ( t )), whee t = 2000, 8 and k = 1,,5. This implies that the indicato descibes the change of jobs fo an eight yeas peiod, and the change is measued as a gowth ate. The fist objective is to match the vaiables 1 1 E,, 5 E against the demand potentials s R() M exp t W and MR( ) exp 2ts W s which both eflect the distancediscounted value of the wage sum in aea and in the othe aeas in the same egion. We fist obseve that the wage sum eflects the puchasing powe of each uban aea, and that it fo most uban aeas is appoximately popotional to goss egional poduct of each aea. This a elevant agument fo the KIBS-secto which has all fims in each local economy as possible customes, wheeas this does not apply to the manufactuing secto. The wage sum is assumed to captue the size of potential custome demand (the size of the economy in the uban aea). Fo the secto of KIBS-supplies this is obviously a meaningful demand indicato, implying that KIBS-supplies ae attacted to locate in aea in popotion to the size of M exp 1t W and MR( ) exp 2ts W s, whee W s is the wage s R() sum in uban aea s. Given this, we apply the same egessions to secto 2, 3, 4 and 5 in ode to compae estimation esult acoss all five sectos. The main inteest is howeve to explain the tempoay (static) location patten of KIBS-supply. The second objective is to examine fo the KIBS-secto how the change indicato esponds to the local and inta-egional demand potentials. In othe wods, in this case we investigate to which extent the change pocess can be explained by same independent vaiables as those that we have used to explain the location patten. We may obseve that the local and intaegional demand potential ae in a fundamental way essential fo fims in the sectos KIBS, OBS, and household sevices. Hence, the gowth of jobs in these sectos is in tivial way affected by the size of M and M R (). The location change of manufactuing jobs may be coelated with these measues as an indiect effect of the fact that the KIBS-supply potential in aea is high when M and M R () have high values. Thus, a spuious coelation. The second objective of the study is to show that the KIBS-supply potentials of each aea function as an additional agglomeation facto that affects the location patten, E,, E, k k and the location change, ln( E ( t )/ E ( t)) fo k = 2,,5. We obseve that since the KIBS-secto supply is an explanatoy facto, it is not included in the set of dependent vaiables

14 Fo each uban aea, the local and the inta-egional supply potentials ae given by the following two expessions: 1 s R() S exp t V and SR( ) exp 2t s V s. The nondiscounted KIBS-supply capacity in uban aea s is given by V s. How can we obseve and measue this capacity? Thee ae two altenatives in the data set that has been available fo this study: V s can, fo uban aea s, epesent eithe the wage sum o the numbe of jobs of KIBS fims. We think that the latte may bette eflect the KIBS-supply capacity. 4.4 Estimation Method and Hypotheses The equations too be estimated ae intoduce in fomulas (2.5)-(2.8). The equations will hee be specified in moe detail to claify the estimation pocedue. The location-patten equations efe to one point in time (t = 2008) and have the following specification: Location patten, demand potential: lne ln M ( ) ln M ( ), k = 1,,5 (2.5 ) k k k k k k R( ) 2 Location patten, supply potential: lne ln S ( ) ln S ( ), k = 2,..,5 (2.6 ) k k k k k k R( ) 2 Regessions ae caied out fo each secto k sepaately. Each egession is made fo a given pai ( k 1, k 2 ), and then the egessions fo new -pais until the objective of a maximized value of R-squae is eached. As a consequence, the -pais may vay between sectos. The constaints applied to the optimization pocedue compise: (i) k 2 > k 1 > 0, (ii) k 1 > k 2 > 0. In case multiple optima ae pesent, these constaints seve to pevent the appeaance of optima that ae not meaningful accoding to location theoy. Fo the location change pocess we consult equations (2.7) and (2.8) which ae e-specified as follows: Location change, demand potential: ln( E / E ) ln M ( ) ln M ( ), k = 1,,5 (2.7 ) k k k k k k k, t, t 1, t 1 2 R( ), t 2 Location change, supply potential: ln( E / E ) ln S ( ) ln S ( ), k = 2,..,5 (2.8 ) k k k k k k k, t t 1, t 1 2 R( ), t 2 The estimation pocedue is the same fo the location-change egessions as fo the location patten egessions, with simila constaints guiding the seach fo optimal -pais. What do we expect? Fist, we would like to find that acoss all egessions the pais ( k 1, k 2 ) emain appoximately invaiant. Second, we would like to see that fo each of the two types of 1 demand-potential egessions the KIBS-secto has highe 1 - and 1 2 -paametes than any othe secto k = 2,,5. Moeove, we would expect that manufactuing has highe supplypotential and 1 2 -paametes than othe sectos. 14

15 5 Regession Results and Intepetation KIBS = Knowledge intensive business sevices LKIBS = Less knowledge intensive business sevices HS = Household sevices KIM = Knowledge intensive manufactuing LKIM = Less knowledge intensive manufactuing Table X.X: Cental uban aeas: Maket potential explaining the location of economic sectos KIBS LKIBS HS KIM LKIM Intecept (t=) (-7.49) (-5.58) (19.11) (-3.38) (-4.94) Local (t=) (36.11) (37.97) (56.37) (12.77) (20.71) Regional (t=) (-4.09) (-0.75) (-4.49) (0.42) (5.03) R Lambda Lambda Table X.X: Non-cental uban aeas: Maket potential explaining the location of economic sectos KIBS LKIBS HS KIM LKIM Intecept (t=) (-8.58) (-7.64) (10.64) (-6.61) (13.99) Local (t=) (24.36) (32.96) (41.27) (13.05) (15.62) Regional (t=) (5.08) (6.40) (-2.06) (-0.51) (-9.78) R

16 Lambda Lambda Table X.X: Cental uban aeas: Maket potential explaining the gowth of economic sectos KIBS LKIBS HS KIM LKIM Intecept (t=) (5.33) (-4.50) (-2.20) (-2.72) (-2.61) Local (t=) (-3.25) (3.29) (0.45) (1.29) Regional (t=) (1.66) (-0.70) (1.10) (1.70) (0.39) R Lambda Lambda Table X.X: Non-cental uban aeas: Maket potential explaining the gowth of economic sectos KIBS LKIBS HS KIM LKIM Intecept (t=) (5.14) (-3.05) (2.51) (0.70) (-2.83) Local (t=) (-0.26) (3.41) (1.53) (-2.48) (0.27) Regional (t=) (-1.21) (-1.40) (6.89) (2.19) (2.04) R Lambda Lambda Table X.X: Cental uban aeas: Supply potential explaining the location of economic sectos KIBS LKIBS HS KIM LKIM Intecept (t=) (-6.93) (11.37) (37.74) (2.58) (38.47) Local (t=) (xxxx) (32.34) (35.74) (14.97) (16.45) Regional xxxx xxxx (t=) (-2.05) (1.26) (0.67) (-0.44) (1.70) 16

17 R Lambda Lambda Table X.X: Non-cental uban aeas: Supply potential explaining the location of economic sectos KIBS LKIBS HS KIM LKIM Intecept (t=) (-10.4) (8.17) (34.5) (2.34) (28.60) Local (t=) (xxxx) (19.49) (25.14) (11.76) (8.05) Regional (t=) (-6.69) (4.45) (-2.91) (-1.68) (-5.94) R Lambda Lambda Table X.X: Cental uban aeas: Supply potential explaining the gowth of economic sectos KIBS LKIBS HS KIM LKIM Intecept (t=) (7.73) (-1.89) (-2.15) (-3.01) (-2.66) Local (t=) (-4.66) (4.4) (3.03) (0.57) (1.28) Regional (t=) (2.21) (1.83) (0.75) (1.62) (0.29) R Lambda Lambda Table X.X: Non-cental uban aeas: Supply potential explaining the gowth of economic sectos KIBS LKIBS HS KIM LKIM Intecept (t=) (4.92) (-2.03) (2.73) (-0.23) (-3.16) Local (t=) (-4.53) (1.22) (1.95) (-2.60) (0.78) Regional (t=) (2.25) (1.60) (5.73) (2.38) (2.10) R

18 Lambda Lambda

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