The sources of the urban wage premium by worker skills: Spatial sorting or agglomeration economies? *

Transcription

1 doi: /pis The souces of the uban wage pemium by woke skills: Spatial soting o agglomeation economies? * Matin Andesson 1, Johan Klaesson 2, Johan P Lasson 2 1 Cente fo Innovation, Reseach and Competence in the Leaning Economy (CIRCLE), Lund Univesity and the School of Management, Blekinge Institute of Technology (BTH) ( matin.andesson@cicle.lu.se) 2 Depatment of Economics, Finance and Statistics, Jönköping Intenational Business School (JIBS), Jönköping ( johan.klaesson@ihh.hj.se, johan.p.lasson@ihh.hj.se) Received: 1 Mach 2012 / Accepted: 19 Januay 2013 Abstact. We estimate the espective impotance of spatial soting and agglomeation economies in explaining the uban wage pemium fo wokes with diffeent sets of skills. Soting is the main souce of the wage pemium. Agglomeation economies ae in geneal small, but ae lage fo wokes with skills associated with non-outine job tasks. They also appea to involve human capital accumulation, as evidenced by the change in the wage of wokes moving away fom dense egions. Fo wokes with outine jobs, agglomeation economies ae vitually nonexistent. Ou esults povide futhe evidence of spatial density binging about poductivity advantages pimaily in contexts when poblem-solving and inteaction with othes ae impotant. JEL classification: R12, R23, J24, J31 Key wods: Spatial soting, agglomeation economies, leaning, skills, spatial wage dispaities, density, innovation 1 Intoduction Wokes in uban aeas of high spatial economic density ean highe wages than thei countepats in ual and moe spasely populated egions. Glaese and Maé (2001) epot that wages of uban wokes in the United States ae about 33 pe cent highe than thei non-uban countepats. Combes et al. (2008) epot that aveage wages in Pais ae about 15 pe cent highe compaed to othe lage Fench cities, 35 pe cent highe than in mid-sized cities and as much as 60 pe cent highe than in the ual aeas of Fance. The empiical egulaities of this kind ae geneally efeed to as the uban wage pemium (UWP). * We ae gateful fo constuctive comments fom thee anonymous eviewes which impoved the pape, as well as fom semina paticipants at the Max Planck Institute in Jena, CIRCLE at Lund Univesity and the Jönköping Intenational Business school. We also wish to thank Kataina Nilsson Hakkala (Aalto Univesity), Fedik Heyman (IFN) and Fedik Sjöholm (Lund Univesity) fo shaing thei data on non-outine job tasks by occupations. Matin Andesson acknowledges financial suppot fom the Swedish eseach council FORMAS (Dn ), as well as the Swedish Reseach Council (Linnaeus Gant No ) and the Swedish Govenmental Agency fo Innovation Systems (Gant ageement ) The Autho(s). Papes in Regional Science 2013 RSAI

2 728 M. Andesson et al. While the UWP is established as a geneal phenomenon, less is known about its souces and paticulaly whethe it diffes acoss wokes with diffeent sets of skills. This pape deals diectly with these issues. We quantify the UWP fo wokes with diffeent degees of nonoutine skills, espectively, and estimate the elative impotance of spatial soting and agglomeation economies in explaining the spatial wage dispaities fo each type of woke. The analyses in the pape povide empiical evidence on which type of skills ae ewaded by density, and bea on the boade question of the contexts in which agglomeation is impotant. 1.1 Backgound and motivation Recent eseach on the UWP has focused on two main lines of inquiy. One puts the issue of untangling the souces of the density wage pemium at cente stage, whee a main question egads the espective impotance of non-andom spatial soting of wokes and agglomeation economies (Glaese and Maé 2001; Wheele 2006; Yankow 2006; Gould 2007; Combes et al. 2008, 2011; Melo et al. 2009; Puga 2010; Baum-Snow and Pavan 2012). Spatial soting efes to selection and explains the gap by moe poductive wokes being moe pone to locate in dense egions. This explanation involves no causal effect of spatial density on woke poductivity. The existence of agglomeation economies, on the othe hand, implies that density boosts woke poductivity, fo example though moe efficient matching o faste human capital accumulation due to knowledge spillove phenomena (cf. Duanton and Puga 2004). 1 A geneal finding in this liteatue is that spatial soting of wokes is the main souce of the UWP (Combes et al. 2008). The othe line of inquiy focuses on diffeences in the magnitude of the UWP acoss wokes with diffeent sets of skills. Bacolod et al. (2009) show that the UWP is not unifom acoss wokes, but depends on wokes skills. They maintain that the empiical liteatue on spatial wage diffeentials tends to equate skills with education levels, which does not captue hoizontal diffeentiation of skills, such as cognitive, people and moto skills. The hoizontal dimension of skills is impotant, they ague, as it may condition the ability to lean fom the envionment as well as the extent to which one benefits fom matching and inteaction with othes, that is, how much one benefits fom agglomeation. Consistent with this, they show that it is pimaily wokes with jobs in which cognitive and people skills ae impotant that enjoy a UWP. 2 Skills that make wokes bette apt to benefit fom agglomeation should not only be eflected in wokes having a highe UWP, but also with egad to the impotance of agglomeation economies as a souce of the wage pemium. Though a highe UWP among wokes with cetain skills could in pinciple be due to stonge self-selection of the moe able ones towads uban egions compaed to wokes with othe types of skills, the agument that leaning and matching effects ae stonge fo wokes with skills elated to poblem-solving and inteaction with othes is indeed not about spatial soting. It is instead an agument emphasizing inteactions between wokes and thei local envionment that lead to poductivity gains, namely, agglomeation economies. The implication is that fo wokes with poblem-solving and inteaction skills, agglomeation economies should quantitatively be a moe impotant souce of the density wage pemium. We test this pediction, thus bidging the two lines of inquiy on the UWP. Available evidence on the magnitude and souces of the UWP by woke skills is limited. Bacolod et al. (2009) employ data on a sample of US wokes and estimate the effect of 1 Duanton and Puga (2004) discuss thee families of mico-foundations of agglomeation economies shaing, matching and leaning. 2 Gould (2007) as well as Mölle and Haas (2003) also find that the UWP is significantly lage fo bette educated wokes, and Baum-Snow and Pavan (2012) show that lage cities foste human capital accumulation, especially fo moe highly skilled wokes. None of these studies conside the hoizontal dimension of skills emphasized by Bacolod et al (2009).

3 The souces of the uban wage pemium by woke skills 729 agglomeation on the hedonic pice of cognitive, people and moto skills, espectively. While the question of the souces of the UWP fo the vaious sets of skills is not spelled out explicitly in thei pape, they isolate agglomeation economies by contolling fo measues of woke ability as well as unobseved woke heteogeneity. Ou appoach is diffeent in tems of both the measue of skills and identification stategy. 1.2 Measuing non-outine skills We employ a longitudinal matched employe-employee dataset coveing the full population of Swedish pivate secto wokes ove a seven-yea peiod ( ). These data do not include any diect infomation on woke skills, but do infom about the occupation accoding to the ISCO-88 classification scheme. To diffeentiate between skills we make use of a job-task classification scheme developed by Becke et al. (2009), which epots the faction of nonoutine job tasks associated by each ISCO-88 occupation. Thei oiginal classification is based on a Geman wok suvey, which epots answes to 81 questions egading wokplace tool use by occupation. Tools ae codified accoding to whethe o not the use of a tool indicates non-outine tasks. Becke s et al. (2009) classification is simila to that of Auto et al. (2003) and Spitz-Oene (2006) in that occupations ae linked to the involved shae of outine vs. non-outine tasks. We thus measue wokes non-outine skills by the extent of non-outine job tasks involved with the occupation of that woke. 3 Auto et al. (2003) define non-outine job tasks as tasks that cannot be pefomed by computes. In Becke et al. (2009) non-outine tasks ae defined as tasks chaacteized by non-epetitive wok methods. 4 Such non-outine job tasks typically involve poblem-solving and a lack of deductive ules and codifiable infomation (Hakkala et al. 2008; Becke et al. 2009). This coesponds to the way in which Auto et al. (2003) conceptualize non-outine tasks. In elation to Bacolod s, et al. (2009) types of skills, cognitive and people skills ae suely moe impotant fo non-outine job tasks, and we expect that wokes with skills associated with non-outine job tasks should benefit moe fom density. Such skills ae fo example likely to imply that wokes ae moe able to lean moe fom inteaction with othes in the local envionment. Wokes with non-outine skills may also be moe specialized, implying that matching is moe impotant thus inceasing the benefits of thicke local labou makets (cf. Bacolod et al. 2009). 1.3 Identification stategy: spatial soting and agglomeation economies As we seek to quantify the souces of the wage pemium of diffeent wokes, a key issue in ou analysis is identification of spatial soting and agglomeation economies, espectively. Recent wok by, fo example, Combes et al. (2008) and Mion and Naticchioni (2009) illustates that quantification of spatial soting of wokes depends cucially on the ability to account fo woke heteogeneity, and that spatial soting on unobsevable skills account fo a lage faction of spatial wage dispaities. We quantify the impotance of spatial soting as a souce of wage dispaities by fist estimating aw wage-density elasticities and then study thei sensitivity to the inclusion of obsevable and unobsevable (time-invaiant) woke chaacteistics. Ou data allow us to assess the ole of seveal obsevable woke, employe and egional chaacteistics, as well 3 This should eflect woke skills in the sense that wokes with a job equiing a lage faction on non-outine tasks should have skills associated with non-outine wok. 4 Details of the classification as well as the coespondence between this and the job task classification in Spitz-Ooene (2006) can be found in Becke et al. (2009).

4 730 M. Andesson et al. as pemanent woke heteogeneity. Agglomeation economies ae indiectly quantified as a esidual wage gap afte accounting fo spatial soting. A significant wage-density elasticity that emains afte contolling fo spatial soting of wokes on obsevable and unobsevable skills should in pinciple captue agglomeation economies (cf. Combes et al. 2008). The empiical stategy is staightfowad: if soting is impotant, we should obseve that the (aw) wage pemium dops significantly as we account fo woke heteogeneity. The impotance of agglomeation economies is instead eflected by the magnitude of the emainde wage-density elasticity. By undetaking these analyses fo wokes with skills associated with high and low factions of non-outine job tasks, espectively, we empiically assess the magnitude and souces of the UWP fo wokes with diffeent degees of non-outine skills. To futhe pobe ou analysis of the souces of the UWP, we follow Glaese and Maé (2001) and identify wokes that move fom uban to ual egions. The idea behind this is that agglomeation economies captue diffeent effects, such as matching and leaning. Leaning implies that wokes in cities may enjoy faste human capital accumulation, fo instance though knowledge spillove phenomena (Glaese 1999; Rauch 1993). Because accumulated human capital stays with the woke, the advantages of having woked in a lage dense egion should emain while moving away. Static agglomeation economies, on the othe hand, should be lost upon moving away fom the agglomeation (cf. De La Roca and Puga 2012). 5 To test the agument that wokes with non-outine skills ae moe apt to lean fom thei envionment, we identify outine as well as non-outine wokes who move away fom dense agglomeations and test, fo each categoy of woke, if thei wage dops o emains the same upon moving. This is a staightfowad and simple test of whethe leaning by wokes depends on the skills, and the hypothesis is that non-outine wokes show stonge leaning. 6 The pape includes some additional featues futhe sepaating it fom pevious studies. Many of the analyses of the UWP sepaate uban fom ual egions with a dichotomous vaiable o employ continuous measues of egional density that only account fo the intenal density of egions. The analysis in this pape ecognizes the message emphasized by Iwin et al. (2010), in othe wods, thee is intedependence acoss egions that poduces a continuum fom dense uban egions to moe emote ual ones. Ou measue of density is access to economic mass, as measued by each egion s exponentially tavel time-distance-weighed access to total wage eanings inside the egion as well as to all othe egions. The total density of a location is decomposed into thee spatially distance-weighed components: (i) municipal; (ii) egional; and (iii) exta-egional. This decomposition allows us to obtain a paamete estimate fo each aggegation level, making it possible to assess the impotance of each component, such as the elative impotance of the municipal and the egional density. With these measues the total density of a egion is not only dependent on its intenal chaacteistics, but also on the chaacteistics of suounding egions and its tavel time-distance to those egions. This captues intedependence between egions. Moeove, most of the existing analyses have been conducted on counties hosting lage metopolitan aeas, such as the US (Glaese and Maé 2001; Gould 2007), Gemany (Mölle and Haas 2003) and Fance (Combes et al. 2008). Sweden is a small and geneally spasely populated county (aound 9 million inhabitants on a total land aea of about 410,000 km 2 ). Most cities and uban aeas in the county ae small in an intenational context, and only thee cities may, with a geneous standad, be labelled metopolitan. 7 An 5 Models of matching effects in thick makets suggest that the aveage quality of each match is highe in agglomeations (cf. Hesley and Stange 1990; Kim 1990). Such an agglomeation economy suely does not follow wokes. 6 We ae cautious in dawing stong conclusions fom the analyses of the wages of moves as we ae not able to fully account fo the endogeneity issue aised by Gould (2007); changes in wages fom moving may be coelated with changes in the quality of oppotunities in diffeent egions. 7 If we fo instance apply the big city classification in Yankow (2006), only one metopolitan aea in Sweden (Stockholm) would baely pass the ba.

5 The souces of the uban wage pemium by woke skills 731 analysis of Sweden thus constitutes a conspicuous contast to existing analyses on counties with big uban aeas such as New Yok and Pais. 1.4 Main findings We find shap diffeences between wokes with non-outine and outine skills in tems of the magnitude of the spatial wage dispaities as well as thei souces. Wokes with skills associated with non-outine job tasks enjoy an unadjusted wage-density elasticity of about thee pe cent. Fo these wokes, agglomeation economies ae significant, though quantitatively of much smalle impotance than spatial soting. Afte contolling fo obseved and unobseved woke heteogeneity we find that a doubling of eithe municipal o egional density yields a wage incease in the ode of 0.5 pe cent. Non-outine wokes also appea to be bette apt to accumulate human capital, as evidenced by that wokes that move away fom dense egions keep (o incease) thei wage upon moving. Fo wokes with skills associated outine job tasks on the othe hand, agglomeation economies appea to be non-existent. 1.5 Outline The est of the pape is oganized as follows: Section 2 pesents the data, defines vaiables and also povides the big pictue egading wages, education levels and skills in the economic geogaphy. Section 3 descibes ou empiical stategy, focusing on how we empiically assess the elative impotance of spatial soting and agglomeation economies as souces of the UWP. Section 4 pesents the esults and Section 5 concludes. 2 Data, vaiables and desciptives 2.1 Data We use a matched employe-employee audited egiste dataset, maintained by Statistics Sweden. The data compise all employees in Sweden duing the peiod 2002 to By constuction of the data, employees ae assigned to thei wok establishment (and thus secto, occupation and location) in the month of Novembe each yea. Though the data span all sectos of the economy, we exclude all public secto employees and wokes in the agicultual and mining industies. This isolates wokes whose wage fomation is detemined by maket outcomes and wokes in sectos whose locations ae not diectly linked to natual esouces. As we ae inteested in labou income, we also exclude wokes whose pimay income comes fom self-employment. Wokes in ou data ae in the age inteval This leaves us with a panel containing about 2.4 million employees with a mean population size of just shot of 2 million yealy obsevations. The discepancy between the numbe of individuals and the numbe of obsevations pe yea is an effect of the cut-off values ceated by the age inteval and to a lesse extent by inceased labou foce paticipation in late stages of the epoting peiod. The data infom about seveal chaacteistics of each employee and thei employe. Fo employees we have infomation such as education (length and specialization), sex, age, wage income and immigant status. Employee chaacteistics include basic obsevables such as secto and employment size.

6 732 M. Andesson et al. 2.2 Vaiables and classification of non-outine job tasks Density Ou vaiable of main inteest is spatial economic density. Many studies of the UWP distinguish uban dense aeas fom ual ones by a dichotomous indicato vaiable based on some theshold value of, fo example, population size. Altenatively, they conside a continuous indicato measuing the intenal density of each egion, commonly employment pe squae kilomete. The density measue employed in this pape is diffeent. We define density in a way akin to Hais s (1954) classic measue of maket potential. The basic spatial unit in ou analysis is the municipality of which thee ae 290 in Sweden. Specifically, the data infom about in which municipality each woke s employe is situated. These spatial units ae in geneal of limited size and thee is significant commuting and othe types of inteaction acoss municipal bodes. Many of the spillove effects alluded to in the liteatue on agglomeation economies and human capital spilloves ae thus likely to tanscend municipal bodes, especially as they may be mediated by labou maket mobility (cf. Andesson and Thulin 2013). The same applies fom the viewpoint of spatial soting. When wokes choose whee to opeate in space, they most likely conside chaacteistics of an integated labou maket, which in geneal compises moe than one municipality. We may thus expect intedependencies between municipalities, such that it is not only the intenal density of municipalities that matte, but also the suoundings. On these gounds we employ an accessibility appoach. One can think of the total density of a municipality as the sum of municipal, egional and exta-egional accessibility to total wage-eanings, W: Tot M R E De = De + De + De, (1) M De = Wexp{ λ Mt}, municipal accessibility to total wage eanings of municipality ; R De = k RWkexp{ λ Rt k}, egional accessibility to total wage eanings of municipality ; E De = l RWlexp{ λ Et l}, exta-egional accessibility to total wage eanings of municipality. Total wage eanings eflect the magnitude of economic activities (o economic mass) and accessibility to economic activity is ou measue of spatial economic density. Municipal density is simply each municipality s total wage eanings weighed exponentially with tavel timedistances by ca between zones within the municipality. Regional accessibility is defined in a simila way but hee we sum the municipality s access to evey othe municipality belonging to the same local labou maket egion. 8 Exta-egional accessibility is the sum of its accessibility to all municipalities outside the egion. The distance-decay paamete l takes on thee diffeent values fo municipal, egional and exta-egional accessibility, espectively. These paamete values ae based on obseved commuting behaviou of wokes, and ae estimated fo Swedish municipalities by Johansson et al. (2003) using doubly constained gavity models. The accessibility appoach ecognizes that the density of a municipality is built up though a geogaphic continuum whee the contibution of othe places economic activities falls as tavel-time distances incease. 9 Theeby, the measue is consistent with Toble s (1970) 1st law of geogaphy : eveything is elated, but nea things ae moe elated than distant things. Because of the natue of the exponential distance-decay function, the contibution of munici- 8 Local labou maket egions compise a numbe of municipalities foming an integated labou maket, and ae delineated based on the intensity of inte-municipality commuting flows. 9 This also alleviates potential poblems with spatial autocoelation (Andesson and Gåsjö 2009).

7 The souces of the uban wage pemium by woke skills 733 palities fa away is small but emains positive. In tems of an uban-ual dichotomy, the accessibility fomulation ecognizes intedependence acoss places whee thee is a continuum fom dense uban egions to moe emote ual ones (cf. Iwin et al. 2010). In the empiical analysis we include De M, De R and De E as thee distinct independent vaiables. This allows us to assess which type of density that mattes. In geneal we expect density effects to pimaily petain to the local labou maket egion in which the wokes wok, namely, De M and De R Contols: obsevable chaacteistics We contol fo seveal chaacteistics of wokes and employes that may influence a woke s wage. The obsevable chaacteistics that we include in the analysis ae pesented and defined in Table 1. Expeience and its squaed value ae standad contol vaiables and in accodance with pevious liteatue we expect that wages incease with expeience but at a diminishing ate. Yeas of schooling is assumed to have a positive influence on a woke s wage. We also include a set of dummy vaiables eflecting the educational specialization of the woke. These ae defined at the 1-digit SUN2000 classification system in Sweden, which coesponds to the 1997 Intenational Standad Classification of Education (ISCED). This leaves us with nine dummy vaiables eflecting the educational specialization of each woke. We have a pioi no clea idea of how diffeent educational specializations may influence a woke s wage, but we acknowledge that they eflect potentially elevant chaacteistics of the wokes. The analysis futhe includes immigant and sex dummies. The fome is 1 if the woke is a fist geneation immigant and the latte is 1 if the woke is male. The geneal finding in the liteatue is that immigants have lowe aveage wages wheeas males have highe aveage wages than females. Tenue is an impotant vaiable in labou maket analyses and is assumed to eflect the quality of the match between the woke and he wokplace (Fabe 1994). On these gounds, we expect that tenue is positively associated with a woke s wage. We define tenue as the numbe of yeas the woke has stayed with he cuent wokplace. Due to data availability easons, max tenue is the obsevation yea minus 2001 because we have no infomation pio to In addition to tenue we also include the numbe of pio employes and a dummy fo whethe the woke switched jobs between yea t and t-1. Both these vaiables may eflect wokes in seach of a good match in the labou maket, why we expect them to be negatively associated with wages. The employment size of the establishment at which the wokes ae employed is anothe impotant deteminant of wages. Ample studies in labou maket economics show that lage fims pay highe wages (Oi and Idson 1999). 10 We expect that establishment size has a positive influence on wages. Futhemoe, we include dummy vaiables to account fo the possibility that wages may depend on the secto in which a woke is employed. The analysis includes one secto dummy fo each 2-digit secto among NACE sectos The secto of a woke is detemined by the secto affiliation of the establishment he o she is employed by. 10 This is often explained by lage fims being bette equipped than smalle fims in tems of esouces and poductivity, as well as by behavioual aguments. The latte includes that lage fims may be moe apt to adopt discetionay wage policies and paying efficiency wages to dete shiking. 11 In the analyses pesented in the sequel, we have also tested if the esults depend on the level at which the secto dummies ae defined. Ou esults ae obust to using secto dummies at the 2, 3, 4 o 5 digit level.

8 734 M. Andesson et al. Table 1. Vaiables, definitions and expected sign Vaiable Definition Expected sign Wage The total wage eanings of a woke duing a yea a n.a Expeience The employee s age minus yeas of schooling minus 6. This + definition follows Rauch (1993). Expeience squaed Same as above but squaed. - Schooling Theoetical yeas of schooling. + Education specialization Dummies fo diffeent education specializations, defined n.a accoding to the 1-digit SUN2000 classification, which is based on ISCED Immigant A dummy which is 1 if the woke is a fist geneation immigant, - 0 othewise. Sex A dummy which is one if the woke is male, 0 othewise. + Tenue The numbe of yeas the woke has been employed at he cuent + wokplace. Max tenue is the obsevational yea minus 2001, as we have no infomation pio to Numbe of pio employes The numbe of diffeent employes the woke has had since Job change A dummy which is 1 if the woke changed occupation between - yea t and t - 1. Log of numbe of employees The natual logaithm of the total numbe of employees at the + wokplace at which the employe is employed. Secto affiliation Dummies fo diffeent sectos at the level of 2-digit NACE n.a sectos. Municipal density Exponentially distance-weighed accessibility to wage sums in the + municipality the woke woks in. Regional density Exponentially distance-weighed accessibility to wage sums to all + municipalities in the local labou maket egion the municipality belongs to. Exta-egional density Exponentially distance-weighed accessibility to wage sums to all municipalities in Sweden except those belonging to the municipality s local labou maket egion. + Notes: a The individuals included ae wokes who ae pimaily wage laboues, but like most othe studies using audited full population egiste data whee wage incomes ae dawn fom tax declaations, we lack infomation on the numbe of hous woked. While this epesents the best infomation available, we ecognize that using yealy wages may be a souce of bias in an OLS setting unde the assumption that wokes in dense aeas systematically wok longe hous than wokes in spase aeas and consequently make highe yealy wages. In a fixed effects setting, this is a smalle poblem. The eason is that a bias can in this case only aise if wokes in dense aeas systematically wok inceasingly longe hous, elative to wokes in spase aeas duing the epoting peiod, o that wokes moving to moe dense egions incease thei woking hous by moving. In the empiical analyses that follow, evey model specification futhe includes egion-yea effects, which means that any systematic egion-specific tends by which wokes in cetain egions incease woking hous ove time is picked up. All vaiables ae based on audited egiste data maintained by Statistics Sweden. Accessibility calculations based on tavel time distances by ca between municipalities. Tavel time distances by ca ae obtained fom the Swedish Road Administation Measuing non-outine job tasks The data on the faction of non-outine job tasks by occupation oiginate fom Becke et al. (2009) and details on the constuction of the data as well as thei vaious obustness checks ae documented theein. 12 They classify answes in a Geman qualification and caee suvey 12 They also classify jobs accoding to the extent it involves inteaction. Thee is consideable ovelap between the two classifications, whee non-outine tasks tend to involve inteaction tasks. In all analyses pesented in the sequel, we have also tested this classification and esults ae obust. We choose the non-outine classification as it emphasize jobs in which cognitive and people skills should be impotant.

9 The souces of the uban wage pemium by woke skills 735 Table 2. The faction of non-outine tasks in diffeent 2-digit occupations accoding to ISCO-88 Occupation title Faction non-outine tasks (%) Physical, mathematical and engineeing science pofessionals Life science and health pofessionals 90.4 Physical and engineeing science associate pofessionals 79.7 Copoate manages 78.4 Othe pofessionals 63.0 Teaching pofessionals 61.2 Life science and health associate pofessionals 56.3 Legislatos and senio officials 54.4 Othe associate pofessionals 52.7 Office cleks 52.1 Geneal manages 46.6 Stationay-plant and elated opeatos 43.6 Metal, machiney and elated tades wokes 41.6 Pecision, handicaft, pinting and elated tades wokes 39.8 Teaching associate pofessionals 36.1 Pesonal and potective sevices wokes 32.0 Custome sevices cleks 27.1 Extaction and building tades wokes 21.4 Machine opeatos and assembles 18.8 Othe caft and elated tades wokes 17.7 Maket-oiented skilled agicultual and fishey wokes 10.8 Models, salespesons and demonstatos 8.1 Dives and mobile-plant opeatos 6.3 Laboues in mining, constuction, manufactuing and tanspot 2.5 Agicultual, fishey and elated laboues 0.9 Note: Based on Hakkala et al. (2008) using task data developed by Becke et al. (2009). fo 1998/1999, undetaken by the Geman Fedeal Institute fo Vocational Taining and the eseach institute of the Geman Fedeal Labou Agency. It tacks the usage of 81 diffeent tools in a multitude of occupations. Becke et al. (2009) classify diffeent tools accoding to thei elation to non-outine tasks (non-epetitive wok methods). The diffeent tasks ae then mapped to ISCO-88 standadized occupations. Fo each 2-digit occupation, the degee of non-outine tasks is then computed as the atio between the aveage numbe of non-outine tasks in the occupation and the maximum numbe in any occupation, and the numbes ae then standadized so that the faction of non-outine tasks in an occupation vaies between 0 and 1. In Table 2 we follow Hakkala et al. (2008) and pesent the faction on non-outine job tasks fo each occupation at the 2-digit ISCO The geneal pictue is that science-based, engineeing and copoate management occupations have the highest faction of non-outine tasks. A low degee of non-outine job tasks ae found in occupations elated to agicultue, fishing, extaction sectos and simple tanspot sevices. The pattens epoted in the table confim that non-outine job tasks typically involve poblem-solving with a geneal lack of deductive ules and codifiable infomation (Hakkala et al. 2008). The occupations with high factions of nonoutine tasks ae also jobs in which cognitive and people skills should be impotant (cf. Bacolod et al. 2009). 13 Hakkala et al. (2008) use the task data mapped to ISCO-88 occupations developed by Becke et al. (2009) in the analysis of how multinational activities influence demand fo diffeent job tasks.

10 736 M. Andesson et al. Table 3. Key figues divided by faction of non-outine wok tasks Job type Mean wage (EUR) Gaduate shae (%) Mean expeience Metopolitan shae (%) All types of pofessions 29, High faction non-outine tasks 36, Low faction non-outine tasks 23, Notes: Gaduate shae is the faction of wokes with a univesity education of at least thee yeas. Metopolitan shae is the faction of wokes that wok in thee biggest labou maket egions: Stockholm, Gothenbug and Malmo. Wages conveted to EUR using the 2008 exchange ate between SEK and EUR of High (low) faction non-outine jobs ae those with faction non-outine tasks above (below) the mean faction acoss all occupations (see Table 2). Table 4. Mean wages (2008) and unadjusted wage gap between metopolitan and non-metopolitan wokes Job type Metopolitan wage (EUR) Non metopolitan wage (EUR) Wage diffeential (%) All types of pofessions 34,417 27, High faction non-outine tasks 41,024 34, Low faction non-outine tasks 22,634 23,195-2 Notes: The metopolitan aeas ae defined as the thee biggest labou maket egions: Stockholm, Gothenbug and Malmo. Wages conveted to EUR using the 2008 exchange ate between SEK and EUR of High (low) faction non-outine jobs ae those with faction non-outine tasks above (below) the mean faction acoss all occupations (see Table 2). 2.3 Wages, education levels and skills in the Swedish economic geogaphy Table 3 pesents the mean wage, faction of gaduates, mean expeience and the faction of wokes woking in any of the thee lagest egions in Sweden fo all wokes as well as fo occupations with high and low factions of non-outine job tasks, espectively. 14 About one thid of all wokes in the population wok in the thee lagest egions and about 15 pe cent ae univesity gaduates. Wokes with jobs equiing moe non-outine tasks ae much bette educated and ae the ones most pone to wok in a metopolitan aea. Roughly 36 pe cent of all wokes with non-outine jobs wok in a metopolitan aea compaed to 19 pe cent fo wokes with less non-outine tasks in thei job. The mean wage of wokes with jobs associated with high factions of non-outine tasks is also highe than fo othe types of jobs. The unadjusted wage diffeential between metopolitan and non-metopolitan wokes oveall and fo jobs with high and low factions of non-outine tasks is pesented in Table 4. Fo the pivate secto as a whole, the aw wage diffeential between metopolitan and nonmetopolitan wokes amounts to just ove 20 pe cent. The uban-ual wage gap appeas to depend cucially on the type of job. The diffeence is substantially lage fo occupations with high faction non-outine tasks (20 pe cent) wheeas the same aw wage diffeential is negative but small fo occupations with low factions of non-outine tasks. These pattens ae boadly consistent with the ecent liteatue (e.g., Gould 2007; Bacolod et al. 2009), and suggest that spatial soting with egad to type of jobs is one eason fo the (unadjusted) oveall UWP. One eason fo the descibed wage diffeences between wokes in metopolitan and nonmetopolitan egions may of couse be that bette educated wokes ae moe inclined to move 14 High faction non-outine jobs ae those occupations with faction non-outine tasks above the mean faction acoss all occupations. Low faction non-outine jobs ae those whose faction of non-outine tasks is below the mean.

11 The souces of the uban wage pemium by woke skills 737 Fig. 1. The elationship between mean wages (log) and accessibility to total wage eanings (log) acoss Swedish municipalities in 2008 to bigge cities. Indeed, highly educated individuals tend to agglomeate in cities, fo instance since specialized wokes ae bette matched with employes whee makets ae thick (Stange 2009) and since highly educated individuals may self-select to cities whee consumption amenities ae abundant (Lee 2010). 15 Wokes with highe education levels indeed have highe wages, and the gaduate shae in the metopolitan aeas was 28 pe cent in 2008, while it was 13 pe cent in othe aeas. The subsequent empiical analysis focuses on the elationship between density as measued by accessibility to total wage eanings and wokes wages. Figue 1 plots the logaithmic elationship between mean wages in ou population and ou (summed up) density measue. It is clealy the case that wokes in dense municipalities have highe aveage wage. A simple odinay least squaes (OLS) estimation of the log of density on the log of aveage wages acoss municipalities in Sweden using the data in Figue 1 yields the following esults (t-values beneath paamete estimates, N = 290): Tot ln w = ln De + ε, M R E ln w = ln De ln De ln De + ε, (2a) (2b) whee the estimation in (2b) sepaates between the thee components of the total density of municipalities (see equation 1). The estimates in (2a) show that 10 pe cent highe density is associated with about 0.5 pe cent highe wages. The decomposition of the total density in (2b) shows that the municipal density is esponsible fo the bulk of this elationship with an estimated coefficient of The density of the local labou maket egion and exta-egional density contibute with a significantly smalle shae amounting to about 0.01 each. 3 Empiical stategy The baseline empiical model is as follows: 15 Thee is a lage liteatue on the extent to which the location of educated wokes is diven by amenities o poductivity (e.g., Moetti 2008) but this issue is not the main focus and beyond the scope of this pape.

12 738 M. Andesson et al. M R E ln w = α + β ln De + β ln De + β ln De + it 1 t 2 t 3 t 81 T TR R R D R = λ 1 t= 1 t t tr= 1 + γ D + + σ ( D D )+ Z g + ε, tr t R it (3) whee w it is the wage eanings of individual i at time t woking in municipality. De t M, De t R and De t E epesent municipal, egional and exta-egional accessibility to wage eanings, espectively. The baseline model always includes yea dummies (D t), dummies fo local labou maket egions (D R) as well as time dummies inteacted with dummies fo local labou maket egions (Dt D R). Yea dummies ae intended to account fo geneal business cycle effects, and egion dummies ae included to captue egion-specific effects. The egion-yea effects account fo any egion-specific time-vaying shocks shaed by all wokes in the same local labou maket egion. 16 Pevious wok, fo example, Moetti (2004) emphasizes the impotance of accounting fo both egion and egion-yea effects. Z is a matix of contol vaiables. e it is an eo tem. Ou main inteest is in the b paametes. To quantify the impotance of spatial soting we stat by estimating aw wage-density elasticities, indicating how wages of pivate secto wokes coelate oveall with ou thee density measues. We obtain these aw elasticities by estimating the model in (3) using pooled OLS without any contols besides yea, egion and egion-yea dummies. We then estimate fou additional models, while keeping the aw wage-density elasticities as points of efeence. In the fist estimation we add standad Minceian obsevable woke chaacteistics in the fom of yeas of schooling, expeience, sex, immigant status as well as dummies eflecting diffeent education specializations (Mince 1974). The second estimation adds labou maket infomation of each woke, that is, tenue, numbe of pio employes, a dummy fo whethe the woke s cuent occupation is new fo the woke and employe size. This second specification also includes two-digit NACE industy dummies to captue diffeences in geneal wage levels acoss industies. As the efeence estimation, these two specifications ae estimated with pooled OLS. This means that identification of the wage-density elasticities is based on diffeences acoss wokes in municipalities of vaying densities, while contolling fo obsevable woke and employe chaacteistics as well as time, industy and egion-yea effects. The two additional specifications exploit the panel stuctue of the data and add woke fixed effects (FE). These woke FE fully absob any pemanent heteogeneity at the woke, employe, industy o municipality level. Due to the within tansfomation of the FE estimato, identification of the wage-density elasticities is now based on changes ove time in the thee density measues. As the within vaiation of each espective density measue is limited, the paametes of the density vaiables ae pimaily identified based on wokes who ove yeas move between municipalities of vaying densities. 17 The fist FE model is the basic model in Equation (3) augmented with woke FE but excluding any othe contols besides yea and egion-yea dummies. The second one adds time-vaying woke and employe chaacteistics, including industy dummies. The inclusion of FE woke effects means that these obsevables ae also identified fom changes ove time To be pecise, the egion-yea dummies account fo shocks ove time that ae common fo all employees woking in municipalities belonging to the same local labou maket egion R. We choose the local labou maket egion as aggegation level fo the egion-specific shocks as the labou maket egions epesent integated local labou makets and compise seveal municipalities connected though intense commuting flows. Thee ae 81 local labou maket egions in Sweden. 17 Fo each of density vaiable, the within vaiation is substantially smalle than the between vaiation. Fo municipal, egional and exta-egional density the between vaiation is about 2.7, 3.7and 2.9 times lage than the within vaiance, espectively. 18 In a simila way, the egions-specific effects (D R) ae identified fom wokes that move between local labou maket egions ove time.

13 The souces of the uban wage pemium by woke skills 739 This empiical set-up allows us to quantify how sensitive the estimated wage-density elasticities ae to spatial soting on obsevable and unobsevable woke chaacteistics. In view of pevious eseach such as Combes et al. (2008), we expect that the wage-density elasticities ae significantly educed when accounting fo woke chaacteistics, especially unobsevable pemanent woke heteogeneity. Any emainde significant wage-density elasticities should eflect agglomeation economies. We futhe isolate wokes who move fom high to low density egions. In ou empiical context we accomplish this in a staightfowad manne by identifying wokes who move fom any of Sweden s thee metopolitan egions (Stockholm, Gothenbug and Malmo) to any othe place in Sweden. We then estimate whethe they educe o keep thei wage upon leaving a metopolitan egion, using both pooled OLS and FE models. The idea behind this is to test fo leaning effects in the fom of human capital accumulation effects (Glaese and Maé 2001; De La Roca and Puga 2012): if wokes gain human capital in cities, the advantages of having woked in a lage and dense city should emain while moving away. We systematically apply the empiical stategy descibed above fo wokes with occupations associated with high and low factions of non-outine job tasks, espectively. We thus split the sample of wokes in two goups; one with wokes having occupations with a faction of non-outine tasks above the mean faction fo all occupations, and one with a non-outine job task faction below the mean (see Table 2). This allows us to identify diffeences in the impotance of spatial soting and agglomeation economies between the two goups in a staightfowad way Results Table 5 pesents esults fo all pivate secto wokes in Sweden. Stating fom the left, the fist thee specifications ae pooled OLS estimations and the last two ae panel estimations with woke fixed effects. The municipal and egional densities ae significant and positive in all specifications. Wokes ean moe in dense egions. It is thus not only the density of the municipality that matte, but also the density of the wide local labou maket egion in which the woke opeates. This is in line with expectations as labou maket egions epesent integated labou makets and consist of municipalities between which thee is intense inteaction. The exta-egional density is negative and significant, indicating that if the suoundings of a labou maket egion gow it has a negative impact on wages in the egion, all else equal. This may be undestood as an effect fom lagging behind the suoundings. The aw unadjusted wage-density elasticity is about 0.03 fo municipal and egional density, espectively. Taken togethe, they coespond boadly with the estimates epoted by Ciccone and Hall (1996), who find that a doubling of density is associated with about six pe cent highe poductivity. The wage-density elasticities ae also athe insensitive to obsevable woke chaacteistics. In the Minceian model which adds yeas of schooling, expeience as well as dummies fo sex, immigants and education specialization, the estimated wage-density elasticities fo municipal and egional density only falls maginally fom 0.03 to about The estimated paametes change only slightly fom adding indicatos fo labou maket status and employe chaacteistics (full OLS model). These pattens suggest that spatial soting of wokes on basic obsevable woke and employe chaacteistics is not a quantitatively impotant souce of the aw wage-density elationship. 19 An altenative stategy would be to include the faction of non-outine job tasks as a sepaate independent vaiable. The pooled OLS estimations would then identify its effect though diffeences acoss wokes, wheeas identification with the FE estimato would be based on wokes that shift occupations ove time (the faction of non-outine job tasks of an occupation is time-invaiant). We have consideed this stategy as well and the findings epoted in the sequel ae obust to this altenative appoach.

14 740 M. Andesson et al. The pictue changes as we contol fo pemanent woke heteogeneity with woke fixed effects. The second column fom the ight shows the esults with the aw specification with woke fixed effects, namely, excluding any othe contols besides yea and egion-yea dummies. A compaison of the wage-density elasticities in this specification with the ones obtained with aw OLS (second column fom the left) illustates what woke fixed effects means fo the magnitude of the estimated wage-density elasticities. As is evident fom Table 5, the inclusion of woke fixed effects induces the wage-density elasticities to dop shaply. Both the municipal and the egional densities dop fom about 0.03 Table 5. The elationship between spatial economic density and wages, all pivate secto wokes Raw OLS Minceian OLS Full OLS Raw with woke FE Full with woke FE Municipal density (log) *** *** *** *** *** ( ) ( ) ( ) ( ) ( ) Regional density (log) *** *** *** *** *** ( ) ( ) ( ) ( ) ( ) Exta-egional density (log) * *** *** *** (0.0185) (0.0139) ( ) ( ) ( ) Yeas of schooling *** *** 0.117*** ( ) ( ) (0.0190) Expeience *** *** *** ( ) ( ) (0.0190) Expeience *** *** *** (5.42e-05) (4.64e-05) (2.84e-06) Immigant (dummy) *** *** ( ) ( ) Male (dummy) 0.351*** 0.330*** ( ) ( ) Tenue *** *** ( ) ( ) Numbe of pio employees *** *** ( ) ( ) New occupation (dummy) *** *** ( ) ( ) Employe size (log) *** *** ( ) ( ) Yea dummies Yes Yes Yes Yes Yes Region dummies Yes Yes Yes Yes Yes Region yea effects Yes Yes Yes Yes Yes Education type dummies No Yes Yes No Yes Industy dummies No No Yes No Yes Obsevations 12,367,700 12,367,700 12,367,700 12,367,700 12,367,700 Individuals 2,681,164 2,681,164 2,681,164 2,681,164 2,681,164 R-squaed Notes: The table epots estimates of wage-density elasticities fo pivate secto wokes in Sweden Raw efes to the wage equation in Equation (3) without any futhe contols. The Minceian model adds yeas of schooling, expeience and its squaed value as well as dummies fo immigants, males and education specialization. The full specification futhe adds vaiables eflecting labou maket status and employe chaacteistics of each woke. OLS efes to the pooled OLS estimato and FE to a panel estimato with woke fixed effects. All vaiables ae defined in Table 1. The full FE model excludes immigant and sex dummies as these eflect time-invaiant woke chaacteistics. All models include yea and egion dummies as well as egion-yea dummies, whee the latte account fo any egion-specific time-vaying shocks shaed by all wokes in the same local labou maket egion. The dependent vaiable is the natual logaithm of wage eanings. Robust standad eos ae pesented in backets. *** p < 0.01, * p < 0.1.

15 The souces of the uban wage pemium by woke skills 741 to The aw OLS estimates ae thus almost fou times as a high as the estimates obtained with woke fixed effects. The estimates show that afte accounting fo woke fixed effects, a doubling of eithe municipal egional density is associated with about 0.8 pe cent highe wages. This esult suggests that spatial soting on unobsevable woke chaacteistics is indeed an impotant souce of the wage-density elationship. Afte contolling fo soting thee emains a small but significantly positive wage-density elasticity, indicating the existence of a small agglomeation effect. Soting effects dominate, and these pattens ae boadly in line with the findings by Combes et al. (2008) on woke-level data fo Fance. Tuning to the contol vaiables we find that the estimated influence of yeas of schooling is positive thoughout, and the magnitude of the estimates ae oughly in accodance with esults epoted in pevious studies (cf. OECD 1998). Moeove, moe expeienced wokes ean in geneal bette though the positive effect falls off as expeience ises. Immigants ean less on aveage wheeas male wokes ean moe than females. In the OLS specifications, tenue and the numbe of pio employees ae positive, though the latte estimate is statistically insignificant. That longe tenue is positive is in line with the hypothesis that tenue signals match quality (cf. Fabe 1994). In the fixed effects specification, howeve, tenue is negative and significant. This may be explained in two ways. Fist, those with long tenue epesent a select goup which may have lowe caee aspiations. Second, the fixed effects model may captue those that switch employe and make a caee move afte a numbe of yeas of accumulation of expeience with the same employe. 20 Employe size is positive and significant thoughout which is an established esult in the liteatue (Oi and Idson 1999). The main aim of this pape is to test whethe the magnitude and souces of the wage density pemium vay acoss wokes with diffeent sets of skills. We split the population of wokes in two goups: one with jobs with high faction non-outine tasks and one with jobs with low faction non-outine tasks. Table 6 epots esults obtained fo the fist goup wokes with jobs associated with high faction non-outine tasks. The esults ae simila as those epoted in Table 5. The aw OLS estimates ae aound 0.03 fo municipal and egional density, while the exta-egional density is negative (though not significant). Contolling fo obsevable woke and employe chaacteistics educes the estimates fo municipal and egional density to about Also fo wokes with non-outine jobs, spatial soting effects dominate. Including woke fixed effects in the aw model educes the estimated wage-density elasticities substantially. Fo municipal and egional density the diffeence between the aw OLS and the aw model with woke fixed effects amounts to a facto of almost fou. Thee is a geneal tendency that the estimates with woke fixed effects ae lage fo wokes with jobs in which non-outine tasks ae impotant, but the diffeences to Table 5 ae still maginal. Results fo wokes with jobs associated with low factions of non-outine tasks ae pesented in Table 7. The fist appaent esult is that the aw OLS estimates suggest a non-existent o negative wage-density elationship fo jobs with low faction non-outine tasks. The estimated coefficient fo municipal density is negative and significant, wheeas the emaining densities ae positive but insignificant. Thee ae thus no clea pattens that wokes with these jobs ean moe in dense aeas. Instead, it appeas that wokes with outine jobs in dense municipalities ean less than thei moe ual countepats. In the Minceian specification which adds education, expeience and othe basic woke chaacteistics, none of the density vaiables is statistically significant. Only in the full OLS model, which futhe adds employe chaacteistics and indicatos of the labou maket status of the wokes, the wage-density elasticities become statistically significant and have the same sign 20 Such effects ae moe likely to be captued when the estimates ae based on within vaiance, as wokes ae hee followed ove yeas.