Professor Paul Bishop
email: paul.bishop@plymouth.ac.uk

Dr Peter Gripaios
email: peter.gripaios@plymouth.ac.uk

Reader In Economics

R11 -Regional Economic Activity: Growth, Development, and Changes

Keywords: JEL classification: R11, R12 Spatial externalities, employment growth, Great Britain Räumliche Externalitäten, Beziehungen und sektorales Beschäftigungswachstum in Großbritannien auf Aspekte der Bereiche Beziehung, Sektorunterschiede, Wettbewerb, grenzüberschreitende Übertragungen und räumliche Autokorrelation ein. Die Ergebnisse weisen darauf hin, dass sich eine Spezialisierung generell negativ auf das Wachstum auswirkt, während die Auswirkung von Vielfalt innerhalb der Sektoren heterogen ausfällt und ein starker lokaler dass Vielfalt, lokaler Wettbewerb und Sektor-Heterogenität wichtige politische Aspekte darstellen. JEL classification: R11, R12 Räumliche Externalitäten Beschäftigungswachstum Großbritannien Efectos externos espaciales, relaciones Factores externos espaciales Crecimiento del empleo Gran Bretaña JEL classification: R11, R12

This paper examines the impact of externalities on employment growth in sub-regions of Great Britain by estimating OLS and maximum likelihood spatial models at the 2-digit level for 23 sectors. Issues arising from relatedness, sector differences, competition, cross-boundary spillovers and spatial autocorrelation are explicitly addressed. Results

indicate that specialisation has a generally negative impact on growth whilst the impact of diversity is heterogeneous across sectors and strong local competition has a typically positive impact. The results question the merits of policies primarily aimed at promoting regional specialisation and suggest that diversity, local competition and sector heterogeneity are important policy issues.

INTRODUCTION

Policy makers have made the development of "clusters" of economic activity a central element of regional policy in recent years [START_REF] Bryan | Investigating the potential of key sectors using multi-sectoral qualitative analysis: a Welsh case study[END_REF][START_REF] Cumbers | Introduction: Clusters in Urban and Regional Development[END_REF]. This renewed interest in the benefits of local specialisation has been associated with the work of [START_REF] Porter | On Competition[END_REF][START_REF] Porter | Locations, clusters and company strategy in[END_REF], although arguments supporting the benefits of local agglomerations can be traced back to MARSHALL (1890).

However, these policy developments have tended to undervalue the potential benefits of a diverse industrial base, including the promotion of economic stability and the facilitation of external economies which operate across industrial sectors [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF].

Indeed, there is a considerable academic debate as to whether specialisation or diversity is most conducive to local growth (CINGANO AND SCHIVARDI, 2004). This debate has been given added stimulus by a resurgence of interest in growth theory and the central importance of knowledge spillovers to many modern theories [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF]. There is a strong geographical dimension to this recent literature, reflecting the widespread view that knowledge spillovers are often highly localised as they are difficult to codify and may be best promoted through face to face contact ( [START_REF] Van Stel | Knowledge spillovers and economic growth: an analysis using data of Dutch regions in the period 1989-1995[END_REF].

A substantial empirical literature assessing the importance of externalities to local growth has developed building on original contributions from [START_REF] Glaeser | Growth in cities[END_REF] and [START_REF] Henderson | Industrial development in cities[END_REF]. However, most of this literature has measured diversity in terms of a single measure reflecting average diversity across an entire local economy. This neglects the fact that spillovers might be best promoted when there is a degree of relatedness between relatively distinct sectors in terms of, for example, products, knowledge-base, technology or skills. In addition, whilst many early studies concentrated on the manufacturing sector, it has been increasingly recognised that the potential to benefit from spillovers may differ across industrial sectors [START_REF] Deidda | Spatial externalities and local economic growth[END_REF]. A further issue is the existence of spillover effects across local boundaries which may give rise to spatial autocorrelation ( [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF][START_REF] Deidda | Spatial externalities and local economic growth[END_REF]. This is particularly relevant given that regional units typically have boundaries that are administrative in nature rather than a reflection of geographical areas that have strong economic coherence. This paper explicitly examines the issues of relatedness, sector differences and crossboundary spillovers within the context of an empirical study of 2-digit industries across sub-regions of Great Britain. Although there have been several European sector studies in recent years, there has been no detailed study utilising data at this level for Great Britain.

Moreover, existing sector studies have typically incorporated measures of overall diversity in their empirical work rather than distinguishing between related and unrelated diversity. Recent studies by [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF] and [START_REF] Deidda | Spatial externalities and local economic growth[END_REF], for example, measure diversity in terms of the inverse of the Herfindahl index and do not include related diversity. Thus, the study presented in this paper is novel both in terms of the data utilised and the consideration of the issue of relatedness at the sector level. In addition, the conclusions provides some interesting contrasts (and some confirmation) of existing empirical studies. The paper begins with an overview of the theoretical arguments linking local growth to externalities, followed by a brief discussion of existing empirical evidence. The next section discusses the model used in the study, which is based on the GLAESER et al (1992) approach. The following section outlines the data and methodology, which incorporate both OLS and maximum likelihood techniques to take into account spatial autocorrelation. Finally, the conclusion examines the wider theoretical and policy-related issues arising from the paper.

SPILLOVERS AND LOCAL ECONOMIC GROWTH

Recent approaches to economic growth have emphasised the importance of knowledge spillovers [START_REF] Romer | Increasing Returns and Long-Run Growth[END_REF]. Such spillovers may foster growth if innovations and improvements in one organisation yield external benefits to other firms without the beneficiary paying full compensation [START_REF] Glaeser | Growth in cities[END_REF]. An important distinction is often made between dynamic knowledge externalities, which reflect the role of prior information accumulations on growth, and static externalities (such as economies arising from the co-location of firms in an industry close to major suppliers), which influence overall spatial patterns of location [START_REF] Henderson | Industrial development in cities[END_REF]. As dynamic externalities are fostered by a history of interactions and long-term relationships, spatial proximity may play a critical role in facilitating the transmission of these effects ( [START_REF] Van Stel | Knowledge spillovers and economic growth: an analysis using data of Dutch regions in the period 1989-1995[END_REF]. However, whilst there is considerable agreement that such externalities are important, there are conflicting views as to the type of spillover effects which are most beneficial. In particular, there is a debate as to whether spillovers occur mainly within industries (localisation economies), across industries (Jacobs externalities) or are associated with the overall size and population density of a local economy (urbanisation economies) [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF].

Much recent literature has distinguished three alternative theoretical approaches which generate hypotheses for the testing of the relative importance of spillover effects (VAN OORT, 2005). The first view, the Marshall-Arrow-Romer (MAR) approach, argues that knowledge is primarily sector specific and hence specialisation enhances growth as it facilitates these within-sector spillovers. This view also argues that local market power encourages growth as it facilitates the internalisation of the benefits from new knowledge. A second approach, associated with [START_REF] Porter | On Competition[END_REF][START_REF] Porter | Locations, clusters and company strategy in[END_REF], agrees that spillovers are primarily sector specific but argues that competition stimulates innovation and growth as firms are pressed to innovate to survive and prosper (PORTER, 1990). The third view, associated with JACOBS (1969), agrees with Porter that competition promotes growth, but also argues that diversity encourages growth as knowledge spillovers frequently occur across sectors. Indeed, such cross-sector spillovers may facilitate more radical innovations than those arising from within-sector spillovers which are likely to take the form of incremental changes to existing technologies [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF].

Whilst the three alternative approaches offer distinct hypotheses concerning the nature of spillovers and competitive effects, the dichotomy between specialisation and diversity 8 risks oversimplifying a complex phenomenon. Some relatively distinct sectors may share some commonalities in terms of, for example, similar customers, technologies and knowledge-bases. If such commonalities foster spillovers, then the benefits gained by a particular sector may be influenced by the presence of related economic sectors rather than diversity per se [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF]. In the corporate strategy literature, for example, it is frequently argued that related diversification is more profitable than unrelated diversification due to enhanced synergies and the ability to utilise core competences and surplus assets (including knowledge) more efficiently across related areas [START_REF] Bruche | Corporate Strategy, Relatedness and Diversification[END_REF]. However, whilst the strategy literature focuses upon the benefits of spillovers across related activities within a firm, economic geography emphasises the importance of spillovers across firms within a specific location. Taken together, these arguments would suggest that both spatial proximity and relatedness contribute towards enhancing spillovers.

One complication in assessing the impact of spillovers arises from the possibility that different types of spillovers have differing impacts on local growth. [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF], for example, argue that related variety (a term they use in preference to related diversity) is likely to be positively associated with employment growth as such external effects often take the form of radical cross-sector innovations involving the creation of new products and technologies. Conversely, within-sector externalities are likely to lead to incremental improvements within a sector and may be positively related to productivity growth. As unrelated variety is less likely to generate spillover effects, it is unlikely to yield direct benefits in terms of employment or productivity growth although it may enhance stability and long term growth if it protects a local economy from sectorspecific demand shocks. These arguments are of some importance as most of the academic literature (including the present study) concentrates on employment growth and, consequently, might underestimate the importance of specialisation externalities and unrelated variety to regional growth and stability.

The concept of relatedness provides a useful basis for theorising about sector differences in spillover effects. For example, sectors operating with highly specialised technologies, may find it difficult to benefit from spillovers as there are few local sectors utilising similar technologies. Conversely, sectors operating on a more generic or diverse basis may find more opportunities to exploit spillovers [START_REF] Bishop | Explaining spatial patterns of industrial diversity: an analysis of sub-regions in Great Britain[END_REF]. This argument might support the view that services and manufacturing sectors benefit disproportionately from diversity. [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF], for example, notes that many services are highly diversified in terms of the range of customers and inputs required and may benefit more from a diverse local economy than some manufacturing sectors that have a narrower customer and input base. Other differences might be related to different degrees of tradability across regional boundaries [START_REF] Deidda | Spatial externalities and local economic growth[END_REF]. The demand for non-tradables (including many services), is limited by local demand and, consequently, there are limits to the extent to which a non-tradable sector can specialise and take advantage of localisation economies. However, tradables (much manufacturing industry) operate in more geographically diverse markets and are less constrained by the need to locate close to consumers. Such industries can become more concentrated to take advantage of specialisation externalities and economies of scale (KRUGMAN AND , 1995). However, it is important to recognise that modern telecommunications systems have enabled the delivery of many services remotely by phone or the internet. This has enabled some services to concentrate in certain locations and potentially gain benefits from local specialisation.

Of course, just as the distinction between specialisation and diversity is oversimplified, the same criticism can be levelled at the distinction between manufacturing and services.

These sectors are far from homogenous and the rise of new services associated with modern technologies may have further enhanced the heterogeneity of the sector. BLIEN AND SUEDEKUM (2005), for example, make a distinction between advanced services (e.g. consulting, higher education) and basic services (e.g. cleaning, domestic services).

They argue that advanced services typically involve a variety of skilled professionals who may potentially generate significant spillovers through personal interactions. This is in contrast to less sophisticated services where the opportunity for significant developments through the interaction of such professionals is more limited. Other researchers utilise slightly different classification schemes to reflect the heterogeneity of services. [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF], for example, distinguishes industry (primarily manufacturing) from three types of services -distribution, personal and business services, whilst other studies (e.g. [START_REF] Deidda | Spatial externalities and local economic growth[END_REF][START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF] conduct analysis at the sector level, typically utilising 2-digit sectors. Given the multiplicity of factors potentially influencing the extent of spillovers, a disaggregated approach would seem to offer the best way forward for understanding these complex issues. A third type of spillover is possible if benefits arise from the size and density of a local economy and potentially benefit all firms regardless of their industry (ESSLETZBICHLER, 2005). These urbanisation economies (often conflated with Jacobs-externalities) may emerge from a variety of sources including a superior infrastructure, larger labour markets, universities, business networks and higher level government functions. Conversely, size may be associated with increased costs arising, for example, through increased congestion and this may offset any urbanisation economies. Given that the local units used in the empirical analysis of externalities are typically of varying size and density, it is essential to control for these effects in empirical analysis.

A final issue of some importance is the spatial extent of spillovers. Whilst it is reasonable to argue that proximity promotes spillover effects and knowledge externalities decline over distance ( [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF], it is not clear how to delineate the area over which spillover effects occur. Moreover, the spatial extent of spillovers may differ substantially across sectors. Given that the spatial units for which data are typically available are administrative units and are not defined with spillover effects in mind, there may be interdependencies across observations. Externalities that generate employment growth in one sub-region may impact on growth in adjacent regions leading to interdependence between employment growth in both regions. Thus, it may be of considerable importance (at least for some sectors) to take into account such dependencies through the use of spatial econometric techniques. In addition to spatial proximity, wider spatial effects may operate across broader regions. These may, for example, reflect the operation of regional labour markets, geography (e.g. peripherality), cultural effects and the influence of spatial regimes operating through regional policy organisations ( [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF]. In the UK, for example, it has frequently been argued that a "north-south divide" has existed in growth rates [START_REF] Roberts | The growth performance of the GB counties; some new empirical evidence for 1997-93[END_REF]. This may be associated with skill differentials, the historical impact of industrial structure and geographical factors such as proximity to the capital city.

Consequently, it is necessary to take into account the possibility of this broader spatial heterogeneity in any modelling.

EMPIRICAL STUDIES

Many empirical studies use variants of a model introduced by GLAESER et al (1992) in which employment growth is used as a proxy for performance. This study finds that employment growth is positively related to competition and diversity whilst specialisation reduces growth. These conclusions are interpreted as evidence in favour of the Jacobs approach. However, in a study of eight U.S. manufacturing industries, [START_REF] Henderson | Industrial development in cities[END_REF] find evidence of both MAR and Jacobs-type externalities, with the latter only of relevance for new high technology industries. [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF] notes that some of the differences between these studies may be attributable to different data sources and industry samples, whilst [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF] has pointed to various methodological problems. Of more general concern is the use of employment growth as a 13 proxy for performance. Given that externalities imply a change in output not fully accounted for by a change in inputs, total factor productivity (TFP) would be a better measure of performance. However, in most studies, the use of employment growth as the dependent variable is necessary as a lack of data on local sector output and capital stock preclude the measurement of TFP. This may lead to a number of problems in interpreting the results of empirical studies [START_REF] Deckle | Industrial Concentration and Regional Growth: evidence from the prefectures[END_REF]. In particular, externalities which have a beneficial impact on TFP do not necessarily yield proportionate increases in employment (CINGANO AND SCHIVARDI, 2004). For example, if a firm benefits from a positive productivity increase arising from an externality, employment may fall if the elasticity of demand is low (COMBES, MAGNAC AND [START_REF] Combes | The dynamics of local employment in France, Institute for the Study of Labor[END_REF]. Thus, whilst employment regressions provide an important insight into the employment implications of externalities, they do not necessarily provide a clear picture of the productivity impact.

Despite these problems, policy makers are frequently concerned with employment creation as an objective and hence the emphasis on employment is of interest from a policy perspective, provided the caveats concerning the method are highlighted.

Whilst the number of studies utilising employment growth regressions has grown in recent years, the results are inconclusive. Many studies find that specialisation has a generally negative impact on growth, including those for France by [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF] and Italian studies by [START_REF] Deidda | Spatial externalities and local economic growth[END_REF]PACI and[START_REF] Paci | Externalities and local economic growth in manufacturing industries[END_REF]. Conversely, a further Italian study by [START_REF] Forni | Knowledge Spillovers and the Growth of Local Industries[END_REF] and a Dutch study by VAN SOEST et al (2006) find a positive impact. There are many studies that find a broadly positive impact for diversity (e.g. PACI and USAI, 2002; [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF] 2005) find no systematic long-term evidence of diversity externalities for Canada. As far as competition is concerned, data limitations often ensure that variables that proxy for competition are directly related to firm size and it is difficult to distinguish between the impact of competition and scale economies. However, in general terms, most studies find a positive impact for competition and/or a negative impact of firm size (e.g. [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF][START_REF] Deidda | Spatial externalities and local economic growth[END_REF].

A small number of recent studies have used alternative measures of performance (e.g. CINGANO and SCHIVARDI, 2004; [START_REF] Van Stel | Knowledge spillovers and economic growth: an analysis using data of Dutch regions in the period 1989-1995[END_REF] However, the results of these studies are far from consistent. Moreover, the studies typically use a higher level of aggregation than most employment based studies or rely upon restricted samples of firms or sectors [START_REF] Deidda | Spatial externalities and local economic growth[END_REF]. Another strand of research has sought to focus attention upon differences across a few broad sectors (e.g. [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF][START_REF] Blien | Local economic structure and industry development in Germany[END_REF]; [START_REF] Van Stel | Knowledge spillovers and economic growth: an analysis using data of Dutch regions in the period 1989-1995[END_REF][START_REF] Deckle | Industrial Concentration and Regional Growth: evidence from the prefectures[END_REF]. The different sector breakdowns, methods used, performance measures and countries examined once again makes any consistent pattern of results difficult to ascertain. However, the results for manufacturing are reasonably consistent suggesting no evidence of positive specialisation externalities, whilst diversity has either a positive or insignificant impact on growth. There is no consistent pattern apparent for competition, whilst the sign and significance of the results for services differ widely across the various categories. The conflicting results of the broad sector studies suggest that a more disaggregated approach may be useful. [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF] examines 94 sectors in France and finds that that specialisation typically has a negative impact on employment growth in services and usually a negative or insignificant impact on industry. Diversity typically has a positive relationship on employment growth in services but a negative or insignificant impact on industry, whilst competition generally has a negative impact on growth across all sectors.

However, there are a number of sectors which do not fit these patterns and the magnitude of the various effects differs, suggesting that whilst the industry/service distinction is useful, it masks some within-sector differences. This point is emphasised by an Italian study by [START_REF] Deidda | Spatial externalities and local economic growth[END_REF] which concludes that, whilst specialisation externalities are mostly negative for services and manufacturing, the magnitude of the effect is much greater for services. Moreover, whilst diversity externalities are positive for the aggregate economy as a whole they play a positive role in less than half of the individual sectors.

The importance of examining externalities at a disaggregated level is emphasised by studies which take into account spatial autocorrelation. [START_REF] Deidda | Spatial externalities and local economic growth[END_REF], for example, find spatial autocorrelation in 10 out of 34 sectors, whilst [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF], finds important differences across four broad sectors. In addition, a number of studies, including VAN OORT (2007) find that regional dummies representing broader spatial regime effects are linked to growth. Taken together, these results imply that spatial relationships across both contiguous and wider areas need to be included in the analysis of externalities but the importance of such effects may be sector specific. Most empirical studies define diversity in terms of a broad measure across the economy as a whole (e.g. the Herfindahl Index). However, the theoretical considerations outlined in the previous section suggest that the distinction between related and unrelated variety may be important. Several recent studies confirm this. [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF], for example, conclude that whilst related variety is positively related to local employment growth in Holland, this is not the case for unrelated variety. [START_REF] Forni | Knowledge Spillovers and the Growth of Local Industries[END_REF] also find that the existence of related industries is important for local growth, whilst FELDMAN and AUDRETSCH (1999) show that the existence of science-based complementary industries stimulates local innovative activity.

Finally, it is worth noting that many studies include population density as an explanatory variable, typically to proxy for urbanisation economies. Again, disaggregated studies find important differences across sectors. However, there is relatively consistent evidence of a negative impact of density on growth in manufacturing from the recent studies by [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF], [START_REF] Deidda | Spatial externalities and local economic growth[END_REF] and [START_REF] Blien | Local economic structure and industry development in Germany[END_REF]. The evidence on services is less clear but, generally, suggests a positive or non-significant impact. [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF] interprets this as evidence that congestion effects outweigh any positive spillover effects in manufacturing. This may arise from increased costs for manufacturing products that need to be transported to geographically diverse markets.

It is clear from this brief review of the empirical evidence that there remain many unresolved issues concerning the impact of externalities on local growth. Given that theoretical considerations and the limited existing evidence suggest that spillovers may differ across sectors, the most promising avenue for further research would seem to involve pursuing sector level studies. The remainder of this paper presents an empirical study that takes this approach and also considers related and unrelated diversity, crossboundary spillovers and region-specific effects.

THEORETICAL MODEL

The theoretical framework underlying the empirical analysis of this paper is a version of the commonly used [START_REF] Glaeser | Growth in cities[END_REF] model. This approach is based on a simple model of production incorporating a single labour input, a simplification which reflects the lack of data on local capital inputs which typically limits most empirical studies.

Suppose that a firm has a production function A t f(l t ), where A t represents technology at time t measured nominally and l t represents labour input. Profit maximization yields the standard condition A t f′(l t ) = w t where w t is the wage rate. Taking logs, this can be written in terms of growth rates as:

(1)

( ) ( )         ′ ′ -         =         + + + t t t t t t l f l f w w A A 1 1 1 log log log
          =         + n competitio Local economies on Urbanisati ies externalit Jacobs ies externalit MAR g A A t local t local , , , log , 1 ,
(2) Setting ( )

) 1 0 ( 1 < < = - α α l l f yields: ( ) . log log log , 1 , 1 1 g A A w w l l t national t national t t t t +         +         - =         + + + α (3)
If it is assumed that wage growth and the growth of national technology do not vary across regions, then (3) implies that employment growth can be explained by the measures of externalities and competitive effects contained in g(.). (Initial empirical models included average earnings to reflect wage differences across sub-regions but the results were almost invariably insignificant and are not presented in the paper). utilising the 1992 SIC classification scheme and covering the period 1995-2002. It is difficult to examine longer term trends due to the changes to the system of collecting employment data from 1998 onwards. Data from 1995 to 1997 have been rescaled to be consistent with the new system but earlier data reflect the previous system [START_REF] Partington | The launch of the Annual Business Inquiry[END_REF]. Data were collected for 203 areas at the local authority, county and unitary authority level. These areas are administrative units and vary from large, densely populated urban regions to smaller, rural sub-regions. Inevitably, this implies that there may be spillovers across areas which have strong economic connections and, consequently it is important to examine spatial autocorrelation.

The 2-digit classification scheme identifies 60 separate sectors although three have zero employment and the data on agriculture are incomplete. The sectors differ considerably in size varying from a few hundred employees to two and a half million. For many of the smaller sectors, sub-regional employment is very small, implying that small changes in employment can give rise to substantial changes in growth rates. Consequently, it was decided to concentrate on the largest 23 sectors, which were each responsible for over 1% of GB employment in 1995. The basic details of the sample industries are presented in and business services. Such a classification is useful in examining the extent to which broader patterns can be identified in the sector results. Individual sectors vary in size from retail, which accounts for over 10% of GB employment to manufacturing of rubber and plastics goods accounting for barely 1% of employment. There are also variations in growth patterns, with manufacturing sectors generally exhibiting falling employment, whilst services typically exhibit growth.

Table 1 inserted approximately here

The dependent variable, employment growth, is defined as the change in the log of employment in a sector in a particular area over the period 1995-2002. This time period is one of positive economic growth and stable levels of diversity and, consequently, the impact of diversity can be examined in the absence of major changes in economic structure (BISHOP AND GRIPAIOS, 2007). However, it is important to recognise that the relationship between diversity and growth may change in more turbulent periods. For example, if industrial structure is changing rapidly, as often occurs during an economic downturn, particular sectors may experience rapid employment change primarily as a consequence of these system-wide factors. This may disrupt the relationship between diversity and growth within sectors affected by such changes.

All explanatory variables are measured in 1995 and are in log form (apart from a regional dummy). Sector specialisation is measured by a location quotient, defined as the the proportion of employment accounted for by the sector nationally. Whilst this is consistent with the approach adopted in most studies, there are some limitations in using the location quotient as a measure of MAR externalities. A high degree of specialisation may, for example, reflect the dominance of large scale production plants rather than the scope for significant within sector-spillovers. Moreover, the measure purely concentrates upon labour specialisation, neglecting variations in other inputs such as capital.

Unrelated variety is measured by the commonly used entropy measure which can be defined as:

        = ∑ = si n i i S E 1 ln 1 (4)
s i is the share of the ith 2-digit Standard Industrial Classification (SIC) category in a region's total employment and there are n different 2-digit categories. E varies from zero if all employment is concentrated in one sector to ln(n) if employment is spread evenly across all sectors.

It is possible to derive a measure of related variety by computing an entropy measure at, the 4-digit level for the economy as a whole and decomposing this into related and [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF]). However, economy-wide related diversity is not the key issue for sector analysis; rather it is relatedness specific to the individual sector under consideration. In order to measure this type of relatedness, an entropy measure was calculated at the 4-digit level within every 2-dgit sector. This method is consistent with [START_REF] Frenken | Related Variety, Unrelated Variety and Regional Economic Growth[END_REF] approach but applies it at the sector level. It is important to recognise that both entropy measures, in common with many similar measures, are reliant upon the validity of SIC codes as a mechanism through which to capture related and unrelated variety. However, classification of establishments to SIC codes is primarily done on the basis of product relatedness and neglects other aspects of relatedness such as technological similarities and knowledge transfers. SIC codes are hence an imperfect measure of variety but capture one important dimension and have the advantage of being readily available.

Growth regressions typically include a variable representing competitive effects.

However, there are contrary views as to the theoretical impact of competition on growth ( VAN STEL AND NIEUWENHUIJSEN, 2004). One view is that competition stimulates firms to innovate and thereby generates growth, whilst another approach argues that growth is promoted by market power as firms can more easily internalise the benefits of new developments ( [START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF].Whichever view one takes, measuring market structure at the local level is a problematic exercise as local concentration ratios or similar measures are not available. Consequently, the paper utilises a measure based on size band data defined as the proportion of establishments in the sector with 10 or fewer employees relative to the proportion in this category in GB as a whole. Whilst such a Population density, defined as population per square kilometre, was used as a proxy for urbanisation economies (DEWHURST AND [START_REF] Dewhurst | Specialisation and regional size, paper presented to the ESRC Urban and Regional Economics Seminar Group meeting[END_REF]. Finally, the possibility of spatial heterogeneity was also included by using dummies for different types of regions. Recent studies by by [START_REF] Roberts | The growth performance of the GB counties; some new empirical evidence for 1997-93[END_REF] and [START_REF] Bishop | Explaining spatial patterns of industrial diversity: an analysis of sub-regions in Great Britain[END_REF] reveal some evidence of a north-south divide in patterns of GDP growth and, consequently, a simple north-south divide dummy variable (south = 1) was utilized, with the south defined as the South East, South West and Eastern regions. Other spatial regime variables (e.g. different definitions of the north-south divide) were investigated but generally performed poorly and are not presented in the results.

METHOD AND RESULTS

The sector growth models were initially estimated using standard OLS. However, specification tests revealed evidence of heteroscedasticity which was only partly relieved by log transformations of the variables. As the precise form of the heteroscedasticity was not obvious (as required for weighted least squares), heteroscedastic-consistent robust standard errors were estimated using the jacknife method and all the reported standard errors for the OLS models are of this type. An additional potential source of specification problems is spatial autocorrelation arising from a lack of independence amongst observations [START_REF] Anselin | The performance of tests for spatial dependence in linear regression models[END_REF]. This may reflect either true interaction of variables across spatial units (lag dependence) arising, for example, through spillover effects, or measurement problems (error dependence) reflecting the fact that spatial units do not reflect the correct spatial extent of relevant variables. These issues were examined by conducting Moran tests for spatial autocorrelation and LM tests to distinguish between error and lag specifications. The Moran statistic suggested the possible existence of spatial autocorrelation in eleven sectors, although in three cases (sectors 45, 50, 54) subsequent investigation revealed non-significant spatial coefficients and hence the OLS model was retained. In the remaining eight cases, the error specification was preferred in six cases and the lag specification in two cases suggesting that measurement related issues are of particular significance. For these eight sectors, maximum likelihood models incorporating either lag or error dependence were estimated with spatial dependence represented by a contiguity based binary weight matrix. Within the matrix, areas were coded as 1 if they shared a geographical boundary and zero otherwise. (This simple order of contiguity was preferable to second order contiguity which did not significantly alter the conclusions or improve the power of the models). The spatial models either eliminated or significantly reduced heteroscedasticity but only resulted in minor changes in the pattern of significant variables compared to the OLS estimates.

The results of the sector models are presented in Tables 234. Most of the OLS models (with the exception of sector 65) have reasonable levels of fit and are comparable to other studies of this type. The R 2 's for the spatial models are pseudo-R 2 's and hence not directly comparable to those of the OLS models. However, in all cases, the log-likelihood measure of fit for the spatial models is an improvement over the OLS alternative and the spatial coefficient (representing either a spatial lag or error) is significant at the 10% level. Inspection of the correlation matrix and other indicators revealed no serious evidence of multi-collinearity.

Tables 2, 3 and 4 inserted approximately here

There is little evidence of inconsistencies across sectors in terms of the signs of the significant variables apart from the north-south and density variables. This suggests that differences across sectors are primarily associated with the magnitude or presence/absence of an effect rather than its direction. The most consistent result is the significant, negative impact of specialisation on employment growth which is observed in all but one of the equations. This confirms the broad results of the recent sector studies by [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF] and [START_REF] Deidda | Spatial externalities and local economic growth[END_REF]. However, it is important to recognise that these results (in common with those of similar studies) cannot be interpreted as definitive evidence against the presence of MAR externalities. It is possible that specialisation may be beneficial but primarily result in improvements in productivity which displace labour due to demand constraints on expanding output.

The competition (or scale effect) variable is significantly positive in 16 of the 23 sectors, implying that a large number of small firms in a sector is generally conducive to employment growth. Interestingly, two of the three service sectors for which the variable is insignificant (75 and 80) are public sector dominated sectors. This is understandable, as one might expect competitive effects to be less important when a sector is characterised by public ownership. The positive impact of local competition on most manufacturing industries is more surprising as it might be expected that such industries would be more affected by national or international competition. The positive sign may possibly reflect a product life-cycle effect, with many small, young firms able to generate rapid employment growth in early years, whilst this is more difficult for larger firms operating at later stages of the life-cycle. It is also interesting to note that the consistent results concerning competition differ markedly from those found in previous studies. [START_REF] Deidda | Spatial externalities and local economic growth[END_REF], for example, find the impact of competition is variable and generally insignificant whilst COMBES (2000) finds competition to have a negative impact where significant. These differences may reflect different measures of competition, countries and time periods and further research is needed on the impact of the variable. However, the consistent and significant results of the variable used in the present study suggest that this type of measure may have some merit.

Unrelated variety is insignificant in 15 sectors, which is consistent with FRENKEN et al's (2004) argument that unrelated variety is unlikely to generate employment growth.

However, there are eight sectors for which a significantly positive effect is observed which suggests that sectors are not homogenous. Interestingly, some broad differences between manufacturing and services can be observed with five out of the eight industrial sectors showing a positive impact in contrast to only three of the fifteen service sectors. These results are more consistent with the results of [START_REF] Deidda | Spatial externalities and local economic growth[END_REF] than [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF] who finds that unrelated diversity generally has a negative or significant impact on industry. Related variety is insignificant in all but four sectors and the sign is inconsistent; it has a positive impact in three sectors and a negative impact in one. Clearly, this fails to support the contention that related variety generally stimulates employment growth. Taken together, these results suggest that the distinction between unrelated variety and related variety is important and that differences across sectors are of some significance.

The density variable performs poorly being significant in only seven equations and with an inconsistent sign. This suggests that either urbanisation economies are not of general significance or are offset by diseconomies, possibly arising from congestion. Again, the results are more consistent with the pattern found in [START_REF] Deidda | Spatial externalities and local economic growth[END_REF] than [START_REF] Combes | Economic Structure and Local Growth: France 1984-93[END_REF]. The north-south divide dummy is significant in nine equations. For manufacturing industries, the sign is negative when significant implying better performance in the north than the south. In other sectors the sign is generally positive, suggesting the reverse. This implies that there are some broad spatial effects at work in some industries but the simple notion of a north-south divide masks significant sector differences. Spatial autocorrelation is most apparent in business services and involves an error specification, suggesting that interdependencies are related to measurement errors reflecting the artificial nature of administrative boundaries in delineating local markets for these services.

CONCLUSION

The analysis presented in this paper highlights a number of issues that are of significance for future research concerning local growth and the development of policies to promote regional development. The consistently negative impact of specialisation suggests that encouraging local specialisation is not a policy option that is likely to yield substantial short-term gains in terms of employment creation. However, it is possible that there may be long term benefits accruing from productivity improvements associated with specialisation which are not apparent from employment regressions. This raises an interesting dilemma for policy makers, who are often concerned with employment creation as a policy objective. From a theoretical point of view, it also emphasises the limited nature of the recommendations that can be made on the basis of the sign of the specialisation coefficient in employment regressions. Unfortunately, in the absence of a substantial improvement in the availability of sub-regional data, it is inevitable that much future empirical work will continue to use this approach.

As far as diversity is concerned, the results suggest considerable heterogeneity across sectors with just under half of the sectors examined benefiting from one of the two forms of diversity. In contrast to the hypotheses in the literature, unrelated variety has a wider impact than related variety, suggesting that a sector approach might question the results of the more aggregated literature. The heterogeneity of the impact of diversity is perhaps not surprising, given that the opportunity to benefit from spillovers is likely to depend critically on the specific technologies, customers and knowledge relevant to a particular sector. Indeed, it seems sensible to conclude that diversity is a complex and heterogeneous phenomenon, rather than looking for a simple relationship between growth and diversity that operates across all sectors. This implies that policy should be concerned with understanding and developing specific opportunities for spillovers, rather than simply promoting the general idea of diversity. Of course, diversity may also yield other benefits, such as improving stability, which are not directly examined in this paper.

One interesting question that arises from the study is where to draw the line between diversity and specialisation. Relatedness might, for example, be regarded as evidence of the existence of a set of sectors which constitute a cluster rather than an indication of diversity. Indeed, making a simple distinction between specialisation and diversity masks the fact that the degree of commonality between sectors varies along a continuum.

Thus, future research might usefully develop more sophisticated measures of the degree of commonality across sectors. One possible method is through the use of input-output analysis to examine demand and supply linkages (e.g. [START_REF] Forni | Knowledge Spillovers and the Growth of Local Industries[END_REF], although this approach will inevitably be constrained by the limited availability of local data.

Another issue raised by the paper concerns the existence of wider spatial effects across economic boundaries. The diverse results concerning spatial autocorrelation suggest that the spatial extent of markets may differ across industrial sectors. The administrative boundaries for which data are collected may be reasonable approximations for some sectors but inappropriate in other cases. Thus, even attempting to construct boundaries (such as functional urban areas) to represent more economically coherent regions, may not fully eliminate spatial autocorrelation. From a policy perspective, this implies that policy makers need to be aware of differences in the spatial extent of markets across which they define clusters and implement policy.

Finally, the generally positive impact of the share of small firms on employment growth suggests that encouraging local competition may be an appropriate policy option. Indeed, the generality of this effect implies that this may be an easier policy to implement than polices stimulating the development of a particular cluster, which requires detailed knowledge of spillovers, linkages and the spatial markets appropriate to a specific sector.

Given the difficulties of such an exercise, policy might be best centred on creating the conditions appropriate to enhancing competitiveness across all sectors rather than attempting to micro-manage specific sectors. Future research into local growth should also perhaps place more attention on the role of competition and firm size, rather than the current emphasis on diversity and specialisation.

F

  of technology is assumed to be the sum of the growth of national and local technology. The growth of national technology reflects changes in product prices and nationwide sectoral technology shifts, whilst local technological growth is assumed to be exogenous to the firm but related to local technological externalities and competitive effects. Thus:

  sub-regions of Great Britain at the 2-digit industry level were obtained from the UK's National On-line Manpower Information System (NOMIS)

  distributive services, personal services (mainly sold to consumers)

  employment accounted for by a sector in a specific locality divided by

  measure competition, it might also be a proxy for the typical size of local business units and hence reflect scale factors. Hence, care needs to be taken in the interpretation of this variable.

Table 1 .

 1 The first column classifies the sector into one of the four broad classes identified in[START_REF] Van Oort | Spatial and sectoral composition effects of agglomeration economies in the Netherlands[END_REF] -namely industry (manufacturing, construction and

Table 1 :

 1 D.P., GERKING, S. &VAN OORT, F.G. (2006). Spatial Impacts of Agglomeration Externalities, Journal of Regional Science, 46(5), pp 881-899. Employment in GB 2-digit sectors 1995

	o
	r
	P
	e e r
	R e v i e w
	O n
	l y

Table 2 :

 2 Industry growth models

	Sector

Table 3 :

 3 Growth models for distribution (50-63) and business services (65-74) ** (*) indicates significance at the 5% (10%) level respectively; figures in brackets after the regression coefficients are heteroscedastic consistent standard errors; N= 203 in all cases.

	Sector

Table 4 :

 4 Growth models for personal services ** (*) indicates significance at the 5% (10%) level respectively; figures in brackets after regression coefficients are heteroscedastic consistent standard errors; N= 203 in all cases.

	Sector

< R1 -General Regional Economics < R -Urban, Rural, and Regional Economics, R12 -Size and Spatial Distributions of Regional Economic Activity < R1 -General Regional Economics < R -Urban, Rural, and Regional Economics


Professor, Thomas F Rutherford

Professor, Hannu Törmä

Methods and Programming < C -Mathematical and Quantitative Methods, D58 -Computable and Other Applied General Equilibrium Models < D5 -General Equilibrium and Disequilibrium < D -Microeconomics, R58 -Regional

Keywords: C68 -Computable General Equilibrium Models < C6 -Mathematical Numeric general quilibrium modelling, payroll taxation, value-added taxation, CGE modelling, RegFin regional model. JEL: C68, R11, R13 eine Reform der Mehrwertsteuer, bei der die Lohnkosten nicht steuerlich veranschlagt werden. Unsere Simulationen scheinen darauf hinzuweisen, dass eine regionale Differenzierung der Sozialbeiträge von Arbeitgebern sowie eine Reform der Mehrwertsteuer wirksame Instrumente der Regionalpolitik darstellen könnten Lohnsteuer Mehrwertsteuer CGE-Modelle Regionalmodell RegFin JEL: C68, R11, R13 Tributación sobre los salarios Impuesto de valor

In this paper we introduce a computable general equilibrium (CGE) model for the Finnish regional economy, RegFin. This multi-sector and interregional model characterizes economic activity in the regions of Lappi, Pohjois-Pohjanmaa, Kainuu, Keski-Pohjanmaa and the rest of Finland. We consider the macroeconomic effects of a regional policy applied to North Finland that is similar to tax reforms which have been implemented in Norway. Tax incentives affect individual choices regarding both migration and employment. We also study a value-added tax reform where labour costs are exempted from the tax base.

Our simulations seem to indicate that the regional differentiation of the employers' social security contributions and the value-added tax reform could be effective tools of regional policy.

Finland experienced an economic boom from 1985 to 1990, but when the 'bubble' in the finance and housing markets burst, there was a loss of 15% in GDP between 1991 and 1995. This caused severe problems for many regions, especially in the eastern and northern parts of the country. The population of North Finland subsequently decreased by over 33 000 inhabitants between 1990 and 2002. At the end of 2002 there were 715 000 people living in the four northern regions of Lappi, Pohjois-Pohjanmaa, Kainuu and Keski-Pohjanmaa, representing 14% of the Finnish population of 5.2 million. The unemployment and net outward migration figures reveal the severity of the problems.

(Table 1 here) Unemployment figures suggest that the economy was at full capacity for all regions in 1990, but over 1991-95 unemployment rates grew by three to fourfold in North Finland. The situation was worst for Kainuu, where 23.5% of the labour force was without a job in 1997. The turning point came in 1994 when the recovery started from the south. The labour force began to move after new jobs were created.

Net outward migration rates have grown considerably in all regions of North Finland since 1994. The situation has been worst for Kainuu and Lappi, where in the worst years 3-6% of the labour force has migrated.

There are some arguments in favour of regional policies which staunch out-migration. The fiscal federalism literature states that, for instance, without intervention, congestion and fiscal externalities can lead to inefficiencies in the spatial allocation of labour and capital. [START_REF] Peter | Efficiency Effects of Changes in Commonwealth Grants to the States: A CGE Analysis[END_REF] studied these and other regional policy measures using their Commonwealth/State Funding (CSF) CGE model for Australia. It might be possible that some features of their model could be incorporated into RegFin. One aspect that we will develop is the migration block to better take into account the fact that the spatial pattern has become more and more mosaic in Finland. Second, when labour out-migrate, there will be sunk costs in the Economists admit that one cannot control the market economy in the long run. Some decision makers, however, think that the government should try to do something in the short run. Many economic and social problems might be avoided if there was enough adjustment time for both the sender and receiver regions. The regional government in North Finland have no means themselves to cope with the serious problems. Most of the municipalities have growing negative budget balances, so the only way to do something is to rely on the goodwill of the national government. There are, however, no guarantees that public policies against out-migration and unemployment are effective. This was demonstrated in Giesecke and [START_REF] Auerbach | A Large-Scale Dynamic Multi-Regional CGE Model with an Illustrative Application[END_REF] where the Australian FEDERAL-F CGE model was used to test whether it would be possible to apply government fiscal policy, in a budget-neutral setting, to stop the GDP share of Tasmania from decreasing. One result was that the phasing out of the payroll tax over five years would increase the GRP and employment only slightly because rising wages would offset the other more favourable effects.

The present government agreement states that regional policy measures will be used to reduce the high rate of out-migration from the north. We do not know a priori if this is a good or bad policy objective, but there are tools for studying the effects of alternative policies to achieve this objective. Political decision makers clearly lack the quantitative tools and policy assessment services at the regional level in Finland for their value-based decisions.

Regional CGE modelling

CGE modelling has gained much attention during the last thirty years. Partridge and Rickman (1998) is the most comprehensive survey article of regional and multiregional CGE models to date. In their footnote 1 they mention five surveys for mostly national models on taxation policy, international trade, the development policy of LDC, energy and environmental issues in their critical analysis. Partridge and Rickman also list the key features of some 28 regional CGE models in their Table 1, of which over a dozen are multi-regional. There are also several sub-national models. Despotakis and Fisher, 1988 is an early example and a clear presentation of a CGE model for the Californian economy comparing the use of generalized (flexible) and ordinary (fixed) Leontief production functions.

In footnote 2 of Partridge and Rickman, 1998 is a reference to [START_REF] Kraybill | Computable general equilibrium analysis at the regional level[END_REF], who mentions a handful of early multi-regional models and gives a short survey, although his emphasis is on comparing CGE to input-output models. An early example is Jones and Whalley, 1989, who The CoPS modelling team of the University of Melbourne, Australia has developed several regional CGE models. The MONASH model (Dixon and[START_REF] Dixon | Dynamic General Equilibrium Modelling for Forecasting and Policy: A Practical Guide and Documentation of MONASH[END_REF]Horridge et al., 1996) has 56 regions and has been developed from the older ORANI model. MMRF-Green has six states and two territories. Finally, the TERM model has 57 regions in a bottom-up manner. These three dynamic regional CGE models have been used in a multitude of applications of Australian national and regional policies. Other wellknown regional CGE models are the Scottish two-region AMOSRUK model [START_REF] Ferguson | The National Impact of Regional Policy: Policy Simulation with Labour Market Constraints in a Two-Region Computable Equilibrium Model[END_REF] and the Brazilian 27-region B-Maria model [START_REF] Haddad | Interregional Computable General Equilibrium Models[END_REF].

Our work on the REGional model for the FINnish economy (RegFin) started in 1994 when we constructed a miniature version [START_REF] Hannu | Large-scaled Regional Policy in Finland 1994 and the RegFin model, The Provincial Council of Etelä-Savo[END_REF]. In 1998 we constructed a model for twelve "lääni" regions to consider the welfare and reallocation effects of government finance cuts [START_REF] Hannu | Regional Computable General Equilibrium Model for Finland[END_REF] [START_REF] Hannu | Integrating Finnish Agriculture into EC´s Common Agricultural Policy[END_REF][START_REF] Hannu | What will EU Membership and the Value Added Tax Reform do to Finnish Food Economy? -A Computable General Equilibrium Analysis[END_REF][START_REF] Risto | Trade Policies and Integration -Evaluations with CGE -Models[END_REF].

The design of the model is presented in the following table .   (Table 2 here) 3. Structure of the RegFin regional model RegFin is built using the blueprint of a well-established computable general equilibrium model. Its uniqueness comes from the fact that the data base has never before been used in a CGE model. The model emphasizes Finnish institutions and the mechanisms of national government economic finance toward the regional economies. Two of perhaps the most serious economic problems of North Finland have been denoted and modelled: unemployment and net migration. North Finland and the rest of Finland are codependent through the allocation of labour, via domestic export and import and through net migration.

The model is static, representing a benchmark equilibrium calibrated to regional economic activity and calculating a "counterfactual equilibrium" in which labour, capital, consumption and trade respond to a new set of policy instruments. The model calculates only the new equilibrium, and the path from the old to the new equilibrium is not revealed. It is, however, possible to perform comparative-static calculations, which are of much value for regional policy analysis. The study of the dynamic evolution of the economy would require at least a recursive version examining a sequence of static equilibriums. We have plans to include dynamics, but here we concentrate on the static model.

We deal here with an equilibrium model where all markets clear and all budget constraints are binding.

There is perfect competition assumed together with constant returns to scale in regional production. Labour markets are an exception to the equilibrium condition, as we allow for unemployment. We are aware that RegFin has the flavour of a disequilibrium model. Due to including unemployment, it could be considered as a computable quasi-Walrasian flex-price model. We feel, however, that it is reasonable to treat

Modelling unemployment

There are several approaches to modelling unemployment. One approach is presented in [START_REF] Peter | The Theoretical Structure of MONASH-MRF[END_REF] where unemployment can be treated either endogenously or exogenously. In the first case, the labour and migration block of the model specifies regional labour supply. With labour supply determined, the labour market and regional migration block determine regional unemployment rates given regional labour wage differentials. With given regional unemployment rates and regional labour supply, regional employment is determined as a residual. Fixing wage differentials determines the demand for labour so that with regional labour supply given, the model will determine regional unemployment as a residual. In the second case, regional wage differentials and unemployment rates are exogenously specified.

Gillespie et al., 2002 use a labour market closure where real consumption wage is negatively related to regional unemployment rate. Wages are determined in accordance with this regional wage curve. Real wages partly determine employment, so unemployment is the difference between regional labour force and regional employment.

Our specification of unemployment is based on the wage curve relation formulated by [START_REF] David | The Wage Curve, Chapter in Palgrave, The New Dictionary for Economics and Law[END_REF]. They consider two regions within a country and assume that region A's unemployment rate is double that of region B. The wage-curve finding states that a worker's wage will then be 10% lower in Region A than the wage of an identical worker in Region B. The mathematical specification for the relationship parameter φ is of the form: 2 = 0.9 φ ==> φ = log(2)/log(0.9) = -6.6

Blanchflower and Oswald postulate that the wage curve is valid in over one hundred countries, including

Finland. This assumption means that we set the following constraint on unemployment.

(2) ur r = (pl r /pc r )

φ
Here ur is the unemployment rate, pl is the wage rate, pc is the consumer price index, and r refers to the regions.

The constraint states that when the labour markets become tight, the demand for labour increases and unemployment decreases, and real wages will increase. This negative relation is evident especially after 1994 when Finland began to recover from the deep recession.

Modelling net migration

There are many possibilities for the migration equation. One way was introduced in Jones and Whalley, 1989, which was based on location-specific preferences in reacting to regional income differences. Ferguson et al., 2004 used an equation wherein migration was determined by the real consumption wage ratio and the unemployment rate ratio between the regions. This was also the case in [START_REF] Gary | A Computable General Equilibrium Approach to the Ex Post Evaluation of Regional Development Agency Policies[END_REF]. Also, Harrigan and McGregor, 1989[START_REF] Mcgregor | Migration Equilibria/Disequilibria and the Natural Rate of Unemployment in a Regional Context[END_REF] show how net migration can be modelled in a CGE model. We follow their example and assume that net migration relative to the lagged labour force is a function of standard of living and unemployment differentials. The migration model is linear and of the form:

(3) netmig i /lforce t-1, i = α + β (grp i /grp j ) -δ (ur i /ur j ) + e 9 The variable netmig is net migration, lforce is labour force, grp is gross regional product (GRP) per capita, ur is unemployment rate, e is the error term, and i and j refer to the regions.

We assume that the rise in the GRP differential correlates positively with the standard of living differential. The parameter β has a positive sign, so we assume a priori that the rise in the standard of living in a region will increase net migration (in-migration -out-migration) toward that region. The unemployment differential, parameter δ, is assumed to correlate negatively with net migration into the region. So the parameter for this term should have a negative sign.

In order to establish parameters for the migration equation we examined a pooled cross section and time series data covering the period 1990-1999. Data from all 20 Finnish regions (n = 200) provided the following estimates for the parameters (significance): β = 0.013 (10%) and δ = -0.008 (5%) with F = 14.686 (1%) and R 2 = 0.106. The signs are correct, but the explanatory power could be better. After writing this article, we estimated the equation again with a larger data set (n = 300), and R 2 rose to 0.67. The coefficient values did not change, but their significance became much better. This relationship determines net migration in the model. Moisio, 1999 summarizes other Finnish research concerning net migration.

Consumption

Apart from labour market disequilibrium and endogenous migration, RegFin is a conventional general equilibrium model. Final demand within each region arises from a representative consumer. Data problems at the regional level prevent us from specifying more households. The representative consumer owns all labour and capital endowments of the regional economy. He sells them at the factor markets, earning factor income to finance his private consumption, which is also dependent on real consumer prices. The representative consumer maximizes a CES (Constant Elasticity of Substitution) utility function defined over the consumption of regional and national products. The representative consumer also pays taxes and receives subsidies and transfers from both the regional and national governments. Central government is divided into two interrelated decision makers: the national and regional governments. Both public agents collect fees and taxes to finance the provision of public goods and services. All relevant tax categories such as output and factor taxes or personal income taxes both at the national and regional level as well as subsidies and transfers are included in the model data base.

Production

Firms are assumed to minimize their production costs. There are 37 sectors per region (see Appendix).

Each region produces for its own use, to satisfy the demand from the other regions, and to participate in domestic and foreign trade. Regional production is modelled through CES production functions with labour and capital as primary inputs. Intermediate factor use is modelled through an input-output model (Leontief structure).

Foreign and domestic trade

Foreign and domestic trade has been modelled assuming that domestic and foreign goods of the same sector are qualitatively different. Armington's assumption (see [START_REF] Armington | A Theory of Demand for Products Distinguished by Place of Production[END_REF] of regionally differentiated products is thus used to explain the cross-hauling of domestic and foreign goods. Domestic goods are produced jointly with exports according to a CET (Constant Elasticity of Transformation) technology.

Imports compete with domestic goods. Foreign imports are used by the regions to satisfy domestic demand for foreign goods. Since RegFin is an equilibrium model, it has several conditions that specify the equality of demand and supply. There is a market-clearing equation for each good and factor. We employ a long-run neoclassical closure in which the trade balance (current account) is exogenous and there is a flexible real exchange rate. The labour market closure is based on a wage curve, so wage, employment and unemployment are jointly determined. Capital stocks are mobile within but not across regions. Final consumption is determined by a conventional neoclassical framework in which consumers maximize welfare subject to the budget constraint. Inter-regional domestic trade is balanced through the income constraints with the relative prices of goods produced in different regions determined endogenously. In the public sector closure, it was assumed that the regional provision of public goods and services is constant in North Finland. The rest of Finland will compensate for the shortfalls in regional tax revenues by lump-sum transfers. It is important to note that our simulation results might be sensitive regarding the choice of the closure.

Benchmark data

The five regions in the RegFin model are Lappi, Pohjois-Pohjanmaa, Kainuu, Keski-Pohjanmaa and the rest of Finland. We have used official data from both regional and national accounts of Statistics Finland.

The same is true for income and expenditure data. A linked set of social accounting matrices (SAMs) were constructed and based on the latest input-output study from 1995. This is also the benchmark year from which RegFin was calibrated. Finally, elasticity values are frequently used literature estimates, and the values are in the range (0 to 4). We conducted some sensitivity analyses of the results by altering the elasticity values. These results are reported in Section 6: Sensitivity analysis. from the year 1990. The objective was to reverse the negative trend that was especially obvious in the 1980s. This included a lack of jobs, a poor economy in business and industry, insufficient qualified personnel and decreasing population figures. The action zone is a superstructure for the following specific measures introduced there: exemption from payroll tax, reduction in the charge on electricity consumption for both commercial enterprises and households, exemption from the investment tax on building and construction work, reduction in personal income tax, increase in child benefits and a release from back payments of loans from the National Education Loan Fund.

These measures have been effective. Eikeland and Pedersen, 1997 have estimated that the number of jobs increased by 3813 or 8.4 percent of the total jobs in the area. They also find that industrial investment has increased since 1990 as has the economic solidity of the enterprises. They report that the population increased by 1921 persons. Unemployment has fallen but is still higher than the average of the country. The supply of qualified personnel to the public sector has also improved.

The political decision makers in the four northern regions of Finland have closely followed what has been done in Norway. In a situation in which they cannot do much to improve their economic situation, they have been lobbying for similar regional economic measures. This is of course a zero-sum game toward the rest of Finland, which should finance these measures.

The literature on the efficiency of indirect and direct taxes is vast. Good references are [START_REF] John | Modelling Indirect Taxes and Tax Reform[END_REF][START_REF] John | Tax Modelling[END_REF] and the wide range of literature they review. Creedy's (2001) analysis does not, however, cover large multi-industry CGE models such as ours. Another good source is Alm et al. (2006), which emphasises the global context of tax reforms. Results from tax incidence analysis emphasise the effect of payroll taxes on the supply and demand of labour. The reform changes the indirect cost of labour, but changes in 13 wages will have an affect on labour demand. On the other hand, changed wages can have an influence on the supply of labour, so the final answer to how employment will change remains uncertain. [START_REF] Gruber | Tax Incidence of Payroll-taxation: Evidence from Chile[END_REF] reviews previous research and reports mixed results concerning to which extent the payroll tax is shifted to wages. His own finding for Chile suggests that the incidence is fully on labour, with only little effect on employment. [START_REF] Don | Tax Incidence[END_REF] state that empirical testing of payroll tax incidence in the US has proved that both employer and employee shares are fully borne on labour. The large tax literature survey of Kesselman and Cheung ( 2004) confirm these findings for Canada. This evidence suggests that introducing a payroll tax will result in lower wages and removing it in higher wages. [START_REF] Don | Tax Incidence[END_REF] point, however, to the result of [START_REF] Fuchs | Economists' Views about Parameters, Values, and Policies: Survey Results in Labor and Public Economics[END_REF], who find that the median belief among economists about the payroll tax is that 20% of the burden is borne by employers. All in all, we should see an increase in wages when we lower labour-related production costs in our simulations.

In our analysis we have decided to focus on the employers' social security contributions. These are payroll taxes as they relate directly to the firm's wage bill with constant percentages. The following chapter reports the results from our model simulations in which we decrease the payroll tax rate. We also study a value-added tax reform where labour costs are exempted from the tax base. Both of these reforms reduce the indirect costs of labour, and we test whether they could decrease unemployment and out-migration.

In each of our simulations we calculate the costs to the national and regional governments. Both of these measures are of interest for the decision makers of North Finland.

Employers' social security contributions as a means of regional policy

We carried out a range of simulations of decreases in payroll taxes (employers' social security contributions), starting with a 10 per cent cut and proceeding in 10 per cent intervals (i.e. -10%, -20%, …, -50%).

We report results below for the case of a halving of payroll taxes in North Finland.

(Table 3 here) We first look at the demand side of the regional economy. The payroll tax reform would lower the indirect costs of labour. The demand for labour would increase because, with the initial factor price ratio, capital would be substituted by labour. This would increase labour incomes and create a short-run increase in aggregate demand that would create economic growth in North Finland. In the long run, both wages and capital rent would increase because of the increase in aggregate demand. The relative factor price ratio would be in favour of capital limiting the growth of the demand for labour. Capital demand and rent would increase both because of the favourable change in the factor price ratio and the increase in economic growth. An increase in capital rent and capital demand would, on the other hand, mean an increase of capital incomes. The disposable incomes of regional consumers would increase. This would further boost aggregate demand and strengthen economic growth, which would have positive multiplier effects on factor and disposable incomes, creating a circle of growth.

On the supply side, the producers would increase their aggregate supply when effective labour costs decrease. Our results seem to indicate, however, that the demand effects would outweigh the supply effects, so consumer prices would increase. The payroll tax reform would create strong economic growth in North Finland. GRP and welfare, measured with the traditional Equivalent Variation (EV) measure, would increase considerably. Economic growth would also decrease unemployment, and 14 000 jobs would be secured. Economic growth and the decrease of unemployment would cause net migration from the North to the rest of Finland to decrease. Halving of the payroll taxes would decrease net migration and foster immigration by about 1057 people. The reform would slightly strain economic growth and welfare and increase unemployment somewhat in the rest of Finland.

The reform would be positive for the regional governments of North Finland because the increase of net income would be FIM 504 million. If the payroll taxes were halved, it would cost the national government FIM 2249 million. If the national government collected the surplus of the regional government, the net cost of the national government would be FIM 1745 million or FIM 2441 per capita.

Value-added tax as a tool of regional policy

Our second simulation was about the value-added tax. We studied a reform where labour costs would be exempted from the tax base. The value-added tax would be based entirely on the use of capital. This reform would benefit labour-intensive sectors. We report here a case where the reform would be fully carried out in North Finland.

(Table 4 here) Implementation of the reform would mean that the effective capital rent would already increase in the short run because the entire value-added tax burden would be on capital. On the other hand, the reform would mean that producers would not have to pay value-added tax on the use of labour. As the effective labour costs decrease, the demand for labour would increase in the short run as dearer capital would be 16 substituted by labour. These relative price and demand changes would mean increasing the short-run factor and disposable incomes and an increase in aggregate demand.

In the long run this economic growth would further increase capital rent and capital incomes. All this would boost economic growth, and a positive growth circle would materialize through multiplier effects.

On the supply side, producers increase their supply when effective labour costs decrease. Our results seem to indicate that the supply effects would outweigh the demand effects because consumer prices would decrease.

The value-added tax reform would also produce considerable economic growth and welfare in North Finland. Unemployment and net outward migration would decrease as aggregate demand increases. The other factor that would decrease unemployment would be the increase of capital rent with respect to consumer prices. Dearer capital would be substituted by labour, unemployment would decrease, and 8 000 jobs could be secured. By means of the value-added tax reform one could decrease net outward migration and foster immigration by about 668 people. The reform would strain somewhat economic growth and welfare, and increase unemployment somewhat in the rest of Finland.

The regional government would benefit from the value-added tax reform. The total benefit would be FIM 423 million. The cost to the national government would be FIM 2535 million. If the national government collected the surplus of the regional government, the net cost would be FIM 2112 million or FIM 2954 per capita.

We now return to the comparison of our results with the findings of previous studies. Our results for the payroll tax reform are partly in line with previous evidence. Wages would increase if the payroll tax rates were lowered. Our results suggest, however, that the burden is not totally on labour but that capital rent would also increase. The primary production inputs would share the burden, and the share of labour 17 would be greater than that of capital. In the value-added tax reform, almost all the burden is on capital because labour is no longer in the tax base.

Sensitivity analysis

A number of elasticities of transformation and substitution in the model are based on limited empirical evidence. In the following we report some sensitivity analyses. In the experiments the corresponding elasticities took the values 0, 1, 2 and 4. All runs were done for both means of regional policy.

We concluded from the sensitivity analyses that our results are in most cases not too sensitive with respect to the elasticity values. There was only little variation in the results with respect to the transformation elasticity between domestic and export goods and the substitution elasticity between domestic and imported goods or the substitution elasticity of regional and national goods. The results are most sensitive with respect to the substitution elasticity of capital and labour.

The key variables, unemployment and net migration, seem to be most sensitive with respect to the value of the substitution elasticity of capital and labour. We found out, however, that differing elasticity values did not change the sign of the key results. In a long-run analysis we might rule out the elasticity value zero. In this case the variations of the results become narrower. The sensitivity of the results should be kept in mind when making conclusions from this study.

Conclusions

The purpose of this paper has been to study tools of regional policy that could be used to restrain unemployment and out-migration in North Finland. As a working tool for our analysis we constructed the multi-sector and interregional computable general equilibrium model RegFin. Our main contribution is the fact that our model is still, after a decade, the only bottom-up interregional CGE model in Finland. It 18 has now been used in twenty applications. The linking of unemployment and net migration to a CGE model has also been done elsewhere. We feel, however, that they should be included in a case where they are growing problems, such as in North Finland.

We have run simulations for one of the regional policy measures used in Norway: the employers' social security contributions (payroll tax). We have also investigated a value-added tax reform where labour costs would be exempted from the tax base. Some key macro economic results were reported from the simulations. We emphasize that we do not want to do a comparative social welfare exercise, but just point to some differences between the two reforms.

Our results seem to suggest that the reduction of the payroll taxes and the value-added tax reform would both be effective tools of regional policy. They would reduce unemployment and out-migration in North Finland. The net cost per capita of the national government would, however, be lower for the payroll tax reform compared to the value-added tax reform. The same is true when we compare the two reforms by the number of secured jobs and by using the standard EV calculation.

Both reforms would benefit labour intensive industries. The reduction of the employers' social security contributions produced the most growth in the output and in welfare because this regional policy measure directly reduces the real price of labour. The regional policy measure, which is "closest" to the problem of too high labour costs, produced more positive effects for employment and was the "cheapest" when measured by the net cost per capita of the national government. At the end, we state that any CGE simulation results, including ours, might be sensitive to the modelling details.

The RegFin model should be developed further. There are at least three aspects of the model that should be investigated. First, the model is static. A dynamic version of the model would reveal the path of the regional economy from the old to the new equilibrium. Second, we should develop the migration block of the model further, perhaps estimating a system of equations where the parameter estimates of both in-and 19 out-migration would be jointly determined. Last, the use of econometric estimation of the sectoral elasticities should be increased. Reliable estimates for sectoral capital-labour substitution elasticities would be valuable.

Halving of the employers' social security contributions or the proposed value-added tax reform are largescaled tax reforms that seem to be effective means of regional policy but are hard to put into effect politically. By means of the RegFin model, a level of the net cost for the national government could be found that would be politically tolerable. We hope that the model simulations will help the decision makers to visualize the regional effects of alternative policy measures in restraining unemployment and outmigration in North Finland.

Finally, we mention that our RegFin simulation results partly influenced the decision of Parliament, where the 13 northern-most municipalities in the Lappi region were given reductions in the employers' social security contributions. The new budget law is in effect for three years. The decision makers in Lappi are pleased with this decision, and they feel that the door to Norway-like regional policy is finally open. iii These regions are chosen for the application. All 20 administrative regions of Finland are represented in the model. With consistent Regional Statistics available in Finland and by using the augmented Flegg location quontient method (Flegg and[START_REF] Flegg | Regional Size, Regional Specialization and the FLQ Formula[END_REF][START_REF] Flegg | Regional size, regional specialization and the FLQ formula: A case study of Finland. An article n Tohmo Timo, Regional Economic Structures in Finland[END_REF], it is also possible to run subregional cases.

F

  , there are unfavorable demographic changes because those moving are usually families with small children.

  constructed a static model for six Canadian regions. Also Liew, 1984 developed a Leontief-type multi-region model for Australia. Today we have several multi-regional CGE models. Just recently in 2003, the Review of Urban & Regional Development Studies published three regional CGE model articles. The research topic of Schwarm and Cutler, 2003 was small city and town SAMs, Giesecke and Madden, 2003 presented a large-scale dynamic multi-regional model, and Diao et al., 2003 investigated China's integration into the WTO using a CGE model.

  a CGE model because we use the wage curve theory where wages, employment and unemployment are jointly determined. Our sensitivity analyses also indicated that including unemployment does not change the other simulation results to an extent that would change the interpretation. RegFin has been implemented with the GAMS (Brooke et al. 2005) and MPSGE (Rutherford, 1998) software. The model is solved with the PATH algorithm.

  Norwegian regional policy modelNorway has established an action zone for Northern Troms and Finnmark. The law has been in effect

  general equilibrium simulation model -static, comparative-static comparisons possible -basically Walrasian, price adjustment equilibrates regional economy -wage, employment and unemployment are jointly determined according to the wage curve theory -net migration as a function of GRP and unemployment differentials Benchmark data provided by Statistics Finland -Lappi, Pohjois-Pohjanmaa, Kainuu, Keski-Pohjanmaa and Rest of Finland as statistical units -based on official regional and national account of Statistics Finland -regional Social Accounting Matrices (SAMs) are based on regional Input-Output Study 1995 -benchmark calibrated for 1995 Consumption -each region has one representative consumer household which maximizes welfare (CES utility function) -public sector is divided into two inter-related agents: national and regional governments which act as separate decision makers Production -constant returns to scale and perfect competition assumed -regional production is modelled through cost minimization of firms -labour and capital as primary inputs (CES production function) -inter-sectoral inputs are modelled via an input-output model (Leontief structure) -37 sectors per region Foreign and domestic trade -domestic production and exports modelled as joint products (CET production function) -domestic and imported goods assumed qualitatively different (Armington assumption) -domestic and foreign export and import included Taxation and transfers -taxes for factors and outputs denoted -representative consumer has income taxation -regional income and expenditure flows through public budgets denoted

  . The RegFin model is a descendent of our GemFin model, which operates at the na-

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	tional level
	F o r
	P
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Table 1 .

 1 Unemployment and net outward migration in Finland 1990-2002.

						20
		Keski-	Pohjois-			Whole of
	Year	Pohjanmaa	Pohjanmaa	Kainuu	Lappi	Finland
	Unemployment rate, %
	1990	3.0	4.3	6.0	4.9	3.2
	1991-94	13.0	14.9	17.1	17.1	12.8
	1995-98	12.7	15.9	21.7	20.6	13.5
	1999-2002	9.9	12.6	17.4	16.6	9.6
	2002	8.0	13.0	16.5	16.2	9.1
	Net outward migration, % of labour force
	1990	0.5	1.1	0.8	1.8	0.0
	1991-94	0.3	0.5	1.4	1.7	0.0
	1995-98	1.4	1.6	2.6	4.7	0.0
	1999-2002	1.4	-0.2	2.8	5.8	0.0
	2002	0.8	1.0	2.7	3.6	0.0
		o r
			P
			e
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						y

Table 2 .

 2 Design of the RegFin model.

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Table 3 .

 3 The macro economic effects of halving the social security payments of the employers in North-Finland.

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	Variable	Keski-Pohjanmaa	Pohjois-Pohjanmaa	Kainuu	Lappi	Rest of Finland	Total
	GDP change as %	6.4	7.5	7.6	7.5	-0.5	0.5
	EV welfare change, FIM million	333	1992	513	1097	-1776	2158
	EV welfare change, %	8.5	10.2	9.7	10.0	-0.7	0.7
	Net outward migration, number of people	-106	-549	-131	-271	1057
	Net outward migration, % of population	-0.3	-0.4	-0.3	-0.3	0.1
	Change in unemployment, thousands of workers	-1	-7	-2	-4	1	-15
	Change in % unemployment rate	-4.7	-5.0	-5.8	-4.9	0.0	-0.7
	Consumer prices, % change [1]	2.8	2.7	2.5	2.7	0.0
	Capital rental rate, % change	2.2	2.6	3.4	2.1	0.0
	Wages rate, % change	5.4	5.4	4.6	4.1	0.0
	Cost to the regional government, FIM million	-39	-214	-68	-151	-33	-504
	Cost to the national government, FIM million	20	127	45	103	1955	2249
	[1] Consumer prices measured with respect to cost of foreign exchange

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Table 4 .

 4 The macro economic effects of the value-added tax reform implemented in North-Finland. Corresponding author: Hannu Törmä, Professor, University of Helsinki Ruralia Institute, Kampusranta 9 C Seinäjoki, Finland,

	Variable	Keski-Pohjanmaa	Pohjois-Pohjanmaa	Kainuu	Lappi	Rest of Finland	Total
	GDP change as %	5.6	6.4	6.2	6.1	-0.6	0.3
	EV welfare change, million FIM million	291	1686	413	893	-2023	1259
	EV welfare change, %	7.4	8.7	7.9	8.1	-0.8	0.4
	Net outward migration, number of people	-63	-355	-79	-171	668
	Net outward migration, % of population	-0.2	-0.2	-0.2	-0.2	0.0
	Change in unemployment, thousands of workers	-1	-4	-1	-2	0	-8
	Change in % unemployment rate	-2.2	-2.7	-2.8	-2.5	0.0	-0.4
	Consumer prices, % change [1]	-2.3	-2.6	-2.8	-2.4	-0.1
	Capital rental rate, % change	6.5	7.1	7.4	6.1	0.0
	Wages rate, % change	2.3	2.6	2.0	1.9	0.0
	Cost to the regional government, FIM million	-29	-180	-48	-106	-60	-423
	Cost to the national government, FIM million	22	143	50	116	2203	2535

ii

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