1 An Economic Geography of Real Estate Investment in England and Wales Peter Byrne Professor of Real Estate Dynamics School of Real Estate & Planning Henley Business School, University of Reading, Whiteknights, READING, RG6 6UD, UK Phone: +44 (0) , Stephen L. Lee Cass Business School, City University London, 106 Bunhill Row, London, EC1Y 8TZ, England Phone: ,
2 An Economic Geography of Real Estate Investment in England and Wales 1. Introduction There has been something of a debate about the thinking that prescribes the decisions to develop or invest in real estate in particular locations in the UK, and how this has continued to dictate the location of such investment. It has focused on the relationship between cultural aspects and economic fundamentals. Discussing property development, and by implication investment, Guy and Henneberry (2000) argued that social structures and processes are as important as economic principles in explaining property development and investment. Ball (2002), calling this an integration of economic and social processes, argued that this was nothing new; it arose from a very long-standing institutional bias in investment allocation through prejudice, meaning in turn that some places are preferred to others for investment. Henneberry and Roberts (2008) revisited this debate by examining the causes of persistent interregional variations in UK Office investment, returning to an integrated argument which comes from the idea that modern investment is predicated by the desire of fund managers to perform satisfactorily against a benchmark, self-restricting their investments and accordingly creating and perpetuating a barrier to more spatially diversified investment. Until recently little was known about the actual stock selection practices of investors, (see Gallimore et al., 2006; Jackson and Orr, 2008 and MacCowan and Orr, 2008 for reviews and surveys of current practice). Evidence suggests that when building and managing their portfolios, investors concentrate their real estate holdings in preferred regions, but that this is not particularly motivated by wider economic considerations in spite of the evidence regarding the advantages of using such approaches (see Hartzell et al., 1986; Hartzell et al., 1987; Malizia and Simmons, 1991; Mueller and Ziering, 1992; Mueller, 1993; Ziering and Hess, 1995; Hoesli et al., 1996 and Lee and Byrne, 1998 amongst others). Previous research has shown that institutional real estate is concentrated in a small number of urban areas and has tried to establish reasons for this. In the US, Shilton and Stanley (1995, 1996) demonstrated that most private real estate investment is found in the larger and richer counties. Similar conclusions were drawn by Smith et al. (2004) and Hess and Liang (2005a, 2005b) who grouped US metropolitan statistical areas into eight clusters based on economic characteristics, geographic proximity and absolute size. They found that the top seven clusters contained just 35 MSAs and accounted for about 94% of private investment and about 80% of estimated public investment. More than 60% of private, and over half of public real estate investments are in the 10 largest US metro areas by population, although less than one-third of the population lives in these areas. The top 30 metro areas have about half of the US population, but account for more than 90% of private investments and almost 75% of public holdings. Private investors hold properties in only about 80 of the 361 MSAs. They concluded that institutional investors prefer to concentrate their investments in the largest metro areas. Byrne et al. (2002) looked at the location of US business centre executive suites. A quarter of 1,692 business centres in the US were in just five cities; the top 12 MSAs accounted for nearly half the centres, and over half of all MSAs had no recorded executive suites. There was a non-linear relationship between the number of suites and size as measured by employment or city size, with suites concentrated in the more economically and demographically expanding cities. This matches much of the prior
3 research on the clustering of economic activity and Office dynamics (see Byrne and Lee, 2006 for a more complete review). In the UK, the actual spatial concentration of institutional real estate investment has not been much researched. While it is necessary to be aware of the major differences in the size and structure of the two markets, such studies as there are show similar kinds of results to the US. Byrne and Lee (2006) found institutional Office investment concentrated in a very few local authorities (LAs), having distinctive economic features such as high business services employment and with a concentration on the largest cities, which compares well with the US (see Shilton and Stanley, 1995; Shilton et al., 1996; Liang and McIntosh, 2000 and Frost et al., 2005). In contrast, Byrne and Lee (2009) find that Retail investment correlates closely with the urban hierarchy of England and Wales, focused on urban areas with higher populations and large population densities which have larger numbers of investable Retail units. Industrial concentration has been shown to be between that of retail and offices, focussed on LAs with high levels of manual employment in areas with smaller industrial units. There has been structural change in the sector, with greater emphasis on investment in the distributional (logistic) element, for which location is a principal consideration (Byrne and Lee, 2010). What remains unclear is whether these concentrations are related to current economic/regional structures because, until recently, the only economic classifications (of towns) in the UK have been based on data from the 1981 national census (see Lee and Byrne, 1998 and Jackson, 2001, 2002 for reviews). In this paper, rather than looking at institutional real estate allocation(s) in each LA, (Byrne and Lee, 2006, 2009 and 2010), the spread of holdings in 1998 and more particularly 2003 is examined by reference to more synthetic socio-economic structures derived from a multivariate classification of LAs (essentially towns) using data from the 2001 census (ONS, 2003). The paper is organised as follows. Section 2 outlines the classification of LAs in England and Wales into socio-economic clusters. Section 3 places the clusters in a real estate context and section 4 discusses the real estate characteristics of the clusters. Sections 5 and 6 examine the concentration of holdings in these clusters from different perspectives. Section 7 concludes the study. 2. The Socio-Economic Clusters of England and Wales Using census Key Statistics, the ONS selected 42 variables, in six dimensions: demography, household composition, housing, socio-economic, employment and industry sector (ONS, 2003). Using a combination of Ward s hierarchical and k-means cluster analysis, each LA was allocated to a group with other LAs to which it was most similar in terms of these 42 variables. This approach grouped the LAs into a number of clusters based on similar characteristics. The hope of such clustering methods is that natural groups will emerge - labelled to represent meaningful categorisations. Here, the largest clustering was the Supergroup (seven clusters) which was then split into groups (13) and then into sub-groups (24). The 13 cluster classification is used here. The analysis is confined to LAs in England and Wales because of data considerations relating to the availability of comparable data for the rest of the UK. The Northern Ireland Countryside group is excluded. With 1.1% of the UK population, it had only 12 (8) Retail properties in 1998 (2003); one industrial property in 1998, none in 2003 and no Offices in either year. The 12 remaining clusters are shown in Table 1.
4 Table 1: The Socio-Economic Clusters of England and Wales ONS Cluster Name Locations Pop % No of LAs Exemplar Regional Centres Built-up areas throughout E&W 9% 20 Plymouth Centres with Industry North West and West Midlands 11% 21 Bolton Thriving London Periphery London Periphery + Oxford and Cambridge 3% 9 Reading London Suburbs Outer London + Slough and Luton 5% 12 Redbridge London Centre Inner London 3% 8 Islington London Cosmopolitan Inner London, Except Brent 3% 7 Haringey Prospering Smaller Towns Throughout the E&W 24% 113 Stroud New and Growing Towns Southern England 6% 24 Dartford Prospering Southern Home Counties England 9% 44 Horsham Coastal and Countryside Coastal E&W + some inland areas 9% 52 Christchurch Industrial Hinterlands South Wales and Northern England 9% 31 Sunderland Manufacturing Towns Southern Yorkshire + isolated Ellesmere locations 9% 34 Port Source: ONS (2003) Tables 2 and 3 show the cluster employment and population profiles. Employment data are the ONS Nomis Labour Market Profile Annual Business Inquiry Employee Analysis numbers of employee (available) jobs in each employment category. These measure net employment for each kind of activity in each LA. Population figures are from the ONS Neighbourhood Statistics: Topics database. Employment and population characteristics in each cluster were calculated relative to the national average, each cell showing whether that cluster has above or below average employment and population. In Table 2 the clusters with greatest concentration of manufacturing (MANU) employment are, unsurprisingly, Centres with Industry, Industrial Hinterland and Manufacturing Towns. Construction (CONS) employment is relatively evenly spread, except for the London Centre cluster. Tourism (TOUR) is greatest in the Coastal and Countryside cluster and is above average in London Centre. As is also expected Distribution (DIST) employment is evenly spread. Transport and Communications (TRANS) employment is, in contrast, concentrated in four clusters:- the Thriving London Periphery, London Suburbs, London Cosmopolitan and New and Growing Towns. Finance, IT, Other Business Activities (FIRE) employment is heavily concentrated in the London clusters, especially in London Centre, where it is more than twice the national average; in New and Growing Towns and Prospering Southern England. In contrast, Public Administration, Education and Health (PAD) employment is evenly spread, while the Other (OTHER) category shows an above average level in the London Centre and London Cosmopolitan clusters. In Table 3 the Regional Centres cluster has an even spread across all population groups apart from full time students (FTS) where it has about 50% more than the national average. Centres with Industry has, in comparison, an above average number of unemployed (NOTW and LTUN) and individuals with routine and semi-routine jobs (ROUT and SROU). The Thriving London Periphery cluster has above average numbers in managerial and high professional jobs in large firms (LEHM and HPF) and below average numbers in routine jobs (ROUT) or unemployed (NOTW and LTUN); similar to the London Suburbs. The London Centre cluster has a population with above average jobs in higher managerial work with large employers (LEHM) and more than twice the national average of highly profession (HPF); individuals who have not worked (NOTW), or are long-term unemployed (LTUN). The London Cosmopolitan cluster has
5 below average managerial workers (LEHM) and average numbers who have not worked (NOTW). Prospering Smaller Towns show an even spread of workers, with a below average number of unemployed (NOTW and LTUN). New and Growing Towns generally have workforces in line with the national average but have below average numbers of unemployed and full time students (NOTW, LTUN and FTS). Prospering Southern England has above average employment in all managerial and professional categories with a below average number of long-term unemployed (LTUN). The Coastal and Countryside group has below average in managerial and professional jobs in large and intermediate employers (LEHM, INTER and HPF) but more with their own business s (SEOB). Industrial Hinterlands is typified low-skilled jobs (LST, SROU, ROUT) and a high percentage of long-term unemployed (LTUN), with the Manufacturing towns cluster showing a similar profile but additionally having an above average percentage of people who have never worked (NOTW).
6 Table 2: Cluster Employment Profile LA Employment MANU CONS TOUR DIST TRANS FIRE PAD Other Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Note: MANU: % in Manufacturing, CONS: % in Construction, Dist: % in Distribution, TRANS: % in Transport & Communications, FI: % in Finance, IT, Other Business Activities, PAD: % in Public Admin, Education & Health, Other: % in Other Table 3: Cluster Population Profile LA Population Characteristics LEHM HPF LEMP INTER SEOB LST SROU ROUT NOTW LTUN FTS NCL Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Note: LEHM: % in LA population in Large Employer High Managerial work, HPF: % in High Professional work, LEMP: % in Low Managerial/Professional work, INTER: % in Large Intermediate Employers, SEOB: % in Small Employer or Own Business, LST: % Low Supervisory/Technical work, SROU: % Semi-Routine work, ROUT: % Routine employment, NOTW: % of LA population who have Not Worked, LTUN: % Long-term Unemployed, FTS: % Students population, NCL: % in LA population in Not Classified
7 3. The Real Estate Characteristics of the Clusters Floorspace and rateable value statistics for commercial property at LA level (ODPM, 2005) 1 are used to place these clusters in an overall real estate context. Rateable values are the basis for commercial real estate taxation in England and Wales - the Business Rate. The tax is based on a rateable value (RV), derived from a hypothetical rental valuation of the taxable unit (called a Hereditament ). These data are, with some qualifications, a strong proxy for actual rents. From the rental value a capital value may be estimated. Importantly, they are defined spatially, with complete coverage for England and Wales. The data are used here to set a scale of institutional activity in particular LAs, since they present good overall measures of commercial real estate in each LA. In 2003 there were 1,295,443 hereditaments in England and Wales made up of 266,022 Offices; 562,712 Retail units and 466,709 factories and warehouses (industrial). The total floor space in England and Wales in 2003 was 568m square metres made up of 81m square metres in Offices; 110m square metres of Retail; and 377m square metres of Industrial. Total RV in 2003 was 303bn; 93bn from Offices; 106bn from Retail and 104bn in Industrial. Table 4 shows that Regional Centres contains about 10% by number, value and floorspace. By sector, it has about 11% of Offices and Retail, but only 8% of Industrial. By value, the cluster has about 8% of the Offices and Industrial properties but nearly 12% of Retail. Larger Retail units dominate Regional Centres. The Centres with Industries cluster has about 12% and 14% of the count and floorspace but only 10% by value, with a large number of small value properties. This is especially noticeable in the Office sector, with 11% by number, but less than 7% by value, and Retail shows a similar picture. In contrast, Industrials account for about 14% of the number and value and almost 16% by floorspace. The Thriving London Periphery has less than 3% of the commercial properties in England and Wales and about 2.5% of the floorspace but 4% by value. It has a small number of larger properties, mostly in Offices and Industrial. Sectors are spread evenly across the London Suburbs, with about 3% of the number, and about 4% by value. With about 3% of the floorspace, Offices show a greater proportion of value at about 5%, with Industrial showing about 2%. This cluster is exemplified by medium sized Offices and smaller Industrial units. London Centre has about 7% by number, but almost 17% of the value in less than 5% of the floorspace. It has a number of very large value
8 properties, especially in Office and Retail. Offices here account for about 40% of the value of all Offices, but only 15% of the number. Retail in this cluster accounts for only 5% by number and floorspace, but 11% by value. In contrast, the Industrial properties represent less than 3% by number, only about 2% by value and only 1% of the floorspace. The London Cosmopolitan cluster contains about 3% of the numbers in England and Wales spread evenly across all property types. Prospering Small Towns contains more than 20% of all commercial property, particularly in the Retail and Industrial sectors. In contrast, although Offices represent about 20% of the number of units, they only account for about 10% by value, i.e. Offices in this cluster are large but lower value units. New and Growing Towns have between 5-7% by number of units, equally spread across the three sectors. Prospering Southern England accounts for about 9% of units, but is overrepresented by Office and Industrial properties and underrepresented by Retail units at about 11% and 7% respectively. Coastal and Countryside has 10% by number, but only about 5% by value. This cluster has a large number of small value properties, especially in the Office sector. Finally, Industrial Hinterlands and Manufacturing towns are almost identical in terms of numbers and value, with about 8% of the numbers, but only 5% of the value. As with Coastal and Countryside they have a large number of small value properties, especially in the Office sector.
9 Table 4: Clusters: Hereditament Profile: 2003 Total Office Retail Industrial Cluster Name HC% HRV% HFS% HC% HRV% HFS% HC% HRV% HFS% HC% HRV% HFS% Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Note: HC is number of hereditaments, HRV is hereditament Rateable Value, HFS is hereditament floor-space.
10 4. Institutional Real Estate Investment Specific institutional real estate investment data come from the Investment Property Databank (IPD) analysis UK Local Markets 2004 (IPD, 2004, with modifications). This provides a detailed view of the performance of institutional real estate investment, by sector. Results are published annually for all LAs with four or more properties in institutional ownership. For the purposes of this study, IPD made data available from 1998 and 2003 (but with much less detail), for all LAs where the number of properties was non-zero, but less than the four required normally for disclosure. The data must be qualified somewhat, because, at the end of 2003, about onethird of the UK real estate investment market was outside the IPD database. Even so, the IPD is the benchmark for assessing UK commercial real estate performance and the results presented here show, for the first time, the spatial extent of the entire IPD universe at these two dates. The IPD universe in England and Wales in 2003 consisted of 9,611 properties; 2,904 Office; 4,054 Retail and 2,653 Industrial. Total floorspace amounted to 56m square metres; 12m square metres of Offices; 18m square metres of Retail and 26m square metres of Industrial. The estimated total capital value was approximately 95bn; 30bn in Offices; 49bn Retail and 16bn Industrial. Thus, although institutional ownership was less than 1% of the total number of taxable units, the ownership was worth about 32% of the total estimated capital value and 9% of the floorspace. The comparator year is 1998, chosen because this is the year to which the rateable value data relate directly. There are considerable differences between the holdings in the two years. In 1998 there were 12,867 properties with an overall floorspace of about 43m square metres and an estimated capital value of approximately 74bn. Hence, the number of properties in the database fell by 25% between 1998 and 2003 while the overall amount of space increased by 29%, and the capital value rose by 30%. There are substantial differences across the sectors. The number of Offices fell by 22% between 1998 and 2003 while its overall space increased by 18%, with capital value rising by 12%. Retail showed the largest fall in numbers, declining by 40% between 1998 and 2003, while its capital value increased by 34% and floorspace increased by 14%. In contrast, Industrials showed increases, with the number of properties increasing by 11%, floorspace by 49% and capital value rising 61%. This was a period when substantial adjustments were taking place in the shape (and scale) of institutional real estate investment. Tables 5 and 6 show the percentage investment allocations across the ONS clusters and indicate that most of the changes between 1998 and 2003 were concentrated in a few clusters, but with different patterns across the sectors. For instance, the percentage in the Regional Centres cluster
11 hardly changes overall, but there is a marked switch from Offices into Retail. Centres with Industry showed an increase in all sectors, but especially Industrials. The Thriving London Periphery group saw only a minor increase in investment and this was mainly in Offices. The London Suburbs, meanwhile, saw little change in any property type. In contrast, London Centre showed the biggest decline over this period, especially in the Office sector. The London Cosmopolitan cluster showed little change. Perhaps unexpectedly, Prospering Smaller Towns saw a decline across all sectors - especially Retail. This was apparently a concentration effect, with the average retained floorspace rising by nearly 10%. New and Growing Towns showed a different effect, substantial increases Retail capital value and floorspace. Prospering Southern England meanwhile showed a decline, especially in the Industrial sector. Investors reduced their allocation to the Coastal and Countryside cluster across all sectors. Industrial Hinterlands showed little change overall; a decline in Office and Retail investment compensated by an increase in Industrials. Manufacturing Towns displayed little variation over the period. Between 1998 and 2003 investors changed their allocations between the sectors, generally reducing their allocation to Offices and Retail while increasing Industrials. Nonetheless, allocation across England and Wales hardly changed. Investors seem to have rationalised their commercial real estate investments within the economic clusters, i.e. increasingly concentrating their holdings within each cluster over this period.
12 Table 5: IPD Profile: 1998 Total Office Retail Industrial Cluster Name Num CV FS Num CV FS Num CV FS Num CV FS Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Note: Num. is the number of properties; CV is the estimated capital value and FS is Floor space Table 6: IPD Profile: 2003 Total Office Retail Industrial Cluster Name Num CV FS Num CV FS Num CV FS Num CV FS Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Note: Num. is the number of properties; CV is the estimated capital value and FS is Floor space
13 5. Institutional Real Estate Concentration in 1998 and 2003 To determine whether institutional investors concentrate their real estate investments in certain economic regions (as is certainly the case in the US) the next section considers the way that sector investment spreads across the local authorities - when they are clustered. Tables 7 and 8 show the concentrations across the 12 clusters in each year. In Table 7, the IPD data show that 167 LAs (45%) had no institutional Office investment in 1998; 259 (69%) had three or less Office holdings and 348 (93%) had less than 30 Offices. Two LAs (Westminster and the City of London) had more than 400 Office holdings in Industrial holdings in 1998 were equally concentrated, with 117 (31%) LAs with no holdings, 205 (55%) with three or less and 361 (96%) with 30 or less and only two local authorities (Leeds and Milton Keynes UA) having more than 50 properties. In contrast, Retail was much more evenly spread with only 30 (8%) LAs having no Retail investment; 62 (17%) had three or less and 299 (80%) less than 30 properties. 75 (30%) local authorities had more than 30 properties and one, Westminster, (which includes Oxford Street) had more than 100 properties. Office investors, in 1998, avoided LAs in the Costal and Countryside, Industrial Hinterland, Manufacturing and especially Prospering Smaller Towns clusters. Office holdings in the UK show a level of concentration comparable with that in the US (Shilton and Stanley, 1995; Shilton et al., 1996; and Liang and MacIntosh, 2000). In contrast, Industrial investment was focused in the Prospering UK Supergroup, especially the Prospering Smaller Towns and New and Growing Towns. Retail investment meanwhile was spread across all clusters.
14 Table 7: Institutional Real Estate Concentration in 1998 Office Zero 1 to 3 4 to 9 10 to to to Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total Retail Zero 1 to 3 4 to 9 10 to to to Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total Industrial Zero 1 to 3 4 to 9 10 to to to Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total Table 8 shows Office investment by 2003 had become even more concentrated in a few preferred LAs. 208 (55%) of the LAs now had no Office investment; a result seen across most clusters, except for London Centre, Cosmopolitan and the Thriving London Periphery. Table 8 also shows the number of LAs with three or less Office holdings reduced, while those with 4-9 properties increased. LAs with no Retail investment more than doubled to 66 (18%), while the number of LAs with less than four properties increased to 173 (46%). The number of LAs with more than 50 properties halved from 25 in 1998 to 12. In contrast, the change in Industrial was much less over the period. The number of LAs with no properties fell to 93 (25%), while those with more than 10 increased to 94 (25%).
15 Table 8: Institutional Real Estate Concentration in 2003 Office Zero 1 to 3 4 to 9 10 to to to Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total Retail Zero 1 to 3 4 to 9 10 to to to Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total Industrial Zero 1 to 3 4 to 9 10 to to to Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total The changes in allocations between 1998 and 2003 are shown more clearly in Table 9.
16 Office Table 9: Changes in Allocation 1998 to 2003 No Change None In Both Increase New Increase Decrease Dec To Zero Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total Office Retail No Change None In Both Increase New Increase Decrease Dec To Zero Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total Retail Industrial No Change None In Both Increase New Increase Decrease Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Total Industrial Dec To Zero Table 9 shows that the large majority of LAs saw a decline in Office investment; 146 (39%), or no change; 197 (52%), with 62 (17%) falling to zero, the biggest reduction being in Prospering Small Towns and Prospering Southern England. Nonetheless, 32 (9%) LAs did see an increase in investment, with 8 (2%) showing investment for the first time. The decrease was even more dramatic in Retail; 323 (86%) showed a decline, with reductions across all clusters. 53 (14%) LAs fell to zero, with
17 the biggest reduction in Prospering Small Towns. Only 8 (2%) saw an increase, with 3 (1%) showing investment for the first time. In contrast, Industrial saw a substantial rise over (38%) LAs showed an increase, 38 (10%) were represented for the first time, the biggest increases being in Prospering Small Towns and Prospering Southern England. There were reductions in 106 (28%) LAs, and 22 (6%) dropped to zero 3. In this period institutions reduced their Office investment in the Small Prospering Towns, while at the same time increasing their allocation to Industrial properties in the same cluster. In contrast, Retails were being reduced in almost all clusters. Effectively, investments were rationalised, eliminating many areas where previously there was minimal investment and focussing on certain other areas through increased investment. 6. Concentration in the Clusters: 2003 Tables 7 to 9 show the focus on a limited number of clustered LAs and that this became slightly more concentrated over time. They do not show the extent to which this is an over- or under-representation of investment in a particular cluster relative to some measure of spatial spread across England and Wales. To do this Location Quotients (LQs) were calculated using the following (generalised) formula (see, Isard, et al., 1960): Spatial Measure of Interest LQ Alternativ e Measure of Spatial Spread An LQ of 1.0 implies that the value of the cluster was proportional to the alternative measure of spatial dispersion; an LQ greater than 1.0 suggests over-representation and an LQ less than 1.0 suggests relative underrepresentation. A number of different LQs were calculated for each of the 375 LAs for which data were available, using number of properties and market value in the numerator and several different denominators. The first two approaches use data in the numerator and denominator that are as similar as possible to each other in each case. For example, when the number of property holdings from IPD is used in the numerator, the number of hereditaments is the denominator. The second LQ uses the IPD market values of the properties in the numerator and rateable value (as a proxy for capital value) in the denominator. Lastly, to make the LQ calculations comparable with those in previous studies, the LQs are recalculated using employment as the denominator. These three sets of LQ estimates provide a more detailed view of the results in Tables 2 to 4. In Table 10 the results of the analysis for 2003 show firstly, that the different property sectors are focused on different economic clusters and
18 secondly that the different LQ calculations show similar results, especially the Capital Value and Employment LQs. To make the discussion comparable across all property types we concentrate on Capital Value Location Quotients (CVLQs). Table 10: LQs: 2003 Office Retail Industrial Cluster Name NLQ CVLQ ELQ NLQ CVLQ ELQ NLQ CVLQ ELQ Regional Centres Centres with Industry Thriving London Periphery London Suburbs London Centre London Cosmopolitan Prospering Smaller Towns New and Growing Towns Prospering Southern England Coastal and Countryside Industrial Hinterlands Manufacturing Towns Note: NLQ is the LQ of the number of properties in each property-type to the corresponding number of hereditaments, CVLQ is the LQ of the capital value of properties to rateable value and ELQ is the LQ of the capital value of properties to total employment. Office investment is concentrated in a handful of clusters, especially London Centre, closely followed by the Thriving London Periphery, with CVLQs of 4.96 and 2.89 respectively. These two represent the first level of Office investment nationally. The high representation of Office allocation to the London Centre is easily explained by the large number of high value properties in this cluster and the above average number of employees in financial services. The Thriving London Periphery contained rather few Offices in 2003 but they were above average in size. In addition, it has a large number of workers in financial services, transport and communications industries. There is a large gap to the next cluster, Prospering Southern England (CVLQ 1.26) which has above average employment in financial services. Investors have only average interest in Offices in the London Suburbs (CVLQ 0.98) but relatively minor interest in New and Growing Towns, the London Cosmopolitan, Centres with Industry and Regional Centres (CVLQs 0.68, 0.47, 0.26 and 0.31). These are clusters which also have above average employment in financial services but have relatively low value Offices. There is little interest in Office investment in Prospering Small Towns; Coastal and Countryside; Industrial Hinterlands and Manufacturing Towns (CVLQs of 0.14, 0.01, 0.05 and 0.01). The latter three have well below average financial service jobs and a large number of small value Offices. All this suggests that institutions prefer areas with a large number of high value Offices supported by the financial services industry. The Retail sector is different. Retail investment is focused in four clusters; Thriving London Periphery (CVLQ 2.67); New and Growing Towns (CVLQ 2.07); London Suburbs (CVLQ 1.59) and Regional Centres (CVLQ 1.42).
19 These have below average unemployment and above average managerial and professional jobs in the financial services, transport and communication industries, i.e. areas with above average spending power. There is a normal level of interest in London Centre (CVLQ 0.93) because of the large number of mixed Retailing in this cluster. After this however, Retail investment is below the Rateable Value spread in all other clusters, but does not fall below Thus, Retail investment is much less concentrated than Office investment; nonetheless, institutions still show preferences for certain localities. The Industrial sector is different again, with investment concentrated in three clusters; London Suburbs (CVLQ 2.62), New and Growing Towns (CVLQ 2.52), and the Thriving London Periphery (CVLQ 2.17). These are clusters with above average sized light Industrial space, and an above average number of managerial and professional jobs in financial services, transport and communications. The next cluster is Prospering Southern Towns (CVLQ 1.40) which displays similar employment and population characteristics but has a large number of smaller Industrial units. The next, London Cosmopolitan, has investment in line with the rateable value and Employment spatial spread (CVLQ 1.16). It has above average jobs in transport and communications, financial services, and public sector administration but has less than 3% of the all Industrial units. There is below average involvement in Centres with Industry (CVLQ 0.83) and Manufacturing Towns (CVLQ 0.67), clusters with above average manufacturing employment. The Regional Centre cluster is next (CVLQ 0.65) with no distinguishing employment characteristic, but 8% of all Industrial units. Lastly, investors avoid the London Centre (CVLQ 0.50), Industrial Hinterland (CVLQ 0.30) and Coastal and Countryside (CVLQ 0.06) clusters, with above average unemployment and a preponderance of rather small Industrial units. 7. Conclusion This paper has considered the extent of real estate investment concentration in institutional portfolios in England and Wales in 1998 and It examined the extent to which this concentration is focused on the multi-variate socio-economic clusters developed by the UK ONS. Using several datasets investment is found to be concentrated in a few preferred clusters but that the significant clusters vary by property sector. Office investment is concentrated in clusters with a large number of large, high values Offices in the financial services industry, i.e. the London Centre and Thriving London Periphery clusters. In contrast, Retail investment is more evenly spread across England and Wales but has above average allocations in clusters with below average unemployment and with individuals in managerial and professional jobs, working in the financial services and transport and communication industries, i.e. clusters with
20 above average spending power. Investors concentrated their Industrial holdings in clusters with above average sized light Industrial space and avoided groups with above average unemployment and a preponderance of smaller Industrial units. These observations tend to support the integrating view of real estate investment decision-making in this period; it is both economically based and culturally biased. Even so, if the pattern of institutional investment presented were to be maintained, then the role that institutional investors have in structuring the built environment within regions varies enormously from area to area. The evidence clearly shows that generally investment was taking place in areas that had appropriate infrastructure, that is, a socio-economic composition with characteristics capable of supporting and sustaining significant development in the sector. More work therefore is clearly necessary to understand the relationships between local economies and investment patterns and the impacts that any local market s socio-economic characteristics have on institutional property investment.
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