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UCL DEPARTMENT OF GEOGRAPHY Statistics for understanding Town Centre Retail Change Miles Davis CASA Seminar 25 th February 2009.

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Presentation on theme: "UCL DEPARTMENT OF GEOGRAPHY Statistics for understanding Town Centre Retail Change Miles Davis CASA Seminar 25 th February 2009."— Presentation transcript:

1 UCL DEPARTMENT OF GEOGRAPHY Statistics for understanding Town Centre Retail Change Miles Davis CASA Seminar 25 th February 2009

2 Statistics for understanding Town Centre Retail Change CASA/CLG Town Centres Statistics Background to the Statistics Developing the Statistics The Statistics in practice – how useful? Future

3 Retail and retail change Retail industry: ~ 10% of businesses, GDP, employees; direct and frequent contact Traditionally in town centres – most accessible place 1960s shopping centre boom; civic pride But already first signs of movement out of town; major structural changes Schiller’s (1986) three waves of decentralisation: Supermarkets – convenience goods Bulky durable goods – DIY, carpets, electrical Comparison goods And more?

4 Retail statistics and retail planning 1971 Census of Distribution (part of series since 1950): turnover, employment, floorspace, count; analysed by trade and kind of business; for each local authority and central shopping areas (272) Growth of modelling (though unpopular at public inquiries) Local government changes and high inflation rendered 1971 Census out of data before publication in 1976 Replacement by VAT-based Retail Inquiry – but no local data Planning policy struggled to keep up with rapid change, increasingly determined at inquiry or by ministers

5 Retail planning without statistics 1980s: “like mushrooms, retailers are being consigned to the dark and heaped with something which smells rather nasty” Jack Butler, Littlewoods -1982 Rayner doctrine Alternative sources of local-level retail data: local studies; commercial, esp. Goad (now Experian) - uses footprints from OS maps; in house research departments; Lack of completeness, availability, comparability, turnover

6 Town Centres Statistics – origin & concept Early 90’s recession, concern over effects of laissez faire policy on town centre vitality and viability; healthchecks Refusal of requests for new census Instead use data already being collected by government Aims: Define centre boundaries Turnover, floorspace, employment statistics CASA: modelled surface approach Took advantage of new datasets recently available within government; also desktop GIS technology

7 Town Centres Statistics – data & methods Data sources and their limitations: Inter Departmental Business Register (IDBR) and Annual Business Inquiry (ABI): register based on VAT and PAYE returns used for sample inquiries; numbers of employees and turnover data by industry imputation, synthetic estimation, slow to finalise Non-Domestic Building Stock Database based on Valuation Office Agency (VOA) property rating information categorisation not very helpful Postcode level - issues Index of Town Centre Activity – create surface: not just retail, but other town centre uses too 7 elements: diversity, financial turnover, pedestrian gateways & access, activities & facilities, intensity of use, visitor attractions, resident population Source: www.geofutures.com

8 Town Centres Statistics - output Centres emerge from the data: threshold of activity, minimum size Boundaries will change over time, centres appear & disappear Areas of Town Centre Activity (ATCAs) and Retail Cores

9 Town Centres Statistics - output Centres emerge from the data: threshold of activity, minimum size Boundaries will change over time, centres appear & disappear Areas of Town Centre Activity (ATCAs) and Retail Cores

10 Town Centres Statistics in practice 1998 Feasibility study: Wolverhampton, then 9 more towns – diverse selection included turnover found to be robust, accurate 2002 Greater London pilot simplified model with 3 elements: diversity, economy, property no turnover – felt to be unreliable 2004 England & Wales (for 2000 and 2002) approx 1000 centres, 45 retail cores, all districts; 2008 England & Wales (for 1999 to 2004 inclusive) Delays due to government reorganisations; re-issuing of source data Not well publicised or easy to access via CLG Lots more retail cores (approx 600, along with 1250 centres), but lots more disclosive data (don’t know what disclosure limits are), no district level outputs

11 Using the Town Centre Statistics to monitor policy effectiveness PPG6 and PPS6 – Town Centres First/Sequential Approach from 1996 onwards Town centre floorspace statistics Also district level stats from CLG – same underlying source in VOA data Can use together to look at in and out of town split (though TCS and plan definitions of town centres not the same)

12 Crown Copyright/database right 2009 An Ordnance Survey/EDINA supplied service

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17 Examining change at centre level Look at changes in floorspace and employment for individual centres - here using retail cores Relatively stable period – policy had started to bite, last of regional shopping centres had already opened Perils of categorisation and hierarchies

18 n=452

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20 (8-fold classification of centres courtesy Andrew Smith, Aberdeen Property Investors; local centres not shown)

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24 n=191

25 What’s good, what’s bad Boundaries well defined, robust – know WHERE Completeness of coverage Self-comparability Comparability with other datasets

26 What’s good, what’s bad Disclosure – a nonsense when synthetic estimates for employment; floorspace available from VOA Lack of breakdown by trade (a function of the source data) so can’t see e.g. comparison goods in superstores, or by business type No shop count (though in VOA data) Lack of Turnover data What about non-central areas? They’re in the model

27 Time is a factor here… Real value is in continuous sequence But releases sporadic, may now have stopped…just when things are getting interesting: 2008 openings (Bristol, Liverpool, Leicester, Westfield plus many smaller) and more to come; towns in competition over retail rank Long gestation periods – 10 years or more for town centre scheme Woolworths etc Policy changes – competition test; impact test, re-emphasis on data Also floorspace stats – change in method

28 Future prospects Build our own Town Centres Stats? Can get VOA data directly What about ABI employment data? Could then solve slow-release problem and use surface to look beyond centres Turnover still a problem

29 Statistics for understanding Town Centre Retail Change Thanks to Mike Batty, Mark Thurstain-Goodwin, David Thorpe, Andrew Smith Miles Davis CASA Seminar - 25 th February 2009 m.davis@ucl.ac.uk


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