NW Place Analysis

1
NW Place Analysis

• Overview
• Pion Economics
• NWDA Research Conference
• June 2009

2

• Space, Place Economic Activity

3
Space, Place Economic Activity

• All activity takes place in a spatial structure
• Places project takes a spatial perspective of
  economic activity in the North West
• Overarching ambition to help understand the
  role of NW Places in the functioning of the
  regional economy

Production Distribution Consumption
Places
Goods Services Information
4
Challenges

• Place Performance
• Is there a link between attributes of place and
  economic performance?
• How well-endowed are NW places in terms of such
  attributes?
• Linking Places
• How do skills, housing and the labour market
  interact to define commuting patterns across the
  North West?
• What is the nature, evidence and scale of
  agglomeration links between NW Places?
• Functionality
• How do the findings contribute to our
  understanding of functional roles within the
  region?

5
Places Project
Place
Agglomeration
Agglomeration
Commuting
Commuting
Place Population Employment Performance
Place
Place
Commuting
Commuting
Agglomeration
Agglomeration
Place
6
Technical Advisory Group

• Professor Brian Robson
• Director Centre for Urban Policy Studies,
  University of Manchester
• Professor Cecelia Wong
• Professor of Spatial Planning and Director
  Centre for Urban Policy Studies, University of
  Manchester
• Professor Harvey Armstrong
• Professor of Economic geography, University of
  Sheffield

7

• Performance Profiling

8
What Sort of Performance Measure?

• Time-series analysis
• Trend Analysis
• Data demanding
• Time-span relatively limited
• Point-to-point analysis
• Profiles highly dependent on points chosen
• Problems with turning-points
• Cross-Section analysis
• Single Point in time
• Allows comparison with all other areas in England
  
• Less demanding data requirements

9
Performance Profiling

• Issue
• Can we use evidence about the existing
  geographical distribution of GVA per employee to
• assess the importance of underlying economic
  characteristics in places to GVA per employee
  performance?
• Assess the economic potential of LADs in the
  light this evidence?
• Process
• Use statistical analysis to define relative
  importance of characteristics
• Assess the status of NW LADs in terms of terms of
  these characteristics

10
Performance Base

• ONS GVA Data at NUTS3 Level
• 93 areas across England
• Some but not all are coterminous with LAD
  boundaries
• In terms of NW GVA per employee
• Only Cheshire County lies within the top quartile
  of areas
• Halton and Warrington and Greater Manchester
  South lie in the second quartile
• Lancashire County and East Cumbria lie in the
  third quartile and
• all other areas (East Merseyside, Greater
  Manchester North, West Cumbria, Wirral, Blackburn
  and Darwen, Liverpool, Sefton and Blackpool) lie
  in the bottom quartile.

11
Performance Driver Groups

• Enterprise
• Proportion of micro firms (lt5)
• Business Density
• VAT Registrations De-registrations to Stock
• Labour Market
• Activity Rate
• Proportion of FT jobs
• Job Density
• Wages
• Location access
• Rail journey time to London
• Accessibility (distance) to 8 largest business
  centres
• Accessibility (distance) to all airports with 5m
  scheduled air passengers

• Industry Structure
• Sector employment distribution weighted by GVA
  contribution
• Location Quotient of KBIs
• Agglomeration Elasticity
• Occupation Skills
• Managerial Professional Jobs
• Level 4 jobs
• GCSE 5 A-C Performance
• Property
• Volume of factory and office floorspace per 1,000
  WA persons
• Factory Office Rateable Values per m2

12
Driver Weight Profiles(percent contribution)
13
Regional Place Profiles(LAD Scores)
Lon
SE
East
NW
WM
EM
SW
YH
NE
14
NW Place Profile(Relative to England Average)

• Strong Attributes
• Macclesfield, Trafford, Stockport
• Fylde, Warrington, Congleton Manchester,
  Chester
• Moderately Strong Attributes
• Vale Royal, Ribble Valley,
• Crewe and Nantwich, Salford

• Weak Attributes
• Wigan, Chorley, South Ribble, Bury
• Bolton, Preston, West Lancashire
• E Port and Neston, Liverpool, Halton
• Sefton, Wirral, Rochdale, Wyre
• Tameside
• Very Weak Attributes
• Lancaster, St Helens
• Oldham, Rossendale South Lakeland
• Blackburn with Darwen, Pendle, Eden
• Burnley, Barrow-in-Furness
• Hyndburn, Knowsley, Carlisle
• Copeland, Blackpool, Allerdale

15
Liverpool Score Profile
Scores
Higher Than Average
Lower Than Average
16
Manchester Score Profile
Scores
Higher Than Average
Lower Than Average
17
Copeland Score Profile
Scores
Higher Than Average
Lower Than Average
18
Blackpool Score Profile
Scores
Higher Than Average
Lower Than Average
19
Performance Cube NW Base
Location/Property
H
M
L
Macclesfield, Warrington, V Royal, Stockport,
Trafford, Congleton
Fylde, Ribble Valley
Chester
Chorley
Copeland
Manchester, Salford,
Rossendale
H
Crewe Nantwich
South Ribble
Wigan
Wyre
W Lancs, Bury, Sefton, Preston
Bolton, Liverpool, Halton
Pendle, Barrow-in-Furness
Wirral
Structure/Enterprise
M
Eden, S Lakeland
Ellesmere Port
H
Lancaster, Allerdale, Carlisle
St. Helens
M
Skills/Occupation
L
Tameside
Hyndburn, Burnley, Blackpool
Oldham, Rochdale, Knowsley, Blackburn
L
20
Performance Cube England Base
Location/Property
H
M
L
R Valley, Fylde, Chester
Macclesfield, Trafford, Stockport
Chorley
Manchester
Copeland
H
Congleton, Warrington
W Lancs
Vale Royal, Crewe, Salford
Barrow, Wyre, Pendle,Preston, Rossendale
Wigan
Structure/Enterprise
M
H
S Ribble, E Port, Lancaster, Eden, S Lakes
M
Skills/Occupation
Bury, Blackpool, Rochdale, Oldham. Hyndburn,
Bburn, Burnley, Knowsley, Sefton, Carlisle,
Allerdale, St. Helens
L
Liverpool, Wirral, Bolton, Halton, Tameside
L
21
Process

• Demonstrates the complexity of spatial processes
  across the region
• Illustrates substantial variation in LAD
  performance status across NW
• Provides a basis for assessing place roles in
  regional performance

22

• Skills, Housing Commuting

23
Background

• The spatial distribution of employment and
  working-age population implies that commuting is
  required to balance supply and demand in the
  labour market
• The focus of this workstream is twofold
• Understanding patterns of commuting flows between
  LADs
• Explaining patterns of commuting across the
  region?
• Analysis across nine occupation groups

24
Commuting

• Over 3m commutes take place on a daily basis
  within NW
• 35/40 cross LAD boundaries but very different
  spatial patterns exist across sub-regions
• Greater Manchester acts as a substantial
  attractor of commutes, dominating flows from
  Cheshire and Lancashire and acting as a secondary
  destination of importance for Merseyside
• Lancashire attracts flows from Cumbria and
  Greater Manchester while Cheshire is itself an
  attractor of flows from Greater Manchester and
  Merseyside
• In no instance is Merseyside a primary attractor

25
Own-LAD Commuting
26
Liverpool Commuter Balance
Flows From
Flows To
27
Manchester Commuter Balance
Flows From
Flows To
28
Determinants of Commuting

• Models developed to assess relative role of
• Location of job opportunities relative to
  residency across the region
• Differences in earnings
• Differences in house prices
• Differences in relative housing stock
• Public transport availability
• Applied across occupation groups

29
Commuting Model Outcomes

• Job opportunities are a primary driver of
  commuting patterns but distance is also a
  barrier to commuting
• lower order occupations are less responsive to
  job opportunities outside the resident area than
  higher order occupations
• Differences in hourly earnings are significant
  commutes generally go from from areas with lower
  earnings to areas with higher earnings
• significance is highest for managers at the upper
  end of the occupation range and skilled trades,
  process and elementary workers at the lower end

30
Commuting Model Outcomes

• House prices differences are statistically
  insignificant in the overall model, but
• are significant and negative for managers and
  professionals (commuting from high to low price
  areas),
• significantly positive for personal sales,
  process and elementary occupations (commuting
  from low to high price areas)
• Public transport availability is positive and
  significant
• positive and significant in all cases but one
  managers
• more notably pronounced for skilled trades,
  process and elementary workers than for
  professional and associate professionals

31
Process

• Confirms that commuting patterns are a complex
  and varied mix of inflows outflows
• Suggests that the distribution of Jobs, housing
  and public transport provision are primary
  determinants of commuting profiles
• Indicates notable differences in responses to
  underlying housing and characteristics across
  occupation groups
• Places display very different roles in balancing
  the distributions of jobs and workers across the
  region

32

• Agglomeration

33
The Agglomeration Phenomena

• Economic activity is rarely if ever uniform
  across space
• Businesses agglomerate
• Resource Endowment
• Transport Links
• Processing Assembly
• Distance to Market
• NEG centrifugal centripetal forces shape
  pattern location of economic activity
• Populations often agglomerate around business but
  extent is variable is influenced by a range of
  factors
• It is that claimed that such agglomeration
  produces productivity benefits

34
Sourcing Agglomeration Economies

• Localisation Economies
• Spatial concentration of plants in same industry
  (Clusters)
• Plant Specialisation
• More proximate supplier linkage
• RD, information technology transfer
  spillovers
• Specialist labour pools
• Urbanisation Economies
• Spatial concentration of plants not necess in
  same industry
• Urban transport systems
• Efficient labour markets
• Business commercial services
• Public infrastructure

35
How Do We Calculate Agglomeration?
What is the benefit of the hinterland area to the
productivity of each place?
Hinterland
Place
Hinterland
Use intelligence from existing DfT Research..
36
Agglomeration Balance
Agglomeration Benefits Generated
Agglomeration Benefits Received
37
Liverpool Agglomeration Balance
Agglomeration Benefits to
Agglomeration Benefits From
38
Overview

• Agglomeration is an acknowledged and verified
  benefit
• Our estimates suggest that
• Agglomeration benefits in the NW are equivalent
  to some 8.5bn
• 30 are generated by the two primary urban nodes
• Differential pattern across sub-regions
• 31 Gtr Mcr
• 26 Lancashire
• 24 Merseyside
• 17 Cheshire
• 2 Cumbria

39

• Integration

40
Project Intelligence..
Place Attributes Performance
Commuting
Agglomeration
41
Bringing Together

• Typology of spatial structures required that can
• Accommodate all three forms of output
• Reflect the spatial diversity that is evident
• Presents a simple but meaningful summary of
  complex analysis
• Build on the Northern Way City Relationships
  Typology
• SURF, Centre for Cities, The Work Foundation

42
City Relationships Typology
43
Functionality Assessment(Liverpool Hinterland)
44
Functionality Assessment(Manchester Hinterland)
45
Functionality Assessment(Carlisle Hinterland)
46
Going Forward..

• Project moving towards conclusion
• A series of technical reports are being drafted
• These are to be accompanied by an overview report