Regional Economies and Commercial Real Estate in the UK: exploring the linkages

ERES Conference, Milan, June 2010

Tony Key, Professor of Real Estate Economics, Cass Business Schoole: tony.key@city.ac.uk

Colin Lizieri, Grosvenor Professor of Real Estate Finance, The Department of Land Economy, University of Cambridgee: tony.key@city.ac.uk

The research

• Preliminary to more detailed & refined analysis– the distribution of investment stock in relation to economic activity– long run allocations vs market performance & fundamentals– the drivers of short-run investment flows

• Illuminating issues in– neo-classical vs uneven vs institutional vs cultural spatial theories– long run economic growth vs property performance– causation & rationality in investment allocations

• At this stage– standard proxy indicators of market dynamics applied to long run– regional scale of analysis recognising aggregation problems– to utilise full set of indicators, test methods, show the big picture

Literature

• A bit of a blind spot– theories of spatial development mostly lack investment property– property market analysis mostly on short run dynamics

• Regional economic development & investment property– skewed distributions of investment stock (Key & Law, 2004)– taken as evidence of cultural bias (Henneberry & Roberts, 2008)– alternative institutional / expectations explanations (Ball, 2001)– … lacking a comprehensive view of sectors, processes

• Property performance, investment flow, local economies– US MSA market performance & economics (Piazzi et al, 2008;

Liang & McIntosh 1998): weak links from long run economics to returns

– US MSA returns & investment flows (Fisher et al, 2009): no consistent forward / backward linkage from returns to flows

Data & methods

• All the usual UK indicators– performance (IPD), portfolios & investment flow (IPD), demand

(ONS), stock (VOA), development (DTI) indicators

– limitations of demand / supply proxies, IPD partial coverage

• 11 GB regions, annual data 1981-2009, three main sectors

• Analysis: regional variation within sectors– Stylised facts on regional property performance

– Long run shifts: portfolios, investment flow vs market performance, market demand-supply fundamentals

– Short-run dynamics: response of investment flow to relative performance, demand & supply

• Basic cross-section & time series correlation / regression

• More rigorous methods – Grainger, VAR – to follow

Findings 1 – regional long run performance

Annualised returns 1981-2009 % pa

0 5 10 15

RETAILLondon

South EastSouth West

EasternEast Midlands

West MidlandsNorth West

Yorks & HumberNorth East

ScotlandWales

OFFICELondon

South EastSouth West

EasternEast Midlands

West MidlandsNorth West

Yorks & HumberNorth East

ScotlandWales

INDUSTRIALLondon

South EastSouth West

EasternEast Midlands

West MidlandsNorth West

Yorks & HumberNorth East

ScotlandWales

• Large variation: terminal

value of £100 invested in

1980 from £623 to

£2,730

• Consistent pecking order

industrial-retail-office for

sectors & within regions

• Differentials in return

primarily the product of

unpriced variation in

rental value growth

• Regional returns reflect

risk only across retail

regions

Source: IPD

Findings 1 – drivers of long run performance

• Across regions negative relationship between– demand growth and rental value growth

– demand growth and total return

– long run supply accommodates variation in economic growth

– yield pricing does not anticipate rental or economic performance

– consistent with Liang & McIntosh (1998)

• But supply response does not explain rental variation– supply response measured by beta of construction volumes wrt

demand, total construction per unit demand, total construction per unit demand growth

• Weak level of explanation in supply factors may be due to low number of cross-sectional observations, problems with proxies, wrong level of aggregation

Findings 1 – regional long run performanceRegional rental growth and demand growth 1981-2009

y = -0.75x + 5.0318

R2 = 0.2567

y = -0.1836x + 5.2185

R2 = 0.0642

y = -0.3196x + 3.5914

R2 = 0.2541

0

1

2

3

4

5

6

1 2 3 4

Mean Demand Growth %

Mea

n R

V G

row

th %

pa

Retail

Office

Industrial

Regional supply elasticity and demand growth 1981-2009

y = -0.8092x + 2.1038

R2 = 0.1357

y = -1.9157x + 5.5034

R2 = 0.7679

y = -1.2748x + 3.048

R2 = 0.4563-3

-2

-1

0

1

2

3

4

1 2 3 4

Mean Demand Growth %

Su

pp

ly E

last

icit

y

Retail

Office

Industrial

Findings 2 – long run portfolio allocations

• All analysis on weights, relative performance within sectors

• Changes in weights:– dominant effect in all sectors fall in London weights– balancing gains southern offices, northern retail, general industrial– weight shifts mainly produced by allocations of capital spending

• Explaining changes in weights & investment allocation– nothing to do with long run returns or rental value growth– linked to rates of demand growth only in office sector– positively link to “oversupply” retail & industrial, negative in offices– no consistent regional preference across sectors

• southern “bias” against relative performance only in office• no over-arching regional picture or weight driver

Findings 2 –investment flow vs demand growth

y = 9.0096x - 23.426

R2 = 0.2435

y = 1.4719x - 4.2283

R2 = 0.0162

y = 0.3852x - 0.921

R2 = 0.0021-25

-20

-15

-10

-5

0

5

10

15

20

1 2 3 4

Demand growth 1981-2009 % pa

Ne

t In

ve

stm

en

t S

hif

t p

p s

ec

tor

va

lue Retail

Office

Industrial

Findings 3 – investment dynamics

• Tracking year by year within sectors– shifts in region weights produced by investment allocation– relative property performance of the region– relative economic growth & changes in new supply

• To identify– direction & persistence in application of investment policy– sensitivity of investment to market cycle, economic fundamentals– regional typology of investment behaviour– leads / lags of capital flow, values & returns

• Results– variation in strength, persistence, sensitivity of money flows– no consistent patterns across sectors / regions– no immediately obvious classification of policy “types”

Investment policy: London offices – relative indices

70

75

80

85

90

95

100

105

110

115

120

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

Ind

ices

198

1 =

100

Capital / Residual Shift

Weight Shift

Net Investment Shift

Capital Spending Shift

Capital Receipts Shift

Investment policy and market performance: London offices standard deviations in 3 year rolling rates around mean values

-3

-2

-1

0

1

2

3

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

Std

Dev

s ar

ou

nd

Mea

n V

alu

es

Total Return

Rental Value Growth

Yield Impact

Weight Shift

Net Investment Shift

Investment policy: West Midlands Industrial – relative indices

90

92

94

96

98

100

102

104

106

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

Ind

ices

198

1 =

100

Capital / Residual Shift

Weight Shift

Net Investment Shift

Capital Spending Shift

Capital Receipts Shift

Investment policy and market performance: West Midlands Industrial standard deviations in 3 year rolling rates around mean values

-2

-1.5

-1

-0.5

0

0.5

1

1.5

2

2.5

3

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

2004

2006

2008

Std

Dev

s ar

ou

nd

Mea

n V

alu

es

Total Return

Rental Value Growth

Yield Impact

Weight Shift

Net Investment Shift

Discussion

• Basic facts– long run property performance independent of market fundamentals– long run shifts in allocation dominated by falling London weight– investment flows: mix of fixed preference, cyclicals, nothing obvious– no over-arching north-south or other regional differentiation– weak explanation of direction & changes in investment policy

• Reservations & further work– limited by regional scale, basic methodology, broad proxies– more powerful methods: leads/lags, Grainger Causality, VAR– urban level (losing some indicators, lumpy flows may add noise)

Implications

• Why the low level of explanation– regional scale means small number of obs, aggregation problems in

terms of spatial scale, consistency problems with proxy measures– analysis is ex-post with full information, decisions are ex-ante with

uncertain information– investment policy may be set by unobserved variables (benchmark

hugging, deal flow, exit risk capital raising)

• Paradigms of spatial adjustment– lack of consistent patterns runs against over-arching explanations– if cultural why not all sectors; if positivist why South East offices; if

cumulative causation why northern retails– next steps to generate testable hypotheses from competing

paradigms, and run with varying levels of aggregation