1. Colin Jones and Michael White
Property Booms and Busts: Retail Property and Office Yield Trends Compared
Colin Jones and Michael White

2. Introduction
Downturn following credit crunch saw investment funds dramatically dry up.
Impact saw first yields rise then fall in development as it became unviable and unfundable, then rents fell
Aftermath credit crunch highlights role of external influences
Increase attention in the concept of asset bubbles
This paper examines the contribution of bubbles by an analysis of urban office and retail yields
It makes a comparison between these two property sectors

3. Office and Retail Yields: London

4. Office and Retail Yields: Edinburgh

5. Bubbles or Cycles
Term ‘bubble’ is inconsistent with the concept of efficient markets
Notion of a bubble creates another debate about its relationship with the cyclical behaviour of real estate markets
Can speculative bubbles occur independently of property cycles or do they amplify cycles?
Potential for bubbles in real estate markets given inefficiencies

6. Existing Research
Extended period of house price inflation across the world in the 1980s and especially from the mid 1990s stimulated academic studies
Tested whether these trends can be justified by reference to fundamentals
Only one by Hendershott (2000) of Sydney, Australia, has examined commercial property
11 years study period over one cycle
Approach = deviations of a fundamental value to replacement cost ratio and requiring an independent forecast of vacancy rates.
Conclusions suggest the existence of a bubble

7. Property and Business Cycle
Capital investment as the key cyclical driver of economic growth
New development = key influence on the business cycle
Occupation demand is linked to business cycle
Property market is inevitably cyclical
But there is a further factor - development time lags

8. Stylised Commercial Cycles
Development lags amplify economic cycle
Studies conceptualised the property cycle by reference to the 'cobweb model' and the role of development lags
Different types of real estate have different cycles reflecting different development lags

9. Barras Model

10. Internal Dynamics of Cycles
Cycles amplified by internal mechanics
Valuers or surveyors tend to over-price in booms (under-price in downturns)
Pressures by developers to support their decisions based on current values or expected values derived from extrapolating the past
Investment demand/ development via adaptive expectations –> prices beyond fundamentals
Supporting element in this process is akin to a Ponzi scheme in that new investors/developers are attracted by the profits made by first investors

11. continued Processes can operate in reverse direction Simplification
Banks financing development also support these processes and display lack of caution in upturns
Arguably a collective under-pricing of risk
Consequences are that construction /development activity at peak of the cycle becomes too “high” and unsustainable
Downturn or slump is also greater

12. Bubble Processes
Mechanisms overshoot price fundamentals -> a bubble
Parallels with bubble processes identified in financial asset markets
Shiller -> bubbles driven by feedback loop theory -> exogenous shocks instigate price increases encouraging further investment demand through adaptive expectations.
Property studies centre on housing - bubble as abnormal
Shiller in the latter sees the bubble as a normal phenomenon/cycle - an exaggerated cycle

13. Bubbles
Smith and Smith (2006) define a bubble as “a situation in which the market prices of certain assets (such as stocks or real estate) rise far above the present value of the anticipated cash flow from the asset”
The rapid price rise brings speculative activity on expectations of future price increases rather than focusing on the asset’s cash flow or fundamental factors driving the market.
In practice it may prove difficult to identify bubbles.
Protagonists of bubbles implicitly assume that prices were equal to fundamental values historically before a period of rapid asset price inflation.
Opponents argue that observed prices may have been too low and that increasing prices may have (at least in part) reflected an adjustment process towards long run equilibrium values.

14. Argument
Unlike asset bubbles instigated by exogenous shocks property cycles driven by internal lags
Shiller’s model of a bubble incorporating endogenous feedback driven by adaptive expectations = generic ‘cyclical’ model
‘Barras’ cycle is special case that adds time lags
‘Bublical’ model is assymetrical
Bubbles are not one off occurrences but are a natural part of property cycles but that the adaptive expectations processes of amplification are greater in the upturn than the downturn

15. Empirical Research
Continuous dynamic price system can be decomposed into a fundamental and bubble component with former present value of future income
Himmelberg et al (2005) approach - examine housing bubbles via a ‘user cost’ approach
Assess whether property is over or under valued
Essentially user cost if a function of the risk free rate of borrowing, expected capital value change (and income growth for commercial property) plus a risk premium
Property taxes etc assumed zero

16. Some detail
Within this framework in long run equilibrium capital value to income ratio should equal the inverse of the user cost, ie initial yield
Dunse et al (2007) model extended - link to real property market via inclusion of key demand variable, finance and business services output
Property markets are taken to be essentially urban with different rent cycles and have different associated risk.
Based on the office markets of British cities over the period
City level property data from IPD & SWIP

17. Model Overall yield model can therefore be rewritten as
IY = f (ΔRRVI, GY, LEP, EA)
GY = return on long dated gilts and LEP = average yield on the FTSE 100 index, ΔRRVI =current real rental growth
Equation models Barras model although development lags are not explicit, implicit in expected rental growth
Model is extended to include market fundamentals capturing the economic activity (EA) by value of finance and business services output (FBO) for offices and GDP or consumers expenditure for retail
Estimated by panel time series multiple regression in logarithmic form.
Long run equilibrium models for the cities

18. Logic of Results
Fundamentals and expectations for yields are captured from the model
Remaining mispricing may be attributed to a ‘bubble’
Following estimation of this model, fitted values were calculated for each city
Proportionate difference between actual yields in each city and those estimated from model
Greater difference then larger over- or under- pricing of office real estate

19. Office Market

20. Retail Market

21. Percentage Differences between Actual and Estimated Office Yields for Individual Cities 1981-2006

23. Percentage Differences between Actual and Estimated Retail Yields for Individual Cities 1981-2006

25. Commentary
Late ‘80s London more susceptible to bubble effects but overpricing across markets
Actual prices rising above fundamentals towards the end of the time period before financial crisis – apparent in both office and retail sectors and across cities
Clear individual patterns over time presumably reflecting localised demand and supply expectations
Asymmetry in these effects is perhaps less straightforward

26. Conclusions
Empirical analysis shows substantial and systematic cyclical bubble effects
Prices will always be ‘over-priced’ in a boom and ‘underpriced’ in a bust
Differences in time lags between office and retail did not seem to significantly affect results
Hence traditional exposition of the property cycle with its time lags needs to be augmented to encompass such ‘bubble’ effects
Barras property cycle as a special case that adds time lags to a more generic model of cycles centring on adaptive expectation stimulated by external shocks
But careful interpretation needed as further analysis required to improve model performance