Housing Price, Mortgage Lending and Speculative Bubble: a UK perspective

1. Housing Price, Mortgage Lending and Speculative Bubble: a UK perspective Dr Qin Xiao University of Aberdeen Business School q.xiao@abdn.ac.uk

2. Contents • Introduction • Model • Empirical Investigations • Tentative Conclusions

3. Introduction

4. Introduction • Experiments in laboratory asset markets suggest that • When an asset market involves a large number of uninformed and inexperienced participants, bubble is a standard state of affairs. • As bubble arises, even the informed and experienced traders may also ride on the bubble. (Smith, Suchanek et al. 1988; Caginalp, Porter et al. 1998; Caginalp, Porter et al. 2000a; Caginalp, Porter et al. 2000b; Caginalp, Porter et al. 2001) • Such observations call for modifications to the conventional analytical framework which assumes that asset markets are continuously efficient.

5. Introduction • Speculative asset price bubble is potentially an interesting topic to both policy makers and market investors • Although they may not use the term “bubble” when talking about one. • Investors are interested in making the most out of a bull market, without being stranded when the bubble deflates • It is also an important issue for the policy makers, although most of them are so far reluctant to face it.

6. Introduction • The bubble literature can be roughly divided into three strands. • To prove or disprove the existence of a bubble in an asset price. • To measure the proportion of that price which is purely bubble. • To forecast • How fast the bubble increases • How likely the bubble will burst in the next period; • When the bubble is purged eventually, in what manner will that happen?

7. Model

8. Model • Model is based on (Caginalp and Ermentrout 1990; and Caginalp and Balenovich 1999)

9. Model • Assumptions • prices adjust as a result of excess demand; • excess demand depends on the relative supply of the housing to the mortgage supply, both finite though not fixed; • The supply of the mortgage is a function of the price dynamics

10. Model • Each unit of wealth is in one of two states: housing or cash. • The fraction of the wealth in housing asset is (1)

11. Model • Participants are both housing and cash holders. • At any time, a typical investor will buy housing with probability k and sell it with probability 1-k • Hence, the flow demand function for housing • And the flow supply function (2) (3)

12. Model • k is a function of investor sentiment, (t). • with (t) driven by two forces: trend following and mean reverting (5)

13. Model • 1: Bubble generation mechanism • 2: price correction mechanism • Price Dynamics (6)

14. Model • Substitute equation 1 - 5 into 6, and define LP (7)

15. Model • Assume the dynamics of the liquidity (8) • P relax borrowing constraint • L 

16. Empirical Investigations

17. Empirical Questions • How much of the house price and mortgage growth in UK can be explained by this model? • The model implies two forces are at play: one is a stabilizer, the other destabilizer • What is the empirical evidence on the relative strengths of the two?

19. Show log changes Adjust scale

21. Building the Statistical Model • The fundamental price: approximated by GDP. • The liquidity: approximated by housing loan • Cross products between pairs of regressors implied by the model are also examined. • Variables are deflated by RPI if appropriate • The regressors are selected using stepwise regressions.

22. Building the Statistical Model

23. Building the Statistical Model

24. Building the Statistical Model • It is possible that agents in the housing and/or the mortgage market behave asymmetrically in different phases of a market cycle.

25. Building the Statistical Model • St: a state variable following a first-order two-state Markov chain, with transition probabilities

26. Model Estimation • Four models are estimated by assuming • no-switching and  0 (no switching SUR) • With switching and  0 (Markov-switching SUR) • No witching and  = 0 (no switching single) • With switching and  = 0 (Markov-switching single)

27. Model Comparison

28. Model Comparison

29. Parameter Estimates Price is meanreverting distablizer

30. Probabilities of the States

31. Probabilities of the States

32. Diagnostic Check

33. Diagnostic Check

34. Diagnostic Check

35. Diagnostic Check

36. Work remains • Use a convergence measure to investigate the forecast power of the model • The significance level of the Markov-switching model is to be established using Monte Carlo experiments • Simulate the time paths of house price and housing loans implied by the statistical model to illustrate • The origin of the bubble • The propagation mechanism of the bubble • The stability of the system

37. Tentative Conclusions

38. Tentative Conclusions • We have investigated a model in which a housing price bubble arises as a result of trend following sentiment • The model takes into account of the feedback effects between housing prices and mortgage lending; • It also accounts for changing sentiment in the market • The application of this model to UK housing market confirms that the model roughly explains 70% of the overall variations of both prices and housing loans. • The significance and forecast ability of the model are still to be established

39. The End • Thank you! • Comments?