Housing Wealth, Credit Conditions and Consumption

1. Housing Wealth, Credit Conditions and Consumption Janine Aron, John Muellbauer and Anthony Murphy CSAE, Nuffield College and Hertford College, Oxford Bank of Spain/CEMFI Conference April 2007

2. Abstract • The role of housing wealth in explaining consumption is still controversial. • Most empirical literature is marred by poor controls for common drivers of both house prices and consumption: income, interest rates, credit supply conditions, other assets, income growth expectations and changes in the unemployment rate.

3. Abstract cont’d • When credit supply conditions ease, house price booms usually follow. Omission of CCI biases housing wealth effect up. Breakdown in BOE model connected with missing credit channel. • This paper studies data for the UK and SA with better controls. Credit markets liberalized in both and consumption to income ratios rose. • Lack of asset price boom in 1983-2000 SA illuminates the direct role of credit liberalization.

4. Literature Review • Recent empirical studies of the housing-consumption link on macro data include: Case et al (2005), Catte et al (2004), Iacoviello (2004), Barrel and Davis (2004), Dvornak and Kohler (2003), Byrne and Davis (2003), Ludwig and Sloek (2002) and Boone et al (2001). • Earlier studies include Brodin and Nymoen (1992), Kennedy and Andersen (1994) and Muellbauer and Murphy (1995).

5. Micro-data • Two studies on UK micro data with diametrically opposed conclusions are Campbell and Cocco (2005) and Attanasio et al (2005).

6. Attanasio et al (2005) • Micro data from the FES for 1978-2001 to explain consumption by age & cohort dummies, household demography, housing tenure, regional house price growth rates & the level of house prices. • They find bigger house price growth rate effects for the young, with the middle aged next and the old last,& similar effects for home owners as for renters. • Since housing wealth increases with age, claim house prices are just a proxy for omitted income expectations & have no direct effect.

7. Critique of Attanasio et al • Consumption is likely to be strongly affected by current income, and also influenced by financial asset ownership (also increasing with age and differing by region), debt and variations in unemployment rates, credit conditions and interest rates. • Their failure to include these controls implies that no conclusions about the effects of housing assets on consumption can be drawn.

8. Campbell and Cocco (2005) • Micro data from the FES from 1988-2000. Explain changes in consumption per head for different cohorts classified by region, controlling for income growth, regional unemployment, interest rates as well as housing tenure, mortgage debt and regional house prices. • Largest house price effects found for the older homeowners and the lowest for renters. • But latter is still significant: suggests in their model house prices contain a general ‘confidence’ effect, as well as wealth effect. • Some peculiar individual coefficients.

9. Case, Quigley and Shiller (2005) • Claim that for, a panel of US states and a panel of 14 countries, the housing wealth effect is larger than the stock market wealth effect. • However, their econometrics are questionable. Their so-called ECM, used on a panel of US states and 14 OECD countries takes the form:

10. The Case et al (2005) ‘ECM’

11. Case et al cont’d • where y is real income, stock is stock market wealth, house is owner-occupied housing wealth. 1986 step-dummy interacted with  log house checks shifts. • Among the omitted controls are levels of housing asset and stock market wealth, interest rates, the unemployment rate, and income growth expectations effects.

12. Case et al cont’d • Pooling 14 countries denies heterogeneity due to institutional differences. • Shifts in credit conditions are omitted from the OECD country data though Finland, Norway, Sweden, the UK and the Netherlands all went through revolutions in credit availability. • Not surprisingly, the supposed housing wealth effect is even larger for the OECD countries, where credit conditions went through larger changes than for US states after 1982.

13. Table 3: Case-Quigley-Shiller specification of UK consumption function 1967-2005.

14. Implications for consumption of credit liberalization • Conventional view is that credit liberalization just makes inter-temporal consumption smoothing easier. • (Hence reduced ‘excess sensitivity’)

15. Consumption con’t • But credit market liberalization has 2 other effects, both omitted in aggregate Euler equation studies. • Increased average cons/income (lower saving rate) as those saving for durables, esp. housing, save less because down-payments lower.

16. Consumption cont’d • Increased liquidity of ‘illiquid assets’ as e.g. housing collateral role enhanced. • Thus missing level effects in standard consumption functions, and missing time varying parameters because of interaction effects between CCI and housing wealth and other variables.

17. Euler vs. solved out cons. fn. • REPIH consumption function comes from solving the Euler equations and life-cycle budget constraint. • Need income forecasting model to generate permanent non-property income • Solved out cons. fn. does not throw away long-run info. on income, assets • Better for policy modelling, forecasting

18. Log-linearize REPIH cons. fn.

19. M&L (1995) Handbook of A.E. consumption model where no immediate credit constraint

20. If some consumers credit constrained, add….

21. Transactions costs in housing suggest possible capital gains term • In principle, forward-looking capital gains term, but backward looking if consumers crudely project past gains.

22. Micro-foundations of higher MPC out of liquid assets • Otsuka (2006) sets up Carroll/Deaton-type calibrated buffer stock saving model where income process has downside. • Assumes credit limit. • Illiquid asset faces transactions cost, though higher return. • MPC higher for liquid assets than illiquid under optimal decision rule.

23. Forecast income growth

24. Forecast income growth 2

25. Forecast income growth 3

26. Forecast income growth 4 • Evidence for shift in fiscal policy around 1980: less ‘Keynesian’ role of government budget surplus and less relevance of trade deficits. • We also test for a shift in the early 1980s in the role of real house prices, to be consistent with the shifting role of housing wealth in consumption with credit market liberalization outlined in section 3(d) above. • We confirm the absence of a positive real house price effect on income before the early 1980s.

27. Results for canonical habits model Striking support for buffer-stock idea

28. Equation (4.1) in paper Includes crucial time variation of parameters with CCI Includes -0.5x2 asset/income term to improve log-linear approx. Uses ma4 of real interest rate and illiquid financial assets (Lettau and Ludvigson 2004 note gradual transmission of stock prices to consumption)

29. CCI from BOE wp.314 • Fernandez-Corugedo and Muellbauer estimate CCI as common factor in 10 jointly estimated credit variables, after controlling for rich set of economic and demographic factors • Interpret as shift in credit supply function

30. Figure 1: UK personal consumption and disaggregated assets relative to personal disposable non-property income

31. Figure 2: Credit conditions index for the UK and the real interest rate

32. UK empirical evidence • CCI level effect is important: lowers hhold saving rate by around 5% relative to pre 1980 (not G.E.). • Interaction effects with CCI important: - Housing collateral effect on consumption rises with CCI - Nominal rate effects weaken with CCI - Mild evidence that real rate effects strengthen with CCI

33. UK evidence cont’d - Interaction effect with income growth expectations - Interaction with uncertainty indicator is weak - MPC for liquid assets roughly 0.13; illiquid financial wealth 0.02-0.03; housing wealth at CCI max also around 0.03.

34. UK evidence cont’d • Weaker long-run housing wealth effects than often estimated. • Omission of CCI biases results seriously: e.g. much slower speed of adjustment, weaker real interest rate effects. • Co-integration analysis suggests single vector linking log(c/y) and 3 asset/income ratios.

35. UK cons. fn. 1967-2005

36. UK cons. fn. cont’d 1967-05

37. Sensitivity to income forecasting model • Use of average model consistent with forecasting literature favouring averaging. • We expected to find somewhat lower MPCs out of assets for sophisticated model than for naïve model. • But found no significant difference. • Can find income models implying slightly lower MPCs out of assets.

38. UK conclusions • Housing wealth effect largely works through the ‘credit channel’: high collateral values give better access to credit and so raise consumption, Aoki et al (2002, 2004) • Important long-run effect of house prices on consumption contradicts BEQM - lacks theoretical foundations for a credit channel. • Model explains recent shifts in correlation between consumption and real house price changes: lower stock market values between 2001 and 2004, and the depressing effect of higher debt to income ratio.

39. South Africa • Major data construction effort, see Review of Income and Wealth 2006 • We have no CCI (credit conditions index). • Hence estimate 2-equation system of debt and consumption. • Use dummies and prior knowledge of periods of credit liberalisation to estimate CCI from both equations.

40. CCI indicator for South Africa

41. Comparing coefficients SA/UK • Broadly consistent results – though we do not have useful unemployment data for SA. • Similar effects of liquid assets minus debt. • Results suggest somewhat higher IFA/y coeff. than for UK – note pensions are separated out. • Housing ‘wealth’ effect larger than for UK and shifts less with CCI. • We suspect asset price effects not fully purged of ‘confidence’, and some under-est. of wealth.