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1 Demographic Change and the Housing Market Eric. J. Levin University of Glasgow Alberto Montagnoli University of Stirling Robert E. Wright University of Strathclyde

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2 Aim: Estimate the impact of demographic change on house prices in Scotland. More specifically: - Population decline - Population ageing

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5 OVERVIEW 1)The Demographic Past 2)The Demographic Future? 3)Demographic Change and House Prices 4)Difference in Differences Approach 5)Empirical Specification 6)Results 7)Conclusions

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6 1. The Past Summary of Current Demographic Situation in Scotland 1. Below replacement level fertility 2. Declining mortality (e.g. increasing life expectancy) 3. Zero net migration (i.e. No. of immigrants No. of emigrants)

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10 2. The Future? Government Actuarys Department (GAD) Annual population projections 2003-based projections Assumptions: Continuation of the status quo

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14 If the Current Demographic Situation Remains Unchanged: 1. Population will decline from its current level of about 5 million to about 4.5 million by Population will age rapidly, e.g. – Increase in the number and percentage of people aged 65+ – Decrease in the number and percentage of people aged < 15

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20 3. Demographic Change and House Prices Levin, E.J. and R.E. Wright, (1997), The impact of speculation on house prices in the United Kingdom, Economic Modelling, vol. 14, no. 4, pp Levin E.J. and R.E. Wright, (1997), Speculation in the Housing Market, Urban Studies, vol. 34, no. 9, pp Levin, E.J., A. Montagnoli and R.E. Wright, (2004), Demographic Change and the Scottish Housing Market, unpublished

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21 Key Paper: Mankiw, G. and D.N. Weil, (1989), The Baby Boom, the Baby Bust and the Housing Market, Regional Science and Urban Economics, vol. 19, pp

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22 Mankiw, G. and D.N. Weil, (1989) US analysis The post-war Baby Boom was followed by the 1970's Baby Bust. Baby Boomers cause demographic bulge of 40 year olds by mid-80's. Baby Busters cause a demographic shortfall of 40 year olds by Mankiw and Weil estimated the demand for housing as a function of age using cross-section data and show that the demand for housing peaks at age 40 and declines for older age groups. Taken together, the ageing of the Baby Boomers and the shortfall of replacement 40 year olds caused by the baby Bust imply that the real price of housing would fall by 3 percent per year during the 1990s and that real house prices would fall by 47% by This conclusion is reinforced by their failure to detect any significant price elasticity of supply that might mitigate this effect.

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23 CRITICISMS OF THE MANKIW AND WEIL PAPER DiPasquale and Wheaton (1994) argue that Mankiw and Weil should have estimated a lagged supply response. D&W estimate the long run price elastic long run supply of housing in the range +1.2 to +1.4 for the USA. They estimate that between 1990 and 2000 USA real house prices would increase by 6.7%. Pitkin and Myers (1994) say that longitudinal inferences should not be derived from cross-sectional estimates. They criticise M&W for assuming that the variation in demand for housing across different ages at a point in time is equivalent to the variation in demand exhibited by members of specific cohorts as they progress through the life cycle. P&M purged the cross-sectional estimation bias and show that the life-cycle trajectory does not peak at age 40 but actually increases well past age 70. Therefore ageing of the baby boomers will not cause a decline in house prices.

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24 House Price age

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25 Engelhardt and Poterba (1991) suggest that the MW results are not robust. The Canadian demographic pattern is similar to the USA, but Canadian house prices are not related to demographic demand. Ohtake and Shintani (1996) apply the MW model to Japanese data and they find that demographics have a significant effect on the housing stock but not on house prices. They find a long run relationship between housing demand and housing stock. There is a short-run effect of demand on price but this disappears in the long run. Holland (1991) points out that the MN prediction of 47% fall in house prices between 1987 and 2007 is implausible because rental prices fell over the 1970s during the period when house prices rose. Therefore it is implausible to attribute the increase in house prices during the 1970s to a demographically induced increase in demand when the user cost of housing was falling. Hamilton (1991) points out that Mankiw and Weil's forecast of house price decline depends largely on an implausible negative time trend of -8.1% in house prices.

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26 Many critics emphasise the need to control for other variables Fortin and Leclerc (2002) suggest that rising incomes will counteract any tendency for prices to fall. They make the important general point that it is necessary to control for other variables when estimating the effect of demographic variables on house prices. Hendershott (1991) criticises the Mankiw-Weil analysis on two rounds. First, the result is not robust because the equation fits the 1950s and 1960s data but does not explain real prices in the 1970s and 1980s. Second, the Mankiw-Weil estimation attributes the entire shift in demand to demographic factors and ignores rising real income and falling interest rates which biases the estimated effect of demographic factors on house demand.

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27 Swan (1995) emphasises that point that the Mankiw-Weil independent variable is a measure of demography, a weighted measure of population that cannot be interpreted as a measure of demand without controlling for other demand shifters like income and interest rates. Holly and Jones (1997). MWs results may be due to a spurious correlation between non-stationary variables. As income and house prices rose over time, part of the rise in house prices may have been incorrectly attributed to increased demand from Baby Boomers.

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28 Recent studies still conclude that demography does matter despite criticism of the MW analysis. Terrones and Otrok (2004) find that even after controlling for fundamental economic variables, an increase in the population growth rate of one quarter percent would lead over time to an increase of about one percent in real house price inflation. This recent finding is close to the original MW estimate that a one percent increase in the demand for housing leads to a 5.3 percent increase in the real price of housing. Holly and Jones (1997) estimate long run cointegrating relationships for real house prices using observations on real income, user cost, building society lending and demographic influences. Their results suggest that the single most important determinant of real UK house prices is real income, but demography matters and that a one percentage point increase in the proportion of the population aged 20 to 20 years is associated with over 1.5% increase in the real house price.

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29 Meen (1998) shows that projected demographic changes affect the owner-occupancy rate via changes in both house prices and rates of new construction. His estimated elasticity of new housing starts with respect to new building profit markup is only Therefore the price elasticity of housing supply is very small bearing in mind that new construction is always small in relation to the existing stock. Therefore any increase in demand will re-establish equilibrium via a price effect rather than an supply response effect.

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30 Changes in institutional arrangements over time make it difficult to control for other variables. Muelbauer and Murphy (1997) explain booms and busts in the UK housing market by a model that includes demography and income expectations, as well as changes in institutional constraints such as financial liberalization that reduced constraints on credit and gearing as well as lumpy transaction costs, interest rates. Buckley and Ermisch (1983) explain how the size of the tax subsidy to owner- occupied housing varies directly with the rate of inflation when capital appreciation of houses is exempt from capital gains tax. Ortalo-Magne and Rady (2004) focus on the impact of changes in institutional arrangements, specifically the interaction between demographic shifts and credit liberalisation from 1981 when banks in England and Wales were allowed to offer mortgages to explain fluctuations in housing demand in England and Wales. Increased demand for housing provided extra purchasing power for existing home- owners to move further up the property ladder.

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31 A strong case remains for continued attention to the likely demographic impact on Scottish house prices despite the critiques of the MW paper. Malpezzi and Maclennan (2001) find the price elasticity of supply for UK housing is about 0.3, ten times smaller than the price elasticity of supply for the USA which is about 3.0. These elasticities refer to the responsiveness of new starts to changes in the price of new houses. But new starts represent about 1 percent of the total housing stock, so the price elasticity of the total housing stock to price is about That is, a one percent rise in house prices increases the total stock of houses by of one percent. That is, the supply response to increased demand is very small.

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32 Earlier Paper on House Price Determination: P = f(i, y, gP, π, by - r, gStock, N 1, N 2, N 3, N 4, S 1, S 2, S 3, S 4 )

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Appendix Table 2 Estimated Impact of Variables on House Prices FactorAn increase of:House prices change by: Real mortgage interest rate (i) 1%-1.9% Real household gross income (Y) 1%+0.8% Real house price growth in the previous period (gP) 1%+0.7% Inflation (π)1%-2.0% Bond yield minus mortgage interest rate (by- r) 1%-1.8% Stock return in previous three years (gStock) 1%-0.16% Proportion of population aged 25 to 34 (S 1 ) 1%+3.7%

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34 4. Difference in Differences Approach Difference in difference is a regression based approach that explains the difference between English and Scottish annual growth rates in house prices by the difference between English and Scottish annual growth rates of income and demographic variables. This technique enables us to ignore all variables affecting house prices that have identical changes in Scotland and England as they change over time.

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44 Real House Prices PS t = Real house prices in Scotland in year t PE t = Real house prices in England and Wales in year t ln(.)= log Change in real house prices = difference between log of real house price in the previous period (t-1) compared with the current period (t): (1) Change in PS t = lnPS t - lnPS t-1 (2) Change in PE t = lnPE t - lnPE t-1 (3) Change in P t = Change in PE t – Change in PS t 5. Empirical Specification

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45 Income IncS t = Real household income in Scotland in year t IncE t = Real household income in England and Wales in year t (4) Change in IncS t = lnIncS t - lnPS t-1 (5) Change in IncE t = lnIncE t - lnIncE t-1 (6) Change in Inc t = Change in IncE t – Change in IncS t

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46 Population NS t = Number of people in Scotland in year t NE t = Number of people aged in England and Wales in year t (7) Change in NS t = lnNS t - lnNS t-1 (8) Change in NE t = lnNE t - lnNE t-1 (9) Change in N t = Change in NE t - Change in NS t

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47 Population Aged N S t = Number of people aged in Scotland in year t N E t = Number of people aged in England and Wales in year t (10) Change in N S t = lnN S t - lnN S t-1 (11) Change in N E t = lnN E t - lnN E t-1 (12) Change in N t = Change in N E t - Change in N S t

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48 Repeat for the Other Three Population Age Groups: (13) Change in N t (14) Change in N t (15) Change in N 65+ t

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49 Difference in Differences Regressions dx = Change in x or difference in x: (16) dP t = a + b 1 dInc t + b 2 dN t (17) dP t = a + b 1 dInc t + b 2 dN t + b 3 dN t + b 4 dN t + b 5 dN 65+ t

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50 6. Summary of Results House price growth rate differentials between England and Scotland are caused by –Income growth rate differences –Population growth rate differences –Age composition rate differences

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52 R 2 (%)35.6%55.7%40.6%64.7% LM (2) 0.95 [0.6] 2.51 [0.3] 2.07 [0.4] 4.20 [0.1] ARCH0.52 [0.5] 0.84 [0.4] 0.05 [0.8] 0.94 [0.3] HET2.87 [0.6] 6.66 [0.5] 5.28 [0.9] 9.49 [0.7] JB0.68 [0.6] 0.41 [0.8] 0.92 [0.6] 0.94 [0.6] Notes: (1) Absolute value of the ratio of the parameter to its standard error in parentheses. (2) LM is the Breusch-Godfrey Lagrange-multiplier test for serial correlation; ARCH is the 2 nd order Lagrange-multiplier test for auto-regressive conditional heteroskedasticity; HET is the White test for heteroskedasticity; and JB is the Jarque Bera test for normality. Numbers in parentheses are the p-values of the test statistics.

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54 7. Conclusions Demography appears to impact on house prices: –Lower population growth is associated with lower house price growth –Younger age groups are of particular importance to rates of house price growth –Future demographic differences between Scotland and England will cause house prices to diverge

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