Published 4 January 2010
Treasury released a working paper on Christmas Eve which can be used to evaluate the impacts of a range of policy interventions in the housing market.
One thing the authors – Andrew Coleman of Motu Economic & Public Policy Research and Grant Scobie of Treasury – worked out was that owner-occupancy rates weren’t a particularly helpful guide to the state of the housing market. As with all the Treasury working papers, “the views, opinions, findings & conclusions or recommendations are strictly those of the authors…. The papers are presented not as policy, but with a view to inform & stimulate wider debate.”
The story below doesn’t venture into particular conclusions on specific policy shifts. But one point the authors have made is this: “For the last 2 decades New Zealand has had some of the highest real interest rates in the world. Were New Zealanders able to borrow at real interest rates closer to world averages, housing affordability could improve by an amount that would dwarf any likely effect of interventions that subsidise owner-occupancy.”
The 2 authors developed the initial version of this paper when they were affiliated with the house prices unit in the Department of Prime Minister & Cabinet in 2007. Their objective was to develop a simple model that captures the essential features of the supply & demand for housing, and which can be used to evaluate the impact of a range of policy interventions.
Interventions they simulated demonstrated:
increases in the stock of housing would reduce rents & house pricesa reduction in tax concessions for landlords would raise rents and moderate house pricesadditional subsidies for owner-occupancy would tend to reduce rents and raise house pricessignificant reductions in rents & house prices would follow a fall in the cost of housing through, for example, lower regulatory & consent costsfalling real interest rates result in lower rents, higher house prices & lower owner-occupancy rates.
“To date, models that simultaneously capture the incentives facing homeowners, landlords & developers have been large & extremely complicated. The principal aim of this paper is to develop a simple model that, while abstracting from much of the complexity, captures the essential dual nature of housing as both a consumption good and an investment good. The model incorporates owner-occupiers, a rental sector & a construction sector.
“The second aim of the paper is to analyse the effects of different policy options. Examples include:
policies that lower the marginal costs of housing (eg, through changes to regulation of land use, consent processes & building codes)policies that support the demand for housing (eg, housing related welfare payments); policies that influence the demand for home ownership through taxes & subsidies (eg, changes in the taxation of investment income from rental housing), andpolicies that change the cost of mortgage finance.
The authors used the model to simulate how house prices, rents & the quantity of rented & owner-occupied houses are affected by these different policy interventions. In turn, these variables could be used to calculate the owner-occupancy rate. In each case, the long-run (equilibrium) state of the housing market was calculated, but the authors said the model was silent on the dynamic adjustment path that house prices might take in moving from one state to another in response to a policy change.
“The analytical approach developed here can be used to guide policy formation in 2 ways. First, it indicates the scale of the change in a policy instrument that may be needed to achieve a given target level of an outcome variable in the housing market. For example, a policy analyst might wish to ask how much new dwelling construction would be needed to generate a rise of 5 percentage points in the owner-occupancy rate. Secondly, it can provide insights into the confidence that can be placed on these estimates by indicating how the answers depend on the various parameters in the model. To this end, we show how some results are indeed sensitive to a range of values for key parameters.”
The simulations investigate the consequence on the housing market of 5 different classes of policy interventions or economic shocks: changes in the number of houses, tax concessions to landlords, home-ownership subsidies, construction costs and interest rates. The model shows how rents, house prices, the number of houses and the owner-occupancy ratio are impacted by the changes.
“An important insight stemming from these simulations is that the owner-occupancy rate is a very poor measure of the state of the housing market. The owner-occupancy rate could be increased by 1% by any one of the following policies: the Government could build (& sell) 375,000 houses, construction costs could fall by 29%, real interest rates could increase by 48%, the Government could reduce the tax concession available to landlords by 29% (or about $1200/property) or the Government could increase the subsidy to owner-occupiers by 53% (or about $2500/household).
“The first 3 of these changes represent enormous interventions. However, they are large not because these interventions have little effect on the housing market but because they change the incentives facing landlords & homeowners in the same way, so induce only minor changes in the owner-occupancy ratio.
“For example, the reduction in construction costs that increases the owner-occupancy rate by 1% lowers house prices by 22%, rents by 11% and increases the quantity of houses by 4%. The change in interest rates that has the same effect on the owner-occupancy rate lowers house prices by 15% but raises rents by 22% and reduces the quantity of housing by 8%.
“In these cases the owner-occupancy rate says little about the overall state of the housing market. Clearly the former change has better housing market outcomes than the latter.
“Even in the case that a policy intervention has a direct effect on the incentives facing landlords or homeowners, the owner-occupancy rate is a poor measure of the state of the housing market. For example, a rise in the owner-occupancy rate can be induced by either an increase in the tax on landlords or an increase in the subsidy for homeowners.
“The former raises rents, lowers house prices and reduces the quantity of housing; the latter lowers rents, raises house prices and increases the quantity of housing. The distributional implications for those who rent and those who already own homes are clearly different, yet the effect on the owner-occupancy rate is the same.
“Part of the problem is that the owner-occupancy rate largely misses the way that households endogenously form or dissolve in response to changes in rents & house prices.
“Overall owner-occupancy rates can fall even if the number of young households owning their own home increases. This is because household formation can change in response to lower rents. There may be more couples deciding to split up because they can afford to live separately (with at least one renting). Young people & students may leave home earlier than otherwise and rent. Flats of 4 people may form 2 flats of 2 people, or flats of 2 people may choose to live as singles.
“All of this increases the number of renting households and improves welfare, without decreasing the number of people owning their own home. Hence, as more households form, the owner-occupier rate may fall, merely because of greater numbers of people choosing to rent. This result carries no implication that overall welfare was lower, and highlights the need for caution when using the owner-occupancy rate as either a target for, or an indicator of, public policy in the housing sector.
“The model suggests that, in the medium term, the largest effect on housing affordability would result from either lowering construction costs or reducing real interest rates. A 10% reduction in either would increase the quantity of housing by 1.5% and lower rents by 4%. Both would reduce the financing cost of owning a house by 7% although, in the event that real interest rates declined, house prices would rise and owner-occupancy rates would fall.
“Both changes are feasible. First, real construction costs were at record levels in 2007 as a result of a construction boom. It therefore seems likely they could fall as demand pressures ease. Furthermore, current policy initiatives could well reduce some elements of the various regulatory & compliance costs. In addition, for the last 2 decades New Zealand has had some of the highest real interest rates in the world. Were New Zealanders able to borrow at real interest rates closer to world averages, housing affordability could improve by an amount that would dwarf any likely effect of interventions that subsidise owner-occupancy.
“2 critical factors influence the success of any intervention in the housing market. These are the responsiveness of the supply of rental property to the rate of return to investors and the responsiveness of the construction s
ctor to house prices.
“Rents, house prices & the quantity of rental units are all much more responsive to a change in the investor returns when the supply elasticity of rental property with respect to returns is higher rather than lower. Unfortunately, little is known about this parameter, or the factors that influence entry & exit of investors into the residential property market. The importance of this parameter in the model suggests that it is a prime topic for further research.
“The model also shows that the way demand conditions affect house prices depends critically on the elasticity of the total supply of housing with respect to prices. This underscores the importance of regulatory & consent procedures that facilitate rather than hinder the growth of the housing stock. The speed that housing supply responds to demand shocks is particularly important in an environment where demand shocks such as changes in interest rates or migration inflows & outflows are common. If the supply of housing responds only slowly to demand shocks, price bubbles may occur, resulting in exaggerated swings in the housing market.”
Mr Coleman & Mr Scobie acknowledged imperfections in their model. They said its tractability required some simplifying assumptions, but it then treated the housing market as a national integrated market of houses of uniform quality, and thus made no allowance for regional patterns. Nor did it explicitly address differences in the quality of housing. However, that wasn’t a huge issue: “To the extent that regional markets and the markets for houses of varying quality are linked, this is not as serious a limitation as might first appear. A change in one part of the market will have flow-through effects on other regions. In regard to quality, the quantity supplied & demanded can be thought of as applying to standardised housing units that have incorporated an adjustment for quality.”
A second limitation was that the model was purely static: “It allows us to consider the market with or without a change in taxes, for example, but is silent on the adjustment path from the existing to the new position. As it focuses on the fundamental drivers of the housing market, it abstracts from the role played by expectations in determining house prices in the short run. This is quite appropriate when choosing between different long-run housing policies. In this case, the short-run dynamics are of less concern. Nonetheless, there is considerable evidence that house prices fluctuate excessively in the short run because price expectations in housing markets are not fully rational. For this reason, it may be worth adding dynamic elements to the model to enhance its capacity to track short-run movements in house prices.”
The data showed that, on a per capita basis, the total number of houses increased by only 4% over the 15-year study period. In sharp contrast, the number of rental units increased by 23%. “Almost all of the rental increase took place between 1996-2001. During this period real house prices increased by 110% while real mortgage rates declined by 60%. Thus the real financing cost of purchasing a house declined by 44% between 1991-2001, before increasing by 53% between 2001-06. The fact that there was almost no change in the per-capita quantity of houses demanded over the 15 years – despite these enormous variations in house prices & interest rates – suggests that the elasticity of total housing demand with respect to the price of housing must be very small – probably less than 0.1.
“The data appear to be more informative about the effect of rents on the demand for rental property. Between 1996-2001, there was almost no change in real house prices but a 9% decrease in real rents. Real mortgage rates declined from 8% to 5%, making home ownership somewhat more attractive. During this period the total number of houses (normalised for population) increased by 2%, while the number of rental houses increased 19%.”
Lastly, the authors noted: “An important feature of the New Zealand housing market in the last 4 years has been the declining size of the average household. The average number of people in each house declined steadily from 3.8 to 2.96 from 1966-1991, or by 1%/year. It declined a little further between 1991-2006 to 2.84.
“Several factors have been behind this trend. Amongst these has been a sharp decline in the average size of households with children, most notably a sharp decline in the number of families with 3 or more children. Between 1966-91, the fraction of households with 5 or more people declined from 28% to 13%. Secondly, there has been a big increase in the number of households comprising a single person or a couple.”
Links: Treasury, working papers
Treasury working paper, household debt
Treasury working paper, Housing market model
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Attribution: Treasury working paper & abstract, story written by Bob Dey for the Bob Dey Property Report.