# RDP 2020-04: The Apartment Shortage 8. How Far Can Housing Prices be Lowered?

Some readers are especially interested in the amount that prices would fall in the absence of planning restrictions. A full answer would require estimation of general equilibrium effects (some of which are modelled in Kulish et al (2011)) and is beyond our scope. Nevertheless, as discussed in this section, our analysis suggests important elements of the answer and may provide a reasonable first approximation.

For context, 98,000 higher-density dwelling units were completed in 2018, representing about 1 per cent of the Australian housing stock. A mid-range estimate of the price elasticity of demand for housing is that a 1 per cent increase in dwellings would reduce housing prices by about 2½ per cent (Saunders and Tulip 2019, Section 5.3). So were the annual supply of new higher-density dwellings to double, the cost of housing would decline by an extra 2½ per cent per year. Costs of supply, shown in Table 6, provide a limit to this.

Table 6: Costs of Supply
Per apartment, \$′000, 2018
Sydney Melbourne Brisbane
Marginal cost of building up(a) 519 491 460
Minimum cost of building out(b) 581 504 468
Minimum cost if building is dispersed(c) 542 456 443

Notes: (a) From Tables 1 and 3
(b) Minimum cost estimates correspond to point C in Figure 7
(c) As in (b), except using the unweighted cost of land from Table 4

Sources: ABS; Authors' calculations; CoreLogic data

The estimates in row 1 represent the cost of supply by increasing building heights, reproduced from Tables 1 and 3. These estimates apply to a small increase in supply. For a large increase, after heights reach their efficient level, the lower-cost approach would then be to construct more apartment buildings. This point, which might be termed a ‘long-run cost of supply’ is represented by point C in Figure 7 and row 2 of Table 6. These estimates assume that new apartment buildings are built in the same areas as recently completed apartments. For a very large increase in construction, it seems possible that apartment buildings would spread throughout the metropolitan area. The final row of Table 6, which might be termed a ‘very long-run cost of supply’ assumes land is valued at the unweighted average price of detached housing.

The estimates in Table 6 provide benchmarks that are relatively straightforward to quantify. However, they are partial equilibrium, holding the price of inputs constant. In reality, costs would change if construction increased. For example, extra building would increase the demand for scarce inputs to the construction industry, such as materials and skilled labour. This would bid up their cost in the short run, until extra supply is forthcoming. However, a more important effect is on the price of land used for detached housing. Land constitutes a large proportion of housing costs and is supplied quite inelastically, so its price moves more than other factors. If new construction replaces each detached house with about 17 apartments, as the average values given in Tables 4 and A2 imply, then the net demand for detached housing will fall. This would alleviate both the physical and administrative scarcity of land used for detached housing and hence lower its price. By how far would depend on the elasticity of substitution between houses and apartments. Lower land prices would reduce the cost of building out. In terms of Figure 7, increases in the supply of apartments would lower the average (orange) cost curve and the equilibrium would move back along the black curve towards the origin. It could be possible to reduce housing costs further if, as discussed in Section 4.3, the risks in the planning process are reduced.

There are other considerations that a comprehensive assessment would take into account. For example, Kulish et al (2011, Section 3.2) argue that, while a relaxation of planning restrictions would reduce overall housing costs, the price of land near the centre and apartment sizes would both be expected to increase. Complications like these would affect quantification, however, they may matter more for the composition and density of housing than its overall price. It is not clear that they would outweigh the changes in costs noted above, of which the factors lowering prices seem to be more important than those raising prices. So apartment prices could fall well below the cost estimates in Tables 1 or 6.