RDP 2020-04: The Apartment Shortage 9. Directions for Further Research

Our main conclusions were stated in the introduction and we do not repeat them here. Instead we offer a few comments on key uncertainties and where further work would be beneficial.

The greatest risk to our results is the possibility that our data do not capture all the costs of supplying new apartments. This may be because we interpret the data incorrectly or because we omit important costs. Developers have given us detailed valuation reports and ARGUS EstateMaster (common industry software) projections that they and their lenders use for financial planning, and we have attempted to align our estimates with these. However, individual reports vary and synthesising this information is difficult.

Within the components of costs we do measure, perhaps the greatest uncertainty is the threshold profit at which developers would be prepared to increase supply, as discussed in Section 4.3. We do not have good data on ex post margins and even less information on what might be needed ex ante in the absence of planning uncertainty.

With respect to prices, there are three uncertainties we would like to emphasise. The first is the difference between new and average apartment sales. We assume that sales within five years of construction are indicative of the returns developers might expect. However, as discussed in Appendix E, there are uncertainties about these estimates and new sale prices might be substantially larger than total sale prices.

Second is the Goods and Services Tax (GST). This is explicitly included in costs, so should also be included in prices. GST is payable on new properties but not on old. CoreLogic's policy is to quote prices including GST; however, it is not clear that their source data are always consistent with this. So some of our prices may be 10 per cent too low.

Third is the tendency of prices to increase with height. Glaeser et al (2005, p 362) estimate that each extra storey of height raises the price of Manhattan condominiums by about 0.08 per cent. A difficulty with estimates like these is that a view is more valuable if you can see over nearby buildings. So values increase more if other heights are constant than if all buildings were taller. We ignore this effect for reasons of simplicity and data availability. In doing so we underestimate the benefits of higher buildings.

We expect that these and other uncertainties could be narrowed with further effort. That said, our estimates seem qualitatively consistent with independent industry estimates of site values, discussed in Appendix B. Moreover, they are in line with international research, a large body of anecdotal evidence and expert judgement, discussed in Sections 1 and 2. So the uncertainty concerns precise quantification rather than the overall results.

With respect to future work, the top priority is to quantify the external costs and benefits of supply restrictions. Our paper estimates private costs. This provides a benchmark against which external benefits, such as those surveyed by Ahlfeldt and Pietrostefani (2019), can be compared.