In an “American Economic Review” paper, Peter Kennedy complained that statisticians often use formulas to get answers - but lack the understanding for their practical application. In today’s world, we see the output of this confusion in many forms when headlines scream “Growth accelerates even as unemployment rises”.
Or alternatively, “Transactions reach historical high in real estate even as prices fall”. For us to make sense of this incongruence, we need to look behind the data to construct an alternative model that has better explanatory power.
In Dubai, there has been a surge in offplan transactions, driven by payment plans, at prices that have been more than 30 per cent higher than their equivalent in the secondary market. Indices have been unable to account for this price variance, focussing their index construction on secondary market sales, which have a number of problems given the nature of heterogenous assets and underlying differences that cannot be accounted for.
Need for more than one indexing
In this environment, an easy fix would be for data providers to construct two alternate price indices; one for the primary market (adjusted for payment plans) and one for the secondary market (where prices have fallen and trade at a discount). When this is done, we observe that in the primary market, prices have remained stable on a per square foot basis. And in some communities, have even risen marginally.
This indicates that there is a latency of demand not only for new builds, but primarily for products that have fractionalized payment plans. Yet, despite this demand, launches have fallen across the board, indicating that a) developers have now reached the outer limit of these post-handover payment plans, and/or b) there is limited ability to service subsequent payments as the practice of “flipping” the properties have receded.
Stark differences
When we look at secondary transactional data, there appears to be a widening chasm between “min/max” values. It suggests that, at the margin, the properties that are being resold at the lower end of the spectrum are the ones that are of lower quality. And reflective of the liquidity constraints that the owner has and/or otherwise commoditized in nature suggesting that minimal upgrades have been done to upkeep the property.
When we look at secondary transactional data, there appears to be a widening chasm between “min/max” values
Meanwhile, at the “max” end of the spectrum, recorded prices have incorporated the distinguishing features of these heterogenous assets, including maintenance of the asset, as well as in certain cases, payment plans that are being offered in the ready market.
Given that the latter is less frequently transacted than the former, intermediaries are incentivized to focus on the primary space, and the “aggregate” mean prices reflect the downward trend that everyone keeps talking about.
What this suggests is that there should be a set of indices that are constructed that reflects three distinct markets at the minimum: one where payment plans are being offered and one where there are not, regardless of whether they are in the primary market or not, and one that distinguishes the primary from the secondary market place.
Make better sense of them
With these filters in place, we can start making better sense of what is transpiring in the ecosystem, having isolated for a) payment plans b) primary and secondary market offerings and c) the effect that upgrades have on the property. Currently, the data distribution pattern does not adequately account for all of these distinctions, making the job of valuators more difficult.
But in sample sizes where this is accounted for, a very different picture starts to emerge. It indicates that prices where payment plans have been offered have remained broadly stable, and the value of price declines have been exaggerated.
However, given the lack of a comprehensive data set, valuators have resorted to “aggregate pricing” models, thereby artificially devaluing the value of the collateral, and thus entrenching the malaise that investors feel. And thereby strengthening the disincentive to invest.
In more developed markets, where such variables are captured, the effect of the upgrades becomes more visible. (In markets such as Australia and America, the impact is as much as 25 per cent.)
And liquidity starts to unlock as the value of the collateral is not artificially devalued.
Data sets are important, but so are the filters that we use in order to construct our version of reality. Only when we are equipped with such tools will we be better able to glimpse at the underlying dynamics on the ground and be better informed in our decision-making.
This is part of the challenge for the "Smart City" this year.
- Sameer Lakhani is Managing Director at Global Capital Partners.
