Personal Finance

The reality about housing statistics

Meera Siva | Updated on January 13, 2019 Published on January 13, 2019

Data on the real-estate market must be taken with a pinch of salt

We look up to numbers to get a snapshot of where things are and which way to go. But in the housing segment, data is not easy to come by and good data is rarer still. So, while there are many reports, statistics and analysis, each has its own set of limitations. A home buyer should, therefore, look at any predictions based on these with a bit of scepticism and reanalyse it considering the factors that may have skewed information.

Inscrutable inventory

To start with, there is no clear answer to the simple question: how many unsold houses are there in the market? Data from different sources give widely varying number of units based on what is considered inventory — completed projects or under-construction, and whether it includes redevelopment or not.

To add to the confusion, inventory is also given in months, based on how many it will take to sell it. The reason to use the time metric is to be able to compare backlog across different cities where demand varies. For example, consider a tier-II city with 100 completed units and a larger one with 1,000 units. It is likely that the demand in the smaller town is five per quarter versus 100 per quarter in the big city. The backlog will take 20 quarters to clear in the tier-II city compared with just 10 quarters for the tier-I city, though it started with more units.

For instance, data from realty research company Liases Foras showed that Chennai had a housing inventory of 63,940 units as of September 2017; it increased to 73,685 units by September 2018. But the stock in 2017 was estimated to take 71 months to sell and the higher number of units in 2018 was expected to be sold out in 68 months, based on increased demand.

But the flip side of this is that demand is not an easy metric to accurately define. So, quarters of unsold inventory must be considered along with the number of units, and that, too, primarily for finding directionality. In the example above, we can infer that more projects are getting completed and demand is improving, both pointing to a positive sentiment.

Price paradox

Property price is also not easy to find data or direction on. One reason is that house prices vary widely even in a micro-market, based on location, project features, construction material and what features are added. For example, two houses, possibly in the same project, could sell at different prices — based on the finish, the number of car parks, location within the project (such as near the pool or park versus the roadside) and the number of bedrooms. Data from the National Housing Bank’s Residex index for Gurugram show that the price per square feet for smaller houses (less than 646 sq ft) in March 2018 was ₹6,589, compared with ₹10,513 for larger ones (over 1,184 sq ft).

Here again, data from different sources may give widely divergent numbers, possibly based on the price data used. Residex, for example, has three different prices — registered price (from the sub-registrar office), assessment price (based on value collected from lenders such as banks) and market price (collected from market survey).

For instance, for Ludhiana, the assessment-based method show that prices fell 13.5 per cent between March 2017 and March 2018; while data based on market information show that prices increased over 3 per cent in the same period.

Worse still is data that is supposed to give a broader view of the market. Property market is very local, and looking at national data may not be of much use. In every period, there are cities where house prices growth is robust — possibly due to local job creation that spurs demand, low supply, or infrastructure growth that creates pockets of buyer interest.

For example, prices were weak in the June and September quarters of 2017 in most cities. In Pune for example, prices dipped from ₹9,273 per sq ft in March 2017 on average to ₹9,171 in September. But in Panvel, prices increased in the same period — from ₹9,952 per sq ft to ₹10,351. This is true for longer time periods as well for other cities.

You must also look at the vested interest of those providing data. Often data from developer bodies, brokers or real-estate consultants may show a picture that is rosier than what the ground realities show. Likewise, online property platforms may have their agenda to promote, and you should consider the biases in their findings or analysis. As a home buyer, look at the specific local market rather than broader trends, find trustworthy sources such as government data, and work with reliable agents, before deciding on a buy or sell transaction.

The writer is an independent financial consultant

Published on January 13, 2019
This article is closed for comments.
Please Email the Editor