The re­al­ity about hous­ing sta­tis­tics

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

The Hindu Business Line - - YOUR MONEY - MEERA SIVA Data rid­dles

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 No price clar­ity Lo­cal vari­a­tions


Is­sues with es­ti­mat­ing de­mand

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