FOREWORD Mild tapering of inflation and a normal monsoon finally paved the way for lowering of REPO rate by 25 basis points, taking it to its lowest level in the last 5 years. The continued fall in both imports and exports, coupled with tepid investment demand has led RBI to pass on the cut. The Y-o-Y GDP growth rate also slowed down from 7.9% in the JFM quarter to 7.1% this quarter. The expected rise in oil prices from next year is also a major concern for the economy, which imports most of the oil it needs. High NPAs in the banking sector and construction delays in infrastructure and real estate also remain as major concerns. However, the economy remains strong despite headwinds facing the world economy and geopolitical turmoil across Asia and Europe. The Manufacturing Purchasing Managers’ Index (PMI) is still above 52 level and GDP growth forecasts till 2020 by various multilateral agencies, remain above 7%. The lowering of Repo rate is expected to bring down both project finance as well as home loan costs, lowering the overall cost of buying a house. The inevitable implementation of Real Estate Regulation and Development (RERA) Act, 2016 has led developers to hasten the delivery of their projects. This trend was clearly evident in the quarterly average prices data of Under Construction (UC) vs Ready-to- Move-in (RM) stock, where the premium commanded by RM properties came down due to increase in RM stock, as a portion of UC projects were delivered over the quarter. RERA is a step in the right direction but will bear fruit only in 2-3 years, and till then the Indian real estate sector remains in turbulent waters, and its health can only be gauged through inferential means like pricing and inflation in the sector. Price, as an end-product of interaction between the underlying demand and supply elements, incorporates all the sector related imperfections like delays and surge/dearth of transactions. Its trend also serves as a guidance to fiscal decision making by the government and RBI and investment decision making by private equity funds and retail home buyers. Real estate in every city is heterogeneous and each locality and project can be mapped to different budget segments and geographies. Each budget segment and geography corresponds to a certain share of supply and consumer preference in the market. Towards this end, Magicbricks presents a holistic price Index for each of the 14 major cities in India. The City Index reflects the price movement across localities, geographies and budget segments in the city. This bottom-up approach helps to identify factors affecting demand-supply dynamics of the city. Analysis of City Indices over a 3-year period shows that Navi Mumbai had the highest gain of 18%, while New Delhi continued to face tough market with a 21% decline. Regionally, Western India performed the best with 8.9% average gain, followed by South with 7.6% increment. North India saw an average decline of 7.4%, while Kolkata had the same average price as eleven quarters ago. It is important to note that any gains made are eroded when benchmarked against inflation in economy, in the study period. Another important sign of our times is the 8% premium commanded by the Ready-to- Move-in (RM) properties over the Under Construction (UC) properties at a pan-India level. This ratio was at 5.1% eleven quarters ago and is a reflection of the falling consumer confidence in timely delivery of projects. These are changing times and we would love to hear from you. Do write to us at Sudhir Pai [email protected] and share yours views on this report and how we could make CEO, Magicbricks.com PropIndex even better. METHODOLOGY Realistic price discovery has been the pricing. If, on the other hand, you are The Interquartile Range technique biggest problem area in the Indian a seller looking for benchmark pricing, works through measuring variability real estate market. As consumers you will effect the fastest sale if your of each data set, while dividing the and industry struggle to arrive at a asking values are close to the buyer’s data set into quartiles. The technique realistic benchmark pricing to assess paying power. measures the value of data points on the first and third quartiles of the data the true value of their individual units, There are various co-relations of and calculates the difference between Magicbricks, as the largest repository demand and the overall real estate the two. of residential property listings, brings market as well as its future potential. you the trusted Indian Apartment Not only is demand a preceding This range, called ‘IQR’, gives the Price Index in a new and easy to indicator to supply, it is also a fairly effective extent of data set, while use format. Mirroring the Indian good indicator of actual transaction removing the first 25% and the last Real Estate scenario, this price index activity in the region. 25%. Subsequently, a test is applied presents an animated representation to each of the values in the data set. If We have aggregated the 14 cities of the real estate market. a particular data lies within an IQR of covered under the report into various the first and third quartile values, then Magicbricks publishes the quarter-on- localities. While calculating the city that data is considered part of the data quarter inflation and deflation trends level property pricing indicator, we set, otherwise not. The set of listing of the residential real estate prices in have applied demand as weight to values of each locality are statistically India. It collects real estate demand- each locality. This weight is equal to cleaned. supply data on a daily basis for more the locality’s share of the demand than 100 cities in India, of which, the being contributed to the city’s total Magicbricks, on an average, covers fourteen top cities are selected for demand. As a consequence, the more than 500 localities for Tier-I cities computing the National Property Price locality receiving higher demand for of India. Yet for the sake of analysis, Index. residential units will be given a higher we take only those localities where the The National Property Price Index and weightage. Following that, each recipient demand is at least 0.05% of its constituent indices are subjected to city’s price movement is calculated by the city’s total demand. Only localities a series of stringent steps. aggregating the price movements of with at least 50 actively traded individual localities, according to their properties have been included in the Each quarter, Magicbricks measures individual weightages. analysis. Following that process, we the individual property level price shortlisted various localities which changes, which are then aggregated at In terms of checks and balances in some sense, impact the pricing the locality level. While comparing the towards making the data and dynamics of the city. average pricing figures for the current analysis more robust and objective, quarter and comparing with the we have made sure that superfluous We then calculate the average prices of previous one, quarterly price changes information does not deviate the the city for the quarter, while applying are calculated. These price changes are desired results. Hence, we have demand weights to the average prices further aggregated at the city level applied checks and balances at the of each locality. These average prices and even further at an all-India level. locality level listing data collection and at the city level are further aggregated aggregation. to the final outcome of the ‘National As the top receiver and aggregator Price Index’. of residential demand, Magicbricks’ A statistical technique called “Inter- data provides consumers with Quartile Range” (IQR) has been used The difference in Under Construction realistic benchmarks to the assess to ensure that unintentional input and Ready-to-Move-in property has true property pricing. Where demand deviations of house size and price been assessed and included in the exceeds supply, consumers have no figures, which may distort the actual report. Rental yield and affordability chance of negotiating values. value of the house and corrupt the too has been addressed for the top 10 analysis, are addressed. The technique localities by supply in every city. These However, where demand is far lower aims to remove the outlier data sets, are critical tools which well used can than supply, buyers can look for more while securing the correct values. help with realistic price discovery. options and therefore, negotiate GLOSSARY & DEFINITIONS 1. City Property Index :This is a composite index which is a function of supply of properties as well as the average capital appreciation/drop in various localities of the city in the quarter. The City Index is the weighted average of the average rate per square foot in that locality and the supply of properties from that locality. Localities with higher supply of properties will have a bigger impact on the Index. 2. Price trend basis budget segments: To better understand the city’s price trend, the localities have been divided into budget segments basis their capital value (Rs/sq ft). We have tracked the weighted average price for each budget segment for a 2+ year period from quarter ending September 2013 to quarter ending September 2016. Subsequently, the movement of the localities in each price segment is mapped to derive respective short term and long term price change trends. The number of budget segments vary according to the city characteristics. 3. Zone wise distribution of localities: The various localities in the cities are all geographically divided into five key regions: Northern, Southern, Eastern, Western and Central.