Recent Trends in Residential Property Prices in India: An exploration using housing loan data by RBI

conclavekandivaliBy Accommodation Times News Services

Central banks monitor developments in property prices in view of their prime objectives of price stability, financial stability and growth. The Reserve Bank of India initiated an information system on residential property prices, viz. ‘Residential Asset Price Monitoring System’, to track movements of residential property prices in India. The information for this purpose is being collected from 35 scheduled commercial banks/ housing finance companies, based on transaction level data on housing loans disbursed across 13 cities. The property price data considered for this purpose is the valuation price of the property as appraised by the concerned bank/HFC. Based on the data compiled on a quarterly basis, a Residential Property Price Index is constructed for each city and at All-India level. The data provided evidence of steady rise in house prices during the past four-and-a-half years. House price inflation which was at its peak during 2012-13, has stabilized in the recent period

I. Introduction: Asset prices provide useful information on the state of the economy. Booms and busts in asset markets give rise to economic imbalances. Changes in asset prices affect consumption spending through its effect on household wealth as well as consumer confidence. Bernanke and Gertler (1999) referred to a balance sheet channel connecting asset prices and economy to a greater extent. Asset price changes can also have impact on banking and financial sectors of the economy through mortgage channel. A decline in the value of asset reduces the value of available collateral which in turn adversely affects the borrower’s creditworthiness. Volatility in house prices can generate wasteful speculative investment, which has adverse impact on economic stability. Central banks monitor developments in residential and commercial property prices keeping in view their prime objectives of price stability, financial stability and growth. Housing market is a key link in the chain of events impacting the economy. Mortgages being one of the biggest financial transaction of households and housing-loan being the major component of households’ liabilities, central banks track property prices for fine-tuning their microprudential supervision and regulation. Large decline in property prices can induce financial instability. Central banks’ concern regarding changes in housing market arises due to these reasons, as observed by Gerlach (2012). The ‘Second Geneva Report on World Economy’ observed that inflation targeting central banks can achieve better performance by adjusting their policy instruments in response to asset price forecasts along with inflation and growth forecasts. Measurement of house prices and compilation of house price indices are challenging tasks, unlike commodity prices. Depending on the availability of house price data and their sources, the compilation method for house price indices, which serve as aggregate measures of house prices, also varies (Eurostat 2011). In India, capturing reliable data on property prices is extremely challenging. Though there are various data sources such as government registration authorities, builders, real estate agents, individual buyers and sellers, housing societies etc.; banks and housing finance companies are comparatively practicable and reliable sources of property/house price data, due to their prominent role in institutional financing for housing as well as timely data availability in electronic form. In view of this, Reserve Bank of India initiated a ‘Residential Asset Price Monitoring Survey’ in July 2010, for collecting residential property prices in the form of transaction level housing loan data from scheduled commercial banks and housing finance companies (HFC) on quarterly basis. II. Prelude to Residential Asset Price Monitoring Survey Considering the significance of real estate property price data for central banks, RBI had set up an ‘Expert Group on Asset Price Monitoring System’ in 2009, with the objective of developing an effective information system on asset prices, in a manner that could be useful for monetary policy and financial stability purposes. The Group recommended to collect real estate property sale/resale price data pertaining to selected 13 centres, directly from scheduled commercial banks and housing finance companies (HFC). These centres1 were selected based on the twin considerations of housing loan disbursement by banks as well as their regional representation. Further, the Group recommended compilation of a real estate price index using data generated from the system, on a quarterly basis with financial year 2009-10 as base year. As Banks/HFCs appraise properties before sanctioning housing loans and these appraisal values are comparatively reliable estimates of property prices, the Group recommended use of such appraisal values for constructing the index, rather than transaction prices. The Group envisaged that the real estate price index based on such data has the potential of becoming a reliable national-level price index. III. Evolution of Residential Asset Price Monitoring Survey The quarterly ‘Residential Asset Price Monitoring Survey’ was launched in July 2010. In the first round of this survey, 42 scheduled commercial banks/ HFCs were requested to provide requisite housing loan transaction data, for the selected 13 centres, for the period January 2009 to June 2010. For most of the banks, the information required for the survey was not forming part of their internal systems. Therefore, banks initially found it cumbersome to cull out the requisite data, which led to severe delays in data submission and poor response from banks. Only 8 banks reported in the first round of the survey. Banks were requested to put in place a system to capture the desired data and were also requested to extract data for the previous periods for increasing the coverage. The regular interactions with banks/HFCs and the relentless follow up efforts resulted in improved data reporting over time. IV. Survey Design & Methodology IV.1 Coverage Presently, the survey covers selected 35 Banks/HFCs2 . However, around 30-32 banks/HFCs are reporting in each quarter. These Banks/HFCs report housing loan transaction in 13 cities viz; Greater Mumbai, Chennai, NCR Delhi, Bengaluru, Hyderabad, Kolkata, Pune, Jaipur, Greater Chandigarh, Ahmedabad, Lucknow, Bhopal and Bhubaneswar. IV. 2 Data items collected The data items captured in the survey include variables such as, type of the property (residential/ commercial), address of the property, type of transaction (under-construction/ ready-construction/resale), floor space area of the structure, date of first disbursement of loan, cost of property, valuated/ estimated price of the property by the bank, first borrower (male/ female/ partnership firm/ proprietary concerns/ company/ others), occupation of first borrower (employed/ self-employed/ others), gross assessed monthly income of the borrower, loan amount, maturity period and Equated Monthly Instalment (EMI).

IV. 3 Residential Property Price Index (RPPI) – Methodology The data received for the survey is used to construct City-level as well as All-India Residential Property Price Index (RPPI) 3 . The assumptions underlying the construction of the index are; (a) the composition of stock of properties remains constant over a certain period of time, (b) unit prices of properties are representative of the sub-category where they belong and (c) the record of stock of properties with commercial banks are adequate for construction of index (Report of Expert Group on APMS, 2010). For compilation of the index, residential property transactions in each city are stratified into 3 area classes viz. small, medium and large, depending on floor space area and the per unit prices of properties in each area class are computed for each transaction. For each of these area classes, the median unit prices are computed and the corresponding price relatives are derived. The city-level RPPI for each city is constructed using Laspeyre’s Price Index method, with the proportion of total loan amount sanctioned in each area class of the city in the base year 2009-10 as weights. The All-India RPPI is constructed using weighed average of city-level indices, with weights as proportion of residential housing stock in the respective city as per Census 2011. The detailed methodology for compiling City-wise and All-India RPPI is given in Annex-I. For constructing city-wise indices, the Expert Group recommended using the proportionate distribution of total loan amount sanctioned in the base year as weight, to arrive at a measure of capital appreciation. Alternatively, to get a measure of price appreciation, the proportionate number of house transactions can be used as weights. However, the city-wise RPPI constructed using both these weights provided similar figures. Similarly, All-India RPPI constructed using weights as proportion of housing stock in each city as well as the proportion of housing loan transactions in each city yielded similar results. However, the weighting based on city-wise housing stock is as per Census 2011 data and hence it is not subject to the limitation of reported transactions. V. Survey Results V.1 Trends in House Prices: City-wise and All-India The housing market witnessed an upward trend in prices during the past four and half years, as evident from the steady rise in RPPI from 107 in Q1:2010-11 to 172 in Q3:2014-15; an increase of almost 61 per cent (Table 1). The highest growth in RPPI was recorded in Jaipur at around 78 per cent, whereas the lowest growth was recorded in Greater Chandigarh and Hyderabad at around 40 per cent, over this period. The trends in house prices during Q1:2010-11 to Q3:2014-15, as indicated by All-India RPPI, The house price inflation, as measured by the annual growth rate in RPPI, increased gradually from about 4 per cent in Q1:11-12 to almost 28 per cent in Q3:12-13, however the trend reversed thereafter and it slid below 4 per cent in Q3:2014-15. House price inflation in most of the cities witnessed its peak during the quarters of 2012-13. The y-o-y growth in RPPI at All-India level during Q1:2011-12 to Q3:2014-15 is presented in Chart 1. The house price inflation for small, medium and large houses4 also followed similar path, though no specific pattern was observed in the relative movement of house price inflation in these size-classes. The area-class wise and city-wise distribution of transactions in the last five quarters is given in Table 5 & 6 respectively The year-on-year growth in All-India CPI-Housing Index5 and All-India RPPI were compared to examine relative movement in house price inflation and housing rent inflation. It is observed that during FY: 2012-13, house prices had been growing at a higher rate than that of housing rent. However, in the subsequent quarters, house price inflation and housing rent inflation moved hand-in-hand IV.3. Comparison of RPPI with Gold price and BSE SENSEX6 Gold and Equity provide alternative avenues of savings for households vis-à-vis housing. A comparison of return on these assets is presented in Chart 4. Growth in equity prices, which was in the negative territory during Q2: 2011-12 to Q1: 2012-13, picked up subsequently and moved to positive territory and shot up further in FY: 2014-15; whereas house price growth started to fall by the last quarter of FY: 2012-13 and approached equity prices growth during FY: 2013-14. Though gold prices witnessed higher growth rate in FY: 2011-12, a declining trend in growth was observed in the subsequent year, which further slipped to negative domain during FY: 2013-14. The variability among growth rates of residential property prices, gold and equity reduced comparatively during Q3:2012-13 to Q4:2013-14.

Pic for illustration purpose.

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