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Chapter 3

MORTGAGE FINANCE AND CONSUMER CREDIT:IMPLICATIONS ON FINANCIAL STABILITY

ByRakesh Kumar1

1. Introduction

The housing sector has strong real and financial linkages with constructionactivities and financial services in the economy. At present housing loans workout to 9% of GDP in India which is lower than the levels achieved in the advancedand emerging market economies. Over the years, the rising demand for housingfinance has also provided new business opportunities for the banking sector.Part of the initial increase in mortgage finance was due to unrealised pent updemand of housing stock. A major source of the demand for housing financeemerged from favourable demography, urbanisation and economic development.However, even at the present level, there is still scope for the expansion ofmortgage loans in India.

Mortgage finance provides ample opportunities for development while itmay also sow seeds for future banking and financial crises, as witnessed in anumber of countries over the past decades. Cross-country literature providesstrong evidence of consumer credit boom preceding banking and financial crises.In particular, credit boom is a major driver of house prices and increasedhousehold’s leverage behaviour all over the world. Thus, increasing the financingof the housing industry can have serious implication for the financial sectoragainst the backdrop of unfavourable trends in house prices and adversemacroeconomic scenarios.

________________1. The author is an Assistant Adviser in the Department of Economic and Policy Research,

Reserve Bank of India, Mumbai. The views expressed herein are solely that of the authorand do not represent the stance of the institution to which he belongs. The author isgrateful to Ajay Prakash for his comments and suggestions. In addition, the author isextremely grateful to the anonymous referee(s) from the DEPR, RBI. The feedback fromthe second workshop on Mortgage Finance conducted by SEACEN has certainly enrichedthe contents of this paper.

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The current study reviews the mortgage finance and consumer credit inIndia from the perspective of financial stability. The study assumes more relevancefor India, given the trade-off between the development of housing finance vis-à-vis its implication on financial stability. The overall study is spread into sixsections. Section 2 provides the chronology of the relevant literature done onIndia as well as other cross-country experiences. Section 3 highlights the recenttrends and developments in mortgage finance and consumer credit in India. Inthis context, it also reviews the drivers of mortgage finance in India. Section 4is the quantitative part of the study. It provides an overall assessment of thepotential impact of mortgage finance and consumer credit on financial stabilityusing macro stress testing approach. Section 5 provides some policyrecommendations, building from the empirical assessment done in Section 4.Finally, Section 6 concludes this study.

2. Mortgage Financing: Literature Review

The empirical evidence suggests strong co-movement between the rise inhouse price and credit expansion in an economy. Episodes of credit boom arealso significantly related with the incidences of financial instability in the economy.Irrational expectations of continuous price appreciation in the housing sectoroften strain the balance sheet of banks and households together. The businesscycle movements also play an important role in lending and default behaviourand bring about changes in house prices. Against this backdrop, this sectiondraws evidence from the empirical literature to review the impact of housingcredit boom on financial stability.

2.1 International Literature

The large swings in credit associated with housing market boom hadculminated in banking and financial crises all over the world. Reinhart and Rogoû(2009) show that the six major historical episodes of banking crises in advancedeconomies since the mid-1970s were all associated with housing price bust. Onaverage, a 10% increase in household credit is associated with increase in houseprices of about 6%. However, the severity of financial crisis may not be similaracross countries. The domestic financial market conditions and regulatoryframework have an important role in the manifestation of a financial crisis.

Numerous empirical analyses confirm that rapid mortgage credit growthand strong house price rise moves together. Moreover, the relationship worksboth ways, with house price increases in turn leading to stronger credit growthby boosting both household net worth and expectations of further house price

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increases (IMF, 2011). Jorda, Schularick and Taylor (2011) find that recessionspreceded by greater private sector leverage are associated with worse outcomesin terms of economic growth, investment spending, and credit growth than thoseassociated with less leverage. House price bust has a significant impact onfinancial stability as well. IMF (2011) estimated the GLS regression for 36countries during 2004-09 and found that a 1% lower house price growth isassociated with about a 0.1 percentage point higher non-performing loan (NPL)ratio.

The house price bubble led by mortgage credit can severely impact financialstability on account of a sudden change in the macroeconomic scenario. Thesupply of housing is generally inelastic, while the demand for houses is moresensitive to various factors. As a result, weak demand sentiments play animportant role dragging down house prices. Generally a house price bubble burstsdue to a number of reasons. An unanticipated fall in house price affects thedemand conditions particularly when the households are highly leveraged. Thefirst round of corrections of house prices cause valuation loss in bank’s balancesheet, which significantly constrains banks’ lending capacity, which furthermoderates house price by constraining new buyers, particularly when NPAs arerising (Gerlach, 2012). As a result, the housing and credit boom will reverse inthe same fashion as it developed in the credit boom stage.

Empirical studies have shown that macroprudential reforms can prevent thehouse price bubble from developing into a full blown financial crisis. Lim, et al.(2011) based on the IMF survey data of countries’ experiences found that theloan-to-value (LTV) and loan-to-interest (LTI) limits and dynamic provisioning,among other instruments, may be effective in reducing credit growth. Ahuja andNabar (2011) found that the LTV and LTI limits slow property lending and thatthe LTV limits lower non-performing loans over the longer term.

2.2 Indian Perspective

There is no empirical study that links consumer credit, housing prices andfinancial stability in the case of India. The empirical research on house pricebubble coinciding with credit boom and bust could not be attempted earlier dueto the non-availability of data for measuring house price in India. Furthermore,the mortgage market still remained at lower levels compared to the advancedand East Asian countries.

Some studies have analysed the role of monetary policy and assets pricesin India. Financial stability is one of the objectives of monetary policy in India.

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In this regard, Singh, et al. (2010) has pointed out that monetary policy does notrespond to asset price behaviour in India; rather, asset prices respond to monetarypolicy in India. Some of the studies have used rental data available from consumerprice index for industrial workers (CPI-IW) for assessing housing market (Joshi,2006 and Mahalik, et al., 2008). Nevertheless, the scope of these studies remainedlimited to explaining the determinants of housing prices.

3. Mortgage Finance and Consumer Credit: Developments and Trends

3.1 Housing Finance: Institutional Framework

Housing finance is provided both by private and public sector financialinstitutions in India. These financial institutions can be further classified intobanks and housing finance companies (Figure 1). The Reserve Bank of India(RBI) regulates the banking sector and provides guideline for provisioning andother macroprudential measures to avoid the building up of the concentration ofrisks. The RBI also plays an important role in the development of the housingsector as a major chunk of credit to housing comes from the banking sector.

The National Housing Bank (NHB) is a regulatory authority to the housingfinance companies. The NHB was formed in 1988 under the National HousingBank Act, 1987, and is wholly owned by the RBI. The major objective of theNHB is to promote a sound financial system to cater for all segments of thepopulation and to integrate the housing financial system with the overall financialsystem. The NHB promotes a network of housing finance companies with anobjective of providing affordable housing credit.

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3.2 Development and Trends in Mortgage Finance

The housing industry is one of the fastest growing industries of the economy.During the last decade, a number of factors such as rapid urbanisation, risingmiddle-class population, economic growth and easing of lending rates haveproliferated demand for housing stock as well as housing finance in India. Asa result, mortgage loans as percentage of GDP increased to 9% of GDP in 2012from 2% in 2002. The performance of the last decade looks impressive exceptthe fact that this sharp rising trend can also be attributed to initial high rate ofgrowth stemming from a low level of mortgage finance in early 2000.Nevertheless, the current level of mortgage finance in India is still quite lowcompared with many advanced and emerging economies. This shows thatmortgage finance has scope for further improvement in the future, given thecurrent demand-supply mismatch of housing stocks and in view of the acceleratingeconomic growth and development.

Housing loan as a percentage of total loans increased from the 2000 onwards,well before the high growth phase that the economy witnessed during 2003-04to 2007-08 (an average GDP growth of 8.9%). The demand for housing financelargely moved in tandem with the gradual fall in weighted average lending rate

Figure 1Structure of Housing Finance in India

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(WALR) that began from 2000 onwards, except for occasional rise in 2004(Chart 1). Further, the sharp rise in housing loan could be seen with thecorresponding sharp fall in WALR since 2004 onwards. The fall in WALR couldbe an outcome of a benign macroeconomic environment and global economicconditions. Thus, a priori, it appears that the moderation in WALR could be themajor factor in driving housing finance demand in India.

The WALR and housing loan data from the basic statistical returns areavailable with lag. However, the latest trend of housing loan data may be gatheredfrom the sectoral deployment of banking credit in India for select banks availableat monthly frequency. Based on the monthly data, non-food credit growth showsa strong co-movement with personal loans and housing loans. After the globalfinancial crisis, non-food credit and housing loan grew in tandem with the reboundin GDP growth and improvement in other macroeconomic fundamentals (Chart2).

Chart 1Determinants of Housing Loans in India

Source: RBI and CSO.

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Chart 2Recent Trends in Credit Growth

Source: RBI.

In the post-financial crisis period, housing credit reached the trough in April2012. A combination of domestic and global factors significantly dampeneddemand for housing credit. The weak demand condition and low GDP growthalong with high inflation also adversely impacted the demand for housing credit.Against this backdrop, the growth of housing loan also moderated to around15% in 2013 after witnessing a peak growth of 27% in October 2010.

3.3 Drivers of House Prices and Mortgage Finance in India

Housing is the fundamental need of human beings. During the last decade,the demand for housing emanated from increasing urbanisation, rising economicgrowth, migration and middle-class population. The emergence of second tiercities such as Hyderabad, Navi Mumbai, Pune and NCR region have also boostedthe demand for housing as a consequence of inter-city migrations. Furthermore,the supply-side factors such as financial market reforms and easy availability ofmortgage finance also facilitated the demand for mortgage finance in India (Figure2).

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According to the latest data, the growth of RBI’s House Price indexsuggested a stable price rise even though there has been significant drag inhousing demand. Adverse macroeconomic conditions such as high inflation andlower returns from other avenues of investments (stock market and lower bankdeposit rates) have significantly pushed demand as well as house prices. Thepreference of households towards household physical savings also points towardsthe stable demand for housing in India, even though there is a significant fallin economic activities in the recent years. Since 2008-09, the growth in houseprices remained stable at around 20%, except in few quarters (Chart 3).

Figure 2Drivers of Mortgage Finance

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3.4 Household Savings and Mortgage Finance

The estimates of household leverage and household wealth are difficult tomeasure in India due to the presence of a large unorganised sector. Moreover,the time series data of household debt is also not available for taking policymeasures. In this regard, the data of national income accounts may be used forassessing the household wealth (change in wealth) in physical assets and financialassets. The data of household savings indicates the preference of householdstowards savings in physical assets as against financial assets. The mortgageloans are around 9% of GDP while the household savings remained close to22% of GDP. The households are net savers in the economy and have highsavings even in the slacked economic environment. Furthermore, the householdsavings (surplus funds) may serve as a cushion during the period of financialcrisis and may prevent possibilities of loan defaults. Thus, the household savingscoupled with lower savings portfolio in risky assets such as equities will beuseful in protecting banks’ balance sheet from deteriorating household balancesheet in the event of a financial crisis (Chart 4).

Chart 3Macro Determinants of House Prices in India

Source: RBI House Price Index and MOSPI.

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In sum, mortgage finance in India has a potential to grow from the currentlevel. The initial growth in housing finance was driven by strong growth cycle,urbanisation and easy availability of credit. The growth in housing prices alsocontributed to a rise in mortgage finance, which provided alternative investmentopportunity in the face of lower returns from the financial market instruments.The mortgage finance is given by banks and housing finance companies. Thebanks provide roughly two-thirds of the total mortgage loans, while the share ofhousing finance companies is also increasing due to aggressive marketing. Inthe banking sector, housing loan constitutes more than half of the personal loans.Going forward, the demand for housing finance continues to rise in India mainlydue to demand-side factors.

Section 4 will assess the implications of consumer credit and house priceson the overall financial stability of the economy. In the absence of micro datafor doing stress testing, a broad macroeconomic model will be used for measuringthe potential risks emerging from the current level of mortgage loans to overallbanking sector by using the macro stress testing.

4. Empirical Assessment

4.1 Mortgage Finance and Consumer Credit: Implications for FinancialStability

The household sector is one of the key sectors in the economy and housingloans have a significant impact on the asset liability management of banks. Thedisproportionate rise in housing credit in the retail portfolio of banks can cause

Chart 4Household Savings and Housing Loans in India

Source: RBI and MOSPI.

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systemic risk to banks in the wake of house price bubble bust. The share ofhousing loans and other retail loans have increased in total credit in India, likemany other advanced and emerging market economies. This section attemptsto measure the impact of the rise in mortgage finance and consumer credit onfinancial stability in India. The surplus funds (savings) moves from householdsector through intermediaries, such as bank and financial institutions, to the deficitsectors in the economy. The housing loan portfolios also expose banks to therisks indirectly associated with the household balance sheet from income loss,inflation, adverse exchange rate movements and monetary policy changes(interest rates). The macroeconomic stability is also reflected in asset pricemovements that also indirectly impact both the bank and household balancesheets. The flow chart shows the transmission of mortgage loans risks to financialstability passing through the household’s balance sheet to the non-performingassets of the banks.

4.2 Determinants of Mortgage Loans in India

In order to assess the risk associated with the mortgage finance and consumercredit, this section attempts to measure the determinants of housing loans inIndia. The data is collected from the basic statistical return (BSR) of the scheduledcommercial banks (SCBs) as compiled by the RBI annually. The latest dataavailable for March 2012 is used for empirical analysis along with other relatedmacroeconomic variables. In the absence of long time series data relating tonon-banking sources, the empirical assessment broadly done on BSR data appliesto SCBs.

Figure 3Mortgage Finance and Consumer Credit Linkage with

Financial Stability

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The housing credit demand largely depends on a number of macroeconomicvariables such as income, interest rates, house prices, etc. The house prices,like any other asset, are interest rate sensitive and affect the transmission ofmonetary policy (Mohanty, 2013). The simple correlation analysis suggests thathousing loans as a percentage of total loans is positively related with GDP growthand negatively related with the dependency ratio and interest rates on savingsdeposits, which is also statistically significant. The correlation coefficients havecorrect signs with other macroeconomic variables, such as inflation and lendingrates (WALR). However, they are not statistically significant (Table 1).

Table 1Correlation between Housing Credit and Macroeconomic Variables:

1992 to 2012

HLT= Housing Loan; DR=Dependency Ratio; PE=Price Earnings Ratio of BSESensex;WPI = WPI inflation; WALR=Weighted Average Lending Rates; Y=GDPgrowth; andSRT=Saving Deposit Rate (1-3 years).Figures in parenthesis are p values.

Further, the correlation analysis is supported by the ordinary least square(OLS) regression for 1992 to 2012 (annual data). The time series analysis requiredall the variables to be stationary i.e. I(0), to have a meaningful estimation ofregression coefficients. As a result, all the variables were tested for unit rootproperties using the ADF test. The results show that housing loan as a percentageof total credit and WALR are I(1) in level and I(0) in first difference, while non-agriculture GDP growth is stationary series at levels. Hence, in order to do

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regression analysis, all the I(1) variables were taken at first difference to convertto stationary variable. The regression results show that the weighted averagelending rates and non-agriculture GDP growth are possible determinants of changein housing credit in India (Table 2).

The regression analysis shows that the change in WALR has a negativerelation with housing loans, which is also statistically significant. Among thisspecification, the first specification seems to be the best representative ofdeterminants of housing loans in India. As noted earlier, the change in housingloans is mainly guided by the moderation in WALR, while other determinantssuch as non-agriculture GDP growth have no significant impact on changes inhousing loans in India. The lag dependent variable is also used to overcomepossible endogeneity problem in the OLS estimates. However, the lag dependentvariables are not significant in all the two specifications. The Lagrange multiplier(LM) test also does not provide evidence of serial correlation in all the estimatedequations, even with the second and third lag.

Table 2Determinants of Household Credit (1992-2012)

WALR: Weighted Average Lending rate for housingloan,NAG= non-agriculture GDP growth rate; Dum2004=1for 2004, otherwise 0;**: significant at 5% level; ***: significant at 10%level.Figures in parenthesis are standard errors stats.

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4.3 Impact of Housing Loan on Financial Stability

Financial stability for the banking sector may be viewed in terms of risingnon-performing loans. The non-performing loans can rise due to a number offactors in the economy, such as disproportionate rise in NPAs in particularsegments like housing or retail credit through the direct impact of significantcorrections in house prices, which may impair asset quality. Apart from thedirect impact, there can be significant indirect risks that can arise from adversechanges in other macroeconomic variables. The credit boom during an upturnin the business cycle can significantly raise the leverage, and thereby NPAsduring the downturn movements in the business cycle. Furthermore, the impactof high inflation can also severely impact the changes in household income andsavings decisions. There can be valuation loss in the balance sheet of householdsand banks due to rising inflationary pressures.

Table 3Impact of Housing Loan on Gross NPA to Advances

(1996-97 to 2012)

Housing Loan= Share of housing loan in total credit.Inflation= based on WPI,Output gap= Actual Growth less GDP trend growthmeasured by HP filter method*: significant at 1% level **: significant at 5% level,Figures in parenthesis are standard errors

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In order to test the above mentioned hypothesis, a simple OLS approachis used for the period 1996-97 to 2012-13 (annual data) (Table 3). The empiricalexercise is restricted to this period due to data availability of the gross NPA.Furthermore, the parsimonious approach is followed to somewhat overcome thedegree of freedom due to the small sample size. The first specification showsthat the change in housing loans to total credit has a negative relationship withchange in gross NPAs. This suggests that housing credit may not have significantincidence of gross NPAs as a result despite rising house loan in overall credit,the gross NPAs has come down in the sample period. In the second equation,the output gap and inflation (WPI) have been imputed to assess the impact ofthe macroeconomic variables on gross NPAs. The signs of the coefficients ofWPI and output gap are correct and statistically significant. The WPI inflationcoefficient suggests that inflationary pressures may raise gross NPAs primarilyon account of creating income uncertainty and hurting the real income ofhouseholds. Further, pro-cyclicality as measured by the output gap suggeststhat gross NPAs increases with negative output gap though with one period lag.This suggests that higher lending made during upturn in business cycle resultsin significant pressures on banks’ balance sheet during the economic downturnwith a one period lag. Lastly, it may also be highlighted that the empirical analysishas a major limitation of small sample properties, which makes the estimatessomewhat less robust. The quarterly data could not be used in the empiricalestimation due to non-availability of data in the public domain.

In sum, the empirical findings of this section suggest that the lending rateturns out to be the major driver of housing loans. The removal of financialrepression in the form of reduction in lending rates supports pent-up demand forhousing in India. Further, the negative relationship between the gross NPAs ofbanking sector with the housing credit to total credit could be seen in the lightof progressive reforms in the banking sector such as the implementation of BaselI and II. This resulted in the lowering of gross NPAs along with the rise inhousing credit. Going forward, the mortgage loans are expected to rise in thefuture due to rising income and other social economic factors. The trends ofmortgage loans look appropriate at present given the current level of householdsavings in India. The household savings may provide some cushion againstmortgage loans in the period of financial crisis. However, efforts should becontinued to monitor and control the building up of house price boom and itsimpact on financial stability in India.

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5. Policy Recommendations

The demand for housing and mortgage loans in India is likely to expandfurther from the current level. The demand for housing will arise from thechanging demography, rising income and urbanisation. At present the level ofmortgage loans is not at high levels and does not pose a significant risk to financialstability. Going forward, with rising mortgage penetration, policy measures willbe needed to address and mitigate the risk to household’s balance sheet.

A number of policy measures have been taken by the RBI to promote aswell as prevent the building up of risks in banking loan portfolios. However, atpresent there is a need to develop mortgage finance in India to support thehousing market. In this regard, some of the policy measures are as follows:

5.1 Empirical and Policy Recommendations

1. The empirical finding shows that mortgage loans are interest rate sensitivein India. The weighted average lending rate (WALR) could explain thesignificant variation in the housing loans in India. This may be a usefulpolicy variable to prevent a housing price bubble.

2. The business cycle as measured by output gap and inflation has a significantrole in impacting the non-performing asset ratio. Given this pro-cyclicalityof non-performing assets, measures taken to prevent negative output gapand inflation management also factored in the possible spillover effect ofthese macroeconomic indicators on default ratios. In the past, macroprudentialmeasures taken by the RBI in 2007 have abated the building up of housingbubble and risk to banks’ balance sheet from housing loan portfolios. Thus,counter-cycle prudential measures hold the key to avert the building up offinancial and banking crisis.

3. The RBI and NHB provide index of house prices. However, in the absenceof one consolidated index of house prices, there is some lacuna in measuringthe building up of housing bubble. In this regard, a consolidated andexhaustively measured house price index for country as a whole is requiredfor the policy making framework.

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4. There is a need to have a credible estimate of household debt in India. Inthe absence of data of household debt/wealth, policy measures are oftenformulated based on the borrowing behaviour of households limited to banks.However, the long term policy may require the linking of housing debt andwealth with macroeconomic variables for long term developments.

5. Housing finance companies are playing a greater role in providing mortgagefinance. The regulation and supervision of these housing finance companiesare becoming important. They are regulated by the NHB. High frequencydata (quarterly) of housing finance companies at consolidated level needsto be made available in the public domain for enhancing transparency andmonitoring risk associated with HFCs (Housing Finance Companies).

6. Purchase of housing for investment (third housing loan) may be treateddifferently. The third housing loan should have higher LTVs requirement.

6. Conclusion

The low level of mortgage finance and demand-supply gap in housing stockprovides ample opportunities for the development of the housing market in India.In the post-global financial crisis period, the rising pace in house price andmortgage finance has moderated. The risks to financial stability emerging frommortgage and personal loans are somewhat limited in India due to various factors.Firstly, the share of mortgage and personal loans to GDP as well as to totalcredit of the banking sector are relatively small at about 9% of the GDP inIndia. Secondly, there is no evidence of house price bubbles in the country assuch. Anecdotal evidence suggests that the price pressures have moderated inthe post-crisis period even in cities like Mumbai and Delhi, where the rally inprices was high during the pre-crisis period. Thirdly, the strength of the householdbalance sheet as reflected by household savings provides the cushion to thehousehold sector against any adverse macroeconomic development. This willpossibly lower the chances of the default scenarios and protect the banks’ balancesheet accordingly. During the post-crisis period, the household savings havemoderated largely on account of savings in shares and debentures, while thesavings in deposits and other contractual savings remained somewhat robust.Hence, the strength of the household balance sheet imparts stability to the bank’sbalance sheet against vulnerability from mortgage and personal loans. Fourthly,the demand for housing is likely to remain stable driven by the changing

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demography and urbanisation. As a result, the house price may not crash andthe housing market is likely to remain vibrant. Finally, the macroprudentialmeasures and monetary policy actions in the past have worked well for Indiaagainst the building up of risks from mortgage loan portfolios. The RBI followsthe multiple indicator approach wherein all the macroeconomic variables aretaken into account while formulating monetary policy. Going forward, thisframework is expected to pacify any adverse asset price movements in India.

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