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This section presents both theoretical and empirical survey of the literature on the determinants of mortgage rates.

CHAPTER TWO 2.0 LITERATURE REVIEW

Over recent years, the Central bank of Kenya has carried out annual survey on the issues related to growth of resident mortgage. The findings have shown that mortgage rates are the main impediment to growth of this sector. Indeed the recent annual survey (Central Bank 2013) singled out mortgage rates as the main factor holding up uptake of mortgage in Kenya. This section presents both theoretical and empirical survey of the literature on the determinants of mortgage rates.

2:1 THEORETICAL LITERATURE According to Mandura (2009 pp 228) mortgage, can be defined as a type of a debt fashioned to back investment in real estate. The debt is protected by property; it therefore, follows that if the borrower fails to pay the property can be seized. Jacobus (2009 pp101) argues that mortgage is an instrument that makes property security for repayment of a debt. Mortgage therefore, is not conveyance of the property since it does not operate to transfer title from the borrower to the lender. It only pledges the property as security for the due payment of the debt, thus creating an encumbrance on the property.

2.1.1 DETERMINANTS AND COMPONENTS OF MORTGAGE INTEREST RATES

Mortgage rates differ from time to time and with regions. This section will examine the reasons why mortgage rates vary by studying its components which include: risk premium, liquidity premium, banks required margin and secondly, an analysis on factors influencing mortgage interest rates.

2.1.1.1 Risk premium

This constitutes the risk premium lenders want in their expected return. Roberts (2008 pp10) observes that investors have the information on how much they will earn from the treasury notes, however, they are uncertain on how much they will earn from fixed mortgage loan. Due to this, they will require an additional compensation, that is, the risk premium. Risk can be looked at from two perspectives; risk on realized ex post returns and risk on ex ante returns. The realized risk may either be more or less than expected; therefore, risk averse investors will demand a premium on ex ante returns. Investors are more concerned with the ex post return uncertainty since it cannot be diversified away (Geltner et.al 2007pp 477). The risk premium depends on the business cycle and when the economy is declining, risk premium increases but declines when the economy is growing. Forgang and Einolf (2007 pp95) notes that the difference between high risk debt instrument and lower risk one is considered as the economic pointer, so that if the variation between the two is decreasing the investors will expecting a strengthening economy. Lenders of FRMS are exposed to interest rate risk because these mortgages are financed from short term deposits. They rely on short term deposits to avail long term mortgages loans. Incase interest rates raise in due course; the financial institutions will incur an increased cost of obtaining funds, consequently, reducing their profits margin. On the other hand, borrowers will not benefit from reducing interest rates; however, they will not be affected by increasing rate.

Under ARMS, interest rate risk is shifted from the lenders to borrowers, since the rate keep fluctuating depending on the state of the economy. Mandura (2009 pp 243) argues that in FRMs the required rate depends on the current risk free rate and risk premium rate. In case, the risk free rate increases, investors will increase their required rate of return and consequently, mortgage prices increases.

2.1.1.2 Tax Rate and Lenders’ required margin

The tax on interest earned by lending institutions affects the mortgage rates. In Kenya interest incurred by borrowers in repayment of mortgage loan (owner occupied) is an allowable expense up to sh. 150, 000 per annum while mortgage institutions pay a corporate tax of 30 per cent. (Mukherjee 2005) It is the interaction of demand and supply factors that dictate interest rates. Events that affect income will cause a shift in the demand curve for loanable funds. If borrowers expect a decrease in future tax rates, they will increase their demand for loable funds, thus, the demand curve will shift outwards. According to a joint study by World Bank and IMF (2005) Kenyans interest rates spread are very close to those of the Sub Saharan countries but considerably higher than those of OECD countries. Then operating costs and profit margins were identified main determinants of interest rates spread. The overhead costs include: wages, security and inefficient payment system. In case a financial institution is not efficient enough it is likely to incur more operating costs that are passed on borrowers increasing the interest rates further. Lenders are likely to be more efficient in a competitive market than when there are just a few them. This is because they strive to streamline their system and reduce operation cost with a view of lowering their interest rates.

2.1.1.3 Liquidity premium

Liquidity of debt instrument refers to the easiness of converting them into cash without loss of value. Liquid money is preferable as opposed to other assets with a higher rate of return because it can used for transactions Investors require compensation by way of a premium for engaging their money in non liquid assets. Reilly and Brown (2011, p.652) Postulates that investors add increasing liquidity premiums to existing rates to arrive at the actual rates. Enrhard and Brigham (2010 pp 216) observes that the liquidity premium on mortgage backed securities in 2008 and 2009 in United States were much high because of the few transactions occasioned by financial crisis. Liquidity premiums depend on the lenders liquidity and the level of securitization in the economy.

2.1.2.1 Mortgage Rates and inflation-The Fisher Hypothesis

This theory asserts that there is one-for-one relationship between inflation and interest rates (Thomas 2005, pp 105).According to Domar (2012 pp. 516). Actual interest rate changes as inflation changes. Inflation erodes lenders purchasing power; since they are rational economic agents they will require reimbursement for the loss.

(1)

Where represents the nominal interest rate, r is the real interest rate and β is the extent to which nominal interest rate change as expected inflation change. In case the real interest rates are constant over time, β=1. Real interest rate is the disparity between the nominal interest rate and expected inflation (Domar, 2012 pp.402).

QUOTE Fisher Identity (2)

Pozdena (1988 pp27), observes that when lenders advance a loan they form some expectations about the probable rate of inflation. If they expect an inflation rate of 8 per cent per annum, they will incorporate 8 percent to the yearly interest rates. Therefore, an increase in inflation expectation will cause long term interest rates including mortgage rates to increase.

2.1.2.2 Central Bank Rate

It is the role of the central bank to control inflation. One of the instruments it uses to achieve this is the bank rate. Taylor (2006, pp.640) argues that when the inflation rises the central bank response by raising the nominal rate and as a consequence the real interest rates rises. Consequently, exports, consumption and investment reduce. The converse is true. Asso, et.al (2010) observes that the Taylor rule can be used to set the Central bank rate subject to some conditions and can be expressed by the following equation:

QUOTE (1)

Where,

r = central bank

y= deviation of GDP from the trend

p= inflation over previous four quarters with a target of 2%

The GDP is growing on its trend at about 2% per annum so that y=0

The ex post interest rate will also equal 2

2.1.2.3 Kenya Banks’ Reference Rate (KBRR)

KBRR is new reference rate set by the Central bank and replaces the base lending rate upon which banks were using to cost their loans. The reference rate is computed based on the base lending rate which now stands at 8.5 per cent and two months moving average of 91- day Treasury bill rate. The Monetary Policy Committee set the reference rate 9.13 per cent and is effective July 8th 2014. Following this move the total cost of credit will be KBRR plus premium ‘K’ that is,

(2)

K represents the premium rate and will depend on: banks required margin, cost of funds, risk and other third party cost such as insurance and government levies.

2.1.2.3 Bond Prices and Mortgage interest Rate

Killin and Derespins (2012 pp 42) observes that there is an inverse relationship between mortgage rates and bond prices; that is, when the prices of the bond increases, the mortgage rates decreases. The opposite is true. The reason behind this argument is that bond prices are unchanging at maturity. If we suppose that the value of the bond at maturity is sh.1, 000 and the present price of bond is sh. 900 and there are 5 years remaining, if the interest rates are escalating the prices of the bond will shift downwards.

2.1.2.4 Demand and Supply for Loans.

Following Keynes, Mankiw (2007 pp 749) argues that interest rates adjust to balance demand and supply for money. The adjustments in the interest charge can be explained by the demand and supply perception (Rockwell 2006 pp 260). If there is high demand for mortgage loans the interest rate will increase. On the other hand, low demand for mortgage rates is followed by low interest rates. Killin and Derespins (2012 pp 41) argues that while mortgage rates move with other interest rates, real rates depends with the supply and demand for mortgage loans. The supply of mortgage is determined by the willingness of the financial institutions to invest in the real estate. Moreover, lenders depend on supply of money which is determined by factors such as the amount of customer deposit and the prevailing interest rates in the market. The demand side depends on the income levels and the general economic conditions. Interest rates and money supply in view of short term liquidity effect are negatively correlated. In particular, an increase in money supply given an existing price level and income creates a surplus supply of money Demand for money is a function of nominal interest rates since interest rate is the opportunity of holding cash. Croushore (2007 pp 280) argues rise in the supply of money must cause interest rates to decrease so to sustain the money market in balance. In case the money supply is increasing that is, a rightward shift in the money supply curve without a corresponding shift in money demand curve the equilibrium interest rates declines. Similarly, if a shift in money supply is followed by a shift in money supply in the short run, the interest will not change. This implies that a monetary policy is ineffective in lowering the mortgage interest rates. On the other hand, the short run equilibrium interest rates may increase than before if an increase in supply for money is followed by an increase in demand for loans. An expansionary monetary policy may not bring interest rates down hence ineffective. Secondly, interest rates and money supply through real output and the price effect in the long run. Even in this case, expansionary policy may not be effective if the increase in money supply the resulting increase in real output and rising prices causes increase in demand since interest rates will also increase.

2:2 EMPIRICAL LITERATURE REVIEW

Sirmans and Smith (2012) did a study on the relationship between mortgage rates and Treasury bill rate. They found that there was a strong relationship between mortgage rate and capital market rate and especially the 10-year treasury rate. The method of examination was regression and the 30-year mortgage rate, 10-year treasury rate data was obtained from the Federal Reserve. When 30-year mortgage rate was regressed against 10-year treasury rate, there was an r- squared of 0.969. A 30-year mortgage rate was also regressed against Swap rate and corporate bond rate. Notably, the Swap rate was found to have a strong relationship (r-squared of 0.985) and with 30-year mortgage rate than 10-year treasury rate because there is a default risk premium not explained by treasury rate. These results were confirmed by recent studies done by Nampewo (2013). Using time series data from Uganda between 1995 and 2010 and applying Engel and Granger two step model he tested for cointegration between bank rate, treasury rate, exchange rate volatilities and share of nonperforming loans to the entire credit sector. The findings showed that interest rate spread was positively related with bank rate, treasury rate and level of nonperforming loans. Toolesman, Jan and Jacobs (2007) studied the proposition that prices are rigid downwards application to mortgage rates. In particular, the suggestion that mortgage rate follow an increase in capital market rate rather than decrease. A 10-year capital market rate running between 1978 and 2000 for Netherlands was used. It was found that during the period of downward movement in interest rates, the gap between the mortgage and the capital market rate was widening. They concluded that switching cost and tacit price coordination are the likely causes of mortgage rate asymmetric response to capital market rate.

Siddiqui (2012) found that banks that are highly liquid have lower interest rate spread. This is because they do not incur cost of sourcing funds externally. The results were confirmed by Millan (2008) where determinants of mortgage rates in the Euro area countries with emphasis on cost of funds, nature of guarantee and customer-banker relationship were investigated. Harmonized monthly interest rates for fifteen countries running between 2003 and 2009 were used. A 10-year benchmark interest rate on government bonds expressed in a monthly average was used as astand in for average cost funding in the financial market. In addition to that, the cost of interbank funding was represented by 3 month Euribor rate expressed in monthly average. From the study it was found that there was a strong positive relationship (0.43) between mortgage rates and cost of funds.

Mallik and Bhar (2010) using data from UK, Sweden and Finland and OLS as method of estimation concluded that the Central Bank increased interest rate when expected inflation increases. In related studies Ikhide (2009), Folowelwol and Tennant (2008) using a panel data model studied the determinants of interest rates spread in Sub Saharan Africa using dynamic panel data model. They singled out inflation and money supply as the key factors. On the contrary, Khediri et al (2005) did not find any significant relationship between inflation between inflation and interest margins. The findings were similar to recent study by Were and Wambua (2013) who concluded that inflation and real GDP statistically insignificant in explaining interest rates differences among banks. Using EGARCH M model, Wilson (2006) found that increased inflation uncertainity negatively affects interest rates and lowered economic growth in Japan. Mishkin (2005) using a monthly data between 1983 and 2003 found that inflation and interest rates are correlated in some periods and not in others. The findings confirmed Fisher-effect in the long run but not in the short run. In the short run when there a change in the expected inflation, it is followed by a change in the short term interest rates. In the long run inflation and interest rates, trend together, that is, the long run Fisher effect. Similar studies on relationship between prices and interest rates confirmed that inflation uncertainity affects the economy by increasing long term interest rates. More specifically, interest rise when inflation rises and falls when there is a greater economic risk. However, recent studies have shown that the monetary authority can control inflation uncercainity and as a result control inflation by adopting credible inflation targeting strategy (Mallik and Bhar 2010).

Bank particular factors have been argued to be some of the determinants of interest rates in the banking sector. Using Panel data, Were and Wambua (2013) found a positive relationship between interest rates charged by banks and credit risk, liquidity risk and net income as a ratio of total income and operating costs. The prevailing credit risk is reflected by risk premium charged by banks. Empirical evidence show that banks shift risks premium is associated with non performing loans to borrowers. Ngugi (2001) and Beck et.al (2010) utilizing Kenyan data, acknowledged risk premiums as a key determinants of interest rates spread. Risk is a situation in which alternative outcome exist with known probability. These findings confirmed past studies by Darrel et al (2008) which found out that when mortgage interest rates are adjusted for risk premium and statutory price ceilings, regional differentials disappeared. Casey et al (2009) observed that mortgage rates are linked to other interest rate. Moreover, maturity risks and default risks should capture those relationships. The more chances of default the higher the risk premiums which reflect the uncertainty of complete payment of mortgage principle and interest. The possible cost of default can be lowered by mortgage firms by taking an insurance cover.

Fazel (2006) studied the effect of expansionary monetary policy on mortgage rates in the US. Contrary to expectations, the study concluded that expansionary monetary policy geared towards inducing investment in housing will not lead to reduced mortgage rates. The analysis utilized multiple linear regression model and data covering the duration between 1990 and 2004 of mortgage and money supply (both M1 and M2). Consumer expectation was used as one of the independent variable based on their sentiments capture the general state of the economy. Remarkably, the results showed that changes in the money supply have no impact on mortgage. Nevertheless, in related studies by Casel (2005) it was found that supply of new houses influences mortgage rates.

2:3 OVERVIEW OF LITERATURE REVIEWFrom the studied literature, it is evident that most of the studies done covered Europe and United states. Most of studies in the region concentrated on factors determining demand for mortgage. This study will help bridge the gap by utilizing local data. It also appears that the main causes of mortgage rate is the levels of inflation, cost of deposit and the opportunity cost of money reflected by the bond rate. Other factors include bond prices, demand and supply and household income. Most of the studies concentrated on determining elasticities and variables were expressed in logarithms.

The study by Milan (2008) attempted to look at non macroeconomic (social-economic variables), for instance, efficiency of the civil justice arrangement. It was observed that there was a positive correlation between mortgage backed securities and the cost of justice. In countries where the cost of justice was prohibitive the financial institutions resulted to securitization, this allowed them to transfer the non performing loans. For this reason fixed mortgage rates are relatively expensive since financial institutions incorporated such cost in case the borrower defaulted.

The reviewed literature also shows that very little interest has been given to the effect of supply of loan to mortgage rates. This is probably because the number of mortgage firms have remained also the over a period of time. Similarly, very little attention has been given to the relationship between the demand for mortgage loans and mortgage rates. However, some studies have used the GDP per capita as a proxy for household income. This proxy can be used to measure demand, since (ceteris peribus) it will increase with increase in income.

A few studies have considered the effect of government policy on mortgage rates. However, the studies were limited to monetary policy in respect to central bank rate. Other government policy related factors such as tax that has been considered by theory as relevant have not been given attention.

Notably, some studies have considered other component of mortgage related costs and the causes of interest rates differentials among regions. These cost include; cost of originating the loan, risk premium and cost of default. The interregional mortgage differential was said to be caused by the risk premium which may differ from one region to another.

CHAPTER THREE

METHODOLOGYThis chapter will consist of three parts: development of the theoretical framework, discussion on the nature of data to be used and the empirical model specification.

3.1 THEORITIACAL FRAMEWORK

The framework is based on consumer behavior. Varian (1992, pp 112) hypothesizes that the consumer being rational will chose the best bundle given a set of affordable alternatives. In a preference maximization problem, the consumer is faced by a budget constraint. The budget constraint and the set of bundles can be represented by:

(1)

In a preference maximization case:

Max

Such that (2)

X as in X

The consumer is assumed to maximize utility on consumption of housing. The cost of financing is interest paid.

U=u (,) (3)

Where,

is the price for housing mortgage rate.

is the price of other goods that is, opportunity cost.

The price or cost for housing is assumed to be determined through the market and all consumers choose interest rate that maximizes their utility subject to constraints. A consumer can either purchase a house using his income or invest in alternative products. The consumer’s decision to pay a given cost for a mortgage will depend on other product (opportunity cost) disposable income and inflation. Inflation is considered by consumer because it reduces the purchasing power.

Hence,

U=u (Px, P Y, π) (4)

Since utility can be measured indirectly through the costs (the amount the consumer is willing to pay)

Y) (5)

(6)

Where, rb, rt, is the opportunity cost. In this regard the economic agent that is, the lender or the borrower can either invest in bonds or buy or sell mortgage security.

The interaction of financial forces in the economy can be illustrated as:

(7)

The equation on the right hand side indicates the indirect utility while the one on the right hand side is for direct utility. The consumer will maximize utility given the price of good x and other goods that is y, subject to his disposable income Y.

3.2 EMPIRICAL MODEL

The multiple linear regression model will be used. This method of analysis is has dominated the literature and will take the following form.

+ (8)

Where,

= variable interest rate.

A constant

are parameters.

= central bank rate

= bond rate

π = the inflation

y = the GD per capita

= the error term

The model will be estimated by natural logarithms so that the parameters can be interpreted in terms of elasticities. The transformation also ensures the errors are normally distributed and that the OLS yields the best linear unbiased estimators.

+ (9)

3:3 DATAThe study will use quarterly data for the period 2003 to 2013. The income measure GDP, Central bank lending rate and inflation data will be collected the Kenya National Bureau of Statistics (KNBS). The study will utilize the real GDP per capita measure as opposed to the nominal measure. The dependent variable will be variable interest rate only and will be collected from five main institutions for mortgage finance that according to Central Bank Survey (2013) represent 70% of the mortgage market. The choice of variable interest rate is informed by central bank residential mortgage survey which showed that 97.4% of mortgage loans in Kenya are on variable interest rate (Central Bank annual Supervision Report 2013).

The choice of the above variables is based purely on empirical and theoretical grounds. Bank rate represents the rate at which the central bank lends to the commercial bank. This variable has been used in the literature as a proxy for the cost of funds by the mortgage finance institutions. The GDP per capita on quarterly basis is the income measure. GDP has been used in the literature as an indicator of a country’s macroeconomic conditions. In this study, the variable has been used as a proxy for household income. The bank rate is the rate at which the Central Bank lends to the commercial bank. This variable is used an indicator of cost of funds to the financial institutions. The bond rate is the rate of ten-year bonds. This represents the opportunity cost of funds incurred by lending institution. This based on premise that the economic agents can either invest in mortgage or long term securities such as bonds. The fourth variable is the inflation. It is a measure of general increase in prices. This variable is important since lenders being rational, would require compensation for the loss in purchasing power.

3.4 ECONOMETRIC APPROACH

The following OLS equation will be estimated:

+ (10)

The dependent variable (mortgage rates) will be regressed against the following independent variables, inflation (CPI), central bank rate, treasury rate and real income. The regressed will make use of logs of the data variables. To obtain real income GDP will be divided with CPI

(11)

The key assumption for the multiple regression model can be stated in terms of conditional expectations.

E (u/…) (12)

The above assumption requires that all the factors in unobserved error term be uncorrelated with the explanatory variables. It enables us to account for the functional relationships between the explained and unexplained variables.

It also the homoskedasticity assumption, that the variance of the unobservable error term is constant.

Var(u/…)= (13)

In case the assumption fails the OLS will be ineffective, this problem will be corrected by heteroskedasticity-robust procedures.

We also assume that autocorrelation does not exist in the error term

E ( ) =0 i≠ j (14)

In case this assumption fails, the problem will be corrected with the use of lagged values.

References

1. Asso P. George A. Khann and Lesson, R. (2010). ‘The Taylor Rule and The Practice of Central Banking. Research Working Paper, Federal Reserve Bank of Kansas City

2. Beck, T and Hesse, H. (2006) Banks efficiency, ownership and market structure: Why interest spreads are so high in Uganda? World Bank Policy Research Working Paper 4027, October.

3. Ben-Khedri, H.B, Casa and F.Sheik Rahim(2005) Profitability and interest raes differentials in Tunisia Banking. University of Wales, Working Paper.

4. Fazel Shoofel (2006). How effective is the monetary policy? A journal of Humanomics vol.22 iss.31 pp 139-144

5. Linda, A. Toolesman and Jacobs (2007), ‘Why prices rise faster than they fall? With an application to mortgage rates’, Journal of Managerial and Decision Economics Vol. 28 No. 7 pp

6. Ling, T. Chenji, Hu and Michael, Casey (2009) Prediction of variability in mortgage rates: International computing solution. Journal of Risk and Finance. Vol.10 No.2 pp 142-154

7. Kandil, M (2005) ‘Money, interest and prices: some international evidence’. Journal of Economics and Finance Vol. 14 pp 129-470

8. Maureen Were and Joseph Wambua (2013) Assessing the Interest rates spread of banks in Kenya: An Empirical Investigation. Kenya Bankers Association: Center for Research on Finance Markets and Policy. Working Paper Series

9. Milan, C (2010) ‘Determinants of Mortgage Rates; Empirical Analysis of Euro Area Countries’ Working Paper No.2 ABI Economic Research Department.

10. Mishkin, F. S (2005) “Is the Fisher Effect for real? A re-examination of the relationship between inflation and interest rates.’’ Journal of monetary Economics vol. 6 No.4 pp 195-215

11. Nampewo, D. (2013), What Drives Interest Rates Spread in Uganda’s Banking Sector? International Journal of Economics and Finance Vol.1 pp 76-85

12. Wilson, B.K (2006) ‘The Link between Inflation Uncertainity and Output Growth: New time series evidence from Japan.’ Journal of Macroeconomics Vol 28 pp 609

13. David R (2012), Advanced Macroeconomics. 4th Edition. The McGraw−Hill Companies, New York.

14. Darrel Croushore (2007) Money and Banking: A Policy Oriented Approach.2nd Edition. Houghton Milflin, Boston.

15. Gujarati (2004), Basic Econometrics (4th edition) The McGraw−Hill Companies, West Point Military Academy

16. Jacobus C (2006), Real Estate Principles (11th Edition). MasonOhio,Thomson South Western

17. Killin, D and Derespinis, D (2012) National Residential Mortgage Loan Originator, 2nd Edition, Cengage Learning; Ohio

18. Liberman, M and Hall, R (2013 pp 111) ‘Economics: Principles & Applications’ 6th Edition. Mason, Oh; Australia.

19. Mandura, J (2009), Financial Institutions and Markets, 9th Edition. South Western, Canada

20. Mankiw G (2007) Macroeconomics, 2nd Edition. Worth Publishers: New York.

21. Pozdena R J (1988). ‘The Modern Economics of Housing: A Guide To Theory and Policy For Finance and Real Estate’, (Revised Edition) Green Publishing Group, New York.

22. Redhead, K (2008) Personal Finance and Investments: A Behavioral Finance Perspective (Revised Edition), Routledge, London.

23. Sampat Mukherjee (2005), Modern Economic Theory, Revised 4th New Age International

24. Smith, S. and Sirmans and Simarns (2011) ‘Determinants of Mortgage Rates’ Department of Finance, University of Florida. <

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CHAPTER TWO 2.0 LITERATURE REVIEW

Over recent years, the Central bank of Kenya has carried out annual survey on the issues related to growth of resident mortgage. The findings have shown that mortgage rates are the main impediment to growth of this sector. Indeed the recent annual survey (Central Bank 2013) singled out mortgage rates as the main factor holding up uptake of mortgage in Kenya. This section presents both theoretical and empirical survey of the literature on the determinants of mortgage rates.

2:1 THEORETICAL LITERATURE According to Mandura (2009 pp 228) mortgage, can be defined as a type of a debt fashioned to back investment in real estate. The debt is protected by property; it therefore, follows that if the borrower fails to pay the property can be seized. Jacobus (2009 pp101) argues that mortgage is an instrument that makes property security for repayment of a debt. Mortgage therefore, is not conveyance of the property since it does not operate to transfer title from the borrower to the lender. It only pledges the property as security for the due payment of the debt, thus creating an encumbrance on the property.

2.1.1 DETERMINANTS AND COMPONENTS OF MORTGAGE INTEREST RATES

Mortgage rates differ from time to time and with regions. This section will examine the reasons why mortgage rates vary by studying its components which include: risk premium, liquidity premium, banks required margin and secondly, an analysis on factors influencing mortgage interest rates.

2.1.1.1 Risk premium

This constitutes the risk premium lenders want in their expected return. Roberts (2008 pp10) observes that investors have the information on how much they will earn from the treasury notes, however, they are uncertain on how much they will earn from fixed mortgage loan. Due to this, they will require an additional compensation, that is, the risk premium. Risk can be looked at from two perspectives; risk on realized ex post returns and risk on ex ante returns. The realized risk may either be more or less than expected; therefore, risk averse investors will demand a premium on ex ante returns. Investors are more concerned with the ex post return uncertainty since it cannot be diversified away (Geltner et.al 2007pp 477). The risk premium depends on the business cycle and when the economy is declining, risk premium increases but declines when the economy is growing. Forgang and Einolf (2007 pp95) notes that the difference between high risk debt instrument and lower risk one is considered as the economic pointer, so that if the variation between the two is decreasing the investors will expecting a strengthening economy. Lenders of FRMS are exposed to interest rate risk because these mortgages are financed from short term deposits. They rely on short term deposits to avail long term mortgages loans. Incase interest rates raise in due course; the financial institutions will incur an increased cost of obtaining funds, consequently, reducing their profits margin. On the other hand, borrowers will not benefit from reducing interest rates; however, they will not be affected by increasing rate.

Under ARMS, interest rate risk is shifted from the lenders to borrowers, since the rate keep fluctuating depending on the state of the economy. Mandura (2009 pp 243) argues that in FRMs the required rate depends on the current risk free rate and risk premium rate. In case, the risk free rate increases, investors will increase their required rate of return and consequently, mortgage prices increases.

2.1.1.2 Tax Rate and Lenders’ required margin

The tax on interest earned by lending institutions affects the mortgage rates. In Kenya interest incurred by borrowers in repayment of mortgage loan (owner occupied) is an allowable expense up to sh. 150, 000 per annum while mortgage institutions pay a corporate tax of 30 per cent. (Mukherjee 2005) It is the interaction of demand and supply factors that dictate interest rates. Events that affect income will cause a shift in the demand curve for loanable funds. If borrowers expect a decrease in future tax rates, they will increase their demand for loable funds, thus, the demand curve will shift outwards. According to a joint study by World Bank and IMF (2005) Kenyans interest rates spread are very close to those of the Sub Saharan countries but considerably higher than those of OECD countries. Then operating costs and profit margins were identified main determinants of interest rates spread. The overhead costs include: wages, security and inefficient payment system. In case a financial institution is not efficient enough it is likely to incur more operating costs that are passed on borrowers increasing the interest rates further. Lenders are likely to be more efficient in a competitive market than when there are just a few them. This is because they strive to streamline their system and reduce operation cost with a view of lowering their interest rates.

2.1.1.3 Liquidity premium

Liquidity of debt instrument refers to the easiness of converting them into cash without loss of value. Liquid money is preferable as opposed to other assets with a higher rate of return because it can used for transactions Investors require compensation by way of a premium for engaging their money in non liquid assets. Reilly and Brown (2011, p.652) Postulates that investors add increasing liquidity premiums to existing rates to arrive at the actual rates. Enrhard and Brigham (2010 pp 216) observes that the liquidity premium on mortgage backed securities in 2008 and 2009 in United States were much high because of the few transactions occasioned by financial crisis. Liquidity premiums depend on the lenders liquidity and the level of securitization in the economy.

2.1.2.1 Mortgage Rates and inflation-The Fisher Hypothesis

This theory asserts that there is one-for-one relationship between inflation and interest rates (Thomas 2005, pp 105).According to Domar (2012 pp. 516). Actual interest rate changes as inflation changes. Inflation erodes lenders purchasing power; since they are rational economic agents they will require reimbursement for the loss.

(1)

Where represents the nominal interest rate, r is the real interest rate and β is the extent to which nominal interest rate change as expected inflation change. In case the real interest rates are constant over time, β=1. Real interest rate is the disparity between the nominal interest rate and expected inflation (Domar, 2012 pp.402).

QUOTE Fisher Identity (2)

Pozdena (1988 pp27), observes that when lenders advance a loan they form some expectations about the probable rate of inflation. If they expect an inflation rate of 8 per cent per annum, they will incorporate 8 percent to the yearly interest rates. Therefore, an increase in inflation expectation will cause long term interest rates including mortgage rates to increase.

2.1.2.2 Central Bank Rate

It is the role of the central bank to control inflation. One of the instruments it uses to achieve this is the bank rate. Taylor (2006, pp.640) argues that when the inflation rises the central bank response by raising the nominal rate and as a consequence the real interest rates rises. Consequently, exports, consumption and investment reduce. The converse is true. Asso, et.al (2010) observes that the Taylor rule can be used to set the Central bank rate subject to some conditions and can be expressed by the following equation:

QUOTE (1)

Where,

r = central bank

y= deviation of GDP from the trend

p= inflation over previous four quarters with a target of 2%

The GDP is growing on its trend at about 2% per annum so that y=0

The ex post interest rate will also equal 2

2.1.2.3 Kenya Banks’ Reference Rate (KBRR)

KBRR is new reference rate set by the Central bank and replaces the base lending rate upon which banks were using to cost their loans. The reference rate is computed based on the base lending rate which now stands at 8.5 per cent and two months moving average of 91- day Treasury bill rate. The Monetary Policy Committee set the reference rate 9.13 per cent and is effective July 8th 2014. Following this move the total cost of credit will be KBRR plus premium ‘K’ that is,

(2)

K represents the premium rate and will depend on: banks required margin, cost of funds, risk and other third party cost such as insurance and government levies.

2.1.2.3 Bond Prices and Mortgage interest Rate

Killin and Derespins (2012 pp 42) observes that there is an inverse relationship between mortgage rates and bond prices; that is, when the prices of the bond increases, the mortgage rates decreases. The opposite is true. The reason behind this argument is that bond prices are unchanging at maturity. If we suppose that the value of the bond at maturity is sh.1, 000 and the present price of bond is sh. 900 and there are 5 years remaining, if the interest rates are escalating the prices of the bond will shift downwards.

2.1.2.4 Demand and Supply for Loans.

Following Keynes, Mankiw (2007 pp 749) argues that interest rates adjust to balance demand and supply for money. The adjustments in the interest charge can be explained by the demand and supply perception (Rockwell 2006 pp 260). If there is high demand for mortgage loans the interest rate will increase. On the other hand, low demand for mortgage rates is followed by low interest rates. Killin and Derespins (2012 pp 41) argues that while mortgage rates move with other interest rates, real rates depends with the supply and demand for mortgage loans. The supply of mortgage is determined by the willingness of the financial institutions to invest in the real estate. Moreover, lenders depend on supply of money which is determined by factors such as the amount of customer deposit and the prevailing interest rates in the market. The demand side depends on the income levels and the general economic conditions. Interest rates and money supply in view of short term liquidity effect are negatively correlated. In particular, an increase in money supply given an existing price level and income creates a surplus supply of money Demand for money is a function of nominal interest rates since interest rate is the opportunity of holding cash. Croushore (2007 pp 280) argues rise in the supply of money must cause interest rates to decrease so to sustain the money market in balance. In case the money supply is increasing that is, a rightward shift in the money supply curve without a corresponding shift in money demand curve the equilibrium interest rates declines. Similarly, if a shift in money supply is followed by a shift in money supply in the short run, the interest will not change. This implies that a monetary policy is ineffective in lowering the mortgage interest rates. On the other hand, the short run equilibrium interest rates may increase than before if an increase in supply for money is followed by an increase in demand for loans. An expansionary monetary policy may not bring interest rates down hence ineffective. Secondly, interest rates and money supply through real output and the price effect in the long run. Even in this case, expansionary policy may not be effective if the increase in money supply the resulting increase in real output and rising prices causes increase in demand since interest rates will also increase.

2:2 EMPIRICAL LITERATURE REVIEW

Sirmans and Smith (2012) did a study on the relationship between mortgage rates and Treasury bill rate. They found that there was a strong relationship between mortgage rate and capital market rate and especially the 10-year treasury rate. The method of examination was regression and the 30-year mortgage rate, 10-year treasury rate data was obtained from the Federal Reserve. When 30-year mortgage rate was regressed against 10-year treasury rate, there was an r- squared of 0.969. A 30-year mortgage rate was also regressed against Swap rate and corporate bond rate. Notably, the Swap rate was found to have a strong relationship (r-squared of 0.985) and with 30-year mortgage rate than 10-year treasury rate because there is a default risk premium not explained by treasury rate. These results were confirmed by recent studies done by Nampewo (2013). Using time series data from Uganda between 1995 and 2010 and applying Engel and Granger two step model he tested for cointegration between bank rate, treasury rate, exchange rate volatilities and share of nonperforming loans to the entire credit sector. The findings showed that interest rate spread was positively related with bank rate, treasury rate and level of nonperforming loans. Toolesman, Jan and Jacobs (2007) studied the proposition that prices are rigid downwards application to mortgage rates. In particular, the suggestion that mortgage rate follow an increase in capital market rate rather than decrease. A 10-year capital market rate running between 1978 and 2000 for Netherlands was used. It was found that during the period of downward movement in interest rates, the gap between the mortgage and the capital market rate was widening. They concluded that switching cost and tacit price coordination are the likely causes of mortgage rate asymmetric response to capital market rate.

Siddiqui (2012) found that banks that are highly liquid have lower interest rate spread. This is because they do not incur cost of sourcing funds externally. The results were confirmed by Millan (2008) where determinants of mortgage rates in the Euro area countries with emphasis on cost of funds, nature of guarantee and customer-banker relationship were investigated. Harmonized monthly interest rates for fifteen countries running between 2003 and 2009 were used. A 10-year benchmark interest rate on government bonds expressed in a monthly average was used as astand in for average cost funding in the financial market. In addition to that, the cost of interbank funding was represented by 3 month Euribor rate expressed in monthly average. From the study it was found that there was a strong positive relationship (0.43) between mortgage rates and cost of funds.

Mallik and Bhar (2010) using data from UK, Sweden and Finland and OLS as method of estimation concluded that the Central Bank increased interest rate when expected inflation increases. In related studies Ikhide (2009), Folowelwol and Tennant (2008) using a panel data model studied the determinants of interest rates spread in Sub Saharan Africa using dynamic panel data model. They singled out inflation and money supply as the key factors. On the contrary, Khediri et al (2005) did not find any significant relationship between inflation between inflation and interest margins. The findings were similar to recent study by Were and Wambua (2013) who concluded that inflation and real GDP statistically insignificant in explaining interest rates differences among banks. Using EGARCH M model, Wilson (2006) found that increased inflation uncertainity negatively affects interest rates and lowered economic growth in Japan. Mishkin (2005) using a monthly data between 1983 and 2003 found that inflation and interest rates are correlated in some periods and not in others. The findings confirmed Fisher-effect in the long run but not in the short run. In the short run when there a change in the expected inflation, it is followed by a change in the short term interest rates. In the long run inflation and interest rates, trend together, that is, the long run Fisher effect. Similar studies on relationship between prices and interest rates confirmed that inflation uncertainity affects the economy by increasing long term interest rates. More specifically, interest rise when inflation rises and falls when there is a greater economic risk. However, recent studies have shown that the monetary authority can control inflation uncercainity and as a result control inflation by adopting credible inflation targeting strategy (Mallik and Bhar 2010).

Bank particular factors have been argued to be some of the determinants of interest rates in the banking sector. Using Panel data, Were and Wambua (2013) found a positive relationship between interest rates charged by banks and credit risk, liquidity risk and net income as a ratio of total income and operating costs. The prevailing credit risk is reflected by risk premium charged by banks. Empirical evidence show that banks shift risks premium is associated with non performing loans to borrowers. Ngugi (2001) and Beck et.al (2010) utilizing Kenyan data, acknowledged risk premiums as a key determinants of interest rates spread. Risk is a situation in which alternative outcome exist with known probability. These findings confirmed past studies by Darrel et al (2008) which found out that when mortgage interest rates are adjusted for risk premium and statutory price ceilings, regional differentials disappeared. Casey et al (2009) observed that mortgage rates are linked to other interest rate. Moreover, maturity risks and default risks should capture those relationships. The more chances of default the higher the risk premiums which reflect the uncertainty of complete payment of mortgage principle and interest. The possible cost of default can be lowered by mortgage firms by taking an insurance cover.

Fazel (2006) studied the effect of expansionary monetary policy on mortgage rates in the US. Contrary to expectations, the study concluded that expansionary monetary policy geared towards inducing investment in housing will not lead to reduced mortgage rates. The analysis utilized multiple linear regression model and data covering the duration between 1990 and 2004 of mortgage and money supply (both M1 and M2). Consumer expectation was used as one of the independent variable based on their sentiments capture the general state of the economy. Remarkably, the results showed that changes in the money supply have no impact on mortgage. Nevertheless, in related studies by Casel (2005) it was found that supply of new houses influences mortgage rates.

2:3 OVERVIEW OF LITERATURE REVIEWFrom the studied literature, it is evident that most of the studies done covered Europe and United states. Most of studies in the region concentrated on factors determining demand for mortgage. This study will help bridge the gap by utilizing local data. It also appears that the main causes of mortgage rate is the levels of inflation, cost of deposit and the opportunity cost of money reflected by the bond rate. Other factors include bond prices, demand and supply and household income. Most of the studies concentrated on determining elasticities and variables were expressed in logarithms.

The study by Milan (2008) attempted to look at non macroeconomic (social-economic variables), for instance, efficiency of the civil justice arrangement. It was observed that there was a positive correlation between mortgage backed securities and the cost of justice. In countries where the cost of justice was prohibitive the financial institutions resulted to securitization, this allowed them to transfer the non performing loans. For this reason fixed mortgage rates are relatively expensive since financial institutions incorporated such cost in case the borrower defaulted.

The reviewed literature also shows that very little interest has been given to the effect of supply of loan to mortgage rates. This is probably because the number of mortgage firms have remained also the over a period of time. Similarly, very little attention has been given to the relationship between the demand for mortgage loans and mortgage rates. However, some studies have used the GDP per capita as a proxy for household income. This proxy can be used to measure demand, since (ceteris peribus) it will increase with increase in income.

A few studies have considered the effect of government policy on mortgage rates. However, the studies were limited to monetary policy in respect to central bank rate. Other government policy related factors such as tax that has been considered by theory as relevant have not been given attention.

Notably, some studies have considered other component of mortgage related costs and the causes of interest rates differentials among regions. These cost include; cost of originating the loan, risk premium and cost of default. The interregional mortgage differential was said to be caused by the risk premium which may differ from one region to another.

CHAPTER THREE

METHODOLOGYThis chapter will consist of three parts: development of the theoretical framework, discussion on the nature of data to be used and the empirical model specification.

3.1 THEORITIACAL FRAMEWORK

The framework is based on consumer behavior. Varian (1992, pp 112) hypothesizes that the consumer being rational will chose the best bundle given a set of affordable alternatives. In a preference maximization problem, the consumer is faced by a budget constraint. The budget constraint and the set of bundles can be represented by:

(1)

In a preference maximization case:

Max

Such that (2)

X as in X

The consumer is assumed to maximize utility on consumption of housing. The cost of financing is interest paid.

U=u (,) (3)

Where,

is the price for housing mortgage rate.

is the price of other goods that is, opportunity cost.

The price or cost for housing is assumed to be determined through the market and all consumers choose interest rate that maximizes their utility subject to constraints. A consumer can either purchase a house using his income or invest in alternative products. The consumer’s decision to pay a given cost for a mortgage will depend on other product (opportunity cost) disposable income and inflation. Inflation is considered by consumer because it reduces the purchasing power.

Hence,

U=u (Px, P Y, π) (4)

Since utility can be measured indirectly through the costs (the amount the consumer is willing to pay)

Y) (5)

(6)

Where, rb, rt, is the opportunity cost. In this regard the economic agent that is, the lender or the borrower can either invest in bonds or buy or sell mortgage security.

The interaction of financial forces in the economy can be illustrated as:

(7)

The equation on the right hand side indicates the indirect utility while the one on the right hand side is for direct utility. The consumer will maximize utility given the price of good x and other goods that is y, subject to his disposable income Y.

3.2 EMPIRICAL MODEL

The multiple linear regression model will be used. This method of analysis is has dominated the literature and will take the following form.

+ (8)

Where,

= variable interest rate.

A constant

are parameters.

= central bank rate

= bond rate

π = the inflation

y = the GD per capita

= the error term

The model will be estimated by natural logarithms so that the parameters can be interpreted in terms of elasticities. The transformation also ensures the errors are normally distributed and that the OLS yields the best linear unbiased estimators.

+ (9)

3:3 DATAThe study will use quarterly data for the period 2003 to 2013. The income measure GDP, Central bank lending rate and inflation data will be collected the Kenya National Bureau of Statistics (KNBS). The study will utilize the real GDP per capita measure as opposed to the nominal measure. The dependent variable will be variable interest rate only and will be collected from five main institutions for mortgage finance that according to Central Bank Survey (2013) represent 70% of the mortgage market. The choice of variable interest rate is informed by central bank residential mortgage survey which showed that 97.4% of mortgage loans in Kenya are on variable interest rate (Central Bank annual Supervision Report 2013).

The choice of the above variables is based purely on empirical and theoretical grounds. Bank rate represents the rate at which the central bank lends to the commercial bank. This variable has been used in the literature as a proxy for the cost of funds by the mortgage finance institutions. The GDP per capita on quarterly basis is the income measure. GDP has been used in the literature as an indicator of a country’s macroeconomic conditions. In this study, the variable has been used as a proxy for household income. The bank rate is the rate at which the Central Bank lends to the commercial bank. This variable is used an indicator of cost of funds to the financial institutions. The bond rate is the rate of ten-year bonds. This represents the opportunity cost of funds incurred by lending institution. This based on premise that the economic agents can either invest in mortgage or long term securities such as bonds. The fourth variable is the inflation. It is a measure of general increase in prices. This variable is important since lenders being rational, would require compensation for the loss in purchasing power.

3.4 ECONOMETRIC APPROACH

The following OLS equation will be estimated:

+ (10)

The dependent variable (mortgage rates) will be regressed against the following independent variables, inflation (CPI), central bank rate, treasury rate and real income. The regressed will make use of logs of the data variables. To obtain real income GDP will be divided with CPI

(11)

The key assumption for the multiple regression model can be stated in terms of conditional expectations.

E (u/…) (12)

The above assumption requires that all the factors in unobserved error term be uncorrelated with the explanatory variables. It enables us to account for the functional relationships between the explained and unexplained variables.

It also the homoskedasticity assumption, that the variance of the unobservable error term is constant.

Var(u/…)= (13)

In case the assumption fails the OLS will be ineffective, this problem will be corrected by heteroskedasticity-robust procedures.

We also assume that autocorrelation does not exist in the error term

E ( ) =0 i≠ j (14)

In case this assumption fails, the problem will be corrected with the use of lagged values.

References

1. Asso P. George A. Khann and Lesson, R. (2010). ‘The Taylor Rule and The Practice of Central Banking. Research Working Paper, Federal Reserve Bank of Kansas City

2. Beck, T and Hesse, H. (2006) Banks efficiency, ownership and market structure: Why interest spreads are so high in Uganda? World Bank Policy Research Working Paper 4027, October.

3. Ben-Khedri, H.B, Casa and F.Sheik Rahim(2005) Profitability and interest raes differentials in Tunisia Banking. University of Wales, Working Paper.

4. Fazel Shoofel (2006). How effective is the monetary policy? A journal of Humanomics vol.22 iss.31 pp 139-144

5. Linda, A. Toolesman and Jacobs (2007), ‘Why prices rise faster than they fall? With an application to mortgage rates’, Journal of Managerial and Decision Economics Vol. 28 No. 7 pp

6. Ling, T. Chenji, Hu and Michael, Casey (2009) Prediction of variability in mortgage rates: International computing solution. Journal of Risk and Finance. Vol.10 No.2 pp 142-154

7. Kandil, M (2005) ‘Money, interest and prices: some international evidence’. Journal of Economics and Finance Vol. 14 pp 129-470

8. Maureen Were and Joseph Wambua (2013) Assessing the Interest rates spread of banks in Kenya: An Empirical Investigation. Kenya Bankers Association: Center for Research on Finance Markets and Policy. Working Paper Series

9. Milan, C (2010) ‘Determinants of Mortgage Rates; Empirical Analysis of Euro Area Countries’ Working Paper No.2 ABI Economic Research Department.

10. Mishkin, F. S (2005) “Is the Fisher Effect for real? A re-examination of the relationship between inflation and interest rates.’’ Journal of monetary Economics vol. 6 No.4 pp 195-215

11. Nampewo, D. (2013), What Drives Interest Rates Spread in Uganda’s Banking Sector? International Journal of Economics and Finance Vol.1 pp 76-85

12. Wilson, B.K (2006) ‘The Link between Inflation Uncertainity and Output Growth: New time series evidence from Japan.’ Journal of Macroeconomics Vol 28 pp 609

13. David R (2012), Advanced Macroeconomics. 4th Edition. The McGraw−Hill Companies, New York.

14. Darrel Croushore (2007) Money and Banking: A Policy Oriented Approach.2nd Edition. Houghton Milflin, Boston.

15. Gujarati (2004), Basic Econometrics (4th edition) The McGraw−Hill Companies, West Point Military Academy

16. Jacobus C (2006), Real Estate Principles (11th Edition). MasonOhio,Thomson South Western

17. Killin, D and Derespinis, D (2012) National Residential Mortgage Loan Originator, 2nd Edition, Cengage Learning; Ohio

18. Liberman, M and Hall, R (2013 pp 111) ‘Economics: Principles & Applications’ 6th Edition. Mason, Oh; Australia.

19. Mandura, J (2009), Financial Institutions and Markets, 9th Edition. South Western, Canada

20. Mankiw G (2007) Macroeconomics, 2nd Edition. Worth Publishers: New York.

21. Pozdena R J (1988). ‘The Modern Economics of Housing: A Guide To Theory and Policy For Finance and Real Estate’, (Revised Edition) Green Publishing Group, New York.

22. Redhead, K (2008) Personal Finance and Investments: A Behavioral Finance Perspective (Revised Edition), Routledge, London.

23. Sampat Mukherjee (2005), Modern Economic Theory, Revised 4th New Age International

24. Smith, S. and Sirmans and Simarns (2011) ‘Determinants of Mortgage Rates’ Department of Finance, University of Florida. <

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