CHAPTER 1 INTRODUCTION 1. 1 Introduction Housing is human basic requirement and the most important and peculiar of commodities. Unlike the most other commodities, it is complex package of goods and services that extends well beyond the shelter provided by dwelling itself. Housing is also primary determinant of personal security autonomy, comfort well being and status, and the ownerships itself structures access to other scarce resources, such as occupational, educational, medical, financial and leisure facilities.
Housing may also be termed as one of the longest life of all durable goods (Muth, 1989) statement taking from previous review done by Wang Leong Seng. Shelter is one of the human basic physiological need (Maslow’s Hierarchy of Needs). In this modern era, shelter comes in a form of house and it is the most important component of the socio-economy sector. This has laid to the formation of many policies and programs aimed at ensuring that all Malaysians, particularly the low-income group, have access to adequate shelter and related facilities To most individuals housing represents the largest single investment item of a lifetime.
This is especially true as family incomes increase and housing viewed less as a basic consumption and more as a key to a secure future. Developing countries have learned that the provision of decent housing for all cannot be left to the play of the market forces alone. Whereas the well-to-do few have no trouble in obtaining comfortable homes, the majority of families in the developing countries go without adequate housing and related facilities. Therefore, the governments found it necessary to intervene in the production of housing for their population.
From economic overview, Malaysia has reached a defining moment in its development path. Vision 2020 is not possible without economic, social and government transformation. Malaysia now moving from middle income to be a higher income economy country. For achieving this, the housing industry in Malaysia is regarded as one of the major industries contributing to the economic and social development of the country. Taking an article from the Real Estate and Housing Developers’ Association (REHDA) of Malaysia, 50% of members expect property prices to rise by up to 20% during the first half of 2010.
Price stability is expected by 30% of respondents, while less than 5% anticipate price falls. Transactions in the first half of 2009 were 30% down on the same period in 2008, according to the Valuation and Property Service Department (JPPH). According to article take from Global Property Guide, Malaysia’s housing market was hit by the global economic slowdown in 2008 and 2009, with political instability and roiling business confidence. Average property prices fell -0. 9% in 2009 when adjusted for inflation. Some developers deferred project launches, while others scaled back. Malaysia’s GDP contracted 3. % in 2009, due to the global recession, after rising 5. 75% annually from 2002 to 2008. Consumption growth slowed sharply. Malaysia’s housing market is expected to recover in 2010, after falling house prices and low sales during 2009. This is due to an expectation of a stronger economy in 2010. Low interest rates, better access to loans, and favourable taxes are also expected to stimulate the housing market and strong growth showed as Malaysia’s GDP in the first quarter 2010, at 10. 1 %. 1. 2 Background of the Study This topic will focus on the effect of interest rate and inflation rate, and real income on housing loan demand.
This topic should be choose because it will give the researcher ideas of relationship between housing loan demand and interest rate, inflation rate and real income. Nowadays housing loan has become one of the important banking products. Most banks in Malaysia has provided housing loan to customer and now they were compete each other to give their customer the best offer and best performance Oliver Hassler (Oct 2003) “Housing Finance In Developing Countries” has found why housing finance is important in developing country like Malaysia.
He found that the benefit consumer will receive from housing finance is they can improve living condition while spreading the cost of major investment. Housing finance will directly help household to build an asset and foster housing supply. He also found that high inflation rate will demolish long term investments such as housing finance. Housing loans approved are assumed to then convert housing demand to housing sales. Housing loans therefore bring housing demand into direct relationship with economy. . Economics variable like interest rate, inflation rate, and real income influence the housing loan demand.
Interest rate plays an important role in market economy. Interest represents the cost of money, what a borrower pays in order to rent money for a certain period of time. Interests rates help determine the allocation of money because, as with other goods in the economy, the demand for money is influenced by its cost. In short, interest rates on loans are critical to borrowers, lenders, and the economy as a whole. The establishment of appropriate interest rates is crucial for the effective operation and financial management of microenterprise finance institutions.
In addition, the interest rate is used as monetary tool, which is imposed on the banking sector through Base Lending Rate (BLR) that controlling by Bank Negara Malaysia (BNM) Interest rate and inflation rate are two economic variables that influence each other. A rise in prices and expectation of worsening of inflation tend to drive up the general level of interest rate, while a slowing of inflation and improvement in the inflationary outlook generally lead to a lower level of interest rate. Real income is the income of an individual or group after taking into consideration the effects of inflation on purchasing power.
A primary factor in housing affordability is household income. The most common approach is to consider the percentage of income that a household is spending on housing costs. The income data include all cash income received by the household head and all relatives living in the housing unit. This includes wages and salaries, self-employment income, as well as interest income, social security, pensions, alimony, and the like. 1. 3 Problem Statement Karimi, Sharifudin and Yusop (March 2009) had mentioned that in 2007 the economy of Malaysia was 29th largest economy in the world and Malaysia had a consistent record of economic growth.
Based on the fast growth economy in Malaysia, demand for housing loan also would increase. However how far this truth able in proves based from housing loan demand. Taking from the speech by Darryl R Francis, President Federal Reserve Bank of St Louis, he said that the high and rising interest rate will cause great impact to demand of loan funds. Lying behind the demand for loan funds has been an excessive total spending and rising inflationary expectations. Level of Income is an important factor. Higher incomes facilitate earlier marriages, and encourage upgrading of housing.
Likewise lower incomes discourage early marriage, and could ultimately cause downgrading of housing. Affordability or the capacity to pay the price, the occupancy costs (including mortgage repayment, or the rent) – is a most important factor in the housing market. The potential demand for housing can be appreciated even more with increasing incomes. Rising incomes also mean growing middle and upper classes group of people with new and higher expectation in the standard of living. As per capita income rises, so does the share of urban real estate assets in national wealth.
This suggests why mortgage finance is so important to the development of housing and national economies. If real estate assets can be effectively used as collateral for household borrowing, households can benefit from both a reduced cost of funds (relative to borrowing on an unsecured basis) and from an improved availability of funds. The study by Burmham Campbell and Nipon Poapongsakorn (1998), which used 1970 census data from Thailand’s Department of Interior, showed that the primary factor influencing housing demand is the number of people in the population.
They concluded that economic factors such as average income and the housing price index do not influence housing demand. Meltzer (1974) shows that while the ratio of mortgage debt to housing rose from 13 to 30 per cent during the period of 1912-1960 in the USA, the ratio of housing to total assets remained at around 25 per cent. Thus, Meltzer (1974) concluded that manipulation of mortgage rates and availability has little effect on housing demand. Tucker (2003) in his study making a distinction between the nominal interest rate and the real interest rate.
When the real interest rate is negative, lenders and savers lose because interest earned does not mean that all the prices of all products in the economy rise during period of time. There are so many theories and study done to show the effects of economics variables like interest rate, inflation rate and real income to housing demand. Most of economist agreed that interest rate would be increase if the expected inflation rates were rise and increase in real income would increase the demand for goods and services.
The effects of interest rate, inflation rate and real income on the housing loan demand have been and continue to be an important topic. Therefore the researcher job is to find out whether there is any relationship exists among the interest rate, inflation rate, real income and the demand of housing loan. This is to give empirical evidence to support statement that “if interest rate and inflation rate is expected to increase therefore the housing loan demand will decrease” and “If real income is increase therefore the housing loan demand also will increase” . 4 Objective of the Study Property investment has traditionally been considered good investment, with property playing an important role in most Asian economies and housing being a form of savings for many households. Changes in property prices influence consumer price inflation, and affect a countries’ competitiveness. The housing market is one of the most volatile sectors of the economy and the behaviour of house prices has attracted many attentions of research. Theoretically, “demand” is a technical economic term.
Changes in demand are affected by price mechanisms and supply in the market. Both demand and supply react against each other to result an equilibrium price in the competitive market. From this aspect of economics, demand cannot be easily captured due to movements in supply and the constraints of the inherent price mechanism. However, in reality, there would be a value of approved loan made to buying houses. Thus, this process can be categorized and counted as a housing demand number. Government can use economic factors as a tool for controlling housing markets.
Housing loans are the main key by which government can control, through housing (home) loan interest rates, the conversion of housing demand units into housing sales. Housing supply and house prices are controlled by market mechanisms. From a social perspective, people should have and expect access to adequate housing and housing security – these are basic needs. From an economic perspective, the advantage of suitable controls linking housing demand and housing supply benefits the related industries. These industries include building supplies, labour, and financial service providers.
Balanced responses to the management of housing supply and housing demand mean long-run efficiency, stability and sustainability in the housing market. This study emphasizes on the effect of interest rate, Inflation rate and real Income on housing loan demand, which specified in 10 years data that span from year 1999 until 2009. The specified objectives as follows: • To determine the relationship between real income and housing loan demand • To determine the relationship between interest rate and housing loan demand • To determine the relationship between inflation rate and housing loan demand . 5 Limitation and Scope of Study 1. 5. 1 Limitation of Study Lack of financial sources The process in finishing this report will consume a large amount of money. These include travelling go to Department of Statistics of Malaysia and Bank Negara Malaysia at Kuala Lumpur for data gathering. The higher the quality, the more expensive it will be. Lack of experience Experience is important. Since this is the first time doing research, researcher has to admit that doing research and working at the same time require a lot of energy, patience, and perseverance besides having knowledge and experience.
Lack of information Certain data which are required for the research were actually private and confidential data. This is regarding all the company’s financial and management information were being kept by public for viewing. Therefore, the information that I received are actually limited. There are plenty of data and information required for the research but only few are being able to access. 1. 5. 2 Scope of Study Housing loans or home loans are the main financial mechanism for buying housing, and housing loan availability has become an important tool for controlling housing demand.
Most house buyers need banking support to finance their purchases. Demand for housing loan in Malaysia boost from a day to day. It will continue to increase as the rate of population in Malaysia increase. This study is focusing commercial banks and Islamic banks in Malaysia. The data collected from BNM will use to determine the relationship between the real incomes and housing the housing loan demand, determine the relationship between the interest rate and housing the housing loan demand and determine the relationship between the inflation rate and housing the housing loan demand.
In order to obtain better analysis, the data from this bank are analyzed in time series of 10 years from 2000 until 2009 on quarterly basis. 1. 6 Significance of Study Real income, interest rate and inflation rate are three economic variables that affect housing loan demand. Banks wide variety of home financing facilities also influence by those economics variables. Consumer could choose to take conventional or the Islamic home financing product since most bank in Malaysia practicing dual banking system. The significant of study are: This study performed to gain knowledge on the housing demand and the variables that related to the housing loan demand in Malaysia. This study also provides the understanding whether the changes in inflation rate, real income and inflation rate will affect the housing loan demand. • The findings from this study will provide additional evidence on the effect of economic variables (i. e. interest rate, inflation rate and real income) on the housing loan demand. • The result from this study could assist the financial institution in their home financing product strategies. . 7 Definition of Terms • Real Income Real is the income of an individual or group after taking into consideration the effects of inflation on purchasing power. For example, if you received a 2% salary rise over the previous year and inflation for the year was 1%, and then your real income only rose 1%. Conversely, if you received a 2% raise in salary and inflation stood at 3%, then your real income would have shrunk 1%. Also known as “real wages”. Ref: http://www. investopedia. com/terms/r/realincome. asp • Inflation Rate
Inflation rate is the rate at which the general level of prices for goods and services is rising, and, subsequently, purchasing power is falling. As inflation rises, every dollar will buy a smaller percentage of a good. For example, if the inflation rate is 2%, then a $1 pack of gum will cost $1. 02 in a year. Ref: http://www. investopedia. com/terms/i/inflation. asp • Interest Rate The amount charged, expressed as a percentage of principal, by a lender to a borrower for the use of assets. Interest rates are typically noted on an annual basis, known as the annual percentage rate (APR).
The assets borrowed could include, cash, consumer goods, large assets, such as a vehicle or building. Interest is essentially a rental, or leasing charge to the borrower, for the asset’s use. In the case of a large asset, like a vehicle or building, the interest rate is sometimes known as the “lease rate”. Ref: http://www. investopedia. com/terms/i/interestrate. asp • Base Lending Rate Base Lending Rate (BLR) is a base interest rate calculated by financial institutions according to a formula which takes into account the institutions cost of funds and other administrative costs.
Base lending rate was set by Bank Negara Malaysia Ref: http://www. realestateagent. com. my/whatisblr. htm CHAPTER 2 LITERATURE REVIEW Literature review is the documentation of comprehensive review of the published and unpublished work from secondary data in the areas of specific interest to the researcher. The purpose of the literature review is to ensure that no important variable that has in the past been found repeatedly to have an impact on the problem is ignored. 2. 1 Housing Prices and Economics Variables
Economics is a discipline concerned with managing and allocating the world’s limited resources to suit the unlimited needs of humans. If there was a perfect match between demand and supply, it would lead to efficient resource allocation, supporting the concept of sustainability. The effects of property market developments on economic activities have received ample attention in recent years. This interest is partly motivated by observations of strong asset prices in the US and other industrialised economies, which many believed had contributed to the robust macroeconomic performance before the sub-prime mortgage crisis.
Debates on the property-economy linkages continue to remain relevant as the crisis unfolds because they offer important lessons for other developing economies. Recent literatures on the impact of property markets on macroeconomic performance include Ho and Wong (2008) who assessed the impact of house prices on domestic private demand in Hong Kong and found that housing market booms significantly increase domestic demand. Economic factors determine affordability: a function that acts as a constraint on housing demand (Liu, Wu et al. 1996). Past review by Pon Vajiranivesa
McQuinn and O’Reilly (2006) find evidence of a significant long run relationship between house prices and the amount an individual can borrow based on disposable income and interest rates. House price can affect aggregate demand and economic activity in various ways. First, more optimistic expectations with regard to the returns on property investment occur with the rising house prices. Market demand in property related sectors increases as builders start new construction. Second, private consumption increases as a result of increased house prices as homeowners feel wealthier.
Third, financial behaviour of homeowners changes as a result of price hike, and homeowners become home purchasers. Taking an empirical study Helbling and Terrones (2003) note that increases in property prices tend to have a positive impact on real GDP in many countries, past review by (Zhu, 2003). The price of housing is also an important factor in housing demand. Housing is considered a normal good, thus, an increase in the price of housing is expected to reduce the demand for it. Borio and Zhu (2008) and Rajan (2005) propose an additional channel through which monetary policy may affect house prices the “risk taking channel”.
According to this theory, low interest rates lead financial intermediaries to take more risk, for example because they target a certain rate of return and need to take more risk to achieve that target when risk-free interest rates are lower. In a separate study, Muellbauer and Murphy (1996) show that demographic changes and interest rates were two important factors causing the UK house price boom of the late 1980s. Housing prices also depend on the interest rate and inflation rate. In a recent paper, Tse (1996b) shows that a declining real rate of interest tends to stimulate house prices and thereby lead to decreases in rent-to-value ratio.
During periods of declining interest rates, house prices are appreciating, making rental housing relatively less expensive (Harris, 1989). It has been argued that rising in inflation rates help to raise home ownership rates because of the tax deductibility Jud and Winkler (2002) conclude that real housing price appreciation is strongly influenced by the growth of population and real changes in income, construction costs and interest rates. The macroeconomic and the housing market are indeed interrelated and co-determined 2. 2 Housing Loan Demand and Interest Rate
Min Hua Zhao, Stephan Whelan (October 2005) “Measuring the Impact of Interest Rate On Housing Demand” the rate of interest is not a direct determinant of either owner occupier or rental investment housing demand. However both are sensitive to movement in the interest rate as it is integral component of debt instrument used to funf the housing purchase. Changes in interest rate will affect to monthly housing repayment and cost of homeownership. Min Hua Zhao found that the most affected by interest rate changes is household income.
If household financial was not strong it will affects the housing loan demand decision. The housing sector is one of the most interest rate sensitive sectors of the economy. Due to the expense; size; and illiquid nature of housing market transactions, there is as heavy reliance by households on debt instruments to finance their purchases. As a result, the rate of interest becomes a critical factor in household’s housing demand decision as it affects both their ability to access adequate housing finance and meet on-going repayments (Lessard and Modigliani, 1975, Feldman, 2002).
The theoretical impact of interest rate on owner-occupier housing demand has been extensively studied in existing research (Lessard and Modigliani, 1975, Kearl and Mishkin, 1977, Titman, 1982, Wheaton, 1985). There is substantial consensus that there should be an overall negative relationship, as a rise in the rate of interest reduces households demand for homeownership through both an increase in the repayment burden and more stringent borrowing requirements.
However, existing empirical evidence are not very robust. At the aggregate level, existing studies have produced mixed results between aggregate homeownership rate and the interest rate in the economy, with many indicating a non-significant effect (Kearl and Mishkin, 1977, Meen, 1998, Painter and Redfearn, 2002, Green, 1996a). Past review by Min Hua Zhao, Stephen Whelan 2005 Both home purchasers and rental investors require adequate housing finance to purchase their desired house.
This is influenced by the rate of interest as housing lenders typically required that loan repayments – calculated on the lending rate – be no more than 30 percent of household income (Bourassa, 1995, Feldman, 2002, Duca and Rosenthal, 1994). Thus, changes in the interest rate affects household’s borrowing capacity through its influence on the maximum housing loan that lenders would agree to. For any given price level, lower interest rates mean lower mortgage repayments which allow borrowers to borrow more at any given repayment-to- income ratio.
This causes an increase in housing demand and housing prices, other things being equal. On the other hand, once interest rates go up, housing demand will ease and price will remain steady or rise moderately or even go down (depending on the collective influences of other factors). Bernanke and Gertler (1995) survey the literature on potential transmission channels between interest rates and housing activity. In a neoclassical world the “user cost of capital” is the only transmission channel. Lower interest rates on bonds decrease the opportunity costs of buying a house and increase the demand for houses.
Past review by Filipa Sa Pascal Towbiny Tomasz Wieladekzx (2010) (J? ager and Voigtl? ander 2007, Demary 2009) said that Increasing interest rates on mortgages increase the cost of financing real estate projects and will thereby have a negative effect on the demand for real estate. The mortgage interest rate is a very important variable that influences the decisions of individuals on whether or not to buy a house. When the mortgage rate increases, people are prevented from buying houses; therefore, the demand for housing decreases.
It has been argued that significant interest rate effects on consumer expenditure are expected through housing wealth, especially in systems characterized by the importance of the collateral role of houses (Muellbauer, 1992; Muellbauer and Murphy, 1997; Maclennan, et al. , 1998). Earlier studies, which analysed the effect of macroeconomic aggregates on the housing sector (i. e. Kearl, 1979; Follain, 1981; Schwab, 1983; Manchester, 1987; Harris, 1989), have not allowed for the fact that these macroeconomic variables are themselves influenced by demand and supply shocks in the housing sector. 2. 3 Housing Loan Demand and Inflation Rate
An increase in housing demand driven by macroeconomics leads to an increase in housing price. House price can be a leading indicator of inflation because supply is more responsive to demand in other goods markets. Increases in housing price also affect workers demand for wages. For these reasons, housing price increases are claimed to provide useful information in predicting inflation. Inflationary expectation can affect the asset demand for housing and hence housing price. It was found that the housing price index is co integrated with inflation (positive sign) and the real interest rate (negative sign). Raymond Y. C. Tse ; 2008) Donald Lessard and Franco Modigliani, (October1975) have studied about the effect of inflation on the housing loan demand. They have found that inflation might affect to the household income and mortgage repayment but does not affect to demand of housing. The inflation rate would have a little impact on the ability of household to possessed owned housing. Inflation have an adverse effect on the demand of houses financed through mortgage because, because the rise of the mortgage rate results in distortion of the time pattern of the real mortgage payments.
Furthermore, it is necessary to consider how inflation will impose a constraint on housing demand. In theory, as expected inflation rises, both the nominal interest rate and the nominal payments also increase, keeping all real values unchanged. However, even if an increase of inflation expectation will bring about higher nominal debt service and nominal income, nominal income will only gradually increase in the future (Alm and Follain, 1984; Kearl, 1979; Schwab, 1982).
For this reason, an inflation-induced increase in interest rates tends to raise the real burden of debt payments, causing a mismatch between the cost of the loan and the ability of the borrower to pay. Follain (1982; 1990) demonstrates that at higher rates of inflation, the households’ liquidity problems tend to dampen housing demand. However, since borrowed debt is leveraged against the inflating value of properties, inflation creates a real growth in housing equity, and therefore allows more borrowing against accumulating housing equity through refinancing.
High inflation and high nominal interest rates backload the repayment of the mortgage principal and increase the real value of repayment in the early part of the repayment period of the loan, thus dampening the demand for housing said (Debelle; 2004) As Tsatsaronis and Zhu (2004) have suggested, inflation can have either a positive or a negative impact on house prices Residential housing is a durable good producing service streams that satisfy the basic human need for shelter while simultaneously serving as a store of purchasing power (Zhu, 2003; Barker, 2005).
With regard to the impact of inflation on the housing sector, different views have been held (Kearl, 1979; Hendershott, 1980; Feldstein, 1992; Poterba, 1992). In particular, Feldstein (1992) indicated that increasing inflation serves to reduce people’s incentive to invest in real estate, which in turn lowers housing demand. On the other hand, Kearl (1979) argued that inflation causes nominal housing payments to rise, which implies a lower housing demand. Demary (2009) explains his findings by the fact that the central bank tightens monetary policy in response to inflationary pressures.
This increases the costs of financing real estate projects, which will result in a declining demand for real estate. Thus, selling prices will decline. 2. 4 Housing Loan Demand and Real Income The relationship between economic factors and housing demand has become more important. Many countries, including Thailand, have a capitalist economic system whereby supply and demand of any good are determined by market forces. In this circumstance, the influence of economic factors, such as household income, housing prices, required repayments on housing loans, and interest rates, play a significant role in determining housing demand (Ellis, 2003)
Income is predicted to be positively related to housing demand. An increase in income leads to an increase in demand for housing. In studies of durable consumer purchases, permanent income has been shown to be the relevant variable in consumers’ housing decision. (Friedman 1957). Past review by Marife M. Ballesteros (2002). A positive relationship exists between household income and housing demand. Fair (1972), Swan (1984) and Goodman (1988) propose that per capita housing demand depends on per capita income and the price of housing services relative to nonhousing prices.
Literature on housing demand convincingly concludes that households make housing decisions based on their permanent income (Mayo, 1981) The degree of desire to bequeath land and house increases as income level increases (Tachibanaki, 1994). This means that as income raises the desire to own a house becomes more and more strong. CHAPTER 3 RESEARCH METHODOLOGY 3. 1 Data Collection and Sample Data collection is key component of research design. Systematic data collection provides valid and reliable data can answers to the research questions in conclusive way.
There are several data collection methods, each with it’s owns advantages and disadvantages. In this chapter the methods how the data gathered and received to develop the hypothesis will discuss. There is secondary data use in this study. In this study, data for dependent variable was collected from BNM about the applied loan of customer who makes housing loan with all the commercial banks. The data for economic variables (i. e. interest rate, inflation rate and real income) were collected from the Economic Planning Unit (EPU) Malaysia, the Department of Statistic Malaysia and Central Bank of Malaysia.
Researcher used data income per capita as a proxy of real income. The data were collected in quarterly basis from year 2000 to 2009. 3. 1. 1 Population Population refers to the entire group of people, events or things of interest that researcher wishes to study. The population for this study is housing loan demand funding and the macroeconomics variables, namely interest rate, inflation rate and real income. 3. 1. 2 Sample A sample is a subset of the population. It comprises some members selected from it.
The samples of this study are the demand of the customer who makes housing loan with commercial banks, interest rate, inflation rate and income. 3. 1. 3 Sources of the Data Data can be obtained from the primary and secondary sources. Primary data refer to information obtained firsthand by the researcher on the variables of interest to the specific purpose of the study. Secondary data refer to the information gathered from sources already existing. For this study researcher will be use secondary data sources. The data were collected from the journals, websites, and reports.
The researcher is going to use published material and computerized database as secondary data as it give some ideas to researcher about key definition, terms and concept of interest rate, inflation rate and income. 3. 1. 4 Procedures on the analysis of data All the data will be analyze by using the Statistical Package for Special Science (SPSS) Software in order to get the actual statistical analysis and result. The procedure saves time as the end output automatically produced by this software. 3. 2 VARIABLE AND MEASUREMENT 3. 2. 1 Dependent Variable Dependent variable is the primary interest to the researcher.
The researcher’s goal is to understand and describe the dependent variable, or to explain its variability, or predict it. The dependent variable for this study is a housing loan demand. To measure the housing loan demand, researcher used the data from Bank Negara Malaysia about the value in Malaysian Ringgit of total applied loan to buying houses from all the commercial banks and Islamic banks in Malaysia in quarterly basis start from year 2000 to 2009. 3. 2. 2 Independent Variable An independent variable is one that influences the dependent variable in either a positive or negative way.
That is when the independent variable is present, the dependent variable is also present, and with each unit of increase in the independent variable, there is an increase or decrease in the dependent variable also. For this study, independent variable that researcher choose is economic variable namely interest rate, interest rate, and real income. • Interest Rate Interest rate is a charged for the use of money from borrower to the lender. The borrower (customer) paid Interest rate charge to the lender (Financial Institution) who lends the money.
Financial institution charged its own interest rate plus the base lending rate that was set by Bank Negara Malaysia. • Inflation Rate Inflation is an increase in general level of price of goods and services in an economy over a period of time. As inflation rises, every dollar will buy a smaller percentage of a good. • Real Income Real is the income of an individual or group after taking into consideration the effects of inflation on purchasing power. Gross National Income Per Capita used as proxy to real income data to provide better results for this study. 3. RESEARCH METHODOLOGY For this study, the data was collected based on demand of customer makes housing loan and for the economic variables (i. e. interest rate, inflation rate, and real income) data were collected from the Economic Planning Unit (EPU) Malaysia, the Department of Statistic Malaysia and Central Bank of Malaysia. The data were collected span is about 10 years. 3. 3. 1 Descriptive Analysis Descriptive analysis is a sensory method which the attributes of a product are identified and quantified, using panellist specially trained for this purpose.
Descriptive analysis is used throughout data analysis in a number of different ways. Simply stated, they refer to means, ranges and numbers of valid cases of one variable. 3. 3. 2 Pearson Correlations Correlation analysis is the study of the relationship between variables. The basic idea of correlation analysis is to report the strength of the association between two variables. If the data is on interval scale, a Pearson’s product correlation is required. In keeping with the theme of the book, only the parametric test Pearson’s Product moment correlation will be presented.
It is also assumed that the scores on the two variables are normally distributed. 3. 3. 3 Multiple Regressions This analysis is done to examine the simultaneous effects of several independent variables on a dependent variable that is interval scaled. This analysis is used to study the relationship between a dependent, Y, or criterion variables and two or more independent, X, or predictor variables. Where: Yi = dependent variable Xi = independent variables a = the Y-intercept, the point of intercept with the Y-axis b1 = is the net change in Yi for each unit change in X1, holding other predictors constant (unchanged) 2 = is the net change in Yi for each unit change in X2i, holding other predictors constant (unchanged) b3 = is the net change in Yi for each unit change in X3i, holding other predictors constant (unchanged) 3. 4 HYPOTHESIS Hypothesis is the testable statement to assume the relationship between two or more variables. By testing the hypothesis and confirming the conjectured relationships, it is expected the solutions can be found to correct the problem encountered. The objectives of the hypothesis are: • To identify whether there are any relationship between real income and housing loan demand. To identify whether there are any relationship between interest rate and housing loan demand. • To identify whether there are any relationship between inflation rate and housing loan demand. The elements of hypothesis are: • Null Hypothesis The null hypothesis is a proposition that states a definitive, exact relationship between two variables. The null statement is expressing as no relationship between two variables or no differences between two groups. • Alternate Hypothesis The alternate statement is expressed as a relationship between two variables or indicating differences between two groups.
Hypothesis Test Hypothesis 1 • Ho: there is no significant relationship between interest rate and housing loan demand • H1: there is significant relationship between interest rate and housing loan demand Hypothesis 2 • Ho: there is no significant relationship between inflation rate and housing loan demand • H1: there is significant relationship between inflation rate and housing loan demand Hypothesis 3 • Ho: there is no significant relationship between real income and housing loan demand • H1: there is significant relationship between real income and housing loan demand 3. 5 Theoretical Framework
Dependent Variable Independent Variables |CHAPTER 4 | | | |FINDINGS AND ANALYSIS | | | |4. 1 DESCRIPTIVE ANALYSIS | |Descriptive statistics are used to describe the basic of the data in a number of different ways.
They provide simple summaries about the | |sample and the measures. | | | |Table 4. 1 Descriptive Statistic. | | | |N |Minimum |Maximum |Mean |Std. Deviation | | |Statistic |Statistic |Statistic |Statistic |Std. Error |Statistic | |loan |40 |$49,980. 50 |$209,619. 00 |$131,134. 6375 |$7,393. 10502 |$46,758. 10167 | |blr |40 |5. 51 |6. 79 |6. 3485 |. 06561 |. 41495 | |Inf |40 |-2. 00 |8. 20 |2. 1100 |. 30994 |1. 96022 | |y |40 |$13,144. 00 |$27,671. 00 |$18,785. 6000 |$680. 49028 |$4,303. 9842 | |Valid N (listwise) |40 | | | | | | | Table 4. 1 shows that from year 2000 until 2009 statistic from 40 data, the minimum housing loan demand for 3 month period is RM 49,980,500. and the maximum of demand is RM 209,619,000. For interest rate, the lowest interest rate from year 2000 until 2009 is 5. 51% and the highest interest rate along that period is 6. 79%. Inflation from year 2000 to 2009 shows that the lowest is about -2% and the highest inflation is 8. 2%. However income data show that the lowest income is RM 13,144. 00 and the highest income along year 2000 to 2009 is RM 27,671. 00 4. Correlation coefficient Table 4. 2 Pearson Correlation. [pic] From the table 4. 2, correlation of housing loan demand which is the dependent variable in this study with independents variables namely interest rate, inflation rate, and income can be determined. The sign of the figure in the correlation table used to explain the relationship of the correlation whether the correlation between these two variables is positive or negative relationship. The interval scale to determine strength of the correlation is from 0 to 0. 5 and 0. 5 to 1. From 0 to 0. 5 the correlation is considered have a weak correlation.
If the figure is 0. 5 the strength of correlation considered have moderate correlation. Lastly if the figure is from 0. 5 to 1 the correlation is strong. The correlation of housing loan demand with interest rate is negative correlation. The magnitude of the correlation between these two variables is -0. 337. This shows that the correlation is negative weak correlation. The correlation of housing loan demand and Inflation rate is positive correlation. The magnitude of this correlation is 0. 272. This means the correlation of these two variables is weak positive correlation.
However the correlation between housing loan demand and income is positive strong correlation. This shows from the correlation table that the figure for the correlation is 0. 939. 4. 3 Multiple Regressions The general purpose of multiple regressions is to learn more about the relationship between dependent variable with several independent variables. Table 4. 3 Model Summary [pic] From the table 4. 3, R of this model shows the figure of 0. 974. This means that the correlation of dependent variable with all of independent variables have strong positive correlation. R-squared is 0. 948.
The R-squared is more than 0. 8. The higher R – Squared, the closer the estimated regression equation fits the sample data. The R-squared shows that 94. 8% of housing loan demand can be explained by interest rate, inflation rate and income, only 5. 2% of the in housing loan demand cannot be explain by these independent variables. Table 4. 4 Coefficient [pic] Estimated equation: Housing Loan demand = 122805. 8 – 28257. 2 X1 – 309. 584 X2 + 10. 028 X3 (4959. 638) (1152. 871) (0. 480) The coefficient table above displays the value of the coefficients in the regression equation.
The coefficient table explained whether the independent variables are significant or insignificant in the changes of dependent variable which is housing loan demand. To determine whether the independent variable is significant or not, the probability of the independent variable must not exceed 0. 05 since significance level used is 5 %. From the table 4. 4 interest rate shows it is significant because its probability value is . 000 and inflation rate is insignificant because its probability value is more than 0. 05. Income as independent value is significant because has . 00 probability. The sign of coefficient value determined the relationship of the independent variables with dependent variable. Positive sign of the coefficient value means the independent variable have direct relationship with dependent variable. Increase in independent variable value cause the dependent value also would increase and otherwise if the independent variable decreases the value of dependent variable followed to decrease. However the negative sign means that dependent variable have indirect relationship with independent variable.
Increase in independent variable value cause the dependent value to decrease and otherwise if the independent variable decreases the value of dependent variable would increase. When interest rate, inflation rate and income are equal to zero, the housing loan demand will be equal to RM 122,805,800. The sign of the interest rate coefficient show the negative sign which means interest rate and housing loan demand has indirect relationship. Increase 1% of interest rate will decrease the housing loan demand by RM 28,257,200. The sign of the inflation coefficient show the negative sign.
This means Inflation and Housing loan demand have indirect relationship. Inflation rate however is not significant in the changes of Housing Loan Demand. The changes in Inflation Rate still give effect to the housing loan but the effect is insignificant to determine the changes of the Housing Loan Demand. The sign of the income coefficient show the positive sign. This means Income and Housing loan demand have direct relationship. Increase 1% in income will increase the housing loan demand by RM 10,280. 4. 4 Hypothesis Hypothesis Test Hypothesis 1 Ho: there is no significant relationship between interest rate and housing loan demand • H1A: there is significant relationship between interest rate and housing loan demand Hypothesis 2 • Ho: there is no significant relationship between inflation rate and housing loan demand • HA: there is significant relationship between inflation rate and housing loan demand Hypothesis 3 • Ho: there is no significant relationship between income and housing loan demand • HA: there is significant relationship between income and housing loan demand Test: When p-value ;lt; 0. 5, rejects Ho A hypothesis is a testable statement of the relationship between two variables. From the findings analysis, the result of hypothesis testing can be known. Hypothesis 1 Researcher will reject Null hypothesis (Ho), and accept Alternate Hypothesis (HA) because the p-value is less than 0. 05. Hypothesis 2 Researcher will accept Null hypothesis (Ho), and reject Alternate Hypothesis (HA) because the p-value is greater than 0. 05. Hypothesis 3 Researcher will reject Null hypothesis (Ho), and accept Alternate Hypothesis (HA) because the p-value is less than 0. 05. 4. 5 FINDINGS
This study provides the investigation of the relationship between housing loan demand and economic variables that are interest rate, inflation rate and income. There is Pearson’s product moment correlation and multiple regressions used to analyze the data for the findings of this study. The data from all variables have been analyzed using quarterly basis from year 2000 to 2009 From the Pearson’s correlation method used, the correlation of housing loan demand with interest rate is negative correlation. The result shows that the relationship of housing loan demand and interest rate is negative weak correlation.
For the relationship between Inflation rate and housing loan demand, the result of the correlation of these two variables is weak positive correlation. However the correlation between housing loan demand and income is positive strong correlation. Another method that had been used is multiple regressions. This method used to determined relationship between dependent variable and independent variables. From the model summary, R of this model shows the figure of 0. 974. This means that the correlation of dependent variable with all of independent variables have strong positive correlation. R-squared is 0. 948. The R-squared is more than 0. . The higher R – Squared, the closer the estimated regression equation fits the sample data. The R-squared shows that 94. 8% of housing loan demand can be explained by interest rate, inflation rate and income, only 5. 2% of the in housing loan demand cannot be explain by these independent variables. By using this method, interest rate describe as significant independent variables where p-value is. 000. The relationship of interest rate and housing loan demand is indirect relationship shown by its negative sign. As interest rate increase it will affect the value of housing loan demand by customer to reduce.
If interest rate falls, the value of housing loan demand will increase. Increase 1% of interest rate will decrease the housing loan demand by RM 28,257,200. Inflation rate however is not significant in the changes of Housing Loan Demand where p-value is 0. 790. The changes in Inflation Rate would give some effect to the housing loan demand but the effect is insignificant to explain the changes of the Housing Loan Demand. This means inflation rate is not important to the changes of housing loan demand value. From this method also shows that income have significant relationship with Housing loan demand where p-value is. 00.. The sign of the income coefficient show the positive sign. This means Income and Housing loan demand have direct relationship. Increase in income will increase the housing loan demand and when incomes for people decrease it also will decrease the housing loan demand. Increase 1% in income will increase the housing loan demand by RM 10,280. Chapter 5 Conclusion and recommendation 5. 1 CONCLUSION This study provides the investigation of the relationship between housing loan demand and economic variables that are interest rate, inflation rate and income.
There is Pearson’s product moment correlation and multiple regressions used to analyze the data for the findings of this study. The data from all variables have been analyzed using quarterly basis from year 2000 to 2009. From the Pearson’s correlation method used, the correlation of housing loan demand with interest rate is negative correlation. The result shows that the relationship of housing loan demand and interest rate is negative weak correlation. The reasons that interest rate have negative low correlation with housing loan is that housing loan have long tenure of payment compare to other loans.
People would have choices to lengthen the period of lending if interest rate is increase for the purpose to minimize the burden of monthly instalment. People have choices to adjust the payback period up to the maximum 35 years. The flexibility of housing loan payback period lowered the strength of relationship between interest rate and housing loan demand value. The changes in interest rate or the base lending rate in Malaysia is not in dramatically moved. Bank Negara Malaysia as the central bank is control the changes of interest rate to ensure Malaysia economy to keep on competitive.
For the relationship between Inflation rate and housing loan demand, the result of the correlation of these two variables is weak positive correlation. The positive sign of the inflation coefficient show the incorrect sign to existing theories. Inflation rate should have indirect relationship with housing loan demand but the expected sign for inflation rate shows a positive sign means inflation rate and housing loan demand have a direct relationship. Inflation rate should have indirect relationship because increase in inflation rate will result increase in housing price and cause increase the cost of housing loan.
But nowadays, people still apply for housing loan although the general price level has increase. As inflation increase and cause the price of consumer goods rise, people that have money from their job still buying a house because nowadays buying a house is necessity for people. However the correlation between housing loan demand and income is positive strong correlation. Income has major influence in explaining the housing loan demand compare to interest rate and inflation rate. This due to the households makes housing decisions based on their income.
This means that as income raises the desire to own a house becomes stronger. As long as people have income from their job, demand for housing loan will increase because people have source of income to pay the loan. Another method that had been used is multiple regressions. This method used to determined relationship between dependent variable and independent variables. From the model summary, R of this model shows the figure of 0. 974. This means that the correlation of dependent variable with all of independent variables have strong positive correlation. R-squared is 0. 948. The R-squared is more than 0. . The higher R – Squared, the closer the estimated regression equation fits the sample data. The R-squared shows that 94. 8% of housing loan demand can be explained by interest rate, inflation rate and income, only 5. 2% of the in housing loan demand cannot be explain by these independent variables. Coefficient table was referring in this method. The coefficient table displays the value of the coefficients in the regression equation. The coefficient table explained whether the independent variables are significant or insignificant in the changes of dependent variable which is housing loan demand.
By using this method, interest rate describe as significant independent variables. The relationship of interest rate and housing loan demand is indirect relationship shown by its negative sign. As interest rate increase it will affect the value of housing loan demand by customer to reduce. If interest rate falls, the value of housing loan demand will increase. Increase 1% of interest rate will decrease the housing loan demand by RM 28,257,200. Inflation rate however is not significant in the changes of Housing Loan Demand. The changes in Inflation Rate would give some effect to the housing oan demand but the effect is insignificant to explain the changes of the Housing Loan Demand. This means inflation rate is not important to the changes of housing loan demand value. From this method also shows that income have significant relationship with Housing loan demand. The sign of the income coefficient show the positive sign. This means Income and Housing loan demand have direct relationship. Increase in income will increase the housing loan demand and when incomes for people decrease it also will decrease the housing loan demand. Increase 1% in income will increase the housing loan demand by RM 10,280.
From all of the analysis result from findings, the conclusion of this study is income and interest rate will give effect to the housing loan demand. The higher the income increase will result the higher increase in housing loan demand. As the rapid growth of Malaysia economy, the income per capita also will increase and makes the housing loan demand increase from time to time. Inflation rate affect the housing loan demand in opposite, where the higher interest rate it will make the lower demand for the housing loan. During 1997 Asian financial crisis which affects Malaysia economy, interest rate has increase up to 12%.
Most banks in Malaysia have strict credit policy that result people hard to make housing loan to buy houses. This situation explains the interest rate as the critical factor in decision on loan by both customer and banks. The inflation rate and housing loan demand is insignificant. This because of inflation rate usually affects the increase in general price of consumer goods. 5. 2 Recommendation This research was done by referring to the earlier study about the same or related topic to get the general idea about the relationship of housing loan demand and economics variable.
Most research paper about relationship on loan demand and economics variable was done by external author which irrelevant for Malaysia context because difference of the economic condition, constraint and policy. Further research on the topics of this study is recommended. This is important especially as Malaysia as developing country to become a developed nation. Home ownership issue in Malaysia can solve when more research is conducted in this topic. The scope in the study will give more information about the relationship of demand for housing and economic variables.
The result can be used by financial institution that offers the housing loan product as useful information in develop their strategies. The future research should add other economics variable that not taken as independent variable in this study like unemployment rate and money supply to make a comparison and better understanding about the topic. In addition, future investigation can also apply by several advance statistical method. ———————– Yi = a + b1X1i + b2X2i + b3X3i+E Real Income Interest Rate Housing Loan Demand Inflation Rate