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Housing credit access model: The case for Lithuania
European Journal of Operational Research 155 (2004) 335–352 www.elsevier.com/locate/dsw
Housing credit access model: The case for Lithuania E.K. Zavadskas, A. Kaklauskas *, A. Banaitis, N. Kvederyte Department of Building Technology and Management, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-2040 Vilnius, Lithuania
Abstract The research described in this paper aimed at achieving two major goals. First, to identify and describe rational credit access development in advanced industrial economies as well as providing recommendations for Lithuania. The multiple criteria quantitative and conceptual analysis of rational credit access in developed countries and in Lithuania allowed for the identification of areas where the Lithuania situation is comparable, partly comparable or quite different from levels attained by advanced industrial economies. The data of this quantitative and conceptual analysis was used to identify rational credit access development trends in Western Europe and the USA as well as providing some recommendations for Lithuania. The determination and realization of efficient housing credit access in Lithuania would create better conditions for the functioning of the housing system. Second, the paper contains a description of a suggested method in choosing efficient housing investment instruments and lenders. The quantitative and conceptual databases that are being developed at present, give an exhaustive description of housing investment instruments and allow for their multiple criteria analysis. This helps to determine efficient investment instruments for the countries in question. The databases and multiple criteria analysis offered could also be used in searching for efficient lenders. The methods suggested in this paper can also be applied to solving similar problems in other countries. 2003 Elsevier B.V. All rights reserved. Keywords: Rational credit access; Housing investment instruments; Multiple criteria analysis; Model
1. Introduction When considering the number of flats per 1000 people, Lithuania lags behind other European countries. At present, i.e. 2001, there are 375 apartments per 1000 people in Lithuania and most of these construction facilities were built before 1990 and very often are in need of renovation. On *
Corresponding author. E-mail address: [email protected] (A. Kaklauskas).
average, only 1.16 new flats per one thousand inhabitants are built in Lithuania each year and this is one of the lowest indices in Europe. Today, more and more flats are being built using credit that is extended by commercial banks. Recently however, the situation has become somewhat better. In 2001, about LTL 50 million (US $12.5 million) was set aside for statutory housing loans on easy terms. The State provides a 6% deduction on the interest for housing loans during the first half of the repayment period and subsidizes up to 20% of the borrowed amount. If
0377-2217/$ - see front matter 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0377-2217(03)00091-2
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the loan is insured with the enterprise ‘‘Building Loan Insurance’’ a loan can be obtained by making a down payment of 5% on the propertyÕs value. In the case of an uninsured loan, a down payment of 30% of the propertyÕs value must be paid. Presently in Lithuania, housing credit terms and the terms for the issuance of State guarantees for such loans are more favorable than in most East and Central European countries. Currently, the enterprise ‘‘Building Loan Insurance’’ is the only company in Eastern Europe offering housing loan insurance services. Since the insurance of loans reduces risks associated with housing loans, on the establishment of the enterprise ‘‘Building Loan Insurance’’ as a result, the competition between banks providing housing loans has increased. Consequently, loans are provided at a lower interest than would be available in the case of uninsured housing loans. Housing loans for the sale of flats has increased considerably also due to better credit facilities. Even flats in basements and other less appealing parts of buildings have been sold because loans have increased the demand. State guarantees are very important for the market and due to the system of these guarantees housing loans have become available to wider groups of people and risks to creditors and investment bankers have decreased somewhat. The loan system has also promoted the growth of businesses and the economy on the whole. The Japanese PHRD Fund has provided Lithuania with a US $0.5 million guarantee for the preparation of a new housing strategy. On drawing up the Lithuanian housing strategy a request for a loan will be necessary for its implementation. The housing strategy will indicate whether social housing, renovations and/or support for young families and retired persons should to be made top priority or not. Having already restructured the system of the Immovable Property Cadastre and the Register, a hypothetical infrastructure has been set up in Lithuania. Therefore, commercial banks have started offering more housing mortgage loans because of the restructuring. The efficiency of the housing policy depends not so much on the support from the State and
international organizations as on the private financial sector as well as its initiative and ability to extend credit services. At the present time, housing credit terms and terms for the issuance of State guarantees for such loans in Lithuania are more favorable than in most Eastern European countries. However, judging by the experiences of other countries, various alternative crediting instruments that would assist further development of the Lithuanian housing credit market, could still be proposed. Such alternatives could include loans to residents on easy terms, the establishment of state institutions which would provide respective guarantees to banks, subsidies provided directly to residents and state guarantees that are given to certain groups of loans, etc. Several alternative ways of the StateÔs participation in the housing financing market are being currently discussed in Lithuania. Examples of this are, the average personÕs income tax concession to receiving a housing loan, subsidies to saving programs, full compensation of a loanÕs insurance premiums, compensation of interest paid on loans taken by homeowners and various associations related to this aspect, etc. Due to the ever-changing micro- and macrolevels of the environmental conditions, the efficiency of alternatives under consideration will vary. Therefore, in the future new crediting instruments that are better adapted to the new micro- and macro-levels of the environmental conditions might be necessary. Each of these alternatives has both advantages and disadvantages. The implementation of some of these crediting instruments would cause serious problems due to the absence of the necessary legal basis or a population at the lower level income bracket and other factors. The level of maintenance of the existing housing, especially apartment buildings, as well as their renovation is also a cause for concern. The Government continues to implement its project for Housing Renovation and Energy Saving in Housing, which started in 1996 by using a World Bank loan. Presently negotiations with the World Bank for a new loan will be carried out. The objective of this paper is to identify and describe rational credit access development in ad-
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vanced industrial economies as well as provide recommendations for Lithuania. The paper contains a description of a suggested method in choosing efficient housing investment instruments and lenders. The paper is structured as follows. Following this introduction, Section 2 outlines housing finance systems in advanced economies. In Section 3 we describe the main stages of forming a Lithuanian housing credit access development model. The development of a rational conceptual Lithuanian model for housing credit access is introduced in Section 4. The determination of rational housing investment instruments and lenders is presented in Section 5. In Section 6 we describe a case study and present the proposed multiple criteria analysis method. Finally, some concluding remarks are provided in Section 7.
2. Housing finance systems used in advanced economies The housing finance systems differ greatly from country to country. As Renaud [12] stated, there are profound differences among the 180 developed and developing countries that are now members of the World Bank. The advanced housing finance systems can be found in OECD countries. Renaud [12] shows that, these systems grew out of two main traditions: Anglo-Saxon systems where the building societies of the UK and the savings and loans from the US are mutual forms of housing finance. There is also the mortgage bank tradition of continental Europe where term funding was mobilized through bond markets. Also, there is wide and increasing literature on the choice of housing investment instruments. This mainly concerns the econometric estimation of the demand for fixed rate mortgages compared with adjustable rate mortgages. There is also a considerable amount of empirical work on the mortgage choice between the conventional annuity mortgage and payment via savings in a diversified portfolio of assets. Leece [8] reviewed recent developments in the design and innovation of mortgage instruments in the UK, from the early to mid-1990s. Rasmussen
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et al. [11] present a more expansive view of reverse mortgages as a financial tool for tapping housing equity for various purposes and at various stages in the life cycle. Dyk [4] examines the mechanisms used since the 1970s to finance social housing in Canada. He demonstrates that direct government assistance has proven to be the most cost-effective mechanism. Experimentation with alternative mortgage instruments such as the graduated-payment mortgage and the indexlinked mortgage has also been central in the attempt to minimize subsidy and financing costs. Dhillon et al. [3] evaluate the choice between 15and 30-year fixed rate contracts in the USA and estimate a simple profit to represent this choice. Lam et al. [7] developed a model for financial decision-making which provides a method of solving borrowing decision problems. Leece [9] estimates reduced form credit demand equations that reflect the interactions between the choice of mortgage instrument, the lessening of mortgage rationing and liquidity constraints and the demand for a housing debt. Most of these studies have concentrated on the single objective of decision making.
3. Main stages of forming Lithuanian housing credit access development model This researchÕs aim was to produce a model, consisting of conceptual and quantitative parts for rational housing credit access in Lithuania by undertaking a complex analysis of credit institutions and instruments affecting the institutions. Also recommendations on the increase of its efficiency have been made. The research was performed by studying the expertise of advanced industrial economies and by adapting it to Lithuania. A simulation was undertaken to provide insight into the creating of effective housing credit access. Fig. 1 indicates diagrammatically the credit institutions and instruments that may impinge on the efficiency of housing credit access. To be efficient, housing credit access must operate within certain boundaries imposed by the credit institutions and instruments. It was recognized that in
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Fig. 1. Credit institutions and instruments that influence the efficiency of the housing credit access.
each country the system of credit, institutions and instruments are different and so Fig. 1 varies accordingly. To increase the efficiency of housing credit access in the country under consideration, it is necessary to utilize knowledge and experiences concerning lending practices. This may be achieved by analyzing experiences and knowledge of advanced industrial economies and applying them to Lithuania. The Lithuanian government may introduce mortgage insurance in order to promote credit for housing. Therefore, the boundary of efficiency will be extended to include this new development. The second mortgage being added to the boundary will change once again in the future (Fig. 2 illustrates a revised level of efficiency as an example of which alterations should be taken into account).
Fig. 3 graphically illustrates interrelationships between credit institutions, instruments and housing credit access. The area inside the ellipse represents the positive effect of credit institutions and instruments on the efficiency of housing credit access. The area outside the ellipse shows the negative effect on the efficiency of housing credit access. The overlapping areas of credit institutions and instruments show where better conditions for housing credit access have been created. Optimum housing credit access is obtained when all ellipse areas are overlapping (i.e. second mortgage, sweat equity, etc.). The greater the common overlapping area, the greater the efficiency level of the housing credit access. Having investigated the effects of the variables affecting housing credit access in advanced industrial economies, some differences have been identified between these countries and
Fig. 2. Fluctuations of efficient boundaries for access to housing credit.
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Fig. 3. Determination of optimal, rational and negative housing credit access.
Lithuania. On the basis of these differences, the main implications for Lithuania can be identified. Studying only one advanced industrial economy could lead to any inferences that will be purely subjective. By studying a number of countries any bias is diminished. The presence of specific variable credit institutions and instruments immediately imposes objective limitations on the efficient activities of interested parties such as debtors and lenders. Interested parties, in the presence of these limited objectives, try to perform their activities in a more rational way.
Based on the above, it is possible to propose an efficient life cycle process model of housing credit access. The basis of the performed search for rational variable credit institutions and instruments is adapted to Lithuanian conditions. On a modelÕs completion, the interested parties will be able to use their financial resources in a more rational manner by considering the existing limitations and the possibilities of credit institutions and instruments. The research included the following stages as presented in Fig. 4.
Fig. 4. Main stages of working out a model of Lithuanian housing credit access development trends.
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In order to throw more light on the subject, a more detailed description of some of the above mentioned stages of analysis follows: • development of a rational conceptual model of housing credit access for Lithuania, • determination of rational housing investment instruments and lenders.
4. The development of a rational conceptual Lithuanian model for housing credit access The development of a rational conceptual model of housing credit access for Lithuania was done by means of an analysis of experiences and knowledge of advanced industrial economies and by their adaptation to Lithuania. To illustrate the conceptual modelÕs part, a sample problem solution based on this approach is given in Table 1. Different versions of advanced industrial economies practical experiences and policies in the field of housing credit access were analyzed. A determination of credit institutions, instruments and the markets describing housing credit access was made. Then, the existing situation of LithuaniaÕs housing credit access and advanced industrial economies was described in a conceptual form. Subsequently the determination of development trends of the housing credit access in advanced industrial economies and their differences to those of Lithuania was made. Having analyzed differences in the situation of housing credit access between Lithuania and advanced industrial economies, a model of housing credit access for Lithuania was developed. In the course of this analysis a few recommendations on how to increase the efficiency of the housing credit access for Lithuania were produced. A conceptual analysis of major trends in advanced industrial economies carried out by the authors [6,16,17] helped to create a conceptual model that reflects the Lithuanian trends in housing credit access development. However, the choice of an actual trend of development in Lithuania is highly dependent on a particular situation. For example, since the Lithuanian economy is transferring from planned development to free
market conditions it is quite natural that the economic, social and legislative situation in Lithuania and advanced industrial economies are different. While forming a model of general regularities of Lithuanian housing credit access development major international trends of housing credit access development were considered and took into consideration the particular actual mentioned situation in Lithuania. The comparative conceptual analysis of housing in developed countries and Lithuania allowed us to identify areas where the situation in Lithuania is comparable, partly comparable or quite different from the level attained by industrially developed foreign countries.
5. Determining rational housing investment instruments and lenders Medium and long-term credits are used for housing investment and certain factors and interested parties have an impact on the efficiency of alternatives of housing investment instruments. 5.1. Factors and interested parties affecting the efficiency of housing investment instruments A great number of effective housing investment instruments have been developed and successfully used in advanced industrial economies. The economic, legislative, political, social, technical and cultural situations and traditions are different in every country. Also market economies have been developed at a variety of levels. Often the efforts to introduce housing investment instruments, which proved to be efficient in some countries, were not successful in others. The same housing investment instruments when applied to various economies yield various results as far as the efficiency is concerned. Researchers and practical workers use diverse criteria when analyzing the efficiency of housing investment instruments. Based on the above mentioned expertise, the efficiency of housing investment instruments may be approached. Efficiency of housing investment instruments also depends on the interested parties (see Fig. 5).
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Table 1 The development of a rational conceptual model of housing credit access for Lithuania Rational housing credit access can be expanded through the use of:
Trends of development in Western Europe and USA
A fragment illustrating the development of Lithuanian rational housing credit access
Second mortgage
Sometimes, a first mortgage may be insufficient. Additional financing may be desirable or even necessary by the borrower, but because of lending policies at the first mortgageÕs institution, a larger amount may not be available. Alternatively, a buyer in a real estate transaction might not be able to produce a sufficient down payment to complete the financial transactionÕs arrangements. Second mortgages are best viewed as supplementary financing vehicles in residential housing markets. They provide flexibility and permit buyers and sellers to try to structure deals that could otherwise possibly not be completed. Although second mortgages are riskier than first mortgages for borrowers and lenders, they are a valuable part of the US mortgage finance system. When lenders want to lend more money quickly, they sell loans. When there is more mortgage money in the market than is needed, companies sell loans to take up some of that capital. The effect of the secondary mortgage market is to increase the amount of capital available for housing and to increase the geographic mobility of that capital [2]
Development of second mortgage
Government and private mortgage insurance
The costly nature of housing means that most home purchasers need a mortgage loan. Mortgage lenders prefer a prospective buyer to have at least 20% of the purchase price for a down payment. Obtaining even 20% of the price of a house is prohibitive for many people. Mortgage insurance helps to overcome the gap between what lenders would like and what borrowers are able to achieve. If a borrower qualifies in every way for a mortgage loan but has less than a 20% down payment, the lender will usually require mortgage insurance. In this case, the borrower pays premiums to protect the lender, in case the borrower defaults Government mortgage insurance. The Federal Housing Administration (FHA) programs require a down payment of between 3% and 5% of the purchase price of the house. It allows people who otherwise would not be able to buy a home to qualify for a loan and thus increases the proportion of homeowners in the US and the countryÕs reliance on debt financing for housing. If the borrower defaults, the FHA pays the lender the whole loan amount and the property belongs to the FHA. There are maximum price limits so that FHA insurance cannot be used for the purchase of more expensive housing. It primarily assists low-to-moderate-income homebuyers. The advantages for the homebuyer include a much lower down payment, standardized terms, and in many cases, the ability to buy a home Private mortgage insurance (PMI). Private mortgage insurance industry companies take on lower-risk insurance cases and charge a lower premium, so homebuyers prefer to use them when possible. PMI do not, however, insure the entire loan amount. Second, the FHA has a reputation for being cumbersome and slow, so many institutions and borrowers prefer to work with private companies. On the other hand, FHA succeeded in helping to create jobs and has been very popular with the private business sector [1,5,10]
Development of government and private mortgage insurance
Waivers of closing costs
Repudiation of Closing costs are the charges and fees incurred in transferring ownership of a home, including charges by the lender for loan processing and by an attorney to examine the closing costs title. Items that may be included in settlement charges are title search, title insurance, attorneyÕs fees, a property survey, a credit report, points, an appraisal fee, recording fee, state and local transfer taxes, escrow fees, and mortgage insurance. The above mentioned are paid at a meeting between the buyer and seller, representatives of the lender, the real estate broker (if one was involved), and attorneys hired by any and all parties. Closing charges may be 3% of the sales price but vary according to local laws, customs, and lending institution practices [5,10] (continued on next page)
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Table 1 (continued) Rational housing credit access can be expanded through the use of:
Trends of development in Western Europe and USA
A fragment illustrating the development of Lithuanian rational housing credit access
Reduced down payment
In a traditional real estate transaction, a long-term mortgage is secured for part of the cost of the purchase. The difference between the purchase price and the mortgage is the required equity contribution. This equity contribution is often referred to as the down payment. The amount may be reduced if the borrower is able to obtain a second mortgage to offset part of the down payment. In some markets, the most difficult requirement for first-time buyers is the amount required for the down payment. A substantial down payment may be necessary for the financial institution to be willing to make the loan [1,10,13]
Reduction of down payment
Sweat equity
Sweat equity includes the use of voluntary labor to reduce the cash costs of renovation while representing the down payment for each participant. Cases in which the repair costs are high, relative to after-repair market values, sweat equity may be a matter of necessity rather than of choice. Where sweat equity is permitted for significant tasks, proof that the homesteader can perform the work in a satisfactory manner is required. Sweat equity may be one of a few ways that these organizations can acquire ownership or control at prices they can afford. The approach tried by self-help housing groups was to allow the use of voluntary sweat labor to perform most of the construction work under the supervision of paid, skilled and licensed professionals [2]
Development of sweat equity
Mortgage analysts study debt-to-income ratios to learn points at which borrowers become overloaded with debt. The evaluation of existing loans provides a statistical basis for setting lending standards to avoid mortgage delinquency and default. Following the example of ratio-based loan qualification criterion: ‘‘Monthly payments plus other payments for long-term debt should not exceed N% (e.g. 33–36% of monthly income)’’
Development of flexible debtto-income qualifying ratios
Flexible debt-toincome qualifying ratios
Example 1. Title 1 Home Improvement Loan Program (USA). Title 1 loans to be made with higher debt-to-income ratios than most other loans. The maximum debt ratio allowed is 45%. Thus, Title 1 offers an attractive financing alternative to property owners who have good credit but little equity in their homes. It is particularly useful for current purchasers Example 2. Highly energy-efficient homes have a higher initial purchase price than conventional homes, many buyers have been unable to qualify for mortgages for the higher purchase costs, because they result in debt-to-income ratios that lenders consider too high Progress has been made in overcoming this barrier through programs in the secondary mortgage market. These programs now provide incentives to lenders to ÔstretchÕ debtto-income ratios for homebuyers [14]
5.2. Development of quantitative and conceptual databases of housing investment instruments In order to find the most efficient housing investment instruments for a particular country, the countryÕs exhaustive conceptual and quantitative description should be formed. The data then obtained should be subject to multiple criteria anal-
ysis, so as to help to choose the most rational variants. Conceptual descriptions of an investmentÕs instrument life cycle presents textual, graphical, numerical, mathematical and other forms of information about investment instruments. The criteria used for their definition, as well as giving the reason for the choice of this particular system of
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Fig. 5. Some factors and interested parties affecting the efficiency of housing investment instruments.
criteria, their values and weights are also essential. Conceptual information is needed to make a complete and accurate evaluation of the alternatives considered. More useful information and the development a system and subsystems of criteria and defining their values and weights (see Fig. 6) illustrates the development of a conceptual database fragment containing information on housing investment instruments. Quantitative information is based on criteria systems and subsystems, units of measure, values and initial weights. The determination of the utility degree and value of the investment instruments and the establishment of the priority order for its implementation does not present much difficulty if the criteria numerical values and weights are obtained and the multiple criteria decision-making methods are used. The process of determining the above the system of criteria, qualitative criteria initial weights and numerical values of the investment instruments under investigation is based on the use of various expert methods, on the Internet, etc. Quantitative criteria numerical values are obtained by analyzing the data on investment instruments and different documents, Internet, etc. The magnitude of weight indicates how many times one criterion is more/less significant than another in the multiple criteria evaluation of in-
vestment instruments. The results of the comparative analysis of the investment instruments are presented as a grouped decision, forming matrix where columns contain n alternative investment instruments, while all quantitative information pertaining to them is found in m lines (see Table 2). 5.3. Search for rational housing investment instruments and lenders The quantitative and conceptual databases, which are being developed at present, give an exhaustive description of housing investment instruments and allow for their multiple criteria analysis. This helps to determine the investment instrumentÕs efficiency, of the country in question. Moreover, the databases and multiple criteria analysis offered could also be used in the search for efficient lenders. Since the efficiency of alternatives of a housing investment instrument and lender is determined by taking into account much varied information, a multiple criteria analysis should include methods enabling a decision maker to implement a comprehensive analysis of the variants, leading to and making a proper choice. The following methods are aimed at performing this function:
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Fig. 6. A fragment of developing a housing investment instrumentÕs conceptual database.
Table 2 A fragment of developing housing investment instrumentÕs quantitative database Criteria describing the investment instruments
Weights
Measuring units
Compared investment instruments a1
a2
aj
an
Interest rates Period of maturity Down payments Loan repayment and payment of interest
q1 q2 qi qt
m1 m2 mi mt
x11 x21 xi1 xt1
x12 x22 xi2 xt2
x1j x2j xij xtj
x1n x2n xin xtn
Source of finance Subsidies Risk and guarantee Delinquency on loan
qtþ1 qtþ2 qi qm
mtþ1 mtþ2 mi mm
xtþ11 xtþ21 xi1 xm1
xtþ12 xtþ22 xi2 xm2
xtþ1j xtþ2j xij xmj
xtþ1n xtþ2n xin xmn
Utility degree of alternatives
N1
N2
Nj
Nn
Priority of investment instruments
Q1
Q2
Qj
Qn
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• a method for determining the initial weights of the criteria (using expertsÕ methods), • a method for the criteria weights establishment, • a method for multiple criteria analysis and setting priorities, • a method for determining alternatives utility degree. When a certain method (i.e. determining the initial weights of the criteria) is used, the results of the calculations obtained become the initial data for another method (i.e. a method for multiple criteria analysis and setting the priorities). The results of the latter, in turn, may be taken as the initial data for some other methods (i.e. determining housing investment instrument or lender utility degree and providing recommendations). An example, is the utility degree of investigated alternative investment instruments and lenders as determined by using the proposed method [15]. This method assumes direct and proportional dependence on the utility degree of investigated alternatives on a system of criteria describing alternatives, values and weights of the criteria. Experts determine the system of criteria, calculate the values and the initial weights of criteria. Interested parties can correct all this information by taking into consideration their goals and financial capabilities. The assessment results of alternatives fully reflect the initial data jointly submitted by experts and interested parties.
6. Multiple criteria analysis of alternative loans 6.1. Sample application To illustrate the efficiency of the model suggested, a sample problem and solution is given below. Firstly, a study case will be described and the problem formulated. A family of three persons would like to obtain a mortgage loan for purchasing a two-room apartment. An approximate value of the housing to be bought is 96,000–104,000 Litas. The amount of the loan is 80,000 Litas. Then net family income per month is 3200 Litas. The maturity of the loan is 10 years (1 US dollar ¼ 4 Litas 2001).
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Regarding the terms of mortgage loans issued by three financial institutions: the Baltic-American Enterprise Fund, Vilnius Bank and Hermis Bank and take into account the information given below (this will be illustrated using Vilnius Bank as an example). 6.1.1. Vilnius Bank Net income of the family per month. Net monthly family income per capita (without loan installments and interest rate payments) should not be less than 500 Litas. In this case, the average loan repayment and interest rates are 1100 Litas, i.e. 700 Litas per capita. Maximum maturity of the loan. Maximum maturity of the loan is 10 years. An average loan installment per month. When the loan is 80,000 Litas, the average loan installment and interest rate payments are 1100 Litas. Loan interest rates. The annual interest rate on loans, having estimated the maturity and the exposure of the loan, fluctuate from 9% to 11%. This year the interest rate on loans issued for 10 years is 11%. Hypothecation bond fee. In order to secure the liabilities under the loan agreement, the bank accepts a mortgage in the form of the housing to be purchased. Hypothecation bond registration fee, which should be taken into account, is 50 Litas. Hypothecation and notarization fees make about 0.5% of the mortgaged housing value. In this case, the mortgage fee is 450 Litas. A one-off loan administration fee. Here a one-off loan is considered where the administration fee is 400 Litas or 0.5% of the loan. Life insurance. The borrowerÕs life insurance is obtained in favor of the bank for the entire maturity of the loan with an insurance company acceptable to the bank. In our case, this will is 240 Litas per year. Insurance of the housing to be purchased. Insurance of the housing to be purchased is obtained in favor of the bank with an insurance company acceptable to the bank. The annual payment in this case will be 260 Litas. General terms and conditions of the loan. Loans are issued to citizens of the Republic of Lithuania who are 21 years old. The mortgage loan is issued
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and repaid in US dollars, which are exchanged into Litas at the official exchange rate that is fixed by the Lithuanian bank. To obtain the loan one has to open an account with the bank to where their salary is to be transferred. The mortgage loan covers up to 70% of the value of the housing to be purchased. A person needs to obtain a certificate from the office of Children Rights Protection in the event of having children under 18. The consent of the housing ownerÕs spouse to pledge the housing notarized must also be obtained. The initial payment. A person to whom the loan is issued transfers to the bankÕs account the amount covering at least 30% of the value of the housing to be purchased. In our case the first payment is 24,000 Litas. Loan repayment. The repayment of the loan and the payment of interest accrued commences on the month following the disbursement of the loan. The payment will be effected in equal installments or its annuity. On the month of the loan disbursement only the interest must be paid. The deadline of the loan repayment is not charged. The interest margin changes slightly throughout the years subject to the fluctuation of London Inter-Bank Offered Rate (LIBOR) per one US dollar. Loan registration. The borrower will have to fill in an application form for a loan by answering the questions presented on the nine pages of the form. The latter refers to the borrowerÕs actual income, property, members of the family, etc. The borrower will be notified of the bankÕs decision to issue the loan within a week. Commission for anticipatory loan repayment. If the loan is repaid prior to the time when it is due and according to the agreement made, the bank will take a commission for the unpaid interests (0.5% of the amount repaid prior to the loan agreement termination). Commission for currency exchange. Mortgage loans are free from currency exchange transaction fees. The same applies to other cases investigated. A decision making matrix is made (see Table 3) by using the description of the presented conceptual alternatives. The total complex weight of major criteria pertaining to the alternative loans is based on their quantitative and qualitative char-
acteristics and may be determined from the above matrix as well as following Eqs. (1) and (9). The calculation results are provided in Table 3. Because the computer calculates with fuller precision, the values presented here differ somewhat from those stored in the computer memory. 6.2. The complex determination of the weights of the criteria The weights of all criteria must be coordinated, including their quantitative and qualitative characteristics. The weights of quantitative criteria can be exactly coordinated if the values of quantitative criteria are expressed through an equivalent monetary unit. Having performed strict mutual coordination of quantitative criteria weights, the same is done with the weights of qualitative criteria. In this case all the weights of qualitative and quantitative criteria are exactly coordinated at the same time. The calculation of the criteria weights is carried out in seven stages. In stages 1–4 the weights of quantitative criteria are identified, whereas stages 5–7 identify the weights of qualitative criteria. Stage 1. The determination of the sum of values for every quantitative criterion: n X Si ¼ xij ; i ¼ 1; t; j ¼ 1; n; ð1Þ j¼1
where xij is the value of the i criterion in the j alternative of a solution, t is the number of quantitative criteria, n is the number of the alternatives compared. According to expression (1) the sum of values is determined for every criterion which can be represented in money terms. Stage 2. The total monetary expression of every quantitative criterion describing the investigated loan is obtained by Pi ¼ Si pi ; i ¼ 1; t; ð2Þ where pi is initial weight of the i criteria. pi should be measured in such a way as, being multiplied by a quantitative criterion value, an equivalent monetary expression could be obtained. According to their effect on the efficiency of the loan in time, the quantitative criteria may be divided into:
The criteria considered
Quantitative criteria (1) Loan repayment and payment of interest (2) Hypothecation bond registration fee (3) A one-off loan administration fee (4) Life insurance (5) Insurance of the housing to be purchased (6) The initial payment (7) Commission for currency exchange
Measuring units
Numerical values of criteria of the compared loans
Determination of
Baltic-American Enterprise Fund
Vilnius Bank
Hermis Bank
Sum of criteria, Si
Initial weight of criteria, pi
Total monetary expression of criteria, Pi
Weight of criteria, qi
Lt/month
)
1148
1100
1200
3448
120
413760
0.8427
Lt
)
400
450
450
1300
1
1300
0.0026
Lt
)
360
400
350
1110
1
1110
0.0023
Lt/year Lt/year
) )
0 160
240 200
240 200
480 560
10 10
4800 5600
0.0098 0.0114
Lt Lt
) )
16000 400
24000 0
24000 0
64000 400
1 1
64000 400
0.1304 0.0008
V ¼ 490970 Qualitative criteria (8) Maturity of the loan (9) General terms and conditions of the loan (10) Loan registration
Years Points
+ +
10 9.47
10 7.56
10 9.05
– –
0.2536 0.3158
– –
0.2468 0.3073
Weeks
)
6
1
2
–
0.0136
–
0.0132
The sign +/) indicates that a greater/lesser criterion value is better. 1 US dollar ¼ 4 Litas.
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Table 3 Weight determination of criteria, including their quantitative and qualitative characteristics
347
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• short-term factors affecting the loan for a certain period of time, • long-term factors affecting the loan throughout its life cycle. The initial weight of long-term criteria (i.e. average monthly installment, life insurance, mortgage insurance) depends on the issued loanÕs maturity as well as the monetary expression of a criterionÕs unit of measure. In the case considered the maturity of the loan is 10 years. Pi ¼ efi ;
ð3Þ
criteria, a compared standard value (E) is set. E is equal to the sum of any selected weight of quantitative criteria. One of the main requirements for this comparative standard value is that according to its utility, it is more easily comparable with all qualitative criteria. In this case, the weights of all qualitative criteria are determined by a comparison of their utility with the weight of the compared standard value. E is determined as follows: E¼
g X
ð8Þ
qz ;
z¼1
where e is repayment time of a loan, fi is monetary evaluation of a measure unit of the i criterion. The initial weight of one-off is equal to the monetary expression of the criterion measuring unit. For example, the initial weight of a one-off hypothecation registration fee is equal to one, since this payment is effected only once per 10 years. pi ¼ fi :
ð4Þ
The physical meaning of the initial weight of a quantitative criterion consists of the fact that multiplying the initial weight by the value of a quantitative criterion, its monetary value which expression is calculated over the maturity of the loan (equivalent to former natural expression) is obtained. Stage 3. The overall quantitative criteria magnitude sum expressed in money terms is determined by V ¼
t X
Pi ;
i ¼ 1; t:
ð5Þ
i¼1
Stage 4. The quantitative criteria weight describing the loan which can be expressed in money terms is determined as follows: qi ¼
Pi ; V
i ¼ 1; t:
ð6Þ
The total sum of weight quantitative criteria is always equal to 1: t X
qi ¼ 1:
ð7Þ
i¼1
Stage 5. In order to achieve full coordination between the weights of quantitative and qualitative
where g is the number of quantitative criteria included into the compared standard; qz is the weight of z quantitative criterion which is included in the compared standard. In our case, all qualitative criteria weights were determined by comparing the qualitative criteria weight with the weight of the loan repayment and payment of interest and the initial payment. Stage 6. The initial weight vi of qualitative criteria is determined by expert methods by comparing their relative weight to the weight E of the selected compared standard. If so, the relative weight of qualitative criteria should be expressed in percentages. Stage 7. The weight of qualitative criteria is determined as follows: qi ¼ mi E;
i ¼ t þ 1; m:
ð9Þ
The above method allows for the determination of weights of criteria that are maximally interrelated and depend on qualitative and quantitative characteristics of all criteria. 6.3. The multiple criteria complex proportional evaluation of variants This method assumes direct and proportional dependence of significance and priority of investigated versions on a system of criteria and adequately describe the alternatives on values and weights of the criteria. The system of criteria is determined and experts also calculate the values and initial weights of criteria. Interested parties taking into consideration their pursued goals and the existing capabilities can check and correct all
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this information. The assessment results of alternatives that fully reflect the initial data jointly submitted by experts and interested parties. The determination of significance and priority of alternatives is carried out in four stages. Stage 1. The weighted normalized decisionmaking matrix D is formed. The purpose of this stage is to receive dimensionless weighted values from the comparative indexes. When the dimensionless values of the indexes are known, all criteria, originally having different dimensions, can be compared. The equation is used as shown below: xij qi dij ¼ Pn ; i ¼ 1; m; j ¼ 1; n; ð10Þ j¼1 xij where xij is the value of the i criterion in the j alternative of a solution, m is the number of criteria, n is the number of the alternatives compared, qi is weight of i criterion. The sum of dimensionless weighed index values dij of each criterion xi is always equal to the weight qi of this criterion: n X dij ; i ¼ 1; m; j ¼ 1; n: ð11Þ qi ¼ j¼1
In other words, the value of weight qi of the investigated criterion is proportionally distributed among alternative versions aj according to their values xij . Stage 2. The sums of weighed normalized indexes describing the j version are calculated. The versions are described by minimizing indexes Sj and maximizing indexes Sþj . The lower the value of minimizing indexes the better (loan repayment and payment of interest, hypothecation bond registration fee, a one-off loan administration fee, etc.). The greater the value of maximizing indexes the better (maturity of the loan, general terms and conditions). The sums are calculated as follows: Sþj ¼
m X
dþij ;
Sj ¼
i¼1
i ¼ 1; m; j ¼ 1; n:
m X
dij ;
i¼1
ð12Þ
In this case, the values Sþj (the greater this value, the more satisfied the interested parties) and
349
Sj (the lower this value, the better is goal attainment by the interested parties) express the degree of goals attained by the interested parties in each alternative loan. In any case the sums of ÔplusesÕ Sþj and ÔminusesÕ Sj of all alternative loans are always respectively equal to all sums of the weights of maximizing and minimizing criteria by n m X n X X Sþ ¼ Sþj ¼ dþij ; j¼1
S ¼
n X j¼1
i¼1
Sþj ¼
j¼1
m X n X i¼1
dij ;
i ¼ 1; m; j ¼ 1; n:
j¼1
ð13Þ Stage 3. The significance of comparative versions is determined on the basis of describing positive loans (pluses) and negative loans (minuses) characteristics. Relative significance Qj of each loan aj is calculated as follows: P S min nj¼1 Sj ; j ¼ 1; n: ð14Þ Qj ¼ Sþj þ Pn S Sj j¼1 Sjmin Stage 4. Loans priority determination. The greater the Qj the higher the efficiency loan. Since Q1 > Q2 > Q3 then priority of the first version is the best (see Table 4). An analysis of the method presented makes it possible to state that the method may be easily applied to evaluating loans and in selecting the most efficient one, while being fully aware of a physical meaning of the process. Moreover, the method allowed for the formulating of a reduced criterion Qj that is directly proportional to the relative effect of the compared criteria values xij and weight qi on the end result. 6.4. The utility degree of the loans Significance Qj of loan aj indicates the satisfaction degree of demands and goals pursued by the interested parties. The greater Qj the higher the efficiency of the loan. In this case, the significance Qmax of the most rational loan will always be the highest. The significance of remaining loans is lower as compared with the most rational one. This means that total demands and goals of
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Table 4 Multiple criteria evaluation of alternative loans from different financial institutions The criteria considered
Measuring units
Weights
Weighted normalized values of criteria of the compared loans BalticAmerican Enterprise Fund
Vilnius Bank
Hermis Bank
0.2806 0.0008 0.0007 0.0000 0.0033 0.0326 0.0008 0.0823 0.1116 0.0088
0.2689 0.0009 0.0008 0.0049 0.0041 0.0489 0.0000 0.0823 0.0891 0.0015
0.2933 0.0009 0.0007 0.0049 0.0041 0.0489 0.0000 0.0823 0.1066 0.0029
The sums of weighted normalized maximizing indices of the loans Sþj The sums of weighted normalized minimizing indices of the loans Sþj
0.1938 0.3276
0.1713 0.3299
0.1889 0.3557
Significance of loans Qj Priority of loans Utility degree of loans, %
0.5415 1 100
0.5166 2 95.40
0.5091 3 94.02
(1) Loan repayment and payment of interest (2) Hypothecation bond registration fee (3) A one-off loan administration fee (4) Life insurance (5) Insurance of the housing to be purchased (6) The initial payment (7) Commission for currency exchange (8) Maturity of the loan (9) General terms and conditions of the loan (10) Loan registration
Lt/month Lt Lt Lt/year Lt/year Lt Lt Years Points Weeks
) ) ) ) ) ) ) + + )
0.8427 0.0026 0.0023 0.0098 0.0114 0.1304 0.0008 0.2468 0.3073 0.0180
The sign +/) indicates that a greater/lesser criterion value is better. 1 US dollar ¼ 4 Litas.
interested parties will be satisfied to a smaller extent than it would be in case of the best loan. The degree of loan utility is directly associated with the related quantitative and conceptual information. With the increase/decrease of the significance of a loan analyzed, its degree of utility also increases/decreases. The degree of loan utility is determined by comparison of the loan analyzed with the most efficient loan. In this case, all the utility degree values related to the loan analyzed will range from 0% to 100%. This will facilitate a visual assessment of the loanÕs efficiency. The equation used for the calculation of loan aj utility degree Nj is given below: Nj ¼ ðQj : Qmax Þ100%;
ð15Þ
here Qj and Qmax are the significance of the loan obtained from Eq. (14). The degree of utility Nj of loan aj indicates the level of satisfying the needs of the interested parties in the loan. The more goals achieved the more important the goals are and the higher the degree of the loanÕs utility. Since clients are mostly in-
terested in how much more efficient one particular loan is than another then it is more advisable to use the concept of a loan utility rather than its significance when choosing the most efficient solution. The degree of a loanÕs utility reflects the extent to which the goals pursued by the interested parties are attained. Therefore, the utility degree may be used as a basis for determining the loanÕs value. The more objectives attained, the more significant the objectives are, and the higher the loanÕs degree of utility and its value will be. Having determined the ratio of the degree of a utility and the value of a loan, one can see the level of the complex effect that can be obtained by investing money into anyone of the loans. There is complete clarity where better to invest the money and to the efficiency degree of the investment. The results of the multiple criteria evaluation of alternative loans from different financial institutions are given in Table 4. From the values, it can be seen that the first version is the best one. The utility degree N1 ¼ 100%. The second version ac-
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cording to its priority was established as the second best variant. The utility degree of it N2 ¼ 95:40%. The degree of loanÕs utility reflects the extent to which the goals pursued by the interested parties are attained. For example, the significance of the difference between the utility degree of loan 1 (N1 ¼ 100:00%) and loan 3 (N3 ¼ 94:02%) shows that loan 1 is more useful by 5.98% than loan 3. Results acquired after calculation (Table 4) show that the first variant of the loan as per established conditions conformed with clientÕs purposes and needs. This analysis of the loans from different financial institutions was made from client/userÕs position. Taking into consideration the acquired results, various participants of the housing credit may also adjust their decisions in accordance to their priorities and the present conditions.
7. Conclusions The improvement of housing conditions in Lithuania requires access to credit. Barriers to rational credit access for low incomes are among the most important obstacles faced by Lithuanian households in seeking affordable dwelling today. Efforts to expand access to rational housing credit have led to reforms in lending practices of advanced industrial economies and to the creation of alternative credit institutions and instruments. This research is based on the analysis of the expertise of advanced industrial economies and aims at adapting the most rational credit access to Lithuania, by taking into account its specific history, economic development, needs and traditions. The comparative conceptual analysis of housing in developed countries and Lithuania allowed us to identify areas where the situation in Lithuania is comparable, partly comparable or quite different from the level attained by industrially developed foreign countries. This paper also describes methods to be used in searching for rational housing investment instruments and lenders. Based on the above, it is possible to propose an efficient life cycle process model of housing credit access. The basis of the performed search for rational variable credit institutions and instruments is adapted to Lithuanian conditions. On a modelÕs
351
completion, the interested parties will be able to use their financial resources in a more rational manner by considering existing limitations and the possibilities of credit institutions and instruments. When analyzing various models one is always confronted with the question, ÔHow long will they be practically useful?Õ If conditions change considerably, some models inadequately describe the subject of this research. Is this going to happen with the suggested model? Housing investment instruments supply and demand and their efficiency change over time. For example, once Lithuania enters the European Union, new housing investment instruments will emerge. An increase of the countryÕs GDP, growth of salaries, improvement of legal environment, emergence of loan insurance and state guarantees will make it possible to reduce the loan risks. Loan insurance reduces the risks associated with housing loans and therefore, after the establishment of the Housing Loans Insurance Company competition between banks offering housing loans will be increased. Therefore, the interest rates on insured loans are lower than the interest rates on uninsured loans. State guarantees are very important to the market: thanks to the system of guarantees the number of housing loan recipients is growing, the risks to creditors and investment bankers will decrease and businesses and the economy as a whole will expand. As we can see very many micro- and macro-level factors influence the efficiency of housing investment instruments. Therefore, on creating a comprehensive database of investment instruments, it is possible to analyze its efficiency in relation to various interested parties at certain intervals. Based on this analysis it is possible to identify investment instruments best adjusted to the conditions at a given period and to actively implement them in practice. If conditions change, this analysis can be repeated. The suggested model can be effectively implemented also in other countries.
References [1] F. Blankenship, The Prentice Hall Real Estate InvestorÕs Encyclopedia, Prentice Hall, Englewood Cliffs, NJ, 1989.
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[2] W. Brueggeman, Real Estate Finance and Investments, Irwin, Homewood, IL, 1993. [3] U.S. Dhillon, S. Upinder, J.D. Schilling, C.F. Sirmans, The mortgage maturity decision: The choice between 15-year and 30-year FRMs, Southern Economic Journal 56 (1990) 1103–1116. [4] N. Van Dyk, Financing social housing in canada, Housing Policy Debate 6 (4) (1995) 815–848. [5] C. Jacobus, Real Estate Principles, Prentice Hall, Upper Saddle River, NJ, 1996. [6] A. Kaklauskas, Total life analysis, modelling and forecasting of construction in Lithuania, Research output, EC Phare-ACE Program 1996, Contract Number: P966708-F. [7] K.C. Lam, G. Runeson, C.M. Tam, S.M. Lo, Modeling loan acquisition decisions, Engineering, Construction and Architectural Management 5 (4) (1998) 359–375. [8] D. Leece, Mortgage design in the 1990s: Theoretical and empirical issues, Journal of Property Finance 8 (3) (1997) 226–245. [9] D. Leece, Choice of mortgage instrument, liquidity constraints and the demand for housing debt in the UK, Applied Economics 32 (2000) 1121–1132.
[10] D. McKenzie, Essentials of Estate Economics, Prentice Hall, Upper Saddle River, NJ, 1996. [11] D.W. Rasmussen, I.F. Megbolugbe, B.A. Morgan, The revenue mortgage as an asset management tool, Housing Policy Debate 8 (1) (1997) 173–194. [12] B. Renaud, The financing of social housing in integrating financial markets: A view from developing countries, Urban Studies 36 (4) (1999) 755–773. [13] D. Tosh, Handbook of Real Estate Terms, Prentice Hall, Englewood Cliffs, NJ, 1990. [14] W. Van Vliet (Ed.), The Encyclopedia of Housing, Sage Publications, Thousand Oaks, CA, 1998. [15] E.K. Zavadskas, F. Peldschus, A. Kaklauskas, Multiple criteria evaluation of loans in construction, in: Institute of Technological and Economic Development, Vilnius Technical University, Technika, Vilnius, 1994. [16] E.K. Zavadskas, L. Simanauskas, A. Kaklauskas, Decision Support Systems in Construction, Technika, Vilnius, 1998. [17] E.K. Zavadskas, B. Sloan, A. Kaklauskas, Total life analysis, modeling and forecasting of the construction industry in Lithuania, in: V. Abrantes (Ed.), Proceedings of the XXV IAHS World Housing Congress, Lisbon, Portugal, 29 June–3 July 1998, Porto, 1998, pp. 69–78.
Housing credit access model: The case for Lithuania E.K. Zavadskas, A. Kaklauskas *, A. Banaitis, N. Kvederyte Department of Building Technology and Management, Vilnius Gediminas Technical University, Sauletekio al. 11, LT-2040 Vilnius, Lithuania
Abstract The research described in this paper aimed at achieving two major goals. First, to identify and describe rational credit access development in advanced industrial economies as well as providing recommendations for Lithuania. The multiple criteria quantitative and conceptual analysis of rational credit access in developed countries and in Lithuania allowed for the identification of areas where the Lithuania situation is comparable, partly comparable or quite different from levels attained by advanced industrial economies. The data of this quantitative and conceptual analysis was used to identify rational credit access development trends in Western Europe and the USA as well as providing some recommendations for Lithuania. The determination and realization of efficient housing credit access in Lithuania would create better conditions for the functioning of the housing system. Second, the paper contains a description of a suggested method in choosing efficient housing investment instruments and lenders. The quantitative and conceptual databases that are being developed at present, give an exhaustive description of housing investment instruments and allow for their multiple criteria analysis. This helps to determine efficient investment instruments for the countries in question. The databases and multiple criteria analysis offered could also be used in searching for efficient lenders. The methods suggested in this paper can also be applied to solving similar problems in other countries. 2003 Elsevier B.V. All rights reserved. Keywords: Rational credit access; Housing investment instruments; Multiple criteria analysis; Model
1. Introduction When considering the number of flats per 1000 people, Lithuania lags behind other European countries. At present, i.e. 2001, there are 375 apartments per 1000 people in Lithuania and most of these construction facilities were built before 1990 and very often are in need of renovation. On *
Corresponding author. E-mail address: [email protected] (A. Kaklauskas).
average, only 1.16 new flats per one thousand inhabitants are built in Lithuania each year and this is one of the lowest indices in Europe. Today, more and more flats are being built using credit that is extended by commercial banks. Recently however, the situation has become somewhat better. In 2001, about LTL 50 million (US $12.5 million) was set aside for statutory housing loans on easy terms. The State provides a 6% deduction on the interest for housing loans during the first half of the repayment period and subsidizes up to 20% of the borrowed amount. If
0377-2217/$ - see front matter 2003 Elsevier B.V. All rights reserved. doi:10.1016/S0377-2217(03)00091-2
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the loan is insured with the enterprise ‘‘Building Loan Insurance’’ a loan can be obtained by making a down payment of 5% on the propertyÕs value. In the case of an uninsured loan, a down payment of 30% of the propertyÕs value must be paid. Presently in Lithuania, housing credit terms and the terms for the issuance of State guarantees for such loans are more favorable than in most East and Central European countries. Currently, the enterprise ‘‘Building Loan Insurance’’ is the only company in Eastern Europe offering housing loan insurance services. Since the insurance of loans reduces risks associated with housing loans, on the establishment of the enterprise ‘‘Building Loan Insurance’’ as a result, the competition between banks providing housing loans has increased. Consequently, loans are provided at a lower interest than would be available in the case of uninsured housing loans. Housing loans for the sale of flats has increased considerably also due to better credit facilities. Even flats in basements and other less appealing parts of buildings have been sold because loans have increased the demand. State guarantees are very important for the market and due to the system of these guarantees housing loans have become available to wider groups of people and risks to creditors and investment bankers have decreased somewhat. The loan system has also promoted the growth of businesses and the economy on the whole. The Japanese PHRD Fund has provided Lithuania with a US $0.5 million guarantee for the preparation of a new housing strategy. On drawing up the Lithuanian housing strategy a request for a loan will be necessary for its implementation. The housing strategy will indicate whether social housing, renovations and/or support for young families and retired persons should to be made top priority or not. Having already restructured the system of the Immovable Property Cadastre and the Register, a hypothetical infrastructure has been set up in Lithuania. Therefore, commercial banks have started offering more housing mortgage loans because of the restructuring. The efficiency of the housing policy depends not so much on the support from the State and
international organizations as on the private financial sector as well as its initiative and ability to extend credit services. At the present time, housing credit terms and terms for the issuance of State guarantees for such loans in Lithuania are more favorable than in most Eastern European countries. However, judging by the experiences of other countries, various alternative crediting instruments that would assist further development of the Lithuanian housing credit market, could still be proposed. Such alternatives could include loans to residents on easy terms, the establishment of state institutions which would provide respective guarantees to banks, subsidies provided directly to residents and state guarantees that are given to certain groups of loans, etc. Several alternative ways of the StateÔs participation in the housing financing market are being currently discussed in Lithuania. Examples of this are, the average personÕs income tax concession to receiving a housing loan, subsidies to saving programs, full compensation of a loanÕs insurance premiums, compensation of interest paid on loans taken by homeowners and various associations related to this aspect, etc. Due to the ever-changing micro- and macrolevels of the environmental conditions, the efficiency of alternatives under consideration will vary. Therefore, in the future new crediting instruments that are better adapted to the new micro- and macro-levels of the environmental conditions might be necessary. Each of these alternatives has both advantages and disadvantages. The implementation of some of these crediting instruments would cause serious problems due to the absence of the necessary legal basis or a population at the lower level income bracket and other factors. The level of maintenance of the existing housing, especially apartment buildings, as well as their renovation is also a cause for concern. The Government continues to implement its project for Housing Renovation and Energy Saving in Housing, which started in 1996 by using a World Bank loan. Presently negotiations with the World Bank for a new loan will be carried out. The objective of this paper is to identify and describe rational credit access development in ad-
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vanced industrial economies as well as provide recommendations for Lithuania. The paper contains a description of a suggested method in choosing efficient housing investment instruments and lenders. The paper is structured as follows. Following this introduction, Section 2 outlines housing finance systems in advanced economies. In Section 3 we describe the main stages of forming a Lithuanian housing credit access development model. The development of a rational conceptual Lithuanian model for housing credit access is introduced in Section 4. The determination of rational housing investment instruments and lenders is presented in Section 5. In Section 6 we describe a case study and present the proposed multiple criteria analysis method. Finally, some concluding remarks are provided in Section 7.
2. Housing finance systems used in advanced economies The housing finance systems differ greatly from country to country. As Renaud [12] stated, there are profound differences among the 180 developed and developing countries that are now members of the World Bank. The advanced housing finance systems can be found in OECD countries. Renaud [12] shows that, these systems grew out of two main traditions: Anglo-Saxon systems where the building societies of the UK and the savings and loans from the US are mutual forms of housing finance. There is also the mortgage bank tradition of continental Europe where term funding was mobilized through bond markets. Also, there is wide and increasing literature on the choice of housing investment instruments. This mainly concerns the econometric estimation of the demand for fixed rate mortgages compared with adjustable rate mortgages. There is also a considerable amount of empirical work on the mortgage choice between the conventional annuity mortgage and payment via savings in a diversified portfolio of assets. Leece [8] reviewed recent developments in the design and innovation of mortgage instruments in the UK, from the early to mid-1990s. Rasmussen
337
et al. [11] present a more expansive view of reverse mortgages as a financial tool for tapping housing equity for various purposes and at various stages in the life cycle. Dyk [4] examines the mechanisms used since the 1970s to finance social housing in Canada. He demonstrates that direct government assistance has proven to be the most cost-effective mechanism. Experimentation with alternative mortgage instruments such as the graduated-payment mortgage and the indexlinked mortgage has also been central in the attempt to minimize subsidy and financing costs. Dhillon et al. [3] evaluate the choice between 15and 30-year fixed rate contracts in the USA and estimate a simple profit to represent this choice. Lam et al. [7] developed a model for financial decision-making which provides a method of solving borrowing decision problems. Leece [9] estimates reduced form credit demand equations that reflect the interactions between the choice of mortgage instrument, the lessening of mortgage rationing and liquidity constraints and the demand for a housing debt. Most of these studies have concentrated on the single objective of decision making.
3. Main stages of forming Lithuanian housing credit access development model This researchÕs aim was to produce a model, consisting of conceptual and quantitative parts for rational housing credit access in Lithuania by undertaking a complex analysis of credit institutions and instruments affecting the institutions. Also recommendations on the increase of its efficiency have been made. The research was performed by studying the expertise of advanced industrial economies and by adapting it to Lithuania. A simulation was undertaken to provide insight into the creating of effective housing credit access. Fig. 1 indicates diagrammatically the credit institutions and instruments that may impinge on the efficiency of housing credit access. To be efficient, housing credit access must operate within certain boundaries imposed by the credit institutions and instruments. It was recognized that in
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Fig. 1. Credit institutions and instruments that influence the efficiency of the housing credit access.
each country the system of credit, institutions and instruments are different and so Fig. 1 varies accordingly. To increase the efficiency of housing credit access in the country under consideration, it is necessary to utilize knowledge and experiences concerning lending practices. This may be achieved by analyzing experiences and knowledge of advanced industrial economies and applying them to Lithuania. The Lithuanian government may introduce mortgage insurance in order to promote credit for housing. Therefore, the boundary of efficiency will be extended to include this new development. The second mortgage being added to the boundary will change once again in the future (Fig. 2 illustrates a revised level of efficiency as an example of which alterations should be taken into account).
Fig. 3 graphically illustrates interrelationships between credit institutions, instruments and housing credit access. The area inside the ellipse represents the positive effect of credit institutions and instruments on the efficiency of housing credit access. The area outside the ellipse shows the negative effect on the efficiency of housing credit access. The overlapping areas of credit institutions and instruments show where better conditions for housing credit access have been created. Optimum housing credit access is obtained when all ellipse areas are overlapping (i.e. second mortgage, sweat equity, etc.). The greater the common overlapping area, the greater the efficiency level of the housing credit access. Having investigated the effects of the variables affecting housing credit access in advanced industrial economies, some differences have been identified between these countries and
Fig. 2. Fluctuations of efficient boundaries for access to housing credit.
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339
Fig. 3. Determination of optimal, rational and negative housing credit access.
Lithuania. On the basis of these differences, the main implications for Lithuania can be identified. Studying only one advanced industrial economy could lead to any inferences that will be purely subjective. By studying a number of countries any bias is diminished. The presence of specific variable credit institutions and instruments immediately imposes objective limitations on the efficient activities of interested parties such as debtors and lenders. Interested parties, in the presence of these limited objectives, try to perform their activities in a more rational way.
Based on the above, it is possible to propose an efficient life cycle process model of housing credit access. The basis of the performed search for rational variable credit institutions and instruments is adapted to Lithuanian conditions. On a modelÕs completion, the interested parties will be able to use their financial resources in a more rational manner by considering the existing limitations and the possibilities of credit institutions and instruments. The research included the following stages as presented in Fig. 4.
Fig. 4. Main stages of working out a model of Lithuanian housing credit access development trends.
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In order to throw more light on the subject, a more detailed description of some of the above mentioned stages of analysis follows: • development of a rational conceptual model of housing credit access for Lithuania, • determination of rational housing investment instruments and lenders.
4. The development of a rational conceptual Lithuanian model for housing credit access The development of a rational conceptual model of housing credit access for Lithuania was done by means of an analysis of experiences and knowledge of advanced industrial economies and by their adaptation to Lithuania. To illustrate the conceptual modelÕs part, a sample problem solution based on this approach is given in Table 1. Different versions of advanced industrial economies practical experiences and policies in the field of housing credit access were analyzed. A determination of credit institutions, instruments and the markets describing housing credit access was made. Then, the existing situation of LithuaniaÕs housing credit access and advanced industrial economies was described in a conceptual form. Subsequently the determination of development trends of the housing credit access in advanced industrial economies and their differences to those of Lithuania was made. Having analyzed differences in the situation of housing credit access between Lithuania and advanced industrial economies, a model of housing credit access for Lithuania was developed. In the course of this analysis a few recommendations on how to increase the efficiency of the housing credit access for Lithuania were produced. A conceptual analysis of major trends in advanced industrial economies carried out by the authors [6,16,17] helped to create a conceptual model that reflects the Lithuanian trends in housing credit access development. However, the choice of an actual trend of development in Lithuania is highly dependent on a particular situation. For example, since the Lithuanian economy is transferring from planned development to free
market conditions it is quite natural that the economic, social and legislative situation in Lithuania and advanced industrial economies are different. While forming a model of general regularities of Lithuanian housing credit access development major international trends of housing credit access development were considered and took into consideration the particular actual mentioned situation in Lithuania. The comparative conceptual analysis of housing in developed countries and Lithuania allowed us to identify areas where the situation in Lithuania is comparable, partly comparable or quite different from the level attained by industrially developed foreign countries.
5. Determining rational housing investment instruments and lenders Medium and long-term credits are used for housing investment and certain factors and interested parties have an impact on the efficiency of alternatives of housing investment instruments. 5.1. Factors and interested parties affecting the efficiency of housing investment instruments A great number of effective housing investment instruments have been developed and successfully used in advanced industrial economies. The economic, legislative, political, social, technical and cultural situations and traditions are different in every country. Also market economies have been developed at a variety of levels. Often the efforts to introduce housing investment instruments, which proved to be efficient in some countries, were not successful in others. The same housing investment instruments when applied to various economies yield various results as far as the efficiency is concerned. Researchers and practical workers use diverse criteria when analyzing the efficiency of housing investment instruments. Based on the above mentioned expertise, the efficiency of housing investment instruments may be approached. Efficiency of housing investment instruments also depends on the interested parties (see Fig. 5).
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Table 1 The development of a rational conceptual model of housing credit access for Lithuania Rational housing credit access can be expanded through the use of:
Trends of development in Western Europe and USA
A fragment illustrating the development of Lithuanian rational housing credit access
Second mortgage
Sometimes, a first mortgage may be insufficient. Additional financing may be desirable or even necessary by the borrower, but because of lending policies at the first mortgageÕs institution, a larger amount may not be available. Alternatively, a buyer in a real estate transaction might not be able to produce a sufficient down payment to complete the financial transactionÕs arrangements. Second mortgages are best viewed as supplementary financing vehicles in residential housing markets. They provide flexibility and permit buyers and sellers to try to structure deals that could otherwise possibly not be completed. Although second mortgages are riskier than first mortgages for borrowers and lenders, they are a valuable part of the US mortgage finance system. When lenders want to lend more money quickly, they sell loans. When there is more mortgage money in the market than is needed, companies sell loans to take up some of that capital. The effect of the secondary mortgage market is to increase the amount of capital available for housing and to increase the geographic mobility of that capital [2]
Development of second mortgage
Government and private mortgage insurance
The costly nature of housing means that most home purchasers need a mortgage loan. Mortgage lenders prefer a prospective buyer to have at least 20% of the purchase price for a down payment. Obtaining even 20% of the price of a house is prohibitive for many people. Mortgage insurance helps to overcome the gap between what lenders would like and what borrowers are able to achieve. If a borrower qualifies in every way for a mortgage loan but has less than a 20% down payment, the lender will usually require mortgage insurance. In this case, the borrower pays premiums to protect the lender, in case the borrower defaults Government mortgage insurance. The Federal Housing Administration (FHA) programs require a down payment of between 3% and 5% of the purchase price of the house. It allows people who otherwise would not be able to buy a home to qualify for a loan and thus increases the proportion of homeowners in the US and the countryÕs reliance on debt financing for housing. If the borrower defaults, the FHA pays the lender the whole loan amount and the property belongs to the FHA. There are maximum price limits so that FHA insurance cannot be used for the purchase of more expensive housing. It primarily assists low-to-moderate-income homebuyers. The advantages for the homebuyer include a much lower down payment, standardized terms, and in many cases, the ability to buy a home Private mortgage insurance (PMI). Private mortgage insurance industry companies take on lower-risk insurance cases and charge a lower premium, so homebuyers prefer to use them when possible. PMI do not, however, insure the entire loan amount. Second, the FHA has a reputation for being cumbersome and slow, so many institutions and borrowers prefer to work with private companies. On the other hand, FHA succeeded in helping to create jobs and has been very popular with the private business sector [1,5,10]
Development of government and private mortgage insurance
Waivers of closing costs
Repudiation of Closing costs are the charges and fees incurred in transferring ownership of a home, including charges by the lender for loan processing and by an attorney to examine the closing costs title. Items that may be included in settlement charges are title search, title insurance, attorneyÕs fees, a property survey, a credit report, points, an appraisal fee, recording fee, state and local transfer taxes, escrow fees, and mortgage insurance. The above mentioned are paid at a meeting between the buyer and seller, representatives of the lender, the real estate broker (if one was involved), and attorneys hired by any and all parties. Closing charges may be 3% of the sales price but vary according to local laws, customs, and lending institution practices [5,10] (continued on next page)
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Table 1 (continued) Rational housing credit access can be expanded through the use of:
Trends of development in Western Europe and USA
A fragment illustrating the development of Lithuanian rational housing credit access
Reduced down payment
In a traditional real estate transaction, a long-term mortgage is secured for part of the cost of the purchase. The difference between the purchase price and the mortgage is the required equity contribution. This equity contribution is often referred to as the down payment. The amount may be reduced if the borrower is able to obtain a second mortgage to offset part of the down payment. In some markets, the most difficult requirement for first-time buyers is the amount required for the down payment. A substantial down payment may be necessary for the financial institution to be willing to make the loan [1,10,13]
Reduction of down payment
Sweat equity
Sweat equity includes the use of voluntary labor to reduce the cash costs of renovation while representing the down payment for each participant. Cases in which the repair costs are high, relative to after-repair market values, sweat equity may be a matter of necessity rather than of choice. Where sweat equity is permitted for significant tasks, proof that the homesteader can perform the work in a satisfactory manner is required. Sweat equity may be one of a few ways that these organizations can acquire ownership or control at prices they can afford. The approach tried by self-help housing groups was to allow the use of voluntary sweat labor to perform most of the construction work under the supervision of paid, skilled and licensed professionals [2]
Development of sweat equity
Mortgage analysts study debt-to-income ratios to learn points at which borrowers become overloaded with debt. The evaluation of existing loans provides a statistical basis for setting lending standards to avoid mortgage delinquency and default. Following the example of ratio-based loan qualification criterion: ‘‘Monthly payments plus other payments for long-term debt should not exceed N% (e.g. 33–36% of monthly income)’’
Development of flexible debtto-income qualifying ratios
Flexible debt-toincome qualifying ratios
Example 1. Title 1 Home Improvement Loan Program (USA). Title 1 loans to be made with higher debt-to-income ratios than most other loans. The maximum debt ratio allowed is 45%. Thus, Title 1 offers an attractive financing alternative to property owners who have good credit but little equity in their homes. It is particularly useful for current purchasers Example 2. Highly energy-efficient homes have a higher initial purchase price than conventional homes, many buyers have been unable to qualify for mortgages for the higher purchase costs, because they result in debt-to-income ratios that lenders consider too high Progress has been made in overcoming this barrier through programs in the secondary mortgage market. These programs now provide incentives to lenders to ÔstretchÕ debtto-income ratios for homebuyers [14]
5.2. Development of quantitative and conceptual databases of housing investment instruments In order to find the most efficient housing investment instruments for a particular country, the countryÕs exhaustive conceptual and quantitative description should be formed. The data then obtained should be subject to multiple criteria anal-
ysis, so as to help to choose the most rational variants. Conceptual descriptions of an investmentÕs instrument life cycle presents textual, graphical, numerical, mathematical and other forms of information about investment instruments. The criteria used for their definition, as well as giving the reason for the choice of this particular system of
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Fig. 5. Some factors and interested parties affecting the efficiency of housing investment instruments.
criteria, their values and weights are also essential. Conceptual information is needed to make a complete and accurate evaluation of the alternatives considered. More useful information and the development a system and subsystems of criteria and defining their values and weights (see Fig. 6) illustrates the development of a conceptual database fragment containing information on housing investment instruments. Quantitative information is based on criteria systems and subsystems, units of measure, values and initial weights. The determination of the utility degree and value of the investment instruments and the establishment of the priority order for its implementation does not present much difficulty if the criteria numerical values and weights are obtained and the multiple criteria decision-making methods are used. The process of determining the above the system of criteria, qualitative criteria initial weights and numerical values of the investment instruments under investigation is based on the use of various expert methods, on the Internet, etc. Quantitative criteria numerical values are obtained by analyzing the data on investment instruments and different documents, Internet, etc. The magnitude of weight indicates how many times one criterion is more/less significant than another in the multiple criteria evaluation of in-
vestment instruments. The results of the comparative analysis of the investment instruments are presented as a grouped decision, forming matrix where columns contain n alternative investment instruments, while all quantitative information pertaining to them is found in m lines (see Table 2). 5.3. Search for rational housing investment instruments and lenders The quantitative and conceptual databases, which are being developed at present, give an exhaustive description of housing investment instruments and allow for their multiple criteria analysis. This helps to determine the investment instrumentÕs efficiency, of the country in question. Moreover, the databases and multiple criteria analysis offered could also be used in the search for efficient lenders. Since the efficiency of alternatives of a housing investment instrument and lender is determined by taking into account much varied information, a multiple criteria analysis should include methods enabling a decision maker to implement a comprehensive analysis of the variants, leading to and making a proper choice. The following methods are aimed at performing this function:
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Fig. 6. A fragment of developing a housing investment instrumentÕs conceptual database.
Table 2 A fragment of developing housing investment instrumentÕs quantitative database Criteria describing the investment instruments
Weights
Measuring units
Compared investment instruments a1
a2
aj
an
Interest rates Period of maturity Down payments Loan repayment and payment of interest
q1 q2 qi qt
m1 m2 mi mt
x11 x21 xi1 xt1
x12 x22 xi2 xt2
x1j x2j xij xtj
x1n x2n xin xtn
Source of finance Subsidies Risk and guarantee Delinquency on loan
qtþ1 qtþ2 qi qm
mtþ1 mtþ2 mi mm
xtþ11 xtþ21 xi1 xm1
xtþ12 xtþ22 xi2 xm2
xtþ1j xtþ2j xij xmj
xtþ1n xtþ2n xin xmn
Utility degree of alternatives
N1
N2
Nj
Nn
Priority of investment instruments
Q1
Q2
Qj
Qn
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• a method for determining the initial weights of the criteria (using expertsÕ methods), • a method for the criteria weights establishment, • a method for multiple criteria analysis and setting priorities, • a method for determining alternatives utility degree. When a certain method (i.e. determining the initial weights of the criteria) is used, the results of the calculations obtained become the initial data for another method (i.e. a method for multiple criteria analysis and setting the priorities). The results of the latter, in turn, may be taken as the initial data for some other methods (i.e. determining housing investment instrument or lender utility degree and providing recommendations). An example, is the utility degree of investigated alternative investment instruments and lenders as determined by using the proposed method [15]. This method assumes direct and proportional dependence on the utility degree of investigated alternatives on a system of criteria describing alternatives, values and weights of the criteria. Experts determine the system of criteria, calculate the values and the initial weights of criteria. Interested parties can correct all this information by taking into consideration their goals and financial capabilities. The assessment results of alternatives fully reflect the initial data jointly submitted by experts and interested parties.
6. Multiple criteria analysis of alternative loans 6.1. Sample application To illustrate the efficiency of the model suggested, a sample problem and solution is given below. Firstly, a study case will be described and the problem formulated. A family of three persons would like to obtain a mortgage loan for purchasing a two-room apartment. An approximate value of the housing to be bought is 96,000–104,000 Litas. The amount of the loan is 80,000 Litas. Then net family income per month is 3200 Litas. The maturity of the loan is 10 years (1 US dollar ¼ 4 Litas 2001).
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Regarding the terms of mortgage loans issued by three financial institutions: the Baltic-American Enterprise Fund, Vilnius Bank and Hermis Bank and take into account the information given below (this will be illustrated using Vilnius Bank as an example). 6.1.1. Vilnius Bank Net income of the family per month. Net monthly family income per capita (without loan installments and interest rate payments) should not be less than 500 Litas. In this case, the average loan repayment and interest rates are 1100 Litas, i.e. 700 Litas per capita. Maximum maturity of the loan. Maximum maturity of the loan is 10 years. An average loan installment per month. When the loan is 80,000 Litas, the average loan installment and interest rate payments are 1100 Litas. Loan interest rates. The annual interest rate on loans, having estimated the maturity and the exposure of the loan, fluctuate from 9% to 11%. This year the interest rate on loans issued for 10 years is 11%. Hypothecation bond fee. In order to secure the liabilities under the loan agreement, the bank accepts a mortgage in the form of the housing to be purchased. Hypothecation bond registration fee, which should be taken into account, is 50 Litas. Hypothecation and notarization fees make about 0.5% of the mortgaged housing value. In this case, the mortgage fee is 450 Litas. A one-off loan administration fee. Here a one-off loan is considered where the administration fee is 400 Litas or 0.5% of the loan. Life insurance. The borrowerÕs life insurance is obtained in favor of the bank for the entire maturity of the loan with an insurance company acceptable to the bank. In our case, this will is 240 Litas per year. Insurance of the housing to be purchased. Insurance of the housing to be purchased is obtained in favor of the bank with an insurance company acceptable to the bank. The annual payment in this case will be 260 Litas. General terms and conditions of the loan. Loans are issued to citizens of the Republic of Lithuania who are 21 years old. The mortgage loan is issued
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and repaid in US dollars, which are exchanged into Litas at the official exchange rate that is fixed by the Lithuanian bank. To obtain the loan one has to open an account with the bank to where their salary is to be transferred. The mortgage loan covers up to 70% of the value of the housing to be purchased. A person needs to obtain a certificate from the office of Children Rights Protection in the event of having children under 18. The consent of the housing ownerÕs spouse to pledge the housing notarized must also be obtained. The initial payment. A person to whom the loan is issued transfers to the bankÕs account the amount covering at least 30% of the value of the housing to be purchased. In our case the first payment is 24,000 Litas. Loan repayment. The repayment of the loan and the payment of interest accrued commences on the month following the disbursement of the loan. The payment will be effected in equal installments or its annuity. On the month of the loan disbursement only the interest must be paid. The deadline of the loan repayment is not charged. The interest margin changes slightly throughout the years subject to the fluctuation of London Inter-Bank Offered Rate (LIBOR) per one US dollar. Loan registration. The borrower will have to fill in an application form for a loan by answering the questions presented on the nine pages of the form. The latter refers to the borrowerÕs actual income, property, members of the family, etc. The borrower will be notified of the bankÕs decision to issue the loan within a week. Commission for anticipatory loan repayment. If the loan is repaid prior to the time when it is due and according to the agreement made, the bank will take a commission for the unpaid interests (0.5% of the amount repaid prior to the loan agreement termination). Commission for currency exchange. Mortgage loans are free from currency exchange transaction fees. The same applies to other cases investigated. A decision making matrix is made (see Table 3) by using the description of the presented conceptual alternatives. The total complex weight of major criteria pertaining to the alternative loans is based on their quantitative and qualitative char-
acteristics and may be determined from the above matrix as well as following Eqs. (1) and (9). The calculation results are provided in Table 3. Because the computer calculates with fuller precision, the values presented here differ somewhat from those stored in the computer memory. 6.2. The complex determination of the weights of the criteria The weights of all criteria must be coordinated, including their quantitative and qualitative characteristics. The weights of quantitative criteria can be exactly coordinated if the values of quantitative criteria are expressed through an equivalent monetary unit. Having performed strict mutual coordination of quantitative criteria weights, the same is done with the weights of qualitative criteria. In this case all the weights of qualitative and quantitative criteria are exactly coordinated at the same time. The calculation of the criteria weights is carried out in seven stages. In stages 1–4 the weights of quantitative criteria are identified, whereas stages 5–7 identify the weights of qualitative criteria. Stage 1. The determination of the sum of values for every quantitative criterion: n X Si ¼ xij ; i ¼ 1; t; j ¼ 1; n; ð1Þ j¼1
where xij is the value of the i criterion in the j alternative of a solution, t is the number of quantitative criteria, n is the number of the alternatives compared. According to expression (1) the sum of values is determined for every criterion which can be represented in money terms. Stage 2. The total monetary expression of every quantitative criterion describing the investigated loan is obtained by Pi ¼ Si pi ; i ¼ 1; t; ð2Þ where pi is initial weight of the i criteria. pi should be measured in such a way as, being multiplied by a quantitative criterion value, an equivalent monetary expression could be obtained. According to their effect on the efficiency of the loan in time, the quantitative criteria may be divided into:
The criteria considered
Quantitative criteria (1) Loan repayment and payment of interest (2) Hypothecation bond registration fee (3) A one-off loan administration fee (4) Life insurance (5) Insurance of the housing to be purchased (6) The initial payment (7) Commission for currency exchange
Measuring units
Numerical values of criteria of the compared loans
Determination of
Baltic-American Enterprise Fund
Vilnius Bank
Hermis Bank
Sum of criteria, Si
Initial weight of criteria, pi
Total monetary expression of criteria, Pi
Weight of criteria, qi
Lt/month
)
1148
1100
1200
3448
120
413760
0.8427
Lt
)
400
450
450
1300
1
1300
0.0026
Lt
)
360
400
350
1110
1
1110
0.0023
Lt/year Lt/year
) )
0 160
240 200
240 200
480 560
10 10
4800 5600
0.0098 0.0114
Lt Lt
) )
16000 400
24000 0
24000 0
64000 400
1 1
64000 400
0.1304 0.0008
V ¼ 490970 Qualitative criteria (8) Maturity of the loan (9) General terms and conditions of the loan (10) Loan registration
Years Points
+ +
10 9.47
10 7.56
10 9.05
– –
0.2536 0.3158
– –
0.2468 0.3073
Weeks
)
6
1
2
–
0.0136
–
0.0132
The sign +/) indicates that a greater/lesser criterion value is better. 1 US dollar ¼ 4 Litas.
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Table 3 Weight determination of criteria, including their quantitative and qualitative characteristics
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• short-term factors affecting the loan for a certain period of time, • long-term factors affecting the loan throughout its life cycle. The initial weight of long-term criteria (i.e. average monthly installment, life insurance, mortgage insurance) depends on the issued loanÕs maturity as well as the monetary expression of a criterionÕs unit of measure. In the case considered the maturity of the loan is 10 years. Pi ¼ efi ;
ð3Þ
criteria, a compared standard value (E) is set. E is equal to the sum of any selected weight of quantitative criteria. One of the main requirements for this comparative standard value is that according to its utility, it is more easily comparable with all qualitative criteria. In this case, the weights of all qualitative criteria are determined by a comparison of their utility with the weight of the compared standard value. E is determined as follows: E¼
g X
ð8Þ
qz ;
z¼1
where e is repayment time of a loan, fi is monetary evaluation of a measure unit of the i criterion. The initial weight of one-off is equal to the monetary expression of the criterion measuring unit. For example, the initial weight of a one-off hypothecation registration fee is equal to one, since this payment is effected only once per 10 years. pi ¼ fi :
ð4Þ
The physical meaning of the initial weight of a quantitative criterion consists of the fact that multiplying the initial weight by the value of a quantitative criterion, its monetary value which expression is calculated over the maturity of the loan (equivalent to former natural expression) is obtained. Stage 3. The overall quantitative criteria magnitude sum expressed in money terms is determined by V ¼
t X
Pi ;
i ¼ 1; t:
ð5Þ
i¼1
Stage 4. The quantitative criteria weight describing the loan which can be expressed in money terms is determined as follows: qi ¼
Pi ; V
i ¼ 1; t:
ð6Þ
The total sum of weight quantitative criteria is always equal to 1: t X
qi ¼ 1:
ð7Þ
i¼1
Stage 5. In order to achieve full coordination between the weights of quantitative and qualitative
where g is the number of quantitative criteria included into the compared standard; qz is the weight of z quantitative criterion which is included in the compared standard. In our case, all qualitative criteria weights were determined by comparing the qualitative criteria weight with the weight of the loan repayment and payment of interest and the initial payment. Stage 6. The initial weight vi of qualitative criteria is determined by expert methods by comparing their relative weight to the weight E of the selected compared standard. If so, the relative weight of qualitative criteria should be expressed in percentages. Stage 7. The weight of qualitative criteria is determined as follows: qi ¼ mi E;
i ¼ t þ 1; m:
ð9Þ
The above method allows for the determination of weights of criteria that are maximally interrelated and depend on qualitative and quantitative characteristics of all criteria. 6.3. The multiple criteria complex proportional evaluation of variants This method assumes direct and proportional dependence of significance and priority of investigated versions on a system of criteria and adequately describe the alternatives on values and weights of the criteria. The system of criteria is determined and experts also calculate the values and initial weights of criteria. Interested parties taking into consideration their pursued goals and the existing capabilities can check and correct all
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this information. The assessment results of alternatives that fully reflect the initial data jointly submitted by experts and interested parties. The determination of significance and priority of alternatives is carried out in four stages. Stage 1. The weighted normalized decisionmaking matrix D is formed. The purpose of this stage is to receive dimensionless weighted values from the comparative indexes. When the dimensionless values of the indexes are known, all criteria, originally having different dimensions, can be compared. The equation is used as shown below: xij qi dij ¼ Pn ; i ¼ 1; m; j ¼ 1; n; ð10Þ j¼1 xij where xij is the value of the i criterion in the j alternative of a solution, m is the number of criteria, n is the number of the alternatives compared, qi is weight of i criterion. The sum of dimensionless weighed index values dij of each criterion xi is always equal to the weight qi of this criterion: n X dij ; i ¼ 1; m; j ¼ 1; n: ð11Þ qi ¼ j¼1
In other words, the value of weight qi of the investigated criterion is proportionally distributed among alternative versions aj according to their values xij . Stage 2. The sums of weighed normalized indexes describing the j version are calculated. The versions are described by minimizing indexes Sj and maximizing indexes Sþj . The lower the value of minimizing indexes the better (loan repayment and payment of interest, hypothecation bond registration fee, a one-off loan administration fee, etc.). The greater the value of maximizing indexes the better (maturity of the loan, general terms and conditions). The sums are calculated as follows: Sþj ¼
m X
dþij ;
Sj ¼
i¼1
i ¼ 1; m; j ¼ 1; n:
m X
dij ;
i¼1
ð12Þ
In this case, the values Sþj (the greater this value, the more satisfied the interested parties) and
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Sj (the lower this value, the better is goal attainment by the interested parties) express the degree of goals attained by the interested parties in each alternative loan. In any case the sums of ÔplusesÕ Sþj and ÔminusesÕ Sj of all alternative loans are always respectively equal to all sums of the weights of maximizing and minimizing criteria by n m X n X X Sþ ¼ Sþj ¼ dþij ; j¼1
S ¼
n X j¼1
i¼1
Sþj ¼
j¼1
m X n X i¼1
dij ;
i ¼ 1; m; j ¼ 1; n:
j¼1
ð13Þ Stage 3. The significance of comparative versions is determined on the basis of describing positive loans (pluses) and negative loans (minuses) characteristics. Relative significance Qj of each loan aj is calculated as follows: P S min nj¼1 Sj ; j ¼ 1; n: ð14Þ Qj ¼ Sþj þ Pn S Sj j¼1 Sjmin Stage 4. Loans priority determination. The greater the Qj the higher the efficiency loan. Since Q1 > Q2 > Q3 then priority of the first version is the best (see Table 4). An analysis of the method presented makes it possible to state that the method may be easily applied to evaluating loans and in selecting the most efficient one, while being fully aware of a physical meaning of the process. Moreover, the method allowed for the formulating of a reduced criterion Qj that is directly proportional to the relative effect of the compared criteria values xij and weight qi on the end result. 6.4. The utility degree of the loans Significance Qj of loan aj indicates the satisfaction degree of demands and goals pursued by the interested parties. The greater Qj the higher the efficiency of the loan. In this case, the significance Qmax of the most rational loan will always be the highest. The significance of remaining loans is lower as compared with the most rational one. This means that total demands and goals of
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Table 4 Multiple criteria evaluation of alternative loans from different financial institutions The criteria considered
Measuring units
Weights
Weighted normalized values of criteria of the compared loans BalticAmerican Enterprise Fund
Vilnius Bank
Hermis Bank
0.2806 0.0008 0.0007 0.0000 0.0033 0.0326 0.0008 0.0823 0.1116 0.0088
0.2689 0.0009 0.0008 0.0049 0.0041 0.0489 0.0000 0.0823 0.0891 0.0015
0.2933 0.0009 0.0007 0.0049 0.0041 0.0489 0.0000 0.0823 0.1066 0.0029
The sums of weighted normalized maximizing indices of the loans Sþj The sums of weighted normalized minimizing indices of the loans Sþj
0.1938 0.3276
0.1713 0.3299
0.1889 0.3557
Significance of loans Qj Priority of loans Utility degree of loans, %
0.5415 1 100
0.5166 2 95.40
0.5091 3 94.02
(1) Loan repayment and payment of interest (2) Hypothecation bond registration fee (3) A one-off loan administration fee (4) Life insurance (5) Insurance of the housing to be purchased (6) The initial payment (7) Commission for currency exchange (8) Maturity of the loan (9) General terms and conditions of the loan (10) Loan registration
Lt/month Lt Lt Lt/year Lt/year Lt Lt Years Points Weeks
) ) ) ) ) ) ) + + )
0.8427 0.0026 0.0023 0.0098 0.0114 0.1304 0.0008 0.2468 0.3073 0.0180
The sign +/) indicates that a greater/lesser criterion value is better. 1 US dollar ¼ 4 Litas.
interested parties will be satisfied to a smaller extent than it would be in case of the best loan. The degree of loan utility is directly associated with the related quantitative and conceptual information. With the increase/decrease of the significance of a loan analyzed, its degree of utility also increases/decreases. The degree of loan utility is determined by comparison of the loan analyzed with the most efficient loan. In this case, all the utility degree values related to the loan analyzed will range from 0% to 100%. This will facilitate a visual assessment of the loanÕs efficiency. The equation used for the calculation of loan aj utility degree Nj is given below: Nj ¼ ðQj : Qmax Þ100%;
ð15Þ
here Qj and Qmax are the significance of the loan obtained from Eq. (14). The degree of utility Nj of loan aj indicates the level of satisfying the needs of the interested parties in the loan. The more goals achieved the more important the goals are and the higher the degree of the loanÕs utility. Since clients are mostly in-
terested in how much more efficient one particular loan is than another then it is more advisable to use the concept of a loan utility rather than its significance when choosing the most efficient solution. The degree of a loanÕs utility reflects the extent to which the goals pursued by the interested parties are attained. Therefore, the utility degree may be used as a basis for determining the loanÕs value. The more objectives attained, the more significant the objectives are, and the higher the loanÕs degree of utility and its value will be. Having determined the ratio of the degree of a utility and the value of a loan, one can see the level of the complex effect that can be obtained by investing money into anyone of the loans. There is complete clarity where better to invest the money and to the efficiency degree of the investment. The results of the multiple criteria evaluation of alternative loans from different financial institutions are given in Table 4. From the values, it can be seen that the first version is the best one. The utility degree N1 ¼ 100%. The second version ac-
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cording to its priority was established as the second best variant. The utility degree of it N2 ¼ 95:40%. The degree of loanÕs utility reflects the extent to which the goals pursued by the interested parties are attained. For example, the significance of the difference between the utility degree of loan 1 (N1 ¼ 100:00%) and loan 3 (N3 ¼ 94:02%) shows that loan 1 is more useful by 5.98% than loan 3. Results acquired after calculation (Table 4) show that the first variant of the loan as per established conditions conformed with clientÕs purposes and needs. This analysis of the loans from different financial institutions was made from client/userÕs position. Taking into consideration the acquired results, various participants of the housing credit may also adjust their decisions in accordance to their priorities and the present conditions.
7. Conclusions The improvement of housing conditions in Lithuania requires access to credit. Barriers to rational credit access for low incomes are among the most important obstacles faced by Lithuanian households in seeking affordable dwelling today. Efforts to expand access to rational housing credit have led to reforms in lending practices of advanced industrial economies and to the creation of alternative credit institutions and instruments. This research is based on the analysis of the expertise of advanced industrial economies and aims at adapting the most rational credit access to Lithuania, by taking into account its specific history, economic development, needs and traditions. The comparative conceptual analysis of housing in developed countries and Lithuania allowed us to identify areas where the situation in Lithuania is comparable, partly comparable or quite different from the level attained by industrially developed foreign countries. This paper also describes methods to be used in searching for rational housing investment instruments and lenders. Based on the above, it is possible to propose an efficient life cycle process model of housing credit access. The basis of the performed search for rational variable credit institutions and instruments is adapted to Lithuanian conditions. On a modelÕs
351
completion, the interested parties will be able to use their financial resources in a more rational manner by considering existing limitations and the possibilities of credit institutions and instruments. When analyzing various models one is always confronted with the question, ÔHow long will they be practically useful?Õ If conditions change considerably, some models inadequately describe the subject of this research. Is this going to happen with the suggested model? Housing investment instruments supply and demand and their efficiency change over time. For example, once Lithuania enters the European Union, new housing investment instruments will emerge. An increase of the countryÕs GDP, growth of salaries, improvement of legal environment, emergence of loan insurance and state guarantees will make it possible to reduce the loan risks. Loan insurance reduces the risks associated with housing loans and therefore, after the establishment of the Housing Loans Insurance Company competition between banks offering housing loans will be increased. Therefore, the interest rates on insured loans are lower than the interest rates on uninsured loans. State guarantees are very important to the market: thanks to the system of guarantees the number of housing loan recipients is growing, the risks to creditors and investment bankers will decrease and businesses and the economy as a whole will expand. As we can see very many micro- and macro-level factors influence the efficiency of housing investment instruments. Therefore, on creating a comprehensive database of investment instruments, it is possible to analyze its efficiency in relation to various interested parties at certain intervals. Based on this analysis it is possible to identify investment instruments best adjusted to the conditions at a given period and to actively implement them in practice. If conditions change, this analysis can be repeated. The suggested model can be effectively implemented also in other countries.
References [1] F. Blankenship, The Prentice Hall Real Estate InvestorÕs Encyclopedia, Prentice Hall, Englewood Cliffs, NJ, 1989.
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