Eight malaysia plan focusing on housing provision

1.0 INTRODUCTION

As for Malaysia, Vision Development 2001 - 2010 has been introduced in order to emphasis on sustainable urban and continue effort to provide the guidelines. In Vision Development Plan, government acts as key player. Meanwhile, Eight Malaysia Plan focusing on housing provision. Plan development and adequate housing and inculcate the citizen understanding 2001 in provision of low cost for all income group towards sustainable development and. Housing development will be integrated with other type of development housing development in line with Local such as industry and commercial. In Agenda 21, the government encourages citizen to participate in 2001 - 2005, emphasis on ICT, encourage more private developers also government as key player in low to construct low medium cost house.

Population and economic growths are two main indicators of real estate market. Positive growth in household and rapid urbanization has several significance implications for housing market especially at the local level. First, demographic mobility is likely to create strong demand for housing. Secondly, rising population and migration will cause serious housing problems especially demand for affordable housing.

Housing needs estimates are a pragmatic device for shaping and implementing public policies. Substantial differences in the treatment of housing needs have occurred over time and between places (Baer 1986, Varady 1996). Housing becomes basic social need as it has been seen as domestic capital, a resource input to the domestic economy. There is an impact of household structure and type upon tenure choice.

Urbanization is a process of expansion in size and population in urban areas. It is associated with changes in economic, social and physical environment of the urban areas. It is also related with the migration of people from rural to urban areas, as well as urban-urban migration. This has resulted in the increased demand of land for houses, commercial complexes, office buildings, industrial properties, recreational facilities, schools, health centres and other public amenity areas. As for the rapid urbanization in the area pose challenges to the urban authority to provide adequate housing to the locals.

Housing needs estimates are a pragmatic device for shaping and implementing public policies. Substantial differences in the treatment of housing needs have occurred over time and between places (Baer 1986, Varady 1996). However, individual studies rarely discuss the alternatives from which they chose their methodology; instead, each study asserts its own implicit definition and approach. In the United States, housing needs estimates are typically prepared for geographic areas governed by municipal or county governments, because it is local governments who control regulation of land use and new development. Although housing construction occurs in localities, the needs are often of regional or state importance. Consequently, preparation of needs estimates can be required by state government, as in California, or by the state judicial system, as in New Jersey. State and regional agencies, or even nonprofit advocacy organizations, also employ housing needs estimates for particular subpopulations as a guide for setting priorities for use of limited public funds. This scenario also implied in Malaysia.

Existing empirical studies of the demand for housing usually based on aggregate cross-section data ignore several crucial features of the urban housing market. First, these studies measure housing consumption in a single dimension, rental payments or housing values, despite the obvious heterogeneity of the housing stock. Secondly, these studies either ignore housing prices completely in focusing on the income-expenditure relation, or they rely upon crude measurements of average housing prices in an entire metropolitan area. The few analyses of the demand for housing based upon micro units such as individual households and dwelling units, have established, not surprisingly that specified types of housing consumers demand particular components of housing services. However, these recent studies have only analyzed the effect of housing prices upon household demand under the implicit assumption that components of housing services may be purchased quite independently of one another.2 Theoretical analyses of residential location and the demand for housing stress the importance of the work trip in determining the spatial location of housing consumption and the quantity of "housing services" demanded, Yet with very few exceptions, these theories ignore the existence of durable and differentiated stocks of residential housing. These theoretical analyses in effect assume that the urban area will be built de novo during any period of analysis. Neglect of the heterogeneity of housing in both residential location and housing demand studies is clearly justified in certain situations, notably in the analysis of comparative statistics when the central focus of the investigation is upon the long-run equilibrium of the entire market for "housing services." Since in the long run housing can be converted or built anew at any site, the convenient notion of undifferentiated "housing services," measured by total monthly expenditures, is appropriate in analyses of both consumer demand and choice of location. Yet it is equally clear that dwelling units emitting the same quantities of "housing services," as measured by contract rent or monthly expenditures, are often viewed as utterly distinct by both housing suppliers and demanders. Indeed, both producers and consumers may view them as much less similar than other units which differ substantially in price. The substantial costs of transforming the characteristics of existing units implies that housing units of various types may barn substantial locational quasirents for long periods of time.

2.0 DEFINITION

Needs and demand are two different terms

2.1 NEED

Need is something necessary for survival such as food and shelter which are important for humans to live a healthy life. Needs are different from wants and can be distinguished because deficiency of need would cause a negative outcome such as dysfunction or death. Needs can be either objective or subjective. Objective needs are physical needs such as food and water while subjective needs are psychological such as the need confidence and achievement.

On a societal level, needs are sometimes controversial issue such as need for a nationalized health care system. There is a theory proposed by Abraham Maslow called Maslow's hierarchy of needs. Five levels of need are classified in this theory; physiological, safety, love/belonging, esteem and self-actualization. The lowest level are the most needed and less needed as it approaches to the top. In this theory, property is considered as the need for safety. In order to be and feel safe, a person must have a shelter.

Myers, Pitkin & Park (2002) explained housing needs as the number and type of housing units required to accommodate a population at a given standard of housing occupancy, the formulation of a quantified estimate of housing needs requires many assumptions that intertwine normative and empirical judgments.

2.2 DEMAND

However, individual studies rarely discuss the alternatives from which they chose their methodology; instead, each study asserts its own implicit definition and approach.

Demandis the desire to own anything and the ability to pay for it and willingness to pay. The term demand signifies the ability or the willingness to buy a particular commodity at a given point of time. Demand is also defined elsewhere as a measure of preferences that is weighted by income. As for the housing demand, the fundamental unit for determining housing demand is the rate of household formation. Projecting household formations and, therefore, the projected demand for housing in a given area requires collecting data on the projected number of households by income, household size, and age of householder. Other quantitative data to be collected for affordable housing development includes age of housing stock, number of substandard housing units, and number of households paying more than 30% of income for rent or owner costs.

There are few factors which affect the demand: good's own price, price of related goods, income, taste or preference and customers' expectations about future prices and income. For example, as compared with flats, houses with gardens provide safe and private areas for play, space for the erection of storage sheds, for hobbies, clothes drying and other domestic cleaning, areas for gardening, including the cultivation of crops which add to the family income, space for other outside activities, and more privacy. Many of these disadvantages can be overcome, at least to some extent, but only at some additional cost. Communal playgrounds, gardens, laundries, drying areas, stores and workrooms can be provided for the residents, dry chutes or the Garchey system can be installed for refuse, and large lifts can be installed to improve access for residents and tradesmen.

3.0 RELATED CONCEPT OF NEED AND DEMAND

There are few related concept in order to determine both housing need and demand. Among those few are concepts of affordability, housing capability and concepts of income elasticity.

3.1 NEED

3.1.1 Concepts of affordability

The capability of a household to purchase a house can be viewed in at least three different ways. There is a distinction between the concepts of purchase affordability, repayment affordability and income affordability. Purchase affordability considers whether a household is able to borrow enough funds to purchase a house. Repayment affordability considers the burden imposed on a household of repaying the mortgage. Income affordability simply measures the ratio of house prices to income. The former two concepts include additional parameters that describe the down payment ratio, the per period mortgage-payment to- income ratio, the length of the mortgage, and the mortgage interest rate. All these parameters are fixed for repayment affordability, with the exception of the mortgage interest rate. By contrast all the parameters in the purchase affordability formula adjust to changes in the mortgage market such as a loosening of credit restrictions.

The distinction between purchase and repayment affordability arises from changes in the mortgage market. In particular, deregulation of the mortgage market has acted to increase average mortgage lengths and the per period mortgage-payment-to- income ratio while reducing average down payment ratios. If house prices remain fixed during this period of deregulation, these changes act to improve purchase affordability without having any impact on repayment affordability. That is, a household with a given initial level of wealth and expected future income stream can now buy a more expensive house that it could previously (i.e., purchase affordability has improved), without any change in the burden of repayment for any particular mortgage (i.e., repayment affordability is unchanged). A fall in the mortgage interest rate when house prices are stable, by contrast, acts to improve both purchase and repayment affordability by increasing the maximum purchase price a household can afford while simultaneously reducing the burden of paying back any particular mortgage. In practice, deregulation of the mortgage market seems to have contributed to the rise in house prices from 1996 to 2006 in the US, Australia and some other countries. That is, rather than improving purchase affordability, deregulation of the mortgage market may have encouraged credit constrained buyers to bid up house prices until the potential gain in purchase affordability is completely nullified. If this is the case, then over this period purchase affordability has remained fairly stable, while repayment affordability has deteriorated.

In the empirical section, we investigate whether this is in fact what happened. Both purchase and repayment affordability are of relevance to policy makers. The availability of either measure without the other can present a misleading impression of what is happening in the housing and mortgage markets. For example, consider again the case discussed above where deregulation of the mortgage market acts primarily to push up house prices. A focus on just purchase affordability, which in this case should be reasonably stable, will mask the fact that households may be becoming more indebted. A focus on just repayment affordability, which in this case has deteriorated, will mask the fact that households are still able to purchase the same range of houses as previously. Income affordability is also of interest. It is easy to calculate and is already widely used. It takes the concept of repayment affordability one step further in that it does not even respond to changes in the mortgage interest rate (except to the extent that this impacts on houses prices and income). Given the mean reverting nature of real interest rates, income affordability in some sense provides a more long-term picture of affordability.

3.1.2 Needs versus affordability approaches

In needs based approaches, output of housing is determined primarily by political/ administrative judgments about the balance between aggregate levels of need and the resources available within public expenditure plans. Distribution of housing tends to be according to some system for measuring priority needs among eligible households, while the type and size of dwelling allocated to individual households is based on a view of what their particular needs are, rather than what they can afford. In this way, needs based approaches break the link between poverty and poor housing, or more generally between income and housing quality.

Implicit in needs based approach is the assumption that price should be no barrier to the consumption of adequate housing. Critics of such approaches, however, argue that in the absence of market pricing signals consumers have no real idea of the true cost of housing, and therefore demand is amplified and distorted. Affordability, or, market based approaches on the other hand start from the position that the production and distribution of housing should reflect what consumers can afford in the market place. Market prices it is argued will attract the level of investment required to meet effective demand, and consumer's demands will be made realistic by the price mechanism.

While needs based approaches tend to generate unmet demand, and require the adoption of ways to ration access or divert excess demand, affordability approaches have the opposite problem to contend with: how to amplify demand among those sections of the population whose lack of resources denies them access to a socially acceptable minimum level of housing (Ermisch, 1984). It is clear, therefore, that the move from needs to affordability based systems is more complex than is implied by arguments about rent to income ratios. In addition to difficult system design choices there are equally challenging implementation problems, as well as interactions with other programme area and with the labour market.

A variable blend of time-series trend, market demand, and normative assumption, housing needs can be expressed in different ways. Estimates are prepared for either of two (sometimes both) essential time periods; estimating the gap or deficit by which current local housing conditions fall short of a normative standard; or estimating the amount, and characteristics, of new construction required to accommodate the projected future population growth at a particular normative standard.

3.2 DEMAND

HH = Hs (Population change) + Current Population (Change in Hs)

Where,

Hs = Headship Rate = the rate at which the population forms households

HH = Households

The total number of household might change over time due to several factors such as population growth, aging children leaving family home, changes in income, housing prices, divorce rate and singles forming housing.

3.2.1 Housing capability

The idea of housing capability can be further expressed by reference to some relevant contexts. First, consider self housing as the dominant type of low and moderate-income housing in many developing countries. Usually self-help housing is evolutionary and progressive within a wider developing economy. Often it begins as meagre shelter with only very basic services: at that stage self-help is sometimes self-build. In time rooms are added, higher standard materials used, and sometimes neighbourhood services and utilities are installed. At this more advanced stage, self-help is largely managed and contracted by the household: it is no longer self-build. Housing capability is also progressively expressed in this process, in sequence covering sanitation, housing design and improvement to meet the personal and societal needs of members, and some improvement of valued neighbourhood amenity.

As a second example, reference can be made to changes occurring in industrial countries and among the middle classes in developing countries. Modern economies place a greater significance upon human capital formation, and as argued by Gershuny (1978) the private and public sectors are increasingly producing goods and services for productive and recreational activities by households. Thus, housing capability is about the provision of study space, the facility for using multi-media and computer electronics, and possibilities of bringing office work home for homework. Much value in housing is about housing capability, closely linked to household structure and household economics. Of course, households and housing can sometimes lack important capability for various reasons and create diswelfare rather than welfare. Such circumstances can then become the objects of policy. Finally, it can be noted that progressive self help housing has potential for modern human capital formation needs and the acceptance of electronic equipment. Self-help housing often has more progressive capability than other types of housing. The idea of housing capability leads towards studies of housing standards in relation to the productivity of housing, especially in human capital formation and childrearing.

4.0 CURRENT NEED

4.1 Current housing deficiencies

They are measured on two different dimensions. One dimension distinguishes between the quality of the physical housing stock, as indicated by such factors as age, presence of complete plumbing, and code violations, and the quality of the fit between households and housing, most often indicated by the ratio of housing payments to income, a measure of affordability, or the ratio of the number of persons to the number of rooms in the unit occupied, a measure of the level of crowding.

Measures of household fit are much more frequently emphasized in the U.S. than those of physical quality. There are likely two reasons for this. For one, the vast improvement of housing quality since 1940 has sharply reduced the incidence of physical problems in the stock (Clemmer and Simonson 1983). Related to this quality improvement, costs have increased, leading to a degradation of housing affordability (Landis and LeGates 2000) and, more recently, to a growing problem of overcrowding (Myers et al 1996).

4.2 Future Construction Needs

The alternative definition is one of future construction needs, representing the additional number of units required to house the projected future growth in population. The estimate is intended to be a credible, policy-relevant projection of future housing requirements. Credibility requires that the projections be both feasible and consistent with observed trends in market behavior and accepted theories of market supply and demand.

Policy relevance requires that they be based on, or related to, meaningful normative standards regarding desired patterns of housing consumption. In practice, future construction is estimated for the population as a whole by a simple translation. Traditionally, the projected population is divided by a current or extrapolated average household size (persons per household). An alternative method which has been widely adopted utilizes separate factors for each age group in the population (Myers 1988). Headship rates, defined as the ratio of householders (formerly termed household heads) per population in each alternative age group, are multiplied by future population numbers in each age group to generate the projected numbers of households expected to be formed by each age group. As will be discussed, there is considerable uncertainty about what set of headship rates to employ for projected periods.

4.3 Joining Existing and Future Needs

Traditionally, the construction needs approach has simply addressed the total housing stock, combining middle and higher income sectors along with the lower income sector. A common approach adopted in recent years to integrate social and future construction needs has been to specify the share of new units required to be produced in different price brackets or for affordability to different income groups. This method assumes that key distributions, such as the ratios of renters to owners and lower income to middle income households, remain constant in the future at the same level as observed in the last census. The distributions from the last census are simply applied to the total projected future households in order to allocate social needs in the future.

4.4 Homeownership Goals

In addition to total and social housing needs, goals for homeownership are of great policy interest. Example, a future population of 10,000 people housed at 2.5 persons per household equals 4,000 housing units expected to be occupied; if the current housing stock is 3,000 units then the construction need is 1,000 units.

One lesson Varady (1996) drew from his study of housing plans in Great Britain was that housing needs needed to be defined for the entire market and not just for the disadvantaged sector. Own homes has been a cornerstone of American housing policy for over half a century. Homeownership has economic and social benefits for owner households as well as civic benefits for the communities in which they live (Green and White 1997, McCarthy et al., 2001). Moreover, as a practical matter in a market economy, production of new housing units requires an expansion of the capacity to own and finance a larger stock of housing units. Future needs for ownership and financial capacity are largely determined by the tenure of the required housing units, whether owned or rented. Inputs of land, materials, and labor also differ markedly for owned and rental units. For these reasons, projections of housing needs usually separately detail the increases in renter and owner occupancies and housing stocks.

5.0 FACTORS CONTRIBUTING NEEDS AND DEMAND OF HOUSING

5.1 NEED

Demographic

Gender

Age

There are large differences in the propensity of adults in various age groups to head, or form, separate households (or be a “householder”). These variations in the ratio of household heads per capita, or “headship rate,” have persisted for over a century and are associated with changes over the life cycle: In late adolescence, people begin to leave their parental homes; in their early twenties, increasing numbers form separate households as incomes rise and families are formed; thereafter, the fraction heading households rises gradually until old age, and eventually begins to decline as people move in with children or into group homes. In 2000, in California, the headship rate at age 15 to 24 years was 11.1 percent and it reached a peak of 63.1 percent for those in the 75 to 84 year age category. (See Figure 1, top line.) Per capita rates of homeownership vary with age for the same life-cycle reasons as headship, though they are lower and rise more gradually in early adulthood. 7 Homeownership is always lower than headship because it is a subset (the remainder of householders being renters).

Status

Race

Occupation

Dependant

Type of house

Factors of buying or renting

Homeownership goals

Although age-specific household headship and ownership rates have persisted for decades, they have not been constant. In California, for example, headship rates at most ages increased between 1960 and 1980, but the next two decades saw declines in early adulthood while rates continued to increase for the older population (Figure 2). Similar but even larger shifts are observed with regard to homeownership rates. Fluctuations in the ratios of housing to population undercut the credibility of projections of housing needs that assume future stability in these rates. If the rates have changed in the past, shouldn't they be expected also to change in the future? Moreover, there persists an urgent policy question about what set of rates is even desirable: should we plan to accommodate the most recent rates, the highest recent rates (implying greater housing well-being), the lowest recent rates (implying lower supply requirements), or whatever trend is extrapolated for the future? Efforts to build credible methods for projecting future housing needs have led to a search for underlying regularities in the data on past housing consumption. Patterns that have been consistent in the past might reasonably be expected to persist in the future and therefore be used to reduce the uncertainty of projections. By making the choice of certain rates seem more reasonable, past regularities can also help focus debate over what is normatively desired. Our approach is to identify past differences in rates across demographic characteristics beyond age and then see whether these differences help to account for recent changes in aggregate headship and homeownership rates.

Suitability

Number of rooms

Location

Adequacy

House size

Housing facilities

Housing conditions

Maintenance

Affordability

Income includes ability to pay, period of payment, amount of payment per month and down payment.

5.2 DEMAND

5.2.1 Determinant of demands

Price of good itself

Price of related goods

Income

Preference

Number of buyers

Expectation of future price

Advertising

Weather

5.2.2 Determinants of supply

Price of good itself

Price of related goods

Price of relevant sources

Technology

Number of sellers

Expectation of future price

Taxes and subsidies

Government restrictions

6.0 CRITICAL SUCCESS FACTORS

6.1 HOUSING ENVIRONMENT

6.2 HOUSING FUNCTION

6.3 HOUSING COMFORT

6.4 HOUSING POLICY

All countries have problems of housing supply but the scale of the problem in developing countries is immense. Twenty one million new housing units are required annually in developing countries just to accommodate housing growth between 2000 until 2010. And, worldwide, 1.1 billion people live in inadequate conditions in urban areas.

As in Malaysia, Ministry of housing and Local Government is responsible for providing such needs. The objectives of the Ministry of Housing and Local Government of Malaysia which are to provide Malaysians of all income levels with affordable and quality shelter by implementing three bottom line sustainable development aspects (economic sustainability, environment sustainability and social sustainability), through the provision of all social services and amenities as well as the funding necessary for the attainment of a better quality of life, national integration and unity (KPKT).

Changes over time and with population size are both central to housing needs. Housing needs are related to population, either directly, on a per capita basis, or indirectly, on a per household basis. Projections of housing needs are based on a population projection, along with specific assumptions about the relationship between population size and the number of housing units that it will occupy. Past changes are the only evidence we have for setting expectations for future changes in the relationship of housing needs to population. Even though much of the following discussion addresses empirical regularities in the past relationship between population and housing, estimates of housing needs are also shaped by policy desires to elevate the housing standards of the population. The analytic use of the observed differences between groups and changes over time unavoidably raises questions of policy. In particular, due to patterns of residential mobility, households over age 45 often selected their current residence a decade or more earlier based on their income at that time, and so their current income becomes less directly linked to their current residence as they age in place.

7.0 STRATEGIC HOUSING PLAN

7.1 Population Projections for Housing Needs

The fundamental driver that generates estimates of future housing needs is projected population growth. In principle, a great many factors could drive future needs, including projected employment growth, housing market projections, political initiatives, or other factors.

For a variety of reasons, however, population projections have been universally adopted as the basis for housing needs projections. One advantage is that people and housing units are so closely linked. Perhaps more important, population projections are widely available and in fact are the most common means by which state and local governments quantify the future for all planning purposes.

7.1.1 Institutional Reliance

Population projections have been highly institutionalized, and projections of housing needs based on those projections have an inherent credibility. The most widely used population projections in the United States are those of federal and state agencies, e.g., the U.S. Bureau of the Census (1996), California State Department of Finance (1998), and Texas State Data Center (2000), which have employed cohort-component methods to project the population by age, sex, and race or Hispanic origin. More recently, to meet rising demands for information on the foreign-born population, the U.S. Census Bureau (2000) issued its first projections of the U.S. population by nativity (i.e., foreign-born or native-born) as well age, race, and ethnicity. One of the authors of this paper has further extended the accounting of immigration status to disaggregate period of arrival (and, implicitly, duration of residence in the U.S.) of the foreign-born population in projections for the U.S. and California (Pitkin and Simmons 1996 and Pitkin 2000)

7.1.2 Accuracy Through Disaggregation

As will be shown in the next section, pronounced differences exist with regard to housing consumption by age, race, ethnicity, nativity, and duration of residence. Whenever the populations of various demographic strata are growing at different rates, projections of housing needs which incorporate the past differences in per capita headship and home ownership rates between the strata are likely to be more accurate than projections based on rates for all strata combined. The existence of suitably disaggregated population projections facilitates the incorporation of these differences into housing needs projections.

7.1.3 Proxy for Income

Economic theory emphasizes income as the factor most directly determining housing consumption. Indeed, mortgage brokers and landlords both know that a certain level of income is required for buyers and tenants to qualify for a given price or rent level of housing. Unfortunately, projections of income are not consistently available or sufficiently reliable for use in housing needs estimates. In any event, the possible inclusion of income does not necessarily raise the reliability or credibility of housing needs projections. Average income is closely correlated with age, race, and ethnicity, factors addressed in population projections. As long as income projections are tied indirectly to ethnicity, race, and age, and housing is related to income level, then of demographic changes serve as a good proxy for changes in average income. Moreover, income actually has much less effect on the current housing of older households than on young households who are newly making housing decisions.6 In this respect, demographic projections possibly serve better than income projections without demographic detail. Thus income may be useful as a policy instrument without adding to the reliability of the projections.

7.2 Calculation of Population Projection

7.2.1 Assumption of Fixed Rates in the Future

The simplest assumption for projections, that rates will remain fixed in the future at their last observed value, in effect ignores the regularity of these trends over time. It has a clear interpretation for projecting housing needs: future generations will attain the same standard of housing (household formation and homeownership) at each age as was achieved by the generation who was that age as of the previous census. Prior to 1980, the implication of this assumption for housing goals was also fairly clear. In view of the sustained increases in headship and homeownership, the backward-looking fixed rate standard was regularly exceeded in the subsequent decade and was therefore conservative; particularly with regard to homeownership rates (see Figure 7). Its implications for overall housing goals in the post-1980 regime are not obvious because of divergent changes at different ages.

There has been, however, a generational pattern in the post-1980 changes in headship and homeownership rates. For cohorts younger than age 45 in 1990, there were declines in headship and homeownership rates, while for those over age 65, there were increases in both rates. Such generational regularities provide the rationale for an alternative assumption and standard for projecting housing needs.

7.2.2 Cohort Dynamic Rates

Generational differences in housing patterns (headship and homeownership) can be carried forward over time and at the same time allow for normal life-course changes as each generation ages. This is accomplished through use of dynamic cohort rates. In this formulation, the life-cycle changes in headship rates are calibrated, for example, to the difference between the headship rate for 65 to 74 year-olds in the 2000 census, say, and the rate for 55 to 64 year olds in the 1990 census. This difference measures the actual change in average headship rate made by a particular group of individuals, or birth cohort, over the 1990s. For purposes of projection into the future, this difference is used to project, say, the headship rate of 65 to 74 year-olds in 2010 starting from the actual rate for 55 to 64-year olds in 2000. In this way, any differences in headship rates between the generation who were 55 to 64 year olds in 1990 and the generation who were that age in 2000 will be carried forward through the life cycle.

In the cohort dynamic model of housing, analogous changes in rates are calculated and applied separately for all ages and race-ethnic classes. An inter-census cohort model for projecting household formation and homeownership was first proposed and implemented for the U.S. by Pitkin and Masnick (1986).

This formulation describes the recent diverging trends in the headship and homeownership rates of younger and older population in California in a credible, consistent manner based on the different conditions that the generations encountered when they entered the housing market. Since 1980, in California, those cohorts coming of age and entering the market in California, the second half of the Baby Boom generation, have encountered higher housing costs than the previous generation, and, as a result, their rates of headship and homeownership have been below those who entered the market in the more affordable 1960s and 1970s. By contrast, the recent continued increases among the elderly (over 65) are in large measure a legacy of the successive increases in middle age (45 to 64) in the 1960s and 1970s. See especially the pattern of changes in homeownership in the lower panel of Figure 7. Cohort models embed an assumption that past advantages or disadvantages in statuses tend to persist as a cohort ages along trajectories that are higher or lower than its successors. The cohort model has a clear interpretation for projecting housing needs: each future generation will progress toward a higher (or lower) standard of housing (household formation and homeownership) at the same net rate (i.e., with similar slopes) as the generation passing between the same ages in the two previous censuses; generational differences are maintained as each cohort tracks on different levels that reflect past advantages or disadvantages.

Because most of the foreign-born population does not enter the housing market when they come of age but instead in the period after they immigrate, the cohort model must be modified for the foreign-born population. Their housing patterns are instead shaped by the market conditions that prevail in the period when they first enter the market. For immigrants who arrive as adults, this period is determined not by when they come of age but by their date of entry in the U.S. The large differences between the headship (and homeownership) rates of recent and less recent immigrants seen in Figures 4 and 5 indicate the importance of this period in immigrants' housing careers. To meet this need, a “double-cohort” model, specifying both birth and period of arrival, of immigrants' housing was specified by Myers and Lee (1996) and further developed by Myers, Megbolugbe and Lee (1998).

A third empirical approach has been used to model changes in per capita household formation over time and can also be applied to homeownership rates. In this alternative, age group rates from past censuses, or surveys, are trended forward. This approach, proposed by Siegel (1972), has been used by the U.S. Census Bureau (e.g., 1996) to project headship rates and households for the U.S.16. When it was developed, i.e. before 1980, headship rates had been rising at all ages and intergenerational differences of the kind we have recently seen had not yet emerged. If applied to California in the post-1990 period, and calibrated to the 1980-1990 changes, this model would imply a continuation of the diverging trends by younger age groups toward lower rates of headship and homeownership and by older age groups toward higher rates (unless future changes are arbitrarily scaled back). This contrasts with the cohort approach, in which increases among the elderly are inherently limited to those cohorts which are already on higher trajectories of headship or homeownership than their predecessors. Furthermore, generational differences, which are especially strong in homeownership, would be blurred.

For these reasons, the method of trended age rates is less credible than either the fixed rate or cohort alternatives. Moreover, projections based on this method lack a clear normative interpretation other than maintaining an arbitrary measure of past progress. This leaves us with two alternative methods for future housing needs that need to be considered. While they have different normative interpretations as bases for future housing needs, both are necessarily empirical compromises between theory, the availability of data, and the requirements of policy-making.

7.2.4Customer profile

Profile of customers must be determined in order to figure out the needs of house for those customers and provide them with the house they wanted. The factors to be considered are age, gender, location, geographic factor, demographic characteristics, family life cycle, desire for relaxation, sport enthusiasts can be called somewhat special because not many people really used to determine profile of customer by considering their sport enthusiasms. Marketing opportunities increase when customer groups with varying needs and wants are recognized. Usually people tend to seek for high quality items with as low price as possible and also convenience for them

8.0 HOUSING SHORTAGES

The principal causes of housing shortages in developing countries are poverty, the sheer scale of population growth and the huge rates of urbanisation that have occurred in recent decades as people move from the countryside into the cities. Even with the most efficient of housing systems, it would be extremely difficult to cope with such poverty and the rate of change, especially in countries that are already very poor.

Neighbourhoods and houses take time to build and only a limited proportion of national income can be devoted to housebuilding. Advanced economies typically devote 3-5% of their national incomes to housing production. Developing countries tend to build more so their housing investment ratios are somewhat higher, but such large allocations mean less for other consumption and investment goods. This creates greater hardship in other aspects of personal consumption and may slow down economic growth.

In developing economies, history shows that crude housing shortages are gradually overcome. Photographs of New York in the midnineteenth century, for example, show what is now Central Park covered in temporary ‘squatter settlements'. Unfortunately, such long-term predictions are of little help to those in need of housing now. In the past, this predicament encouraged politicians to go for the apparent ‘quick-fixes' of rent control and public housebuilding, with the result that private investors were discouraged from providing housing. Housing problems are never completely eradicated, no matter how high the level of economic development. Extra housing is always needed as populations and household numbers change. Houses deteriorate and need replacement and modernisation. Also, in common with other consumption goods, demand for housing is nearly inexhaustible. The higher incomes rise, the more housing people want and the better the locations in which they prefer to live.

Location is important in making housing problems permanent fixtures of social and political life. Demand pressures at highly desired locations are inevitably greater than the available supply. This problem is often neglected in debates over housing policy. People do not want just any sort of housing, they want accommodation that is in an attractive place and convenient for work and other aspects of their life. Therefore housing shortages are, in part, expressions of the fact that many people want to live in the same place. Markets help to sort out such locational preferences through willingness-to-pay. Alternative social criteria on which to base policy when choosing between one person or another to live in a particular location are by no means self-evident. They evolve by custom and practice when they occur in countries with bureaucratically allocated housing tenures and often only seem fair to their beneficiaries and supporters, not to those that lose out.

Even so, the ways in which resources are directed to housing can make a great deal of difference. They affect the amount of housing that can be created, the way it is used and the extent to which housing is maintained and periodically refurbished. As with most other goods and services, a market-led approach is generally superior at directing resources into housing. The profitmotive and people's desire to better themselves can mobilise resources into housing in ways that taxation and government direction cannot.

More choice is available in the market and there are better and more rapid responses to people's changing preferences and needs. Market-based competition, in addition, forces home producers and providers to be efficient and cost effective. The desire for financial gain encourages less wasteful use of the existing stock and promotes continued maintenance and improvement. Locational desires are tested against willingness-to-pay, so that preferred locations are not simply the gain of a politically-privileged few.

9.0 CONCLUSION

There are many theories regarding to housing need and demand. As for Malaysia, there are few that can be applied from other countries as discussed above. As a conclusion, need is something necessary in order to survive while demand is something requested to have better quality item. As discussed within housing scope, the need of housing can be concluded as a shelter that provides basic facilities with minimum rooms which can be dwelled by certain family. While for the housing demand, it is more towards the structural building. As they have the ability to pay, they will request something worth their money. There are many factors to be considered in determining both need and demand such as household size, income, age, demographic and geographic factors and many others. As those factors are determined, then it is easier to build house because their needs and wants are recognized.