Demand And Supply For Housing

The main determinants of the demand for housing are demographic. However other factors like income, price of housing, cost and availability of credit, consumer preferences, investor preferences, price of substitutes and price of compliments all play a role. The core demographic variables are population size and population growth: the more people in the economy, the greater the demand for housing. But this is an oversimplification. It is necessary to consider family size, the age composition of the family, the number of first and second children, net migration (immigration minus emigration), non-family household formation, the number of double family households, death rates, divorce rates, and marriages. In housing economics, the elemental unit of analysis is not the individual as it is in standard partial equilibrium models. Rather, it is households that demand housing services: typically one household per house. The size and demographic composition of households is variable and not entirely exogenous. It is endogenous to the housing market in the sense that as the price of housing services increase, household size will tend also to increase. Income is also an important determinant. Empirical measures of the income elasticity of demand in North America range from 0.5 to 0.9 (De Leeuw, F. 1971). If permanent income elasticity is measured, the results are a little higher (Kain and Quigley 1975) because transitory income varies from year-to-year and across individuals so positive transitory income will tend to cancel out negative transitory income. Many housing economists use permanent income rather than annual income because of the high cost of purchasing real estate. For many people, real estate will be the most costly item they will ever buy. The price of housing is also an important factor. The price elasticity of the demand for housing services in North America is estimated as negative 0.7 by Polinsky and Ellwood (1979), and as negative 0.9 by Maisel, Burnham, and Austin (1971). An individual household’s housing demand can be modeled with standard utility/choice theory. A utility function, such as U=U(X1,X2,X3,X4,...Xn), can be constructed in which the households utility is a function of various goods and services (Xs). This will be subject to a budget constraint such as P1X1+P2X2+...PnXn=Y, where Y is the households available income and the Ps are the prices for the various goods and services. The equality indicates that the money spent on all the goods and services must be equal to the available income. Because this is unrealistic, the model must be adjusted to allow for borrowing and/or saving. A measure of wealth, lifetime income, or permanent income is required. The model must also be adjusted to account for the heterogeneousness of real estate. This can be done by deconstructing the utility function. If housing services (X4) is separated into the components that comprise it (Z1,Z2,Z3,Z4,...Zn), then the utility function can be rewritten as U=U(X1,X2,X3,(Z1,Z2,Z3,Z4,...Zn)...Xn) By varying the price of housing services (X4) and solving for points of optimal utility, that household's demand schedule for housing services can be constructed. Market demand is calculated by summing all individual household demands. Housing supply is produced using land, labour, and various inputs such as electricity and building materials. The quantity of new supply is determined by the cost of these inputs, the price of the existing stock of houses, and the technology of production. For a typical single family dwelling in suburban North America, approximate percentage costs can be broken down as: acquisition costs 10%, site improvement costs 11%, labour costs 26%, materials costs 31%, finance costs 3%, administrative costs 15%, and marketing costs 4%. Multi-unit residential dwellings typically break down as: acquisition costs 7%, site improvement costs 8%, labour costs 27%, materials costs 33%, finance costs 4%, administrative costs 17%, and marketing costs 5%. Public subdivision requirements can increase development cost by up to 3% depending on the jurisdiction. Differences in building codes account for about a 2% variation in development costs. However these subdivision and building code costs typically increase the market value of the buildings by at least the amount of their cost outlays. A production function such as Q=f(L,N,M) can be constructed in which Q is the quantity of houses produced, N is the amount of labour employed, L is the amount of land used, and M is the amount of other materials. This production function must, however, be adjusted to account for the refurbishing and augmentation of existing buildings. To do this a second production function is constructed that includes the stock of existing housing, and their ages, as determinants. The two functions are summed yielding the total production function. Alternatively an hedonic pricing model can be regressed. The long-run price elasticity of supply is quite high. George Fallis estimates it as 8.2 (Fallis, G. 1985), but in the short run supply tends to be very price inelastic. Supply price elasticity depends on the elasticity of substitution and supply restrictions. There is significant substitutability both between land and materials, and between labour and materials. In high-value locations, multi-story concrete buildings are typically built to reduce the amount of expensive land used. As labour costs increased since the 1950s, new materials and capital intensive techniques have been employed to reduce the amount of relatively expensive labour used. However supply restrictions can significantly affect substitutability. In particular the lack of supply of skilled labour (and labour union requirements), can constrain the substitution from capital to labour. Land availability can also constrain substitutability if the area of interest is delineated (that is, the larger the area, the more suppliers of land, and the more substitution that is possible). Land use controls such as zoning bylaws can also reduce land substitutability.