Real estate economics

The main participants in real estate markets are:

• Users: These people are both owners and tenants. They purchase houses or commercial property as an investment and also to live in or utilize as a business. Businesses may or may not require buildings to use land. The land can be used in other ways, such as for agriculture, forestry or mining.
• Owners: These people are pure investors. They do not occupy the real estate that they purchase. Typically, they rent out or lease the property to other parties.
• Renters: These people are pure consumers.
• Developers: These people are involved in developing land for buildings for sale in the market.
• Renovators: These people supply refurbished properties to the market.
• Facilitators: This group includes banks, real estate brokers, lawyers, government regulators, and others that facilitate the purchase and sale of real estate.

The choices of users, owners, and renters form the demand side of the market, while the choices of owners, developers and renovators form the supply side. In order to apply simple supply and demand analysis to real estate markets, a number of modifications need to be made to standard microeconomic assumptions and procedures. In particular, the unique characteristics of the real estate market must be accommodated. These characteristics include:

• Durability. Real estate is durable. A building can last for decades or even centuries, and the land underneath it is practically indestructible. As a result, real estate markets are modelled as a stock/flow market. Although the proportion is highly variable over time, the vast majority of the building supply consists of the stock of existing buildings, while a small proportion consists of the flow of new development. The stock of real estate supply in any period is determined by the existing stock in the previous period, the rate of deterioration of the existing stock, the rate of renovation of the existing stock, and the flow of new development in the current period. The effect of real estate market adjustments tend to be mitigated by the relatively large stock of existing buildings.
• Heterogeneity. Every unit of real estate is unique in terms of its location, the building, and its financing. This makes pricing difficult, increases search costs, creates information asymmetry, and greatly restricts substitutability. To get around this problem, economists, beginning with Muth (1960), define supply in terms of service units; that is, any physical unit can be deconstructed into the services that it provides. Olsen (1969) describes these units of housing services as an unobservable theoretical construct. Housing stock depreciates, making it qualitatively different from new buildings. The market-equilibrating process operates across multiple quality levels. Further, the real estate market is typically divided into residential, commercial, and industrial segments. It can also be further divided into subcategories like recreational, income-generating, historical or protected, and the like.
• High transaction costs. Buying and/or moving into a home costs much more than most types of transactions. The costs include search costs, real estate fees, moving costs, legal fees, land transfer taxes, and deed registration fees. Transaction costs for the seller typically range between 1.5% and 6% of the purchase price. In some countries in continental Europe, transaction costs for both buyer and seller can range between 15% and 20%.
• Long time delays. The market adjustment process is subject to time delays due to the length of time it takes to finance, design, and construct new supply and also due to the relatively slow rate of change of demand. Because of these lags, there is great potential for disequilibrium in the short run. Adjustment mechanisms tend to be slow relative to more fluid markets.
• Both an investment good and a consumption good. Real estate can be purchased with the expectation of attaining a return (an investment good), with the intention of using it (a consumption good), or both. These functions may be separated (with market participants concentrating on one or the other function) or combined (in the case of the person that lives in a house that they own). This dual nature of the good means that it is not uncommon for people to over-invest in real estate that is, to invest more money in an asset than it is worth on the open market.
• Immobility. Real estate is locationally immobile (save for mobile homes, but the land underneath them is still immobile). Consumers come to the good rather than the good going to the consumer. Because of this, there can be no physical marketplace. This spatial fixity means that market adjustment must occur by people moving to dwelling units, rather than the movement of the goods. For example, if tastes change and more people demand suburban houses, people must find housing in the suburbs, because it is impossible to bring their existing house and lot to the suburb (even a mobile homeowner, who could move the house, must still find a new lot). Spatial fixity combined with the close proximity of housing units in urban areas suggest the potential for externalities inherent in a given location.

The housing industry is the development, construction, and sale of homes. Its interests are represented in the United States by the National Association of Home Builders (NAHB).[1] In Australia the trade association representing the residential housing industry is the Housing Industry Association.[2] It also refers to the housing market which means the supply and demand for houses, usually in a particular country or region. Housing market includes features as supply of housing, demand for housing, house prices, rented sector and government intervention in the Housing market.

The main determinants of the demand for housing are demographic. But other factors, like income, price of housing, cost and availability of credit, consumer preferences, investor preferences, price of substitutes, and price of complements, 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, which 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 1971). If permanent income elasticity is measured, the results are slightly 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 costliest 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 modelled with standard utility/choice theory. A utility function, such as U=U(X1,X2,X3,X4,...Xn), can be constructed, in which the household's 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 household's 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 saving. A measure of wealth, lifetime income, or permanent income is required. The model must also be adjusted to account for the heterogeneity of real estate. This can be done by deconstructing the utility function. If housing services (X4) are separated into its constituent components (Z1,Z2,Z3,Z4,...Zn), 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, the household's demand schedule for housing services can be constructed. Market demand is calculated by summing all individual household demands.

A customer perusing real estate listings at an agent's office in Linxia City, China

Developers produce housing supply 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, one can assign approximate cost percentages as follows: 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 follows: acquisition costs, 7%; site improvement costs, 8%; labour costs, 27%; materials costs, 33%; finance costs, 3%; administrative costs, 17%; and marketing costs, 5%. Public-subdivision requirements can increase development costs 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, a hedonic pricing model can be regressed.

The long-run price elasticity of supply is quite high. George Fallis (1985) estimates it as 8.2, 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, developers can typically construct multi-story concrete buildings to reduce the amount of expensive land used. As labour costs have increased since the 1950s, new materials and capital-intensive techniques have been employed to reduce the amount of 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 (i.e., 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.

The basic adjustment mechanism is a stock/flow model to reflect the fact that about 98% the market is existing stock and about 2% is the flow of new buildings.

In the adjacent diagram, the stock of housing supply is presented in the left panel while the new flow is in the right panel. There are four steps in the basic adjustment mechanism. First, the initial equilibrium price (Ro) is determined by the intersection of the supply of existing housing stock (SH) and the demand for housing (D). This rent is then translated into value (Vo) via discounting cash flows. Value is calculated by dividing current period rents by the discount rate, that is, as a perpetuity. Then value is compared to construction costs (CC) in order to determine whether profitable opportunities exist for developers. The intersection of construction costs and the value of housing services determine the maximum level of new housing starts (HSo). Finally the amount of housing starts in the current period is added to the available stock of housing in the next period. In the next period, supply curve SH will shift to the right by amount HSo.

The diagram to the right shows the effects of depreciation. If the supply of existing housing deteriorates due to wear, then the stock of housing supply depreciates. Because of this, the supply of housing (SHo) will shift to the left (to SH1) resulting in a new equilibrium demand of R1 (since the number of homes decreased, but demand still exists). The increase of demand from Ro to R1 will shift the value function up (from Vo to V1). As a result, more houses can be produced profitably and housing starts will increase (from HSo to HS1). Then the supply of housing will shift back to its initial position (SH1 to SHo).

The diagram on the right shows the effects of an increase in demand in the short run. If there is an increase in the demand for housing, such as the shift from Do to D1 there will be either a price or quantity adjustment, or both. For the price to stay the same, the supply of housing must increase. That is, supply SHo must increase by HS.

The diagram on the right shows the effects of an increase in costs in the short-run. If construction costs increase (say from CCo to CC1), developers will find their business less profitable and will be more selective in their ventures. In addition some developers may leave the industry. The quantity of housing starts will decrease (HSo to HS1). This will eventually reduce the level of supply (from SHo to SH1) as the existing stock of housing depreciates. Prices will tend to rise (from Ro to R1).

There are different ways of real estate financing: governmental and commercial sources and institutions. A homebuyer or builder can obtain financial aid from savings and loan associations, commercial banks, savings banks, mortgage bankers and brokers, life insurance companies, credit unions, federal agencies, individual investors, and builders.

Over the last decade, residential prices increased every year on average by double digits in Beijing or Shanghai. However many observers and researchers argue that fundamentals of the housing sector, both sector-specific and macroeconomic, may have been the driving force behind housing price volatility.[3]

• Affordable housing
• Affordability of housing in the United Kingdom
• Australian property market
• Effective gross income
• Investment rating for real estate
• Real estate trends
• Real estate business
• Short sale (real estate)
• Real estate development
• Real estate bubble
• United States housing bubble

• Bourne, L. S. and Hitchcock, J. R. editors., (1978) Urban Housing Markets :Recent directions in research and policy, University of Toronto Press, Toronto, 1978.
• De Leeuw, Frank (1971). "The Demand for Housing: A Review of Cross-Section Evidence". The Review of Economics and Statistics. 53 (1): 1–10. doi:10.2307/1925374. JSTOR 1925374.
• Fallis, G. (1985) Housing Economics, Butterworth, Toronto, 1985.
• Harris, Richard (2016). "The Rise of Filtering Down". Social Science History. 37 (4): 515–549. doi:10.1017/S0145553200011950.
• Kain J. F. and Quigley J. M. (1975) Housing Markets and Racial Discrimination, National Bureau of Economic Research, New York.
• Kawaguchi, Y., (2013), Real Estate Economics, Seibunsha, Tokyo.
• Kawaguchi, Y., (2001), Real Estate Financial Engineering", Seibunsha, Tokyo.
• Maisel, Sherman J.; Burnham, James B.; Austin, John S. (1971). "The Demand for Housing: A Comment". The Review of Economics and Statistics. 53 (4): 410–413. doi:10.2307/1928748. JSTOR 1928748.
• Muth, R. (1960) “The demand for non-farm housing”, in A.C.Harberger, ed., The demand for durable goods, University of Chicago Press, Chicago, 1960.
• Olsen, Edgar O. (September 1969). "A Competitive Theory of the Housing Market". The American Economic Review. 59 (4, Part 1): 612–22. JSTOR 1813226.
• Polinsky, A. Mitchell; Ellwood, David T. (1979). "An Empirical Reconciliation of Micro and Grouped Estimates of the Demand for Housing". The Review of Economics and Statistics. 61 (2): 199–205. doi:10.2307/1924587. JSTOR 1924587.

• Humboldt Real Estate Economics : real estate market conditions in Humboldt County, California by the Department of Economics at Humboldt State University.
• Grant Thornton International Business Report : 2008 Construction and real estate industry focus
• Numbeo: user-contributed database about worldwide housing / real estate prices and its indicators
• Jose Francisco Bellod Redondo, University of Malaga, Detection of real estate bubbles: the Spanish case: performance of Spanish housing market between 1989 and 2009 (in Spanish), May 2011
• Diana Rádl Rogerová; Filip Endal; Petr Hána; Pavel Novák (May 2012). "Overview of European Residential Markets" (PDF). Deloitte Czech Republic.