130 PART • Producers, Consumers, and Competitive Markets TABLE 4.4 PRICE AND INCOME ELASTICITIES OF THE DEMAND FOR ROOMS GROUP PRICE ELASTICITY INCOME ELASTICITY Single individuals −0.10 0.21 Married, head of household age less than 30, child −0.25 0.06 Married, head age 30–39, or more children −0.15 0.12 Married, head age 50 or older, child −0.08 0.19 land.) Table 4.4 lists price and income elasticities for different demographic groups There are significant differences among subgroups of the population For example, families with young household heads have a price elasticity of −0.25, which is more price elastic than the demands of families with older household heads Presumably, families buying houses are more price sensitive when parents and their children are younger and there may be plans for more children Among married households, the income elasticity of demand for rooms also increases with age, which tells us that older households buy larger houses than younger households For poor families, the fraction of income spent on housing is large For instance, renters with an income in the bottom 20 percent of the income distribution spend roughly 55 percent of their income on housing, as compared to 2.8 percent of income for households overall.4 Many government programs, such as subsidies, rent controls, and land-use regulations, have been proposed to shape the housing market in ways that might ease the housing burden on the poor How effective are income subsidies? If the subsidy increases the demand for housing substantially, then we can presume that the subsidy will lead to improved housing for the poor.5 On the other hand, if the extra money were spent on items other than housing, the subsidy will have failed to address policy concerns related to housing The evidence indicates that for poor households (with incomes in the bottom tenth percentile of all households), the income elasticity of housing is only about 0.09, which implies that income subsidies would be spent primarily on items other than housing By comparison, the income elasticity for housing among the wealthiest households (the top 10 percent) is about 0.54 This discussion assumes that consumers choose their expenditures on housing and other goods to maximize their overall satisfaction, where the benefits of housing (and thus the demand for housing) arise from the amount of living space, the safety of the neighborhood, the quality of schools, etc In recent years, however, the demand for housing has been partly driven by speculative demand: People bought homes under the assumption that they can re-sell the homes in the future at a much higher price Speculative demand—demand driven not by the direct benefits one obtains from owning a home but instead by an expectation that the price will increase—has caused housing prices in many parts of the United States to increase sharply, far more than could be justified by demographics Speculative demand can lead to a bubble—an increase in price based not on the fundamentals of demand, but instead on a belief that the price will keep going up Eventually, bubbles burst—the price stops rising as new buyers stop coming into the market, owners of the good become alarmed and start to sell, the price drops, more people sell, and the price drops further As we will see in Chapter 5, bubbles are problematic because they can distort the functioning of a market and lead to financial dislocations when they burst That is what happened to the U.S housing market, which experienced a housing price bubble that finally burst in 2008, leading to mortgage defaults and contributing to the financial crisis that hit the U.S and the global economy in late 2008 This is the starting point of the “affordable” housing debate For an overview, see John Quigley and Steven Raphael, “Is Housing Unaffordable? Why Isn’t It More Affordable,” Journal of Economic Perspectives 18 (2004): 191–214 Julia L Hansen, John P Formby, and W James Smith, “Estimating the Income Elasticity of Demand for Housing: A Comparison of Traditional and Lorenz-Concentration Curve Methodologies,” Journal of Housing Economics (1998): 328–42