Aggregate Housing Demand Research Articles

Credit constraints and college attendance

ABSTRACT This paper shows that housing wealth alleviates credit constraints for potential college attendees by enabling homeowners to extract equity from their property and invest it in education. Using a comprehensive U.S. individual-level survey dataset, we find that one standard deviation increases of housing prices translate into approximately 72,000 more students enrolled in college each year. Our results stay significant when we use proxies for aggregate housing demand shocks and for the topological elasticity of housing supply to generate variation in home equity that should be exogenous to the decision of going to college.

Demographic changes and the housing market

What is the contribution of demographic changes to house prices? We answer this question by analyzing various channels through which changes related to demographics may affect aggregate housing demand and supply differently. Specifically, we focus on the changes in life expectancy, international immigration, urbanization and fertility. As these changes are sustainable and predictable, understanding the role they play in the real estate markets is important for predicting future house prices. We develop and estimate a general equilibrium supply-demand model to evaluate the contribution of these factors and find that they can account for 40.54% of the observed house price growth from 1970 to 2010. Adopting the projection of these four factors provided by Census and the United Nations, we use our model to predict house prices through 2050. We find that the house price will keep growing from 2010 to 2050 by 4.42%–18.85%, depending on urbanization rates and the level of immigration.

Absolute income inequality and rising house prices

AbstractIncome inequality and house prices have risen sharply in developed countries during 1975–2010. In line with theoretical models, we argue that this co-movement is no coincidence, but that inequality has driven up house prices on the grounds that it raises the aggregate demand for housing. Our results suggest that absolute inequality and house prices in most Organisation for Economic Co-operation and Development (OECD) countries were positively correlated and cointegrated, whereas relative inequality and mean income were not significant long-run determinants. This finding indicates that the surge in OECD house prices in part can be explained by a top-income-induced increase in housing demand, and that it is important to consider the interaction of rising mean income and its relative distribution when studying potential correlates of house prices. Moreover, our results confirm previous findings that the short-term real interest rate also is an important correlate of house prices.

A Theory of Housing Demand Shocks

Aggregate housing demand shocks are an important source of house price fluctuations in the standard macroeconomic models, and through the collateral channel, they drive macroeconomic fluctuations. These reduced-form shocks, however, fail to generate a highly volatile price-to-rent ratio that comoves with the house price observed in the data (the “price-rent puzzle”). We build a tractable heterogeneous-agent model that provides a microeconomic foundation for housing demand shocks. The model predicts that a credit supply shock can generate large comovements between the house price and the price-to-rent ratio. We provide empirical evidence from cross-country and cross-MSA data to support this theoretical prediction. Institutional subscribers to the NBER working paper series, and residents of developing countries may download this paper without additional charge at www.nber.org.

북한지역 장기주택수요 및 연관 주택건설투자 추정 (Estimation of Long-term Housing Demand and Related Housing Construction Investment in North Korea)

Korean Abstract: 본고는 북한 사경제의 중요한 부문으로 여겨지는 주택건설 활성화가 앞 으로 지속될 것인지 점검하기 위하여 북한 장기 주택수요와 이와 연관된 주택건설투자의 추세를 추정하였다. 우선 Mankiw-Weil 모형에 의거하여 북한지역 장기주택수요를 추정하였다. 북한이탈주민 설문조사 자료를 기초로 북한 주민의 개인 주택수요를 추정한 후 이를 연령별 인구수에 적 용하여 인구기반 총주택수요를 산출하였다. 이를 통해 북한의 인구기반 총주택수요는 2001~20년중 연평균기준 0.6~0.9%에서 2021~30년중 0.3% 로 증가세가 점차 둔화될 것으로 예상되었다. 한편 2021년 이후 북한이 대외개방을 본격적으로 추진하고 이를 통해 소득수준이 상당폭 개선되는 시나리오를 가정할 경우, 사망률 저하에 따 른 인구증가 효과와 소득증가에 따른 개인의 주택수요 효과가 더해져 2021~30년중 북한의 총주택수요 증가율이 연평균 0.6%p(저성장 시나리 오)~1.8%p(고성장 시나리오) 만큼 추가로 확대되는 것으로 추정되었다. 이를 주택건설투자와 연결해서 보면 주택의 면적기준으로는 10년간 누적 1230(저성장)~3410만평(고성장), 금액기준으로는 28(저성장)~77조원(고 성장) 정도 추가 투자될 것으로 보인다. 이는 북한의 대외개방이 본격화 된다면 주택수요가 큰 폭으로 증가될 수 있어 예상보다 많은 주택건설 투 자가 필요할 것임을 시사한다. Engish Abstract: This paper estimates long-term housing demand and the related housing construction investment in North Korea, to ascertain whether the growth in housing construction investment, which is considered an important part of private economic activity in North Korea, will continue in the future. First, long-term housing demand is estimated based on the Mankiw-Weil model. We then calculate the demographics-driven aggregate housing demand in North Korea, by estimating individuals’ demands for housing using age-based survey data on North Korean defectors, and applying it in view of the age structure of North Korea’s population. According to these estimates, the pace of increase in demographics-driven housing demand shows a gradual slowdown, from an annual average of 0.6% to 0.9% between 2001 and 2020, to 0.3% between 2021 and 2030. This paper next forecasts housing demand and the scale of housing construction in North Korea based on the assumption that the country will pursue external openness on full scale from 2021, and that this will lead to considerable growth in income. If external openness leads to a declining mortality rate and increases in individual demand, then an additional 0.6%p (for the low growth scenario) to 1.8%p (for the high growth scenario) in the annual rate of growth in total housing demand is likely, compared to the baseline scenario. The related housing construction investment is anticipated to show additional increases of 12.3 million pyeong (1 pyeong ≒ 3.3㎡) (low growth scenario) to 34.1 million pyeong (high growth scenario) in terms of area, and of 28 trillion won (low growth) to 77 trillion won (high growth) in terms of amount during the 10 years from 2021. This suggests that, if North Korea’s efforts to open to the world reach full swing, housing demand is likely to grow significantly and more housing construction investment will be needed than is currently projected.

International Real Estate Review

Since the late 2000s, many universities worldwide have seen a significant increase in the number of non-local students. This study examines the aggregate housing demand of those students and their impact on local rentals by using mainland students in Hong Kong as an example. The findings show that students have very different residential patterns and housing demand than other types of residents. Their income elasticity of commuting is close to 0, and they have lower income elasticity of housing demand compared with the local residents. As a group, they exhibit strong patterns of clustered living situations. By applying the differences-in-differences approach, the study finds that the average annual rental price has increased over 10% in neighborhoods with student clusters than in other comparable neighborhoods in recent years.

Accounting for the Decline in Homeownership Among the Young

Homeownership rate for young households in the United States has declined significantly since 1976. An examination of the ownership-age profile of college and non-college households suggests that while college graduates are postponing home purchasing, a large fraction of non-college graduates have become permanent renters. This paper shows that the diverging homeownership dynamics between college and non-college graduates can be accounted for by an inelastic supply of houses combined with a change in the income distribution due to a higher population share of college graduates and a widening gap in household income between college and non-college graduates. The change in the income distribution drives up aggregate housing demand and leads to higher house prices. As a result, non-college graduates find owning less affordable while college graduates with steeper earning profile postpone home purchasing. Using data for the 105 largest metropolitan areas in the U.S. over 1980 to 2010, I find that cities with more college graduates tend to have higher local house prices, lower young homeownership rate for both college and non-college households, and lower middle-aged homeownership rates especially among the non-college households. Moreover, a rise in the household income of college graduates further increases local housing price and lowers homeownership rates for non-college graduates. The changing income distribution can account for the majority of the observed changes in young and middle-aged homeownership rates for both college and non-college graduates.

Age, demographics, and the demand for housing, revisited

The United States is aging, and many baby boomers are reaching or will soon reach the retirement age of sixty-five. At the same time, Millennials—the largest generation in U.S. history—have faced problems of high rents relative to incomes, and volatility in housing markets. These shifts are reigniting debates about how changes in age structure will affect housing and labor markets.To address some of these concerns, we revisit Green and Hendershott (1996) and analyze the links between the willingness to pay for a constant-quality house and demographics using microdata from the 1990 and 2000 Censuses and from the 2006, 2010, and 2014 American Community Surveys. The results generally reconfirm what Green and Hendershott (1996) found; The massive demographic shift will not result in another housing crisis on its own. This is because the education and income levels of current and future seniors are still relatively high, leading them to consume more than previous generations. Also, the size of the Millennial generation will drive the growth of aggregate housing demand, although the growth of per household housing demand may be relatively modest.

Age, Demographics, and the Demand for Housing, Revisited

The United States is aging, and many baby boomers are reaching or will soon reach the retirement age of sixty-five. On the other hand, the Millennials, the biggest generation in the U.S. history, has been experiencing the issues of rental affordability and uncertainty in housing market. Given the shifts, we are again seeing growing debates about how these changes in age structure will affect our housing and labor market.To address the concerns, we revisit Green and Hendershott (1996) and analyze the links between the willingness to pay for a constant-quality house and demographics using the Census 2000 and 2005-2011 American Community Survey 1-Year Public Use Microdata Sample data. The results generally reconfirm what Green and Hendershott (1996) found: The massive demographic shift will not result in another housing crisis. This is because the educational and income levels of the current and future seniors are relatively higher than before, leading them to consume more than previous generations. Also, the size of the Millennial generation will drive the growth of aggregate housing demand, although the growth of per household housing demand may be relatively modest.

House Prices, Home Equity Borrowing, and Entrepreneurship

This paper shows that housing wealth helps alleviate credit constraints for potential entrepreneurs by enabling home owners to extract equity from their property and invest it in their business. Using a large U.S. individual-level survey dataset for the 1996–2006 period, we find that a 10% increase in home equity raises the share of individuals who transition into self-employment each year from 1% to 1.07%. Our results persist when we use proxies for aggregate housing demand shocks and for the topological elasticity of housing supply to generate variation in home equity that is orthogonal to entrepreneurial choice

An Estimation of Long-Term Housing Demand Considering Cohort Effect

Most models of aggregate housing demand assume that households follow demand estimated with a single cross-sectional observation. However, housing demand depends not only on the current social and economic context characterized by stage of life course, or the age, but also on the past socio-economic experiences and physical properties differently formed by generations, or the birth cohort. This study proposes a methodology to estimate aggregate housing demand that reflects inter-generational differences of housing consumption. Using the Korean Labor and Income Panel Study (KLIPS) and Korean Census data, a methodology was developed to determine inter-generational differences of housing demand on the basis of a modified Mankiw and Weil (M-W) model. In the model, birth cohort rather than age group of household members are used as exploratory variables. The estimates are then applied to the process to estimate future housing demand. The results reveal that the post baby-boom generations including the baby boomer are reducing their housing consumption compared to previous generations, and that the aggregate housing demand is smaller than what was estimated using the M-W model.

Evidence on the Relationship between Housing and Consumption in the United States: A State‐Level Analysis

We estimate the dynamic effects of U.S. housing market shocks on state‐level spending and home prices from a dynamic common factor model, and identify housing demand and supply shocks using a sign‐restrictions approach. While state‐level spending and house prices gradually respond positively and persistently to aggregate housing demand shocks, there is significant variation across states in the magnitude of these responses. Cross‐state regressions of the estimated responses on an index of mortgage market development suggest that spending in states with greater opportunities for home equity borrowing is more sensitive to housing demand shocks than in states with fewer opportunities, which is consistent with the prominence of a “collateral” channel over a “wealth” channel in explaining the link between housing and the overall economy.

Evidence on the Relationship between Housing and Consumption in the US: A State-Level Analysis

We estimate the dynamic effects of aggregate US housing market shocks on state-level retail sales and home prices from 1976 to 2008. We use a common factor VAR model to account for the dynamics of the state-level variables, and identify housing demand and supply shocks using a signs-restriction approach. We find that local spending and real house prices generally respond positively but with a lag to aggregate housing demand shocks, that these responses vary significantly across states, and that differences in the level of mortgage market development most likely explain this variation.

Strategic Behavior in Capital Markets and Asset Prices

In this paper we study the impact of the degree of concentration of a financial system on the aggregate demand for housing as well as the feedback effect of the size of the mortgage loan market on lenders’ profits, internal capital accumulation, loan losses and potential bailouts. In a general equilibrium framework with endogenous borrowing constraints, we show that, contrary to the traditional view, competitive lenders can generate larger profits and accumulate more internal capital than monopolistic lenders. Furthermore, in the event of a severe economic downturn, a competitive financial system can withstand a financial crisis just as well as a concentrated financial system. We provide empirical evidence consistent with the main predictions of our model.

Where are the speculative bubbles in US housing markets?

In the first half of this decade, US house prices experienced significant real rates of appreciation. The dramatic increase in house prices led some economists to conclude that there was a speculative bubble in the US housing market. This paper explores how much of the recent appreciation in US house prices was attributable to the fundamental economic determinants of house prices. On the demand side, we note that the rate of homeownership in the US increased from 66.8% in 1999 to 69% in the fourth quarter of 2005. http://www.census.gov/hhes/www/housing/hvs/historic/histt14.html, accessed 10/17/2007. Each percentage point increase in the homeownership rate increases the demand for owner-occupied housing by about one million units. On the supply side, land prices and housing construction costs increased substantially in real terms over this period. The national average increase in house prices conceals significant spatial variation in appreciation rates. According to OFHEO, house prices in some California cities increased by more than fifteen percent per year during this period while house prices in Texas cities increased four percent per year. The increase in aggregate housing demand had different effects on metropolitan area house prices because housing market supply elasticities vary spatially. We estimate housing supply elasticities for 133 metropolitan areas and conclude that although areas on the East Coast and in California had large observed price increases, they owe much of their house price increases to inelastic supplies of owner-occupied housing.

The Demand for Housing in Britain and Population Ageing: Microeconometric Evidence

The paper estimates a household's demand function for housing using household data. Esti- mates of the price and (current) income elasticities are robust at about -0 4 and 0 5 respec- tively. Independent of price and income effects, there is a strong age pattern to household demand. In conjunction with the age profile of household formation, this pattern implies that changes in the age distribution of the population have important effects on aggregate housing demand, although economic growth dominates in determining its rate of growth. During the 1980s there was a dramatic boom in British house prices, followed by large declines in the early 1990s. While financial deregulation and rapid growth in real incomes for people in non-manual occupations contributed to the rise in housing demand and prices, changes in the population's age distribu- tion also played a role (Ermisch 1990). In particular, the number of people in the prime ages for first house purchase increased as a consequence of the baby boom of the 1960s. The fall in birth rates during the 1970s and continued low fertility during the 1980s entail smaller numbers in these prime ages and an ageing of the population more generally. What effect will these changes in the age distribution of the population in Britain have on housing demand and house prices? It may be possible to use aggregate data to answer this question, (e.g. in Fair and Dominguez 1991), but, as recently stressed by Stoker (1993), the most informative assessments of such distributional effects on demand come from studying individual-level cross-section or panel data. A recent study in this vein, by Mankiw and Weil (1989), of the US housing market experience has attracted a great deal of attention because it suggests that house prices are going to fall dramatically in the coming years because of the ageing of the population. While their study estimates an age pattern of housing demand from micro data, they admit it is a biased estimate, and their conclusions concerning the impact of age distribution on house prices are based on a simple, aggregate time-series equation, which omits income and other housing demand and sup- ply shifters. This paper takes a microeconometric approach. It estimates a demand func- tion for housing in Britain, and then examines the implications of prospective changes in the age distribution for housing demand. An important by-product in estimating the demand function is an estimate of the price elasticity of housing demand. Despite the importance of this parameter in assessing the impact of policy changes, estimates of it for Britain are few, and existing ones are questionable, because of the absence of appropriate data for its estimation.

Contents of volume 57

The United States is aging, and many baby boomers are reaching or will soon reach the retirement age of sixty-five. At the same time, Millennials—the largest generation in U.S. history—have faced problems of high rents relative to incomes, and volatility in housing markets. These shifts are reigniting debates about how changes in age structure will affect housing and labor markets.To address some of these concerns, we revisit Green and Hendershott (1996) and analyze the links between the willingness to pay for a constant-quality house and demographics using microdata from the 1990 and 2000 Censuses and from the 2006, 2010, and 2014 American Community Surveys. The results generally reconfirm what Green and Hendershott (1996) found; The massive demographic shift will not result in another housing crisis on its own. This is because the education and income levels of current and future seniors are still relatively high, leading them to consume more than previous generations. Also, the size of the Millennial generation will drive the growth of aggregate housing demand, although the growth of per household housing demand may be relatively modest.

Demography and the demand for housing A reinterpretation of the Mankiw-Weil demand variable

This paper argues that the Mankiw-Weil forecast of a 47% decline in house prices over the period to 2007 is based on a serious misinterpretation of their demand variable. In a time-series context this variable, which comes from a cross-section regression of house values against the age of occupants, is a measure of the adult population, not the demand for housing services or the stock of houses. Econometric work suggests that in addition to adult population, real income, relative prices and real interest rates are important factors determining the aggregate demand for housing. To be credible, forecasts of house prices need to integrate information on demand with information on cost factors and the supply of new houses.

Do Teaser-Rate Adjustable-Rate Mortgages Make Owner-Occupied Housing More Affordable?

In this paper, we estimate the structural parameters of an aggregate housing demand curve and the relationship between ARM teaser rates and house prices using a simultaneous-equation Tobit model. The data come primarily from the Federal Housing Finance Board monthly interest rate survey in May of 1987-1989. The empirical results suggest that teaser ARMs produce significant price distortions in local housing markets. These price distortions ameliorate housing affordability for teaser ARM borrowers and worsen affordability problems for all other homebuyers.

The Specification of Demographic Effects on Housing Demand: Avoiding the Age-Cohort Fallacy

Most models of aggregate housing demand have used cross-sectional estimates to determine variations in demand over the life course and the effects of forecastable changes in population age structure. However, the potential for bias in longitudinal inferences derived from cross-sectional estimates has long been recognized. This note proposes a specification that eliminates such bias by defining a cohort-linked cross section (CLCS) schedule of housing demand from cross sections in successive periods. Estimates using the CLCS specification are found to be more stable over time than comparable cross section-based estimates. They also imply substantially higher levels of future housing demand, relative to the past, than projections based on a purely cross-sectional specification.