Fundamental value and housing policy: a closer look

A sharp increase in Chinese house prices combined with the extraordinary lending growth during the 2000 s has led to concerns of an emerging real estate bubble and impairment of consumer financial well-being. This article studies real house prices relative to fundamental house values. Housing constitutes a large fraction of most household portfolios therefore affect household well-being, and its characteristics are in contrast to what prevails in most financial markets as arbitrage is limited, and hence correction toward fundamental values can be a prolonged process. Using a time-varying present value approach, our findings suggest evidence of bubbles in the Chinese housing market nationally and in representative cities using real-term data. We also find that price dynamics have an important role to play in determining house prices. Moreover, the results reveal that the dominant driving force of house price deviations from fundamental values might be the less than fully rational behavior of investors rather than fundamental factors. This seems plausible in an emerging market such as China.

There are intensive concerns about the causes of rising housing prices in Taipei. The aims of this study are twofold. The first addresses the issue of whether the low-interest-rate policy is adversely driving housing prices in the metropolitan area of Taipei. The second is to investigate if two important housing policies, luxury tax and actual price registration, help to depress the rising residential house prices. With the mega tick data of Taipei city for more than 80,000 residential house transaction records, we examined the factors influencing the actual house prices spanning the period from June 2008 through May 2014. We applied the least squares regression and the quantile regression in the model estimations for housing valuation. In addition, the megadata set is organized in time series and cross-section structures for five subdistricts and the whole Taipei city as well. The empirical results show that low mortgage rates have been the most significant factor for soaring housing prices in Taipei for the past decade. We estimate that a 1% increase in mortgage rates reduces housing prices from 5% to 17%. The actual price registration policy contributes to the decrease in housing prices by 4% to 29%. Housing policy implications are made based on our empirical findings.

Editors' Summary The Brookings Panel on Economic Activity held its eighty-first conference in Washington, D.C., on March 30 and 31, 2006. This issue of the Brookings Papers includes the papers and discussions presented at the conference. The first paper takes a new approach to assessing the boom in home prices, using a model that parallels the one commonly used to value assets such as stocks. The second analyzes labor force participation and its determinants and projects future labor force growth. The third examines changes in wealth by age group and relates them to changes in law and the economy and to demographic characteristics. The fourth examines the present defined-benefits pension system and considers how to reform its regulation and insurance by the federal government. In financial markets the hallmark of a bubble is an asset that is priced far above its fundamental value, which depends on the discounted stream of future cash flows—earnings, dividends, or interest. Differences of opinion about whether or not a bubble exists reflect differences of opinion about the fundamental value of the asset. In the case of owner-occupied housing, there is no readily available, easily estimated analogue to cash flow, and therefore opinions about fundamental value can differ widely. Many observers and market participants have instead focused on the behavior of prices themselves as a way of assessing whether "irrational exuberance" exists in the housing market. During the past five years housing prices have more than doubled in some metropolitan markets and have risen by 50 percent for the United States overall, leading many to conclude that there is a speculative bubble in housing. Those holding this view cite as evidence the sheer magnitude of the price increases, the rise in the ratio of average housing prices to average income, and the more rapid growth of home prices than of rents. In the first article of this volume, Margaret Hwang Smith and Gary Smith argue that all of these are flawed indicators [End Page ix] of a housing bubble because they do not measure prices relative to fundamental values. Using data they have collected on individual homes in ten metropolitan areas, they calculate such a measure from the capitalized value of the stream of services that a home provides. They conclude that, in nearly all the markets they study, home prices remain near or below fundamental values. The authors note that many of the features associated with a bubble as the term is commonly used—prices rising rapidly, a speculative focus on future price increases rather than the asset's cash flow, and the likelihood of an eventual price collapse—could also be present in a bubble defined relative to fundamental values. But not necessarily. Prices can increase rapidly for a considerable period and still remain below fundamental values, as they are likely to do when a significant, unexpected drop in mortgage rates both increases fundamental values and leads to rapid price increases. The authors stress that housing prices are not determined in a smoothly functioning, efficient market rooted in fundamentals. Instead they are influenced importantly by "comps," or the prices of recently purchased comparable homes; appraisers, real estate agents, and buyers and sellers themselves all rely heavily on data from these "comps." In this situation, speculative behavior can lead to rapid price increases or to price declines, and the corrective pull of fundamentals may be very weak. Hence the authors see their calculations as most directly relevant to individuals deciding whether to buy or rent, rather than to those deciding whether to buy or sell now rather than later. They themselves believe that short-run price movements are hard to predict, irrespective of the relationship between current prices and fundamental values, so that market timing is quite risky. The authors provide an extensive discussion of what they call "bub-blemetrics," arguing that most of the measures commonly used to label the current housing situation a bubble are flawed. These include the pervasive use of aggregate measures that ignore the heterogeneity of homes, differences in location and quality, and the use of overly simple measures of affordability. They note that the conclusions of more sophisticated regression models depend on the implicit...

Purpose This paper aims to investigate the impact of financial stress on house price expectations using unit-level observations from novel survey data. Design/methodology/approach The authors use household-level data from the Inflation Expectation Survey of Households of the Reserve Bank of India and the Financial Stress Index (FSI) released by Tracking Asian Integration of the Asian Development Bank. The authors exploit the variations in household price expectations and estimate the impact of lagged FSI on house price expectations. Findings The authors find that increased financial stress results in lower house price expectations and has a stronger impact for the near term vis-à-vis a year ahead. Heterogeneity analysis reveals that a rise in FSI leads to increased expectations of house prices among women. Expectations are lower for the older population and people with less income stability. Asymmetric analysis reveals that house price expectations are more sensitive to high financial stress, offering new insights into the cyclical nature of housing sentiment. Moreover, the equity market and the foreign exchange market have the highest negative impact on house price expectations during financial stress. Practical implications The findings of the association between financial stability, housing prices and credit and house price expectations have crucial implications for the central bank. Originality/value To the best of the authors’ knowledge, this study is the first to examine the impact of FSI on house price expectations observational data. The authors also uncover the heterogenous impact of FSI based on the socio-economic characteristics of the households. The authors further explore the asymmetric and disaggregated impact of FSI on house price expectations.

After considering resource-based cities as the research object, this paper theoretically analyzes the impact of land finance on housing prices and economic growth, considers the mediating role of housing prices, and constructs a random effect model of panel data. A total of 111 resource-based cities with well-developed land and real estate markets were chosen by categorization based on panel data from 2011 to 2019 to investigate the mediating influence of housing prices on land finance and economic growth in resource-based cities. This study presents some findings as follows. Firstly, land finance has a significant positive impact on economic growth and housing prices in resource-based cities, but there are some differences in the degree of impact. In addition, land financing has the greatest influence on economic growth and housing prices in regenerating cities but on the other hand, land financing in mature cities has the least impact on economic growth and housing price. This difference is related to the resource guarantee ability of the city. Secondly, housing prices in resource-based cities and mature cities have significant partial mediating effects on land finance and economic growth. Most importantly, our analysis found that housing prices had no substantial mediating influence on land finance and economic growth in regenerating, growing, and declining cities. These findings add to the literature by enlightening guidance to policymakers and regulatory organizations for the advancement of land financing and economic growth.

Moderate rising of house prices are beneficial to the economic development. However, over high house prices worsen the economic distortions and thus hinder the development of the real economy. We use the stochastic frontier models to calculate the fundamental value in the housing in Chinese large and medium cities, and then obtain indexes which could measure the house prices’ deviations from the fundamental value. With the macroeconomic data in the city-level, this paper empirically investigates the effects of the house prices’ deviations on macro-economic variables like consumption, investment and output. The study reveals that the housing bubble exists in most Chinese cities, and first-tier cities fare the worst. House prices over the fundamental value, which could increase the scale of real estate investment, bring adverse impacts on GDP, as it causes declining civilian consumption and discourages real economy’s investment and production. The encouragement and the discouragement on macroeconomy caused by house prices’ deviation from its basic value take turns to play a key role in the process of China’ eco-nomic growth. In the early stage of China’s economic growth, the encouragement effect predominates. As urbanization and industrialization gradually upgrade to a higher level, the discouragement effect takes charge.

A fall in house prices due to a change in fundamental value redistributes wealth from those long housing (for whom the fundamental value of the house they own exceeds the present discounted value of their planned future consumption of housing services) to those short housing. In a closed economy representative agent model (the special case when the birth rate is zero, of the Yaari-Blanchard OLG model used in the paper), there is no pure wealth effect on consumption from a change in house prices if this represents a change in their fundamental value. When the birth rate is positive, higher fundamental house prices driven by the housing demand of future generations will boost current consumption. There is a pure wealth effect on consumption from a change in house prices even in the representative agent model, if this reflects a change in the speculative bubble component of house prices. Two other channels through which a fall in house prices can affect aggregate consumption are (1) redistribution effects if the marginal propensity to spend out of wealth differs between those long housing (the old, say) and those short housing (the young, say) and (2) collateral or credit effects due to the collateralisability of housing wealth and the non-collateralisability of human wealth. A decline in house prices reduces the scope for mortgage equity withdrawal. For given sequences of future after-tax labour income and interest rates, a fall in house prices will then depress consumption in the short run while boosting it in the long run.

Household finance has been known to be a challenging research area in economics due to difficulties in measuring household behavior and the numerous unpredictable conditions each household faces, such as borrowing constraints and uninsurable income. This dissertation studies how the household consumption behavior has been changed along with the housing market and monetary policy shocks. In Chapter one, the big events and changes that have had huge impacts on consumer finance are presented in chronological order and results from them are examined based on the literature. Tax policies, monetary policies, housing policy and housing markets, and mortgages are chosen as topics that have affected consumer finance and are related to the rest of chapters. Chapter two finds a dynamic linkage between household consumption expenditures and housing prices based on the structural breaks and how the relation has changed along with structural changes. By employing two structural equations, it is tested that any detected structural breaks in relation between housing prices and household consumption appears to make changes in consumer's behaviors. The estimated break dates are 1982Q2 and 1981Q4 with consumer credit from two structural equations. When the mortgage debt is included in the equation, estimated break dates are 2013Q2 and 2013Q1 from each structural equations. This result is in line with the big tax cut in 1981 and housing price crash in 2012 mentioned in the chapter one. Before the 1982Q2, the predictive powers of interest rate and consumer credit for consumption appear. The mortgage debt is statistically significant to explain the total personal consumption expenditures after 2013Q1 which is close to the structural breaks in the volatility of housing price, 2011Q1 where housing prices were the lowest. Thus, this paper finds the apparent evidence of changes in consumption behaviors after the break dates. In chapter three, I use a structural VAR using Gibbs sampling with sign restrictions estimated on quarterly data to investigate the impulse response of households' assets and credits in balance sheets to a monetary policy shock. This paper studies if households may change their consumption behaviors or adjust their portfolios when the value of assets in households' balance sheet changes unexpectedly and borrowing constraints change due to a monetary policy shock. In other words, changes would be expected in the composition of asset portfolios and balance sheets through the credit market after a monetary policy shock. Results show that the reaction of PCE was positive and kept its positive impact for quite a long period, which supports the idea that households do not cut their spending after a monetary policy shock. Also, financial wealth showed a negative impact on the impulse response function. This is consistent with the basic schematic suggested by Elbourne (2008) and added the possibility that households rebalanced their portfolios after a shock rather than cut their expenditures.

Abstract: This paper studies actual (real) house prices relative to fundamental (real) house values. Such a focus is warranted since housing constitutes a large fraction of most household portfolios, and its characteristics are such that, in contrast to what prevails in financial markets, arbitrage will be limited and hence correction toward ‘true’ value is likely to be a prolonged process. Using UK data and a time‐varying present value approach, our results preclude the existence of an explosive rational bubble due to non‐fundamental factors. We further find that intrinsic bubbles have an important role to play in determining actual house prices although price dynamics appear to impact, particularly in periods of strong deviation from fundamental value. Price dynamics are found to be driven by momentum behaviour.

This paper studies fundamental housing values and housing bubbles based on Time-varying Present Value model. Using data of four typical cities in China, our results preclude the existence of housing bubbles in Tianjin and Chongqing. We further preclude the existence of explosive and intrinsic bubbles, but include that of momentum bubbles in Beijing and Shanghai, which accounts for 18.4% and 8.5% of housing price deviations from fundamental values respectively. Housing price monitoring should be strengthened, and consumer's expectation towards housing prices should be properly guided in order to restrict market speculations in China.

Taking cities at prefecture-level and above in China as the research object, we theoretically analyze the effects of land finance on housing prices and economic growth as well as the effects of housing prices on economic growth, consider the mediating role of housing prices, and construct a random-effects model of land finance affecting economic growth. It is of great significance to make rational use of land finance to promote the economic development and formulate the “city specific policies” plan for the real estate market. The 278 resource-based cities with relatively well-developed land and real estate markets in China are selected to test the mediating effect of housing prices on land finance affecting economic growth in resource-based cities by type based on panel data from 2011–2019. The results show that (1) land finance significantly and positively affects economic growth and housing prices in cities at the prefecture-level and above nationwide, but there is some variability in the degree of influence. The central region has the smallest impact on economic growth but the largest impact on housing prices; the eastern region has the deepest impact on economic growth; and the western region has the smallest impact on housing prices. (2) In the national sample cities and cities in the northeast region, housing prices have a significant partial mediating effect at the 1% level on economic growth affected by land finance, accounting for 22.03 and 2.84%, respectively. The mediating effect of urban housing prices on land finance affects economic growth in the eastern, central, and western regions is not significant.

1 Housing Markets and Housing Institutions in a Comparative Context.- Housing Is Peculiar.- Housing Policies Are Special.- The Rationale of this Book.- Metropolitan Markets in National Economies.- A Taxonomy of Housing Policies.- Conclusion.- 2 The Swedish Housing Market: Development and Institutional Setting Alex Anas.- The State, the Counties, and the Municipalities.- Housing Policy.- The Planning System.- Land Use and the Ownership, Supply, and Pricing of Land.- The Housing Stock, Housing Production, and the Building Sector.- Financing of New Construction and Modernization.- Pricing, Rent Control, Rent Pooling, and Rent Negotiations.- The Public Queue: The Case of Greater Stockholm.- Swapping, Black Markets, Mobility, and Household Formation.- Housing Allowances.- Housing and Income Tax.- Conclusions.- 3 The Finnish Housing Market: Structure, Institutions, and Policy Issues.- Historical Background.- Urban Land.- Administration of Housing and Urban Planning.- Housing Production.- Development of the Dwelling Stock and Housing Finance.- Pricing of Housing.- Obtaining Shelter in the Helsinki Metropolitan Area.- Mobility, Household Formation, and the Housing Market.- Housing Allowances.- Housing and the Income and Wealth Taxes.- Conclusions.- 4 The Functioning of the Housing Market in Amsterdam.- An Institutional-Economic Framework.- The City of Amsterdam.- The Development of the Housing System.- Population, Housing, and Mobility in Amsterdam.- The Planning System.- Pricing and Financing.- The Allocation of Households to Dwellings.- The Black Market: Squatting.- Conclusions.- 5 Housing in San Francisco: Shelter in the Market Economy.- The San Francisco Bay Area.- Federal and State Housing Policy.- Regionalism and Localism in Bay Area Land Use and Development 195 Summary and Conclusions.- 6 Analysis of the Housing Sector, The Housing Market, and Housing Policy in the Budapest Metropolitan Area.- The Budapest Metropolitan Area in the Settlement System of Hungary and Central Europe.- Development of the Housing Sector in Budapest.- Housing Quality and the Evolution of Financing.- Conclusion.- 7 The Vienna Housing Market: Structure, Problems, and Policies.- The Structure of the Housing Market in Metropolitan Vienna.- The Governmental Role in the Housing Market.- Conclusion: Major Impacts of Housing Policies.- 8 Glasgow: From Mean City to Miles Better.- The Message and the Medium.- Time's Arrow.- New Pluralism.- Remaking Council Housing.- Conclusion.

The stirrings of reform or more of the same? U.S. Housing Policy, Politics, and Economics shares a stark and urgent message. With a new president in the White House and the economy emerging from its peak pandemic lows, the time is right for transformative federal housing legislation—but only if Congress can transcend partisan divides. Drawing on nearly a century of legislative and policy data, this briefing for scholars and professionals quantifies the effects of Democratic or Republican control of the executive and legislative branches on housing prices and policies nationwide. It exposes the lasting consequences of Congress’ more than a decade of failure to pass meaningful housing laws and makes clear just how narrow the current window for action is. Equal parts analysis and call to arms, U.S. Housing Policy, Politics, and Economics is essential reading for everyone who cares about affordable, accessible housing.

The house price boom that has been present in most Chinese cities since the early 2000s has triggered substantial interest in the role that China’s housing policy plays in its housing market and macroeconomy, with an extensive literature employing both empirical and theoretical perspectives developed over the past decade. This research finds that the privatization of China’s housing market, which encouraged households living in state-owned housing to purchase their homes at prices far below their market value, contributed to a rapid increase in homeownership beginning in the mid-1990s. Housing market privatization also has led to a significant increase in both housing and nonhousing consumption, but these benefits are unevenly distributed across households. With the policy goal of making homeownership affordable for the average household, the Housing Provident Fund contributes positively to homeownership rates. By contrast, the effectiveness of housing policies to make housing affordable for low-income households has been weaker in recent years. Moreover, a large body of empirical research shows that the unintended consequences of housing market privatization have been a persistent increase in housing prices since the early 2000s, which has been accompanied by soaring land prices, high vacancy rates, and high price-to-income and price-to-rent ratios. The literature has differing views regarding the sustainability of China’s housing boom. On a theoretical front, economists find that rising housing demand, due to both consumption and investment purposes, is important to understanding China’s prolonged housing boom, and that land-use policy, which influences the supply side of the housing market, lies at the center of China’s housing boom. However, regulatory policies, such as housing purchase restrictions and property taxes, have had mixed effects on the housing market in different cities. In addition to China’s housing policy and its direct effects on the nation’s housing market, research finds that China’s housing policy impacts its macroeconomy via the transmission of house price dynamics into the household and corporate sectors. High housing prices have a heterogenous impact on the consumption and savings of different types of households but tend to discourage household labor supply. Meanwhile, rising house prices encourage housing investment by non–real-estate firms, which crowds out nonhousing investment, lowers the availability of noncollateralized business loans, and reduces productive efficiency via the misallocation of capital and managerial talent.

Using a new database of consumers’ expectations, this paper examines the nature of house price forecasts across a select sample of European Union (EU) member states for the period 2020 to 2024. Across many EU countries, post COVID-19, house price increases have been apparent. Therefore, understanding the dynamics of house price movements is especially important at this time. In particular, we examine the rationality or otherwise of consumers’ house price expectations, and then examine the relationship between the expectations and forecasts of key fundamental determinants of house prices, such as interest rates and income levels. In this way we distinguish our work from most other studies of house price forecasts, which have not examined links between house price forecasts themselves and forecasts of the variables typically assumed to be determining prices. This is particularly relevant as oftentimes house price expectations themselves are influenced by changes in market fundamentals.