Average House Price Research Articles

The housing crisis and London

City has, from its inception, paid close attention to London, to the ‘World City’ or ‘Global City’ ideologies underwriting its concentration of wealth and of poverty and to challenges from among its citizens to the prevailing orthodoxy. This paper focuses on London's extreme experience of the housing crisis gripping the UK—itself the European nation with the fastest long-term growth of average house prices and widest regional disparities, both driven by overblown financialisation and the privileging of rent as a means of wealth accumulation, often by dispossession. Londoners’ experiences stem partly from four decades of neo-liberal transformation and partly from accelerated financialisation in the last two decades and are now being accelerated by the imposition of ‘austerity’ on low- and middle-income people. The social relationships of tenancy in social housing, private tenancy and mortgage-financed owner-occupation are, however, divisive and the paper ends by identifying what may be the beginning of a unified social movement, or at least a coalition, for change.

Does Tourism Affect House Prices? Evidence from Italy

AbstractThe purpose of the present work is to analyze whether—and to what extent—tourism activity affects urban house price dynamics in Italy. Using a system Generalized Method of Moments (GMM‐SYS) approach and after controlling for socioeconomic characteristics of the local housing markets as well as amenities and disamenities, we test for the effect of tourism by employing a composite index that enables us to capture the complexity of the tourism market. Data consist of yearly observations on the average house prices of 103 Italian cities over the period of 1996–2007. The results confirmed by several robustness checks demonstrate that tourism activity positively affects house prices. In addition, this work provides several first hints that this relationship might not be the same for all types of cities; hence, further developments of the present work should proceed in the direction of searching for different potential regimes through the use of mixture models.

Inequality in housing affordability: Measurement and estimation

This research proposes and examines a new measure for assessing the state of housing affordability inequality. We employ a large micro-level data set by which we estimate and evaluate the time-varying housing affordability inequality in Israel over the period 1992–2011. Results show that our developed housing affordability inequality Gini coefficient has considerably increased in the past decade. Moreover, controlling for changes in net income inequality and macroeconomic conditions, housing affordability inequality is found to positively correlate with average housing prices (computed in net income terms). Outcomes are robust to the alternative Atkinson inequality index. Furthermore, our method allows for an examination of segmentation in housing affordability. We find that segmentation particularly prevails across household head’s gender, family status, working status, the number of income providers in the household and household geographical residence. Research outcomes may direct policymakers in designing policies aiming to reduce inequality and segmentation in housing affordability.

LIBOR, base rate spreads and the UK housing market

Purpose– The purpose of this paper is to analyse how London Interbank Offered Rate Index (LIBOR) and the spread between LIBOR and the base rate of interest as set by the Bank of England (BoE) influences the variation in house prices in the UK.Design/methodology/approach– This paper uses monthly data over a long time series, since 1986, to investigate the relationships between house price and LIBOR. Data are drawn from several different sources to include housing, financial and macro-economic variables. The time series is sub-divided into a series of splines based on stages in the economic and property market cycle. Both value-based and percentage change models are developed.Findings– The results show that BoE base/LIBOR margin variable has a strong positive and significant effect on house price; however, the percentage change model infers a weaker and inverse relationship. The spline analysis re-emphasised the significance of the BoE base/LIBOR margin variable. Where variation between base rates and LIBOR is reduced, a significant positive effect can be observed in the average house price; however, where significant variation exists, the BoE base/LIBOR margin has little effect and LIBOR itself becomes a significant driver.Research limitations/implications– The results highlight that the predictive qualities of the BoE base/LIBOR margin, as the contribution of this margin to the explanation of house price, exceeds both the base rate and LIBOR variables individually. Also highlighted is the contribution of unemployment to the explanation of house price. In both the value and percentage change models, unemployment is shown as a negative and highly significant contributor.Originality/value– Previous papers have demonstrated the important linkage between house price and interest rates, the originality in this paper lies in examining the impact of LIBOR and the spreads between LIBOR and base rate as key variables influencing variation in UK house prices.

Did Monetary Policy Fuel the Housing Bubble in Ireland?

This paper provides empirical evidence of the role of the euro in the genesis of the recent Irish financial-economic crisis caused by a regional housing boom and its inevitable bust. By using a Taylor-rule, estimated by Generalized Method of Moments, we measure the appropriateness of the ECB’s one-size-fits-all policy rate for the Irish economy. A counterfactual analysis suggests that the Irish interest rate should have been on average 6.5% higher. In addition, using a multivariate housing model, we provide econometric evidence for the causal relationship between the low interest rate and the Irish housing boom. Under an alternative sovereign monetary policy, the average house price would have been 25 to 30 percent lower just before the housing bust in the second quarter of 2007. In addition, it shows that a monetary policy tailored to the needs of the member state is enough to prevent housing prices from dramatically increasing and suggests that it is not necessary to include a lean against house price fluctuations in monetary policy strategies.

The Analysis of the Housing Markets in Beijing and Washington, 2005-2014

Since the economic reform of the late 1970s, China has achieved a magnificent economic growth. China’s socialist market economy has become the world’s second largest economy by nominal GDP, reaching 10,380 billion dollars and holding a 13.43 percent share of global GDP. The dramatic growth of economy also has boosted the development of Chinese housing market. But the question remains: Is the Chinese real estate market developing in a positive way? This paper first compares the housing prices in Washington and Beijing using hypothesis test for population means and linear regression model. It is found that despite China’s low housing price in early years, the average housing prices are almost the same in Beijing and Washington area. The most reasonable proposal is that the personal income in Beijing is higher. However, the data and the line chart illustrate that the opposite is actually true. Therefore, in order to further explore the reasons behind the high housing prices in Beijing, the paper then statistically analyzes a series of factors, including per capita income, limited land resources, city functions, unbalanced regional development, the influence of cultural traditions, the government policies, the structure of housing supply, and the investment demand. The last part of the paper points out the problems of the Chinese housing market by looking at the housing price to income ratio and the economic growth trend. The result shows that Chinese housing price has far exceeded common people’s affordability, which has the potential to cause social instability.

The Impact of Foreclosure on Housing Prices

The aim of the study is to explain if the foreclosure effect on prices is explained by a lower quality of foreclosed houses, which is a crucial aspect in the intelligibility of foreclosures. Based on a novel and comprehensive dataset, we estimate the impact of foreclosure on home prices in Florida and Indiana from 2000 to 2008. We employ a model of housing demand, which enables us to flexibly estimate (unobserved) quality as a house-specific fixed effect. We find that house-specific quality explains the vast majority of the foreclosure effects on house prices. Our results also show that foreclosed homes in Florida and Indiana lost a considerable amount of value. For example, foreclosed homes in Fort Lauderdale (Florida) lost, on average, $42; 110 (12 percent) of the average house price in Florida), while foreclosed houses in Lafayette (Indiana) lost $23; 798, which corresponds to 16:1 percent of the average house price in Indiana. The estimation results show a significant degree of heterogeneity. In much of Florida, foreclosed houses lost most value at the upper part of the house size and income distributions. In contrast, foreclosed houses in Indiana lost most value at the lower part of those distributions. Finally, we show that non-foreclosed houses agonized losses (from 0:8 percent to 4:7 percent) due to other houses in the neighborhood being foreclosed.

Comparing Housing Booms and Mortgage Supply in the Major OECD Countries

The house price and lending boom of the 2000s is widely considered to be the main cause of the financial crisis that began in 2007. However, looking to the past, we find a similar boom in the late 1980s which did not lead directly to a global systemic banking crisis – there were widespread banking difficulties in the early 1990s but these were linked mainly to commercial property exposures. This raises the question whether the received wisdom is incorrect, and other factors than the housing boom caused the crisis, while macroprudential policy is overly targeted at the control of house prices and lendingper se.Accordingly, in this paper we compare and contrast the cycles in house prices over 1985–94 with 2002–11. There are more similarities than contrasts between the booms. Stylised facts include a similar rise in real house prices where booms took place, and a marked rise in the real mortgage stock along with real incomes. The aftermath periods are also comparable in terms of house price changes. Econometrically, determinants of house prices are similar in size and sign from the 1980s to date.There remain some contrasts. Leverage rose far more in the later episode and did not contract in the aftermath. Mean reversion of house prices is greater in the earlier period. The earlier boom period showed differences with average house price behaviour which was not mirrored in the most recent boom and inflation was higher. Despite the contrasts, on balance we reject the idea that the recent boom was in some way unique and hence the key cause of the crisis. There is a need for further research to capture distinctive structural and conjunctural factors underlying the recent crisis which differ from the earlier boom and some suggestions are made.

Evaluation of the Affordability Level of State-Sector Housing Built in Iran: Case Study of the Maskan-e-Mehr Project in Zanjan City

AbstractSupplying affordable housing for urban lower- and medium-income classes has always been considered an important planning objective. The policies of Iran’s fourth and fifth development plan (referred to as Maskan-e-Mehr or Kindness Housing Project) is intended to supply more affordable housing for the urban low-income classes. For this purpose, the state sector has strove to reduce the average house price as much as possible through cession of land in cities and new towns surrounding metropolises. In turn, families just have to pay the housing construction. Unfortunately, the lack of suitable services and facilities in these areas has resulted in an increase in household transportation costs. Therefore, the present research work deals with evaluating the affordability level of these houses through a new index of housing affordability, which simultaneously considers housing and transportation costs. The study revealed that high transportation costs that result from inadequate accessibility to public...

Prediction in a spatial nested error components panel data model

This paper derives the Best Linear Unbiased Predictor (BLUP) for a spatial nested error components panel data model. This predictor is useful for panel data applications that exhibit spatial dependence and a nested (hierarchical) structure. The predictor allows for unbalancedness in the number of observations in the nested groups. One application includes forecasting average housing prices located in a county nested in a state. When deriving the BLUP, we take into account the spatial correlation across counties, as well as the unbalancedness due to observing different numbers of counties nested in each state. Ignoring the nested spatial structure leads to inefficiency and inferior forecasts. Using Monte Carlo simulations, we show that our feasible predictor is better in root mean square error performance than the usual fixed and random effects panel predictors which ignore the spatial nested structure of the data.

Analyzing the Dynamical Factors of Housing Price in China

This study tries to explore the main dynamical factors on housing price in China based on various parameters and housing price models. Such parameters covers in this study are GDP, average housing area per person, average house price per meter square, Engel coefficient, etc. A number of data from a number of government departments, research organization and other resources (China Statistics Bureau, Statistical Commission, “Annual Statistical Report of China”, “Annual Statistical Report of Chinese Cities”, “Annual Report of Chinese Cities”, “Annual Statistical Report of Real Estate in China) for establishing benchmarks. The major contribution of this study is to reveal an empirical analysis of the dynamical factors of housing price in China. It also can provide the high reference value for social and economic fields in China.

Why homebuyers have a high housing affordability problem: Quantile regression analysis

Previous researchers discussing housing affordability issues have primarily focused on the housing pressure of the whole society, and most papers on this topic have discussed to a degree on the housing affordability situation of individual households. However, housing affordability involves many problems, and cannot be analyzed using only the average or median housing price. To clearly identify the housing affordability situation of individual households, the individual household housing price-to-income ratio (i.e., the micro PIR) is used in this paper.We used the ordinary least squares model and quantile regression to analyze the micro PIR. The empirical results of this study show that the micro PIR has a right-skewed long-tail distribution. The empirical results revealed that general homebuyers with higher budgets and lower permanent incomes, who have purchased new houses with large amounts of space, located in downtown areas, tend to exhibit relatively higher micro PIR. Moreover, the results suggested that increasing search times or viewing additional houses cannot resolve the housing affordability problem.The 90th quantile result indicated that homebuyers with high micro PIRs may have high budgets and low incomes, and may be purchasing houses to invest. Thus, high housing PIRs may not indicate housing affordability.

Income distribution and housing prices: An assignment model approach

We present a framework for studying the relation between the distributions of income and house prices that is based on an assignment model where households are heterogeneous by incomes and houses by quality. Each household owns one house and wishes to live in one house; thus everyone is potentially both a buyer and a seller. In equilibrium, the distribution of prices depends on both distributions in a tractable but nontrivial manner. We show how the impact of increased income inequality on house prices depends on the shapes of the distributions, and can be inferred from data. In our empirical application we find that increased income inequality between 1998 and 2007 had a negative impact on average house prices in six US metropolitan areas.

Housing Market Responses to Immigration; Evidence from Italy

This study empirically examines the impact of immigration on the dynamics of housing prices across Italian provinces from 1996 till 2007 using the number of valid residence permits as a measure of immigration stock and the self-reported housing values from the Survey of Households Income Wealth in Italy. The massive debate upon the impact of current intensive immigration flows on the well-being of the is mainly focused on labor market outcomes which is, however, only one of the channels through which the real income and wealth can alter. This paper contributes to our understanding of the influence that recent intensive immigration flows have on the housing market in Italy. Moreover, the study exploits different methodological approach with respect to one dominating in migration literature. The obtained results suggest that an increase in immigrant population leads to an increase in average housing prices. Instead, the increase in the concentration of immigrants in the Italian provinces has a positive but declining effect on the average housing prices in provinces. The performed Difference and System GMM estimations confirm both the positive response of average housing prices to the increase in immigrant population and the non-linearity of its response to immigrants’ concentration.

Superstar Cities

We document large long-run differences in average house price appreciation across metropolitan areas over the past 50 years, and show they can be explained by an inelastic supply of land in some unique locations combined with an increasing number of highincome households nationally. The resulting high house prices and price-to-rent ratios in those “superstar” areas crowd out lower income households. The same forces generate a similar pattern among municipalities within a metropolitan area. These facts suggest that disparate local house price and income trends can be driven by aggregate demand, not just changes in local factors such as productivity or amenities. (JEL R11, R23, R31, R52)

Using GIS and Hedonic in the modelling of spatial variation of housing price in Xiamen city

Valuing the built environment with the support of GIS and housing price model is an interesting topic because it connects the spatial thinking with economic concerns. In this paper, we chose the ordinary commercial housing in Xiamen City as our research targets, and the technology of GIS and Hedonic price model were used. Xiamen city is a typical coastal city, and from the research result, we found that the distribution of higher housing price was kept consistent with the coastal areas of Xiamen city. Besides, the average housing price of Xiamen inner-island (the old urban island area) was far higher than the outer-island. To reveal the degree of different spatial elements affecting housing price, we chose 21 variables (three types: location characteristic, structure characteristic and neighbourhood characteristic) and measured them in GIS platform. The Hedonic model showed that the main elements that influencing the price of commodity housings in Xiamen included Property Management Fee, Distance to Commercial Center, Distance to Hospital, Distance to Primary School, Near Village or Not, Near Green space or Not, Near kindergarten or Not. At the end of the paper, we provided three suggestions to balance the spatial variation of housing price in Xiamen City.

The Housing Crisis and Bankruptcy Reform: The Prepackaged Chapter 13 Approach

The housing crisis threatens to destroy hundreds of billions of dollars of value by causing homeowners with negative equity to walk away from their houses. A house in foreclosure is worth 30 to 50 percent less than a house that a homeowner either retains or sells on the market, and a foreclosed house damages neighboring property values as well. We advocate a reform of Chapter 13 that would allow homeowners to strip down the value of their mortgages in a prepackaged bankruptcy. Such a plan would give homeowners an incentive to keep or resell their homes, thus reducing the market value loss of homes while protecting the effective value of creditors' interests. Two further key elements of the plan are that it uses prices based on the average house price in a particular ZIP code, which reduces moral hazard; and it is automated, requiring only a rubber stamp by a bankruptcy judge or other official, thus preserving judicial resources. Other plans, including that of the Obama administration, are compared.

Urban Decline in Rust-belt Cities

Many Rust-Belt cities have seen almost half their populations move from inside the city borders to the surrounding suburbs and elsewhere since the 1970s. As populations shifted, neighborhoods changed—in their average income, educational profile, and housing prices. But the shift did not happen in every neighborhood at the same rate. Recent research has uncovered some of the patterns characterizing the process.

The Impact of Housing Markets on Consumer Debt: Credit Report Evidence from 1999 to 2012

We investigate the impact of large swings in the housing market on nonmortgage borrowing, including student, credit card, auto, and home equity debts. For this purpose, we use CoreLogic geographic house price variation, matched with rich data on consumer liabilities from the Equifax-sourced FRBNY Consumer Credit Panel. The length and timing of our panel allow us to study the consumer debt portfolio response to house price changes during a boom-and-bust cycle of historic magnitude as well as during more ordinary times. In first-differenced instrumental variables estimation, we find that during 1999-2001, homeowners substituted out of nonhousing (largely credit card) debt and into home equity-based debt at a nearly dollar-for-dollar rate in response to house price increases. During the housing boom of 2002-06, however, homeowners abandoned the practice of substituting into less costly debt as equity grew, and instead increased obligations across the board. From 2007-12, sample homeowners experienced a 23 percent average house price decline, and withdrew from home equity debt without adding to non-housing debt. We observe substantial heterogeneity in this pattern: Substitution in both 1999-2001 and 2007-12 ranges from 50 cents to more than dollar-for-dollar for older and prime borrowers, while the decidedly nonprime borrow more modestly, show less evidence of substitution, and shed large amounts of all types of debt from 2007-12. Finally, difference-in-differences and FD-IV estimates are consistent with both 1) a 2012 relative debt overhang of at least $1,800 on average, despite little remaining home equity advantage, for homeowners who experienced a more pronounced boom-and-bust cycle and 2) little substitution out of home equity debt into student loans in response to recent house price declines.

A comparison of hedonic price and stated preference methods to derive monetary values for aircraft noise disturbance and annoyance

This paper compares monetary values for aircraft noise disturbance and annoyance derived using hedonic price and stated preference methods in the same sample areas and over the same sampling time periods. The hedonic price method compares house prices in residential areas across a range of aircraft noise sound levels. The statistical power can be compromised by the many other variables which have significant and often greater effects on prices and because only small fractions of the overall housing stock are bought and sold at any one time. The stated preference method on the other hand, by requiring study participants to trade hypothetical money against hypothetical noise, is entirely based on subjective opinion. It seems that neither method is entirely satisfactory, but there are strong positive correlations between the ratios of aggregated stated preference values to weighted average house prices and LAeq, 16h and similar noise metrics suggesting sufficient underlying similarities