Air pollution and the housing market: A neural network approach

Using the neural network method, this research explores the impact of total suspended particulate (TSP) and sulfur dioxide (SO₂), two major air pollutants, and of air pollution controls on the median real price of housing in Jacksonville, Florida. The results of this case study confirm the adverse effect of air pollution on the price of housing. The simulation of the model further suggests that pollution control measures improve property values. The findings imply that, in addition to other measures influencing the price of housing, property owners and buyers take air pollution and pollution controls into account.     

Canadian city housing prices and urban market segmentation

Abstract .  This paper provides a detailed empirical analysis of Canadian city housing prices. We examine the long-run relationship between city house prices in Canada from 1985 to 2005 as well as idiosyncratic relations between city prices and city-specific variables. The results suggest that city house prices are only weakly correlated in the long run and that there is a disconnect between house prices and interest rates. City-specific variables such as union wage levels and the issuance of building permits tend to be positively related to existing city house prices. Surprisingly, there is mixed evidence with respect to standard measures of economic activity such as per capita GDP and interest rates.     

House prices,land prices,the housing market and house purchase debt in the UK and other countries

This paper brings together information about house prices, land prices, housing market transactions, house purchase debt and personal savings for a number of countries and compares them with those in the UK to see to what extent conditions in the UK are unique and how far something similar is to be observed in the countries of Europe and North America     

Superstition and real estate prices: transaction-level evidence from the US housing market

We investigate the impact of superstition on prices paid by Chinese-American home buyers. Chinese consider 8 lucky and 4 unlucky. Lacking explicit buyer ethnicity identifiers, we develop a binomial name classifier, a machine learning approach applicable to any data set containing names, that allows for falsification tests using other ethnic groups, and mitigates ambiguity from the transliteration of Chinese characters into the Latin alphabet. Chinese buyers pay 1–2% premiums for addresses including an 8 and 1% discounts for addresses including a 4. These results are unrelated to unobserved property quality; no premium exists when Chinese sell to non-Chinese. The persistence of superstitions reflects the extent of cultural assimilation.     

Ripple effect in house prices and trading volume in the UK housing market: New viewpoint and evidence

This study adopts the data of house prices and trading volume in the overall UK housing market and in the housing markets in the 10 major regions in the UK to estimate the ripple effect in the trading activities in the housing markets. First, this study details why the ripple effect occurs in the housing market price and volume using static and cobweb dynamic models. The results of the panel-based unit root tests indicate that the relative price and volume ratios show constancy, signifying that long-run equilibrium relationships exist between the regional and national housing markets in the UK. The frequency of the transaction volume convergence behavior is higher than that of the overall house prices.     

Seoul housing prices and the role of speculation

Between June 1998 and March 2006, the price index of apartment houses in Seoul, Korea, more than doubled, while fundamentals such as GDP, wage, and population increased by less than 35%. This study examines the role of a rational speculative bubble in this price surge. We find that unobservable information explains part of the price volatility; and that a rational bubble proxy is a significant driver of prices. However, neither latent information nor rational bubble is enough to explain the recent housing price appreciation, even in conjunction with observable fundamentals.     

A hedonic analysis of the impact of LUST sites on house prices

Petroleum from leaking underground storage tanks (LUSTs) can contaminate local soil and surface and groundwater. This can pose health risks to the surrounding population. Focusing on single family home sales from 1996 to 2007 in three Maryland Counties, we use a hedonic house price model and a difference–in-difference approach to estimate the willingness to pay to clean up the LUST sites. Particular attention is given to how property values are affected by leak and cleanup activity at a LUST site, the severity of contamination, the presence of a primary exposure pathway (i.e., private groundwater wells), and publicity surrounding a LUST site. The results suggest that although the typical LUST may not significantly affect nearby property values, more publicized (and more severe) sites can decrease surrounding home values by more than 10%.     

Modelling the housing market in OECD countries

Recent episodes of housing bubbles, which occurred in several economies after the burst of the United States housing market, suggest studying the evolution of housing prices from a global perspective. We utilise a theoretical model for the purposes of this contribution, which identifies the main drivers of housing price appreciation, such as, for example, income, residential investment, financial elements, fiscal policy and demographics. In a second stage of our analysis, we test our theoretical hypothesis by means of a sample of 18 OECD countries from 1970 to 2011. We employ the vector error correction econometric technique in terms of our empirical analysis, which permits us to model the long-run equilibrium relationship and the short-run dynamics, which also helps to account for endogeneity and reverse causality problems.     

Behavioral heterogeneity in the Australian housing market

We propose a heterogeneous agent model (HAM) of four groups of investors with Markov chain regime-dependent beliefs for the housing market. Within the Markov switching framework, we take into account how heterogeneous investors shift their trading behaviour in response to changes in housing market conditions. The model is estimated and compared with the benchmark rational expectation models using the Australian housing market data from 1982Q1 to 2013Q2. We find evidence of within- and between-group heterogeneity in the Australian housing market. We show that HAM with Markov switching beliefs provides a better in-sample estimation efficiency and outperforms the conventional rational expectation models in terms of out-of-sample prediction.     

The value of remoteness: a hedonic estimation of ranchette prices

Throughout the western United States, production ranches are being subdivided into recreation-oriented ‘ranchettes’. This change has dramatic impacts on local environmental and economic viability. Ranchettes fall in a gap in the economic literature between production agriculture and residential uses. This paper presents the first hedonic model for ranchettes, introducing the use of remote sensing vegetative indices and the use of sale status of adjacent ranchettes as explanatory variables. Parcel level sale data in Yavapai County, Arizona is combined with satellite greenness indices. It is found that increased greenness raises sale prices. Access to roads, cities, and neighbors also increase sale prices, implying that isolation is a disamenity and that it may be beneficial for policymakers to encourage ranchette grouping.     

我国住宅业的市场前景预测

一、我国住宅业市场前景广阔 据统计,这些年我国每年在房地产的投资约3000亿元人民币。至1999年全国商品住宅的施工面积达到11879万平方米,比1998年的9539万平方米增加了24.5％。如果从全国的主要城市来看,住宅开工量的增长更为迅速。与1997年相比,天津     

Using house prices to compute the price of housing in the CPI

Rental-equivalence is often used in computing price changes of owner-occupied housing in the CPI. We use an alternative approach, employing interest-adjusted house prices. For Norway 2000–2008 our method yielded a 30% CPI-increase, compared to the official 17%.     

Motivated sellers and predation in the housing market

We develop an equilibrium search model of the housing market where sellers may become distressed as they are unable to sell. A unique steady state equilibrium exists where distressed sellers attempt liquidation sales by accepting prices that are substantially below fundamental values. During periods where a large number of sellers are forced to liquidate customers exhibit ‘predation’: they hold off purchasing and strategically slow down the speed of trade, which in turn causes more sellers to become distressed. The model naturally suggests several proxies of liquidity. Interestingly, the average time on the market (TOM), one of the most frequently used statistics in the literature, does a poor job within the context of liquidation sales and predation. Specifically we show that TOM falls during periods of predatory buying, which, if interpreted on face value, indicates that the market becomes more liquid with predation. We propose an alternative proxy – the profit loss in fire sales – which appears to be a more robust measure of liquidity than TOM.     

The external cost of asbestos in the housing market

This study uses a Generalized Method of Moments spatial error hedonic model to estimate the potential impact of asbestos on residential property prices. The analysis examines a large sample of 32,403 housing sales occurring between 2008 and 2015 in a fast-growing Coastal Alabama region. Results indicate the presence of asbestos depreciates house values by 13.44%, translating into an external cost of approximately $25,300 per property.     

Capital asset prices in an oligopolistic market

The author wishes to thank Kalyan Chatterjee, George Monahan, Martin Shubik, and a referee for helpful comments on an earlier version of this paper.     

Expectation,volatility and liquidity in the housing market

Measuring housing price volatility is fundamental to understanding the dynamics of housing price risk. This article aims to explore whether a liquidity factor plays a role in explaining the second moment (i.e. the volatility) of housing prices. Housing price volatility is measured as the conditional variance of a Generalized Auto Regressive Conditional Heteroscedasticity (GARCH) model under the Adaptive Expectations framework. The empirical evidence reveals that volatility transmits from smaller housing units to larger housing units, which indirectly supports the trade-up effect discussed in the literature. In addition, less liquid housing classes are more sensitive to unexpected liquidity shocks, and the starter housing class is extraordinarily sensitive to negative liquidity shocks. Consistent with friction search theory, pricing errors are alleviated as the trading volume increases, because the valuation price tends to be more accurate as more information is available.     

Testing for rational bubbles in the US housing market

The presence of a bubble in the US housing market prior to the 2007 subprime mortgage financial crisis is investigated. This is done by looking into the relationship between house prices and rental prices, known as the price–rent ratio, which is an important measure of a potential deviation between house prices and its fundamental value. Additionally, the interest rate is taken into account since it is an important factor in determining demand for housing mortgages and thereby influencing house prices, and explosive behavior of house prices is considered. These relationships are investigated through a theoretical and econometrical framework. The empirical evidence suggests that there was a bubble in the housing market prior to the financial crisis, even when controlling for the decreasing interest rate and the fundamental information given by the rental price in the period. Explosiveness was the main source of the price increase, such that a bubble was present in the housing market after correcting for other fundamental factors. The econometric procedures used in the analysis may therefore be relevant for monitoring the housing market.     

Outsiders,insiders and interventions in the housing market

In the wake of China’s “great migration,” many cities, including Beijing and Shanghai, restrict some residents from owning housing, forcing them to rent. We build a model studying motivations for and effects of ownership-restricting policies. When some agents are prohibited from purchasing housing, competitive equilibrium further punishes renters, failing to attain a “second-best” that maximizes welfare subject to the policy’s intended constraint. We then consider real estate taxation, a hotly debated topic in China, currently undergoing reform. We show that positive taxes on housing transactions can help mitigate the inefficiency caused by restricted ownership, but only by introducing a new distortion. Meanwhile, subsidizing rental transactions could, in theory, restore the second-best, but only by diverting public funds away from other uses.     

Exchange market pressure,stock prices,and commodity prices in West Africa

As Africa continues its decade of rapid economic growth, the continent also faces the risk of becoming more susceptible to financial ‘contagion.’ Capital flows and trade linkages might cause one country’s currency market to influence those of its neighbors. Likewise, shocks to global commodity or asset markets might induce a crisis in one or more countries in the region. This study generates monthly measures of exchange market pressure (EMP) for four individual West African countries, as well as for the WAEMU franc zone, from 2002 to 2012. Vector Autoregressive (VAR) methods are then used to test for linkages among them, as well as to analyze the effects of various external price shocks. A number of spillovers are uncovered. More importantly, local connections dominate global ones in the case of stock- and commodity-price declines. Ghana, for example, is shown to be a ‘commodity currency’ when West African commodity prices are included in the VAR, but not when a global index is used.