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Real estate is an established investment medium for pension funds and for individual investors seeking to maximize after-tax income. Successful real estate investment requires analytical and management skills, for which most nonprofessional investors rely upon real estate investment trusts (REITs) or limited partnership syndicates. Many REITs have achieved a creditable yield performance over the past decade and are highly suitable for the investor not requiring tax shelter. Analysis of the limited partnership presents greater difficulties, although track records for offerings in the 1970s can be a useful guide. Front-end loads, management cash-flow participation, and back-end loads are major considerations for the purchaser of limited partnership interests. [ABSTRACT FROM AUTHOR]

House price prediction is a hot topic in the economic literature. House price prediction has traditionally been approached using a-spatial linear (or intrinsically linear) hedonic models. It has been shown, however, that spatial effects are inherent in house pricing. This article considers parametric and semi-parametric spatial hedonic model variants that account for spatial autocorrelation, spatial heterogeneity and (smooth and nonparametrically specified) nonlinearities using penalized splines methodology. The models are represented as a mixed model that allow for the estimation of the smoothing parameters along with the other parameters of the model. To assess the out-of-sample performance of the models, the paper uses a database containing the price and characteristics of 10,512 homes in Madrid, Spain (Q1 2010). The results obtained suggest that the nonlinear models accounting for spatial heterogeneity and flexible nonlinear relationships between some of the individual or areal characteristics of the houses and their prices are the best strategies for house price prediction. [ABSTRACT FROM AUTHOR]

We show that dynamic stochastic general equilibrium (DSGE) models with housing and collateralized borrowing predict a fall in house prices following positive government spending shocks. By contrast, we show that house prices in the United States rise persistently after identified positive government spending shocks. We clarify that the incorrect house price response is due to a general property of DSGE models-approximately constant shadow value of housing-and that modifying preferences and production structure cannot help in obtaining the correct house price response. Properly accounting for the empirical evidence on government spending shocks and house prices using a DSGE model therefore remains a significant challenge. [ABSTRACT FROM AUTHOR]

We present a hybrid model for diagnosis and critical time forecasting of real estate bubbles. The model combines two elements: (1) the Log Periodic Power Law Singular model to describe endogenous price dynamics originated from positive feedback loops among economic agents; and (2) a diffusion index that creates a parsimonious representation of multiple macroeconomic variables. We explicitly compare the in-sample and out-sample behaviour of our model on the housing price indices of 380 US metropolitan areas. Empirical results suggest that the model is able to forecast the end of the bubbles and to identify the variables that are highly relevant during the bubble regime. [ABSTRACT FROM AUTHOR]

The current longitudinal study evaluated the individual, housing, and neighborhood characteristics predictive of feeling psychologically integrated within one's neighborhood among a population of homeless and vulnerably housed individuals. Participants were recruited at homeless shelters, meal programs, and rooming houses in Ottawa, Canada and participated in three in-person interviews, each approximately 1 year apart. Prospective and cross-sectional predictors of psychological integration at Follow-up 1 and Follow-up 2 were examined. There were 397 participants at baseline, 341 at Follow-up 1 and 320 at Follow-up 2. A hierarchical multiple regression uncovered several significant predictors of psychological integration. The most salient and common predictors were being older, having greater social support, living in high quality housing, and residing in a neighborhood with a positive impact. Implications for service provision and policy advancements are discussed. [ABSTRACT FROM AUTHOR]

Given the existence of nonnormality and nonlinearity in the data generating process of real house price returns over the period of 1831–2013, this article compares the ability of various univariate copula models, relative to standard benchmarks (naive and autoregressive models) in forecasting real US house price over the annual out-of-sample period of 1874–2013, based on an in-sample of 1831–1873. Overall, our results provide overwhelming evidence in favour of the copula models (Normal, Student’st, Clayton, Frank, Gumbel, Joe and Ali-Mikhail-Huq) relative to linear benchmarks, and especially for the Student’st-copula, which outperforms all other models both in terms of in-sample and out-of-sample predictability results. Our results highlight the importance of accounting for nonnormality and nonlinearity in the data generating process of real house price returns for the US economy for nearly two centuries of data. [ABSTRACT FROM AUTHOR]

Purpose ' The purpose of this paper is to create an endurance index of housing investor sentiment and use it to forecast housing stock returns. This study performs not only in-sample and out-of-sample forecasting, like many previous studies did, but also a true forecasting by using all lag terms of independent variables. In addition, an evaluation procedure is applied to quantify the quality of forecasts. Design/methodology/approach ' Using a binomial probability distribution model, this paper creates an endurance index of housing investor sentiment. The index reflects the probability of the high or low stock price being the close price for the Philadelphia Stock Exchange Housing Sector Index. This housing investor sentiment endurance index directly uses housing stock price differentials to measure housing investor reactions to all relevant news. Empirical results in this study suggest that the index can not only play a significant role in explaining variations in housing stock returns but also have decent forecasting ability. Findings ' Results of this study reveal the considerable forecasting ability of the index. Monthly forecasts of housing stock returns have an overall accuracy of 51 per cent, while the overall accuracy of 8-quarter rolling forecasts even reaches 84 per cent. In addition, the index has decent forecasting ability on changes in housing prices as suggested by the strong evidence of one-direction causal relations running from the endurance index to housing prices. However, extreme volatility of housing stock returns may impair the forecasting quality. Practical implications ' The endurance index of housing investor sentiment is easy to construct and use for forecasting housing stock returns. The demonstrated predictability of the index on housing stock returns in this study can have broad implications on housing-related business practices through providing an effective forecasting tool to investors and analysts of housing stocks, as well as housing policy-makers. Originality/value ' Despite different investor sentiment proxies suggested in the previous studies, few of them can effectively predict stock returns, due to some embedded limitations. Many increases and decreases inn prices cancel out each other during the trading day, as many unreliable sentiments cancel out each other. This dynamic process reveals not only investor sentiment but also resilience or endurance of sentiment. It is only long-lasting resilient sentiment that can be built in the closing price. It means that the only feasible way to use investor sentiment contained in stock prices to forecast future stock prices is to detach resilient investor sentiment from stock prices and construct an index of endurance of investor sentiment. [ABSTRACT FROM AUTHOR]

The dynamics of house prices, sales, construction, and population growth in response to city-specific income shocks are characterized for 106 US cities. A dynamic model of search in the housing market in which construction, the entry of buyers, house prices, and sales are determined in equilibrium is then developed. The theory generates dynamics qualitatively consistent with the observations and a version calibrated to match key features of the US housing market offers a substantial quantitative improvement over models without search. In particular, variation in the time it takes to sell induces transaction prices to exhibit serially correlated growth. (JEL D83, R21, R23, R31) [ABSTRACT FROM AUTHOR]

This paper examines the short-horizon return predictability of the ten largest international securitized real estate markets, paying special attention to possible nonlinearity-in-mean as well as nonlinearity-in-variance predictability. Although international securitized real estate returns are generally not predictable based on commonly-used statistical criteria, there is much evidence for the predictability based on economic criteria (i.e., direction of price changes and trading rule profitability), which is more often due to nonlinearity-in-mean. The forecast combinations for various models appear to improve the forecasting performance, while the allowance of data-snooping bias using White's reality check substantially mitigates spurious out-of-sample forecasting performance and weakens otherwise overwhelmingly strong predictability. Overall, there is robust evidence for the predictability in many international securitized real estate markets. [ABSTRACT FROM AUTHOR]

The paper presents a method and results for the generation of future residential land use scenarios for the Elbe River Basin. The challenge of this study is to develop scenarios that consider two processes, accelerated urban sprawl in growth centres while peripheral regions are depopulating. The question is whether the demand for built-up areas can be reduced to achieve the objective of the German sustainability strategy. Current socioeconomic developments of the study area are described, and approaches to calculate residential land use demand are reviewed. Regionalised socioeconomic scenarios of the IPCC-SRES as well as households and housing forecasts are applied to calculate residential land demand for regions. The Land Use Scanner, a spatially explicit land use change model, is then used to allocate the demand on grid-cells within the spatial planning units. The results show a shift of residential developments from urban areas in general to agglomerations leading to a polarisation of developments. Residential land consumption can only be minimised to achieve the sustainable development goals if a strict land use policy with the implementation of higher building densities, activation of inner city quarters and application of effective planning instruments is followed. [ABSTRACT FROM AUTHOR]

As defined by the Investment Dictionary, housing bubbles usually start with an increase in demand in the face of limited supply, which takes a relatively long period of time to replenish and increase. At some point, however, demand decreases or stagnates at the same time supply increases, resulting in a sharp drop in prices known as a bubble burst. During the last two decades, the Slovenian housing market has been characterized by a very high housing demand under circumstances of a limited supply, which may primarily be attributed to the effects of the housing reforms introduced in the early 1990s. As is always the case in such situations, speculators seeking huge quick profits drove house prices to in sustainable levels relative to average incomes. Like in many countries throughout the world, the situation has recently changed. Statistical records show a slight decline in the growth of house prices and there are signs of stagnation in housing demand. These developments have prompted various (contrasting) viewpoints among housing experts. Some are convinced that the bubble has finally burst because house prices had reached the highest possible levels that buyers were willing to pay. On the other hand, others argue that house prices would have continued to grow had the credit crunch not occurred, which resulted in the reduced availability of mortgages and therefore depressed demand. These two viewpoints represent the main hypotheses of this discussion. This paper reviews the housing market circumstances over the last two decades and identifies facts that may substantiate or disprove these hypotheses. [ABSTRACT FROM AUTHOR]

Abstract: This paper provides new estimates of Hispanic–white residential segregation in new destinations and established Hispanic places. New Hispanic destinations are defined broadly to include metropolitan cities, suburban places, and rural communities with unusually rapid Hispanic growth rates. The analysis is framed with the spatial assimilation and place stratification perspectives and is based on block data from the 1990 and 2000 decennial censuses. The analysis confirms our basic hypothesis – that Hispanics are highly segregated in new Hispanic destinations, often at levels greatly exceeding those in established places. Hispanic suburbanization or exurbanization into new destinations is no marker of spatial assimilation. Consistent with the place stratification perspective, differences in Hispanic–white segregation between new destinations and established Hispanic areas cannot be explained by place-to-place differences in ecological location, population composition, economic growth, employment, or Hispanic–white income inequality. Hispanic segregation in new destinations is especially sensitive to the size of the foreign-born population and to preexisting “minority threats” in communities with large black populations. Segregation levels in new destinations also are less responsive to income disparities between Hispanics and whites; economic assimilation does not insure Hispanic spatial assimilation. Understanding how newcomers are spatially incorporated in new destinations will be a continuing challenge for scholars concerned about the spatial diffusion and apparent geographic balkanization of America’s growing Hispanic population. [Copyright &y& Elsevier]

Demographics are not quite destiny but do exert a powerful influence on future housing demand. This paper examines how demographics shape demand and projects household growth, second home and additional vacant unit demand, and replacement demand from 2010 to 2020 under different assumptions. To analyze the housing supply-demand balance entering 2010, results are presented from a backward look at long-run construction demand compared to actual new construction and from a simple econometric model of long-run demand for starts using pooled metropolitan area data from 1982 to 2000. Implications of the housing and mortgage market meltdown for homeownership in the years ahead are also explored. [ABSTRACT FROM AUTHOR]

This paper demonstrates that, in the context of U.S. housing data, rents and ex ante user costs diverge markedly--in both growth rates and levels--for extended periods of time, a seeming failure of arbitrage and a puzzle from the perspective of standard capital theory. The tremendous volatility of even appropriately-smoothed ex ante annual user cost measures implies that such measures are unsuitable for inclusion in official price statistics. The divergence holds not only at the aggregate level, but at the metropolitan-market level as well, and is robust across different house price and rent measures. But transactions costs matter: the large persistent divergences did not imply the presence of unexploited profit opportunities. In particular, even though detached housing is readily moved between owner and renter markets, and the detached-unit rental market is surprisingly thick, transactions costs would have prevented risk-neutral investors from earning expected profits by buying a property to rent out for a year, and would have prevented risk-neutral homeowners from earning expected profits by selling their homes and becoming renters for a year. Finally, computing implied appreciation as a residual yields a house price forecast with huge errors; but either longer-horizon or no-real-capital-gains forecasts--which turn out to have similar forecast errors--imply a far less divergent user cost measure which might ultimately be useful for official price statistics. Some conjectures are offered. [ABSTRACT FROM AUTHOR]

In house architecture, the steel technologies use has constituted, specially in Italy, a research and experimentation field rather delimited. Although the house topic has been most important in the modernist discussion, becoming, after the war, a social problem, its declension as to steel technology remains conditioned by the historical events, the autarky, and cultural background doesn't accept the temporary idea of housing, suggested by use of steel. In the outlook of vicissitude with fragmentary border reconstruction, the goal is to research technical modes and building system and to assess technique and shape implications. These technical-project vicissitudes were analyzed as to different topic trends: "experimental house", "anti-seismic house", "temporary house" and "steel house". The building experiences of steel house have implied innovation processes, marginal and partial, and large and general tendency to technique hybridization, researching more the factors of constructive and functional rationalization, than the syntactic and linguistic potentialities. [ABSTRACT FROM AUTHOR]