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This research discovers the spatial regularities of house prices across Chinese prefecture cities in an economic common area and investigates the underlying formation process. It reveals an uneven distribution of house prices across cities, with those large and/or higher-tier cities and their neighbours having significantly higher house prices. Such an uneven pa����ern of house prices demonstrates the agglomeration spillovers in the interurban housing market. Two forms of spillovers are empirically examined. The first is the urban hierarchy distance effect, which is related to the position of a city in a hierarchical urban system. In general, the distance penalty of higher-tier urban centres is confirmed, that is, all else being equal, the further away a city is from the higher-tier city, the lower the house price. The second form of spillovers relates to a city's position in a city network system, in which no hierarchical structure is imposed. In such a situation, the spillovers arise from the interaction with neighbouring cities and it is found that a city that has larger neighbours tends to have higher house prices. These two forms of spillovers are somewhat correlated with each other because a higher-tier city is always associated with a larger urban size.
The purpose of this paper is to apply recent advances in the econometrics of panel data to a problem that has a clear spatial dimension. We model the dynamic adjustment of real house prices using data at the level of US States. In the last decade, in most OECD countries there has been a significant rise in real house prices. This attracted the attention of many international organisations and central banks. In this paper we consider interactions between housing markets by examining the extent to which real house prices at the State level are driven by fundamentals such as real income, as well as by common shocks, and determine the speed of adjustment of house prices to macroeconomic and local disturbances. We take explicit account of both cross sectional dependence and heterogeneity. This allows us to find a cointegrating relationship between house prices and incomes and to identify a small role for real interest rates. Using this model we then examine the role of spatial factors, in particular the effect of contiguous states by use of a weighting matrix. We are able to identify a significant spatial effect, even after controlling for State specific real incomes, and allowing for a number of unobserved common factors.
This study discusses ways of measuring and explaining the development of house prices. The goal of the research underpinning this dissertation was to develop a methodological framework for studying these developments. This framework relates, first, to correcting for changes in the composition of dwellings and, second, to the fundamentals of the price development. Using the weighted repeat sales method and sale price appraisal ratio (SPAR) method, house price indexes were developed for the Netherlands. Both the Dutch land registry office and Statistics Netherlands publish the SPAR based house price index monthly. To explain and predict changes in prices, a house price model is presented. As suggested in literature on western housing markets, the Dutch house price developments can be explained by demand-oriented short-run term variables and a long-run term variable.
The appearance of Oscar Newman's Defensible SpaceÓ in 1972 signaled the establishment of a new criminological subdiscipline that has come to be called by many Crime Prevention Through Environmental DesignÓ or CPTED. Over the years, Mr. Newman's ideas have proven to have significant merit in helping the Nation's citizens reclaim their urban neighborhoods. This casebook will assist public & private organizations with the implementation of Defensible Space theory. This monograph draws directly from Mr. Newman's experience as consulting architect. Illustrations.
This open access book discusses booming housing markets in cities around the globe, and the resulting challenges for policymakers and central banks. Cities are booming everywhere, leading to a growing demand for urban housing. In many cities this demand is out-pacing supply, which causes house prices to soar and increases the pressure on rental markets. These developments are posing major challenges for policymakers, central banks and other authorities responsible for ensuring financial stability, and economic well-being in general.This volume collects views from high-level policymakers and researchers, providing essential insights into these challenges, their impact on society, the economy and financial stability, and possible policy responses. The respective chapters address issues such as the popularity of cities, the question of a credit-fueled housing bubble, the role of housing supply frictions and potential policy solutions. Given its scope, the book offers a revealing read and valuable guide for everyone involved in practical policymaking for housing markets, mortgage credit and financial stability.
Between 1996 and 2006 the U.S. has experienced an unprecedented boom in house prices. As it has proven to be difficult to explain the large price increase by observable fundamentals, many observers have emphasized the role of speculation, i.e. expectations about future price developments. The argument is, however, often indirect: speculation is treated as a deviation from a benchmark. The present paper aims to identify house price expectation shocks directly. To that purpose, we estimate a VAR model for the U.S. and use sign restrictions to identify house price expectation, housing supply, housing demand, and mortgage rate shocks. House price expectation shocks are the most important driver of the boom and account for about 30 percent of the real house price increase. We also construct a model-based measure of exogenous changes in price expectations and show that this measure leads a survey-based measure of changes in house price expectations. Our main identification scheme leaves open whether expectation shifts are realistic or unrealistic. In extensions, we provide evidence that price expectation shifts during the boom were primarily unrealistic and were only marginally affected by realistic expectations about future fundamentals.
Spatial fixity is one of the characteristics that distinguishes housing from most other goods and services in the economy. In general, housing cannot be moved from one part of the country to another in response to shortages or excesses in particular areas. The modelling of housing markets and the interlinkages between markets at different spatial levels - international, national, regional and urban - are the main themes of this book. A second major theme is disaggregation, not only in terms of space, but also between households. The book argues that aggregate time-series models of housing markets of the type widely used in Britain and also in other countries in the past have become less relevant in a world of increasing income dispersion. Typically, aggregate relationships will break down, except under special conditions. We can no longer assume that traditional location or tenure patterns, for example, will continue in the future. The book has four main components. First, it discusses trends in housing markets both internationally and within nations. Second, the book develops theoretical housing models at each spatial scale, starting with national models, moving down to the regional level and, then, to urban models. Third, the book provides empirical estimates of the models and, finally, the models are used for policy analysis. Analysis ranges over a wide variety of topics, including explanations for differing international house price trends, the causes of housing cycles, the role of credit markets, regional housing market interactions and the role of housing in urban/suburban population drift.