Housing Market Indicators Research Articles

Ethnic prejudices and public support for anti-discrimination policies on the housing market

Notwithstanding persistent levels of ethnic discrimination on the rental housing market, we have witnessed in many West-European countries a shift from targeted multicultural to colour-blind policies. At the same time, anti-immigration attitudes remained relatively stable. Whether and how these attitudes are translated in support or aversion toward anti-discrimination policies is, however, still unclear. As the first study in Europe we analyse public support for eight policy measures to tackle rental discrimination against ethnic minorities. Based on multilevel analyses among a sample of 899 adults in Belgium, we show that there is large support among the general public for testing, training and campaigning against ethnic discrimination on the housing market. General support for affirmative action measures is, however, much lower. In addition, support for anti-discrimination policies is strongly related to ethnic prejudices. People with more – especially subtle – prejudices are less likely to support policies against rental discrimination. Moreover, prejudices also mediate the effects of interethnic contacts and outgroup size on policy support. Finally, local housing market indicators do not play a significant role in the public support for anti-discrimination policies on the housing market.

Heterogeneous effects and spillovers of macroprudential policy in an agent-based model of the UK housing market

AbstractWe develop an agent-based model of the UK housing market to study the impact of macroprudential policy experiments on key housing market indicators. The heterogeneous nature of this model enables us to assess the effects of such experiments on the housing, rental, and mortgage markets not only in the aggregate, but also at the level of individual households and sub-segments, such as first-time buyers, homeowners, buy-to-let (BTL) investors, and renters. This approach can, therefore, offer a broad picture of the disaggregated effects of financial stability policies. The model is calibrated using a large selection of micro-data, including data from a leading UK real-estate online search engine as well as loan-level regulatory data. With a series of comparative static exercises, we investigate the impact of (i) a hard loan-to-value limit and (ii) a soft loan-to-income limit, allowing for a limited share of unconstrained new mortgages. We find that, first, these experiments tend to mitigate the house price cycle by reducing credit availability and therefore leverage. Second, an experiment targeting a specific risk measure may also affect other risk metrics, thus necessitating a careful calibration of the policy to achieve a given reduction in risk. Third, experiments targeting the owner-occupier housing market can spill over to the rental sector, as a compositional shift in home ownership from owner-occupiers to BTL investors affects both the supply of and the demand for rental properties.

One hundred years of rent control in Argentina: much ado about nothing

Following World War I, rent control became a standard policy response to the housing shortage and the resulting rent increases. Typically, economists blame it for creating inefficiencies in the housing market and beyond. We investigate whether rental market regulations (including rent control, protection of tenants from eviction, and housing rationing) had any effects in a middle-income Latin American economy, such as Argentina. To answer this question, we take advantage of a wide range of housing market indicators and restrictive rental regulation indices covering almost one century. Using a standard OLS model and MARS, a nonlinear estimation technique, we find that rental market regulations have exerted a statistically significant negative impact on the growth rates of the real housing rents. However, they were only effective for short periods following both World Wars, when regulations were novel and particularly strong.

Проблемы динамического моделирования ввода в действие жилых домов в постсоветских странах

The article is devoted to the description of procedures of economic and mathematical modeling of trends in the field of housing construction taking into account the peculiarities of various countries of the post-Soviet space. The results of analysis of well-known scientific publications on forecasting the dynamics of housing market indicators are presented. It has been shown that most domestic and foreign scientists as the most effective methods of modeling these indicators consider methods of analyzing time trends, in which polynomials of high (in some cases up to the fourth degree) order are used to approximate the available retrospective data. Other common approaches to solving this problem are the use of short-term forecasting based on moving average algorithms, as well as the use of the SARIMA model, which takes into account the trend and seasonal wave. The article shows that these methods do not fully take into account the profound changes in the construction complexes of the post-Soviet states caused by the significant structural transformation of their socio-economic systems. The authors proposed to use econometric models based on regressions with dummy variables to model the main indicators of housing construction, taking into account the complex structure of the external and internal environment of national construction complexes. It has been shown that in a significant number of practical situations, a fairly simple but effective way to take into account the components of the time series of the indicators under consideration in one complex model is to use the model of "change in growth (fall)" when choosing the time of the beginning (end) of a crisis situation as a characteristic point. The results of modeling the main indicators of housing construction for various countries of the post-Soviet space showed that the proposed model when constructing the medium-term forecast allows taking into account the situation component of the analyzed time series.

Preservation Planning: Redeveloping Public and Affordable Housing

Urban planners face an affordable housing crisis compounded by federal programs that eliminated subsidized housing. Prior work indicates profit-making motivations and race influenced housing removal but overlooks planning efforts to rebuild affordable housing. This paper explores the neighborhood factors affecting the redevelopment of subsidized housing under the Housing Opportunities for People Everywhere (HOPE VI) program, using multivariate regression analysis of U.S. Department of Housing and Urban Development (HUD) and Census data. Findings show housing market indicators, racial composition, and poverty rates do not predict the mix of rebuilt units, which suggests opportunities for planning to promote affordable housing goals in public–private development projects.

The Effects of Rent Control in Latin America: A Century of Regulations in Argentina

Following World War I, rent control became a standard policy response to the housing shortage and the resulting rent increases. Typically, economists blame it for creating inefficiencies in the housing market and beyond. We investigate whether rental market regulations (including rent control, protection of tenants from eviction, and housing rationing) had any effects in a middle-income Latin American economy, such as Argentina. To answer this question, we take advantage of a wide range of housing market indicators and restrictive rental regulation indices covering almost one century. Using a standard OLS model and MARS, a non-linear estimation technique, we find that rental market regulations have exerted a statistically significant negative impact on the growth rates of the real housing rents. However, they were only effective for short periods following both World Wars, when regulations were novel and particularly strong.

Determinants of Housing Market Fluctuations: Case Study of Lithuania

The article aims to distinguish the most important determinants of housing market fluctuations in Lithuania for period of 2005–2015. Analysis of housing market cycle performed, major prices’ movements and affecting factors discussed. Moreover, in order to distinguish the most significant determinants of housing market fluctuations, expert survey performed and significances of determinants by using the Analytic Hierarchy Process (AHP) method identified. Research reveals that prices movements in Lithuania's housing sector can be largely explained by economic fundamentals as well as housing market indicators.

Macroprudential Policy in an Agent-Based Model of the UK Housing Market

This paper develops an agent-based model of the UK housing market to study the impact of macroprudential policies on key housing market indicators. This approach enables us to tackle the heterogeneity in this market by modelling the individual behaviour and interactions of first-time buyers, home owners, buy-to-let investors, and renters from the bottom up, and observe the resulting aggregate dynamics in the property and credit markets. The model is calibrated using a large selection of micro-data, mostly from household surveys and housing market data sources. We perform a series of comparative statics exercises to investigate the impact of the size of the rental/buy-to-let sector and different types of buy-to-let investors on housing booms and busts. The results suggest that an increase in the size of the buy-to-let sector may amplify house price cycles and increase house price volatility.Furthermore, in order to illustrate the effects of macroprudential policies on several housing market indicators, we implement a loan-to-income portfolio limit. We find that this policy attenuates the house price cycle.

Macroeconomic News and Asset Prices Before and After the Zero Lower Bound

With short-term policy interest rates constrained by their effective zero lower bound (ZLB), monetary policy relied on communicating the future path of policy conditional on incoming macroeconomic data. Motivated by this, we exploit intra-day prices to investigate how updates on the state of the U.S. economy affect interest rates and exchange rates before and after the ZLB. We find that releases reflecting the dual mandate of the Fed rose in importance and – as an ex-post acknowledgement of the sources of the Great Recession – additional housing market indicators and GDP revisions, that hitherto left markets unaffected, became market movers.

Episodes of Exuberance in Housing Markets: In Search of the Smoking Gun

In this paper, we examine changes in the time series properties of three widely used housing market indicators (real house prices, price-to-income ratios, and price-to-rent ratios) for a large set of countries to detect episodes of explosive dynamics. Dating such episodes of exuberance in housing markets provides a timeline as well as empirical content to the narrative connecting housing exuberance to the global 2008 −09 recession. For our empirical analysis, we employ two recursive univariate unit root tests recently developed by Phillips and Yu (International Economic Review 52(1):201–226, 2011) and Phillips et al. (2015). We also propose a novel extension of the test developed by Phillips et al. (2015) to a panel setting in order to exploit the large cross-sectional dimension of our international dataset. Statistically significant periods of exuberance are found in most countries. Moreover, we find strong evidence of the emergence of an unprecedented period of exuberance in the early 2000s that eventually collapsed around 2006 −07, preceding the 2008 −09 global recession. We examine whether macro and financial variables help to predict (in-sample) episodes of exuberance in housing markets. Long-term interest rates, credit growth and global economic conditions are found to be among the best predictors. We conclude that global factors (partly) explain the synchronization of exuberance episodes that we detect in the data in the 2000s.

Housing and the Business Cycle: Evidence from the UK Housing Price and Quantity

This paper investigates the importance of housing price and quantity variables in the UK business cycle since the mid 1950s. We start with a baseline Markov-switching common factor model for the UK economy into which we incorporate a house price variable (nationwide house price index) and a quantity variable (new housing starts) into the baseline model. Then, we evaluate the importance of the two housing market variables in the fluctuations of the overall economic activities. When house variables are allowed to directly affect the evolution of key macro indicators, the results are similar to those for the US in the previous studies: although the year-onyear housing quantity changes have significant on the UK business cycle beyond the three macro indicators, the usual yearon-year house price changes do not. However, asymmetric decreases in house price significantly affect the UK business cycle more than the asymmetric decreases in house quantity. When house variables are accommodated to influence the probabilities of transitions between expansions and contractions, we find strong evidence that changes in both house price and quantity variables significantly affect the switching of the UK economy between the two phases, although house quantity variables predict the upcoming business cycle phases better than house price. Moreover, for both house price and quantity variables, most useful information is contained in their asymmetric decreases.Keywords: Housing, Price, Quantity, UK, Business cycle, Markov-switchingJEL Classification: E21, E44, D41I. IntroductionThe extended period of sharp and continued house price increases, coupled with the booming investment in residential construction since the mid 90s has engendered a plethora of studies on the link between the housing market and the macroeconomy. As summarized in the satisfactory survey by Muellbauer and Murphy (2008), housing markets and the rest of the economy interact in multiple ways. However, if we concentrate on the of housing price on macroeconomic activities, we seem to have reached a wide consensus on the theoretical front. The effects channel emphasizes price appreciation, which causes subsequent increases in the wealth of homeowners, a direct extension of the permanent income hypothesis. More recent research, such as those by Aoki et aL (2004) and Iacoviello (2005), suggest that innovations in housing finance allow homeowners to use their homes as collateral to loosen their borrowing constraints.Unlike the general agreements revolving around the presence of the house price-macroeconomy relation in the theoretical front, the empirical evidence on the role of house prices over the business cycle remains mixed. For example, Davis and Heathcote (2005) find a contemporaneous correlation between the nationwide house prices in the US and output as high as 65% over the 1971-2001 period. However, Kan et aL (2004) find that the contemporaneous correlation between house prices and output growth is merely 15% or smaller on average in about 50 major US cities. Recently, Learner (2007) challenged the traditional view on the role of house prices, arguing that housing markets are grossly understudied by macroeconomists interested only in understanding business cycles. He reported several stylized facts about the behavior of the US housing market over the business cycle, claiming that i) housing investment leads the business cycle, and a fall in residential investment is a reliable harbinger of a recession, and ii) volumes, rather than prices, in the housing sector are what matter for business cycles. Supporting the second stylized fact, he pointed out that eight out of ten US postwar recessions have been preceded by substantial problems in quantity variables such as housing investment and consumer durables. Alvarez et aL (2009) (for the Eurozone) and Alvarez and Cabrero (2010) (for Spain) provided similar evidence highlighting the leading nature of housing market cycles with respect to business cycles, which reflects the cyclical features of a variety of housing market indicators such as hous- ing starts, housing permits, and the amount of residential investment. …

Explaining the Spatial Variation in Homeownership Rates: Results for German Regions

Lerbs O. W. and Oberst C. A. Explaining the spatial variation in homeownership rates: results for German regions, Regional Studies. This paper employs cross-sectional data on ninety-six German regions to investigate the interregional variability of homeownership rates. Among the explanatory variables, the analysis includes important regional housing market indicators as well as regional socio-demographic composition, urbanization and labour market performance. An estimation strategy is chosen which accounts for different forms of spatial dependence between the regional units. It is found that regional differences in the relative price of owning versus renting and the affordability of owner-occupied housing play a key role in explaining why homeownership rates vary so substantially across the country. The results indicate significant neighbourhood effects for several variables.

Trends and Prospects of the U.S. Housing Market Using the Markov Switching Model

Accurate projection of the economic conditions in a country can enable the government to establish appropriate policies in a timely manner. This also applies to enterprises and individuals in terms of decision-making processes, such as investing and production planning and household consumption and saving. The housing market is no exception to this practice. The prompt and accurate assess- ment of the trends in the housing market enables consumers to make quick decisions and to come up with the corresponding measures, thus minimizing risks associated with market uncertainty. The monthly indices of the housing market indicators are released at the end of the following month, creating a month-long standstill in making a judgment regarding the housing market. Consequently, it is not possible to predict the current month's market status. Therefore, in this study, various U.S. housing market-related indicators were calculated as aver- age month-to-month changes using the composite index methodology of the National Bureau of Economic Research (NBER). The trends in the housing market were analyzed using the Markov switching models: the Markov switching random walk (MS-RW) model and the Markov switching autoregressive (MS-AR) model. Results showed that the methods can accurately determine the trends in the housing market. Findings from the forecasting performance test made it possible to predict or forecast the prospects of the housing market within the month-long standstill period. DOI: 10.1061/(ASCE)UP.1943-5444.0000098. © 2012 American Society of Civil Engineers.

The Effect of Consumers' Expectations in a Booming Housing Market: Space-time Patterns in the Netherlands, 1999–2000

Even though economic models have been relatively successful in explaining the long-run patterns of house prices, they have more difficulties in explaining short-run developments in the housing market. However, the fact that during such ‘bubbles’ the spatial pattern of house prices, which can mainly be attributed to accessibility differences, usually remains unchanged, suggests that the irrational forces that are presumably responsible for unexplained movements in house prices obey some regularities: they seem to affect the level of house prices, but not their spatial pattern. This suggests that it is worthwhile to consider the explanatory power of psychological variables like those reflecting general (nation-wide) feelings of optimism or pessimism. This paper considers the development of Dutch house prices in the years 1999 and 2000, when house prices increased fast. Existing explanations of the long-run development of Dutch house prices on the basis of economic fundamentals (notably income and the mortgage interest rate) would suggest a much more modest development of house prices over these years. The paper also shows that commonly used housing market indicators, notably the number of vacancies (houses for sale) and the time on the market, are unable to explain the development of house prices during this period. However, the paper finds a strong relationship between the development of house prices and the Dutch index of consumer confidence.

The Effect of Consumers' Expectations in a Booming Housing Market: Space-Time Patterns in the Netherlands, 1999-2000

Even though economic models have been relatively successful in explaining the long run patterns of house prices, they have more difficulties in explaining short run developments of the housing markets. However, the fact that during such 'bubbles' the spatial pattern of house prices, which can mainly be attributed to accessibility differences, usually remains unchanged, suggests that the irrational forces that are presumably responsible for unexplained movements in house prices obey some regularities: they seem to affect the level of house prices, but not their spatial pattern. This suggests that it is worthwhile to consider the explanatory power of psychological variables like those reflecting general (nation wide) feelings of optimism or pessimism. This paper considers the development of Dutch house prices in the years 1999 and 2000, when house prices increased fast. Existing explanations of the long run development of Dutch house prices on the basis of economic fundamentals (notably income and the mortgage interest rate) would suggest a much more modest development of house prices over these years. We also show that commonly used housing market indicators, notably the number of vacancies (houses for sale) and the time on the market, are unable to explain the development of house prices during this period. However, we find a strong relationship between the development of house prices and the Dutch index of consumer confidence.

Speculative housing supply land and housing, markets: a comparison

Speculative development is significant as a way of providing new owner occupied housing in Europe. Yet because this sector of supply is developed under very different policy conditions, the relationships between new build output, housing markets and the wider economy can vary considerably. Previous research, which has sought to understand the determinants of speculative housing development, has largely failed to recognize the contribution that can result from a comparative European study. In this paper, the UK is compared with the Netherlands, where speculative housing sectors operate under different land and planning systems. Supply or 'cost' based theoretical frameworks are contrasted with quantity 'signal' approaches in an investigation of the relationship between macroeconomy, existing housing, and new build market. It is shown, via an analysis of the period 1975-1997, that both UK and Dutch speculative housing sectors respond to a significant extent to changes in housing market indicators such as the level of turnover and house prices; however, Dutch speculative housing output has been more responsive to changes in the wider economy. This is explained not only in terms of the system of municipal land supply, but also in terms of a tenure neutral new build housing policy. It is argued that although there will be some convergence with respect to the long run land-house price relationship, development industries will continue to operate very differently, particularly in dealing with public sector bodies.

Indicators of Local Housing Affordability: Comparative and Spatial Approaches

This paper focuses on the measurement of local housing affordability problems. A number of different housing market indicators are offered that help identify the magnitude and nature of housing affordability problems and their geographic distribution. This interest is prompted by the predominance of housing affordability problems and the severity of the problems for many of the lowest income renter households. In addition, there is significant policy interest in “the national goal that every American family be able to afford a decent home in a suitable environment” (National Affordable Housing Act of 1990). This paper develops measures of the spatial distribution of affordability problems and implements measures of the mismatch between the demand and supply of housing affordable to the lowest income households.

Regional house-price dispersion and interregional migration

This paper evaluates the effects of regional house-price dispersion on interregional population mobility. In the place-to-place migration model developed, household moves depend upon the relative housing and labor market opportunities in the origin and destination regions, local amenities, population characteristics, and relocation costs. Estimation and simulation of a logistic model suggest that house price differentials are important determinants of household moves and operate to offset some of the added incentive to migrate to areas characterized by the most favorable labor market conditions. Moreover, these findings apparently stem, in part, from capital market imperfections, suggesting that the effectiveness of migration as a labor allocation mechanism could be improved by addressing cash-flow affordability issues. The estimating equations further evaluate alternative housing market indicators, including mortgage-servicing costs and home-ownership user costs, in the analysis of household mobility.