Supply In Housing Market Research Articles

Why Did the “Missing Middle” Miss the Train? An Actors-In-Systems Exploration of Barriers to Intensified Family Housing in Waterloo Region, Canada

(1) Background: Missing Middle (MM) housing may be critical to address decreasing housing affordability and to achieve critical density in transit-oriented neighborhoods; however, its production is in decline. We report on a case study of housing development around a new light-rail transit line in the Region of Waterloo, Canada, investigating the puzzle of how a residential building boom coincided with decreasing housing affordability. (2) Methods: Following participatory co-creation and communication of background research characterizing housing demand with stakeholder partners, we created a data narrative arguing that MM housing was desired by residents and profitable for developers and then used it to guide semi-structured interviews with planners and real estate industry stakeholders. Based on these interviews, we developed a qualitative system map and causal loop diagrams that demonstrate interactions between key actors (residents, brokers, planners, developers, and investors) as mediated by boundedly rational real estate demand expectations. (3) Results: Our interviews identify multi-faceted barriers, beyond demand perception, to MM housing development. Systems analysis illustrates how high-density, small-unit high-rise development can become locked in, concurrently locking out MM housing. (4) Conclusions: Our research identifies barriers to MM housing supply by articulating the systemic feedbacks between the planning and land/housing market realms and reveals key leverage points, empowering planners to develop policies that catalyze hoped-for housing market supply responses to increase housing affordability. Based on these findings, we suggest targeted interventions: multi-unit base residential zoning, MM site plan typologies, non-profit and co-op financing, unit-mix requirements, pre-build MM condo purchase by municipalities or non-profits, and MM demonstration projects.

Spatial Inequality in China’s Housing Market and the Driving Mechanism

Housing inequality is a widespread phenomenon around the world, and it varies widely across countries and regions. The housing market is naturally spatial in its attributes, and with the transformation of China’s urbanization, industrialization, and globalization, the spatial inequality in the housing market is increasingly severe. According to the geospatial differences in the housing market supply, demand, and price, and by integrating the influencing factors of economic, social, innovation, facility environment, and structural adjustment, this paper constructs a “spatial–supply–demand–price” integrated housing market inequality research framework based on the methods of CV, GI, and Geodetector, and it empirically studies the spatial inequality of provincial housing markets in China. The findings show that the spatial inequality in China’s housing market is significant and becomes increasingly serious. According to the study, we have confirmed the following. (1) Different factors vary greatly in influence, and they can be classified into three types, that is, “Key factors”, “Important factors”, and “Auxiliary factors”. (2) The spatial inequalities in housing supply, demand, and price vary widely in their driving mechanisms, but factors such as the added value of the tertiary industry, number of patents granted, and revenue affect all these three at the same time and have a comprehensive influence on the development and evolution of spatial inequalities in the housing market. (3) All the factors are bifactor-enhanced or non-linearly enhanced in relationships between every pair, and they are classified into three categories of high, medium, and low according to the mean of interacting forces; in particular, the factors of GDP, expenditure, permanent resident population, number of medical beds, and full-time equivalent of R&D personnel are in a stronger interaction with other factors. (4) Based on housing supply, demand, price, and their coordination, 31 provinces are classified into four types of policy zones, and the driving mechanisms of spatial inequalities in the housing market are further applied to put forward suggestions on policy design, which provides useful references for China and other countries to deal with housing spatial inequality.

The impact of local residential land use restrictions on land values across and within single family housing markets

We provide estimates of the impact of restrictive residential land use environments on the price of land across major American housing markets. Using micro data on vacant land purchased to develop single family housing, we implement a new empirical strategy for estimating so-called ‘zoning taxes’ – the amount by which land prices are bid up due to supply side regulations. Our results are broadly consistent with previous findings that zoning taxes are especially burdensome in large coastal markets. However, our more recent data indicates that price impacts in the big west coast markets now are the largest in the nation. In the San Francisco, Los Angeles, and Seattle metropolitan areas, the price of land everywhere within those three markets having been bid up by amounts that at least equal typical household income. Finally, we show that our zoning tax estimates are strongly positively correlated with a new measure of local housing market supply constraint (the Wharton Residential Land Use Regulatory Index of 2018). This relationship is not mechanically driven as the regulatory index is constructed from survey data that do not incorporate land or house price data in any way.

The Impact of Local Residential Land Use Restrictions on Land Values Across and within Single Family Housing Markets

We provide estimates of the impact of restrictive residential land use environments on the price of land across major American housing markets. Using micro data on vacant land purchased to develop single family housing, we implement a new empirical strategy for estimating so-called ‘zoning taxes’ – the amount by which land prices are bid up due to supply side regulations. Our results are broadly consistent with previous findings that zoning taxes are especially burdensome in large coastal markets. However, our more recent data indicates that price impacts in the big west coast markets now are the largest in the nation. In the San Francisco, Los Angeles, and Seattle metropolitan areas, the price of land everywhere within those three markets having been bid up by amounts that at least equal typical household income. Finally, we show that our zoning tax estimates are strongly positively correlated with a new measure of local housing market supply constraint (the Wharton Residential Land Use Regulatory Index of 2018). This relationship is not mechanically driven as the regulatory index is constructed from survey data that do not incorporate land or house price data in any way.

Government Intervention in Malaysian Housing Market

Housing is a basic need for society to improve their quality of life and as important assets for the country’s economic. Malaysian Housing Policy has focused and concentrated to provide adequate housing supply for the targeted group, especially for the bottom 40% income earner. The urbanisation process creates the socio-economic changes has led to the increases in demand for housing. The previous study stated that there was a discrepancy between demand and supply in housing market resulted from rising trend in house price compared to the household income, thus leading to market imperfection. Thus, this paper attempted to explore the government intervention in the housing market. In a nutshell, government intervention is necessary to correct the market imperfection through policies and project implementations. There is a need to improve market efficiency and review the delivery of both supply and demand in the housing market.

HUBUNGAN INDEKS HARGA PROPERTI RESIDENSIAL DAN KREDIT PERBANKAN

Demand and supply in housing market depends on macroeconomic conditions such as Gross Domestic Product, interest rates, and housing prices. Changes to these variables are related to changes in housing market. This study aims to examine the relationship of housing prices, Gross Domestic Product, mortgage interest rate to Banking Credit. Knowing the relationship will be useful in making strategic decisions related to property investment and portfolio management. Housing price using Residential Price Index in primary market will be grouped into three parts based on land area of residential property consist of small house type, medium house type, and big house type. Data processing using Auto Regressive Distribution Lag (ARDL) bound test model to test the relationship between variables. The result of the research shows that there is a significant long run cointegration on the variable of housing price, Gross Domestic Product, and mortgage interest to banking credit. Furthermore, in testing each housing price group, the test results also show the relationship between these variables.

Analysis of demand and supply in the Colombian housing market: impacts and influences 2005-2016

PurposeThe purpose of this paper is to provide an estimate of the demand and supply in the housing market in Colombia in a period of high real estate valuation (2005-2016). On the demand side, it evaluates the impact of new housing prices, unemployment, stock market returns, real wages in the retail sector, remittances and mortgage rates. On the supply side, it estimates the influence of the price of new housing, construction costs, time deposit (TD) and mortgage rates. Real estate valuation was analyzed considering foreigners migration and land prices evolution.Design/methodology/approachOrdinary least squares (OLS) was used to estimate housing area with the semilog regression model and also to construct price models. OLS was also used in price models. Since quantities depend on prices and vice versa, a two-stage least squares (2SLS) was implemented.FindingsRising prices in new homes have an “elastic” effect on both demand and even higher effect on supply. Likewise, the real wage index for the retail sector has an elastic effect. On the other hand, the response to interest rates is negative, but statistically significant only on the supply side. Furthermore, the inflow of remittances is “inelastic” and statistically insignificant.Originality/valueHousing can sometimes be a Giffen good, this result challenges the traditional neoclassical model, but it can be explained by investment reasons and “bubble” behavior in the housing market. One last influence is the difference between “temporary” and “permanent” migrations. The latter has a statistically significant and perfectly inelastic effect on the price of new homes.

Heterogeneity of sellers in housing market: Difference in pricing strategies

The present study analyzes Perm, Russia residential housing market supply focusing on sellers’ heterogeneity. Many indicators of heterogeneity were considered in the previous research, and all of them were proved to have a great impact on housing prices and time on the market. However, the gap exists in evaluating sellers’ pricing strategies in dynamics mostly because of unavailable data. Current study clears out the effect of time on price using data on asking price dynamics. We employ semiparametric sample selection estimation procedure which accounts for the unobserved property characteristics and non-random selection of objects out of the sample. We consider two main types of sellers: real estate agents and property owners, and show that real estate agents appear to be more impatient compared to property owners. Specifically, they set a lower asking price initially and are more likely to revise it over time if the object is not sold.

Sellers' Heterogeneity in Housing Market: Difference in Pricing Strategies

The present study analyzes Perm, Russia residential housing market supply focusing on sellers' heterogeneity. Many indicators of heterogeneity were considered in the previous research, and all of them were proved to have a great impact on housing prices and time on the market. However, the gap exists in evaluating sellers’ pricing strategies in dynamics mostly because of unavailable data. Current study clears out the effect of time on price using data on asking price dynamics. We employ semiparametric sample selection estimation procedure which accounts for the unobserved property characteristics and non-random selection of objects out of the sample. We consider two main types of sellers: real estate agents and property owners, and show that real estate agents appear to be more impatient compared to property owners. Specifically, they set a lower asking price initially and are more likely to revise it over time if the object is not sold.

Where are the speculative bubbles in US housing markets?

In the first half of this decade, US house prices experienced significant real rates of appreciation. The dramatic increase in house prices led some economists to conclude that there was a speculative bubble in the US housing market. This paper explores how much of the recent appreciation in US house prices was attributable to the fundamental economic determinants of house prices. On the demand side, we note that the rate of homeownership in the US increased from 66.8% in 1999 to 69% in the fourth quarter of 2005. http://www.census.gov/hhes/www/housing/hvs/historic/histt14.html, accessed 10/17/2007. Each percentage point increase in the homeownership rate increases the demand for owner-occupied housing by about one million units. On the supply side, land prices and housing construction costs increased substantially in real terms over this period. The national average increase in house prices conceals significant spatial variation in appreciation rates. According to OFHEO, house prices in some California cities increased by more than fifteen percent per year during this period while house prices in Texas cities increased four percent per year. The increase in aggregate housing demand had different effects on metropolitan area house prices because housing market supply elasticities vary spatially. We estimate housing supply elasticities for 133 metropolitan areas and conclude that although areas on the East Coast and in California had large observed price increases, they owe much of their house price increases to inelastic supplies of owner-occupied housing.

Is New Zealand Facing a Baby Boomer Housing Bust?

The baby boomer generation (1946-1964) represents a population bulge that isn’t replicated in the younger generation who might be expected to live in the houses vacated by the baby boomers. Several authors have observed from 2010 there are likely to be more sellers than buyers, hence price reductions. This paper takes a contrary viewpoint. The following reasons are advanced as to why a baby boomer housing bust is unlikely to occur in New Zealand: positive demographic projections, reduced occupancy rates per dwelling, the elasticity of housing market supply, increasing numbers of investor buyers, policies relating to encouraging retirement in place, legislation underpinning the price of second hand houses, real incomes rising and intergenerational transfers. At a national level, demographic projections and housing supply characteristics are the variables most likely to influence future house prices. The paper then goes on to consider the regional implications of a baby boomer housing sell off, by examining possible future changes in housing preferences as well as trends in internal migration and regional economies.