Housing Value: Factors Affecting Housing Prices, Research Paper Example

Introduction

The housing market plays a critical role in the American economy because of how profoundly it impacts financial stability, output growth, and the fiscal policy transmission mechanism. Evidence gleaned from across the nation pinpoints purchasing a house as one of the most if not the most pertinent household decisions because it typically calls for the spending of a huge portion of the total wealth of one household in addition to expenditure (Englund and Ioannides 125). According to Greenwood and Hercowitz, the currency of the residential capital stock supersedes business capital stock in the United States, while the annual average GDP is commensurate with the market value of residential property (Greenwood and Hercowitz 1188). Furthermore, housing loans remains the primary liability class for households and have profoundly escalated in the past ten years. In light of the recent economic recession and persistent stagnation, it is necessary to take into consideration what factors directly impact housing value prices. Factors that impact the housing market include Gross Domestic Product (GDP) per capita, the cost of building and infrastructure repair, the acquisition cost of land, salary, availability of mortgage, consumer confidence, unemployment, and geographical factors etc. The housing market is extremely sensitive to inflation, which is why housing prices in particular areas have immensely oscillated during the past few years. A conglomeration of contributing factors undergird current housing trends and need to be considered as both dependent and independent variables. State lawmakers across the country have become increasingly concerned over the lack of affordable housing despite the pervasion of gentrification at the macro level because housing market conditions and the value of housing profoundly changed following the seemingly catastrophic housing bubble in 2007.

Literature review

There is a large corpus of literature that investigates what factors determine housing prices and how that impact the relative market value of housing. Several scholars point to empirical studies that underscore the centrality of income and other demographic trends in addition to nominal interest rates as critical factors in the housing price. Equity returns, however, also have been impactful in the determination of housing value and price (Pages and Marza). Other studies demonstrate that empirical methodologies, panel co-integration, error correction paradigms, and panel unit root tests have also been appropriated in this topic of inquiry. These studies also suggest that interest rates in addition to a household’s level of income were primary factors. Within the current economic climate, it is clear that interest rates and household level of income merely predisposes how much a person is able to borrow from financial institutions in order to become house owners. This particular decision over the amount of money a financial institution will loan to a borrower represents merely one way that housing prices are determined (Malpezzi 235). In other words, if an interest rate is high, then the price of housing will be a well.

In a different vein, Tazgi and Dokmeci applied a multiple regression model and ascertained that the most critical factor determining housing prices is simply the size of the floor area. Secondary factors impacted prices and values are area of the floor and the surface ratio of the road. Finally, the distance of housing to the coastline constitutes the tertiary factor in the determination of housing prices (Yazgi and Dokmeci). As such, if the floor size is bigger, than the housing price increases, thereby elucidating how this particular study broached the topic through a geographical lens. Hiebert and Roma also used empirical data and regression analysis to investigate beyond the locale of the facilities in order to ascertain whether population demographics and the differences there are when traversing urban areas influenced housing value (Hiebert and Roma). This study concluded that regardless of whether or not a particular locale has sound facilities and infrastructure, people prefer to live in areas that are comprised of a population that has certain demographic traits. Finally, a handful of studies have also used regional economic information in order to see how amenity values and housing services figured in housing values overall. All in all, it is evident that regional economic activity profoundly impacted housing prices. Interest rate, housing price, income, financial system, population composition, cost of living index, user costs, and land supply all play formative roles in the fluctuating housing market in the present day. Cost of living index determines housing value and thus where a homeowner can potentially live within their means. Once the economy begins to boom again, it is important to understand what factors contribute to housing prices and values in order to provide correctives so that the housing market oscillates less during periods of economic stagnation.

Researchers often pinpoint two fundamental metrics in order to analyze and assess housing values and prices contextualized within epochal exigencies: the price-to-income ratio and the affordability index. Studies further show a direct correlation between median annual incomes of households and housing causes. The price-to-income ratio represents housing prices in relation to median incomes. Traditionally, the prototypical median home in the United States costs approximately two and a half times as much as the household’s median income. For example, if the median income for a household was an estimated $100,000, than the average price of a house would cost approximately $260,000. The affordability index represents a measurement of a certain percentage of a consumer’s income on a monthly basis that is kept specifically to make mortgage payments (Zillow). Prior to the housing bubble period between 1985 and 1999, homeowners spent an estimated 20% of their monthly income on payments for their mortgage. However, exceedingly low interest rates at their nadir at 3%, by the end of 2012, homeowners spent only about twelve percent of their income on mortgages. These low interest rates have thus granted homeowners far more purchasing power than before, and research has shown that the cost to finance a house has dipped as well. Through these metrics, researchers working for Zillow argue that lower mortgage rates that make it appear to consumers that housing in the modern day is very affordable veils a trend at the macro level in which the overall price of housing is much more expensive than it has been historically in relation to median annual incomes. It must be noted that wage appreciation has been unable to keep pace with the value appreciation of housing. As such, this illusion of housing affordability undergirded by smaller mortgage payments on a monthly basis will eventually dissipate, resulting in a housing market filled with housing that is far too pricey for households living off of a median wage.

Within contemporary contexts, economists often first look at the dynamics between unemployment and the home price index due to the fact that the unemployment rate continues to oscillate within a reeling U.S. economy. Yaw Owusu-Ansaw examines these dynamics by applying the structural vector autoregression (SVAR) model to consider how unemployment and mortgage default rates coexist between 1979 and 2000 and subsequently between 2001 and 2010. First the model was applied to the first sample in order to trace any shifts in mortgage default rates at both the regional and national from the second sample. SVAR did well in forecasting the tenable changes in the national and regional default rates between 2001-2007. However, its efficacy was lost between 2008 and 2010 due to the housing bubble. Unemployment in addition to home price stocks figured far more prominently in the second sample because of the housing bubble which reached its apex in 2007 amidst the potentially catastrophic financial meltdown.

Works Cited

Englund, p. And y. M. Ioannides (1997). “House Price Dynamics: An International Empirical Perspective.” Journal of Housing Economics 6(1997): 119-136. Print.

Greenwood, J. and Z. Hercowitz. “The Allocation of Capital and Time Over the Business Cycle.” Journal of Political Economy 99(1991): 1188-1214.

Hiebert, Paul and Moreno Roma. “Relative house price dynamics across euro area and US cities Convergence or Divergence?” 2010. Web. 2 Dec. 2015. https://www.ecb.europa.eu/pub/pdf/scpwps/ecbwp1206.pdf

Jud, G. Donald and Daniel T. Winkler. “The Dynamics of Metropolitan Housing.” JRER 23.1/2(2002): 29-45. Print.

Malpezzi, S. “Housing Prices, Externalities, and Regulation in U.S. Metropolitan Areas.” Journal of Housing Research 7.2(1996): 209–42. Print.

Owusu-Ansa, Yaw. “Dynamics of Unemployment and Home Price Shocks on Mortgage Default Rates.” 2012. Web. 4 Dec. 2015. http://www.columbia.edu/~yao2103/wp2.pdf

Pages, Martinez and Jorge and Luis Angel Marza (2003). “Analysis of House Prices in Spain. Bank of Spain.” 2003. Web. 2 Dec. 2015. http://www.bde.es/informes/be/docs/dt0307e.pdf

Schilling, J.D., C.F. Sirmans, and K.A. Guidry. “The Impact of State Land-Use Controls on Residential Land Values.” Journal of Regional Science 30.1(1991): 83-92. Web. Urbanpolicy.berkeley.edu/pdf/QR2005.pdf

SGS Economics and Planning. “Understanding the Property and Economic Drivers of Housing.” SGS Economics & Planning. 2013. Web. 7 Oct. 2015. www.melbourne.vic.gov.au/Building andPlanning/FutureGrowth/Documents/Understanding_Property_Economics_Drivers_Housing.pdf

Zillow. “High Home Price-to-Income Ratios Hiding Behind Low Mortgage Rates.” Forbes Magazine. 2013. Web. 4 Dec. 2015. http://www.forbes.com/sites/zillow/2013/04/16/high-home-price-to-income-ratios-hiding-behind-low-mortgage-rates/

Yazgi, Burcin and Vedia Dokmeci. “Analysis of Housing Prices in the Metropolitan Area of Istanbul.” 2007. Web. 2 Dec. 2015. http://www.spacesyntaxistanbul.itu.edu.tr/papers%5Clongpapers%5C084%20-%20Yazgi%20Dokmeci.pdf