Rent/Price Ratio Data
2000-2014 Price/rent ratio data and commentary on overall change
The following chart and data, outlining the Gross Rent-Price Ratio for U.S. properties from 1960 through early 2014, were retrieved from the Lincoln Institute of Land Policy; however, it is important to note that the focus of this paper will be the period between 2000 and 2014.
Figure 1. Land and Property Values in the U.S.: Rent-Price Ratio
Figure 1. Land and Property Values in the U.S.: Rent-Price Ratio. Copyright 2015 by Lincoln Institute of Land Policy.
Case-Shiller Index: Rent-Price Ratio
|CSW Rent-Price Ratio||Difference to Prior|
Note. Adapted from Land and Property Values in the U.S.: Rent-Price Ratio. Copyright 2015 by Lincoln Institute of Land Policy.
As can be seen in the chart and table, the changes that occurred between the years 2000 and 2014, according to the data shown from Case-Shiller (CSW), demonstrate the ratio dropping by more than one and a half percentage points from a high for the reported period in January 2000 to a low point in January 2006, rebounding by roughly the same percentage back to a near-peak in January 2012, and then receding by roughly half a percentage point in of January 2014.
Lowest and highest points of rent/price ratio data relative to economic events
Regarding the highs and lows in rent/price ratio data for the reported period, a peak in the ratio represents the point at which purchase annualized rents (numerator) relative to average prices (denominator) converged more closely, and the lowest point of the ratio is found when those rents have diverged from prices. In terms of context for the highest and lowest points of the rent/price data cited above for January 2000 and January 2006, multiple news outlets covered what are now described as the “housing bubble” (Shiller, 2007) and “The Great Recession” (Lennihan, 2013), respectively. As of January of 2000, the U.S. had experienced an unprecedented 10-year expansion that was coming to an end (Martel et al., 2001). As described in a working paper for the National Bureau of Economic Research by Robert Shiller, author of the Case-Shiller index, the cause for the expansion was irrational buyer expectations for ever-growing marginal benefit, which will be explored more later in this paper:
The view developed here of the boom in home prices since the late 1990s has it operating as a classic speculative bubble, driven largely by extravagant expectations for future price increases. (Shiller, 2007).
Subsequent to March 2001, reports cited studies from Federal Reserve Banks and the Bureau of Labor Statistics showing that by mid-2006, “US home prices peaked after decades of financial deregulation and government promotion of home ownership,” and in December 2007 the “Great Recession” officially began (Lennihan, 2013). The following graph illustrates this change:
Figure 2. Case-Shiller Home Price and Rent Data: 1/2000 to 1/2014
Figure 2. Adapted from Land and Property Values in the U.S.: Rent-Price Ratio. Copyright 2015 by Lincoln Institute of Land Policy.
After home prices reached their peak in 2006, where the rent/price ratio showed its lowest point in Figure 1, home values corrected through early 2012.
Rental Housing vs. Owner-Occupied Housing
Whether rentals and owner-occupied housing are substitutes or complements
In terms of whether rentals and owner-occupied housing are substitutes or complements, economic theory suggests we must consider their cross-price elasticity of demand (Samuelson et al., 2014). The data provided for this project only includes prices, not demand/sales numbers of existing homes (and existing home sales are the foundation for the CSW Index), which are need to establish elasticity of demand. The following data on U.S. unit sales of existing homes from the National Association of Realtors and the Federal Reserve Bank of St. Louis (FRED) provides insight into demand quantities during the years analyzed in the earlier section:
Figure 3. Existing Home Sales
Figure 3: From Federal Reserve Economic Data (FRED) – Existing Home Sales. Copyright 2015 of source data by National Association of Realtors.
Economic theory states that when an increase in price for one good causes an increase in demand for the other, cross-price elasticity (Ep) will be negative if they are complements and positive if substitutes (Samuelson et al., 2014). Combining the CSW price index with the FRED unit sales data we find:
Cross Elasticity of Demand: Rental Prices Relative to Existing Home Unit Sales
|Existing Home Unit Sales (Q)||Annualized Rental Prices (P)|
Note. Adapted from Land and Property Values in the U.S.: Rent-Price Ratio and Existing Home Sales. Copyright 2015 by Lincoln Institute of Land Policy and National Association of Realtors, respectively.
Using the selected data from January 2000 and January 2014, the cross-price elasticity of demand is negative, suggesting on the surface that rental housing and owner-occupied housing are complements. Also, it is important to recall Shiller’s earlier statement regarding buyer exuberance for homes. While housing is considered a normal good, because as income rises homeownership is more desirable, economic theory holds that renting is an inferior good (Mackenzie, 2003). However, it is worth noting that the magnitude of EP at .27 suggests that while the two are complements they are not a strong a set of complements were the ratio to be closer to -1.
Relationship of the rent/price ratio and demand for owner-occupied housing
Multiple media, lending, and real estate publications, including Forbes, Bankrate.com, CNN, and Trulia, all suggest to prospective home buyers that they analyze the rent/price ratio, or more popularly, the price/rent ratio, before considering buying a home – in other words, if prices are rising faster than rents, consider renting instead (Google, 2015). As a result, if consumer psychology plays an important part in driving demand, per the earlier citation from Robert Shiller on housing bubbles, one would expect to find that the rent/price ratio has a strong correlation to owner-occupied housing demand. The subsequent figure illustrates the relationship between the rent/price ratio (CSW) and demand for owner-occupied housing demand (FRED):
Figure 4. Rent/Price Ratio and Owner-Occupied Housing Demand
Figure 4. Adapted from Land and Property Values in the U.S.: Rent-Price Ratio and Existing Home Sales. Copyright 2015 by Lincoln Institute of Land Policy and copyright 2015 by National Association of Realtors, respectively.
The data shows that between 2000 and 2014, there is a moderate negative correlation between the rent/price ratio and demand for existing housing, when applying a Pearson product moment correlation to the two data sets using the same time period for each trendline. Based on the sample analyzed in this paper, one could conclude that there is a demonstrated, albeit not ‘extravagant’, negative relationship between the rent/price ratio and demand for owner-occupied housing.
Impact of Changes in Rent/Price Ratio
How increases and decreases in the rent/price ratio affect demand for rental units, along with the marginal benefit and the marginal cost of owning
Per the data presented above, and perhaps counter to the media coverage, the negative correlation between the rent/price ratio and existing home demand suggests buyers in fact were not fully utilizing the Case-Shiller data in their decision to buy a home. Assuming that they were, an increase in the rent/price ratio would mean that rents are more expensive relative to buying, and as a result, demand for rentals should drop. Data from the Joint Center for Housing Studies at Harvard University (JCHS) has shown a correlating decline and then flattening in rental unit demand when this author compared it to the same trend shown by the CSW in the ratio from 2000-2006 (JCHS, 2015). Using this data, the following table provides a detailed view into how changes in the rent/price ratio should affect rental demand and marginal benefits & costs of ownership:
Outcomes of Increases & Decreases in Rent/Price on Demand and Marginals
|Ratio Increase||Ratio Decrease|
|Rental Demand||If faster than income growth, reduces demand||Increases demand|
|Ownership Marginal Benefit||Mortgage payments can be less than renting; owners charge more for rent (e.g. AirBnB)||Home equity may increase, improving borrowing options|
|Ownership Marginal Cost||Equity decreases relative to mortgage, maintenance and upkeep fees||Mortgage payments increase opportunity cost relative to renting; borrowing fees and taxes grow|
Note. Adapted from Run-up in the House Price-Rent Ratio: How Much Can Be Explained by Fundamentals? and The State of the Nation’s Housing 2015. Copyright 2007 by U.S. Bureau of Labor Statistics, and 2015 by Joint Center for Housing Studies at Harvard University, respectively.
The assertions in the table may seem controversial on the surface, but they follow logic and theory. As stated in a piece on home ownership in The Economist from 2014:
Rents cannot grow much faster than the rate of income growth or demand will tumble. As the cost of buying rises relative to rents, new market entrants seeking housing services will increasingly opt to rent. As the flow of new buyers dries up, price growth will necessarily slow, tipping the credit loop into contraction. (Economist, 2014).
In other words, variance in the ratio are impacted by and impact factors beyond just the rents and prices themselves, including supply, income, mortgage rates, and production, as will be discussed next.
How a rising ratio impacts production decision making
Most of this paper has focused on the effects or the ratio as it relates to consumer demand; however, the impacts to the supply side and their production decision making must be considered as well. Four of the main constituents on the supply side are: contractors, mortgage lenders, business suppliers, and landlords. As reviewed in the preceding section, based on JCHS data, a positive correlation exists between rental demand and the rent/price ratio. The following graph further shows that for the period from 2000-2014, rental demand and supply rose in tandem as well, suggesting that as a whole those four constituents functioned in unison to match rental supply to demand and therefore to the rent/price ratio:
Figure 5. Apartment Demand and Supply 2000-2014
Figure 5. From The State of the Nation’s Housing 2015. Copyright 2015 by Joint Center for Housing Studies at Harvard University.
When considering the four constituents individually, an increasing rent/price ratio means that in lieu of building single-family dwellings, contractors will build more multi-unit dwellings to support rental landlords, mortgage lenders will fund developers and landlords who need capital for these rental units, business suppliers such as permit issuers will move their headcount staffing to focus on developers of multi-unit dwellings, and landlords will continue to develop these new units for a rental market until the equilibrium price (the supply of goods matches demand) is found. Even as recently as October of 2015, Reuters reported that the demand for rental apartments boosted U.S. housing starts, one of the engines for continuing economic growth (Mutikani, 2015).
The Recent Housing Crisis
A specific housing market failure and how the government responded
There are three core causes of market failure: monopoly power, externalities, and imperfect information (Samuelson, 2014). While one might argue that all three were at play during the recent housing crisis and subsequent Great Recession, the focus of this paper will be on the role of imperfect information. It is important to note that imperfect information existed not only for the consumers who bought homes but for the consumers of the mortgage-backed securities (MBSs) that provided capital to fund the loans to those homebuyers. On the consumer side, a Journal of Urban Economics study funded by the Board of Governors for the Federal Reserve uncovered significant underestimation of the interest rate reset risks among consumers of subprime adjustable-rate mortgages (ARMs) during the housing crisis, which accounted for 53% of all mortgage products sold (Bucks, 2008). On the creditor side, while subprime borrowers were not new players to the market and showed similar characteristics on paper as conforming homebuyers, the speed of growth and breadth of this category spread the risk of default because transparency did not increase contemporaneously: “With less equity and no established history of making mortgage payments, both the heterogeneity of the pool and the lack of market knowledge about how these loans would perform over a cycle increased” (Green, 2008).
While there were numerous subsequent government responses to the market failure, specific to righting the information asymmetry, there were two critical actions. First, in October 2008 the U.S. Treasury launched the Troubled Asset Relief Program (TARP), which gave the Treasury $700 billion to buy illiquid mortgage-backed securities and other assets from key financial institutions in an attempt to restore liquidity to the money markets (Investopedia, 2015). In doing this, the Treasury stabilized the mortgage market by simultaneously making more transparent where the most troubled MBS’s existed and effectively removing them from the open market. Second, in July 2010 the Dodd Frank act was passed. Dodd Frank enabled mortgage consumers to better understand their lending options among competing banks along with better information disclosures on interest and payments along with easier-to-understand forms (Carrns, 2015). For lenders, both programs increased the responsibility of brokers and mortgage consumers to properly disclose key lending criteria including household income, existing debts and liens, and other data regarding credit risk.
The government-led initiative to increase homeownership and why the government would subsidize homeownership
Programs introduced during the Clinton and Bush administrations were designed to promote homeownership across all economic strata of American society. Under President Clinton’s architect of the “The National Homeownership Strategy: Partners in the American Dream” (HUD, 1995), Henry Cisneros, the government wanted to subsidize home ownership because:
There is the economic evidence that suggests a ticket to the middle class for Americans is to become a homeowner. So if we want to close the gap — not just in income, but in wealth in our country — then helping people become homeowners is an important part of the economic rationale (Vigeland, 2010).
Subsequently, President Bush’s administration included a push for what he called an “Ownership Society,” by enabling citizens to take more control from government over their own financial destiny:
For much of the Bush presidency [post 9/11]… on the economic front, its pressing concerns were cutting taxes and privatizing Social Security, a government retirement and disability benefits program. The housing market was a bright spot: Ever-rising home values kept the economy humming, as owners drew down on their equity to buy consumer goods and pack their children off to college. (Becker et al., 2008)
Moreover, as mentioned earlier regarding the production/supply side, housing starts are widely seen as one of the key indicators regarding the health of the economy. Beyond the theory and rhetoric cited, the following data shows how government subsidies caused demand to continue rising even as house prices also increased up until 2006 when the market failed:
Figure 6. Existing Home Prices and Sales
Figure 6: Adapted from Existing Home Sales vs. Home Prices. Copyright 2015 by National Association of Home Builders.
Ironically during both presidencies, the assertion was that homeownership represented a public good and created positive externalities. However, the classic definition of a public good includes nonrivalry, where increased consumption of the good doesn’t decrease the amount available to others — which is antithetical to the definition of homeownership. And in terms of externalities, they were more negative than positive: government subsidies actually created banking monopolies that were ‘too big to fail’ and created deadweight loss in the form of homebuyer mortgage defaults and abandoned homes (Becker et al., 2008).
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