August 1, 2014
By Natalia S. Siniavskaia, Ph.D.
Report available to the public as a courtesy of HousingEconomics.com
One of the often overlooked impacts of building regulations is their effect on housing affordability. Every time a local or higher level government issues a new construction regulation it raises construction costs by, for example, increasing the price of construction permits or impact fees. Higher costs invariably translate into higher home prices and higher prices in turn disqualify more households from being able to afford new homes. NAHB Economics relies on its Priced Out model to evaluate effects of pending new regulations on housing affordability in local markets. The model estimates how many households can qualify for a mortgage before and after a house price increase. The resulting difference is the number of priced out households.
NAHB regularly updates the Priced Out model to account for changing economic environment. This article presents and discusses the new 2014 priced out estimates for the United States and 324 metro areas. The 2014 estimates show that nationally a $1,000 increase in the home price leads to pricing out about 206,269 households. The size of the impacts varies across states and metro areas and largely depends on their population, income distribution and new home prices.
The Priced Out Methodology and Data
Most home buyers take out a mortgage to finance a purchase of a new home, so the Priced Out model uses ability to qualify for a mortgage as an affordability standard. To qualify for conventional loans, housing expenses should not exceed 28 percent of homebuyers’ gross monthly income. Monthly housing costs include principal and interest on the mortgage, property taxes and homeowner’s Insurance – often abbreviated as “PITI”. The affordability standard is thus a ratio of housing expenses to income, and the number of households that qualify for a mortgage to buy a home of a given price will depend on the income of households in an area and current mortgage rates.
The American Community Survey (ACS) which replaced the decennial Census long form provides the detailed income distribution for the United States and all states and metro areas with population of 65,000 people or more annually. The most recent income estimates are now available for 2012. To adjust for expected 2012-2014 income growth, NAHB uses the annual estimates of median family income published by the Department of Housing and Urban Development (HUD) for every state and county. The 2014 estimates were made available in December 2013. To adjust for population growth, NAHB relies on annual household estimates reported by the ACS and extrapolates the most recent household growth into 2014. Table below shows the projected US household income distribution that underlies the 2014 priced out estimates.
Other assumptions used in the priced out calculations are a down payment equal to 10 percent of the purchase price and a 30-year fixed rate mortgage. The mortgage interest rate is set at 4.5 percent with zero points. For this typical loan, the model also assumes lenders require private mortgage insurance with an annual premium of 45 basis points. Effective local property tax rates come from the 2012 ACS. The ACS reports both median home values and real estate taxes paid and, thus, allows estimating the effective property tax rates for all metro areas. For the US, the median rate is $12 per $1,000 of property value. Property hazard insurance rates are constructed based on the 2007 ACS Public Use Microdata Sample (PUMS). For the US as a whole, the insurance rates work out to $5 per $1,000 of property value.
The priced out analysis requires a representative house price as a starting point. Data availability pretty much limits the choices to basic summary statistics, like the median or average home price. Of the two, the median usually makes a better starting point for priced-out calculations, as the average tends to be skewed upward by a handful of expensive homes, while the median typically lies in the center of the price range where more new homes are built. To analyze changes in regulatory or other construction costs, prices of new homes are most relevant, since new homes are the ones directly affected by new regulations.
The median new home price for the United States is set at $275,000 for 2014. It is based on monthly median new home prices reported by the Census Bureau over 2013 and the first four months of 2014. First, the average of monthly medians is estimated over 2013. It is then adjusted for expected inflation based on price appreciation that took place over the first four months of 2014.
To estimate median new home prices for states and metropolitan areas, NAHB relies on data reported by the 2013 Census Bureau’s Building Permits Survey and Survey of Construction (SOC). The Permits Survey provides both the number and aggregate value of new housing units authorized by building permits and, thus, allows calculating average permit values for all states and metro areas. For metro areas where average permit values are highly volatile and likely to have a large margin of error, the averages are smoothed out across most recent years.
Permit values, however, do not include brokerage commissions, marketing/finance costs, the cost of raw land and may not include the cost of lot’s development. These additional costs are likely to differ across geographic areas but not available for metro areas. Nevertheless, the SOC provides enough data to tabulate median new home prices for all nine Census divisions and, consequently, division-wide ratios of median new home prices to average permit value. The ratios are then used as scaling mark-ups to convert state and metro average permit values into median new home prices. The resultant median new home prices range from less than $116,704 in Brownsville-Harlingen, TX to more than $878,625 in Bridgeport-Stamford-Norwalk, CT (see Table 2).
Metro Priced Out Results
Table 1 and Table 2 present the priced out results and data that underlie the estimates for all states and 324 metropolitan areas. In addition to median new home prices, the tables display income needed to qualify for a mortgage to buy a median price new and the number of households that will be priced out of the market for a new home if its price increases by $1,000.
A typical household in Brownsville-Harlingen, TX, where half of all new homes are sold for less than $116,704, needs an annual income of $35,831 to qualify for a mortgage, while a household in Bridgeport-Stamford-Norwalk, CT will need to earn $240,996 to qualify for a new home loan. Clearly, these differences are driven by large divergences in new home prices across metropolitan areas. The more expensive new homes, the higher monthly principal and interest payments, the higher income required to qualify for a mortgage. But the relationship is not always linear as property tax and insurance payments also affect monthly housing costs. For example, even though Brownsville-Harlingen, TX metro area has the lowest median price new homes, the income needed to qualify for a mortgage to buy these homes are not the lowest in the nation. Sumter, SC, Florence-Muscle Shoals, AL, Valdosta, GA, Clarksville, TN-KY all have new homes that are more expensive but require a lower income to qualify for a mortgage. This is a result of higher property tax and insurance payments in Texas.
Next, the priced out model estimates how many households in each state and metro area actually earn enough income to qualify for new home loans. Not surprisingly, in Bridgeport-Stamford-Norwalk, CT metro area where new homes largely target the high income households, only 1 percent of all households residing in this metro area earn enough money to qualify for a new home loan. Among other metro areas with least affordable new homes are Buffalo-Niagara Falls, NY, Barnstable Town, MA, Sebastian-Vero Beach, FL, and Napa, CA where less than 15 percent of all households can afford a median price new home. In sharp contrast stand metro areas like Dover, DE and Jacksonville, NC where two out of three households residing in these metros can afford a median-priced new home.
These differences translate into different effects of adding $1,000 to a new home price. When starting affordability of new homes is low the priced out effects will be small since they would only affect a few households at the thin end of the household income distribution. On the contrary, if new homes are widely affordable, rising home prices would affect a bigger slice of households in the thicker part of the income distribution and the priced out effects will be larger.
Increasing a price of a new home in New York-Northern New Jersey-Long Island, NY-NJ-PA, by $1,000 disqualifies 5,742 households from buying a new home. This is by far the largest priced out effect among metropolitan areas, mainly as a result of being the most populous metro area with more than 7 million households. The second largest number of priced out households is in Chicago-Naperville-Joliet, IL-IN-WI, where more than 5,325 households are priced out. The Chicago metro is half the size of the New-York metro area but the priced out effects are similarly large. This is because the Chicago area is relatively more affordable to begin with. Close to a third of all local households are able to afford new homes here while in the New-York area only 19 percent of households can qualify for new home mortgages before any price hikes.
Los Angeles-Long Beach-Santa Ana, CA - the second most populous metro area with more than 4 million households but low affordability – registers only the sixth highest number of priced out households, 3,813. Ahead of Los Angeles on the priced-out effects list are three large metro areas with more affordable new homes. In Houston-Sugar Land-Baytown, TX and Atlanta-Sandy Springs-Marietta, GA, where almost half of all households can afford new homes, the priced out effects exceed 4,000 households. In Philadelphia-Camden-Wilmington, PA-NJ-DE-MD where 41 percent of households can afford new homes an increase in new home price of $1,000 disqualifies 3,914 households.
At the other end of the spectrum are small and often unaffordable high new home priced metropolitan areas. In Barnstable Town, MA where half of all new homes sell for more than $616,381, adding another thousand to a price, affects only 24 households, since there were only a few of them who could afford such expensive new homes in the first place. In Napa, CA, where new homes are similarly unaffordable the priced out effects are only limited to 19 households. Looking at the affordable metro areas, where close or more than fifty percent of households can afford new homes, the priced out effects are typically large and can often disqualify thousands of new home buyers, as in case of Houston-Sugar Land-Baytown, TX, Atlanta-Sandy Springs-Marietta, GA , Las Vegas-Paradise, NV MSA, Baltimore-Towson, MD among other metro areas.
Among the states, Texas registers the highest priced out effects where more than 18,000 households can be pushed out of the market for a median-priced new home here if its price increases by $1,000. California that is more populous but has less affordable new homes register the second highest priced out effects – 14,423 households.
Quite frequently and often unintentionally local regulations raise construction costs and trigger hikes in home prices. NAHB consistently relies on the priced out model to estimate the impacts of price changes. Even though the model does neither answer all questions nor estimate effects of regulation on new home sales or housing starts, it highlights often overlooked effects of regulation on affordability of new homes. The new 2014 estimates show that, in relatively affordable metro areas, hundreds and sometimes thousands of households can be priced out of the new home markets as a result of prices rising by $1000.
Note: Regulatory Costs Boost Home Prices by up to 39 Percent More than Building Fee Increases
Hidden in median new home prices is the cost of government regulations. NAHB research shows that, on average, regulations imposed by government at all level account for 25 percent of the final price of a new single family home built for sale. Every time a local or regional government raises construction costs by, for example, increasing the price of construction permits or impact fees, the cost of building a house rises. In fact, the final price of the home to the buyers will usually go up by more than the increase in the government fee. This is because each time construction costs increase other costs such as commissions and financing charges automatically rise as well. As a result, most cost increases are passed on to the buyers with additional charges. The size of these charges depends both on the type of fee/cost increase and when it is imposed in the development/construction process. NAHB estimates that the add-on charges range from 0 percent if a fee is imposed directly on buyers to 39 percent if cost is incurred when applying for site development approval (see Table 3). So that for every $1 increase in fees incurred, for example, when acquiring a building permit, the final price of a new home to its final customer rises by $1.20. Alternatively, every $833 increase in fees results in a $1,000 increase in house prices.
Download the Full Article (PDF)
Table 1 - Metro (PDF)
Table 2 - State (PDF)
See other Special Studies
 In cases, where counties comprising a metro area are estimated to have different median incomes, an estimate for the county containing the core urban area listed first in the name of the metro area is set to represent the median family income for the entire metro area.
 In the PITI formula, mortgage insurance is essentially treated as part of the interest payment. Like interest on the loan, it is a percentage of the declining mortgage balance.
 Producing metro level estimates from the ACS PUMS involves aggregating PUMA level data according to the latest definitions of metropolitan areas. Due to complexity of these procedures and since metro level insurance rates tend to remain stable over time, NAHB revises these estimates only periodically.
 See P. Emrath “How Government Regulation Affects the Price of a New Home”, Housing Economics Online, July 2011.