New Vacancy Data Adds Local Information to the Mix
Natalia Siniavskaia, Ph.D.
Multifamily developers and the analysts and researchers who track vacancy rates for them should be aware that there are now several sources of local vacancy rate data available to the general public on the internet. These include the Housing Vacancy Survey (HVS), the American Community Survey (ACS), and the newest data series, the US Postal Service/HUD (USPS) data base.
Table 1 presents a summary of the type of data that can be found in each of these data sources.
Housing Vacancy Survey
The traditional source of rental vacancy data is the Census Bureau’s HVS. The HVS provides timely vacancy data on a quarterly basis for the U.S. as a whole, as well as for the four principal census regions, and has been doing so since 1956. On an annual basis, it provides vacancy rates for all states, and for the 75 largest metropolitan areas. The greatest advantage of the HVS is its extended historic coverage. Having access to such long time-series allows analysts to evaluate not only short-term trends but also to figure out what vacancy rates can be considered natural for various geographic areas.
The US Census Bureau provides access to the HVS data free of charge. And, unlike other sources, the HVS provides data for both 2005 and 2006, thus allowing annual change comparison. Conveniently, the HVS vacancy rates are already tabulated for all available geographies and available at http://www.census.gov/hhes/www/housing/hvs/hvs.html.
American Community Survey
A second source of vacancy data is the American Community Survey (ACS). The ACS is designed to replace the decennial census long form and provide equivalent data on a timelier basis. It was implemented for the first time in 2001, but only in a limited number of areas. Currently, it is the largest household survey in the US, covering about 3 million addresses per year. Owing to its wide coverage of households, information – including rental vacancy rates – is available for many detailed levels of geography, including states, metropolitan areas, congressional districts, and a number of counties and cities. More geographic detail will become available after data is accumulated for five years.
However, it does not estimate vacancy rates explicitly. Rather, it provides summary counts of occupied and vacant housing units that can be used to calculate vacancy rates. Because it was first implemented on a wide geographic scale in 2005, the ACS does not yet show patterns over time. Another disadvantage of the ACS is that, just like any other survey-based data set, including the HVS, estimates’ margins of errors become rather large for lower levels of geography.
The US Census Bureau provides access to the ACS data free of charge at http://factfinder.census.gov/servlet/DatasetMainPageServlet?_program=ACS&_submenuId=&_lang=en&_ts=.
The great advantage of the ACS over the HVS is its wider geographic coverage. In 2005, the ACS covered only counties with population of 65,000 or more, but eventually it will report statistics for all counties, census tracts, and block groups using multi-year averages. Figure 1 displays county rental vacancy rates available in the 2005 ACS. Even though only a limited number of counties are covered, some patterns already emerge.
For example, coastal counties in the South tend to have higher rental vacancy rates – most likely a result of a higher share of seasonal and vacation properties.
U.S. Postal Service Records
The newest source of vacancy data comes from the Department of Housing and Urban Development (HUD). HUD recently entered into an agreement with the USPS to aggregate and publicly release Postal Service data on vacant addresses on a quarterly basis. The USPS data cover the entire universe of all addresses in the United States, and thus potentially can turn into a new timely “census-like” source of data on vacancies that provides comprehensive coverage at a very detailed level of geography, including states, counties and census tracts.
However, several features make the USPS data less attractive. The USPS data set:
does not separate residential and commercial properties;
employs an unusual definition of vacancy — as urban addresses not collecting their mail for 90 days or longer;
has an awkward “no-stat” category separate from vacant, which includes: 1) addresses under construction not yet occupied; 2) rural addresses vacant for 90 days or longer; 3) urban addresses identified by a carrier as not likely to be active for some time (e.g., if a building is being demolished to be replaced by another building, the address is preserved and considered “no-stat”);
has only been available for a limited time; not yet possible to identify local trends or see if vacancies are currently above or below some natural rate.
The USPS definition of vacant addresses is quite different from those in long-established survey-based data sources such as HVS and Decennial Census/ACS. The USPS data combine residential and commercial vacancies and do not include rural vacancies in the “vacant” category. The 90-day rule also is unique to this data set. These differences make it difficult to compare the USPS data to other popular vacancy data sources.
The USPS data also are available to the public free of charge at HUD’s website: http://www.huduser.org/datasets/usps.html. However, these raw data are not tabulated, and require additional steps before they can be loaded into Excel or any other statistical package.
As mentioned above, comparing the USPS results to the ACS and HVS is not straightforward, since the USPS data set does not differentiate between rental and homeowner vacancies, and combines residential and commercial empty properties. But analysis of these data might still bring some insights into cross-country variation in overall vacancies rates. Unfortunately, it is impossible to judge whether this cross-country variation is dominated by differences in commercial or residential vacancy rates.
One of the biggest advantages of the new USPS data set is that it provides vacancy data at a very detailed level of geography, including county and census tract. As the USPS data are refined and the longer time-series are collected, the dataset will become of a greater practical value to builders deciding whether and when to downsize or expand building operations in their locality.
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