Survey of Market Absorption of Apartments (SOMA) 

NOTE TO DATA USERS
The SOMA adopted new ratio estimation procedures in 1990 to derive more accurate estimates of completions^{1}. Please use caution when comparing the number of completions in 1990 and following years with those in earlier years.
SAMPLE DESIGN
The U.S. Census Bureau designed the survey to provide data concerning the rate at which privately financed, nonsubsidized, unfurnished units in buildings with five or more units are rented or sold (absorbed). In addition, the survey collects data on characteristics such as number of bedrooms, asking rent, and asking price.
Buildings for the survey come from those included in the Census Bureau's Survey of Construction (SOC)^{2}. For the SOC, the United States is first divided into primary sampling units (PSUs), which are stratified based on population and building permits. The PSUs to be used for the survey are then randomly selected from each stratum. Next, a sample of geographic locations that issue permits is chosen within each of the selected PSUs. All newly constructed buildings with five units or more within sampled places and a subsample of buildings with one to four units are included in the SOC.
For the SOMA, the Census Bureau selects, each quarter, a sample of buildings with five or more units that have been reported in the SOC sample as having been completed during that quarter. The SOMA does not include buildings completed in areas that do not issue permits.
In each of the subsequent four quarters, the proportion of units in the quarterly sample that are sold or rented (absorbed) are recorded, providing data for absorption rates 3, 6, 9, and 12 months after completion.
The Census Bureau publishes preliminary estimates for a given quarter and may revise these estimates in ensuing quarters. Each quarter, some of the absorption data for some buildings arrive after the deadline for that quarter’s report; these late data appear in a revised table in the next quarterly report. Final data appear in the Census Bureau’s H130 report series, Market Absorption of Apartments annual report.
Beginning with data on completions in the fourth quarter of 1990 (which formed the basis for absorptions in the first quarter of 1991), the Census Bureau modified the estimation procedure and applied the new procedure to the data for the other three quarters of 1990, so that annual estimates using the same methodology for four quarters could be derived. The Census Bureau did not perform any additional reestimation of past data.
Using the original estimation procedure, the Census Bureau created designunbiased estimates by multiplying the counts for each building by its base weight (the inverse of its probability of selection) and then summing over all buildings. Multiplying the designunbiased estimate by the following ratio estimate factor for the country as a whole provided the final estimate:
In the modified estimation procedure, instead of applying a single ratioestimate factor for the entire country, the Census Bureau computes separate ratioestimate factors for each of the four census regions. Multiplying the unbiased regional estimates by the corresponding ratioestimate factors provides the final estimate for regions. The Census Bureau obtains the final estimate for the country by summing the final regional estimates.
This procedure produces estimates of the units completed in a given quarter that are consistent with the published figures from the SOC and reduces, to some extent, the sampling variability of the estimates of totals.
Absorption rates and other characteristics of units not included in the interviewed group or not accounted for are assumed to be identical to rates for units about which data were obtained. The noninterviewed and notaccountedfor cases constitute less than 2 percent of the sample housing units in this survey..
ACCURACY OF THE ESTIMATES
The SOMA is a sample survey and consequently all statistics in this report are subject to sampling variability. Estimates derived from different samples would likely differ from these.
Two types of possible errors are associated with data from sample surveys: nonsampling and sampling.
Nonsampling Errors
In general, nonsampling errors can be attributed to many sources: inability to obtain information about all cases in the sample, difficulties with definitions, differences in interpretating questions, inability or unwillingness of the respondents to provide correct information, and data processing errors. Although no direct measurements of any bias that might result from nonsampling errors have been obtained, the Census Bureau thinks that many of the important response and operational errors were detected during review of the data for reasonableness and consistency.
Sampling Errors
The particular sample used for this survey is one of many possible samples of the same size that could have been selected using the same design. Even if the same questionnaires, instructions, and interviewers were used, estimates from different samples would likely differ from each other. The deviation of a sample estimate from the average of estimates from all possible samples is defined as the sampling error. The standard error of a survey estimate provides a measure of this variation and, thus, is a measure of the precision with which an estimate from a sample approximates the average result from all possible samples.
If all possible samples were selected, if each was surveyed under the same general conditions, and if an estimate and its estimated standard error were calculated from each sample, then:
This report uses a 90percent confidence level as its standard for statistical significance^{4}. The estimates in this report show the totals, percents, and medians with the 90percent confidence interval.
For very small estimates, the lower limit of the confidence interval may be negative. In this case, a better approximation to the true interval estimate can be achieved by restricting the interval estimate to positive values, that is, by changing the lower limit of the interval estimate to zero.
The average result from all possible samples either is or is not contained in any particular computed interval. However, for a particular sample, one can say with specified confidence that the average result from all possible samples is included in the constructed interval.
For example, Table 8 of this report shows that there were about 2,500 condominium apartments completed in buildings with five units or more during the second quarter of 2009 in the West region. The 90percent confidence interval around this estimate is +/ 600. Thus the 90percent confidence interval shown by these data is 1,900 to 3,100. A conclusion that the average estimate derived from all possible samples lies within a range computed in this way would be correct for roughly 90 percent of all possible samples.
Footnotes
1. See Estimation.
2. See Section V (sample design) for further details on the SOC sample design.
3. Beginning with January 2001 completions, the SOC revised its methodology for estimating the number of units completed for 5+ multiunit structures. See http://www.census.gov/ftp/pub/const/www/new_methodology_const.html for these changes. Thus, caution is advised when comparing data from 2001 and forward to any estimates prior to 2001.
4. Beginning with data for completions in the second quarter of 1999, the Census Bureau implemented a new procedure for computing standard errors. The new procedure may result in differences in standard errors derived using the prior methodology, so standard errors were revised back to the third quarter of 1998.