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Survey of Market Absorption of Apartments (SOMA)
CHARACTERISTICS OF THE DATA
The Survey of Market Absorption (SOMA) measures how soon privately financed, nonsubsidized, unfurnished units in buildings with five or more units are rented or sold (absorbed) after completion. In addition, the survey collects data on characteristics such as number of bedrooms, asking rent, and asking price.
All statistics from the SOMA refer to apartments in newly constructed buildings with five units or more. Absorption rates reflect the first time an apartment is rented after completion, or the first time a condominium or cooperative apartment is sold after completion. If apartments initially intended to be sold as condominium or cooperative units are, instead, offered by the builder or building owner for rent, they are counted as rental apartments. Units categorized as federally subsidized are those built under two Department of Housing and Urban Development programs (Section 8, Low Income Housing Assistance and Section 202, Senior Citizen Housing Direct Loans) and all units in buildings containing apartments in the Federal Housing Administration (FHA) rent supplement program. The data on privately financed units include privately owned housing subsidized by state and local governments. Time-share units, continuing care retirement units, and turnkey units (privately built for and sold to local public housing authorities after completion) are outside the scope of the survey.
Tables 1 through 4 are restricted to privately financed, nonsubsidized, unfurnished rental apartments. Table 5 is restricted to privately financed, nonsubsidized, condominium and cooperative apartments, while Table 6 is limited to privately financed, nonsubsidized condominium apartments only. Table 7 covers privately financed, nonsubsidized, furnished, rental apartments and Table 8 is a historical summary of the totals for all types of newly constructed apartments in buildings with five units or more. Estimates published in this report are preliminary and are subject to revision in the H-130, Market Absorption of Apartments annual report.
NOTE TO DATA USERS
The SOMA adopted new ratio estimation procedures in 1990 to derive more accurate estimates of completions (see section on ESTIMATION). This new procedure was used for the first time in processing annual data for 1990. Please use caution when comparing completions in 1990 and following years with those in earlier years.
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, rent and price.
Buildings for the survey came from those included in the Census Bureau's Survey of Construction (SOC). For the SOC, the United States is first divided into primary sampling units (PSU's), 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 units or more that have been reported in the SOC sample as having been completed during that quarter. The SOMA does not include buildings in areas that do not issue permits. In eqach 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.
Beginning with data on completions in the fourth quarter of 1990 (which formed the base for absorptions in the first quarter of 1991), the Census Bureau modified the estimation procedure and applied the new estimation procedure to data for the other 3 quarters of 1990 so that annual estimates using the same methodology for 4 quarters could be derived. The Census Bureau did not perform any additional re-estimation of the past data.
Using the original estimation procedure, the Census Bureau created design-unbiased quarterly 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 design-unbiased estimate by the following ratio estimate factor for the country as a whole provides the following estimate:
total units in buildings with five units or more in permit-issuing areas as estimated by the SOC for that quarter divided by total units in buildings with five units or more as estimated by the by the SOMA for that quarter
Beginning with January 2001 completions, the SOC revised its methodology for estimating the number of units completed for 5+ multi-unit structures. See http://www.census.gov/ftp/pub/const/www/new_methodology_const.html for these changes. Thus, use caution when comparing data from 2001 and forward to any estimates prior to 2001.
In the modified estimation procedure, instead of applying a single ratio-estimate factor for the entire country, the Census Bureau computes separate ratio-estimate factors for each of the four Census regions. Multiplying the design-unbiased regional estimates by the corresponding ratio estimate factors provides the final estimates for regions. The Census Bureau obtains the final estimates for the country by summing the final regional estimates.
This procedure produces estimates of the units completed in a given quarter which are consistent with unpublished figures from the SOC and reduces, to some extent, the sampling variability of the estimates of totals. Annual absorption rates are obtained by computing a weighted average of the four quarterly estimates.
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 not-accounted-for cases constitute less than 2 percent of the sample housing units in this survey.
ACCURACY OF THE ESTIMATESThe SOMA is a sample survey and consequently all statistics are subject to sampling variability. Estimates derived from different samples would differ from one another. The standard error of a survey estimate is a measure of the variation among the estimates from all possible samples. The methodology for calculating standard errors is explained below.
Two types of possible errors are associated with data from sample surveys: nonsampling and sampling 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 interpretation of 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 has been obtained, the Census Bureau thinks that most of the important response and operational errors were detected during review of the data for reasonableness and consistency.
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 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, each of them was surveyed under the same general conditions, and an estimate and its estimated standard error were calculated from each sample, then:
Approximately 68 percent of the intervals from one standard error below the estimate to one standard error above the estimate (i.e., the 68-percent confidence interval) would include the average result from all possible samples.
Approximately 90 percent of the intervals from 1.6 standard errors below the estimate to 1.6 standard errors above the estimate (i.e., the 90-percent confidence interval) would include the average result from all possible samples.
Approximately 95 percent of the intervals from two standard errors below the estimate to two standard errors above the estimate (i.e., the 95-percent confidence interval) would include the average result from all possible samples.
This report uses a 90-percent confidence level as its standard for statistical significance.
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 reliability of an estimated absorption rate (i.e., a percentage) computed by using sample data for both the numerator and denominator depends on both the size of the rate and the size of the total on which the rate is based. Estimated rates of this kind are relatively more reliable than the corresponding estimates of the numerators of the rates, particularly if the rates are 50 percent or more.
Tables A, B and C present approximations to the standard errors of various estimates shown in the report. Table A presents standard errors for estimated totals, and Tables B and C present standard errors of estimated percentages for rental apartments and condominiums, respectively. To derive standard errors that would be applicable to a wide variety of items and could be prepared at moderate cost, a number of approximations were required. As a result, the tables of standard errors provide an indication of the order of magnitude of the standard errors rather than the precise standard error for any specific item. Standard errors for values not shown in Tables A, B, or C can be obtained by linear interpolation.
ILLUSTRATIVE USE OF THE STANDARD ERROR TABLES
Table 2 of this report shows that there were about 23,000 new apartments built in 2004 with an asking rent of $750 - $849. Table A shows the standard error of an estimate of this size to be approximately 2,380. To obtain a 90-percent confidence interval multiply 2,380 by 1.6 and add and subtract the result from 23,000 yielding limits of 19,190 and 26,810. The average estimate of these units completed in 2002 may or may not be included in this computed interval, but one can say that the average is included in the constructed interval with a specified confidence of 90 percent.
Table 2 also shows that the rate of absorption after 3 months for these apartments renting for $750 - $849 is 59 percent. Table B shows the standard error on a 59 percent rate on a base of 23,000 to be approximately 5.3 percent. Multiply 5.3 by 1.6 (yielding 8.5) and add and subtract the result from 59. The 90-percent confidence interval for the absorption rate of 59 percent is from 50 percent to 68 percent.
Table 2 also shows that the median asking rent for the estimated 22,900 one-bedroom apartments built in the South was $796. The standard error of this median is about $28.
Several statistics are needed to calculate the standard error of a median.
The base of the median -- the estimated number of units for which the median has been calculated. In this example, 22,900.
The estimated standard error from Table B of a 50-percent characteristic on the base of the median (sigma 50%). In this example, the estimated standard error of a 50-percent characteristic with the base of 22,900 is about 5.4 percent.
The length of the interval that contains the median. In this example, the median lies between $750 and $849. The length of the interval is $100.
The estimated proportion of the base falling in the interval that contains the median. In this example, 19 percent (4,300 units completed in the South renting for $750 to $849 / 22,900 total units completed in the South). The standard error of the median is obtained by using the following approximation:
Standard error of median = sigma 50% times [length of interval containing the sample median] divided by [estimated proportion of the base falling within the interval containing the sample median]
For this example, the standard error of the median of $796 is:
5.4 X 100/19 = $28
Therefore, 1.6 standard errors equals $45. Consequently, an approximate 90-percent confidence interval for the median asking rent of $796 is between $751 and $841 ($796 plus or minus $45).