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How the Data are Collected (Building Permits Survey)

PURPOSE

The purpose of the Building Permits Survey (BPS) is to provide national, state, and local statistics on the number and valuation of new privately-owned housing units authorized by building permits in the United States. The United States Code, Title 13, authorizes this survey and provides for voluntary responses.



SOURCE OF DATA AND SURVEY QUESTIONNAIRES

The statistics from the Building Permits Survey are based on reports that are submitted by local building permit officials in response to a voluntary mail survey. The data are collected using Form C-404, "Report of Building or Zoning Permits Issued for New Privately-Owned Housing Units." Annual respondents receive an introductory letter each year.



GEOGRAPHIC COVERAGE

Building permits data are collected from individual permit offices, most of which are municipalities; the remainder are counties, townships, or New England and Middle Atlantic-type towns. Because building permits are public records, local area data can be published without any confidentiality concerns. From local area data, estimates are tabulated for counties, states, metropolitan areas, Census Divisions, Census Regions, and the United States. Data are also collected for Puerto Rico and U.S. territories, although these areas are excluded from the national estimates.

For more geographic information, please refer to the definitions of Census Regions and Divisions and metropolitan areas

The Building Permits Survey covers all "permit-issuing places," which are jurisdictions that issue building or zoning permits. Zoning permits are used only for areas that do not require building permits but require zoning permits. Areas for which no authorization is required to construct a new privately-owned housing unit are not included in the survey.

Periodically, we use Form C-411 "Survey of Residential Building or Zoning Permit Systems" to canvass active governments in the United States. An introductory letter explains the survey. The Building Permits sampling frame or "universe" is updated by adding all places that reported the establishment of a new permit system since the last canvass. The universe is defined as all unique permit offices at the time the sample is selected. Unique permit offices are those jurisdictions that would not result in double reporting. For example, if a city issues zoning permits and its county issues building permits (including permits for buildings in the city), only the county office is included in the universe. The numbers associated with the various universes are:

  • 1959 Universe included approximately 10,000 permit-issuing places and was used from January 1959 to December 1962
  • 1963 Universe included approximately 12,000 permit-issuing places and was used from January 1963 to December 1966
  • 1967 Universe included approximately 13,000 permit-issuing places and was used from January 1967 to December 1971
  • 1972 Universe included approximately 14,000 permit-issuing places and was used from January 1972 to December 1977
  • 1978 Universe included approximately 16,000 permit-issuing places and was used from January 1978 to December 1983
  • 1984 Universe included approximately 17,000 permit-issuing places and was used from January 1984 to December 1993
  • 1994 Universe included approximately 19,000 permit-issuing places and was used from January 1994 to December 2003
  • 2004 Universe included approximately 19,300 permit-issuing places and was used from January 2004 to December 2013
  • 2014 Universe includes approximately 20,100 permit-issuing places and is used from January 2014 forward

The impact of updating the universe of permit-issuing places is shown in the Building Permits Universe Overlap table. It shows the number of housing units authorized by building permits for both the new and the old universe in the year that the universe was updated, going back to 1963.

The list of jurisdictions from which permits data are collected is updated monthly to reflect ongoing changes in permit coverage reported to the Census Bureau by local governments. These updates are reflected in the data for individual permit-issuing places, but all other estimates include only areas that had permit coverage at the time the current universe was established. This provides data that can be compared over time without the need to account for changes in permit coverage.



SAMPLE DESIGN

Slightly less than half of the permit-issuing places in the United States are surveyed monthly. The remainder of places are surveyed annually.

The design of the monthly sample that has been used since January 2022 is as follows:

The places surveyed monthly include those places in the current (2014) universe that were identified as issuing an average of 6 or more permits in the most recent 3 years (initially 2018-2020). The remaining places in the universe represent about 1% of total permit activity and will only be surveyed annually.

The monthly estimates shown for the United States, Census Regions, Census Divisions, States, Counties, and each jurisdiction are based on received reports for places in the monthly survey and imputed activity for non-reporters and those not surveyed monthly.

For information on the monthly sample design that was used prior to January 2022, see the Historical Methodology section below.



COMPILATION OF DATA

Edits are performed to review data received on survey forms; checks include high or low numbers of units, units per building, cost per unit, cost per building, etc. When a report is not received, missing housing unit data are either (1) obtained from the Survey of Construction (SOC), which is used to collect information on housing starts, sales, and completions, or (2) imputed. Data from SOC are available only for about 900 places for which Census Bureau field representatives list permits issued for new residential construction as part of the SOC sampling operation. (Please go to the Survey of Construction Methodology for more information.) If data are not reported and are not available from SOC, estimates are imputed based on the assumption that the ratio of authorizations for the current time period to the prior year total is the same for reporting and nonreporting jurisdictions in that Census Region. Data for the four types of structures (one unit, two units, 3-4 units, and 5 units or more) are imputed separately.

Building permits data are available in four basic levels of aggregation: state, metropolitan area (MA), county, and permit-issuing place. The state data are also aggregated to create estimates for the Census Divisions, Census Regions, and the United States. Data are shown for the number of buildings, number of housing units, and permit valuation within four sizes of residential buildings: (1) single family houses (attached and detached combined), (2) two-unit buildings, (3) three- and four-unit buildings, and (4) residential buildings with five or more units.

Monthly data are tabulated for the current month, cumulative monthly, and for the year to date. Cumulative and year-to-date data include any late reports received or corrections made to reports from prior months in the year. Because the cumulative and year-to-date estimates include corrections not reflected in the monthly data, summing the published monthly data will not generate the published cumulative or year-to-date estimate. Cumulative files show all months of the calendar year for each permit office. Prior months of the year are shown with the latest data available (late reports and corrections modify previous data). The annual cumulative file contains the latest monthly data for each permit office at the time final annual estimates are released for the year. Prior to January 2022, monthly and year-to-date estimates for state and higher aggregates were sample-based estimates that represent the entire geographic area. Estimates below the state level were a simple tally of sampled jurisdictions and therefore not necessarily complete if the sample did not include all jurisdictions within the sub-state geography.

Beginning in January 2022, all aggregates include data on all places in the current universe. Data on places not included in the monthly survey is imputed.

Annual data are obtained by summing monthly data for places in the monthly sample and using annual data for annual reporters or places in the monthly sample that provided only annual totals. If both monthly and annual data exist, the annual data are used. If no annual data are received, but there were some months reported, the sum of the monthly reported and imputed data is used rather than the imputed annual data. Similar to the monthly data, annual data are tabulated from the entire universe of building permit offices. Monthly data are not revised except for the highest aggregates (U.S. and Census Regions) after annual processing. Monthly estimates of housing units authorized for the U.S. and Census Regions are revised using a benchmark process to sum to the final annual totals.



RELEASE AND REVISION SCHEDULE

Preliminary estimates for the United States and Census Regions are released each month in the New Residential Construction (NRC) Press Release according to the release schedule.

According to the release schedule, revised monthly estimates for the U.S. and Census Regions are released on approximately the 18th working day of the month. An analysis of the NRC revisions is updated with the release of each year's preliminary January and July data.

Estimates in the New Residential Construction release are not revised on the 18th working day; any revisions are shown in the following month's release.

On the same day that the revised monthly estimates for the U.S. and Census Regions are released, monthly estimates by Census Division, state, metropolitan area, county, and permit-issuing place are also released. The monthly estimates by Census Division, state, metropolitan area, county, and permit-issuing place are not revised after their initial release. However, the year-to-date estimates are revised each month to reflect late reports received or corrections made to reports from prior months in the year.

After the completion of the annual survey, final annual estimates for the previous year for the U.S. and by Census Region, Census Division, state, metropolitan area, county, and permit-issuing place are released on the first working day in May. Revised monthly estimates for the U.S. and Census Regions for the prior year which have been "benchmarked" to the final annual totals are also released. No other not seasonally adjusted monthly data are revised after the completion of the annual survey. No annual data are revised after the release of the final annual estimates.

With each April release, seasonally adjusted data are revised for an additional five years beyond the revision period for unadjusted data to reflect updated seasonal factors. Research has shown that this revision span should produce more reliable seasonally adjusted time series.



RELIABILITY OF DATA

The portion of residential construction measurable from building permits records can be limited because such records do not reflect construction activity outside of areas subject to local permits requirements. For the nation as a whole, less than 1 percent of all privately owned housing units are constructed in areas not requiring building permits. However, this proportion varies greatly from state to state and among metropolitan areas.

The reported statistics on building permits are influenced by the following factors:

  1. Some new residential construction work in building permit jurisdictions escapes recording. However, the number of such unrecorded units is likely very small.
  2. Detailed evidence is lacking as to how closely the valuation recorded for building permit purposes approximates the dollar amount of construction work involved.
  3. Changes in boundaries of localities resulting from annexations, new incorporations, etc., result in some problems of comparability over time, even for statistics for the same places.
  4. Some building permit jurisdictions close their books a few days before the end of the month, so that the time reference for permits is not in all cases strictly the calendar month.

To the extent that most of these limiting factors apply rather consistently over an extended period, they may not seriously impair the usefulness of building permit statistics as prompt indicators of trends in residential construction activity. However, the geographic limitations of the data need to be kept in mind. In addition, the dollar volume of residential construction should be used with caution. Because of the nature of the building permit application process, valuations may frequently differ from the true cost of construction. Any attempt to use these figures for inter-area comparisons of construction volume must, at best, be made cautiously and with broad reservations.

Prior to January 2022, the monthly estimates shown for the United States, Census Regions, Census Divisions, and states (with the exception of a few states that have complete coverage in the monthly sample) were based on representative samples and may differ from statistics that would have been obtained from a complete census using the same schedules and procedures. For a particular estimate, statisticians define this difference as the total error of the estimate. When describing the reliability of survey results, total error is defined as the sum of sampling error and non-sampling error. Sampling error is the error arising from the use of a sample, rather than a census, to estimate population values. Nonsampling error encompasses all other factors that contribute to the total error of a survey estimate. The sampling error of an estimate can usually be estimated from the sample, whereas the nonsampling error of an estimate is difficult to measure and can rarely be estimated. Consequently, the actual error in an estimate exceeds the error that can be estimated. Data users should take into account the estimates of sampling error for estimates prior to January 2022 and the potential effects of nonsampling error when using all published estimates.

SAMPLING ERROR

Beginning with January 2022, the monthly estimates of building permits are not based on a probability sample and will be tabulated from the entire universe of building permit offices, similar to annual data. Although not subject to sampling error, these estimates are subject to various nonsampling errors. For information on sampling error for estimates prior to January 2022, see the Historical Methodology section below.

NONSAMPLING ERROR

Nonsampling error encompasses all factors, other than sampling error, that contribute to the total error of a sample survey estimate and may also occur in censuses. It is often helpful to think of nonsampling error as arising from deficiencies or mistakes in the survey process. Nonsampling errors are usually attributed to many possible sources: (1) coverage error - failure to accurately represent all population units in the sample, (2) inability to obtain information about all sample cases (nonresponse), (3) response errors, possibly caused by definitional difficulties or misreporting, (4) mistakes in recording or coding the data obtained, and (5) other errors of coverage, collection, processing, or imputation for missing items or inconsistent data. Although nonsampling error is not measured directly, the Census Bureau employs quality control procedures throughout the process to minimize this type of error.



NONRESPONSE

When a report is not received, missing housing unit data are either (1) obtained from the Survey of Construction (SOC), which is used to collect information on housing starts, sales, and completions, or (2) imputed. Data from SOC are available only for about 900 places for which Census Bureau field representatives list permits issued for new residential construction as part of the SOC sampling operation. (Please go to the Survey of Construction Methodology for more information.) If data are not reported and are not available from SOC, estimates are imputed based on the assumption that the ratio of authorizations for the current time period to the prior year total is the same for reporting and nonreporting jurisdictions in that Census Region. Data for the four types of structures (one unit, two units, 3-4 units, and 5 units or more) are imputed separately.

Many of our data products by county and permit-issuing place show "Reported only" data as well as "Estimates with Imputation." The "Reported Only" data are based only on reports received from permit offices and data obtained from the SOC, and do not include any imputation for missing data. "Estimates with Imputation" include both reported and imputed data.

The total quantity response rate is the percentage of an estimate that is based on data reported directly by the respondent or data obtained from another source determined to be of equivalent quality as respondent reported data. For 2021, the average total quantity response rate for revised monthly estimates of the total number of housing units authorized by building permits was approximately 79%. After the conclusion of the 2021 Annual Survey, the total quantity response rate for the 2021 final annual estimate of the total number of housing units authorized by building permits was approximately 92%

At the end of the year, a second request for data is mailed to delinquent monthly offices. If an office has not reported for up to 4 months during the year, a form is sent for each missing month; if an office has missed reporting for 5 months or more, an annual form is sent. Each office that is requested to report annually receives a second request if the annual report has not been received by the initial due date.

The unit response rate is the percentage of reports requested that were received. For 2021, the average unit response rate for revised monthly estimates of units authorized was approximately 66%. To combine monthly and annual requests to determine the annual unit response rate, requests for annual data from places not in the monthly sample are counted as 12 monthly requests and annual data received are counted as 12 monthly reports. After the conclusion of the 2021 Annual Survey, the unit response rate for all monthly and annual offices was approximately 81%.

The Census Bureau uses many additional methods to improve response rates for this voluntary survey. These include contacting nonrespondents by telephone or email, contacting other government jurisdictions such as counties or states to encourage response from permit offices in their areas or to obtain data for individual jurisdictions, and working with public and private organizations to encourage and facilitate response to the survey.

Some permit offices are able to report the number of housing units authorized, but not the valuation of construction for those units. Valuations for these offices are imputed based on the average cost per unit for the same type of structure and Census Region.



SEASONAL ADJUSTMENT

Seasonal adjustment is the process of estimating and removing seasonal effects from a time series to better reveal certain nonseasonal features such as underlying trends and business cycles. Seasonal adjustment procedures estimate effects that occur in the same calendar month with similar magnitude and direction from year to year. In series whose seasonal effects come primarily from weather, the seasonal factors are estimates of average weather effects for each month. Seasonal adjustment does not account for abnormal weather conditions or for year-to-year changes in weather. Seasonal factors are estimates based on present and past experience. Future data may show a different pattern.

The mechanics of seasonal adjustment involve breaking down a time series into a trend-cycle, a seasonal component, and an irregular component.

The trend-cycle is the long-term tendency of a series to grow or decline.

The seasonal component consists of seasonal effects that are reasonably stable in terms of timing, direction, and magnitude. Possible causes include natural factors (the weather), administrative measures, and social/cultural/religious traditions.

Monthly time series that are totals of daily activities can be influenced by each calendar month's weekday composition. This influence is revealed when monthly values consistently depend on which days of the week occur five times in the month. For example, building permit offices are usually closed on Saturday and Sunday. Thus, the number of building permits issued in a given month is likely to be higher if the month contains a surplus of weekdays and lower if the month contains a surplus of weekend days. Recurring effects associated with individual days of the week are called trading-day effects.

Trading-day effects can make it difficult to compare time series values or to compare movements in one series with movements in another. For this reason, when estimates of trading-day effects are statistically significant, they are adjusted out of the series. The removal of such estimates is referred to as trading-day adjustment.

Series may have moving-holiday effects. Economic effects from holidays such as Easter, Labor Day, and Thanksgiving may affect more than one month, so their timing is not strictly seasonal, but they are predictable calendar events. When these moving-holiday effects are statistically significant, they are adjusted out of the series. The removal of such estimates is referred to as moving-holiday adjustment.

The irregular component is anything not included in the trend-cycle or the seasonal effects (which include trading-day effects and moving-holiday effects). Its values are unpredictable with respect to timing, impact, and duration. It can arise from sampling error, nonsampling error, unseasonable weather, natural disasters, strikes, etc.

Most of the seasonally adjusted series are shown as seasonally adjusted annual rates (SAAR). The seasonally adjusted annual rate is the seasonally adjusted monthly value multiplied by 12. The benefit of the annual rate is that not only can one monthly estimate be compared with another, monthly data can also be compared to an annual total. The seasonally adjusted annual rate is neither a forecast nor a projection; rather it is a description of the rate of building permits in the particular month for which they are calculated.

The seasonal adjustment factors for these data are indexes, that is, they are the factor times 100. They were developed using X-13ARIMA-SEATS software. The X-13ARIMA-SEATS software improves upon the X-13-ARIMA seasonal adjustment software by providing enhanced diagnostics as well as incorporating an enhanced version of the Bank of Spain's SEATS (Signal Extraction in ARIMA Time Series) software, which uses an ARIMA model-based procedure instead of the X-11 filter-based approach to estimate seasonal factors. The X-13ARIMA-SEATS and X-13-ARIMA software produce identical results when using the X-11 filter-based adjustment methodology. The X-13ARIMA-SEATS software will be available from the Census Bureau's Internet site in the coming months. Note that BPS estimates continue to be adjusted using the X-11 filter-based adjustment procedure. For more information on X-13-ARIMA please refer to the Census Bureau's X-13 website.

Seasonally adjusted annual rates are developed each month for building permits by Region and type of structure. Each month, 10 series are run through the X-13ARIMA-SEATS program. The seasonally adjusted U.S. single-family total is the sum of the seasonally adjusted single-family structures in each of the four Census Regions. The seasonally adjusted U.S. total is the sum of the seasonally adjusted U.S. total single-family, U.S. total for two-to-four unit structures, and U.S. total for structures with five units or more. The totals for each of the four Regions are seasonally adjusted and modified so that the seasonally adjusted U.S total derived from the Region totals equals the seasonally adjusted U.S. total derived from the structures.

For further information on time series and seasonal adjustment, please refer to the Seasonal Adjustment Frequently Asked Questions.



HISTORY OF SURVEY PROGRAM

The first collection of data on building permits by the U.S. federal government was conducted by the U.S. Geological Survey beginning in 1889. The information was used to compare the usage of wood, brick, stone, and concrete to the availability of these raw materials near urban areas. Data were collected from about 200 cities on the kinds of materials used in construction, but not on the number of housing units authorized.

In 1920, the U.S. Congress requested data on new housing to address housing shortages that had developed after World War I. The U.S. Bureau of Labor Statistics (BLS) took over the program and developed a new building permit reporting system. Data on the number and value of new housing units authorized were collected for the first time. BLS agents were sent to cities to compile the data, because only a few cities were compiling their own reports on building construction, and each used a different format. In the 1920s, the BLS collected and published annual data for 257 of the 287 cities that had populations of 25,000 or more. In 1930, the BLS developed a uniform reporting form for cities to use to send in their data by mail.

In 1954, the BLS established a permit-issuing universe for the first time and created a new sample design. By 1959, the BLS was receiving reports from about 7,350 permit-issuing places. In 1959, the work to estimate building permits was moved to the U.S. Census Bureau and a survey was conducted that identified almost 3,000 additional permit-issuing places. The basic survey design still used today was initiated, with monthly estimates published from a sample of places selected to report monthly and the remainder of places reporting annually. Data were collected by mail. The universe of permit-issuing places and monthly sample were updated periodically as needed until 1984, when it was decided that the universe and monthly sample would be updated once a decade going forward.

Data were collected on both residential and nonresidential permits until the nonresidential data were discontinued in 1995. An online reporting option was offered to respondents beginning in 2011.

HISTORICAL METHODOLOGY

Prior to January 2022:

  • Tables by MA show all MAs, but most do not include complete counts on a monthly basis because no estimate is made of monthly activity of areas not in the monthly sample. The MAs that are completely covered monthly include the 75 MAs having the greatest number of housing units authorized in 2002. The remaining are simply the sum of monthly reporters with no estimate for annual reporters. To provide a measure of sample coverage, monthly tables by MA show the percentage of housing units authorized in the previous year represented by those places in the monthly survey in each metropolitan area. This is referred to as the "monthly coverage percent." Annual MA tables include estimates for all permit-issuing areas in each MA.
  • Monthly county totals are the sum of the data for places requested to report monthly in a county; for counties not fully covered by monthly reporters, county totals will be incomplete. Annual county totals include estimates for all permit offices.
  • Monthly data by permit-issuing place only includes municipalities that were requested to report monthly. Annual estimates included all permit issuing places.

Prior to January 2022, monthly estimates were based on a probability sample and subject to sampling error. Sampling error reflects the fact that only a particular sample was surveyed rather than the entire population. Each sample selected for the BPS is one of a large number of similar probability samples that, by chance, might have been selected under the same specifications. Estimates derived from the different samples would differ from each other. The standard error (SE), or sampling error, of a survey estimate is a measure of the variation among the estimates from all possible samples and, thus, is a measure of the precision with which an estimate from a particular sample approximates the average from all possible samples.

Estimates of the standard errors were computed from the sample data for selected statistics. They are presented in the form of relative standard errors (RSEs). The relative standard error equals the standard error divided by the estimated value to which it refers. Estimates of the RSEs are available at the Building Permits variance web site.

The sample estimate and an estimate of its standard error allow us to construct interval estimates with prescribed confidence that the interval includes the average result of all possible samples with the same size and design. To illustrate, if all possible samples were surveyed under essentially the same conditions, and estimates calculated from each sample, then:

  1. Approximately 68 percent of the intervals from one standard error below the estimate to one standard error above the estimate would include the average value of all possible samples.
  2. Approximately 90 percent of the intervals from 1.645 standard errors below the estimate to 1.645 standard errors above the estimate would include the average value of all possible samples.

Thus, for a particular sample, one can say with specified confidence that the average of all possible samples is included in the constructed interval. For example, suppose that an estimated 100,000 housing units were authorized by building permits in a particular month and that the average relative standard error of this estimate is 1 percent. Multiplying 100,000 by .01, we obtain 1,000 as the standard error. This means that we are confident, with 68% chance of being correct, that the average estimate from all possible samples of housing units authorized during the particular month is between 99,000 and 101,000 homes. To increase the probability to a 90% chance that the interval contains the average value over all possible samples (this is called a 90-percent confidence interval), multiply 1,000 by 1.645, yielding limits of 98,355 and 101,645 (100,000 units plus or minus 1,645 units). The average estimate of housing units authorized during the specified month may or may not be contained in any one f these computed intervals; but for a particular sample, one can say that the average estimate from all possible samples is included in the constructed interval with a specified confidence of 90 percent. It is important to note that the standard error and the relative standard error only measure sampling error. They do not measure any systematic nonsampling errors in the estimates.

Beginning in January 2022, the monthly estimates of building permits are no longer based on a probability sample and are tabulated from the entire universe of building permit offices, similar to annual data. Although not subject to sampling error, these estimates are subject to various nonsampling errors.




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Source: U.S. Census Bureau | Building Permits | (301) 763-5160 |  Last Revised: June 16, 2022