Description

HHWT indicates how many households in the U.S. population are represented by a given household in an IPUMS sample.

It is generally a good idea to use HHWT when conducting a household-level analysis of any IPUMS sample. The use of HHWT is optional when analyzing one of the "flat" or unweighted IPUMS samples. Flat IPUMS samples include the 1% samples from 1850-1930, all samples from 1960, 1970, and 1980, the 1% unweighted samples from 1990 and 2000, the 10% 2010 sample, and any of the full count 100% census datasets. HHWT must be used to obtain nationally representative statistics for household-level analyses of any sample other than those.

Users should also be sure to select one person (e.g., PERNUM = 1) to represent the entire household.

For further explanation of the sample weights, see "Sample Designs" and "Sample Weights". See also PERWT for a corresponding variable at the person level, and SLWT for a weight variable used with sample-line records in 1940 1% and 1950.

HHWT is a 6-digit numeric variable which indicates how many households in the U.S. population are represented by a given household in an IPUMS sample and has two implied decimals. For example, a HHWT value of 010461 should be interpreted as 104.61. HHWT specific variable codes for missing, edited, or unidentified observations, observations not applicable (N/A), observations not in universe (NIU), top and bottom value coding, etc. are provided below if applicable by Census year (and data sample if specified).

User Note: Users should also be sure to select one person (e.g., PERNUM = 1) to represent the entire household when using HHWT.

HHWT Specific Variable Codes

Comparability

For all 1940-onward samples, HHWT is an integer provided in the original public-use sample.

• The techniques for constructing weights vary; interested users should consult the technical documentation.

• For 1940 1% and 1950, users can identify a smaller "flat" subset of the data that requires no weights, using the household variable SELFWTHH.

• In 1990-2000, some cases have HHWT values of 0. This is a function of the complex sample design used by the Census Bureau.

For all 1850-1930 samples, on the other hand, HHWT is calculated by the IPUMS such that statistics match published population counts for counties and/or State Economic Areas, or SEAs:

• If all counties of a specific State Economic Area (SEA) had a population of at least 10,000 persons in the reference year, then HHWT is benchmarked on each county's population.

• If all counties in an SEA had populations less than 10,000, then HHWT is based on the aggregate population total for the group of counties comprising the SEA.

• If the SEA contained a mix of counties above and below the 10,000 population threshold, HHWT uses the SEA population if the aggregated total for the counties under 10,000 does not equal or exceed 10,000. However, if the aggregated total for the counties under 10,000 does equal or exceed 10,000, then the aggregated total is used for the counties under 10,000, and the county population is used for specific counties within the SEA that have a population total that equals or exceeds 10,000.

• The exceptions to this rule are the 1900 and 1910 1.4% samples with oversamples, where HHWT is benchmarked on the published national population count. Here, HHWT is particularly likely to be useful for researchers studying the oversampled groups in this dataset (Alaskans, Hawaiians, American Indians, African-Americans, and Hispanics). More information about oversampled groups in this sample is available in the 1900 sample design page and the 1910 sample design page.

• In 1900-1910, some cases have HHWT values of 0. These records are part of fragmentary households that were enumerated outside of the original "sample window." When possible, data entry staff located these individuals and reunited them with the remainder of their household (i.e., the portion of the household that was within the "sample window").

User Note: Users combining multiple samples from the same year must make an adjustment to HHWT in order to get accurate population estimates. When combining two 1% samples from a given year (for a total of a 2% sample), users need to multiply the HHWT values in both samples by 0.5, so that the weights will inflate the two samples together to represent that year's entire U.S. population. Similarly, when combining a given year's 1% and 5% samples together (for a total of a 6% sample), users must multiply HHWT values in the 1% sample by 0.167 (1/6) and HHWT values in the 5% sample by 0.833 (5/6).

User Note: Users should note that in the 2020 ACS 1-year file the standard HHWT variable was replaced with an experimental weight that was designed to account for the effects of the COVID-19 pandemic on the 2020 1-year ACS data quality. The experimental weight uses the same name and is in place of the standard HHWT variable, so selecting HHWT for the 2020 ACS 1-year file will select the household-level experimental weight for this sample. For more information, please see ACS and COVID-19: Guidance for Using the PUMS with Experimental Weights.

Universe

Availability

• 2022: All samples
• 2021: All samples
• 2020: All samples
• 2019: All samples
• 2018: All samples
• 2017: All samples
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• 1990: All samples
• 1980: All samples
• 1970: All samples
• 1960: All samples
• 1950: All samples
• 1940: All samples
• 1930: All samples
• 1920: All samples
• 1910: All samples
• 1900: All samples
• 1880: All samples
• 1870: All samples
• 1860: All samples
• 1850: All samples

• 2022: All samples
• 2021: All samples
• 2020: All samples
• 2019: All samples
• 2018: All samples
• 2017: All samples
• 2016: All samples
• 2015: All samples
• 2014: All samples
• 2013: All samples
• 2012: All samples
• 2011: All samples
• 2010: All samples
• 2009: All samples
• 2008: All samples
• 2007: All samples
• 2006: All samples
• 2005: All samples
• 2000: All samples
• 1990: All samples
• 1980: All samples
• 1970: All samples
• 1930: All samples
• 1920: All samples
• 1910: All samples

Flags

This variable has no flags.

Editing Procedure

There is no editing procedure available for this variable.