I am working with 2024 ACS 1-year PUMS data that were released recently.
For Yearbuilt variable, I am confused about the codes
Is 28 really representing housing built in 2024 or is it supposed to be 2023? In 2023 sample, 27 represent units built in 2022 and the current one is different than the other years.
Thank you
I have another related question.
I am now looking at 2023 and 2024 Tennessee data for housing units by year built. My purpose is simply to determine the share of renter/owner-occupied housing units built in certain years. I noticed that there was change in earlier years too (it is normal to find more or less housing units built 2020 and later, for example, but units built before 1940 would not change). There might be change in tenure (maybe a unit was renter-occupied, but became owner-occupied or vacant or vice versa). Therefore, I decided to look at all housing units regardless of tenure. Still there is variation in the number of housing units built.
This is the following simple data I got
| Tennessee | ||
|---|---|---|
| 2023 | 2024 | |
| Pre_1940 | 169,256 | 179,201 |
| 1940_1959 | 370,878 | 358,484 |
| 1960_1979 | 728,332 | 717,636 |
| 1980_1999 | 873,103 | 894,146 |
| 2000_2009 | 511,229 | 496,013 |
| 2010_2019 | 400,714 | 407,518 |
| 2020plus | 141,626 | 190,956 |
| To get this data I filtered only the group quarters. What can be the reason for having more housing units built before 1940, for example, in 2024 than 2023? Am I missing something or making a mistake? |
Thank you
The American Community Survey (ACS) samples about 1% of US households in each survey year by sending selected households a self-administered questionnaire. Though estimates should closely match across survey years, these data are subject to some variability based on household sampling and response rates as well as reporting error. This is partially addressed by using the household sampling weight HHWT, which adjusts the ACS sample to be representative of the US population.
I was unable to replicate your estimates using the IPUMS USA online analysis tool. To run this analysis, I selected the American Community Survey, 2001-2024 sample. In the tables function (see screenshot below), I input BUILTYR2 into the Row field, year into the Columns field, and YEAR(2023, 2024), STATEFIP(47), GQ(1,2,5), PERNUM(1) into the Selection Filters(s) field. This produces a tabulation of BUILTYR2 by YEAR for 2023 and 2024; STATEFIP restricts the analysis to Tennessee, GQ retains only households, and PERNUM ensures that each household is only counted once. I also selected the household weight HHWT. The resulting table showed an estimate of 144,455 pre-1940 housing units in the 2023 sample and 148,375 such units in the 2024 sample. You can also request confidence intervals for the estimates in the online tool (find this under the Output Options menu). The 95% confidence intervals for the two estimates show significant overlap, suggesting that any difference is due to random sampling error.
Going back to your first post, there is indeed an error in BUILTYR2 code 27. In both the 2023 and 2024 ACS samples, BUILTYR2 = 27 (“2022”) combines units built in 2022 with those built in 2023. I will alert my colleagues of this error so that a separate code for units built in 2023 can be created. Meanwhile, you may use the source variables US2024A_YRBLT and US2023A_YRBLT to differentiate units between these two construction years. BUILTYR2 = 28 (“2024”) correctly identifies units constructed in 2024.
Thank you for the response.
I need to check to understand why my numbers are different, but I still have the same concern and confusion: Why the number of housing units pre-1940 is 144,455 in 2023 and 148,375 in 2024? Since those are units already built in the past, why are the numbers changing?
Thank you
Hulya
Due to the sampling method and respondent error, it is expected that estimates using the ACS will not be identical across sample years. Data from the ACS is used to produce estimates, but it cannot provide the true value. Random sampling may result in more households residing in older buildings being included in the survey in one year compared to another. Respondents may also differ in their knowledge of when their home was constructed. For example, tenants may be more likely to make a mistake in reporting the decade that the home they rent was constructed in when compared to homeowners. Changes in renting patterns in this case will affect estimates even when the housing units being sampled remain constant.
I also was able to replicate your previous estimates of the number of households residing in housing units constructed before 1940 (169,256 households in 2023 and 179,201 in 2024). I was able to replicate these estimates by including vacant units in my sample. These are housing units that do not have any usual residents (see VACANCY for more information). These units do not have any person records attached to them and are excluded from the online analysis tool.
Thank you.
I realized that you already explained that the random sampling errors could be the reason for this change. My bad that I did not read that part more carefully.
I included the vacant units because I wanted to eliminate the possibility of occupancy affecting the number of units in different years.
Thank you for taking the time to explain this in more detail.
