Hi,
I am trying to match the official ACS poverty rate (OFFPOV) with the rate reported in the Census ACS brief. I applied the following steps and obtained a household income estimate within the margin of error:
drop if gq == 3 | gq == 4
keep if pernum == 1
gen adjhhincome = hhincome * adjust
Median total household income: 77,687.3
After that, I checked the poverty rate using the OFFPOV variable from the dataset. However, I found the rate as 12.71%, whereas the Census ACS brief reports 12.5%. No matter what I try, I am unable to produce a value within the margin of error. I can confirm the poverty universe, and I also dropped group quarters, and those under age 15 who are not related to the household head.
Could you please help me understand what might be causing this discrepancy?
My second question: Another problem is about total family income (ftotinc), which I also could not find it closer to the Census report. After adjusting, I found it as 92,776.14.
Thank you!
The ACS Public Use Microdata Sample (PUMS) will not perfectly replicate poverty rates that are reported by the Census Bureau using the full data file. This is due to both confidentiality protections (e.g., rounding of earnings and suppression of details for group quarters types) as well as the fact that the PUMS microdata includes only about two-thirds of the records that are used to produce ACS estimates (refer to the PUMS User Guide for further information). With this caveat in mind, I can share a few suggestions for your approach.
First, the 12.5% estimate from the Poverty in States and Metropolitan Areas: 2023 report is the percent of people who are below the official poverty threshold. For person-level estimates, you should not filter by PERNUM. Restricting by PERNUM = 1 is only necessary for household-level estimates (i.e., the percent of households below the poverty threshold). You should also weight person-level estimates with PERWT. Second, I recommend using the variable OFFPOV to more accurately replicate published statistics (rather than HHINCOME). OFFPOV directly reports whether the respondent’s family income is below or above their poverty threshold, removing the need to calculate this yourself. This variable also does not need to be adjusted for inflation and correctly applies the group quarters universe for poverty estimates.
In the screenshot below, I tabulate OFFPOV in the 2023 ACS using the IPUMS USA online analysis tool. I apply the selection filter OFFPOV(0,1) to only keep cases that are in-universe. This results in an estimate of 12.2% of the population being below the official poverty threshold. Given the constraints in the PUMS file, this seems reasonably close to the 12.5% estimate in the report.
FTOTINC (total family income) will not replicate estimates reported by the Census Bureau. FTOTINC reports family income using a more inclusive family definition (see FAMUNIT) rather than the one used by the Census Bureau. In particular, FTOTINC sums incomes of unmarried cohabiting couples (and their relatives) whereas family incomes reported by the Census Bureau are only summed across members related by blood, marriage, or adoption. As a result, family incomes using FTOTINC will on average be slightly higher than official estimates.
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Thank you very much for this detailed response. I use pernum==1 to calculate household income.
Regarding the poverty rate, in my latest analysis I also found 12.2. However, because the Census reports a 0.1 margin of error, I initially thought I should obtain a value of either 12.4 or 12.6. If, as you suggest, 12.2 is reasonable given the data constraints, then that resolves my concern.
I have one additional question. When I calculate the poverty rate for people with specific characteristics, such as widowed women aged 65 and older, does this imply that the estimate may deviate even more from the official figures due to the smaller sample size in the ACS PUMS? In addition, since I am calculating poverty for specific population groups, am I correct in assuming that I should use person weights rather than household weights?
Due to the smaller sample size in subgroup analyses, the official poverty rate will typically have a larger margin of error than it does for the entire population. Similarly, estimates using the PUMS data may deviate more from published point estimates due to this greater sampling variability.
You should continue using person weights (i.e., PERWT) for analyzing specific groups if your outcome of interest is in terms of people (e.g., percent of widowed women aged 65 and older who are below the poverty threshold) rather than in terms of households (e.g., percent of households below the threshold).
If you do not require individual-level microdata, you might consider using data from IPUMS NHGIS for your analysis. IPUMS NHGIS offers geographically aggregated summary statistics from the full ACS data file released by the Census Bureau. We offer a User Guide on IPUMS NHGIS to help familiarize users with the data as well as a brief FAQ page.
