CPS Basic Monthly and State-Level Estimate of Working Families by Year

Hi, I’m trying to find yearly averages of the number of working families in GA with children in the household that are 13 and younger. Here’s a sample of my R code:

GAWorkingFamilies_2019to2022 ← GA_Data%>%
filter(year >= 2019, year <= 2022, empstat >= 10, empstat <= 12,
yngch >= 0, yngch <= 13)%>%
group_by(year = haven::as_factor(year))%>%
summarize(WFsamplePerYear = n(),
WorkingFamiliesYearlyEstimate = sum(wtfinl/12, na.rm = TRUE))

Based on what I’ve seen from similar previous questions, I cannot use replicate weights to statistically verify my yearly estimates. Am I wrong? Is there a preferable way to get SE’s/MOE’s for this type of microdata to determine the reliability of my analysis?

Much thanks for any help on this,

Replicate weights are currently available via IPUMS for the Annual Social and Economics Supplement (ASEC) of the CPS that is fielded in March of each year, but not for any of the basic monthly surveys. There is no specific recommendation for calculating standard errors using Basic Monthly CPS microdata. One method you might follow is Davern et al. (2006, 2007). They specify the lowest level of identifiable geography (STATEFIP) as the strata, and household (CPSID) as the PSU, and find that it improves variance estimation relative to the baseline of using just the weighted least squares variance estimator. You will need to have the survey and srvyr packages installed. You will also want to use the subset() option rather than filter() to retain sample design information. See sample R code:

data ← as_survey(data, id = CPSID, weight = HWTFINL, strata = STATEFIP, nest = TRUE)
subset(data, year >= 2019, year <= 2022, empstat >= 10, empstat <= 12, yngch >= 0, yngch <= 13)

As a reminder, in the CPS microdata each observation is a person. The filters you provide therefore identify individuals who are employed and have a child under 13 in the household; it does not identify other members of the household (e.g., the child wouldn’t be included in your current filters). Note that people are nested within households in the CPS, and not necessarily families (e.g., a household may contain one or more families). One way to restrict your file for household-level analyses is to filter on PERNUM==1; these analyses should use the household weight (HWTFINL) instead of the person weight (WTFINL). For family-level analyses, you will need to filter to one-person per family using FAMUNIT, SERIAL, MONTH, and YEAR; CPS does not provide a family weight for BMS data (you might choose to use the household weight for this). If you are interested in household- or family-level analyses, note that you might want to assign values for a “working family” variable before filtering to a single person per household or family because the first person may not be employed, but other adults may be (e.g., a household reference person with a child who is not employed but whose spouse is; filtering on PERNUM==1 before defining working families would not flag this family).

If you are open to other data sources besides the CPS, you might consider using IPUMS USA ACS data for your estimates. The ACS is an annual survey that includes more respondents than the CPS and also provides replicate weights for more accurate variance estimation. EMPSTAT as well as YNGCH are available. You might also access IPUMS NHGIS to search for official Census estimates in aggregated tables. While there isn’t a table for the specific criteria that you specify, you may get a lot of use out of it if you are willing to slightly modify your criteria. Using the Data Finder tool, you might filter geographic level to State, years to the most recent 5-year ACS (2018-202 2), and topics to Children in Households and Labor Force and Employment Status. Table B23010, Presence of Own Children Under 18 Years in Married-Couple Families by Work Experience of Householder and Spouse, will provide you with a state-by-state breakdown of the number of married-couple families by presence of own children under 18 years and the work experience of the householder and their spouse. The tables provide point estimates as well as margins of error calculated by Census statisticians.