In all surveys except the PSID, estimated poverty is based solely on who was living with the family at the time of the interview, and annual family income is the sum of the annual incomes of the persons present at the time of the interview, regardless of where they lived during the income reference year. In contrast, PSID family income and poverty thresholds reflect the income and composition of the family during each month of the year, a contemporaneous measure creating an annual poverty threshold and income consistent with changing family composition throughout the income reference year. Essentially, the PSID calculates twelve separate poverty thresholds, one for each month, and sums the values for the year. Similarly, PSID collects information on people who lived with a sample family for just part of the income reference year and the amount of income they received during their period of co-residence, and these part-year contributions of persons who lived with the family for only part of the reference year are included in the family’s annual income.
Based on simulations that we conducted with SIPP, and which are discussed in the next chapter, we found that the contemporaneous measurement of income and family composition reduced the estimated poverty rate by 0.6 percentage points relative to a poverty rate calculated with a fixed family composition measured in the third month after the end of the income reference year (the CPS model). Other things being equal, we would expect the PSID to produce a lower poverty rate than the CPS (or any of the other surveys) due to the PSID’s contemporaneous measurement of income and family composition. Compared to the CPS, the PSID poverty rate ought to be (very roughly) 0.6 percentage points lower. If the observed difference departs substantially from that expectation, then we would infer that some additional factors are at play. The PSID may be capturing more income or less income than the CPS, or the sample after 40 years may over- or under-represent families in particular ranges of income.
Given the low weighted total for the PSID, we focus on rates rather than numbers. We obtain a poverty rate of 9.8 percent from the PSID, based on a CPS-comparable family concept and universe (Table IV.11). This compares to 12.2 percent for the full CPS and 11.6 percent for the CPS-X, which removes subpopulations that were excluded from the CPS population controls when the PSID weights were post-stratified. If we allow that contemporaneous measurement will depress the PSID poverty rate by roughly 0.6 percentage points, this implies that the remaining gap is perhaps a little over a percentage point. This is not a particularly large difference, but it is consistent with the earlier evidence that the PSID may be capturing more income from families at the lower end of the income distribution than the other surveys or under-representing such families.
We find a somewhat larger difference between the PSID estimate of the near poor (15.6 percent of the population) and the estimates from the other surveys, which range from 17.7 percent for the ACS to 20.5 percent for the SIPP. The CPS-X estimate is 18.1 percent or 2.5 percentage points higher than the PSID estimate. In our SIPP simulations we found no net difference between contemporary measurement of income and family composition and the CPS model with respect to the number of near poor, so it would appear likely that, except for sampling error, all of the 2.5 percentage point difference between the PSID and CPS-X can be attributed to some combination of better income measurement and under-representation of the near poor in the PSID sample.
|Millions of Persons|
|Total Low Income||86.19||83.89||89.50||66.58||81.62|
|Percent of the Population|
|Total Low Income||30.5||30.2||31.8||25.5||29.7|
Source: Mathematica Policy Research, from tabulations of poverty status in calendar year 2002 from the 2003 CPS ASEC supplement, the 2001 SIPP panel, the 2002 Full-year Consolidated MEPS-HC, and the 2003 NHIS, and poverty status in the prior 12 months, inflation-adjusted to calendar year 2002, from the 2002 ACS. Note: The poor have a family income below the poverty threshold. The near poor have a family income at or above the poverty threshold but below twice the poverty threshold.
|Millions of Persons|
|All Children under 18||71.67||70.79||71.36||67.48||70.82|
|Total Low Income||27.41||27.45||30.50||23.08||26.78|
|Percent of the Population|
|All Children under 18||100.0||100.0||100.0||100.0||100.0|
|Total Low Income||38.2||38.8||42.7||34.2||37.8|
Source: Mathematica Policy Research, from tabulations of poverty status in calendar year 2002 from the 2003 CPS ASEC supplement, the 2001 SIPP panel, the 2002 Full-year Consolidated MEPS-HC, and the 2003 NHIS, and poverty status in the prior 12 months, inflation-adjusted to calendar year 2002, from the 2002 ACS. Note: The poor have a family income below the poverty threshold. The near poor have a family income at or above the poverty threshold but below twice the poverty threshold
The PSID estimate of poor children (14.3 percent) is 2.5 percentage points lower than the full CPS and 2.1 percentage points lower than CPS-X (Table IV.12). This is comparable to what we observed for the general population. The PSID estimates of near-poor children, however, are closer to the CPS and ACS estimates than was true of the general population. The PSID estimate of 19.9 percent is just 1.5 percentage point lower than the estimate from CPS-X, 1.6 percentage points lower than the full CPS, and 1.2 percentage points lower than the ACS. SIPP is an outlier.
Among the elderly, the differences between the PSID and other survey estimates reverse the pattern observed for children. The elderly poverty rate estimated by the PSID matches the rate recorded by SIPP and is just 0.6 percentage points lower than the ACS and 1.4 percentage points lower than CPS-X (Table IV.13). However, the PSID identifies substantially fewer elderly than the other surveys as near poor—18.2 percent versus 28.0 percent for CPS-X and the full CPS, 25.2 percent for SIPP, and 23.8 percent for the ACS. This pattern suggests that representativeness may play a greater role than better income measurement within this subpopulation.