The definition of income used in the comparative analysis is the same definition that is used in official poverty statistics, which is pretax money income as measured in the CPS. Table II.8 in Chapter II identifies differences between the CPS income concept and the income concepts used in the other seven surveys. For example, SIPP excludes educational benefits that are included in CPS money income, but it includes lump-sum payments from certain retirement accounts that are not counted in CPS money income. MEPS excludes tax exempt interest for tax filers, which is counted in the CPS, but includes taxable lump-sum payments from retirement accounts. In addition, by referring respondents to their tax returns, MEPS implicitly uses tax concepts to define income, which implies that wages may exclude, for example, pre-tax deductions for contributions to 401(k) plans or some health insurance premiums. For other surveys, whether there are differences in the income concepts depends heavily on respondent interpretation of questions asking about broadly-defined sources.
While our intent was to adjust the survey estimates for departures from the CPS income concept, very few adjustments were needed or possible. CPS income includes only regular payments from an IRA, Keogh, or 401(k) plan whereas a single MEPS variable includes both regular and lump-sum payments from this source. Since we needed micro-level data, our two options were to include or exclude the entire amount of the MEPS variable. The regular payments captured by the CPS question totaled only $3.3 billion whereas the MEPS item collected $65.6 billion in both regular and lump-sum payments. Based on these comparative magnitudes, we concluded that the income captured by the MEPS item was almost entirely outside the CPS income concept. Therefore, we excluded the MEPS variable from MEPS income. But in Chapter V we show the income picked up by this variable and how its inclusion or exclusion affects the number of poor. SIPP also collects lump-sum payments, but they are recorded separately from regular payments. We were able to exclude just the lump-sum payments from the SIPP income estimates. Our analysis in Chapter V compares the MEPS and SIPP amounts of combined regular and lump-sum payments.
NHIS collects total family income in a single question, so there were no sources to add or subtract in order to match the CPS income concept. However, in more than a fifth of NHIS families the sum of reported personal earnings over all family members exceeds the reported total family income. We investigated substituting the sum of reported earnings for total family income when the former exceeded the latter; the results are reported in Chapter IV.
Both the HRS, through a version of the data produced and released by RAND, and the PSID provide a single constructed family income variable. For both surveys this is what we used as family income in our analyses. MCBS collects dollar amounts for only one measure of income, which is the sum of the incomes of the sample member and spouse.
SIPP required a special income adjustment to compensate for income that is not collected in SIPP but is needed to calculate annual income. SIPP is unique among the eight surveys in collecting income month-by-month, four months at a time, rather than asking respondents to report their income for a previous 12-month period. To obtain annual income for a population defined at a point in time, the monthly amounts must be summed over a specified 12-month period. This in itself is not difficult, but because SIPP was not designed to collect retrospective annual income, some respondents are missing one or more months out of a prior 12-month period. For example, to construct annual income for the 2002 calendar year, as we do here, we sum the reported amounts for January through December 2002 for the sample of respondents with weights for December 2002.12 Among these weighted respondents, those who joined sample households after January 2002 will have no reported income for the months before they joined these households. Those whose households missed one or more interviews during the year, regardless of when they joined the sample, will be missing up to four months of CY 2002 income data for each missed interview. To produce an estimate of annual income for each such respondent, it is necessary to compensate for the missing months in some way. To create the estimates presented in this report, we applied a simple ratio adjustment to the sum of the reported months, inflating the reported sum by a factor of 12 divided by the number of reported months. This is not a sophisticated imputation strategy, by any means, but it serves the purpose of giving us annual numbers that are consistent with the reported data. It also reflects what a typical user might do.
Two of the surveys—HRS and MCBS—provided income for a 2003 reference year rather than 2002. Following the recommendation of the TAG, we deflated the 2003 incomes to 2002 dollars. This was accomplished by dividing each reported 2003 income by 1.0228, which represents the price increase between calendar years 2002 and 2003 recorded in the CPI-U series.
Income data from the ACS do not correspond to a calendar year or to any single 12-month period. Instead, respondents are asked to report their incomes for the 12 months preceding the interview. Thus the income data collected in the 2002 ACS represent 12 successive 12-month periods ending December 2001 through November 2002 (or starting January 2001 through December 2001).13In the Census Bureau’s internal files, which are used to produce both published and on-line tables, income from the 12 different reference periods is inflation-adjusted to reflect price levels during a fixed period corresponding to the calendar year of the survey. The public use files contain only unadjusted income and an average of the 12 adjustment factors, and they do not include the interview month. With these data it is not possible to replicate the adjusted incomes that appear in the Census Bureau’s internal files. To prepare the estimates of ACS income presented in this report, we inflated the reported incomes by the average adjustment factor. This under-adjusts incomes collected early in the survey year and over-adjusts incomes collected late in the survey year. To prepare estimates of ACS poverty status, we used the ratio of income to poverty reported on the public use file, which incorporates the Census Bureau’s inflation adjustments by interview month.14