Survey Estimates of Wealth - Mathematica Policy Research

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holdings. The PSID has also realized significantly lower item nonresponse rates on most of its wealth items than either the SCF or the SIPP. The HRS, which is also a panel study, began in 1992 with a sample of about 7,600 households containing at least one individual born between 1931 and 1941. These initial respondents have been reinterviewed every two years. A companion survey, the Asset and Health Dynamics Among the Oldest Old Survey (AHEAD), was started a year later, in 1993, with a sample of 7,500 households containing persons born in 1923 and earlier. These respondents were reinterviewed in 1995 and then again in 1998, when the HRS and AHEAD surveys were combined into a single data collection with a common instrument. At the same time, two additional HRS cohorts drawn from about 5,000 households were added. The “War Babies” cohort consists of persons born 1942 to 1947, and the “Children of the Depression” cohort includes persons born from 1924 through 1930, bridging the gap between the original HRS and AHEAD cohorts. Interviews with the combined sample will be conducted every two years. Additional cohorts will be added every six years to renew the combined sample’s representation of all persons over 50. Data on financial assets and liabilities have been collected since the first HRS interview in 1992. Like the PSID, the HRS has employed unfolding brackets in its wealth modules, and it, too, has enjoyed comparatively low item nonresponse. To SSA, which has contributed to the funding of this new survey, the expanded HRS holds interest as an additional source of data on the wealth holdings of near- and recent retirees because it offers significantly larger sample sizes of these populations than even the SIPP and because the data on income and wealth can be analyzed in conjunction with many types of outcomes. 6
C. ACCOUNTING FOR DIFFERENCES IN SURVEY ESTIMATES OF WEALTH There are a number of reasons why estimates of the level and distribution of wealth may differ substantially across surveys. As our discussion of Table I.1 suggests, content and coverage have a major impact. The parallel estimates from SIPP in the late 1990s indicate that the addition of 401(k) plans to that survey’s estimates of wealth increased the household median by nearly 15 percent. The SIPP still does not routinely collect estimates of wealth held in pension accounts, and as the Census Bureau has noted repeatedly over the years, the SIPP does not measure the cash value of life insurance, the monies held in annuities and trusts, or the value of “other” nonfinancial assets, such as jewelry, art, and other collections. Some of these are very small, but we will show that the collective value of assets that are measured in the SCF but not the SIPP is not trivial; nor are such assets limited to the wealthy. Even assets and liabilities that are measured in the SIPP may be defined differently in other surveys, and few are captured with the same thoroughness in the SIPP (or the PSID or HRS) with which they are collected in the SCF. The most important differences, however, stem from the high concentration of wealth in the United States. Estimates from the SCF show that the wealthiest one percent of families hold one-third of all wealth, the next nine percent hold another third, and the bottom 90 percent hold the last third (Kennickell 2003). This distribution has changed little since 1989, but only the SCF, with wealth as its primary focus, employs a design whose sample allocation, questionnaire, interviewer training, and post-survey processing take into account the concentration of wealth. Survey differences in the capture of data from the wealthiest families may be compounded by procedures designed to minimize the risk that a sample member can be identified from the data in the survey. The SIPP makes particularly heavy use of topcoding, which caps the amounts 7
Page 1: Contract No.: 0600-01-60121/0440-02
Page 4 and 5: CONTENTS (continued) Chapter Page I
Page 7: ACKNOWLEDGMENTS The authors would l
Page 10 and 11: Wealthy Families. Wealth is highly
Page 12 and 13: Growth in Aggregate Assets. The SIP
Page 14 and 15: SIPP estimate of aggregate or mean
Page 16 and 17: difference between SIPP and SCF est
Page 19 and 20: I. INTRODUCTION The Office of Resea
Page 21 and 22: At the same time, however, evidence
Page 23: sample included about 4,300 househo
Page 27 and 28: either the 1984 SIPP or the PSID. T
Page 29 and 30: II. COMPARATIVE ESTIMATES OF WEALTH
Page 31 and 32: children) or a parent and child who
Page 33 and 34: identification of unmarried partner
Page 35 and 36: to make comparisons with earlier SI
Page 37 and 38: from the March 1997 CPS, and the pe
Page 39 and 40: weights, which is reasonably close
Page 41 and 42: Rates of home ownership are nearly
Page 43 and 44: the marginally greater PSID populat
Page 45 and 46: 3. The Distribution of Net Worth Ta
Page 47 and 48: families and a little over 84 perce
Page 49 and 50: which members of our expert panel r
Page 51 and 52: and 96 to 105 percent of the aggreg
Page 53 and 54: ut we imposed a floor of zero. This
Page 55 and 56: 3. Liabilities Table II.12 provides
Page 57 and 58: 2. Assets and liabilities not measu
Page 59 and 60: y only one percent, which provides
Page 61 and 62: underreporting of amounts. Conditio
Page 63 and 64: ownership rates across the three su
Page 65 and 66: more slowly than the SCF estimates
Page 67 and 68: What is immediately evident is an a
Page 69 and 70: donors to cases with missing values
Page 71 and 72: SIPP shows 81 percent growth in fin
Page 73 and 74: III. SUBPOPULATIONS Each of SSA’s
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differences by gender are smaller t
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somewhat more pronounced than in th
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Comparisons of SIPP and PSID median
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65.0 percent of the HRS aggregate,
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exceeds the SIPP median by nearly $
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wealth, and, furthermore, the Censu
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TANF and other forms of welfare or
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We can use the information containe
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B. COVERAGE AND CONTENT In developi
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We constructed an additional measur
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Table IV.6 summarizes the effects o
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generated under earlier jobs. The w
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Because of the growing importance o
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tax payment if the money is used fo
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From the marginal distribution of a
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suggests greater error in their wav
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statistics on item nonresponse. Whi
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2. Response Brackets One device for
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of the second bracket. The same is
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4. Motor Vehicles One area where th
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The deficiencies in the Census Bure
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A. REWEIGHTING THE SIPP DATABASE As
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levels in the public use version of
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the cash value of life insurance, a
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To adjust for the topcoding in the
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the disparity between the surveys w
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Checking/Savings Accounts. Only 77
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V.8, the fully adjusted SIPP distri
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here are only able to reduce the SI
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assets that are concentrated among
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of this year, and we were able to i
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way to do so is to use a Pareto dis
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insurance as well as annuities and
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The PSID and the HRS have had consi
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imputed values and a change from th
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institutions and in IRA and Keogh a
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REFERENCES Curtin, Richard, F. Thom
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TABLES
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TABLE II.1 SIPP ESTIMATES OF THE NE
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TABLE II.3 ESTIMATES OF NET WORTH,
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TABLE II.5 PERCENTILES OF NET WORTH
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TABLE II.6 PERCENTILES OF ASSETS AN
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TABLE II.7 DISTRIBUTION OF NET WORT
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TABLE II.9 CLASSIFICATION OF ASSETS
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TABLE II.11 DECOMPOSITION OF DIFFER
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TABLE II.13 DECOMPOSITION OF DIFFER
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TABLE II.15 AGGREGATE ESTIMATES OF
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TABLE II.17 OWNERSHIP AND CONDITION
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TABLE II.19 CHANGE IN SELECTED PERC
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TABLE II.21 SELECTED PERCENTILE VAL
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TABLE II.23 SELECTED PERCENTILE VAL
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TABLE II.25 CONSTANT DOLLAR GROWTH
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TABLE III.2 DISTRIBUTION OF ASSETS
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TABLE III.4 OPERATIONAL DEFINITIONS
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TABLE III.6 ESTIMATES OF MEAN AND M
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TABLE III.8 ESTIMATES OF NET WORTH,
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TABLE III.10 OWNERSHIP AND CONDITIO
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Table IV.1 Continued Cumulative Rat
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Table IV.2 Continued Ratio of Ratio
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TABLE IV.4 SELECTED PERCENTILES AND
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TABLE IV.6 COMPARISON OF SIPP AND S
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TABLE IV.8 PERCENTAGE DISTRIBUTION
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TABLE IV.10 NET WORTH OF SIPP FAMIL
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TABLE IV.12 COMPARISON OF SIPP AND
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TABLE IV.14 DISTRIBUTION OF FAMILIE
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TABLE IV.16 WEIGHTED CORRELATION BE
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TABLE IV.18 MEAN VALUE OF FIRST THR
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TABLE V.2 MEANS OF INDEPENDENT VARI
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TABLE V.2 (continued) MEANS OF INDE
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TABLE V.4 LEVEL AND DISTRIBUTION OF
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Page 220 and 221:
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TABLE V.10 LEVEL AND DISTRIBUTION O
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TABLE VI.1 SIPP 1996 PANEL FILES US
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FIGURE V.1 DISTRIBUTION OF TOTAL RE
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FIGURE V.3 DISTRIBUTION OF OWN HOUS
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FIGURE V.5 DISTRIBUTION OF CHECKING
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FIGURE V.7 DISTRIBUTION OF MOTOR VE
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FIGURE V.9 DISTRIBUTION OF LIFE INS
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FIGURE V.11 DISTRIBUTION OF OTHER N
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FIGURE V.13 DISTRIBUTION OF TOTAL N
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FIGURE V.15 DISTRIBUTION OF TOTAL A
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FIGURE V.17 DISTRIBUTION OF TOTAL L
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APPENDIX A SURVEY QUESTIONS BY ASSE
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Assets Explicitly Covered 1996 SIPP
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Assets Explicitly Covered 1996 SIPP
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113: STOCKS AND MUTUAL FUNDS Assets
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114: US SAVINGS BONDS Assets Explic
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115: OTHER FINANCIAL ASSETS 1996 SI
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116: IRA AND KEOGH ACCOUNTS 1996 SI
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117: 401(k) AND THRIFT ACCOUNTS 199
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118: OTHER, QUASI-LIQUID PENSION AS
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118: OTHER, QUASI-LIQUID PENSION AS
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Assets Explicitly Covered 121: HOME
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Assets Explicitly Covered 123: ALL
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123: ALL OTHER REAL ESTATE Key Vari
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124: MOTOR VEHICLES 1996 SIPP, Wave
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125: BUSINESS EQUITY 1996 SIPP, Wav
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130: OTHER NON-SIPP ASSETS 1996 SIP
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131: SIPP PENSION ASSETS 1996 SIPP,
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211: MARGIN AND BROKER ACCOUNTS Ass
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212: MORTGAGES ON OWN HOME 1996 SIP
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214: PERSONAL BUSINESS DEBT Assets
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215: VEHICLE LOANS 1996 SIPP, Wave
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221: CREDIT CARD OR STORE DEBT Asse
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222: LOANS FROM FINANCIAL INSTITUTI
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223: OTHER UNSECURED LIABILITIES 19
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A. CODE FOR 1998 SCF *This program
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*[note, this is the value side of t
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IF EHOWNER3 = EPPPNUM THEN DO; MPR1
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* hmowner not in hhld in this month
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MPR100 = MPR110 + MPR120; /* MPR130
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IF ER15222 = 3 AND ER15223 = . THEN
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APPENDIX C EQUATION COEFFICIENTS FO
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APPENDIX TABLE C.2 COEFFICIENTS OF
Page 312 and 313:
Page 314 and 315:
APPENDIX TABLE C.5 (continued) COEF
Page 316 and 317:
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