Survey Estimates of Wealth - Mathematica Policy Research

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only temporarily away from their usual places of residence, as part of the household rather than group quarters population. 7 Consequently, comparatively few of the persons who were in fact living in non-institutional group quarters at the time the SIPP wealth data were collected are excluded from our estimates. 8 Table II.1 compares SIPP estimates of net worth for households, families defined using SCF family concepts, and families defined using Census Bureau family concepts. The families defined using SCF family concepts include the SCF-like families described above and a residual consisting of subfamilies, secondary families and individuals, and the additional members of primary families that we excluded because they were 25 years of age and older. Each of these last persons counts as a separate family, which inflates the estimated total of all these other non- SCF-like families to 19.6 million. The number of households and the number of SCF-like families are identical by construction, at 102.5 million. Families defined using Census Bureau family concepts include: (1) primary families and primary individuals, with subfamilies excluded from the former, and (2) a residual consisting of subfamilies, secondary families, and secondary individuals. Unmarried partners were included in the residual. Indeed, our purpose in defining a set of householder-based families using only Census Bureau concepts was to allow us 7 Most of the college dormitory population is counted in households rather than in these group quarters. The population actually counted in non-institutional group quarters by the 1996 SIPP panel numbered about one-half million whereas the 2000 census counted four million persons in non-institutional group quarters. 8 The treatment of group quarters residents in the SCF and the PSID is not entirely clear. Neither survey includes the institutionalized population in its estimates, and the SCF does not appear to sample non-institutional group quarters, but college students who are temporarily away at school may be counted in both SCF and PSID families. We could not determine if the PSID continues to interview sample members who move into noninstitutional group quarters. Regardless, because of the age of the residents or the circumstances that lead individuals into non-institutional group quarters living arrangements, this population has low average wealth, and this fact in combination with its small size implies that the treatment of this population has little impact on estimates of aggregate, mean, or even median wealth. 16
to make comparisons with earlier SIPP panels, which do not identify unmarried partners. Like SCF families, therefore, primary families and individuals also correspond to households in number, but the residual families total less than 12 million. The all-family total using Census Bureau concepts is 114 million versus 122 million using the SCF family concepts. Columns two through four reveal how little wealth is held by families that do not include the householder, underscoring why the SCF focuses on the primary economic unit. SCF-like families account for nearly 98 percent of the total measured household net worth, or $14.4 trillion out of $14.7 trillion, and have a mean net worth of $140,200 with a median of $48,000. The residual families have a mean net worth of only $18,600 with a median of only $75. Using the Census Bureau concepts, primary families and individuals account for nearly 99 percent of the total measured household net worth, or $14.5 trillion out of the aforementioned $14.7 trillion. 9 Their mean net worth of $141,900 and median of $48,600 contrast sharply with the mean of only $16,500 and median of zero among the residual families. In sum, while the SCFlike families mimic the SCF primary economic unit most closely, we could substitute primary families and individuals or even households and not materially change the SIPP estimates of net worth. 9 Using the limited wealth data that the SCF collects for the set of household members who are not included in the primary economic unit, we estimate the aggregate net worth of this group at $204 billion, which is very close to the SIPP estimate for sub- and secondary families and individuals in Table II.1 and only about half as large as the SIPP estimate of $365 billion for “all other families”—the group excluded from our construction of SCF-like families. Because of the limited questions and the use of proxy respondents, however, the SCF probably understates the wealth of household members outside the primary economic unit. Regardless, our SIPP estimate of the aggregate wealth of persons outside the SCF-like family is sufficiently close to the SCF estimate to assure us that our method of constructing SCF-like families does not exclude too much or too little household wealth from the SIPP universe on which we base most of the cross-survey comparisons in this report. These results also indicate that when we have to substitute a Census Bureau family concept, as we must when comparing the 1996 SIPP panel with earlier SIPP panels later in this chapter, the shift in family concepts has a negligible impact. 17
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 and 24: sample included about 4,300 househo
Page 25 and 26: C. ACCOUNTING FOR DIFFERENCES IN SU
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: identification of unmarried partner
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
Page 75 and 76: differences by gender are smaller t
Page 77 and 78: somewhat more pronounced than in th
Page 79 and 80: Comparisons of SIPP and PSID median
Page 81 and 82: 65.0 percent of the HRS aggregate,
Page 83: exceeds the SIPP median by nearly $
Page 86 and 87:
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
Page 162 and 163:
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
Page 218 and 219:
Page 220 and 221:
Page 222 and 223:
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
Page 233 and 234:
FIGURE V.7 DISTRIBUTION OF MOTOR VE
Page 235 and 236:
FIGURE V.9 DISTRIBUTION OF LIFE INS
Page 237 and 238:
FIGURE V.11 DISTRIBUTION OF OTHER N
Page 239 and 240:
FIGURE V.13 DISTRIBUTION OF TOTAL N
Page 241 and 242:
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
Page 264 and 265:
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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