Survey Estimates of Wealth - Mathematica Policy Research

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Table II.8 provides estimates of aggregate assets, liabilities, and net worth by quintile of net worth for SIPP and the SCF. Including the bottom quintile, where the SIPP finds greater aggregate negative net worth than the SCF, the SIPP estimates much lower aggregate net worth than the SCF in every quintile. The SIPP approaches the SCF most closely in the third and fourth quintiles, where the SIPP accounts for 68 and 73 percent, respectively, of the SCF aggregate net worth. But the SIPP finds only 45 percent of the SCF aggregate net worth in the top quintile and only 51 percent in the second quintile. Families with a net worth of two million dollars or more account for nearly $12 trillion of the aggregate wealth estimated by the SCF and $7 trillion of the net worth estimated by the PSID but only $1.5 trillion of the net worth estimated by the SIPP. After excluding this group the SIPP share of the SCF estimate of aggregate wealth in what remains of the top quintile rises to nearly 79 percent, or somewhat higher than the SIPP share of the aggregate net worth in the fourth quintile. Over the whole population the SIPP estimate of aggregate net worth excluding the wealthy is 75 percent of the comparable SCF estimate. The similarity between the PSID and SCF estimates of aggregate net worth by quintile is striking. The estimates are essentially identical in the second and fourth quintiles, and they become identical in the top quintile and over the whole population after the wealthy families are removed. The PSID falls short of the SCF aggregate only in the first and third quintiles. Separating assets and liabilities shows that the story is more complex than the net worth distributions would suggest. In the bottom quintile of the net worth distribution, the SIPP captures 36 percent more aggregate assets and 65 percent more aggregate liabilities than the SCF. With liabilities dominating assets in this quintile, however, the SIPP ends up with lower (that is, substantially more negative) aggregate net worth than the SCF. In the middle three quintiles of the net worth distribution, the SIPP captures 77 to 82 percent of the aggregate assets 32
and 96 to 105 percent of the aggregate liabilities reported in the SCF. Overall, the SIPP captures 80.3 percent of the aggregate assets and 100.9 percent of the aggregate liabilities of the nonwealthy as estimated by the SCF. Again, by doing better with liabilities than assets, the SIPP does less well with net worth than with total assets in every quintile. C. COMPONENTS OF WEALTH Previous comparisons of SIPP and SCF wealth data have provided evidence that the SIPP is more effective at capturing some types of assets than others (Curtin, Juster and Morgan 1989; Wolff 1999). We compare the SIPP and the SCF with respect to the components of wealth that can be identified in common across the two surveys, and we show the contributions of components that are measured in the SCF but not the SIPP. We also include a more limited comparison that includes the PSID. We conclude this section by examining the ownership of assets and liabilities as reported across the three surveys. 1. A Typology of Wealth As the basis for organizing this comparison, we developed a typology of wealth components, which separates assets and liabilities. Because the SCF collects so much more detail than the SIPP, we decided to base this typology primarily on the asset and liability categories identified in the SIPP—adding categories, as necessary, to account for additional types of assets for which the SIPP collects no data but other surveys do. Table II.9 presents this classification scheme for assets and liabilities. A document mapping the SIPP, SCF, PSID, and HRS survey questions into this typology is presented in Appendix A. Computer code that we used to create these components from the public use files of the four surveys is included in Appendix B. Our typology recognizes nine types of financial assets, four types of property assets, and two additional categories that we label “SIPP pension assets,” which are collected in a separate 33
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 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: which members of our expert panel r
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
Page 88 and 89: TANF and other forms of welfare or
Page 90 and 91: We can use the information containe
Page 92 and 93: B. COVERAGE AND CONTENT In developi
Page 94 and 95: We constructed an additional measur
Page 96 and 97: Table IV.6 summarizes the effects o
Page 98 and 99: 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:
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
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FIGURE V.7 DISTRIBUTION OF MOTOR VE
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FIGURE V.9 DISTRIBUTION OF LIFE INS
Page 237 and 238:
FIGURE V.11 DISTRIBUTION OF OTHER N
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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
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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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