Survey Estimates of Wealth - Mathematica Policy Research

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the asset column as equity, with no associated liability, because that is how they are reported in either the SCF or SIPP (and we treat them the same). Comparing the separate estimates of assets and liabilities from the SIPP and the SCF yields a somewhat surprising explanation for some of the SIPP’s shortcomings in capturing net worth. The SIPP understates aggregate net worth by as much as it does, in part, because it does a better job of capturing total liabilities than total assets. Table II.4 compares SIPP and SCF estimates of total assets, non-retirement assets, and total liabilities. The SIPP estimate of total assets, at $18.8 trillion, is only 55 percent of the SCF estimate of $34.0 trillion, but the SIPP estimate of total liabilities, at $4.5 trillion, is 90 percent of the SCF estimate. More importantly, the SIPP estimate of median assets is 83 percent of the SCF estimate while the SIPP estimate of median liabilities of 97 percent of the SCF estimate. But because the SIPP accounts for a greater share of liabilities than assets, it accounts for a smaller share of net worth than assets. Excluding retirement accounts has little effect on the comparative size of SIPP and SCF assets, lowering the SIPP share of SCF assets by just a percentage point. This small impact implies that both surveys measure retirement wealth about equally well. We will examine each survey’s measurement of the components of retirement wealth in the next section of this chapter. Because there are no liabilities associated with these retirement accounts, removing them from total assets reduces aggregate and mean asset values by the same amount that it reduces net worth, as reported in Table II.3. 20 20 While the SCF captures the amounts of any outstanding loans against retirement accounts, the retirement account balances that respondents report may already be net of these loan balances. Because of the ambiguity in the questionnaire, we do not count these loans as liabilities in our estimates from the SCF. 26
3. The Distribution of Net Worth Table II.5 reports percentiles of the net worth distribution from 1 to 99 for each of the three surveys. We note, first, that negative net worth is more common in the SIPP than in either the PSID or the SCF. Families with negative net worth account for 11 to 12 percent of the population in the SIPP versus 8 to 9 percent in the PSID and 7 to 8 percent in the SCF. The SIPP also has somewhat more families with zero net worth than either the PSID or the SCF although we can infer only crude proportions from the percentile values in Table II.5. Between 15 and 16 percent of SIPP families have net worth that is less than or equal to zero compared to 11 to 12 percent of PSID families and 10 to 11 percent of SCF families. SIPP net worth continues to lag behind SCF net worth by 5 to 7 percentile points over much of the distribution. For example, $5,000 corresponds to the 26th percentile of the SIPP distribution but only the 20th percentile of the SCF distribution; and $100,000 corresponds to the 65th percentile in the SIPP distribution but only the 58th percentile in the SCF distribution. The lag diminishes near the very top of the distribution, but the differences between the percentile values become very large. As a proportion of SCF net worth, SIPP net worth rises from 0 percent at the 15th percentile to 25.2 percent at the 20th percentile and 46.8 percent at the 30th percentile. Between the 40th and 95th percentiles, SIPP net worth varies between 60 and 74 percent of SCF net worth, with the peak occurring at the 64th percentile. Near the top of the distribution the ratio of SIPP to SCF net worth begins to fall at an increasing rate. At the 99th percentile the SIPP net worth is only 32 percent of the SCF net worth. Taken at face value, this comparison of wealth distributions suggests that the SIPP misses a larger share of family wealth among families lower in the distribution—say, the bottom two quintiles—than among those higher in the distribution but short of the top few percentiles. 27
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: the marginally greater PSID populat
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
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
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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:
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
Page 235 and 236:
FIGURE V.9 DISTRIBUTION OF LIFE INS
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FIGURE V.11 DISTRIBUTION OF OTHER N
Page 239 and 240:
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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