Survey Estimates of Wealth - Mathematica Policy Research

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last day of November 1998 through the last day of February 1999. 2 The newly expanded HRS was conducted in 1998. To assess the SIPP’s capture of change in wealth over the 1990s, we also present limited estimates comparing the SIPP and the SCF in late 1992 and early 1993, and we include additional SIPP estimates from early 1995 and from waves 3, 6, 7, and 12 of the 1996 panel, which are centered on early 1997 and 1998, mid-1998, and early 2000. The remainder of this report is organized as follows. Chapter II compares recent estimates of wealth from the SIPP with estimates from the SCF and the PSID. Chapter III extends this comparison to a number of subpopulations and includes a comparison of SIPP and HRS estimates of wealth among the persons born before 1948. The findings presented in these two chapters provide the basis for a more detailed review of factors that account for the SIPP’s general underestimation of levels of wealth and its misrepresentation of at least some aspects of recent trends. The results from these analyses are reported in Chapter IV. Chapter V presents the results of an application of econometric modeling to decompose the differences between SIPP and SCF estimates of wealth and to test an approach to adjusting the SIPP microdata to more closely approximate the distribution of wealth in the SCF. Finally, Chapter VI presents a number of recommendations regarding the ORES’s continued use of SIPP wealth data, including strategies to adjust the SIPP wealth data and, thereby, improve its resemblance to the wealth data from the other surveys, and both interim and longer term strategies that the data producer—the Census Bureau—could employ to improve the quality of the SIPP wealth data. 2 The Census Bureau interviews one quarter of the SIPP sample—a “rotation group”—each month. The interviews for each wave of data collection, therefore, are distributed across four months. 10
II. COMPARATIVE ESTIMATES OF WEALTH Wealth, or net worth, is defined as total assets less total liabilities. In this chapter we compare SIPP estimates of net worth and component assets and liabilities with estimates from the SCF and the PSID. Additional comparisons, focusing on subpopulations, are presented in Chapter III, where we also include estimates from the HRS. This chapter is organized as follows. Section A compares the survey universes and their units of observation and outlines a strategy for making comparative estimates from the three surveys. Section B compares SIPP, SCF, and PSID estimates of net worth, assets, and liabilities in the period 1998 to 1999. Section C examines differences in survey estimates of the components of wealth for the same period. Section D compares the SIPP and the SCF with respect to estimates of change in wealth holdings over the 1990s. Finally, Section E summarizes the chapter’s main conclusions. A. SURVEY UNIVERSES AND UNITS OF OBSERVATION Each of the three surveys on which we base our comparisons in this chapter is ultimately intended to be representative of the entire noninstitutionalized population, but each collects data from a different unit of observation. We will use the term “family” in speaking generically about the data collection and reporting unit for all three surveys, but first we lay out how the survey concepts differ. 1. SCF Families The SCF collects its most detailed data on the “primary economic unit”, which is defined as the “economically dominant single individual or couple (whether married or living together as partners) and all other persons living in the household who are financially dependent on that person or those persons” (Kennickell, Starr-McCluer, and Surette 2000). The SCF collects very 11
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: either the 1984 SIPP or the PSID. T
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
Page 75 and 76: differences by gender are smaller t
Page 77 and 78: 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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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
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Page 314 and 315:
APPENDIX TABLE C.5 (continued) COEF
Page 316 and 317:
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