taking risks in investing in the equity market

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Taking Risks in Investing in theEquity MarketMartha N. Ozawa PhD a & Yat-Sang Lum PhD ba George Warren Brown School of Social Work ,Washington University in St. Louis , USAb University of Minnesota-Twin Cities , USAPublished online: 11 Oct 2008.

To cite this article: Martha N. Ozawa PhD & Yat-Sang Lum PhD (2001) Taking Risksin Investing in the Equity Market, Journal of Aging & Social Policy, 12:3, 1-21, DOI:10.1300/J031v12n03_01

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GENERAL ARTICLES

Taking Risks in In vestingin the Eq uity Mar ket:

Ra cial and Eth nic Dif fer ences

Mar tha N. Ozawa, PhDGeorge War ren Brown School of So cial Work

Yat-Sang Lum, PhDUni ver sity of Min ne sota

ABSTRACT. Some pol icy mak ers and pol icy an a lysts have pro posedthat So cial Se cu rity should be pri vat ized to en able par tic i pants toachieve higher re turns through in vest ment in the stock mar ket. How well in di vid ual re tir ees would fare fi nan cially un der a pri vat ized sys tem

Mar tha N. Ozawa, PhD, is Bettie Bofinger Brown Pro fes sor of So cial Pol icy atGeorge War ren Brown School of So cial Work, Wash ing ton Uni ver sity in St. Louis. Her re cent re search fo cuses on the eco nomic well-be ing of el derly per sons and chil -dren; redistributive ef fects of EITC and chil dren’s al low ances on chil dren; eco nomicclass and re dis tri bu tion of in come through spousal ben e fits un der So cial Se cu rity;money’s worth in So cial Se cu rity; and de ter mi nants of early re tire ment. Dr. Ozawa can be con tacted at Wash ing ton Uni ver sity, Cam pus Box 1196, One Brookings Drive, St.Louis, MO 63130 (E-mail: [email protected]).

Yat-Sang Lum, PhD, is As sis tant Pro fes sor at the School of So cial Work at the Uni -ver sity of Min ne sota-Twin Cities. Dr. Lum’s cur rent re search agenda fo cuses on thein ter face be tween eco nomic well-be ing, health, and long-term care of the el derly. Dr.Lum may be con tacted at the Uni ver sity of Min ne sota, School of So cial Work, 105 Pe -ters Hall, 1404 Gortner Avenue, St. Paul, MN 55108 (E-mail: [email protected]).

This ar ti cle was a pa per pre sented at the 52nd An nual Sci en tific Meet ing of the Ge -ron to log i cal So ci ety of Amer ica, San Fran cisco, No vem ber 20, 1999.

Jour nal of Aging & So cial Policy, Vol. 12(3) 2001 2001 by The Haworth Press, Inc. All rights re served. 1

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largely de pends on their de ci sion to in vest in the eq uity mar ket, ratherthan in other types of in vest ment ve hi cles. For that rea son, it is im por tantto in ves ti gate the de gree to which mi nor ity peo ple are cur rently in vest -ing in this mar ket. This ar ti cle pres ents the find ings of a study that com -pared the in vest ment be hav ior of black and His panic peo ple aged 51 to61 with the in vest ment be hav ior of their white coun ter parts. The ma jorfind ings in di cate that black and His panic peo ple: (a) are less likely to in -vest in the eq uity mar ket than are white peo ple, and (b) tend to in vestsmaller per cent ages of their as sets in the eq uity mar ket. Im pli ca tions for pol -icy are dis cussed. [Ar ti cle cop ies avail able for a fee from The Haworth Doc u mentDe liv ery Ser vice: 1-800-342-9678. E-mail ad dress: <[email protected]>Website: <http://www.HaworthPress.com> © 2001 by The Haworth Press, Inc. Allrights re served.]

KEYWORDS. In vest ment be hav ior, mi nor ity, So cial Se cu rity, pri vat -iza tion

INTRODUCTION

Fac ing the even tual in sol vency of Old-Age, Sur vi vors, and Dis abil ity In -sur ance (OASDI) and rec og niz ing that the in vest ment of fi nan cial as sets in thepri vate sec tor rather than in So cial Se cu rity gen er ally yields a higher rate of re -turn, many Amer i cans have come to be lieve that So cial Se cu rity should be pri -vat ized. One of the three rec om men da tions made by the 1994-1996 Ad vi soryCoun cil on So cial Se cu rity (1997) re flects the pub lic’s grow ing in ter est in thepri vat iza tion of So cial Se cu rity. This rec om men da tion, called the Per sonal Se -cu rity Ac counts (PSA) plan, pro poses to trans form OASDI into a two-tier sys -tem, with the first tier pro vid ing a flat-amount ben e fit (equiv a lent to 65% ofthe pov erty line) and the sec ond tier con sist ing of large-scale in di vid u al izedre tire ment ac counts, fi nanced by five per cent age points of the OASDI em -ployee pay roll tax. In ef fect, this plan would trans form So cial Se cu rity into acom bi na tion of de fined-ben e fit and de fined-con tri bu tion pro grams. The de -vel op ment of in di vid u al ized re tire ment ac counts, with to tal con trol by in di vid -u als, and the in cor po ra tion of the de fined-con tri bu tion scheme are clearin di ca tions of “pri vat iza tion.”

Given the rap idly chang ing ide ol ogy of So cial Se cu rity in the United Statesand the pub lic’s grow ing in ter est in the pri vat iza tion of So cial Se cu rity, a ma jorques tion is this: How will mi nor ity peo ple fare in in vest ing their fi nan cial re -sources if and when So cial Se cu rity is par tially pri vat ized, as de tailed in the PSA

2 JOURNAL OF AGING & SOCIAL POLICY

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plan? Mi nor ity peo ple–es pe cially blacks and His pan ics–seem hand i capped inthis re gard: First, their level of ed u ca tion is gen er ally lower than that of other ra -cial and eth nic groups (U.S. Bu reau of the Cen sus, 1998, p. 167). Higher ed u ca -tion trans lates into a better un der stand ing of in vest ment op por tu ni ties, as well asskills in in vest ing to max i mize the rate of re turn. Sec ond, their net worth is onlya frac tion of white peo ple’s net worth, even af ter other so cio eco nomic vari ablesare con trolled (Ol i ver & Shapiro, 1995; Ozawa, Lum, & Tseng, 1999; Ozawa &Tseng, 2000; Shea, Miles, & Hay ward, 1996; Smith, 1995). Pressed for im me di -ate con sump tion, these mi nor ity groups have lit tle money to in vest for fu ture re -turns and thus have lit tle ex pe ri ence in vest ing in the eq uity mar ket. Third, evenaf ter other vari ables are con trolled, there may be cul tural dif fer ences in the al lo -ca tion of fi nan cial as sets–for ex am ple, eq uity mar ket ver sus cer tif i cate of de -posit ver sus home eq uity–each of which has a dif fer en tial risk and a dif fer en tialrate of re turn. That is, mi nor ity peo ple may have dif fer ent lev els of tol er ance intak ing risks in in vest ing in the eq uity mar ket. Last, fi nan cial in sti tu tions may en -gage in dis crim i na tory prac tices in deal ing with mi nor ity cli ents, who, as a re -sult, may be dis cour aged from in vest ing in the eq uity mar ket. Un der stand ing the in vest ment be hav ior of black and His panic peo ple is vi tal as the na tion de batesthe fea si bil ity and the de sir abil ity of pri vat iz ing So cial Se cu rity.

The pres ent study, the find ings of which are pre sented in this ar ti cle, probed the in vest ment be hav ior of black and His panic peo ple, and com pared that be -hav ior with that of white peo ple. In par tic u lar, it is im por tant to in ves ti gate thelike li hood of mi nor ity groups in vest ing their fi nan cial re sources in the eq uitymar ket, that is, stocks and stock mu tual funds, be cause in vest ing in these in -stru ments gen er ally yields a higher rate of re turn in the long run than does in -vest ing in other types of in stru ments, al though in vest ing in stocks and stockmu tual funds in volves a higher risk. In vesting in stocks and stock mu tual funds is cru cial be cause only through suc cess ful in vest ment in these in stru ments canone en sure ad e quate re tire ment in come un der a pri vat ized Social Se cu ritysystem. Thus, this study ad dressed the fol low ing two ques tions:

1. What is the like li hood of black and His panic peo ple in vest ing their fi -nan cial re sources in stocks and stock mu tual funds, in com par i son to thatof white peo ple?

2. What de ter mines the pro por tion of to tal as sets, net of home eq uity, that is in vested in stocks and stock mu tual funds?

REVIEW OF THE LITERATURE

U.S. in ves tors can be char ac ter ized as mid dle-of-the-road. For ex am ple, astudy by the Gen eral Ac count ing Of fice (GAD, 1996) re ported that among

Mar tha N. Ozawa and Yat-Sang Lum 3

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those who par tic i pate in 401(k) plans, 27% in vest ex clu sively in stocks, 26%in vest ex clu sively in bonds, and the rest, 46%, in vest in a com bi na tion ofstocks and bonds. Over the years, in ter est in stock hold ing has in creased. From1992 to 1995 alone, the like li hood that Amer i can fam i lies would hold stocksdi rectly or in di rectly in creased from 37% to 41%, and the share of such stockhold ings in creased from 32% to 40% of their to tal fi nan cial as sets (Kennickell, Star-McCluer, & Sunden, 1997).

Whether a per son is an ag gres sive in ves tor–that is, will ing to in vest instocks and stock mu tual funds–largely de pends on so cio eco nomic fac tors andde mo graphic vari ables. Re search has ex ten sively shown that those who havehigh in comes, have better ed u ca tion, and hold high-skilled/high-pay ing jobs arepar tic u larly ag gres sive in ves tors (Grabel, Lyt ton, & Kratzer, 1996; Hunger ford,1997; Zhong, 1994). Shefrin and Tha ler (1988) hy poth e sized that those withhigh in comes tend to have types of in come, such as cap i tal gains, div i dends,rents, and bo nuses, that are not nec es sary for im me di ate con sump tion; there -fore, they can af ford to set aside a pro por tion of their in come for sav ing and in -vest ing. In ad di tion, those who al ready have em ployer-pro vided pen sioncov er age, such as 401(k) plans, tend to be ag gres sive in ves tors by in vest ing instocks and stock mu tual funds on their own (Hunger ford, 1997). Per sons inhigh-skilled and high-pay ing jobs can main tain cer tain life styles, such as hav -ing greater au ton omy in their use of time, that are con du cive to spend ing timeon in vest ing (Grabel et al., 1996). Re searchers iden tify ed u ca tion as a strongcor re late of risk tak ing in in vest ing, in di cat ing that ed u ca tional level is a goodproxy for level of knowl edge about in vest ing (Bernheim & Garrett, 1996;Grabel et al., 1996; Sunden & Surette, 1998; Zhong, 1994). In ad di tion, knowl -edge about in vest ment that is ac quired through fi nan cial ed u ca tion given at awork place is a strong de ter mi nant of in vest ment de ci sions (Bernheim &Garrett, 1996). Fur ther more, Barsky, Juster, Kimball, and Shapiro (1997)found that the will ing ness to in vest in the eq uity mar ket is re lated to how muchrisk one can tol er ate in in vest ment.

The lit er a ture has shown that de mo graphic vari ables–age, gen der, mar i talsta tus, and race–and health con di tion make a dif fer ence in in vest ment be hav -ior. The im por tance of age as a de ter mi nant of in vest ment be hav ior stems from the lifecycle hy poth e sis, which states that in di vid u als “dissave” (that is, de -pend on other peo ple) dur ing the early stage of the lifecycle, save dur ing themid dle years, and dissave (that is, use their own sav ings) in old age (Hurd,1990; Kuehlwein, 1995; Shefrin & Tha ler, 1988). Re search has shown thatamong all age groups, peo ple aged 55-64 are the most likely not only to holdstocks, but to hold the larg est num ber of stocks. Parke (1998) noted that oldage is re lated to con ser va tive in vest ment, in di cat ing that in vest ment in stocksde clines as one be comes older.


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Women tend to be more con ser va tive in in vest ing than are men(Bajtelsmight & Vanderhei, 1997; GAO, 1996; Grabel et al., 1996; Hinz, Mc -Car thy, & Turner, 1997; Hunger ford, 1997; Parke, 1998; Zhong, 1994). But inre cent years, re search has shown the im por tance of the in ter ac tion be tweengen der and mar i tal sta tus as a de ter mi nant of risk tak ing in in vest ment. For ex -am ple, Sunden and Surette (1998) found that in vest ment de ci sions are drivenmore by a com bi na tion of gen der and mar i tal sta tus than by gen der alone andin di cated that sin gle women and mar ried men are less likely than sin gle men(the com par i son group) to choose “mostly stocks” as an op tion for in vest ingtheir money. They dem on strated that if this in ter ac tion fac tor was not in cludedin the re gres sion, the out come of gen der as a pre dic tor would be dif fer ent.

The vari able race and eth nic ity, which is the fo cal point of the pres ent study, has been gen er ally dealt with as a con trol vari able in pre vi ous re search. Law -rence (1991) in cluded race as a con trol. Hunger ford (1997) re ported that His -panic peo ple are more con ser va tive than other peo ple in their in vest ments. The GAO study (1996) men tioned that black peo ple are more likely to be cov eredby a de fined ben e fit plan, and white work ers are more likely to par tic i pate in a401(k) pen sion plan, which is a de fined-con tri bu tion plan. No study has in ves -ti gated the prob a bil ity of black and His panic peo ple in vest ing in stocks andstock mu tual funds and the al lo ca tion of nonhousing as sets for in vest ing inthese in stru ments. The pres ent study is an at tempt to fill this void.

METHODOLOGY

Hy poth e sis and Con cep tual Frame work

We posit that black and His panic peo ple are not only less likely to in vest inthe stock mar ket than are white peo ple, but that they in vest a smaller por tion oftheir to tal as sets, net of home eq uity, in the stock mar ket. To net out the ef fectof race and eth nic ity on these two as pects of in vest ment be hav ior, we in cluded, as con trols, the vari ables that are known to af fect in vest ment be hav ior: age, ed -u ca tion, gen der, health con di tion, risk tol er ance, and in come. (Mar i tal sta tuswas in cluded in the sam ple se lec tion model.) As im plied ear lier, better ed u ca -tion pro vides peo ple with skills in and knowl edge about sav ing and in vest ing,be sides be ing a strong in di ca tor of so cio eco nomic sta tus. Health con di tion was in cluded as a con trol be cause peo ple with poor health are ex pected to in curlarger ex pen di tures for health care than are those with good health. (Ideally,for the pur pose of this study, an in di ca tor of life time health ex pen di tures isneeded, but it is im pos si ble to in clude such a vari able be cause of the lim i ta -tions of the data.) In ad di tion, we in cluded in come and risk tol er ance as con -


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trols. We ex pect that those with high in comes find it eas ier to set aside apor tion of their in comes for sav ing and in vest ing. The de gree of risk tol er ancemay af fect whether and how much one in vests in the eq uity mar ket, as the lit er -a ture re view in di cated. Finally, age may af fect in vest ment be hav ior, as the lit -er a ture re view in di cated. For these rea sons, age, ed u ca tion, health con di tion,gen der, risk tol er ance, and in come were in cluded in our study as con trol vari -ables to es ti mate the ef fect of race and eth nic ity on in vest ment be hav ior.

We rec og nized that the vari able in come might have an endogenuity prob -lem in re la tion to ed u ca tion. Thus, we de vel oped two mod els for ourmultivariate anal y sis: one in clud ing the vari able in come, and the other ex clud -ing this vari able (for a de tailed dis cus sion, see Ozawa et al., 1999).

We chose the in vest ment of fi nan cial re sources in stocks and stock mu tualfunds as the fo cal point of our study be cause this vari able clearly in di cates in -di vid u als’ will ing ness to take risks to max i mize the rate of re turn. Cer tainly,other types of in vest ment ve hi cles, such as 401(k), 403(b), and Keogh ac -counts, may in volve in vest ing in stocks and stock mu tual funds. How ever,only 35% of the U.S. workforce are el i gi ble to par tic i pate in de fined con tri bu -tion plans through these ac counts, and fewer work ers who are em ployed insmall com pa nies are el i gi ble to par tic i pate be cause these com pa nies gen er allydo not pro vide such plans (GAO, 1996; Poterba, Venti, & Wise, 1995); there -fore, these ac counts do not truly re flect vol un tary risk tak ing in in vest ment.

Sam ple and Source of Data

The source of data for the study was Wave 1 of the Health and Re tire mentStudy (HRS), col lected in 1992, by the Uni ver sity of Mich i gan un der a con -tract with the fed eral gov ern ment. The sam ple was com posed of fam i lies withat least one fam ily mem ber aged 51 to 61. The sur vey asked the pri mary re -spon dent and his or her spouse ques tions re gard ing their cur rent and past em -ploy ment (in clud ing pen sion cov er age), fam ily as set hold ing and debts, andde mo graphic in for ma tion. Thus, the sur vey pro vides an im por tant set of dataabout peo ple who are ap proach ing re tire ment, but who are not old enough tore ceive So cial Se cu rity ben e fits.

For our study, we in cluded those who fell in the cat e go ries of non-His panicwhite, non-His panic black, and His panic peo ple, ex clud ing other ra cial/eth niccat e go ries of peo ple. Through this se lec tion pro cess, we iden ti fied 7,381 re -spon dents: 5,259 non-His panic whites, 1,412 non-His panic blacks, and 710His pan ics. Here af ter, they are re ferred to sim ply as whites, blacks, and His -pan ics.

The de mo graphic vari ables and vari ables for ed u ca tion, health sta tus, andrisk tol er ance per tain to the pri mary re spon dent of the house hold unit. If the


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pri mary re spon dent was not age el i gi ble (age 51-61) at the time of the in ter -view, we used the vari ables per tain ing to the age-el i gi ble spouse. The data onto tal as sets (net worth), home eq uity, and non-home as sets, as well as in come,per tain to house holds in which the re spon dents re sided.

Def i ni tion of Vari ables

De pend ent vari able: In vesting in stocks and stock mu tual funds. One of thetwo de pend ent vari ables in this study was whether or not the re spon dents ap -proach ing re tire ment had their money in vested in the stock mar ket. To mea -sure this vari able, we de vel oped a dummy vari able, where the value of 1 wasgiven to the re spon dents who had at least one dol lar in vested in stocks and/orstock mu tual funds, and the value of zero was given to those who did not.

De pend ent vari able: Amount of in vest ment in stocks and stock mu tualfunds. To mea sure this vari able, we cal cu lated the per cent age of the to tal as -sets, net of home eq uity, that was in vested in stocks and/or stock mu tual funds.

In de pend ent vari able: Race and eth nic ity. We di vided the re spon dents intothree groups: non-His panic white, non-His panic black, and His panic. SomeHis pan ics are non white, while oth ers are white. In our study, we iden ti fiedHis pan ics (re gard less of their race) as one dis tinct group and di vided non-His -pan ics into white and black groups. Two dummy vari ables were de vel -oped–one for blacks and the other for His pan ics–giv ing the value of zero towhites.

Con trol vari able: Ed u ca tion. Ed u ca tion was mea sured by dummy vari ables for the groups of re spon dents who did not com plete high school, com pletedhigh school, had at least some col lege ed u ca tion, and com pleted col lege.Those who did not com plete high school were as signed to the ref er ence group.

Con trol vari able: Mar i tal sta tus. We de vel oped three dummy vari ables forthe groups of re spon dents who were wid owed, di vorced or sep a rated, andnever mar ried. Those who were mar ried were as signed to the ref er ence group.This vari able was used in the sam ple se lec tion model.

Con trol vari able: Health con di tion. To mea sure this vari able, we de vel -oped three dummy vari ables for those whose health was “ex cel lent,” “verygood,” and “fair,” as sign ing those with “poor” health to the ref er ence group.

Con trol vari able: Risk tol er ance. Risk tol er ance was mea sured by threedummy vari ables for groups of re spon dents whose lev els of risk tol er ancewere low, mod er ately low, and mod er ately high. Re spon dents with a highlevel of risk tol er ance were as signed to the ref er ence group.

Fol low ing the ap proach taken by Barsky et al. (1997), we de vel oped our in -di ca tors of risk tol er ance by mea sur ing the de gree of re spon dents’ will ing nessto change their jobs un der dif fer ent sce nar ios: The re spon dents who were will -


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ing to take a sim i lar job that would pro vide a 50-50 chance of ei ther in creas ingtheir in come by 50% or re duc ing their in come by 50% were char ac ter ized ashav ing a high level of risk tol er ance. Those who were will ing to take a sim i larjob that would pro vide a 50-50 chance of ei ther in creas ing their in come by50% or re duc ing their in come by 33% were char ac ter ized as hav ing a mod er -ately high level of risk tol er ance. Those who were will ing to take a sim i lar jobthat would pro vide a 50-50 chance of ei ther in creas ing their in come by 50% orre duc ing their in come by 20% were char ac ter ized as hav ing a mod er ately lowlevel of risk tol er ance. Those who were not will ing to take a sim i lar job thatwould pro vide a 50-50 chance of ei ther in creas ing their in come by 50% or re -duc ing their in come by even less than 20% were char ac ter ized as hav ing a lowlevel of risk tol er ance (see Barsky et al., 1997).

Con trol vari able: In come. In come was mea sured by plac ing the re spon -dents in the low est, sec ond, third, fourth, or fifth (high est) quintile of the in -come dis tri bu tion. We de vel oped four dummy vari ables for those who fell inthe sec ond, third, fourth, and fifth quin tiles, as sign ing those in the low estquintile to the ref er ence group.

Data Pre sen ta tion and Sta tis ti cal Pro ce dure

We gen er ated de scrip tive sta tis tics on the back grounds of the re spon dents.We also gen er ated de scrip tive sta tis tics on the per cent age of the re spon dentswith as set hold ings in var i ous types of as sets and on the mean amount of as -sets.

We per formed two types of re gres sion mod els. We used (1) the probitmodel with sam ple se lec tion to es ti mate the like li hood of the black and His -panic re spon dents, com pared with the white re spon dents, in vest ing in the eq -uity mar ket (Greene, 1997; Van de Ven & Van Pragg, 1981) and (2) the OLSre gres sion model with sam ple se lec tion to es ti mate the ef fects of race and eth -nic ity on the pro por tion of the to tal as sets, net of home eq uity, that was in -vested in the eq uity mar ket. Both mod els used the Heckman (1976, 1979)tech nique to cor rect for sam ple se lec tion bias in the data and thus to yield un bi -ased re gres sion co ef fi cients. These mod els were par tic u larly suited for ourstudy be cause they al lowed us to in ves ti gate the in vest ment be hav ior of allblack and His panic re spon dents, in stead of just those who had as sets to in vestin the eq uity mar ket.

The fol low ing de pend ent and in de pend ent vari ables were in cluded in thesam ple se lec tion model: The de pend ent vari able was a dummy vari able, where the value of 1 was given to the re spon dents who had any types of as sets, andthe value of zero was given to those who did not. The in de pend ent vari ableswere age, race/eth nic ity, gen der, ed u ca tion, mar i tal sta tus, and in come.


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We used the weight vari able that was de vel oped by the HRS re search teamto gen er ate de scrip tive sta tis tics on all vari ables. This pro ce dure was needed to ad just for the sam pling, post strat i fi ca tion, and nonresponse bi ases in the HRSdata sets.

FINDINGS

De scrip tive Sta tis tics

Back grounds of the re spon dents. Ta ble 1 in di cates that there were dis cern -ible dif fer ences in the mar i tal sta tus, ed u ca tion, health con di tion, risk tol er -ance, and eco nomic sta tus of the white, black, and His panic re spon dents. Agreat ma jor ity of the white re spon dents were mar ried (72%), com pared with45.7% of the black re spon dents and 62.8% of the His panic re spon dents.

The white re spon dents were con sid er ably better ed u cated than were theblack or His panic re spon dents. Al though only 11% of the black re spon dentsand 7.2% of the His panic re spon dents were col lege grad u ates, 23.4% of thewhite re spon dents were col lege grad u ates. Fewer than 1 in 5 white re spon dents had less than a high school ed u ca tion ver sus 42.7% of the black re spon dentsand 61.9% of the His panic re spon dents.

In ad di tion, the health con di tion of the white re spon dents was better. Thatis, 1 in 4 white re spon dents had ex cel lent health, com pared with 11.4% of the black re spon dents and 17.5% of the His panic re spon dents. In con trast, thehealth con di tions of 12.3% of the black re spon dents and 14.3% of the His -panic re spon dents were poor, com pared with only 6.6% of the white re spon -dents. As Barsky et al. (1997) found, larger per cent ages of black andHis panic re spon dents than of whites had the high est level of risk tol er ance. In par tic u lar, the His panic re spon dents had the larg est per cent age of the threegroups with the high est risk tol er ance, and the black re spon dents had higherper cent ages with high and low lev els of risk tol er ance than did the white re -spon dents. This find ing may in di cate that there was a greater vari a tion in thede gree of risk tol er ance among the black re spon dents than there was amongthe white re spon dents.

As ex pected, the black and His panic re spon dents were con sid er ably worseoff than the white re spon dents in terms of both as sets and in come. The me di ans of the to tal as sets of the black and His panic re spon dents were only 21.3% and24.7%, re spec tively, of the white re spon dents’ me dian to tal as sets. Sim i larly,the me dian in comes of the black and His panic re spon dents were only 52.9%and 55.8%, re spec tively, of the white re spon dents’ me dian in come.


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As sets al lo ca tion. Ta ble 2 pres ents the per cent age of the re spon dents withas set hold ings and the mean amounts of the as sets.

The ta ble in di cates that the dif fer en tial in the own er ship of stocks orstock mu tual funds by the white re spon dents ver sus black and His panic re -spon dents was par tic u larly great. The per cent age of whites own ing stocksor stock mu tual funds was 4.1 times and 4.9 times, re spec tively, of theblacks and His pan ics own ing them. The hold ing of re tire ment ac counts(IRA and Keogh ac counts) dif fered greatly as well. The per cent age ofwhites with re tire ment ac counts was 3.5 times and 4.2 times, re spec tively,


TABLE 1. Back grounds of the Re spon dents

All White Black His panic

(N = 7,381) (N = 5,259) (N = 1,412) (N = 710)

Mar i tal Sta tus

Married 68 .4 72 .0 45 .7 62 .8

Widowed 8.2 7.2 15 .0 8.8

Di vor ced or sep a rated 18 .7 16 .6 30 .5 23 .2

Never mar ried 4.7 4.2 8.7 5.2

Race/Eth nic ity

White 81 .6 n.a. n.a. n.a.

Black 10 .9 n.a. n.a. n.a.

His panic 7.5 n.a. n.a. n.a.

Ed u ca tion

Less than high school 25 .4 19 .7 42 .7 61 .9

High school grad u ate 34 .3 36 .5 28 .9 17 .8

Some col lege 19 .5 20 .3 17 .5 13 .1

Col lege grad u ate 20 .8 23 .4 11 .0 7.2

Health Sta tus

Ex cel lent 23 .5 25 .6 11 .4 17 .5

Very good 28 .8 30 .9 21 .9 16 .0

Good 26 .5 25 .7 31 .2 28 .9

Fair 13 .4 11 .1 23 .3 23 .3

Poor 7.8 6.6 12 .3 14 .3

Risk Tolerance

Low 64 .2 64 .3 67 .1 58 .0

Mod er ate low 12 .2 12 .7 10 .2 8.8

Mod er ate high 10 .9 10 .8 9.8 13 .6

High 12 .8 12 .3 12 .9 19 .6

Eco nomic Sta tus

Me dian to tal as sets ($) 102,000 127,200 27,100 31,500

Me dian in come ($) 39,228 43,000 25,000 24,000

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the per cent ages of blacks and His pan ics with these ac counts. The own er -ship of busi ness eq uity was also more prev a lent among the whites thanamong the blacks or His pan ics. The ra tio of own er ship of busi ness eq uityby whites ver sus blacks was 2.1:1, and the ra tio of own er ship by whites ver -sus His pan ics was 1.7:1.

Ta ble 2 also in di cates that the mean amount of as sets held by whites wasfar greater than the mean amount of as sets held by blacks or His pan ics. Inpar tic u lar, the value of stocks or stock mu tual funds held by whites($24,350) was 5.4 times and 11.9 times, re spec tively, the amounts held byblacks ($4,532) and His pan ics ($2,048). The dif fer en tial in the amount ofbusi ness eq uity was just as great. The ra tios of busi ness eq uity held bywhites to those held by blacks and by His pan ics were 6.4:1 and 1.7:1, re -spec tively.


TABLE 2. Per cent age with As set Hold ings and Amount of As sets

All White Black His panic

(N = 7,381) (N = 5,259) (N = 1,412) (N = 710)

Per cent age with As set Holdings

Home eq uity 78 .6 83 .3 58 .6 56 .7

Liq uid fi nan cial as sets 83 .0 89 .6 57 .4 49 .3

Re tire ment ac counts 42 .2 48 .8 14 .1 11 .7

Stocks/mu tual stock funds 30 .2 35 .2 8.5 7.2

Busi ness eq uity 17 .4 19 .7 6.6 7.7

Other real es tate 32 .0 35 .1 16 .9 20 .6

Other as sets 90 .5 95 .1 67 .3 75 .1

Amount of As sets (mean)

Home eq uity 66,117 73,695 28,742 38,265

Liq uid fi nan cial as sets 25,302 29,530 7,132 5,870

Re tire ment ac counts 19,874 23,378 5,223 3,177

Stocks/mu tual stock funds 20,507 24,350 4,532 2,048

Busi ness eq uity 40,584 46,253 7,254 27,550

Other real es tate 50,524 57,049 22,209 20,944

Other as sets 20,028 23,043 6,697 6,725

To tal As sets (net worth)

Mean 242,937 277,298 81,788 104,577

Me dian 102,000 127,200 27,100 31,500

Note: Liq uid fi nan cial as sets in clude CDs, T-bills, and bonds. Re tire ment ac counts in clude IRA and Keogh ac -counts.

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Multivariate Anal y ses

Probit re gres sion anal y sis. Ta ble 3 pres ents the re sults of the probit re gres -sion anal y sis, with sam ple se lec tion, of in vest ing in the eq uity mar ket. The re -sults of Model 1 show that com pared with the white re spon dents, the blackre spon dents were 49.1% less likely to in vest in the eq uity mar ket (stocks orstock mu tual funds) than were the white re spon dents, con trol ling for othervari ables. The re sults also show that His panic re spon dents were 59.4% lesslikely to in vest in the eq uity mar ket than were the white re spon dents. (The per -cent ages were ob tained as fol lows: First we mul ti plied the probit co ef fi cientsby 1.6 to trans form the probit co ef fi cients to logit co ef fi cients [Amemiya,1981]. Sec ond, we trans formed the logit co ef fi cients to odds ra tios. Finally, we con verted the odd ra tios to per cent ages).

Un der Model 1, the con trol vari ables age, gen der, ed u ca tion, and healthwere all sig nif i cant. The prob a bil ity of the men in vest ing in the eq uity mar ketwas 1.2 times the prob a bil ity of the women. The prob a bil ity of those with acol lege ed u ca tion in vest ing in the eq uity mar ket was 4.2 times the prob a bil ityof those with less than a high school ed u ca tion. Sim i larly, the prob a bil ity ofthose in ex cel lent health in vest ing in the eq uity mar ket was 2.1 times the prob -a bil ity of those in poor health. Age was pos i tively re lated to the prob a bil ity ofin vest ing in the eq uity mar ket, but risk tol er ance was not sig nif i cantly re lated.

Model 2 in cludes in come as a con trol vari able. The level of in come wasstrongly re lated to the prob a bil ity of in vest ing in the eq uity mar ket. The prob a -bil ity of the re spon dents in the fifth (high est) in come quintile in vest ing in theeq uity mar ket was 2.4 times the prob a bil ity of those in the low est in comequintile. It is im por tant to note that the in clu sion of the in come vari able madethe like li hood of black and His panic re spon dents in vest ing in the eq uity mar -ket even smaller, with blacks be ing 55.8% less likely and His panics be ing63.3% less likely to do so. The in clu sion of the in come vari able did not al terthe di rec tions and sig nif i cance lev els of the other con trol vari ables, with theex cep tion of gen der, which be came in sig nif i cant.

Ta ble 3 also shows the co ef fi cients of the sam ple se lec tion model. Since thesam ple se lec tion model was in cluded in our anal y ses to cor rect for the sam plese lec tion prob lem in our data, the find ings of the sam ple se lec tion model arenot dis cussed.

OLS re gres sion anal y sis. Ta ble 4 pres ents the re sults of the OLS re gres sionanal y sis, with sam ple se lec tion, of the pro por tion of to tal as sets, net of homeeq uity, that was in vested in the eq uity mar ket. The re sults of Model 1 in di catethat the pro por tion of to tal as sets, net of home eq uity, that the black re spon -dents in vested in the eq uity mar ket was 4.4 per cent age points smaller than thepro por tion that the white re spon dents in vested. Sim i larly, the pro por tion of to -


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TABLE 3. Probit Re gres sion Anal y sis of In vesting in Eq uity Mar ket, with Sam -ple Se lec tion

Model 1 Model 2

Vari ables Co ef fi cient S.E. Co ef fi cient S.E.

Probit Model

In ter cept �1.841*** 0.244 �2.354*** 0.293

Age 0.012** 0.004 0.019*** 0.004

Race/Eth nic ity

Black �0.422*** 0.055 �0.510*** 0.069

His panic �0.564*** 0.081 �0.627*** 0.092

(White)

Male 0.092** 0.035 0.038 0.037

Ed u ca tion

High school grad u ate 0.377*** 0.052 0.382*** 0.058

Some col lege 0.601*** 0.057 0.575*** 0.064

Col lege grad u ate 0.900*** 0.057 0.804*** 0.065

(Less than high school)

Health Con di tion

Ex cel lent 0.470*** 0.080 0.396*** 0.086

Very good 0.435*** 0.078 0.386*** 0.085

Good 0.322*** 0.079 0.275** 0.085

Fair 0.172* 0.087 0.144 0.093

(Poor)

Risk Tol er ance

Low �0.071 0.045 �0.083 0.048

Mod er ately low �0.090 0.062 �0.106 0.065

Mod er ately high �0.026 0.064 �0.026 0.067

(High)

In come

(low est quintile) �0.006 0.078

2nd quintile 0.199* 0.084

3rd quintile 0.309*** 0.086

4th quintile 0.538*** 0.089

5th quintile

Sam ple Se lec tion Model

In ter cept �0.336 0.339 �0.313 0.349

Age 0.024*** 0.006 0.024*** 0.006

Race/Eth nic ity

Black �0.567*** 0.052 �0.606*** 0.053

His panic �0.376*** 0.070 �0.419*** 0.070

(White)

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tal as sets, net of home eq uity, that the His panic re spon dents in vested in the eq -uity mar ket was 3.8 per cent age points smaller than the pro por tion that thewhite re spon dents in vested.

Ed u ca tion was pos i tively re lated to the pro por tion of to tal as sets, net ofhome eq uity, that was in vested in the eq uity mar ket. The pro por tion that wasin vested by those with col lege ed u ca tion was 8.2 per cent age points larger thanthe pro por tion that was in vested by those with less than a high school ed u ca -tion. Al though age was also pos i tively re lated to the pro por tion of to tal as sets,net of home eq uity, that was in vested in the eq uity mar ket, since we usedcross-sec tional data, it was not clear whether the age dif fer ence was due to theage ef fect or the co hort ef fect. With re gard to the health vari able, only thosewho were in very good health in vested a sig nif i cantly larger pro por tion of their to tal as sets, net of home eq uity, in the eq uity mar ket than did those who were in


TABLE 3 (con tin ued)

Model 1 Model 2


Male 0.015 0.049 0.035 0.050

Ed u ca tion


Some col lege 0.395*** 0.074 0.444*** 0.076



Mar i tal Sta tus

Widowed �0.577*** 0.054 �0.591*** 0.056

Di vor ced or sep a rated �0.426*** 0.072 �0.436*** 0.074

Never mar ried �0.538*** 0.083 �0.562*** 0.086

(Married)

In come

(low est quintile)

2nd quintile 0 .506*** 0.056 0.550*** 0.059

3rd quintile 0 .860*** 0.070 0.824*** 0.074

4th quintile 0 .889*** 0.075 0.814*** 0.079

5th quintile 1 .141*** 0.102 0.989*** 0.106

Model Fit

Log like li hood �5,166.9 �5,117.1

Wald χ2 466.83*** 397.5***

7,338 7,388

N

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poor health. Risk tol er ance turned out to be a rel a tively weak pre dic tor of thede gree of in vest ment in the eq uity mar ket. Only those with a low level of risktol er ance in vested a sig nif i cantly smaller pro por tion of their to tal as sets, net ofhome eq uity, in the eq uity mar ket than did those with a high level of risk tol er -ance.

Model 2 in Ta ble 4 in cluded the in come vari able as a con trol vari able. Thepro por tion of to tal as sets, net of home eq uity, that was in vested by those in thefifth quintile (high est) was 5.2 per cent age points larger than the pro por tion that was in vested by those in the low est quintile. Sim i larly, there was a 3.4 per cent -age-point dif fer ence in the pro por tion of to tal as sets, net of home eq uity, thatwas in vested in the eq uity mar ket by those in the fourth quintile ver sus those inthe low est quintile.

Note that af ter con trol ling for in come, the ra cial and eth nic dif fer ences inthe pro por tion of as sets that was in vested in the eq uity mar ket be came evenlarger. The in clu sion of the in come vari able did not al ter the di rec tion or thesig nif i cance lev els of other con trol vari ables.

Ta ble 4 also shows the co ef fi cients of the sam ple se lec tion model. Again,since the sam ple se lec tion model was in cluded in our anal y ses to cor rect forthe sam ple se lec tion prob lem in our data, the find ings of the sam ple se lec tionmodel are not dis cussed.

CONCLUSIONS AND POLICY IMPLICATIONS

The ma jor find ings of this study are that (1) even af ter age, mar i tal sta tus,gen der, ed u ca tion, health con di tion, in come, and risk tol er ance are con trolledfor, the like li hood of blacks and His pan ics in vest ing their fi nan cial re sourcesin the eq uity mar ket is sig nif i cantly smaller than the like li hood of whites do ing so and (2) the pro por tion of such as sets that is in vested in the eq uity mar ket issig nif i cantly smaller among blacks and His pan ics than among whites.

Be yond what was ex plained by our study, what else can ac count for theenor mous dif fer ences in the in vest ment be hav ior of whites ver sus blacks andHis pan ics? Law rence (1991) hy poth e sized that the de gree of time pref er encein fa vor of im me di ate con sump tion is higher for socioeconomicaly de privedgroups (peo ple with low in comes and those with low ed u ca tional achieve-ment) and that the time pref er ence may have a cul tural com po nent, im ply ingthat cer tain eth nic and ra cial groups may have a high level of time pref er encein fa vor of im me di ate con sump tion. The sec ond com po nent of this hy poth e sissug gests that black and His panic peo ple may have a dif fer ent time pref er encethan do white peo ple, the di rec tion of which is not clear in the ab sence of em -pir i cal stud ies. Also, the hy poth e sis, de vel oped by Shefrin and Tha ler (1988),


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TABLE 4. OLS Re gres sion Anal y sis of the Por tion of As sets In vested in theEq uity Mar ket, with Sam ple Se lec tion

Model 1 Model 2


OLS Re gres sion Model

In ter cept �7.898* 3.323 �13.174*** 3.426

Age 0.197** 0.062 0.254*** 0.058

Race/Ethnicity

Black �4.382*** 0.806 �5.146*** 0.828

His panic �3.830*** 0.838 �4.044*** 0.887

(White)

Male 1.016 0.647 0.681 0.607

Ed u ca tion


Some col lege 6.218*** 1.107 5.812*** 1.053



Health Condition

Ex cel lent 1.408 0.849 0.663 0.860

Very good 2.694*** 0.725 2.225** 0.762

Good 1.563 0.820 1.176 0.811

Fair 2.273 1.259 2.094 1.208

(Poor)

Risk Tolerance

Low �1.467* 0.729 �1.492* 0.720

Mod er ately low �1.562 0.925 �1.580 0.922

Mod er ately high �2.410 1.400 �2.390 1.392

(High)

In come

(low est quintile) 0.577 0.874

2nd quintile 1.868 1.405

3rd quintile 3.421** 1.133

4th quintile 5.197** 1.721

5th quintile

Sam ple Se lec tion Model

In ter cept �0.379 0.351 �0.398 0.352

Age 0.025*** 0.006 0.026*** 0.006

Race/Eth nic ity

Black �0.617*** 0.052 �0.621*** 0.052

His panic �0.435*** 0.070 �0.439*** 0.070

(White)

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sug gests that one’s in vest ment pat tern is af fected by the types of in come onehas; for ex am ple, ir reg u lar and un ex pected in come, such as in her i tance, bo -nuses, prizes, stock op tions, is more likely to be in vested in the eq uity mar ketthan is in come earned through work. It is pos si ble that black and His panic peo -ple re ceive less in come from such ir reg u lar and un ex pected sources than dowhites and thus are less likely to in vest their in come in the eq uity mar ket.More over, there may be in sti tu tional bar ri ers against mi nor ity groups that dis -cour age these groups from in vest ing in the eq uity mar ket. All these ex pla na -tions are spec u la tive and hence need to be tested in fu ture em pir i cal re search.

For now, how ever, the find ings from this study have pro found im pli ca tionsfor pol icy. The smaller like li hood of blacks and His pan ics in vest ing in the eq -uity mar ket means that these mi nor ity groups have much less ex pe ri ence in -vest ing in the eq uity mar ket. That these groups place a smaller pro por tion oftheir as sets in the eq uity mar ket means that they have lower rates of re turn ontheir in vest ments than do whites. These ten den cies among these mi nor ity


TABLE 4 (con tin ued)

Model 1 Model 2


Male 0.036 0.051 0.041 0.051

Ed u ca tion


Some col lege 0.425*** 0.077 0.423*** 0.077



Mar i tal Sta tus

Widowed �0.570*** 0.057 �0.569*** 0.057

Di vor ced or sep a rated �0.430*** 0.076 �0.430*** 0.077

Never mar ried �0.572*** 0.088 �0.578*** 0.088

(Married)

In come

(low est quintile)

2nd quintile 0.556*** 0.059 0.558*** 0.059

3rd quintile 0.805*** 0.073 0.806*** 0.073

4th quintile 0.826*** 0.080 0.814*** 0.081

5th quintile 1.031*** 0.110 1.020*** 0.110

Model Fit

Log like li hood �32,408.2 �32,395.7

Wald χ2 297.54*** 327.14***

N 7,388 7,388

*p < .05; **p < .01; ***p < .001.

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groups would make them less ef fi cient than whites in max i miz ing their rate ofre turn. Be cause the PSA plan in tro duces a de fined-con tri bu tion pro gram, un -der which the level of re tire ment ben e fits would be di rectly re lated to the in -vest ment be hav ior of in di vid u als, black and His panic re tir ees would re ceivedis pro por tion ately smaller ben e fits from the de fined con tri bu tion pro gram.

Fur ther more, their in vest ment pat tern makes it dif fi cult for blacks and His -pan ics to nav i gate and ne go ti ate the com plex sys tem of se cu rity mar kets. First, small-lot in vest ments tend to in cur larger trans ac tion fees per share. Sec ond,large, rep u ta ble se cu rity firms dif fer en ti ate the ways they treat their cus tom ers. Some se cu rity firms cat e go rize their cli ents ac cord ing to the amount of moneyin vested through these firms and pro vide ser vices ac cord ingly. So-called Pri -or ity Cli ents re ceive, pe ri od i cally and at other times of alert, de tailed,up-to-date di ag no ses and prog no ses of par tic u lar stocks that are known to be of in ter est of them, while other cli ents do not.

Even if blacks and His pan ics han dle their in vest ments through Internete-trans ac tions, which in cur rel a tively low fees, their lack of ex pe ri ence in in -vest ing in the eq uity mar ket would be to their dis ad van tage. In vest ment with -out much knowl edge about the in tri cacy of stock mar kets of ten re sults indi sas trous in vest ment out comes.

Be cause these groups re ceive con sid er ably lower wages than do whites(U.S. Bu reau of the Cen sus, 1998, p. 436), 5% of the tax able pay roll that theyput into their in di vid ual re tire ment ac counts, ac cord ing to the PSA plan, would be small in ab so lute terms. With this in mind, sup pose that blacks and His pan -ics have the same like li hood of in vest ing in the eq uity mar ket as do whites, that they al lo cate the same pro por tion of their fi nan cial re sources to the eq uity mar -ket, and that their eq uity in vest ment yields the same rate of re turn. Even un derthe best cir cum stances as sumed here, a vi tal pol icy ques tion re mains: Wouldthe pro por tion ately same re turn be a good enough per for mance for blacks andHis pan ics from the so cial pol icy point of view?

Un der the cur rent So cial Se cu rity pro gram, black and His panic re tir ees areen ti tled to Old-Age In sur ance ben e fits that rep re sent a larger pro por tion oftheir life time av er age earn ings than do white re tir ees be cause these mi nor itygroups, on av er age, re ceived lower wages while they worked. Un der the pro -posed PSA plan, be yond the flat pay ment of $410 a month (as sum ing that theyworked 35 years un der cov ered em ploy ment; oth er wise, the flat-amountwould be lower), the re tire ment in come that the work ers could ex pect from thepri vat ized part of So cial Se cu rity would de pend en tirely on their in vest mentbe hav ior. Thus, the cen tral ques tion is this: Would these mi nor ity groups farebetter un der the cur rent sys tem or un der the pro posed PSA plan? It is hard totell.


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Un der the cur rent sys tem, black and His panic ben e fi cia ries in deed re -ceive monthly ben e fits that are a larger pro por tion of their life time av er agemonthly earn ings, as is clearly in di cated by the pro gres sive ben e fit for mulaused in the sys tem. How ever, when one looks at the re la tion ship be tweenlife time con tri bu tions and life time ben e fits, black ben e fi cia ries find lessmoney’s worth in their ben e fits than do white ben e fi cia ries, as a study byOzawa and Kim (in press) found. Un der the PSA plan, the own er ship of theac cu mu lated funds in in di vid u al ized re tire ment ac counts would rest withthe in di vid u als. Thus, the par tic i pants would be free to buy an nu ities withthe ac cu mu lated funds, use the funds as they wished, or leave the un usedfunds for their heirs. This as pect of the PSA plan clearly would ben e fitblack and His panic work ers be cause their life ex pec tancy is shorter thanthat of white work ers.

On the other hand, if the par tic i pants of the PSA fare poorly in their in vest -ments, the free dom to be queath a por tion of their as sets in their ac counts, forex am ple, would be a moot is sue: There sim ply would not be enough money toleave. Fur ther more, poor per for mance in in vest ing their money would re sult in the re ceipt of only $410 a month plus not much more from their in vest ments intheir re tire ment years. For these rea sons, the find ings from this study shouldcom pel pol icy mak ers to pay spe cial at ten tion to the con se quences of adopt inga pri vat ized sys tem of So cial Se cu rity, such as the PSA plan, for black and His -panic peo ple.

How ever, given the im pend ing fi nan cial in sol vency of the So cial Se cu rity pro gram in a few de cades and given the chang ing pub lic at ti tudes to ward par -tial pri vat iza tion of So cial Se cu rity, the par tial pri va tion may be come a re al -ity. If such a move is made, then it be hooves the pol icy mak ers inWash ing ton to make sure that black and His panic work ers are fully pre paredfor in vest ing part of their So cial Se cu rity taxes in the eq uity mar ket. Manyamong the mi nor ity groups need to learn the de grees of risks in volved in in -vest ing in the eq uity mar ket, the dif fer en tial rates of re turn, the types of in -vest ment ve hi cles avail able, and the dif fer en tial trans ac tion costs in volved in buy ing and sell ing stocks and mu tual funds. Some forms of na tion-widetrain ing pro grams re gard ing the me chan ics of in vest ing money in the eq uitymar ket may be called for. Fur ther more, cer tain safe guards should be de vel -oped against fraud u lent and dis crim i na tory busi ness prac tices by se cu rityfirms that han dle the trans ac tions of stocks and stock mu tual funds on be halfof low-wage work ers in gen eral, and black and His panic low-wage work ersin par tic u lar.


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RECEIVED: Jan u ary 27, 2000REVISED: Oc to ber 20, 2000

ACCEPTED: No vem ber 1, 2000


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taking risks in investing in the equity market

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