The Economic Value of Medical Research

The Economic Value of Medical Research Kevin M. Murphy Rober Topel Universiy of Chicago Universiy of Chicago March 1998 Revised Sepember, 1999 Absrac Basic research is a public good, for which social reurns may grealy exceed privae ones. This paper develops an economic framework for evaluaing he social benefis of medical research. We begin wih a model of he economic value of healh and life expecancy, which we apply o US daa on overall and disease-specific moraliy raes. We calculae i) he social value of increased longeviy ha ook place from 1970 o 1990 and, ii) he social value of poenial fuure progress agains various major caegories of disease. The hisorical gains from increased longeviy have been enormous, on he order of $2.8 rillion annually from 1970 o 1990. The reducion in moraliy from hear disease alone has increased he value of life by abou $1.5 rillion per year over he 1970 o 1990 period. The poenial gains from fuure innovaions in healh care are also exremely large. Eliminaing deahs from hear disease would generae approximaely $48 rillion in economic value while a cure for cancer would be worh $47 rillion. Even a modes 1 percen reducion in cancer moraliy would be worh abou $500 billion. Unless coss of reamen rise dramaically wih he applicaion of new medical knowledge, hese esimaes indicae ha he social reurns o invesmen in new medical knowledge are enormous. We acknowledge suppor from he Lasker Chariable Trus, he Milken Insiue, and he Bradley Foundaion. An earlier version was presened as he Thompson Lecure o he Midwes Economic Associaion, and in workshops a he World Bank, he Universiy of Chicago, Boson Universiy, and MIT. 1

I. Inroducion The Unied Saes invess over $35 billion annually in medical research. Federal suppor accouns for abou 38 percen of his oal, and privae indusry abou half; he res comes from various public and privae sources. Federal suppor of medical research has also grown subsanially: beween 1986 and 1995 real federal expendiures on medical research increased by 46 percen, reaching $13.4 billion annually. 1 This is more han onefifh of federal oulays on research and developmen. As hese figures indicae, he US invess subsanial public and privae resources in mainaining and improving he healh of is populaion. 2 Are hese expendiures warraned? Do we inves enough? The answers are non-rivial because medical knowledge, once produced, is a public good whose benefis can be enjoyed by all. Ye even wih he subsanial public expendiures indicaed above, he social benefis from greaer invesmen in medical knowledge may far ousrip coss, so ha curren invesmen is oo low. Wheher in fac i is oo low is he empirical issue ha we ake up. This paper begins an analysis of he social reurns o healh relaed research. We begin by addressing a broader quesion: Wha is he economic value of improvemens in healh and life expecancy? Armed wih a suiable economic framework for his problem, we are able o esimae he economic value of he changes in life expecancy observed over he pas several decades. Our resuls imply ha he economic value of hese gains has been enormous. We esimae ha improvemens in life expecancy alone added approximaely 1 Over he same period, real per-capia annual spending on healh care roughly doubled, from $1,360 per person in 1980 o $2771 in 1995. Healh care spending also increased as a share of oal spending; oal spending on healh care accouned for abou 16% of personal consumpion expendiures in 1995 versus 10% in 1980 and only 8% in 1970. 2 Comparison o oher OECD 2

$2.8 rillion per year in consan 1992 dollars) o naional wealh beween 1970 and 1990. For comparison, real GDP for 1980 he midpoin of he period) was abou $4.6 rillion, so he flow of uncouned addiions o naional wealh due o rising longeviy was more han half of measured GDP in a ypical year. While some of he growh in life expecancy is due o facors oher han improvemens in healh care or medical knowledge, narrowly defined, he magniudes of overall gains sugges ha he conribuions of improved healh care and medical knowledge are similarly large. Indeed, we esimae ha more han half of he $2.8 rillion annual value of increasing longeviy can be aribued o declining moraliy from hear disease, for which medical advances are known o be significan see Culer & Richardson 1997). More imporan han hese hisorical gains, our analysis also demonsraes ha he prospecive value of furher improvemens in healh care is large. For example, we esimae ha curing hear disease would generae abou $48 rillion in economic value while eliminaing deahs from cancer would be worh $47 rillion. One migh argue ha such dramaic improvemens in healh are no on he immediae horizon. Ye our calculaions mean ha even a 1 percen permanen reducion in moraliy from cancer would be worh abou $500 billion. To pu his value in perspecive, consider a federal commimen of an addiional $100 billion for cancer research o be spen, say, over he nex 10 years. Such a program enails a 75 percen increase in federal expendiures on medical research, wih all of he increase devoed o a single disease. Our esimaes imply ha he program would be worhwhile if i had only a one-in-five chance of producing a 1 percen reducion in cancer moraliy, and a four-in-five chance of producing nohing. 3

The economic gains from increasing life expecancy are rising over ime. We show ha he economic reurn o improvemens in healh are greaer: a) he larger is he populaion, b) he higher are average lifeime incomes, c) he greaer is he exising level of healh and d) he closer are he ages of he populaion o he age of onse of disease. These facors poin o a rising value of healh improvemens over he pas several decades and ino he fuure. As he U.S. populaion grows, as lifeime incomes grow, as healh levels improve and as he baby-boom generaion ages oward he primary ages of diseaserelaed deah, he economic reward o improvemens in healh will coninue o increase. We find ha he growh and aging of he populaion alone will raise he economic reurns o advances agains many diseases by almos 50% beween 1990 and 2030. Projeced increases in real incomes and life expecancy will add a leas ha much again Our analysis highlighs some of he ineresing economic issues surrounding he valuaion of improvemens in healh, healh research and he growh in healh expendiures. Many of hese issues have significan policy implicaions. For example, he annuiizaion of many public and privae reiremen benefis Social Securiy, privae pensions, Medicare and privae medical coverage) and he prevalence of hird pary payers increase he incenive o spend on medical care. These disorions also skew invesmens in research away from cos-decreasing improvemens in echnology. In he presence of such disorions, we mus ake accoun of he induced effec ha research has on expendiures when evaluaing he social reurns o improvemens in echnology. Our mehodology does his. We also show ha improvemens in healh are complimenary wih one anoher for example, improvemens in life expecancy from any source) increase he economic value of furher improvemens by raising he value of remaining life. This means ha advances 4

agains one disease, say hear disease, raise he economic value of progress agains oher diseases, such as cancer. This is of significan empirical relevance, as i implies ha he well-documened hisorical progress agains hear disease, for which moraliy has fallen by roughly 30 percen since 1970, has increased he economic reurns o research on cancer and oher diseases. While our resuls srongly sugges ha he economic reurn o medical research is high, we do no assign numerical values o he changes in longeviy and healh ha are due o research advances. So some of he paper is devoed o laying ou a research plan ha can lead o more definiive resuls. The plan divides he problem ino seps. The firs sep is o isolae he impac of improvemens in healh care on healh and life expecancy by disease caegory over ime. These improvemens can hen serve as measures of he oupus of he healh care sysem. The difference beween he growh in healh sysem oupus and healh sysem inpus is a measure of he rae of echnological progress or growh in oal facor produciviy [TFP]. TFP growh can hen be linked o invesmens in medical R&D o deermine he social produc of medical research. This approach is no unique; raher i follows he sandard economic mehodology for esimaing he social value of R&D see Griliches and Lichenberg, 1984). The paper is organized as follows. Secion II oulines our economic model for valuing improvemens in healh and life expecancy. We illusrae how value-of-life esimaes can be applied o he problem a hand. We also develop our mehodology for relaing he increase in life expecancy o improvemens in medical echnology, and idenify he key deerminans of he economic reurn o improved healh. Secion III presens esimaes of he economic gains associaed wih pas improvemens in life expecancy, as 5

well as prospecive esimaes of he value of progress agains several major caegories of disease. Secion IV provides a preliminary evaluaion and analysis of he reurns o medical research while secion V oulines proposals for a more deailed analysis. II. A Framework for Valuing Improvemens o Healh and Longeviy Improvemens in healh and medical knowledge affec he qualiy of life and he risks of moraliy a various sages of he lifecycle. How much are people willing o pay for hese improvemens? We follow Rosen 1988) by assuming ha willingness o pay is deermined by he expeced discouned presen value of lifeime uiliy. 3 Wrie lifeime discouned uiliy for a represenaive individual a age a as 1) U a) = H ) u c ), l )) S, a) d a In 1) H) is healh, so we assume ha improvemens in healh raise insananeous uiliy from consumpion, c), and non-marke ime, l). S,a) is he discouned survivor funcion : 3 Rosen s 1988) seup is similar o ours, bu i does no resul in empirically racable formulae for valuing changes in longeviy. Our equaion 11), below, incorporaes esimaes of he value of nonmarke ime and he value of improvemens o healh while living in assessing he value of medical advances. 6

2) S, a) = exp[ ρ a) λ τ) dτ] a which reflecs boh ime preference ρ) and moraliy risks via he ime-varying insananeous hazard funcion λτ). If ρ = 0 hen S,a) is jus he probabiliy ha he agen survives from age a o. To economize on noaion we do no specify variables ha shif ' he hazard; an obvious facor is healh iself, where we expec τ ) < 0so ha improvemens o healh reduce he per-period probabiliy of dying. Bu i is also reasonable o hink of siuaions where moraliy is changed wihou improvemens in healh, as when λ H safey improvemens reduce he likelihood of indusrial accidens. 4 A a more fundamenal level we expec ha healh and moraliy are deermined by he sock of medical knowledge, he availabiliy of healh care ha applies medical knowledge, public healh infrasrucure, and privae decisions. These are aken up below. Noice from 2) ha any facor ha affecs he insananeous hazard of deah, λτ), affecs he survivor funcion in proporion o he survivor funcion iself. Formally, for any facor θ ha shifs he hazard a paricular ages he impac on S,a) is 3) S, a) θ Sθ, a) = S, a) λ θ τ) dτ a So, a given change in he hazard a some age prior o has a larger impac on he probabiliy S,a) when S,a) iself is large. We reurn o he implicaions of his poin laer. 4 Likewise, medical innovaions can change healh wihou changing moraliy. Orhopedic advances such as hip replacemens and arificial knees are examples. 7

To close he lifecycle problem, we mus specify a budge consrain. We assume a perfec and complee annuiy marke, which means ha a each age a he lifeime expeced discouned value of fuure consumpion mus equal expeced lifeime wealh 4) c ) S, a) d = A a) + y ) S, a) d a a where Aa) is iniial asses a age a and y) is income a age. Equaion 4) is he lifecycle equivalen of a complee marke for consumpion insurance. The individual mus choose an opimal consumpion profile o maximize 1) subjec o 4). Tha is, he individual chooses c) o 5) Max U * a) = H ) u c ), l )) S, a) d + µ [ A a) + { y ) c )} S, a) d ] a a The necessary condiion for opimal consumpion is 6) H ) u c c ), l )) = µ 8

so he ime pahs of opimal consumpion and nonmarke ime equalize he marginal uiliy of consumpion over he remaining lifecycle. Noice ha healh, H), and consumpion of oher goods are naural complemens in our seup. For example, if healh declines a older ages, 6) implies ha consumpion will decline as well. Equaion 5) is our basic building block for hinking abou facors such as medical knowledge ha provide value by exending lives or improving healh. Before urning o hose issues, however, noice ha 5) and 6) provide a dollar figure for he value of a life. Divide 5) by he consan marginal uiliy of consumpion in 6): * U a) u c ), l )) 7) V a) = [ + y ) c ))] S, a) d + A a). µ u a c The erms in brackes of 7) represen he conribuion a age o he dollar value of lifeime uiliy from increasing S,a). This gain consiss of insananeous uiliy uc),l)) plus ne savings ha accrue a age. The laer erm appears because savings a are used o finance consumpion in oher periods, wih marginal uiliy µ. Topel and Welch 1986) refer o he inegrand in 7) as full uiliy : insananeous uiliy from consumpion and leisure, plus he uiliy-equivalen value of ne savings. Noice ha healh, H), does no appear explicily in he value of life formula 7). So, for example, hink of wo socieies, A and B, wih idenical moraliy S,a) and wealh, bu where sociey A has uniformly greaer H). Equaion 7) implies ha he moneary value of a life will be he same in each sociey, so i appears ha healh has no 9

economic value. This occurs because, in our seup, healh raises oal uiliy and he marginal uiliy of consumpion by he same proporional amoun. Pu differenly, he marginal rae of subsiuion beween life or he probabiliy of living) and consumpion does no depend on healh. 5 This does no mean ha healh has no economic value, however; i simply says ha willingness o pay for changes in survival do no depend on he level of healh. Willingness o Pay for Improvemens in Healh or Longeviy To see his more clearly, consider some facor, θ, ha can affec boh he healh of agens and he probabiliy of survival o any age. For purposes of subsequen discussion we will refer o θ as he sock of medical knowledge, which can be augmened hrough invesmens in research. Bu θ could also represen expendiures on public healh or increased availabiliy of medical care. Wih his in mind, he marginal value of changing θ follows from he displacemen of 4): 5 Think of a uiliy funcion for hree goods: 1) healh, H, 2) he probabiliy of surviving a given period of ime, S; and 3) consumpion, c. If uiliy is of he form vh)us,c) hen he marginal rae of subsiuion beween S and c does no depend on H. Neverheless, H is valuable, wih marginal value v H)/u c S,c). 10

8) Vθ a) = u c ), l )) [ u a c + y ) c )] Sθ, a) d + Hθ ) u c ), l ) S, a) d H ) u a c The firs line of 8) is he dollar value of he gain in lifeime expeced uiliy from changes in moraliy, indexed by changes in he survivor funcion S θ, a) S, a) / θ. These changes in he probabiliy of survival weigh he dollar value of full uiliy uiliy plus ne conribuions o wealh) in each period. The second line of 8) represens he value of changes in healh a each fuure age, H ) H ) / θ, ha raise uiliy holding moraliy θ fixed. Equaion 8) measures changes in he value of life induced by changes in healh and/or moraliy. I is he foundaion for our effors o value he pas and prospecive conribuions of medical research o healh and longeviy. To make headway wih 8), however, we need o add slighly more srucure. The firs erm in 8) highlighs he error in using income alone o value changes in moraliy. The inegrand can be rewrien as u c ), l )) y ) + c ) 1 ' cu c = 1 e y ) + c ), e 11

where e = dlog u/dlog c is he elasiciy of oal uiliy wih respec o consumpion Rosen 1988). Algebraically, e < 1 when he average uiliy of consumpion exceeds marginal uiliy, yielding a consumer s surplus in each period of life. There are wo basic reasons for e < 1. Firs is he value of nonmarke ime, or leisure, l). Suppose ha uiliy is linear in c) and l), say u c c) + u l l), so here is perfec u l ineremporal subsiuion in consumpion and leisure. Then e = c ) / c ) + l ) is he u expendiure share of c). This share is smaller han uniy so long as nonmarke ime is valued u l /u c > 0). c The second reason for e < 1 is ha levels of consumpion in differen periods may no be perfec subsiues because average and marginal uiliies of consumpion are no he same. For example, le uiliy ake he power funcion form uc, l) = c e, so ha leisure has no value. Here 1 e is he coefficien of relaive risk aversion, c u c) / u c), wih e < 1 when uiliy is concave. Then he iming of consumpion maers in addiion o income because he opimal consumpion program equaes marginal uiliies a all ages. We incorporae boh of hese effecs in an empirically racable specificaion of insananeous uiliy. We assume ha uc), l)) is homogeneous of degree r, so ha 1 9) u c ), l )) = [ u c c ) + u l l )] r 12

13 We can hink of 1 r as an index of concaviy in insananeous uiliy. Using 9), he inegrand in he firs line of 8) becomes ) ) ) ) )] ) [ 1 ) ) )) ), 10) F c F y c y l u c u l c r c y u c l c u Φ + = + + = + where Φ = 1-r)/r and ) ) ) 11) ) ) ) l u c u l c F c l u c u l y F y + = + = The expressions in 11) represen he full values of income y F ) and consumpion c F ), boh of which include he shadow value of non-marke ime consumed a age. Using hese relaions and 3) yields he following expression for he change in he value of a life induced by dθ: d a S a a F c H H d a d a S F c F y a V ), ) ) ) ) 1 ] ) )[, )] ) [ ) 12) +Φ + Φ + = θ τ τ λ θ θ

Implicaions for Valuing Healh and Longeviy Equaion 12) has a number of imporan implicaions for valuing changes in longeviy and healh. 1. The value of increased longeviy S θ, a) ) and healh H θ ) ) are proporional o he levels of full income and full consumpion, so willingness o pay rises wih wealh. In a populaion, his means ha wealhier people place greaer value on addiional life years, which we expec will be refleced in behavior. For example, our model predics ha wealhy individuals are less likely o smoke, and ha hey were more likely o qui smoking when he healh consequences became well known. These predicions are consisen wih paerns of smoking in he U.S. 6 2. Full income and full consumpion include he value of non-marke ime. Value of life calculaions ha focus solely on earned income will herefore undersae willingness o pay for addiional life years. This is paricularly imporan in our analysis, where improvemens in healh and longeviy may be concenraed a older, ypically posreiremen, ages, when income is small. Then non-marke ime may be he mos imporan deerminan of willingness o pay. 3. The values of improvemens in healh and longeviy increase wih Φ. When Φ = 0 here is perfec ineremporal subsiuion in consumpion or leisure) agens don care when hey consume so here is no gain o reallocaing consumpion over ime. Wih concave uiliy and fixed wealh, however, an increase in he survivor probabiliy in any period yields a uiliy surplus: he expeced uiliy of addiional consumpion and leisure, 14

uc,l), exceeds he opporuniy cos of foregone consumpion from oher periods, µc. Then empirical applicaion of he firs erms in 12) requires knowledge of boh he ime pahs of income and consumpion, as well as knowledge of ineremporal subsiuion indexed by Φ, which deermines he premium for consumpion smoohing. We reurn o his poin below. 4. Because fuure life years are discouned due boh o posiive ineres and moraliy he value of progress agains a disease is greaer he closer is curren age, a, o he onse of he disease. For example, progress agains Alzheimer s disease which srikes older people is of greaer value o a 60 year-old han o a 25 year-old, for whom he disease is a disan possibiliy. 5. Reducions in moraliy from any disease are more valuable he greaer is S,a), he probabiliy of surviving o age. This means ha advances agains disinc diseases say hear disease and Alzheimer s are complemenary: A reducion in moraliy from hear disease raises he value of advances agains Alzheimer s because people are more likely o survive o old age. I also means ha reducions in he hazard from a paricular disease are more valuable in a sociey wih greaer longeviy. Progress agains Alzheimer s is of lile value in Guinea Bissau because relaively few of is ciizens reach old age, bu i may be of grea value in advanced counries where expeced lifeimes are longer. To his poin our discussion has focused on he value of changed healh or longeviy a he individual level. The public good naure of medical knowledge and many oher 6 See Naional Cener for Healh Saisics, Naional Healh Inerview Survey, 1998, Table 63.h 15

facors ha fi he rubric of 12)) implies ha he gains in 12) will be realized by many. Formallyl, o calculae he social value of an increase in medical knowledge, we mus aggregae over he curren and expeced fuure populaions ha benefi from such a change. Assume ha 12) represens willingness o pay for a represenaive agen of age a. Then he marginal social value of a change in medical knowledge is a 13) W θ τ ) = N a, τ ) Vθ a) + N * τ ) V θ 0). a= 0 In 13), Na,τ) is he populaion of age a a dae τ and N*τ) is he presen discouned value of he number of birhs in fuure years. Equaion 13) provides wo addiional implicaions for valuing changes in longeviy and healh: 6. The social value of an increase in life expecancy or healh is proporional o he size of he populaion. 7. The social value of an increase in life expecancy or healh is greaer when he age disribuion of he populaion is concenraed around bu before) he ages where he greaes reducions in deah raes, or increases in healh, occur. These implicaions are useful for gauging he value of changed moraliy and healh in he Unied Saes. Over ime he US populaion is aging, moraliy from various diseases coninues o decline, he populaion is growing, and income levels are rising. Each of hese facors implies ha he social value of improvemens o healh and longeviy is higher han 16

in he pas, and is likely o grow over he nex several decades. All else equal, hese facs indicae ha opimal expendiures on healh-relaed research are increasing over ime. Calibraing he Model: The Value of a Life-year Equaion 12) conains wo erms, one dealing wih changes in moraliy S θ ) ) and he oher wih changes in healh H θ ) ). The remaining discussion will focus on changes in moraliy, which is easier o measure; we reurn o he problem of measuring changes in healh below. To value changes in moraliy using 12), we need informaion on he erms y F ), c F ), and Φ, along wih esimaes of he changes in survivor raes across ages. Survivorship daa can be obained from published moraliy ables, broken down by various caegories such as age, race, and sex. Reasonable esimaes of lifecycle paerns of income and consumpion can be garnered from survey daa, bu Φ is a srucural parameer ha mus be esimaed from compensaion for observable risks. Our sraegy for esimaing Φ relies on esimaes of he value of a saisical life aken from he lieraure on compensaing wage differences for risks of job-relaed deah see Viscusi [1993] for a survey or Thaler and Rosen [1975] for an original analysis). Briefly, he value of a saisical life is derived from regression esimaes of he wage premium ha workers would demand in order o bear a, say, 1 in 10,000 greaer annual probabiliy of deah from job-relaed causes. Suppose his premium is $500 per worker per year. In a populaion of 10,000 workers his change in risk 17

would raise expeced deahs by 1 each year, wih an aggregae value of $500 10,000 = $5 million. Thus he value of one saisical life in his is example is $5 million. To calibrae he concepual experimen in erms of our lifecycle model, suppose ha workers make career choices of an occupaion a ime zero say, age 20), afer which here is no mobiliy among occupaions. Differen occupaions involve differen risks of job-relaed deah, as indexed by he insananeous hazard funcion λ). Oher hings equal, differences in moraliy risks across occupaions are he observable analogue of raising he moraliy hazard by dλ > 0 a each insan of a career from ime 0 o he reiremen dae T. The value of a saisical life is he uniform increase in labor income dy ha compensaes for his increase in risk, resuling in dv = 0. Solving he displacemen of 7), he value of a saisical life is 14) dy dλ = [ y F ) + Φc F )] S λ ) d 0 T S ) d 0 The empirical lieraure ha sudies radeoffs beween income and job-relaed moraliy yields a reasonable range of values for dy/ dλ of $3 million o $7 million per saisical life Viscusi, 1993). Suppose we sele on he midpoin of his inerval, $5 million, as our value in 14) for a represenaive individual. Then knowledge of he ime pahs of i) full income, ii) full consumpion, and iii) moraliy raes by age allow us o esimae Φ. Given his esimae, say Φˆ, we can reurn o 12) o esimae he change in he value of a life for facors ha change he survivor funcion in any specific way. Focusing 18

only on he value of changed moraliy ha is, neglecing he value of changes in healh) we obain: 15) V = [ F ) + Φˆ F θ y c )] Sθ ) d 0 Equaion 15) is he basis for our esimaes of he value if increased longeviy in he Unied Saes over he pas several decades. The brackeed erm is he value received a age per uni change in he probabiliy of survival o ha age. I consiss of full income plus a premium ha is proporional o full consumpion a ha age. Figure 1 illusraes he values of life by age for men and women based on a $5,000,000 value of a saisical life. For his calculaion, he lifecycle profile of y F ) plus he surplus on c F ) is assumed o be proporional o a represenaive earnings profile for men from age 20 o 65. We use he value of he profile a age 20 for all years from birh o age 20. We also assume ha he value of a life year declines a a rae of 5% per year afer age 65. While somewha ad hoc, his profile illusraes he main forces ha deermine he economic value of remaining life a differen ages. III. Esimaing he Value of Acual and Poenial Improvemens in Healh The resuls in Secion II have imporan implicaions for he valuaion of boh hisorical and prospecive fuure improvemens in life expecancy. To illusrae, we firs apply he model o changes in moraliy due o hear disease. 19

The effecs of discouning are illusraed in Figures 2 and 3. Figure 2 shows he reducion in he deah rae from hear disease by age caegory measured by he change in annual deahs per 100,000 individuals in he populaion group). The reducion in deah raes is concenraed a ages 55+ for men and 65+ for women. Figure 3 uses our framework o calculae he change in he value of life caused by hese reducions in moraliy. The value of he reducion in hear disease peaks for men a abou age 50 jus prior o he major reducions is deah raes for men) and for women a abou age 65 jus prior o he major reducion in deah raes for women). The peak a older ages for boh sexes reflecs he fac ha hear disease deahs are concenraed a older ages. The difference in iming beween men and women reflecs he fac ha deahs from hear disease ypically occurred a somewha younger ages for men han for women. The model aribues greaer value o reducions in male hear disease because of he greaer absolue reducion in deah raes from hear disease among men, as shown in Figure 2. Our model indicaes ha increases in life expecancy are worh more when survival raes are higher. This is in perhaps our mos ineresing resul and has many implicaions. I accouns for he relaively low value placed on even large reducions in deah raes a very old ages. A old ages he expeced remaining lengh of life is so low ha marginal increases in life have relaively low value. This can be seen by comparing Figures 2 and 3; he greaes reducions in deah raes occurs in he wo oldes age groups while he greaes increase in value of life occurs a significanly younger ages. This resul also implies ha improvemens in life expecancy are complemenary; progress agains one disease raises life expecancy and herefore increases he value of furher improvemens in survival raes. For example, he reducion in deah raes from hear disease shown in Figure 2 has served o 20

increase he reurn o reducing deah raes from cancer and oher diseases prevalen lae in life. We generalize his analysis by addressing a broad quesion: Wha is he economic value of he increase in life expecancy ha occurred beween 1970 and 1990, wihou regard o he sources of he increase? To make hese compuaions we use published daa on deah raes from all causes by age for 1970, 1980 and 1990 ogeher wih he reference profile for he economic value of life years by age shown in Figure 1. We firs compare he value of life by age for he 1980 populaion, using 1980 survival raes, wih wha he value of life would have been for his populaion had survival raes remained a heir 1970 values. This difference represens he value as of 1980 of he cumulaive improvemens in life expecancy ha occurred beween 1970 and 1980. The resuls are shown in Figure 4 and Table 1. As Figure 4 illusraes, he gains a he individual level are subsanial. Improvemens in life expecancy had a peak value of abou $170,000 for men beween he ages of 40 o 55 and abou $120,000 for women around age 40. The discreely larger increase in he value of life a age 0 for boh sexes reflecs he value of he reducion in infan moraliy. The figure also shows he corresponding increases in values from 1980 o 1990. We do his in an analogous way by comparing he value of life by age for he 1990 populaion using 1990 survival raes, wih wha he value of life would have been for his populaion had survival raes remained a heir 1980 values. While he gains from 1980 o 1990 are smaller han hose from 1970 o 1980 hey are sill very large in absolue erms, on he order of $130,000 for 50 year old men and $60,000 for 50 year old women. 21

Table 1 aggregaes he individual values in Figure 4 o deermine he social value of he improvemens in life expecancy ha occurred beween 1970 and 1990 using equaion 13)). The op half of Table 1 gives he disribuions of he populaion across age groups and gender for 1980 and 1990 and he corresponding average increases in he value of life by age group and gender. We calculae he changes in value for hree ime periods, from 1970 o 1980, 1980 o 1990 and he average annual change from 1970 o 1990 using he 1980 populaion disribuion and survival benchmarks). The populaion daa in he firs wo columns are he census populaion disribuions for he indicaed years. The rows labeled Fuure give esimaes of he discouned presen value using a 3% ineres rae) of he number of individuals in fuure cohors aken here o be a perpeuiy a he curren birh rae). The lower panel of Table 1 accumulaes he values across age and gender groups o provide esimaes of he social value of hese increases in life expecancy. These values are ruly enormous: over $36 rillion for he change from 1970 o 1980 and $21 rillion from 1980 o 1990. The annual change, shown in he final column, amouns o abou $2.8 rillion per year for he 1970 o 1990 period. This figure for he economic value of he annual improvemen in life expecancy is more han half of real 1980 GDP $4.6 rillion) and nearly equal o real aggregae consumpion $3.0 rillion) in ha year. In oher words, adding he increased value of life generaed by advances in healh o convenional measures of naional oupu would increase real oupu over his period by a saggering 60%. The improvemens in healh shown in Table 1 resul from many sources in addiion o improvemens in medical knowledge. Examples are improvemens in public healh, changes in lifesyles some of which may hemselves be relaed o increases in medical 22

knowledge), and increased access o healh care. As such, hey do no isolae he conribuion of medical research and he knowledge gained from ha research from he conribuion of hese oher facors. They also do no deduc he economic cos of eiher he underlying medical research or he expansion of per-capia medical expendiures over his same period. Tables 2 and 3 aemp o address hese shorcomings. Table 2 calculaes he economic value of he reducion in he risk of deah from hear disease over he 1970 o 1980 and 1980 o 1990 ime periods boh evaluaed using he 1990 age disribuion). Comparing Table 2 and Table 1 illusraes ha a significan componen of economic gains from he improvemen in healh from 1970 o 1990 are a resul of he subsanial reducion in deahs from hear disease ha ook place over his period. The reducion in hear disease deah raes generaes abou half $1.5 rillion) of he $2.8 rillion annual gain from he improvemens in healh. I is also possible o deal explicily wih he increase in medical expendiures over ime. Allowing for increases in expendiures seems imporan from boh heoreical and empirical perspecives. In heory, idenifying he marginal effec of knowledge requires us o conrol for changes in oher inpus. This may be imporan since many echnical advances also increase opimal expendiures. Empirically, we know ha medical expendiures expanded enormously from 1970 o 1990. So i is necessary o conrol for expendiure growh wheher hese increases are causally relaed o he growh in knowledge or no. If we allow expendiures o change wih he level of knowledge hen he marginal value of a change in knowledge will be 23

16) ~ V θ a) = e = a ρ a) F F S, a) + S, a) Z ) y + Φ c ) S, a) Z d. θ Z θ θ Where Z θ represens he increase in healh expendiures in response o an increase in medical knowledge i.e. Z θ = dz/dθ). The firs erm in brackes represens he oal increase in he fuure value of life generaed by boh he increase in knowledge and he increase in expendiures. The second erm represens he change in he discouned value of fuure healh expendiures. Equaion 16) implies ha we can measure echnical improvemen including he impac of changes in medical knowledge) as a sor of producion residual equal o he increase in he discouned value of he increase in life years less he increase in expendiures. In fac, if healh expendiures are chosen efficienly, hen his expression will reduce o equaion 12) since he ne reurn o he marginal increase in Z will be zero. Indeed, equaion 16) will measure he ne conribuion of healh knowledge regardless of he source of he growh in healh expendiures as long as healh expendiures are chosen efficienly on he margin. We discuss he case where healh expendiure choices are disored below. The improvemens in healh ha we measured in Tables 1 and 2 include increases in life expecancy from all sources including healh expendiures). Then 16) implies ha we can conrol for he effecs of increased healh expendiures by subracing he growh in expeced fuure expendiures from observed increase in he value of life. This will isolae he increase in he value of life due o sources oher han he increase in expendiures. Table 24

3 does his by deducing he increase in discouned expendiures from he resuls in Table 2. As he able shows, he growh in remaining lifeime expendiures have been small relaive o he increases in he value of life on he order of 15%). Correcing for he increase in healh expendiures reduces he growh in he value of life from $37 rillion o $34 rillion from 1970 o 1980, from $21 rillion o $16 rillion from 1980 o 1990, and he average annual increase from $2.8 rillion o $2.4 rillion. The resuls in Table 3 imply ha here has been subsanial improvemen indeed he vas majoriy of he oal improvemen) in life expecancy above and beyond wha would be expeced based on he growh in healh expendiures alone. In economic erms, he healh producion secor has experienced rapid raes of echnological improvemen. Even so, i remains o be shown ha his echnical progress is due o medical research. Based on he exremely large numbers in Table 3, if even a small fracion of his improvemen is due o medical research, he economic reurn o ha research could be subsanial. The values in Table 3 may seem unbelievably large. Ye hese esimaes are a direc resul of hree basic facors: 1) he $5,000,000 value of life drawn from economic research on individuals willingness o ake on risk; 2) he magniude of he reducion in deah raes over he 1970-1990 period; and 3) he sheer size of he U.S. populaion, o which increases in he sock of knowledge can be applied. Wih hese parameers, changes in healh which increase life expecancy by 1 discouned life year generae an increase in he value of life of abou $150,000 o $200,000 per person. Wih a populaion of 280 million his would imply a gain of abou $42 o $56 rillion. In order o evaluae he plausibiliy of generaing such significan economic gains from progress agains paricular disease caegories, Table 4 liss he gains o men, women and he 25

populaion as a whole from eliminaing deahs from various caegories of disease. Figures 5 and 6 give he corresponding changes in he value of life a individual ages for men and for women. The numbers are compued using he 1995 disribuion of individuals across age and gender groups and correspond o eliminaing deahs from each specific disease holding age-specific deah raes no deahs) from oher diseases consan. The $47 and $48 rillion dollar numbers for cancer and hear disease are saggering. These esimaes imply ha an innovaion ha reduced overall cancer deah raes by only 1% would be worh almos $500 billion or abou 6% of GDP. Reducing age-specific deah raes from a single caegory of cancer such as breas or digesive cancer by 10% would have a similar value. Reducing he age-specific deah rae from AIDS by 10% would be worh abou $750 billion. To pu hese values in perspecive, we should noe ha oal Federal suppor for healh relaed research in 1995 was abou $13 billion, or abou 1/50 of he gain from a 1% reducion in he overall deah rae from cancer. Even if we offse hese gains by subsanial increases in he cos of he reamens required o implemen poenial new echnologies, he poenial gains would sill be very large recall ha he hisorical increase in expendiures was only abou 1/8 of he oal increase in he value of life and only 1/5 of he increase in he value of life from he reducion in hear disease alone. The resuls in Table 4 sugges ha he poenial economic gains o progress agains he caegories of disease lised in Table 4 are very large indeed. IV. Invesmens in Medical Research Our discussion so far has focused on he social value of pas improvemens in healh and he poenial gains o progress agains various caegories of disease. We now urn our 26

discussion o funding for medical research. Table 5 provides some crude esimaes of he invesmens in medical and aggregae R&D for he US in 1995 and he growh in R&D over he preceding decade. Our esimae of spending on medical research is based on daa from he NIH Exramural Funding Daa, fiscal year 1996 Esimaes of Naional Suppor for Healh R&D). Values for oal R&D and R&D for oher secors are based on he Science and Engineering Indicaors 1998 published by he NSF. As Table 5 makes clear, he invesmen in medical R&D by he US is subsanial, abou $35.8 billion in 1995. Moreover, he level of funding for healh research grew 80.1% in real erms beween 1986 and 1995. In 1995 spending on healh relaed research was equal o 3.5% of oal healh care spending, a percenage similar o he 2.5% of GDP accouned for by spending on aggregae R&D. The growh in funding for medical research of 80.1% from 1986 o 1995 essenially kep pace wih he 64.7% growh in healh care spending over he same period and significanly oupaced he growh in overall GDP of 22.9%. The growh in medical research also oupaced he growh in overall R&D 80.1% versus 14.3%). The bigges conras is for federally funded research, where federal funding for healh relaed research increased by 45.8% in real erms while aggregae federal funding for R&D acually declined by 13.2%. I would appear, based on he numbers in Table 5, ha healh relaed research funding is abou in line wih funding in he economy as a whole on a percen of oupu basis and growh in his funding has roughly kep pace wih he rapid growh in healh care expendiures. Moreover, while he federal governmen s real dollar commimen o R&D in he economy as a whole has declined, is commimen o healh relaed research has increased faser han GDP and almos as rapidly as healh care expendiures. 27

Is he $35.8 spen on healh relaed R&D in 1995 oo high or oo low from a social sandpoin? While a precise answer o his quesion is beyond he scope of our analysis here, we can pu some perspecive on he issue. Firs, he amoun spen on medical research is very small relaive o he growh in he overall value of life figures shown in Tables 1-3. In fac, if we ake he ne annual number of $2.4 rillion per year for he 1970 o 1990 period from Table 3) as a saring poin, and assume ha only 10% of his increase is due o increases in medical knowledge, hen we are lef wih roughly a $240 billion annual gain. Compare his o he $36 billion annual expendiure on medical research for 1995. The esimaes for he value of progress agains specific disease caegories from Table 4 ell a similar sory. Reducing he deah rae from hear disease or cancer by.1% e.g. reducing he deah rae per 100,000 from 100 o 99.9) would be worh abou $50 billion or abou 1.5 imes our annual expendiures on healh research. The lower panel in Table 5 also provides some perspecive on he curren level of funding for healh relaed research. The panel liss R&D expendiures as a percen of ne sales for some of he mos research-inensive indusries. The 10.4% number for he drug indusry is he highes of any indusry. However, he 2.8% share for he healh care secor as a whole ranks significanly behind he 8% shares for office and compuing equipmen, communicaions equipmen, elecronic componens, and specialized insrumens. The acual differences may in fac be somewha larger since he R&D numbers for hese indusries are undersaed he esimaes include only indusry-based research and do no include academic research in relaed underlying disciplines. In conras, he 3.5% share for medical care is closer o he shares for moor vehicles and non-elecrical machinery han i is o he R&D shares of high echnology secors. The ideniy of he secors wih he highes R&D 28

raios provides no real surprises he heavy R&D secors are hose closely linked o basic echnologies: elecronics, opics and bioechnology. The R&D o sales figures in Table 5 sugges wo ypes of comparisons. Firs we can compare he 3.5% figure for he healh care secor as a whole o he figures for he oher indusries lised in he able and he 2.5% figure for he economy as a whole. As we noed above, he secors wih high R&D raios are hose where he links o underlying echnological advances in microelecronics, ec.) are highes. Should we expec he share of R&D for healh care o be closer o hose for high echnology secors or closer o shares of echnologically maure secors such as auomobiles 3.0%) or he economy as a whole 2.5%). Our reacion is ha medicine is an area closely ied o basic research, so is 3.5% R&D share appears surprisingly close o he 2.5% aggregae figure. One of he poenial reasons for he relaively low raio of R&D o sales for healh care and he high dependence on governmen suppored research) compared o high echnology areas is ha in a service based indusry i may be difficul for privae invesors o capure he economic gains on he heir invesmens. For service indusries, echnical advances may come in he form of procedures or echniques ha canno be paened or copyrighed, and so hey do no lend hemselves o providing reurns o he original invesor. The embodimen of ideas ino physical goods creaes an indirec way for innovaors o collec on heir invesmens in ideas. The view is bolsered by he difference beween he 3.5% R&D o sales raio for medical care as a whole and he 10.4% raio for he drug secor. Since drugs are can be paened, hey are no subjec o many of he limiaions characerisic of oher advances in healh knowledge. The reliance on federal funding also mirrors his idea: funding for drug relaed research is for all inens and purposes enirely indusry based 29

while funding for oher areas of medical research is dominaed by federal suppor. While no conclusive, he analysis of indusry R&D o sales raios suggess ha spending on medical research is no high by economy-wide sandards. In fac, i may be low relaive o wha is invesed in oher secors wih srong links o basic echnological advances. I is indeed low relaive o wha is invesed in he drug componen of medical care secor iself. The issue of he divergence beween he social reurn o invesmens in medical knowledge and he incenives for privae invesors is endemic o discussions of R&D. As we have noed, his divergence is severe for innovaions ha canno be embodied in physical goods ha can be paened and sold. We believe ha such disorions are imporan for undersanding he curren configuraion of research funding and for guiding policy o funding medical research. The medical secor is also subjec o several oher disorions ha are imporan for our purposes. The firs and mos widely recognized facor is he prevalence of hird pary payers. Many medical spending decisions are made by individuals who bear only a small porion of he consequen economic coss. While he growh in managed care has alered his o some exen, i seems clear ha hird pary payers will remain a key par of he medical care secor for he foreseeable fuure. The key implicaion of his fac is ha medical spending will end o be higher han under a sysem where individuals bear he coss of heir decisions. This has wo implicaions. Firs, when we evaluae he gains o sociey from medical research, we mus ake accoun of he effec of increased knowledge on medical spending. Since individuals do no bear he coss of medical choices, i is possible ha he induced increase in healh expendiures could offse he direc gains from he medical knowledge. The mos pracical 30

soluion o his problem is o calculae he increased value of improved healh ne of he increase in medical spending as we did in Table 3). This eliminaes he need o separae he conribuions o healh of increases in medical knowledge and he associaed increases in medical spending which may be difficul boh heoreically as well as empirically). Second, if increases in medical knowledge increase or decrease) medical spending, any divergence beween he cos and value of hese expendiures will be accouned for in he calculaions. Thus i would appear ha while imporan, he impac of hird pary payers for evaluaing he reurns o medical research is somehing ha can be deal wih. The effec of hird pary payers also skews he paern of research. Ideally, he search for medical advances would be driven by he poenial ne gains he value of increased healh and life expecancy less he rue coss of he reamens and faciliies needed o implemen hese advances. In he presence of hird pary payers, he weigh placed on he economic coss of reamens will be reduced relaive o he weigh placed on he increased value of life. This will skew innovaions oward owards hose ha are cosincreasing. This is aggravaed by he fac ha cos-increasing innovaions ofen involve new equipmen or drugs ha allow a leas limied abiliy o collec he value produced. Funding crieria for medical research should be conscious of hese incenives, and perhaps lean oward developmen of cos-reducing innovaions. Anoher poenial issue is he annuiizaion of benefis for older individuals. Privae pensions, Social Securiy, privae medical plans, and Medicare all provide annuiized benefis for reired workers. Under such sysems, program benefis are income o older individuals since hey will no be received if he individual dies) and are valued as such. Ye from a social perspecive hey are really ransfers, and should no be included in he 31

valuaion of life-exending innovaions. As Becker and Mulligan 1997) have poined ou, his generaes an excess incenive for individuals o inves in life-preserving aciviies. Empirically, his can be handled in our framework by reducing he esimaed gains o life exension for each specific age by he value of annuiized paymens received a ha age. From a policy sandpoin he prevalence of annuiized paymens leads o over-invesmen in boh reamens and research o increase life expecancy bu no qualiy of life). Our analysis a his sage is oo preliminary o suppor definiive conclusions. Ye i appears ha curren expendiures on medical research are exremely small relaive o boh he economic value of hisorical improvemens in healh and relaive o he poenial gains from even small progress agains major caegories of disease. Moreover, he level of R&D relaive o sales for he healh care secor is surprisingly close o he economy-wide average, and much smaller han for many of he high echnology secors. The R&D inensiy for he medical secor as a whole is also small relaive o he level of R&D inensiy for he drug indusry. This discrepancy may be relaed o he basic naure of much medical research and he inabiliy for individuals o capure a subsanial fracion of he social gains from medical research. We also find ha here are several oher disorions in he medical markeplace, in paricular he prevalence of hird pary insurance and he annuiizaion of old-age benefis. Boh facors disor incenives o expend resources on healh care and so indirecly disor research incenives oward cos increasing life exension. Our analysis suggess ha even afer aking accoun of hese disored incenives he poenial gains o medical advancemen are enormous. The remaining quesion is wheher medical research is able o capialize on his enormous poenial for social gain. Based on our calculaions, even limied progress would easily jusify curren expendiures and mos 32

likely expendiures above curren levels. Bu even wih expendiures fixed a curren levels, our analysis provides a mehod for valuing he relaive gains from progress on alernaive research frons, and helps o idenify hose areas where he curren funding sysem is mos likely o over or under inves. V. Furher Research Our analysis so far has been very preliminary. While we have idenified he enormous magniude of he hisorical and poenial fuure gains o increasing life exension, our analysis has also lef much ou. We have explicily ignored he role of advances in medical knowledge for improving he qualiy and no jus he lengh) of life. We have made no aemp o isolae he impac on life expecancy of advances in medical knowledge specifically, or he oupu of he healh care sysem as a whole, from he influence of oher facors. We have made no aemp o direcly link research and healh oucomes. The daa we have been using are largely preliminary and could almos cerainly be improved in mos dimensions by relying on more deailed, bu publicly available, sources. Finally, he heoreical and analyical framework we have oulined here can be expanded along several dimensions including dealing wih changes in healh as opposed o simply dealing wih longeviy) and allowing for lags in he impacs of medical knowledge and expendiures on healh. Refining he Value of Life Calculaions One area where we can improve he analysis here is in erms of he value of life calculaions. Deailed empirical evidence on he lifecycle paerns of income and consumpion can be used o obain beer esimaes of he relaive values of life a differen sages of he lifecycle. In addiion, a more horough 33

analysis of he lieraure on he valuaion of life would help us validae or sugges modificaions o some of he assumpions ha underlie our empirical model. Life Expecancy Daa Clearly, he life able daa used in his paper play a cenral role in our analysis. Our esimaes are pieced ogeher from readily available sources and involved some significan inerpolaions where only daa by age inervals or ime inervals were easily available. I would be relaively sraighforward o obain more deailed daa for each ime period as well as exend he ime period of our analysis o earlier years. Disease Specific Daa One of he major improvemens o our analysis would be o obain more deailed daa on he incidence of disease, deah raes and life expecancy condiional on disease over ime. Such daa would allow us o beer model he observed reducion in deah raes and aribue hese changes o reduced incidence and reduced deah raes condiional on incidence a specific ages. Daa on expendiures for he reamen of specific diseases over ime would allow us o beer model he relaionship beween expendiures, healh improvemen and he growh in medical knowledge. By looking a disease incidence we should also be able o gain some informaion abou he correlaions of disease risks. The disease specific model presened in his paper implicily assumes ha increased survival from one disease leaves he risks from oher diseases unchanged. However, if he incidence of disease is correlaed across diseases a he individual level his will no be he case. Given ha many individuals ofen suffer from muliple condiions, his cerainly is an issue ha should be addressed. Specific Daa on Healh Research The daa on healh research presened in his paper is exremely crude. I covered only aggregae spending and even hen was incomplee. In order o analyze he impac of research on healh oucomes i is essenial ha 34

we assemble he daa on healh research by disease caegory over ime. Such daa are available and have been analyzed for oher purposes see Lichenberg 1998). Daa on Healh and Qualiy of Life Daa on he qualiy of life by disease classificaion over ime would allow us o exend our analysis beyond life expecancy and include direc healh effecs. Analysis of his ype has been carried ou by Culer and Richardson 1997) in work similar in spiri o our work on he value of hisorical improvemens in healh. Their findings ha improvemens in healh while alive accoun for abou 30% of he increase in he value of life seems o sugges ha incorporaing healh changes is poenially imporan. The framework hey lay ou for analyzing he value of changes in healh i.e. qualiy of life) would be an excellen saring poin for such an analysis. Linking Oucomes o Research All of our proposed research projecs so far have deal wih collecing addiional or more deailed daa. The improved daa will allow us o refine he ypes of calculaions carried ou in our preliminary work. More deailed daa by disease will also allow us o ake he crucial second sep and link he daa on healh oucomes o healh research expendiures. Our basic plan of aack is as follows: The firs sep is o calculae he hisorical and poenial gains o reducions in disease incidence, reducions in he deah raes from disease condiional on incidence and increases in he qualiy of life condiional on disease. The second sep is o calculae changes in healh expendiures condiional on disease. This will allow us o calculae he ne increase in he value of improved 35

healh above and beyond he cos of increased expendiures. The boom line of his second sep will be he ne increase in healh care produciviy by age, disease, and ime period. This ne difference represens he difference beween he increase in he value of oupu and he growh in measured inpus and is analogous o he calculaion of TFP growh in he sandard analysis of indusrial produciviy. The final sep will be o link he produciviy growh by disease and ime period o expendiures on healh research. This is he sage where he exac idenificaion sraegy is difficul o idenify ex-ane and will depend on wha daa are available. The idea will be o look for exogenous variaions in research expendiures ha can be linked o variaions in oucomes. The overall incidence of disease, he availabiliy of specific funding and oher facors may be candidae insrumens. A final decision will have o wai unil he daa are assembled. The Allocaion of Research Dollars - While poenially useful for evaluaing he overall impac of biomedical research, he analysis oulined above may be even more imporan for hinking abou he allocaion of research dollars. The empirical framework laid ou above is ideal for evaluaing he relaive values of poenial progress on alernaive frons. The heoreical model is also useful for idenifying wha areas and ypes of research are likely o be over or under funded based on individual incenives alone. More work on guiding he allocaion of funds would seem o be a naural offshoo of his analysis. Exending he Analyical Framework - As par of implemening he work oulined above we will need o exended he analyical framework oulined in his 36

work o accoun for several facors including he cumulaive naure of he effecs of healh knowledge and healh expendiures on healh and life expecancy. Essenially, his amouns o hinking of healh as a sock variable ha is accumulaed by invesmens where he efficiency of hese invesmens is deermined by healh care and oher consumpion expendiures and he level of healh knowledge. This adds a dynamic elemen above and beyond ha buil ino he model above. Exacly how much can be done on his margin from an empirical perspecive remains o be seen bu i seems like a direcion of research worh pursuing. Dealing wih a correlaed srucure of disease incidence will also require an expanded analyical framework. Finally, a more horough heoreical and empirical analysis of he impac of hird pary payers, he annuiizaion of reiremen benefis, and variaion across reamens in he abiliy o collec reurns on research breakhroughs are all poenial policy offshoos of he analysis oulined above. Clearly, much remains o be done. 37

References Becker, Gary S. and Casey B. Mulligan. The Endogenous Deerminaion of Time Preference. Quarerly Journal of Economics. 1123), Augus 1997: 729-58. Culer, David. Technology, Healh Coss, and he NIH, Unpublished paper prepared for NIH Roundable on Economics, Ocober 19, 1995. Culer, David, and Richardson, Elizabeh. Measuring he Healh of he U.S. Populaion, Brookings Papers: Microeconomics 1997, pp. 217-271. Griliches, Zvi, and Lichenberg, Frank. R&D and Produciviy a he Indusry Level: Is There Sill a Relaionship? in R&D, Paens, and Produciviy, edied by Zvi Griliches. Chicago: Universiy of Chicago Press, 1984. Lichenberg, Frank R. The Allocaion of Publicly-Funded Biomedical Research, Naional Bureau of Economic Research Working Paper No. 6601. Cambridge, MA: NBER, June 1998. Rosen, Sherwin. The Value of Changes in Life Expecancy, Journal of Risk and Uncerainy 1 1988): 285-304. Topel, Rober H., and Finis Welch. Efficien Labor Conracs wih Employmen Risk, Rand Journal of Economics 17 Winer 1986): 490-507. Viscusi, W. Kip. The Value of Risks o Life and Healh, Journal of Economic Lieraure 31 1993): 1912-1946. 38

Table 1. The Economic Value of Increases in Life Expecancy from 1970 o 1980 and 1980 o 1990 by Age Group and Gender Ages Populaion Couns 1000's) Increase in Value of Life$'s) 1980 1990 70 o 80 80 o 90 70 o 90 Males Annual Fuure 55,747 63,993 $121,912 $60,128 $9,115 0 o 4 8,362 9,599 $89,076 $48,151 $6,873 5 o 13 15,923 16,295 $93,440 $51,120 $7,241 14 o 17 8,298 6,857 $107,818 $58,143 $8,313 18 o 24 15,054 13,738 $122,894 $61,362 $9,230 25 o 34 18,382 21,565 $150,683 $75,810 $11,347 35 o 44 12,570 18,511 $171,583 $110,890 $14,152 45 o 54 11,009 12,232 $167,068 $126,061 $14,687 55 o 64 10,152 9,955 $132,838 $102,660 $11,800 65 o 74 6,757 7,907 $78,376 $69,082 $7,388 75 o 84 2,867 3,745 $40,520 $36,076 $3,836 85+ 682 841 $20,298 $18,604 $1,947 Females Fuure 53,240 61,053 $94,595 $41,532 $6,812 0 o 4 7,986 9,158 $67,776 $30,338 $4,911 5 o 13 15,237 15,532 $70,321 $30,821 $5,063 14 o 17 7,950 6,482 $81,969 $35,137 $5,862 18 o 24 14,969 13,212 $93,300 $38,268 $6,586 25 o 34 18,700 21,596 $110,115 $46,375 $7,833 35 o 44 13,065 18,924 $119,027 $56,165 $8,770 45 o 54 11,791 12,824 $114,295 $53,520 $8,401 55 o 64 11,551 11,158 $105,988 $45,143 $7,566 65 o 74 8,824 10,139 $90,422 $42,971 $6,677 75 o 84 4,862 6,267 $63,525 $33,547 $4,856 85+ 1,559 2,180 $33,820 $18,701 $2,623 Toal Values Millions of Dollars) 70 o 80 80 o 90 70 o 90 Annual Males $20,547,654 $13,333,130 $1,619,017 Females $16,042,877 $7,966,696 $1,158,343 Toal $36,590,530 $21,299,826 $2,777,360

Table 2. The Economic Value of he Reducion in Hear Disease from 1970 o 1980 and 1980 o 1990 by Age Group and Gender Ages Increase in Value of Life$'s) 70 o 80 80 o 90 Males Fuure $28,814 $27,874 0 o 4 $30,881 $29,873 5 o 13 $38,216 $36,969 14 o 17 $46,332 $44,820 18 o 24 $54,989 $53,195 25 o 34 $70,823 $69,280 35 o 44 $86,568 $89,228 45 o 54 $90,305 $96,547 55 o 64 $74,225 $83,247 65 o 74 $43,646 $57,699 75 o 84 $13,821 $29,746 85+ -$2,833 $12,012 Females Fuure $15,042 $12,564 0 o 4 $16,093 $13,442 5 o 13 $19,898 $16,619 14 o 17 $24,091 $20,121 18 o 24 $28,457 $23,768 25 o 34 $36,109 $30,687 35 o 44 $44,998 $39,748 45 o 54 $52,191 $46,974 55 o 64 $54,220 $50,507 65 o 74 $43,599 $45,374 75 o 84 $20,576 $27,564 85+ $2,726 $10,342 Toal Values Millions of Dollars) 70 o 80 80 o 90 Males $9,831,282 $10,107,711 Females $5,729,049 $5,138,526 Toal $15,560,332 $15,246,237

Table 3. The Ne Economic Value of Increases in Life Expecancy from 1970 o 1980 and 1980 o 1990 by Age Group and Gender Ages Populaion Couns 1000's) Increase in Value of Life$'s) 1980 1990 70 o 80 80 o 90 70 o 90 Males Annual Fuure 55,747 63,993 $116,618 $50,418 $8,365 0 o 4 8,362 9,599 $83,619 $38,065 $6,096 5 o 13 15,923 16,295 $87,253 $39,680 $6,360 14 o 17 8,298 6,857 $100,813 $45,201 $7,316 18 o 24 15,054 13,738 $114,999 $46,812 $8,108 25 o 34 18,382 21,565 $141,816 $59,490 $10,088 35 o 44 12,570 18,511 $162,636 $94,271 $12,874 45 o 54 11,009 12,232 $158,782 $110,532 $13,496 55 o 64 10,152 9,955 $125,626 $89,084 $10,761 65 o 74 6,757 7,907 $72,795 $58,432 $6,576 75 o 84 2,867 3,745 $36,761 $28,883 $3,289 85+ 682 841 $18,125 $14,405 $1,629 Females Fuure 53,240 61,053 $88,887 $31,132 $6,007 0 o 4 7,986 9,158 $61,873 $19,527 $4,075 5 o 13 15,237 15,532 $63,586 $18,490 $4,109 14 o 17 7,950 6,482 $74,305 $21,128 $4,778 18 o 24 14,969 13,212 $84,668 $22,512 $5,366 25 o 34 18,700 21,596 $100,397 $28,672 $6,462 35 o 44 13,065 18,924 $109,055 $38,038 $7,365 45 o 54 11,791 12,824 $104,755 $36,295 $7,062 55 o 64 11,551 11,158 $97,271 $29,594 $6,352 65 o 74 8,824 10,139 $83,215 $30,212 $5,678 75 o 84 4,862 6,267 $58,469 $24,658 $4,159 85+ 1,559 2,180 $30,977 $13,773 $2,235 Toal Values Millions of Dollars) 70 o 80 80 o 90 70 o 90 Annual $19,441,601 $11,040,528 $1,461,346 $14,781,280 $5,426,623 $980,800 $34,222,882 $16,467,151 $2,442,146

Table 4. The Economic Value of Reducing Deahs from Seleced Caegories of Disease Overall and by Gender Increase in Value of Life$1,000,000's) Disease Caegory Men Women Toal Cancer $24,325,209 $22,211,974 $46,537,183 Breas $25,080 $4,617,170 $4,642,251 Digesive Organs $5,469,042 $4,160,405 $9,629,447 Genial and Urinary Organs$1,810,372 $2,334,439 $4,144,811 Hear $28,636,005 $19,711,577 $48,347,582 Sroke $3,472,990 $4,156,135 $7,629,125 Circulaory Disease $3,085,051 $2,654,387 $5,739,438 Flu. $1,841,048 $1,591,013 $3,432,061 AIDS $6,277,524 $1,262,572 $7,540,097

Table 5. Expendiures on R & D - Bio-medical and Aggregae by Funding Source for 1995 Expendiure % Growh Biomedical R&D Funding $1,000,000's) % of Toal 1985-1995 Federal Governmen $11,407 45.3% 53.8% Indusry - Drug Indusry $10,202 40.5% 108.9% * Academic Research - Non Gov. Funding $3,593 14.3% ****** Toal $25,202 100.0% 75.7% ** Spending on Healh Care $784,200 78.0% Healh R & D as % of Healh Expendiures 3.2% -1.3% Healh R & D as % of GDP 0.3% 38.6% Healh R & D as % of Toal R & D 13.8% 50.3% ** Aggregae R & D Funding Federal $63,147 34.5% -12.1% Indusry $110,998 60.7% 220.1% Oher $8,868 4.8% 68.8% Toal R & D Funding $183,013 100.0% 16.9% GDP $7,253,800 26.7% Toal R & D as % of GDP 2.5% -7.8% R & D as % of Sales Seleced Indusries) Drugs & Medicines 10.4% Office & Compuing Equipmen 8.1% Communicaion Equipmen 8.0% Elecronic Componens 8.0% Opical, Surgical & Phoographic Equipmen 8.0% Scienific Insrumens 6.6% Indusrial Chemicals 4.7% Moor Vehicles 3.0% Non-elecrical Machinery 2.4% * Based on daa for 1986 ** Based on daa for federal and drug indusry only

$7,000,000 Figure 1. Value of Life by Age for 1990 $6,000,000 $5,000,000 Males Females Value $1992) $4,000,000 $3,000,000 $2,000,000 $1,000,000 $0 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 Age 60 64 68 72 76 80 84 88 92 96 100 104 108

Figure 2. Reducions in Hear Disease Deah Raes 1970 o 1990 1600 Reducion in Deah Rae 1/100,000) 1400 1200 1000 800 600 400 Males Females 200 0 25 o 34 35 o 44 45 o 54 55 o 64 65 o 74 75 o 84 85+ Ages

Figure 3. Economic Value of Reducions in Hear Disease Deahs From 1970 o 1990 by Age For Men and Women $200,000 $180,000 $160,000 Men Women $140,000 $120,000 Value$1992) $100,000 $80,000 $60,000 $40,000 $20,000 0 6 12 18 24 30 36 42 48 54 60 66 72 78 84 90 96 $0 AGE 102 108

Increase in Value $1992) $200,000 $180,000 $160,000 $140,000 $120,000 $100,000 $80,000 $60,000 $40,000 Figure 4. Increases in he Value of Life by Age for men and Women1970 o 1980 and 1980 o 1990 Men 70 o 80 Men 80 o 90 Women 70 o 80 Women 80 o 90 $20,000 $0 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88 92 96 100 104 108 AGE

$300,000 Figure 5. Economic Value of Disease Reducion by Age for Men Value $1992) $250,000 $200,000 $150,000 Hear Cancer Sroke Circ. Flu. AIDS $100,000 $50,000 $0 0 5 10 15 20 25 30 35 40 45 50 55 60 Age 65 70 75 80 85 90 95 100 105 110

$250,000 Figure 6. Economic Value of Disease Reducion by Age for Women Value $1992) $200,000 $150,000 $100,000 Hear Cancer Sroke Circ. Flu. AIDS $50,000 0 4 8 12 16 20 24 28 32 36 40 44 48 52 56 60 64 68 72 76 80 84 88 92 96 $0 Age 100 104 108