Amy Finkelstein. April 2006

THE AGGREGATE EFFECTS OF HEALTH INSURANCE: EVIDENCE FROM THE INTRODUCTION OF MEDICARE * Amy Finkelsein April 2006 Absrac: This paper invesigaes he effecs of marke-wide changes in healh insurance by examining he single larges change in healh insurance coverage in American hisory: he inroducion of Medicare in 1965. I esimae ha he impac of Medicare on hospial spending is over six imes larger han wha he evidence from individual-level changes in healh insurance would have prediced. This disproporionaely larger effec may arise if marke-wide changes in demand aler he incenives of hospials o incur he fixed coss of enering he marke or of adoping new pracice syles. I presen some evidence of hese ypes of effecs. A back of he envelope calculaion based on he esimaed impac of Medicare suggess ha he overall spread of healh insurance beween 1950 and 1990 may be able o explain abou half of he increase in real per capia healh spending over his ime period. Key Words: Healh Insurance; Healh Spending; Medicare; Hospials JEL Classificaion Codes: H51, I11, I18 * I am graeful o Daron Acemoglu, Anna Aizer, Timohy Bresnahan, Amiabh Chandra, David Culer, Joseph Doyle, Mark Duggan, Susan Dynarski, Alan Garber, Michael Greensone, Jonahan Gruber, Brian Jacob, Benjamin Jones, Charles Jones, Lawrence Kaz, Melissa Kearney, Emme Keeler, Kaherine Levi, Jeffrey Liebman, Adriana Lleras-Muney, Erzo Lumer, Ellen Meara, Robin McKnigh, Joseph Newhouse, Benjamin Olken, James Poerba, Sarah Reber, Jonahan Skinner, Sco Sern, Melissa Thomasson, Vicor Fuchs, numerous seminar paricipans, and wo anonymous referees for helpful commens, o Mireya Almazan, Prashanh Bobba, Erku Kucukboyaci, Sarah Levin, Mahew Noowidigdo, Sharon Shaffs, and especially Erin Srumpf for ousanding research assisance, and o he NIA (P30-AG12810) and he Harvard Milon Fund for financial suppor.

Over he las half-cenury, he dramaic rise in medical expendiures has been one of he mos salien feaures of he U.S. healh care secor. Toal healh care expendiures in he Unied Saes as a share of GDP have more han ripled, from abou 5 percen in 1960 o abou 16 percen in 2004 [CMS 2004]. Early work by Feldsein [1971, 1977] suggesed ha he spread of healh insurance was a primary cause of he rapid rise in healh spending. Such argumens promped he underaking of he Rand Healh Insurance Experimen, one of he larges randomized, individual-level social experimens ever conduced in he Unied Saes, o invesigae he impac of healh insurance on healh care uilizaion and spending [Manning e al. 1987]. Is findings suggesed ha he responsiveness of healh spending o healh insurance was subsanially smaller han wha Feldsein [1971, 1977] had esimaed, and consequenly, ha he spread of healh insurance was no an imporan cause of he rise in healh spending (Manning e al. [1987], Newhouse e al. [1993], Newhouse [1992]). Today, he resuls of he Rand Experimen are generally acceped as he gold sandard, and are widely used in boh academic and applied conexs (Culer and Zeckhauser [2000], Zweifel and Manning [2000]). This paper revisis his debae and suggess ha he spread of healh insurance may have played a much larger role in he growh of healh spending han he Rand Experimen would sugges. The basic insigh is ha marke-wide changes in healh insurance may have fundamenally differen effecs on he healh care secor han wha parial equilibrium analyses such as he Rand Experimen would sugges. To sudy he impac of marke-wide changes in healh insurance, I examine he impac of he inroducion of Medicare in 1965. Medicare s inroducion consiued he single larges change in healh insurance coverage in American hisory. Medicare is currenly one of he larges healh insurance programs in he world, providing healh insurance o 40 million people and comprising one-eighh of he federal budge and 2 percen of GDP (Naional Cener for Healh Saisics [2002], Newhouse [2002], US Congress [2000]). Ye we know surprisingly lile abou he impac of is inroducion. Indeed, o my knowledge, he only exising evidence comes from a comparison of ime series paerns of healh expendiures before and afer is inroducion [Feldsein and Taylor 1977]. I use he fac ha he elderly in differen regions of he counry had very differen raes of privae 1

healh insurance coverage prior o Medicare o idenify is effec. I sudy he impac of Medicare on he hospial secor. This was he single larges componen of healh spending a he ime of Medicare s inroducion and of he subsequen growh in healh spending. My esimaes sugges ha, in is firs five years, he inroducion of Medicare was associaed wih an increase in spending ha was over six imes larger han wha he esimaes from he Rand Healh Insurance Experimen would have prediced. They also sugges ha he long-erm impac of Medicare may have been even larger han is five-year impac. One reason why he general-equilibrium impac of a marke-wide change in healh insurance may be much larger han wha parial-equilibrium analysis would sugges is ha marke-wide changes in healh insurance can fundamenally aler he naure and characer of medical pracice in ways ha small-scale changes will no. Consisen wih his, I find ha he inroducion of Medicare is associaed wih subsanial new hospial enry. I also find some suggesive evidence ha Medicare s inroducion is associaed wih increased adopion of cardiac echnologies and increased spending on non-medicare paiens; however due o daa limiaions discussed below, hese resuls are necessarily more speculaive in naure han he oher findings of he paper. Exrapolaion from he Rand esimaes of he impac of healh insurance on healh spending suggess ha he overall spread of healh insurance beween 1950 and 1990 can explain only a very small par of he six-fold rise in real per capia healh spending over his period (Manning e al. [1987], Newhouse [1992]). The resuls of he same exercise using my esimaed impac of Medicare sugges ha he spread of healh insurance may be able o explain half of he increase in healh spending over his period. Of course, imporan concerns abou exernal validiy sugges ha he findings of each of hese back of he envelope calculaions should be viewed wih considerable cauion. Noneheless, a a broad level, my findings raise he possibiliy ha he spread of healh insurance and he public policies ha encouraged i may have played a much larger role in he subsanial growh in he healh care secor over he las half cenury han he curren convenional wisdom suggess. A he same, however, my findings are no inconsisen wih he convenional wisdom ha echnological change is he primary cause of he rapid rise in healh expendiures (e.g. Newhouse [1992], Fuchs [1996], and Culer [2003]). The large impac of 2

marke-wide changes in healh insurance on healh spending may sem in par from heir impac on decisions o adop new medical echnologies, as conjecured by Weisbrod [1991]. A complee picure of he impac of an aggregae change in healh insurance requires an undersanding no only of is impac on he healh care secor he subjec of his paper bu also of is benefis o consumers. In relaed work, Finkelsein and McKnigh [2005] explore hese poenial benefis. We find ha while he inroducion of Medicare appears o have had no impac on elderly moraliy in is firs en years, i did subsanially reduce he righ ail of ou of pocke medical spending by he elderly. The res of he paper proceeds as follows. Secion one describe he daa and empirical sraegy. Secion wo presens esimaes of he effec of Medicare on he hospial secor. Secion hree shows ha hese esimaes are subsanially larger han wha exising parial equilibrium esimaes would have prediced; i also presens some evidence in suppor of he likely explanaions. Secion four provides a back of he envelope calculaion for wha he esimaes imply for he conribuion of he spread of healh insurance o he growh of he healh care secor over he las half cenury. The las secion concludes. I. Sudying he impac of Medicare: Approach and Daa I.A. Idenifying he impac of Medicare: geographic variaion in pre-medicare insurance coverage Medicare, enaced July 1 1965 and implemened July 1 1966, provided universal public healh insurance coverage for he elderly. I covered hospial and physician expenses; he services covered and he reimbursemen raes were very generous for he ime (Somers and Somers [1967], Newhouse [2002]). Prior o Medicare, public healh insurance coverage was pracically non exisen, and meaningful privae healh insurance for he elderly was also relaively rare (Sevens and Sevens [1974], Unied Saes Senae [1963], Anderson and Anderson [1967], and Epsein and Murray, [1967]). Based on daa from he 1963 Naional Healh Survey (NHS), I esimae ha in 1963, only 25 percen of he elderly had meaningful (i.e. Blue Cross) privae hospial insurance. 1 Upon he implemenaion of Medicare, hospial insurance coverage for he elderly rose virually insananeously o almos 100 percen [US HEW, 1969]. 1 Mos privae insurance a his ime was exremely minimalis in naure, bu Blue Cross plans had relaively comprehensive coverage (e.g. Anderson e al. [1963], Sevens and Sevens [1974]). For more informaion on he 1963 NHS, see NCHS [1964]. I am exremely graeful o Will Dow for his work unearhing hese daa. 3

The impac of Medicare on elderly insurance coverage varied considerably across he counry. Through a special reques, I obained a version of he 1963 NHS ha idenifies in which of he 11 subregions he individual is locaed. Broadly speaking, insurance coverage for he elderly is higher in he Norh Eas and Norh, and lower in he Souh and Wes. Table I indicaes ha he proporion of he elderly wihou Blue Cross hospial insurance ranged from a low of 49 percen in New England o a high of 88 percen in he Eas Souh Cenral Unied Saes. The available daa sugges ha his geographic paern was quie sable in he years prior o Medicare (see Naional Cener for Healh Saisics [1960]). A key crierion for using geographic variaion in privae insurance coverage for he elderly o idenify he impac of Medicare is ha his insurance was redundan of wha Medicare subsequenly covered. Consisen wih his, Lichenberg [2002] and Finkelsein and McKnigh [2005] presen evidence of a subsanial crowd-ou effec of Medicare s inroducion on privae healh insurance spending. The abiliy o idenify Blue Cross insurance is also paricularly imporan in his regard, as Medicare s benefi and reimbursemen srucure was explicily modeled on he Blues (Anderson e al. [1963], Ball [1995], Epsein and Murray [1967], Newhouse [2002], Sevens and Sevens [1974], and Sevens [1999]). I.B. Daa: The American Hospial Associaion Annual Survey I use 26 years of hospial-level daa from he annual surveys of he American Hospial Associaion (AHA) for every AHA-regisered hospial in he U.S. These daa, which are available in hard-copy in he annual Augus issues of Hospials: The Journal of he American Hospial Associaion, cover he years from 1948 o 1975 (wih he excepion of 1954). The AHA daa from he 1980s and laer have been widely used o sudy he hospial secor (e.g. Baker and Phibbs [2002], Culer and Sheiner [1998]). However, he hisorical daa have been largely ignored. I exclude he approximaely five percen of hospials ha are federally owned, producing a sample of abou 6,500 hospials per year. The analysis ceners on six hospial oucomes: oal expendiures, payroll expendiures, employmen, beds, admissions and paien days. Uilizaion and bed daa are exclusive of newborns. I conver all expendiure variables o 1960 dollars using he CPI-U. Hospial expendiures consis of expendiures on inpus, and do no reflec hospial oupu prices. Employmen and payroll 4

expendiures exclude mos physicians, since hey are no employed direcly by he hospial. Appendix A provides a more deailed descripion of hese variables and of he daa qualiy. Figure I shows he naional ime series paerns for each oucome based on aggregaing he hospiallevel daa o he naional level. Mos oucomes are increasing over he enire sample period. However, beds and paien days began decreasing in he early 1960s as shor-erm hospials ook over many of he funcions previously performed by long-erm hospials, such as reamen of uberculosis paiens [Somers and Somers 1967]; prior o his decline, long-erm hospials consiued above 10 percen of hospials, bu half of beds and paien days. Table II repors mean hospial oucomes prior o Medicare (1962-1964). I shows ha prior o Medicare, average hospial oucomes were consisenly higher in he Norh and NorhEas (where insurance coverage was comparaively high) han in he Souh and Wes (where insurance coverage was comparaively low). This is consisen wih he evidence in he paper of an impac of insurance coverage on hese oucomes, bu may also reflec oher differences across regions. II. The Impac of Medicare on Hospial Uilizaion, Inpus and Spending II.A. Economeric model The empirical sraegy is o compare changes in oucomes in regions of he counry where Medicare had a larger effec on he percenage of he elderly wih healh insurance o areas where i had less of an effec. Since his approach will no capure any effec of Medicare on he previously-insured ha operaes via Medicare s income effec, i will underesimae he full impac of Medicare. Of course, privae insurance raes prior o Medicare are no randomly assigned. Daa from he 1960 census indicae ha differences in socio-economic saus can explain a subsanial share of he variaion in insurance coverage across subregions. Areas ha differ in heir socio-economic saus may also differ in heir desired level or growh of healh care uilizaion and spending. The empirical approach is herefore o look a wheher here is a break in any pre-exising differences in he level or rend of hese oucomes around he ime of Medicare s inroducion in 1966. The idenifying assumpion is ha absen Medicare, any pre-period differences would have coninued on he same rends. 5

The basic esimaing equaion is: 1975 = log( y ) = α * 1( couny ) + δ * 1( Year ) + λ ( Mcareimpac ) * 1( Year ) + X β + ε. = (1) ij j j z s ij 1948 The dependen variable is he log of oucome y in hospial i in couny j and year ; a level specificaion would consrain he oucomes o grow by he same absolue amoun each year, which would be inappropriae given he considerable variaion in size across hospials. 1(Couny j ) are couny fixed effecs; hese conrol for any fixed differences across counies. 1(Year ) are year fixed effecs; hese conrol for any naionwide year effecs. Mcareimpac z measures he percenage of he elderly in subregion z wihou privae Blue Cross hospial insurance in 1963 (see Table I). To accoun for possible serial correlaion over ime wihin areas, I allow for an arbirary variancecovariance marix in he error srucure wihin each hospial marke. 2 The exising lieraure suggess he use of he sandard meropolian saisical area (SMSA), defined in 1960, o approximae he hospial marke (see e.g. Makuc e al. [1991], Gaynor and Vog [2000], and Dranove e al. [1992]). This produces 210 separae markes; I also include 50 addiional markes for he rural (non-smsa) areas in each sae. The key variables of ineres are he ineracions of he year fixed effecs wih Mcareimpac z ( Mcareimpac z ) * 1 ( Year ) ). The paern of coefficiens on hese variables he λ s shows he ( flexibly esimaed paern over ime in he dependen variable in areas where Medicare had a larger impac on insurance coverage relaive o areas where i had a smaller impac. The change in he rend of hese λ ' s before and afer he inroducion of Medicare provides an esimae of Medicare s impac. Crucially, equaion (1) does no privilege 1965 relaive o oher years. Because I do no impose any exane resricions on when any srucural breaks may occur, I allow he daa o show where changes in he ime paern if any acually occur, and can gauge wheher Medicare may plausibly have played a role. To alleviae concerns ha oher hings migh also have been changing differenially over ime across ' 2 Clusering a he marke level allows for direcly comparabiliy of hese resuls wih hose of subsequen analyses esimaed a he marke level. In pracice, however, p-values are very similar if I insead cluser a he sae level (see Finkelsein [2005]), or implemen he randomized inference procedure described by Berrand e al. [2004]. 6

differen areas of he counry, equaion (1) also includes a series of ime-varying sae-level covariaes ( X s ). Of paricular concern is he poenial confounding impac of Medicaid which, like Medicare, was also enaced in 1965. Medicaid accouned for less han one-hird of combined Medicare and Medicaid hospial spending in he early 1970s [Naional Cener for Healh Saisics 2002]. Because he iming of Medicaid implemenaion unlike Medicare was lef up o he individual saes, I can ry o separaely conrol for any impac of Medicaid. 3 In all of he analyses, I herefore include a series of eigh indicaor variables for he number of years since (or before) he implemenaion of a Medicaid program in sae s. 4 In pracice, he esimaed effecs of Medicare are no sensiive o including hese conrols for Medicaid implemenaion. Of course, even conrolling for he iming of Medicaid s inroducion, equaion (1) may overesimae he impac of Medicare if he size of a sae s Medicaid program is posiively correlaed wih Mcareimpac z. In pracice, however, here is a weak negaive correlaion beween Medicaid spending per capia and Mcareimpac z, reflecing he fac ha saes in he Norh and Norheas implemened more generous Medicaid programs (U.S. Deparmen of Healh, Educaion and Welfare [1968], Suar [1972]). Finally, i is imporan o highligh wo limiaions o using he resuls from equaion (1) o gauge he aggregae impac of Medicare on naional spending and uilizaion. Firs, hospial unis of varying size are given equal weigh in he esimaion, bu migh have differen responses o Medicare. Second, esimaion a he hospial level may no capure any impac of Medicare ha occurs via an effec on hospial enry and exi. Therefore when I urn o he aggregae impac of Medicare in secion II.D below, I presen addiional resuls aggregaed o he hospial marke level which capures any ne effecs of hospial enry and exi and weighed by marke size. I also direcly invesigae he impac of Medicare on hospial 3 By July 1, 1966 (he dae ha Medicare was implemened) 22 saes accouning for half he naional populaion had implemened Medicaid. By January 1967 26 saes (62 percen of he populaion) had implemened Medicaid. These numbers increased o 37 saes (77 percen of he populaion) by January 1968, 40 saes (80 percen of he populaion) by January 1969, and 49 saes (99 percen of he populaion) by January 1970 (US Deparmen of Healh, Educaion and Welfare [1970], Gruber [2003] and populaion esimaes from he 1960 census). 4 Alhough in principle, esimaes of equaion (1) could shed ligh on he impac of Medicaid, in pracice, he resuls sugges ha he iming of sae implemenaion of Medicaid was no random wih respec o hospial oucomes, and analysis does no yield sable esimaes of he impac of Medicaid. 7

enry and exi in secion III.B. 5 II.B. Basic Resuls The core empirical findings are readily apparen in Figure II, which shows he λ s from esimaing equaion (1) for six (log) dependen variables: admissions, paien days, employmen, beds, payroll expendiures, and oal expendiures. The ime paern of he λ ' s idenifies changes in he dependen variable in areas in which Medicare had a larger impac on insurance coverage relaive o areas in which Medicare had a smaller impac. The dashed lines indicae he 95 percen confidence inerval for each coefficien, which naurally increases wih he disance from he reference year 1963. A verical line demarcaes 1965, he year in which Medicare was enaced. 6 Consider firs he resuls for hospial admissions (he upper-lef graph in Figure II). There is a general downward rend over ime in he λ ' s up hrough 1965. This indicaes ha, prior o 1965, hospial admissions were no growing as fas in low insurance areas relaive o high insurance areas. However, here is a dramaic reversal in his paern afer 1965, a which poin admissions sar o grow a he same rae or faser in he areas where Medicare s inroducion had a larger impac on insurance coverage. The oher five hospial oucomes examined in Figure II show he same paern of a dramaic reversal of a generally downward or fla rend afer 1965. The esimaes for payroll and oal expenses are somewha noisier han he oher esimaes, which may reflec he greaer noise in he expendiure measures (see Appendix A). The exisence of a prior relaive rend across more and less affeced areas is no surprising given he differences across hese areas in he level of hospial aciviy (and oher characerisics) prior o Medicare, alhough he sign of his relaive rend was no obvious a priori. Moivaed by he graphical resuls, I perform a variey of saisical ess of he n-year change in λ afer he inroducion of Medicare relaive o he n-year change in λ before he inroducion of 5 As I discuss below, esimaion a he marke level has is own disadvanage, namely increased noise in aggregaed sums due o non-rivial amouns of missing daa. 6 Daa from year are from he survey period Ocober (-1) o Sepember (). Since Medicare was enaced in July 1965 and implemened in July 1966, he year 1965 (i.e. Oc 1964 o Sep 1965) is reaed as he year prior o Medicare. Any effecs deeced in 1966 (i.e. Oc 1965 o Sep 1966) may be anicipaion or acual effecs. 8

Medicare. For example, he impac of Medicare in he firs five years is calculaed as follows: (2) Δ ( λ λ ) ( λ ). 5 1970 1965 1965 λ1960 Δ 5 hus denoes he five-year change in he hospial oucome afer he inroducion of Medicare relaive o he five-year change prior o he inroducion of Medicare in areas where Medicare had a greaer impac on insurance coverage relaive o areas where i had a smaller impac. The firs hree rows of Table III repor he esimaes for he wo-year, five-year and en-year change in he oucome, respecively; p- values are repored in parenheses below each esimae. The resuls indicae ha he inroducion of Medicare is associaed wih a saisically significan increase in all of he dependen variables. Because he reference (or pre-) period varies across he wo-year, five-year, and en-year ess, comparisons across he ess should no be inerpreed as differen effecs a differen ime inervals. To compare he effecs in differen ime inervals, he fourh row of Table III repeas he five-year es in he second row for he second five year period 1970 o 1975, using he same reference period (1965 o 1960) as he firs five year es. The resuls indicae ha Medicare is associaed wih a furher saisically significan increase in all of he oucomes in he second five year period. The resuls from he firs five-year es indicae an effec of Medicare for log admissions of 0.504, and for log oal expendiures of 0.332. To ranslae hese ino he implied naional impac of Medicare, I muliple hem by 0.75, since naionwide, Medicare increased he proporion of he elderly wih insurance coverage by 75 percenage poins. The resuls herefore imply ha he inroducion of Medicare is associaed wih a naionwide increase beween 1965 and 1970 in admissions and oal spending of, respecively, 46 percen (~ [exp(0.504 x 0.75)-1]), and 28 percen (~ [exp(0.332 x 0.75)-1]). In Secion II.D below, I discuss some limiaions o using he resuls in Table III o esimae he implied naional impac of Medicare, and presen and discuss some alernaive esimaes. II.C. Robusness I invesigaed he robusness of he preceding resuls o a number of alernaive specificaions. Overall he resuls were quie robus. This secion briefly summarizes some of he more imporan robusness 9

ess. Many of he resuls are presened in Table IV, where, o conserve space, I only repor he five-year esimaes. To make he resuls comparable across differen specificaions, I presen he implied five-year impac of Medicare. Row 1 herefore akes he baseline resuls from Table III and muliplies hem by 0.75 since, naionwide, Medicare increased he percen of he elderly by 75 percenage poins. A primary concern is he validiy of he idenifying assumpion ha absen he inroducion of Medicare, he differen subregions of he counry would no have exhibied divergen growh from he pre-medicare paerns. Figure II suggess ha in no year prior o 1965 (or afer i for ha maer) is here evidence of he dramaic reversal in rend in all oucomes ha occurs afer 1965. To examine his more sysemaically, I limi he daa o he years prior o 1966 and re-esimae equaion (1) and he wo-year and five-year ess from Table III if couner o fac I assign some year prior o 1966 as he year in which Medicare was implemened. I end no o find saisically or subsanively large effecs from hese false ess, which is broadly supporive of he idenifying assumpion (see Finkelsein [2005] for resuls). Furher supporing he idenifying assumpion, row 2 of Table IV shows ha he resuls are robus o including sae-specific linear rends in equaion (1), and row 3 shows ha he resuls are robus o including addiional ime-varying covariaes for real per capia sae income, sae infan moraliy rae, he rae of violen crime and sae populaion. 7 Finally, since he inroducion of Medicare coincided wih a period of enormous social upheaval in he Souh, including he civil righs movemen and he Hill Buron hospial consrucion program row 4 shows ha he resuls are robus o excluding he four souhern subregions (abou one-hird of hospials) from he sample. More generally, he resuls are robus o omiing any given subregion from he sample (see Finkelsein [2005] for resuls). A relaed concern is ha he esimaed impac of Medicare migh in par reflec he impac of increases in privae healh insurance for oher age groups. However, I find no indicaion in he 1959, 1963 and 1970 NHS surveys of a relaive increase in non-elderly privae healh insurance afer Medicare s inroducion relaive o before in he more affeced census regions relaive o less affeced census regions. 7 I am graeful o Larry Kaz for providing hese daa. All variables are measured annually, excep sae populaion which is inerpolaed beween censuses. See Kaz, Levi, and Shusorovich [2003] for more deails. 10

A final se of sensiiviy analyses uses alernaive sources of cross-secional heerogeneiy in he impac of Medicare on insurance coverage. Row 5 shows ha he resuls are robus o using variaion in insurance coverage a he subregion by-urban or subregion by-rural level insead of jus variaion a he subregion level. 8 Row 6 shows ha he resuls are robus o replacing he linear measure of Mcareimpac z wih an indicaor variable for wheher he subregion is one of he eigh subregions above he naional average in he impac of Medicare on insurance coverage. Row 7 shows he resuls are robus o measuring Mcareimpac z by he percen of elderly wihou any hospial insurance, raher han wihou Blue Cross hospial insurance (see Table I). Finally, row 8 shows ha he resuls are quie similar if Mcareimpac z is measured as he share of hospial expendiures in he subregion covered by elderly insurance, which is calculaed as he percen of he elderly wihou BC insurance imes he proporion of hospial expenses ha are elderly. 9 This is no surprising since in pracice here is very lile variaion in he percen elderly across subregions (or even across counies). II.D. The magniude of he impac of Medicare s inroducion on aggregae spending There are wo imporan limiaions o using he resuls from esimaing equaion (1) a he hospial level o infer he aggregae impac of Medicare. Firs, he analysis will no capure any effecs of Medicare ha operae via an impac on hospial exi or enry. Second, he analysis reas hospial of differen size equally, alhough hey may have differenial responses o Medicare. This secion herefore esimaes alernaive models o address boh of hese poenial issues. One way o capure any impac of Medicare ha operaes via an impac on hospial exi or enry is o aggregae (i.e. sum) he oucomes o he hospial marke. The disadvanage of analysis a he marke-level is he increased noise in he esimaes due o non-rivial amouns of missing daa, paricularly for he expendiure measures where only abou wo-hirds of hospials repor he informaion in a given year (see 8 Insurance raes are uniformly lower in rural areas, bu he geographic paern across subregions is quie similar in rural and in urban areas. I do no use hese urban- and rural-specific raes in he main specificaions because of he small sample size of some rural subregions in he NHS and because here is some uncerainy abou how o map he rural areas in he NHS daa ino he appropriae hospials in he AHA. 9 The percen of hospial expenses ha are elderly is based on he percen of he populaion in he subregion ha is elderly, and an esimae from he 1963 Healh Care Uilizaion Survey ha hospial spending per individual aged 65 and over was 2.3 imes ha per individual under age 65. 11

Appendix A). 10 As a resul, he flexibly esimaed model in equaion (1) ofen produces insignifican esimaes a he marke-level. I herefore esimae a more parameric, deviaion-from-rend model wih a rend break in 1965. This makes more efficien use of all he daa in esimaing he effec of Medicare han he poin-o-poin comparisons shown in Table III, which uilize only hree years of daa (see e.g. equaion 2). A relaed advanage of he deviaion-from-rend analysis over he more flexible esimaion is ha he poin-o-poin comparisons may produce misleading esimaes if a paricular poin in he comparison is no in line wih neighboring poins. Because of he imposiion of a funcional form on he ime series paern, I resric all of he deviaion from rend analyses o he years 1960 o 1970. I firs esimae he deviaion-from-rend analysis a he hospial level, o confirm ha i produces broadly similar resuls o hose from esimaing equaion (1). I esimae: (3) log( y ij ) = α * 1( couny ) + δ * 1( Year ) + β ( * Mcareimpac ) + β (( 1965) 2 j j * Mcareimpac ) + X β + ε z s 1 ij z. As in he flexible equaion (1), equaion (3) includes a full se series of couny fixed effecs ( α j ' s ) and year fixed effecs ( δ 's). However, insead of ineracing a full se of year dummies wih he subregion s insurance coverage prior o Medicare as in equaion (1), equaion (3) ineracs a linear ime rend wih he subregion s insurance coverage prior o Medicare * Mcareimpac ) and allows for a rend shif afer ( z he inroducion of Medicare ha varies wih he subregion s insurance coverage prior o Medicare ((- 1965)*Mcareimpac z ). The coefficien of ineres is β 2 ; i indicaes he differenial slope shif in 1966 experienced by hospials wih more of an impac of Medicare on insurance coverage relaive o hose wih less of an impac. The primary drawback o equaion (3) is ha i ex-ane resrics any shif o occur in 1966; he resuls from he preceding more flexible model in equaion (1) ogeher wih he falsificaion ess done on he pre-period sugges ha his is a reasonable resricion. The resuls from esimaing equaion (3) are shown in he firs row of Table V. The resuls are 10 There is no evidence of anyhing sysemaic deermining which observaions have missing daa, eiher by he cross-secional variaion in Medicare s impac, he ime period, or perhaps more imporanly he ineracion of he cross-secional variaion and ime period ha is used o idenify he impac of Medicare. 12

saisically significan for all oucomes and he implied five-year impac of Medicare (shown in bold in curly brackes) is similar o he implied five-year impac of Medicare from esimaing equaion (1) and performing he poin-o-poin es of equaion (2) (see row 2 of Table III). When he oucomes are aggregaed (summed) o he marke-level, I esimae: (4) log( y m ) = α * 1( marke m + β (( 1965) 2 m ) + δ * 1( Year ) + β ( * Mcareimpac ) * Mcareimpac ) + X z m β + ε 1 m z where m denoes he hospial marke. The dependen variable now measures he log of oal hospial spending (or inpus or uilizaion) in marke m and year. 11 Recall ha a hospial marke is an SMSA, or he rural (non-smsa) par of a sae. 12 The second row of Table V repors he resuls. All of he esimaes are saisically significan. For admissions, paien days, beds, and payroll expendiures, he magniudes are quie similar o he hospiallevel esimaes in he preceding row. However, for employmen and oal expendiures, he esimaes a he marke level are double he esimaes a he hospial level. For example, for oal spending, he coefficien on (-1965)*Mcareimpac z from equaion (4) a he marke level is 0.101, implying a five-year impac of Medicare on oal spending of 46 percen (~ [exp(0.0.101 x 0.75 x 5)-1]). By conras, he analogous coefficien from equaion (3) a he hospial level, is 0.056, implying a five-year impac of Medicare on oal-spending of only 23 percen (~ [exp(0.097 x 0.75 x 5)-1]). Noneheless, for all bu he employmen esimaes, each poin esimae a he hospial (marke) level lies wihin he 95 percen confidence inerval for he marke (hospial) level esimae. While aggregaion o he marke level will capure any impac of Medicare ha occurs via hospial enry or exi, i does no address he issue ha markes of differen size are given equal weigh in he regression esimae, ye may have heerogeneous responses o Medicare. Alhough furher aggregaion o 11 12 SMSA's cross a subregion border and 18 cross a sae border. In hese cases, I assign he subregion and saelevel variables he value in he subregion or sae wih he majoriy of hospials. The resuls are no sensiive o assigning average values insead. 12 The marke-level resuls are robus o he alernaive specificaions explored in Table IV (no shown). They are also robus o esimaing equaion (4) by a GLS procedure which allows for a separae variance-covariance marix wihin each marke as well as a marke-specific AR(1) erm. The poin esimaes from he GLS esimaion are quie similar o he OLS esimaes repored in Table V bu he sandard errors end o be an order of magniude smaller. 13

he naional level would address his issue of poenially heerogeneous reamen effecs, i would desroy he cross-secional variaion used o idenify he effec of Medicare. 13 One poenial soluion is o weigh each marke by a measure of is size. The hird row of Table V herefore repors he resuls from esimaing a weighed version of equaion (4) in which each marke s observaions are weighed by he number of paien days in ha marke in he base year (1960). There is no sysemaic change in he resuls; some oucomes such as admissions, employmen, and payroll expendiures are virually unaffeced. Ohers, such as beds and oal expendiures are abou 20 percen smaller. The one dramaic change is in paien days for which he effec declines in half and is no longer saisically significan. 14 Finally, an issue wih boh he unweighed and weighed esimaes is ha hey produce unbiased esimaes of E(log(y x)), no log(e(y x)), which is he objec of ineres (Manning [1998]). A simple soluion is o esimae a generalized linear model (GLM) wih log links: (5) log( E( y m + β (( 1965) 2 )) = α * 1( marke m * Mcareimpac ) + X m ) + δ * 1( Year ) + β ( z m β 1 * Mcareimpac ) z The boom row of Table V repors he resuls of esimaing he condiional expecaion funcion in equaion (5) by maximum likelihood, assuming a gamma disribuion of he error erm (see e.g. McCullagh and Nelder, 1989). As in he prior row, I weigh each marke s observaions by he number of paien days in he marke in 1960, and allow for an arbirary variance-covariance marix wihin each marke. Wih he excepion of he esimae for paien days, which remains insignifican bu declines even more in magniude, he oher esimaes are virually indisinguishable from he weighed OLS esimaes in he previous row. 13 A ime series comparison of spending or admissions growh since 1965 relaive o a pre-exising quadraic rend suggess ha Medicare is associaed wih a 31 percen increase in spending by 1970, bu no effec on admissions. 14 A poenial issue wih he weighed analysis is ha he impac of Medicare on insurance coverage may also differ across markes of differen size, making i difficul o disinguish heerogeneous reamen effecs from heerogeneous reamens. An alernaive approach would be o esimae he impac of Medicare separaely for urban and rural areas, since he NHS provides separae esimaes of insurance coverage for each area wihin each subregion. The separae esimaes can hen be averaged using heir relaive conribuion o naional oals o produce an esimae of he aggregae impac of Medicare. Deaon [1995] discusses he relaive advanages of his approach and he weighing approach. Resuls using his alernaive approach sugges ha he impac of Medicare was greaer in urban han in rural areas, and yield an implied naional impac of Medicare on spending ha is abou weny percen lower han he weighed esimae in Table V (no shown). 14

I use he resuls from he weighed GLM analysis (row 4 in Table V) as my cenral esimaes of he aggregae effec of Medicare. Table V indicaes ha hese resuls end o be he same or smaller han he resuls from alernaive marke-level specificaions. The Using he resuls from he weighed GLM esimaes a he marke level, he coefficien 0.083 on (- 1965)*Mcareimpac z from he oal expendiures regression (Table V, row 4, column 6) implies ha he inroducion of Medicare is associaed wih a 37 percen (~ [exp(0.083 x 0.75 x 5)-1]) increase in hospial spending over is firs five years. A similar analysis using he esimae of he impac of Medicare on admissions (coefficien of 0.074) suggess ha in is firs five years Medicare was associaed wih a 32 percen increase in admissions. Noe ha hese esimaes speak o he proporional effec of Medicare on hospial admissions and spending for all ages, no jus he elderly. In 1965, he elderly consiued 10 percen of he populaion, and 20 percen of hospial expendiures. 15 Daa from he Naional Healh Expendiure Accouns indicae ha real hospial expendiures grew by 63 percen beween 1965 and 1970, compared o only 41 percen over he previous five years. The esimaes herefore sugges ha Medicare can accoun for over half of he growh in hospial spending over his five year period, and all of he above-average growh relaive o he previous five years. III. Parial Equilibrium versus General Equilibrium Effecs of Healh Insurance III.A. Comparison o he Rand HIE esimaes Several aspecs of he Rand experimen faciliae comparison of my esimaes wih wha he Rand esimaes would predic for he impac of Medicare. The Rand experimen ook place only shorly afer he inroducion of Medicare (i was conduced from 1974 o 1982). Like Medicare, i provided hospial insurance for free, so ha boh esimaes incorporae a posiive income effec on hospial spending. I also esimaed he spending effecs of healh insurance separaely for differen ypes of healh care, so ha I can compare my esimaes of he impac of Medicare on hospial spending o Rand esimaes of he impac of healh insurance on hospial spending. Finally, he Rand experimen specifically invesigaed 15 Populaion esimaes come from inerpolaing he 1960 and 1970 census esimaes. The elderly s share of hospial expendiures is calculaed using he 1963 Survey of Healh Service Uilizaion and Expendiures. 15

he impac of shorer- versus longer-erm changes in healh insurance and found no differences, suggesing ha he expeced permanence of Medicare relaive o he Rand experimen is unlikely o be an imporan facor. The resuls from he Rand HIE indicae ha moving someone from no insurance o a policy similar o Medicare s would increase heir hospial spending by 37 percen. 16 Therefore, he Rand HIE would predic ha moving 75 percen of he elderly from no insurance o Medicare would increase hospial spending among he elderly by 28 percen, or as he elderly accouned 20 percen of hospial spending in 1965 oal hospial spending by 5.6 percen. This is less han one-sixh he magniude of he 37 percen effec of Medicare on hospial spending in is firs five years ha I esimaed above; he confidence inerval on my esimae rejecs he Rand poin esimae wih more han 99% confidence. 17 A poenially imporan cavea o his comparison is ha he Rand experimen excluded individuals age 62 and over. I seems doubful, however, ha a larger spending response of he elderly relaive o he non-elderly can explain he over six-fold higher esimaed impac of Medicare. Indeed, a priori, i is no clear wheher o expec ha he elderly have a larger price elasiciy of demand for healh care (for example, because hey end o be poorer han he non-elderly), or a smaller price elasiciy (for example, because heir healh problems are likely o be more severe.) There are wo broad classes of explanaions for he empirical finding ha marke-wide changes in healh insurance appear o have a disproporionaely larger impac on he healh care secor han smallscale changes in healh insurance. The fixed coss hypohesis is ha aggregae changes in healh insurance may sufficienly change he naure and magniude of he marke demand for healh care ha 16 Medicare hospial insurance originally imposed a $40 deducible (in 1965 dollars) and no co-paymen for he firs 60 days. The HIE esimaes sugges ha he effec of moving from no insurance o a policy wih no co-paymen and his deducible (i.e. a $125 deducible in 1983 dollars, which are he dollars used in he repored HIE esimaes) would be o increase spending from $500 o $685; see Keeler e al. [1988] and Newhouse e al. [1993], especially pages 129-130. Accouning for he fac ha Medicare imposed a 25 percen co-paymen afer 60 days in he hospial would only decrease he implied spending effec of Medicare from he Rand esimaes. Noe ha alhough he HIE placed limis on maximum ou of pocke spending, Keeler e al. [1988] describe how o esimae he effec of cossharing in he absence of such limis, and he esimaes I use from he HIE follow his approach. 17 Uilizaion esimaes from he HIE ha adjus for he ou of pocke maximums are no available. Noneheless, he resuls of cruder comparisons also sugges ha he HIE s implied impac of Medicare on hospial admissions would also be subsanially lower han wha I have esimaed here (see Newhouse e al. [1993], Table 3.2). 16

hey aler he incenives for hospials o incur he fixed coss of enering he marke or of adoping new pracice syles. The spillovers hypohesis is ha changes in insurance for one se of paiens can have spillover effecs o he reamen of oher paiens. Spillovers may arise from joinness in hospial producion, medical ehics, fears of malpracice liabiliy, or simply hospial income effecs. Consisen wih he presence of spillovers, several sudies have found ha, conrolling for an individual s own insurance, average insurance coverage in a hospial or physician pracice is sysemaically correlaed wih reamen inensiy and spending on he individual (Baker [1997], Baker and Shankarkumar [1998], Glied and Graff Zivin [2002], Baicker and Saiger [2004], Dafny [2005]). These wo hypoheses may be complemenary, and herefore no necessarily separable in an accouning sense. For example, if Medicare induces a hospial o incur he fixed cos of adoping a new echnology, he new echnology, once adoped, may also be used on non-elderly individuals. The hypoheses are, however, concepually disinc. The fixed coss hypohesis enails fundamenal nonlineariies in he impac of healh insurance on healh spending. The spillovers hypohesis, by conras, can operae even if he ypical communiy healh insurance has a linear impac on healh spending (alhough here may also be imporan non-lineariies). The res of his secion provides suggesive empirical evidence for each hypohesis. III.B. Evidence for he fixed coss hypohesis III.B.1. The impac of Medicare on hospial enry and exi If Medicare sufficienly increases aggregae demand for hospial care, i may induce new hospials o incur he fixed coss associaed wih marke enry. Medicare may also affec hospial exi if, for example, increased marke size increases he minimum efficien scale of a hospial, hereby inducing smaller hospials o exi. I herefore examine he impac of Medicare on hospial enry and exi using he deviaion-from-rend analysis (equaion 4); as before, I limi his analysis o he 1960 1970 period. For he enry analysis, he dependen variable is he raio of he number of hospials in marke m ha have enered beween 1960 and year o he oal number of hospials in marke m in 1960. For he exi analysis, he dependen variable is he share of hospials in marke m in 1960 ha have lef beween 1960 17

and year. (I use shares raher han logs because in mos marke-years here is no enry or exi and herefore he median value of he dependen variable is zero). On average, by 1970, new hospial enry had increased he number of hospials in he marke by 18 percen over he 1960 level; a he same ime, 14 percen of hospials ha were in he marke in 1960 had exied by 1970. 18 The resuls are shown in Table VI. They sugges ha he inroducion of Medicare had a saisically significan effec on hospial enry. This is consisen wih he larger esimaes of he impac of Medicare a he marke-level han a he hospial-level in Table V. By conras, Medicare does no appear o have a subsanively or saisically significan impac on hospial exi. I can use he resuls in Tables V and VI o decompose Medicare s five-year spending effec ino he porion due o Medicare-induced hospial enry. In doing so, I accoun for he fac ha he daa prior o 1965 indicae ha, on average, five years afer opening, a hospial s spending is only abou 40 percen ha of pre-exising hospials. Therefore, he resuls from he enry analysis (columns (1) and (2) of Table VI) suggess ha in is firs five years, Medicare-induced hospial enry may be responsible for an 18 percen (~ [0.12 x 0.75 x 5 x 0.4)) increase in hospial spending, or abou half of he overall 37 percen Medicareinduced increase in hospial spending. Since Medicare appears no o have affeced hospial exi, he remaining 19 percen spending effec of Medicare presumably reflecs growh wihin exising hospials. III.B.2 Suggesive evidence of he impac of Medicare on echnology adopion The large increase in aggregae demand associaed wih Medicare s inroducion may also have encouraged hospials o incur he fixed coss associaed wih adoping new echnologies. I invesigae he impac of Medicare on he adopion of new cardiac echnologies; hese have had an imporan role in boh 18 Idenifying enry and exi requires linking hospials across years based on name and locaion. To ry o disinguish genuine exi and enry from apparen exi or enry semming from hospial non-reporing or inadequae maching, I define a hospial as exiing in year if i is in he daa in year -1 and no in any subsequen year hrough 1975. Analogously, I define a hospial as enering in year if i is in he daa in year and no in any prior year back hrough 1948. As a realiy check, I compared my esimae of hospial enry o an alernaive esimae based on he hospial s esablishmen dae; his does no require linking hospials across ime, bu unforunaely, esablishmen dae is no repored afer 1964. Using he esablishmen dae, I esimae ha hospial enry increases he number of hospials beween 1955 and 1964 by 12 percen; using he panel daa approach, he analogous esimae is 17 percen. This suggess ha I may overesimae enry or exi by abou 40 percen. However, here is no evidence of sysemaic differences across subregions in my esimae of enry using he panel daa approach relaive o he esablishmen dae approach. I is herefore unlikely ha he esimaed impac of Medicare on enry or exi is biased. 18

he rise in healh spending and he increase in life expecancy over he las several decades [Culer, 2003]. The AHA daa provide informaion on wo cardiac echnologies: he open hear surgery faciliy and he cardiac inensive care uni (CICU). Virually all hospials wih open hear surgery have a CICU, which performs necessary pos-operaive care for open-hear surgery paiens. However he CICU serves oher purposes as well; only abou one-fifh of hospials wih a CICU have an open hear surgery faciliy. Unforunaely, AHA daa on cardiac echnologies do no exis prior o Medicare s inroducion. As a resul, I canno direcly examine he impac of Medicare s inroducion on changes in each echnology s geographic diffusion paern. This imporan daa limiaion makes he analysis of Medicare s impac on echnology adopion considerably more speculaive han he previous analyses. I proxy for wha he geographic diffusion paern of a cardiac echnology migh have looked like in he absence of Medicare by examining he geographic diffusion paern of oher echnologies ha reached roughly he same naionwide diffusion level prior o Medicare s inroducion ha a given cardiac echnology reached afer Medicare s inroducion. The idenifying assumpion is ha, absen Medicare, he geographic diffusion paern of he cardiac echnology would have looked similar o ha of he older echnology. The pronounced sabiliy across ime and across very differen echnologies in he geographic paern of echnology diffusion provides some suppor for his assumpion [Skinner and Saiger 2005]. Open hear surgery had reached a 9 percen diffusion rae by 1975. Four echnologies were a roughly his diffusion level prior o Medicare: he EEG (1950), he pos-operaive recovery room (1951), he diagnosic radioacive isoope herapy (1955) and he inensive care uni (1958). The CICU firs appears in he daa in 1969 wih a diffusion rae of 35 percen. 19 Anoher form of inensive care he posoperaive recovery room had diffused o his level by 1957. Table VII presens he resuls. Columns (1) hrough (7) show he coefficien on Mcareimpac z from Probi esimaion of (6) Newechis = λ * Mcareimpac z + X s β + ε is. 19 This is an aberraion for he AHA daa, as mos echnologies firs appear wih a diffusion rae of abou 10 percen. 19

Newech is is an indicaor variable for wheher hospial i in sae s has acquired a given echnology in he year of analysis (which varies across he echnologies as described above). Mcareimpac z measures he increase in insurance coverage in subregion z associaed wih he inroducion of Medicare. X s conrols for sae-level socio-economic condiions in he year of analysis; hese may help conrol for oher facors besides Medicare ha have changed over ime and may affec echnology adopion. The resuls indicae ha neiher open hear surgery nor he CICU is differenially diffused across areas wih differen Mcareimpac z. By conras, each of he conrol echnologies is less likely o be adoped in areas wih higher Mcareimpac z, and his geographic paern is ofen saisically significan. Columns (8) and (9) of Table VII show he resuls from sacking each cardiac echnology wih is conrol echnologies and esimaing by Probi he difference-in-differences equaion: Newech = α CARDIAC + δmcareimpac + λ( Mcareimpac * CARDIAC ) + X β + ε (7) is i z z i s is CARDIAC i is an indicaor variable for wheher echnology i is he cardiac echnology. The variable of ineres is Mcareimpac z *CARDIAC i. The resuls rejec he null hypohesis ha Medicare had no impac on cardiac echnology adopion. The geographic adopion paern of each cardiac echnology is saisically significanly more skewed oward areas more affeced by Medicare han he geographic adopion paern of is conrol echnologies. The resuls look similar if he sample is limied o hospials ha were buil prior o Medicare (no shown). 20 III.C. Suggesive evidence of spillovers If healh insurance spillovers are quaniaively imporan, esimaes of he impac of an individual s healh insurance could produce downward biased esimaes of he aggregae impac of healh insurance. One reason is ha mos empirical analyses of he impac of an individual s healh insurance use oher individuals in he same marke wih differen healh insurance as a comparison group; such analysis nes ou any spillover effec. Even wih an empirical design ha avoids his problem, i is unlikely ha spillovers would be capured in a sudy of he impac of an individual s healh insurance on healh 20 The analysis is no well suied o gauging he magniude of any impac of Medicare on echnology adopion, since i condiions on he echnologies reaching a given diffusion rae naionwide. 20

spending; he marginal impac of one s own healh insurance on he ypical healh insurance in he communiy is sufficienly small ha even a large spillover effec would be virually impossible o deec. To provide a rough gauge of he poenial imporance of spillovers in he curren conex, I calculae an alernaive esimae of he impac of Medicare based on changes in spending for he elderly relaive o he non-elderly. The esimaes are based on individual-level survey daa from he 1963 and 1970 Surveys of Healh Service Uilizaion and Expendiures. 21 Any impac of a change in ypical insurance saus will impac boh age groups and herefore be need ou of he esimae; he differenial spending change picks up only he direc impac of one s own age group s insurance, condiional on average insurance coverage. Consisen wih poenially large spillovers, I find ha analysis based on he age-variaion in Medicare coverage produces subsanially smaller esimaes of he impac of Medicare on hospial spending han he analysis in Secion II based on variaion across subregions, which includes any spillover effecs. Table VIII shows mean overall hospial spending in 1963 and in 1970 for individuals aged 65 o 74 and for individuals aged 55 o 64. The ime series comparison shows increases in spending for boh he elderly and non-elderly. The difference-in-differences esimae is more han seven imes smaller han he ime series increase in hospial spending for he elderly. I suggess ha he inroducion of Medicare is associaed wih an increase in hospial spending for he elderly relaive o he non-elderly of 16 percen (wih no covariae adjusmen) or 30 percen (covariae adjused). Even he larger esimae is less han one-fifh he magniude of he implied esimae from Secion II if he enire effec were limied o he elderly (185 percen, since he cenral esimae of he effec of Medicare in Secion II is 37 percen and 20 percen of hospial spending prior o Medicare was for he elderly). Ineresingly, i is quie similar o he 28 percen increase in elderly spending prediced by he Rand esimaes. IV. The spread of healh insurance and he growh of healh spending Beween 1950 and 1990, real per capia medical spending increased by a facor of six. Over he same 21 The 1963 survey is designed o be represenaive of he non-insiuionalized U.S. populaion; he 1970 survey also excludes he insiuionalized populaion bu over samples he elderly, rural areas, and he urban poor. Neiher survey includes usable populaion weighs. Spending daa is based on individual self-repors, bu aemps were made o verify insurance claims wih hird pary payers. Neiher survey conains geographic idenifiers. For more deails see ICPSR [1988] and ICPSR [2002]. 21

period, he average coinsurance rae for he populaion (calculaed as he raio of naional ou of pocke healh spending o naional oal healh spending) fell by abou 50 percenage poins (Gibson [1978], Cooper a al. [1976], CMS [2004]). Using he esimaes from he Rand experimen, Manning e al. [1987] and Newhouse [1992] conclude ha he spread of healh insurance can explain only a very small par on he order of one-eighh o one-enh of he increase in spending over his period. 22 I re-implemen he same back of he envelope calculaion using my cenral esimae of he 37 percen spending increase associaed wih Medicare over is firs five years. Medicare also decreased he average co-insurance rae in he populaion by abou 7 percenage poins. 23 Exrapolaing from his relaionship implies ha he 50 percenage poin decrease in co-insurance raes beween 1950 and 1990 would increase spending by 264 percen. The overall spread of insurance may herefore be able o explain half of he six-fold increase in real per capia healh spending over his period. My findings herefore sugges ha he spread of healh insurance may have played a much larger role in he subsanial growh in he healh care secor over he las half cenury han he curren convenional wisdom suggess. Of course, issues of exernal validiy sugges ha he exac resul from his back-of-he envelope calculaion should be viewed wih considerable cauion; i is primarily of ineres in comparison o he resuls of he same calculaion ha had previously been performed using he Rand esimaes. One issue wih exernal validiy is ha Medicare may have had more of an effec on spending han he spread of oher public and privae healh insurance due o Medicare s generous reimbursemen raes, including is generous reimbursemen of capial spending (Somers and Somers [1967], Unied Saes 22 To esimae he effec of he spread of healh insurance on healh spending, Manning e al. [1987] and Newhouse [1992] use he Rand s esimaes of spending differences beween various ypes of plans, bu no he difference beween no insurance and a Medicare-like policy which is he Rand esimae I compare my resuls o in he res of he paper. Also, Manning e al. [1987] and Newhouse [1992] look a he prediced effec of he spread of healh insurance on spending from 1950 o 1980 or 1950 o 1984, raher han 1950 o 1990, as I do here. However heir mehod is easily exrapolaed ou o 1990 and doing so does no change he esimaed conribuion of healh insurance. I do no exend he exrapolaion beyond 1990 due o he spread afer his poin of managed care, which may have very differen effecs on healh spending han radiional fee for service healh insurance. 23 Medicare increased insurance coverage among he elderly by 75 percenage poins, bu imposed an approximaely 5 percen co-pay (i.e. a one day deducible wih an average lengh of say for he elderly prior o Medicare of 20 days)); herefore on average i decreased he co-insurance rae for he elderly by abou 71 percenage poins (~ 0.75*0.95). The elderly were 10 percen of he populaion in 1965, herefore he average co-insurance rae for he populaion declined by abou 7 percenage poins. 22

Senae [1970], Feder [1977]) which may have conribued o is apparenly large effec on new hospial consrucion. On he oher hand, i is possible ha he long-run impac of Medicare is larger han he fiveyear impac used in he back of he envelope calculaion. Indeed, he resuls in Table III indicae ha he impac of Medicare on healh spending rises over he second five years of is exisence. Moreover, he suggesive evidence of an impac of Medicare on echnology adopion raises he possibiliy ha he increased marke size for new echnologies may have increased he incenives o develop new echnologies, and hus he subsequen arrival rae of new echnologies, as conjecured by Weisbrod [1991]. This dynamic feedback loop could produce long-run effecs of Medicare on echnological change and healh spending beyond he en-year pos-medicare window analyzed here. Alhough I can no invesigae his hypohesis direcly, empirical evidence of he effec of increased expeced demand on innovaion in he pharmaceuical indusry suggess ha such a feedback mechanism may be presen for hospial echnologies as well (Finkelsein [2004], Acemoglu and Linn [2004]). V. Conclusion By sudying he inroducion of Medicare, his paper has examined he impac of marke-wide changes in healh insurance on he healh care secor. My cenral esimae is ha Medicare is associaed wih a 37 percen increase in real hospial expendiures (for all ages) beween 1965 and 1970. This esimae is over six imes larger han wha evidence from he impac of an individual s healh insurance on healh spending would sugges. Abou half of he impac of Medicare on spending appears due o he induced enry of new hospials, while he res is due o growh in exising hospials. This induced hospial enry helps explain he disproporionaely larger impac on healh spending of marke-wide changes in healh insurance relaive o individual-level changes. The paper also presens suggesive evidence ha marke-wide changes in healh insurance may fundamenally aler he characer of medical care boh for individuals who experience a change in insurance coverage, and for hose who do no as well. A back of he envelope calculaion ha exrapolaes from he esimaed impac of Medicare o he impac of he spread of healh insurance more generally suggess ha he spread of healh insurance beween 1950 and 1990 may be able o explain abou half of he six-fold rise in real per capia healh 23

spending over his ime period. This raises he naural quesion of wheher a similar mechanism can explain why mos oher OECD counries have also experienced susained growh in he healh care secor over he las half-cenury [OECD 2004]. Ineresingly, like he Unied Saes, many of hese counries also esablished heir naional healh insurance sysems in he 1960s and 1970s [Culer 2002]. An imporan quesion for furher work is wheher oher healh insurance sysems had a similar impac on healh spending, or wheher idiosyncraic feaures of he Medicare sysem resuled in a uniquely high impac. In addiion, if Medicare s impac on he pracice of medicine in he Unied Saes influenced reamen pracices or coverage decisions in oher counries naional healh care sysems, i is also possible ha he effec of Medicare on healh spending may subsanially exceed is impac wihin he Unied Saes. This is also an ineresing avenue o explore in fuure research. 24

Appendix A: The American Hospial Associaion (AHA) Hisorical Daa. Sample definiion and ime period The daa are from he Augus issue of Hospials: The Journal of he American Hospial Associaion. Surveys were sen o every AHA-regisered hospial in he US. For flow daa (such as expendiures, employmen, and paien days), he survey asks hospials o repor for he 12- monh period ending Sepember 30 h of he year prior o he publicaion year. For sock daa (such as he number of beds, or wheher he hospial has various faciliies or echnologies) i is less clear wheher i is as of he survey response (i.e. before February of he publicaion year) or as of Sepember 30 h of he prior year. In all of he analysis, I ake he year o be he year prior o publicaion year. Thus, for example, he 1966 daa was published in he 1967 Augus issue of Hospials and conains flow daa for he period Ocober 1 1965 hrough Sepember 30 h 1966, and sock daa as of he fall of 1966. The AHA repors a response rae for he period I am sudying of over 90 percen in all years, and ofen above 96 percen. This is considerably higher han he repored response rae in more recen decades. Conversaions wih he research librarian a he AHA sugges ha his discrepancy may reflec he fac ha he older saisics on response rae may include hospials who respond o he survey wih heir name and address, even if hey repor no daa (and are herefore no included in he published saisics). This appears corroboraed by aemps by he auhor o rack hospials over ime in he daa, as hospials ofen disappear for a year or wo only o re-appear. Exrapolaing from he frequency of such occurrences suggess a response rae of closer o 80 percen, which is more in line wih daa from more recen decades. Condiional on reporing any daa, virually all responding hospials repor bed informaion, and abou 93 percen repor informaion on admissions, paien days, and employmen. However, only abou 83 percen repor payroll or oal expendiure informaion; his is probably because such informaion is considered more proprieary by he hospial. Hospial expendiures are herefore likely o be measured wih more error han he oher variables. Daa are more likely o be missing in smaller hospials and in poorer areas of he counry. There is no evidence of a change in reporing paerns associaed wih Medicare. Variable definiions are consisen over he period used in his sudy. They are as follows: Toal Expendiures. These consis of payroll and non payroll expenses. Non-payroll expenses are abou 40 percen of oal expenses and include employee benefis, professional fees, depreciaion expenses, ineres expenses, and oher expendiures (supplies ec.). The AHA does no repor hospial revenue during his ime period; esimaes of Medicare-induced changes in hospial expendiures herefore do no include any effec of he marke-wide change in healh insurance on he markup charged for healh care services. Payroll Expendiures: These include all salaries and wages for full ime personnel and full-ime equivalens of par-ime personnel, excep hose paid o inerns, residens and sudens. Beds: Excludes Bassines Employmen: Includes all paid personnel (boh full-ime and full-ime equivalens for par-ime personnel) excep residens, inerns and sudens. Does no include mos physicians, since mos physicians are no direcly employed by he hospial. The 1964 daa indicae ha jus over half of paid personnel are devoed o he professional care of paiens (i.e. nurses and echnicians); he remainder are divided among a variey of cusodial and adminisraive funcions. (This breakdown is no available in mos years). Admissions: Toal inpaien admissions for a 12-monh period, excludes newborns. Average Daily Census: Average number of inpaiens receiving care each day during a 12-monh period; excludes newborns. The Paien Days measure used in paper is creaed by muliplying average daily census by 365. MIT and NBER 25

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TABLE I: Share of Elderly Wihou Hospial Insurance, 1963 Blue Cross Any insurance New England (CT, ME, MA, NH, RI, VT) 0.49 0.37 Middle Alanic (NJ, NY, PA) 0.60 0.41 Eas Norh Cenral, Easern Par (MI, OH) 0.55 0.32 Eas Norh Cenral, Wesern Par (IL, IN, WI) 0.75 0.42 Wes Norh Cenral (IA, KS, MN, MO, NE, ND, SD) 0.81 0.47 Souh Alanic, Upper Par (DE, DC, MD, VA, WV) 0.75 0.45 Souh Alanic, Lower Par (FL, GA, NC, SC) 0.81 0.50 Eas Souh Cenral (AL, KY, MS, TN) 0.88 0.57 Wes Souh Cenral (AR, LA, OK, TX) 0.85 0.55 Mounain (AZ, CO, ID, MT, NV, NM, UT, WY) 0.78 0.50 Pacific (OR, WA, CA, AK, HI) 0.87 0.52 NATIONAL TOTAL 0.75 0.45 Daa are from individuals aged 65 and over in he 1963 Naional Healh Survey. Sample size is 12,757. Minimum sample size for a subregion is 377. 30

Oucome caegory TABLE II: Descripion of Dependen Variables from he AHA daa Dependen variable Firs year Sample mean (1962 1964) daa Full Norh & Souh & presen sample Norheas Wes Expendiures Toal 1955 1,486 1,782 1,180 ($1960, 000) Payroll 1948 976 1,196 748 Major Inpus Beds 1948 228 283 174 Employmen 1951 253 307 200 Uilizaion Inpaien admissions 1948 4,004 4,307 3,701 Inpaien days 1955 70,371 88,303 52,370 All variables are measured annually a he hospial level for non-federal hospials. Employmen and payroll expendiures exclude residens and inerns. 31

TABLE III: Impac of Medicare on Hospial Behavior Uilizaion Inpus Expendiures Log admissions Log paien days Log employmen Log beds Log payroll expendiures Log oal expendiures 1. Firs 2 Years: (1967-1965 vs. 1965-1963) 0.272** (0.040) 0.402*** (0.0004) 0.253*** (0.001) 0.094 (0.363) 0.342*** (0.003) 0.279*** (0.006) 2. Firs 5 Years: (1970-1965 vs. 1965-1960) 0.504*** (0.004) 0.567*** (0.0001) 0.340*** (0.009) 0.346*** (0.006) 0.560*** (0.0001) 0.332** (0.011) 3. Firs 10 Years (1975-1965 vs. 1965-1955) 0.394* (0.096) 0.419** (0.043) 0.376** (0.015) 0.693*** (0.0000) 0.449*** (0.008) 0.267* (0.093) 4. Second 5 Yrs: (1975-1970 vs. 1965-1960) 0.295* (0.057) 0.226* (0.096) 0.256** (0.017) 0.408*** (0.0001) 0.401*** (0.003) 0.239* (0.051) N 161,146 125,737 144,042 171,883 139,275 115,005 Table repors resuls from esimaing equaion (1) and calculaing es saisics as shown in equaion (2). Column heading shows dependen variable. Time varying sae-level conrols (X s ) in all analyses consis of eigh indicaor variables for he number of years before (or since) he implemenaion of Medicaid in sae s (see ex for more deails). P-values are in parenheses and are calculaed allowing for an arbirary variance-covariance marix wihin each hospial marke. ***, **, * denoes significance a he 1 percen, 5 percen, and 10 percen level respecively. Sample covers firs year of daa availabiliy hrough 1975. Firs year of daa availabiliy ranges from 1948 o 1955 depending on oucome; see Table II for deails. Differences in sample size across he columns primarily reflec differen saring years; however, o some exen hey also reflec differen proporions of missing daa (see Appendix A). Resuls are no sensiive o limiing all variables o a common sample. 32

TABLE IV: Impac of Medicare on Hospial Behavior; Alernaive Specificaions Uilizaion Inpus Expendiures Log admissions Log paien days Log employmen Log beds Log payroll expendiures Log oal expendiures 1. Baseline specificaion 0.378*** (0.004) 0.425*** (0.0001) 0.255*** (0.009) 0.260*** (0.006) 0.420*** (0.0001) 0.249** (0.011) 2. Sae-specific linear rends 0.355*** (0.006) 0.490*** (0.0000) 0.260*** (0.007) 0.266*** (0.005) 0.396*** (0.0002) 0.254** (0.011) 3. Addiional Time varying covariaes 4. w/o 4 souh n subregions 0.433*** (0.002) 0.485*** (0.001) 0.452*** (0.0001) 0.560*** (0.0000) 0.283*** (0.005) 0.234** (0.030) 0.251** (0.011) 0.360*** (0.0004) 0.438*** (0.0002) 0.329*** (0.005) 0.322*** (0.001) 0.264** (0.015) 5. Urban- and rural-specific insurance 6. Indicaor for >= 75% wo BC insurance 7. % w/o any privae insurance 8. % wo BC ins * % elderly 0.390*** (0.0004) 0.348*** (0.005) 0.275** (0.050) 0.443*** (0.0000) 0.421*** (0.0001) 0.376*** (0.0005) 0.260*** (0.004) 0.235** (0.017) 0.270** (0.013) 0.318*** (0.0000) 0.278*** (0.003) 0.188* (0.063) 0.380*** (0.0001) 0.386*** (0.0003) 0.438*** (0.0008) 0.254** (0.034) 0.192* (0.057) 0.243** (0.019) 0.338*** (0.007) 0.418*** (0.0001) 0.134 (0.144) 0.252*** (0.006) 0.310** (0.022) 0.196* (0.065) Table repors implied impac of Medicare from esimaing a varian of he baseline specificaion of equaion (1), performing he Firs 5 Years es in equaion (2), and he ranslaing he es saisic ino he implied impac of Medicare. This las sep is done so ha he esimaes are direcly comparable across specificaions. P-values are in parenheses and are calculaed allowing for an arbirary variance-covariance marix wihin each hospial marke. ***, **, * denoes significance a he 1 pc, 5 pc, and 10 pc level respecively. Row 1: Baseline specificaion: Esimaes are as shown in Table III, hen muliplied by 0.75 (he naionwide impac of Medicare on insurance coverage as measured by percen of elderly wihou BC insurance in 1963). Time varying sae-level conrols (X s ) consis of eigh indicaor variables for he number of years before (or since) he implemenaion of Medicaid in sae s Sample covers firs year of daa availabiliy hrough 1975. Firs year of daa availabiliy ranges from 1948 o 1955 depending on oucome; see Table II for deails. Row 2: Row 1 wih sae-specific linear rends included in he regression. Row 3: Row 1 wih addiional ime-varying sae covariaes (real per capia income, infan moraliy rae, violen crime, and populaion) added o he regression. Row 4: Row 1 wihou 4 Souhern subregions (and herefore muliplying by 0.7, he average % of he elderly wihou BC insurance in he non-souhern Unied Saes in 1963). Row 5: Row 1 bu wih urban- and rural-specific insurance raes wihin each subregion (see ex for deails). Row 6: Mcareimpac z in equaion (1) is measured wih an indicaor variable for subregion has >=75% of elderly w/o BC insurance raher han a linear measure of % of he elderly w/o BC insurance as in he baseline specificaion. Esimaes are muliplied by 2.7 since on average areas >= 75% or more of elderly w/o BC insurance have 28 percenage poins less insurance han areas where <75% of he elderly are w/o BC insurance. Row 7: Mcareimpac z is measured as he percen of he elderly wihou any privae hospial insurance. Esimaes are herefore muliplied by 0.45 (he percen of he elderly wihou any hospial insurance). Row 8: Mcareimpac z uses variaion in % of populaion ha is elderly as well as % of elderly w/o BC insurance. Esimaes are herefore muliplied by 0.15 (i.e. 0.75*0.20 where 0.75 is he average percenage poin increase in elderly insurance due o Medicare and 0.20 is he average share of he elderly in hospial expendiures. 33

Log admissions TABLE V: Aggregae Impac of Medicare Log paien Log Log beds days employmen Log payroll expendiures Log oal expendiures Hospial-level analysis 0.081** (0.034) [N=66,669] {0.35} 0.092*** (0.029) [N=66,376] {0.41} 0.046** (0.023) [N=66,510] {0.19} 0.077*** (0.021) [N=70,534] {0.33} 0.096*** (0.029) [N=59,905] {0.43} 0.056** ( 0.028) [N=60,842] {0.23} Marke-level analysis Unweighed 0.072*** OLS (0.020) {0.31} 0.094*** (0.035) {0.42} 0.099*** (0.021) {0.45} 0.077*** (0.029) {0.33} 0.094*** (0.026) {0.42} 0.101*** (0.024) {0.46} Weighed OLS 0.077*** (0.015) {0.33} 0.055 (0.049) {0.23} 0.092*** (0.025) {0.41} 0.060* (0.031) {0.25} 0.105** (0.043) {0.48} 0.082** (0.035) {0.36} Weighed GLM 0.074*** (0.015) {0.32} 0.036 (0.053) {0.14} 0.091*** (0.023) {0.41} 0.060** (0.029) {0.25} 0.104*** (0.040) {0.48} 0.083** (0.034) {0.37} N 2,846 2,846 2,846 2,847 2,844 2,844 Table repors coefficien on (-1965)*Mcareimpac (i.e. β 2 ) from esimaing deviaion-from-rend analysis in equaion (3), (4) or (5). The firs row repors he resuls from esimaing equaion (3) a he hospial level. The second and hird rows repor he resuls from esimaing equaion (4) a he marke level. The boom row repors he resuls from esimaing equaion (5) a he marke level. For all esimaes, he sample is limied o 1960 hrough 1970. All analyses include eigh ime-varying sae-level indicaor variables for he number of years before (or since) he implemenaion of Medicaid in sae s. Weighed esimaions (in rows 3 and 4) use he number of paien days in a given marke in 1960 o weigh each marke s observaions. Sandard errors are (in parenheses) and are calculaed allowing for an arbirary variance-covariance marix wihin each hospial marke. Implied five-year (percen) aggregae impac of Medicare is in bold {in curly brackes}. This is calculaed based on he repored coefficien (β 2 from he relevan equaion) and he ranslaion (exp(β 2 x 0.75 x 5)-1); his ranslaion accouns for he log specificaion, he fac ha Medicare on average increased insurance coverage by 75 percenage poins and ha β 2 only gives a one year effec. ***,**, * denoes saisical significance a he 1, 5, and 10 percen levels respecively. 34

TABLE VI: Analysis of Exi and Enry Enry analysis (columns 1-2) Exi analysis (columns 3-4) Unweighed OLS Weighed OLS Unweighed OLS Weighed OLS (1) (-1965)* Mcareimpac 0.116*** (0.019) (2) 0.121*** (0.017) (3) 0.011 (0.011) (4) 0.013 (0.010) Mean dep. var. in 1970 0.18 0.18 0.14 0.17 Table repors he coefficien on (-1965)*Mcareimpac (i.e. β 2 ) from esimaing he OLS deviaion-from-rend analysis a he marke level (equaion 4). For he enry analysis, he dependen variable is he proporion of hospials in marke m in 1960 ha have enered beween 1960 and year. For he exi analysis, he dependen variable is he proporion of hospials in marke m in 1960 ha have lef beween 1960 and year. For all esimaes, he sample is limied o 1960 hrough 1970. All analyses include eigh ime-varying sae-level indicaor variables for he number of years before (or since) he implemenaion of Medicaid in sae s. Weighed esimaions (in columns 2 and 4) use he number of paien days in a given marke in 1960 o weigh each marke s observaions. Sandard errors are in parenheses and are calculaed allowing for an arbirary variance-covariance marix wihin each hospial marke. ***,**, * denoes saisical significance a he 1, 5, and 10 percen levels respecively. N = 2,832 35

TABLE VII: Medicare and he Adopion of New Cardiac Technologies Analysis of Open Hear Surgery (Columns 1 5) Analysis of CICU (columns 6-7) Open hear EEG Pos-op Diagnosic Inensive CICU Pos-operaive surgery recovery radioacive care uni recovery room faciliy room isoope Difference-in-Differences Analysis (columns 8-9) Open hear CICU vs. Posoperaive surgery vs. conrols recovery room Wihou saelevel covariaes (1) 0.0004 (0.065) (2) -0.182*** (0.059) (3) -0.087** (0.044) (4) -0.210*** (0.068) (5) -0.143*** (0.053) (6) -0.097 (0.095) (7) -0.341*** (0.106) (8) 0.150*** (0.046) (9) 0.243*** (0.077) Wih sae-level covariaes 0.015 (0.063) -0.087 (0.063) -0.049 (0.057) -0.118 (0.072) -0.054 (0.062) 0.102 (0.096) -0.327** (0.127) 0.123*** (0.048) 0.247*** (0.092) Year of analysis 1975 1950 1951 1955 1958 1969 1957 Mean dependen 0.09 0.10 0.12 0.10 0.13 0.35 0.35 variable Esimaing (6) (6) (6) (6) (6) (6) (6) (7) (7) equaion All esimaes are marginal effecs from probi esimaion. Columns (1) hrough (7) repor he marginal effec of Mcareimpac from esimaion of equaion (6); dependen variable is shown in column heading and resuls for cardiac echnologies are in bold. Columns (8) and (9) repor he marginal effec of he ineracion of Mcareimpac wih CARDIAC indicaor from esimaion of equaion (7). CARDIAC is 1 for he cardiac echnology in he analysis, (open hear surgery or CICU) and 0 oherwise. Sandard errors (in parenheses) are adjused for correlaion wihin hospial markes. Firs row repors resuls from regressions wihou covariaes. Second row repors resuls from a separae regression which adds conrols for sae-level socio-economic characerisics (specifically, real per capia sae income, sae infan moraliy rae, violen crime rae, and sae populaion). 36

TABLE VIII: Changes in Hospial Spending for Individuals Aged 65-74 and Aged 55-64 1963 1970 Difference Difference (covariaeadjused) Differenceindifference Difference-indifference (covariae adjused) Ages 65-74 281 919 639*** (125) Ages 55-64 245 840 595*** (127) 651*** (133) 570*** (116) Difference 35 80 44 86 (63) (167) (178) (171) All dollars are in year 2000 dollars. Daa on overall hospial spending are from he 1963 and 1970 Surveys of Healh Service Uilizaion and Expendiures. N=3,030 (pooled sample); see ex for more deail on hese surveys. Robus sandard errors are in parenheses. ***, **, * indicaes saisical significance a he 1 percen, 5 percen and 10 percen level respecively. Covariae-adjused esimaes conrol for gender, marial saus, age, age-squared, and indicaors for educaion group (6 or fewer years of school, beween 6 and 12 years of school, and 12 or more years of school). 37

ToalExpendiures PayrollExpendiures 5 10 15 20 25 2 4 6 8 10 12 1950 1955 1960 1965 1970 1975 year 1950 1955 1960 1965 1970 1975 year Employmen Beds 1 1.5 2 2.5 3 1.2 1.3 1.4 1.5 1.6 1950 1955 1960 1965 1970 1975 year 1950 1955 1960 1965 1970 1975 year Admissions PaienDays 15 20 25 30 35 1950 1955 1960 1965 1970 1975 year 350 400 450 1950 1955 1960 1965 1970 1975 year Figure I: Naional Time Series Paerns Figure I graphs he naional aggregaes from he hospial-level daa described in he ex. Y-axis scale is in millions, excep for expendiure variables for which i is in billions of consan (1960) dollars. 38

Admissions PaienDays.5 0.5 1 1.8.6.4.2 0 1950 1955 1960 1965 1970 1975 year 1950 1955 1960 1965 1970 1975 year Employmen Beds.8.6.4.2 0 1950 1955 1960 1965 1970 1975 year.6.4.2 0.2 1950 1955 1960 1965 1970 1975 year 1.8.6.4.2 PayrollExpenses 1950 1955 1960 1965 1970 1975 year 1.8.6.4.2 ToalExpenses 1950 1955 1960 1965 1970 1975 year Figure II: Baseline Specificaion Figure II graphs he paern of he λ coefficiens from esimaing equaion (1) for he log of he dependen variable given above each graph. The scale of he graph is normalized so ha in he reference year (1963) i is he average difference in he dependen variable beween he souh and wes (where Medicare had a larger impac) relaive o he norh and norheas (where Medicare had a smaller impac). The fain dashed lines show he 95 percen confidence inerval on each coefficien relaive o he reference year (1963). Time varying sae-level conrols (X s ) in all analyses consis of eigh indicaor variables for he number of years before (or since) he implemenaion of Medicaid in sae s (see ex for more deails). 39