Social Exclusion and the Two-Tiered Healthcare System of Brazil

Transcription

1 Inter-Amercan Development Bank Banco Interamercano de Desarrollo Latn Amercan Research Network Red de Centros de Investgacón Research Network Workng paper #R-436 Socal Excluson and the Two-Tered Healthcare System of Brazl by Densard Alves* Chrstopher Tmmns** *Unversty of São Paulo **Yale Unversty December 2001

2 Catalogng-n-Publcaton data provded by the Inter-Amercan Development Bank Felpe Herrera Lbrary Alves, Densard. Socal excluson and the two-tered healthcare system of Brazl / by Densard Alves, Chrstopher Tmmns. p. cm. (Research Network workng papers ; R-436) Includes bblographcal references. 1. Margnalty, Socal--Brazl. 2. Medcal care--brazl. I. Tmmns, Chrstopher. II. Inter-Amercan Development Bank. Research Dept. III. Latn Amercan Research Network. IV. Ttle. V. Seres A482--dc21 &2001 Inter-Amercan Development Bank 1300 New York Avenue, N.W. Washngton, D.C The vews and nterpretatons n ths document are those of the authors and should not be attrbuted to the Inter-Amercan Development Bank, or to any ndvdual actng on ts behalf. The Research Department (RES) produces the Latn Amercan Economc Polces Newsletter, as well as workng papers and books, on dverse economc ssues. To obtan a complete lst of RES publcatons, and read or download them please vst our web ste at: 2

3 Abstract 1 In Brazl, there exsts a two-tered system of healthcare access. Those wth suffcent means have access to a prvate system of healthcare that provdes qualty treatment on demand, whle the remander of the country reles on an overburdened system of publc clncs and hosptals. Household survey data are used to determne whch soco-demographc groups rely most on ths publc healthcare system. Current demographc trends suggest that the publc healthcare nfrastructure wll become more and more heavly used n the comng decades. A stylzed model of healthcare choce s estmated, and ts parameters are used to conduct counterfactual smulatons of the welfare mplcatons of ths ncreased congeston, and of polces to offset t, lke prvate healthcare subsdes. 1 The authors gratefully acknowledge the fnancal support of the Inter-Amercan Development Bank. Ignez Trstao and Fabana Tto provded outstandng research assstance. Helpful comments and advce were receved from Paul Schultz, Chrs Udry, and all the partcpants of the Yale Unversty Development Lunch and the IDB semnars assocated wth ths research ntatve. 3

4 Table of Contents 1. Introducton 5 2. The Brazlan Healthcare System 7 3. Data Research Methodology Publc v. Prvate Healthcare and Brazlan Soco-Demographc Groups A Model of Indvdual Healthcare Choce Estmaton of the Shadow Prce of Publc Health Servce Results and Polcy Analyss Analyzng Welfare Effects of a Change n the Prce of Publc Healthcare Analyzng the Welfare Effects of a Prvate Healthcare Subsdy Conclusons and Extensons 24 Tables 26 References 35 Tables 1. Perceptons of Healthcare Qualty by Type Data Summary, Household Heads Probt Regresson, PrvHP Probt Regressons, Determnants of Dseases Heckman Procedure to Impute the Prce of Prvate Health Servces 31 S 6. Determnants of ln P Soco-Demographc Effects on Proportonal Measure of Compensatng S Income Varaton From a 50% Increase n P Soco-Demographc Effects on Proportonal Measure of Compensatng P Income Varaton From a 50% Reducton n P 34 4

5 1. Introducton In Brazl there exsts a two-tered system of healthcare. Those wth suffcent means, or whose employers provde health coverage, have access to a prvate system of healthcare that provdes qualty treatment on demand. The rest of the populaton reles on a system of publc clncs and hosptals. As s the case wth most publc healthcare systems around the world, the Brazlan system s characterzed by long watng tmes and questonable qualty, wth the practcal mplcaton that those who are forced to rely on the system spend more tme beng sck and, subsequently, have a dmnshed health stock. Ths two-tered system of healthcare s a partcularly relevant concern n Brazl n lght of recent changes n the country s soco-demographc structure. In 1990, only 6.7 percent of Brazl s populaton was over age 60, but by 2010 ths s expected to be 9.7 percent and by 2030, 16.9 percent (World Bank, 1994 and 2000). Durng the last twenty years, famly szes among the poorer segments of Brazlan socety (.e., those who typcally rely most on the publc provson of healthcare), have been larger than n wealther segments of socety. Ths large populaton group has been agng, and t s nearng a tme when ts healthcare needs wll grow rapdly (Cutler and Meara, 1998). Concerns have been rased that the Brazlan publc health system wll not be up to meetng ths growng demand. In partcular, already-long watng tmes for treatment wll contnue to grow, wth the practcal mplcaton that many of the poorest segments of socety wll receve no healthcare at all. Ths mechansm of socal excluson of the poor, elderly, and rural populaton wll ncrease at the rate at whch ths segment of the Brazlan populaton s growng. Ths mechansm may have long-run feedback effects as well. Growng demand due to the ncreasng sze of the poor, elderly populaton, as well as the ncreasng cost of treatment for a lmted supply of publc health servces, wll mean that the poorest segments of Brazlan socety wll begn to lose access to healthcare. Ths wll result n a declnng health stock for the poor, renforcng ther soco-economc poston. To the extent that the poor contnue to have larger famles (e.g., as a retrement-nsurance mechansm or a source of labor for subsstence agrculture), ths wll lead to further strans on the publc healthcare system n the future and the lkelhood of further falures. 5

6 Ths paper seeks to accomplsh three tasks. Frst, an outstandng set of Brazlan household survey data wll be used to characterze whch socal groups have access to prvate healthcare. These data nclude the 1998 PNAD, a broad household survey that provdes detaled nformaton on health, healthcare consumpton, and, most mportantly, the source from whch one receves health servces. On the bass of these data, t can be argued that certan groups are systematcally dened access to prvate healthcare n an ndrect fashon. After dentfyng whch groups are subject to ths form of excluson, the second part of the study wll construct and emprcally dentfy a stylzed model of choce between alternatve sources of healthcare provson, from whch t wll be possble to derve a crude measure of the welfare consequences of the ncreased healthcare congeston costs that are lkely to accompany the demographc transton currently observed n Brazl. Wth these welfare conclusons, the fnal part ths study wll analyze the mplcatons of polcy alternatves such as prvate healthcare subsdes. Secton 2 of ths paper descrbes the healthcare system n Brazl. Secton 3 descrbes the household survey data used n the analyss. Secton 4 outlnes the methodologcal approach for demonstratng that ndrect excluson exsts and measurng ts consequences, reportng how the mplct prce of publc healthcare vares across soco-demographc groups n Brazl. Secton 5 carres out two counterfactual smulatons. The frst examnes the mpacts of an ncrease n the mplct prce of publc healthcare, such as that whch would arse from the ncreased congeston that would accompany the predcted ncreases n healthcare demand n Brazl. 2 The second smulaton consders the mpact of a prvate healthcare subsdy beng provded by the government, makng that opton more accessble to groups who had prevously been able to afford only publc healthcare. Gven the propensty of ndvduals to swtch ther source of healthcare provson, such a polcy mght only result n rent transfers to those segments of socety that would not be consdered excluded. Secton 6 concludes by suggestng lmtatons to, and possble extensons of, ths research. 2 It s mportant to note that these smulatons could just as well descrbe any change n the publc provson of healthcare n Brazl that () ncreased the mplct prce of obtanng servces, or () reduced the qualty of servces receved, relatve to prvate healthcare. Avalable data do not permt a dstncton between prce and qualty of healthcare receved. Instead, t s necessary to speak n terms of the mplct prce of effectve unts of healthcare. Hgher qualty healthcare allows one to receve effectve unts at a lower prce n ths analyss (.e., t requres fewer trps to the doctor to get a fxed quantty of servces), just as would a dscount provder of low-qualty healthcare. More wll be sad about ths later 6

7 2. The Brazlan Healthcare System The healthcare system n Brazl s rooted n a belef that ndvduals and households should, at the most basc level, be protected by the publc sector. Therefore, whle many Brazlan ctzens rely on prvate sources of healthcare provson, the system also ncludes a very large publc component, whch s ntended to act as a safety net. The publc system, whch has ts own hosptal facltes and s federally fnanced by the SUS (Sstema Únco de Saude, or Unfed Health System n Englsh), s ntended to provde resources to meet the healthcare demands of those parts of the Brazlan populaton that do not have prvate nsurance to cover medcal expenses. The need for such a system n Brazl s very real. Publc health fgures show the persstence of endemc dseases, leadng to an annual mortalty rate s 0.6 percent (.e., approxmately 1 mllon people). The UN estmates that the Unfed Health System provded for 12.6 mllon hosptalzatons n about 2,000 publc and prvate hosptals n 1995, and 1.2 bllon consultatons n out-patent clncs. Smlarly, there are some 507,000 hosptal beds n Brazl (about 1 per 300 members of the populaton), of whch about one thrd are n publc establshments. Alves, Carvalhero and Hemann (2000) show that, n the state of São Paulo, 48.9 percent of the health servces used n 1998 were pad by the SUS, 6 percent were pad drectly by the users and 45.1 percent of the health servces were pre-pad. 3 Among the total populaton of the state of São Paulo, 44.2 percent have some type of health nsurance coverage, whle 55.8 percent have none. Those wthout health nsurance coverage have to rely entrely on the SUS. Alves (2000) shows that for the cty of São Paulo, located n the more developed southern area of Brazl, close to 40 percent of the populaton s cared for by the publc healthcare system. In the rest of Brazl, over 50 percent of the populaton reles on ths publc health system. In terms of ts structure, the SUS s a decentralzed system that provdes healthcare by dstrcts down to the muncpal level. The Muncpal Health Secretary has jursdcton over SUS health centers, hosptals, labs and servces, and admnsters funds provded by the federal, state and muncpal governments. A Muncpal Health Councl conssts of organzaton members, ctzens and school personnel, and t approves health programs; establshment of ths type of councl s necessary for the muncpalty to receve federal funds. Dstrcts and muncpaltes can cooperate n the paper. 3 In Brazl the man pre-pad health care servces are group-medcne plans, medcal cooperatves, or corporate plans. All 7

8 n sharng expenses and resources wth the am of enhancng healthcare effcency. The hstory of the SUS goes back more than a decade, to the Brazlan consttuton of 1988, whch mandated a free, unversal health care system as a result of a long socal movement to counter the nequtable health polces of prevous regmes. Prevous mltary regmes n Brazl had left a healthcare system that was hghly centralzed and wth lttle capacty n effect, a system that was extremely unresponsve to Brazl s local needs and regonal dversty. In the 1970s, nflaton was rampant and the Brazlan economy was n crss. A severe recesson followed n the early 1980s and publc healthcare expendtures fell substantally, drvng down the qualty of both health servces and nfrastructure. In response to ths, a councl consstng of federal mnstry representatves undertook the Reforma Santara, a health care reform effort. The frst phase of ths reform was the Integrated Health Actons, an effort to mprove coordnaton and decentralze servce delvery from the Mnstry of Health and INAMPS (Insttuto Naconal de Assstenca), the man fnancng mechansm, to state and muncpal levels. The second phase of the reform was the creaton of the SUDS (Sstemas Unfcados e Decentralzados de Saude) n , whch completed the process of decentralzaton. Then came along the new consttuton n 1988, whch paved the way for the creaton of SUS, the thrd and fnal phase of the reform. Snce that tme, the SUS has begun to contract-out a large majorty of patent care to a network of prvate and phlanthropc hosptals, clncs, and other facltes. Alves, Carvalhero, Hemann (2000) estmate that 20 percent of the avalable hosptal beds n Brazl used by the SUS n 1998 belonged to prvate hosptals. The government tself owns just 31 percent of the hosptal beds t supports and has been gradually decentralzng the control of publcly owned facltes. Ths trend towards decentralzaton and prvatzaton n Brazlan healthcare reform wll be mportant to the polcy conclusons n Secton 5. Prvate healthcare n Brazl has grown rapdly, wth about 26 percent of Brazlans covered by such plans. The plans vary a great deal n terms of prce and qualty but usually exclude expensve, catastrophc condtons, leavng them to be covered by the publc system. The prvate plans are also subject to vrtually no regulaton. Attrbutes of the avalable prvate plans are descrbed n Secton 3. of them offer pre-pad servces for ndvduals, famly and other enttes such as frms and unons. 8

9 Whle the state s theoretcally responsble for healthcare n Brazl, state expendtures on healthcare represent only about 4.2 percent of GNP each year, a low fgure relatve to some of Brazl s neghbors and countres lke Inda. In comparson, the US allocates about 12.7 percent of ts GNP to health care, France about 9 percent, El Salvador about 6 percent, and Paraguay 3 percent. Ths low level of spendng has led to many questons about the qualty of publcly provded healthcare n Brazl. Less than $80 per capta was spent on healthcare n Brazl last year, whereas the correspondng per capta expendture n Argentna was more on the order of $300 and n the US, $2,300. Almost $16 bllon was spent on health care n 1995, of whch $2.7 bllon was used to pay staff and $2.9 bllon was used to cover old loans. Alvarez (1998) states, the prvate sector n Brazl currently does a reasonably good job of provdng for the 25% of the populaton that ts plans and servces reach. However, the publc sector SUS s dong a poor job of servcng the other 75%. Numerous anecdotes and some emprcal evdence llustrate just how neffectve the SUS may be. For example, the world record for hosptalzatons occurred n Campo Grande do Sul n the State of Parana n Brazl, where over 60 percent of the populaton was hosptalzed n one year. An audt of the system then revealed that about 24.1 percent of all dagnoses were false. The detaled household survey data n the 1998 PNAD, whch are descrbed n the followng secton, makes t possble to look specfcally at ndvdual perceptons of healthcare qualty. In partcular, the PNAD questons ndvduals as to whether they sought healthcare durng the prevous two weeks, and f so, were they able to receve t. If they were unable to receve healthcare, questons determne whether t was, among other causes, because doctors were not present at the healthcare faclty or equpment was malfunctonng. Table 1 dvdes the sample of heads-of-households n the PNAD nto those who use the prvate healthcare system, and those who rely on the publc system, and examne ther answers to each of these questons. The results ndcate a clear-cut superorty of the prvate health system over the SUS system. For the country as a whole, the prvate system exhbted lower watng tmes than dd the publc system. The responses No Vacancy (n the case of hosptals) and No Attendng Doctors have hgher rates for the publc system. The remanng attrbutes of the qualty of the health systems, as perceved by patents, are smlarly unfavorable towards the SUS. At the regonal level the pcture s smlar, although less relable due to the smaller number of observatons. 9

10 A World Health Organzaton (WHO) Report released n June of 2001 placed Brazl 125 th out of 191 countres n the world and clamed that ts health stuaton s comparable to that n countres lke Nepal, Camboda, and Vetnam. Brazl s low rankng s mostly attrbuted to the nequtable manner n whch the healthcare system s fnanced; the WHO generally concludes that Brazlans have to pay too much for healthcare, and that the poor suffer the most under the Brazlan system. There are huge ncome dspartes n Brazl: 35 mllon of the 120 mllon Brazlans wthout prvate health nsurance are below the poverty lne. Accordng to the World Bank Operatons Evaluaton Department (1998), Brazl s health system mght appear to be effcent (t substantally separates fnancng from the provson of servces), but t s nchng toward crss. The publc system s underfnanced and therefore exhbts severe regonal nequaltes, ratonng, and declnng qualty. The World Bank Report goes further:...the hypernflaton of the late 1980s and early 1990s and the rregular flow of resources to health have contrbuted to the evoluton of a fee structure for medcal treatment that has not kept pace wth costs, and payment can be sporadc. Doctors frequently must work at several stes to make ends meet. Stores of long lnes for hosptal servces, mstakes n emergency care, strkes and walkouts by medcal professonals, arbtrary trage, and other crses are reported daly n the press. Ths system covers about 70 percent of npatent and outpatent care. However, local governments are gven responsbltes under the decentralzaton of the publc health care system, but do not necessarly have the resources or ncentves to delver cost-effectve servces. Expendtures do not target the poor, and nsttutons are extremely fragmented and expensve. Brazl has one of the lowest ratos of nurses to doctors n the developng world (0.33:1 n 1996) and an average of only 13 doctors per 10,000 resdents. Moreover, the SUS has also brought wth t a decrease n physcans pay. Accordng to the Natonal School of Publc Health at Brazl s Oswaldo Cruz Foundaton, a doctor of the old Natonal Insttute would have receved a much hgher salary there than he can now, even though he stll performs the same functons and mantans the same caseload and hours. 10

11 In summary, n Brazl and n most Latn Amercan countres, 4 the publc sector stll has a major responsblty for the provson of health servces. The Brazlan government uses general revenues to pay for the healthcare of mddle- and low-ncome populaton groups, whle upper ncome groups tend to use ther own resources to pay for prvate healthcare. Those wth low ncome and educaton, as well as members of certan racal groups, tend to be dscrmnated aganst by the system n the sense that, for publc health care, access s more dffcult, watng tmes on lnes are longer, as are travel dstances, yet these groups do not have the fnancal resources to take part n the prvate system wthout nordnate sacrfces of other consumpton. Gven ths two-tered system of servce provson, healthcare utlzaton would be expected to exhbt large varance across the populaton, and ths s supported by the lterature ndcatng that utlzaton of health servces dffers vastly by ncome groups n Brazl (Alves, 2000). 3. Data The 1998 PNAD s an annual household survey on soco-economc condtons of the Brazlan populaton, collected under the responsblty of the Insttuto Braslero de Geografa e Estaststca (IBGE). The 1998 PNAD has a specal supplement dealng wth the health condtons of the Brazlan populaton, makng t partcularly sutable for ths analyss. The survey covers 344,975 ndvduals and 98,166 households. In the present analyss, however, the number of observatons s smaller due to mssng values for some mportant varables, partcularly ncome per person n the household. The use of ths survey data presents a number of advantages. Frst, t s one of the only surveys to collect data on health of the populaton n a consstent fashon. Second, data collecton on health s accompaned by a full set of soco-economc data on the ndvdual and the household. Use of the PNAD also presents some dsadvantages. The collecton of such data reles on the tranng of data enumerators to record health status. Thus, when lookng at reported llnesses, the accuracy mght not be as hgh as t would be f medcal professonals were examnng the ndvduals and reportng ther llnesses. In addton, data n the Northern regon of Brazl are restrcted to the urban sector and are, therefore, not representatve of the entre regon. The full data set, however, does cover thoroughly the remanng regons of Brazl, and the excluson of the rural North does not 4 See Parker and Wong (1997) and Wong (2000) for an analyss of the Mexcan health system. 11

12 harm the survey s representatveness, snce ths populaton s very scarce. The present analyss uses the household data set nstead of the larger ndvdual sample data. Decsons on healthcare utlzaton are major decsons made at the level of the household, and usng ndvdual data would lkely ntroduce correlatons between household members. Table 2 shows some major characterstcs of the data set. The varable Wth_HP measures the proporton of household heads who have a prvate health nsurance plan pad ether by hmself or by hs employer. Ths amounts to 17 percent of total household heads. The remanng households use the publc health system. The varable PrvHP ndcates whether a household pays for ts own health plan, and Whopay ndcates that a household has a prvate plan that s pad for by an employer. The average household ncome n the sample s R$ monthly. The average payment of health nsurance for the 6.9 percent who pay ther own medcal nsurance s R$ and ther average household ncome s hgher than the sample average, at R$ 2, and R$ of household per capta ncome (ncome reported n Table 2 s the average household per capta ncome). The average per capta ncome for the households payng for a prvate health plan s twce the average per capta ncome of the household sample. The mean of the Metro varable gves the proporton of the household heads lvng n Brazlan metropoltan areas. Age60 s a varable that specfes whether the head of the household s over 60 years of age, whle Chld_14 ndcates the proporton of persons, below age 14, lvng n the household. The set of race-dfferentaton varables are Whte, Mxed, Black and Asan. The proporton of Blacks s qute small, although t should be noted that a large porton of the people who nclude themselves n the Mxed racal would generally be perceved as Black. The proporton of households not reportng llness s 49.1 percent. The remanng 50.9 percent reported the occurrence of at least one llness, and the proporton of people seekng medcal treatment n the last two weeks s 13.1 percent. Table 1 reports the results of users evaluatons of the qualty of the healthcare sought by those households. Illnesses are self-reported by the head of the household. The characterstcs of the prvate health nsurance plans are presented at the bottom of Table 2. The health plan attrbutes are defned by a set of dummy varables. The varable plcons takes a value of 1 when the health plan allows for the pror appontment of a doctor consultaton and zero otherwse. Table 2 shows that percent of the health nsurance plans cover pre-appontment 12

13 for vsts to doctors. Pllst s 1 when the health nsurance polcy presents a lst of authorzed doctors, hosptals and laboratores that can be used by the polcyholder and 0 otherwse; percent of the prvate health nsurance polces present a lst of authorzed doctors, hosptals and laboratores. The value for the varable plreemb ndcates that percent of the health plans permt rembursement of medcal expenses when the ndvdual s attended by doctors or health centers not afflated wth the health plan. Plother ndcates that percent of polcyholders can be attended by doctors, hosptals and laboratores n ctes other than the one n whch they resde, and pldent ndcates that only percent of health nsurance plans cover dental treatment. Ths attrbute s clearly not a wdespread characterstc of prvate health nsurance, and plans wth ths attrbute are more expensve than those wthout. Paymore s a varable capturng the fact that some health nsurance polces mpose a celng on what they pay for healthcare expenses, and any expense above ths lmt has to be pad by the polcyholder. 5 The varable plexam ndcates that percent of health plans allow the polcyholder to take complementary lab exams durng treatment. Among prvate polcyholders, percent are covered for hosptalzaton, as ndcated by the varable plnter. Platend ndcates that percent of polcyholders are attended by medcal servces under contract wth ther heath nsurance company. Very few health plans cover the acquston of medcnes and drugs. Plmedc ndcates that ths attrbute s very specal and covers only 4.85 percent of the prvate health nsurance holders. Among health nsurance holders, only 3.07 percent of plans cover orthodontal treatment. Ths aspect of the health nsurance s represented by the varable odonto. Ths detaled lst of prvate health plan attrbutes wll prove valuable n the followng analyss n that t makes t possble to mpute prces for a standardzed prvate health plan (.e., a smplfed plan wthout any of the bells and whstles descrbed above) for every member of the sample, regardless of whether they actually bought a prvate health plan (of any type). Calculaton of these mputed prces wll be necessary for determnng the welfare consequences for each ndvdual of facng an ncrease n the shadow prce of publc healthcare. 5 Ths s the only attrbute among the eleven descrbed here for whch the dummy varable assumes the value of one when t ndcates a detrmental characterstc of the health plan. 13

14 4. Research Methodology In order to characterze ndrect excluson from prvate healthcare n Brazl, a two-pronged methodologcal approach s adopted. Frst, the detaled survey nformaton n the 1998 PNAD data set, descrbed n Secton 3, s employed to determne generally whch groups n Brazlan socety have access to prvate health nsurance and whch rely on publc healthcare. Beng relegated to publc healthcare s not a drect form of excluson, but rather one based on relatve prces for prvate and publc healthcare that may be dfferent for ndvduals from dfferent segments of socety. Moreover, dfferences n employment patterns for ndvduals from dfferent soco-economc groups wll nfluence ther access to employer-provded prvate health nsurance Publc v. Prvate Healthcare and Brazlan Soco-Demographc Groups Certan groups, delneated by race, educaton, and locaton n Brazl, are expected to be systematcally more relant on the publc healthcare system. The queston of whch groups fall nto ths category s determned wth a smple Probt regresson (Greene, 2000) of the followng form: P( y = 1)= Φ ( X, j _ β ) (4.1.1) where y = form of healthcare coverage for ndvdual (1 = prvate, 0 = publc) X = soco-economc attrbutes of ndvdual ; these nclude - Race (Black, Asan, Mxed, Whte) - Age - Educaton s defned by years of schoolng - Household Income - Regonal Indcators: - Percentage of Persons n the Household wth less than fourteen y ears of age - Percentage of People above 60 years of Age 6 Ths dffcult ssue (.e., health nsurance as an attrbute of a job for whch an ndvdual may or may not face a correspondng reducton n pay) s avoded by consderng only those ndvduals who ether buy prvate nsurance drectly (.e., those who do not receve t through an employer) or use the SUS. 14

15 - Household Income: the total sum of wage and other types of ncome of ndvduals lvng n the household. The results of ths regresson, whch are found n Table 3, correspond to general perceptons about Brazlan healthcare. Those who tend to be more relant on the publc system are less educated, female, come from the Black and Mxed racal groups and from the Northern and Center- Western regons of Brazl, have lower ncomes, and are elderly. The presence of people above sxty years of age n the household s hghly sgnfcant, whle the presence of people below fourteen years of age does not make a dfference n the household s health nsurance decson. Gven the results descrbed n Table 1 regardng dfferences n the qualty of healthcare across provders, ths alone could be consdered evdence of excluson of these groups. Table 4 provdes addtonal evdence along these lnes. Specfcally, t presents the results of a number of Probt regressons n whch a dummy varable ndcatng that an ndvdual has suffered from a partcular dsease (e.g., depresson, arthrts, cancer, dabetes, respratory alment, hypertenson, cardac dsease, tuberculoss, crrhoss, tendonts, and kdney dsease) s regressed on a set of ndvdual attrbutes, ncludng the form of healthcare provson (.e., SUS vs. prvate) that the ndvdual uses. The dea here s that an ndvdual s health stock, whch determnes how lkely he s to suffer from any of these alments, s, n part, determned by the effectve quantty of healthcare he consumes. Ths s drectly a functon of ts qualty, as well as ts (shadow) prce. An ndvdual who reles on the publc system mght, therefore, receve lower qualty care, or less care n general (f watng tmes for treatment are longer), leadng to a lower health stock and a hgher lkelhood of dsease because the qualty of publc healthcare s low, and t s dffcult to consume effectve healthcare unts. These results should be nterpreted wth extreme cauton, however, as the form of healthcare provson may be smultaneously determned wth the ndvdual s health stock; e.g., an ndvdual who knows he s lkely to develop cancer mght purchase prvate health nsurance n order to guarantee hmself a hgher qualty of care. The presence of an endogenous varable n a Probt regresson can potentally lead to nconsstent estmates of all the model s parameters. The results, however, are very much consstent wth a pror expectatons about health and about the Brazlan health system. Women, generally, are less lkely to suffer from almost all dseases but crrhoss;.e., women seem to be healther than men. Hgher ncome follows good 15

16 health, meanng that poor people are more lkely to suffer from some of the llnesses defned n the PNAD survey. One mportant pont to note, however, s that people wth prvate health plans, ether self pad or employer pad, are more lkely to suffer from some of the llnesses, whle healther people are less lkely to go to a prvate pad health plan. Ths mght smply be the result of gettng better dagnoses from a prvate healthcare provder than from a publc clnc. Certan llnesses seem more lkely to strke the Northeastern regon, whle people from the Southern and Southeastern regons are more lkely to report cardac dsease, cancer, depresson and respratory dseases. 4.2 A Model of Indvdual Healthcare Choce Whle descrbng whch elements of Brazlan socety are more lkely to rely on publcly provded healthcare, the precedng analyss does not provde any way of measurng the welfare consequences of ths ndrect form of excluson. In order to do so, t s necessary to develop a more elaborate model that takes nto account the fact that ndvduals optmally choose what form of health nsurance to obtan n the face of market prces and a budget constrant. The second part of the emprcal analyss develops such a model. The bndng constrants on the scope of the conclusons that can be taken away from ths model come from the lack of data descrbng ndvduals full ncome endowments and actual expendture patterns on health and non-health commodtes. Instead, the model takes a stylzed vew, descrbng the ndvdual s choce of health coverage as a choce between alternatve types of nsurance n a statc context. To the extent that ndvduals change health nsurance status durng the course of ther lfe, ths may bas answers. In partcular, t s assumed that ndvdual chooses hs form of healthcare provson n order to maxmze a utlty functon of the form: subject to a smple budget constrant: U a ( C, H ) = C H (4.2.1) H C represents s consumpton of a composte numerare commodty, H represents the consumpton of effectve healthcare servces (the prce for these servces, P H s allowed to dffer by ndvdual, and to reflect the qualty of the nomnal healthcare consumed), and I represents the ndvdual s ncome. P H wll also dffer accordng to the form of healthcare provson chosen;.e., 16 a 1 C + P H = 1 (4.2.2.)

17 P S for SUS healthcare and P P for prvately provded healthcare. The chef source of dffculty n ths analyss s that P S s not observed (all SUS healthcare s nomnally free), but s rather only a shadow prce of SUS healthcare consumpton. Utlty maxmzaton subject to ths budget constrant yelds the followng ndrect utlty functon: V ( P H, I ) ( α I ) α (1 α ) I P 1 = H 1 α 1 (4.2.3) whch dffers by whether the ndvdual chooses SUS healthcare (V(P S,I )) or prvate healthcare (V(P P,I )). Takng the optmal allocaton of ncome between composte consumpton and healthcare as gven, ndvdual s choce between the two forms of healthcare provson can be modeled as a comparson of these two ndrect utlty functons. In partcular, ndvdual wll choose SUS healthcare as long as: s P V P, I ) V ( P,1 ) (4.2.4) ( Because of the smple functonal forms adopted for the present purpose, condton (4.2.4) bols down to P S P P. The prce of an effectve unt of publc healthcare s not an observed magntude; nomnally, publc healthcare s free to everyone n Brazl. It has a prce, however, n the form of tme n and dsutlty of crowded watng rooms and other factors (see dscusson n Secton 2). Ths prce would be expected to dffer across ndvduals accordng to ther opportunty cost of tme, preferences for cleanlness and qualty, and dsutlty of congeston;.e., dfferences for whch control may be possble wth a set of observable ndvdual attrbutes (X ). The avalable data make t possble to recover each ndvdual s shadow prce for an effectve unt of publc healthcare by usng nequalty (4.2.4). Once ths s done, all the tools necessary are avalable for consderng the welfare mpacts of an ncrease n the congeston costs assocated wth recevng health servces from the SUS. In partcular, assumng that the ndvdual chooses the healthcare opton that maxmzes hs ndrect utlty (wth the ndvdual s percepton of the qualty dfference between publc and prvate provson factored nto that prce), prvate healthcare wll be chosen f P P P S. 17

18 4.3 Estmaton of the Shadow Prce of Publc Health Servce P P s observed n avalable data. P S, on the other hand, s not observed and has to be estmated. In partcular, n PNAD data the prce s observed of the prvate health nsurance pad for everyone who opted for that form of coverage. Prvate health nsurance premums are mputed for the rest of the sample usng the Heckman selecton model: where P p Z + u 1 = γ (4.3.1) Zare dummy varables descrbng the characterstcs of the health plan and γ s a vector of coeffcents assocated wth the matrx of attrbutes. P P s not observed for all households, but rather only for those who purchased prvate health nsurance. It s not known, however, whch households were more lkely to purchase prvate health plans, even f they had not actually acqured one. The probablty can be descrbed by the Probt regresson n equaton (4.1.1). Equaton (4.1.1) thus descrbes the sample selecton component of a Heckman Selecton Model (Greene, 2000). Prvate health nsurance premums are mputed for the whole sample by estmatng equaton (4.3.1), accountng for selecton nto prvate health provson wth a Heckman selecton correcton as specfed n equaton (4.1.1). The results of ths model are presented n Table 5. After estmatng the parameters of equaton (4.3.1) t s possble to forecast the prvate premum for a standardzed polcy for all ndvduals. In partcular, the standardzaton adopted sets all of the attrbutes of the healthcare polcy to ther smplest values.e., to gve the prce of a polcy wthout any bells or whstles. Ths creates a level playng ground for comparson of the ndvdual s decson between publc and prvate coverage (.e., what would be the welfare effect of an ncrease n the prce of publc healthcare f everyone had the same smple prvate opton to choose as an alternatve). Usng ths procedure, t s possble to estmate a shadow prce, P S, whch establshes how much each household would pay for the use of the publc health system. The natural logarthm of P S s paramaterzed as a lnear functon of ndvdual attrbutes (X ) and an unobservable determnant (ε ), whch s assumed to be dentcally and ndependently normally dstrbuted wth a varance σ 2 and a zero mean. The choce of prvate health coverage s then determned by the followng condton beng satsfed: P ln P LE X _ β + ε (4.3.2) 18

19 whch wll be the case f: P ln P - X _ β LE ε (4.3.3) whch occurs wth probablty 1 - Φ[(ln P P - X β)/σ]. Smlarly, the probablty that ndvdual chooses publc health coverage s gven by Φ[(ln P P - X β)/σ]. The lkelhood of observng all of the health coverage choces of the ndvduals n the data set (y ), gven ther observable attrbutes (X ) and prvate healthcare prce (P P ), can therefore be wrtten as: L( y, X, P P ; β, σ )= Π y = 0 ln Φ P P - X _ β σ Π y = 1 ln 1 - Φ P P - X _ β σ (4.3.4) Ths lkelhood functon s maxmzed over the parameter vector, β, usng data descrbng the decsons and attrbutes of a 10 percent subsample of household heads n the PNAD. The use of only household heads elmnates the correlaton n nsurance type between members of a household that exsts n the full data set, and the 10 percent subsample s chosen for computatonal tractablty. Elmnatng data wth mssng observatons for some varables, ths yelds a sample sze of N = Coeffcent estmates and standard errors are reported n Table 6. The parameter σ s not dentfed n ths dscrete choce model; n partcular, the parameters β are only dentfed up to a scalng parameter ntroduced by σ. Ths regresson s therefore performed for a range of plausble values for the condtonal standard devaton of ln P S : 0.5, 1, 2, and 3; hgher and lower values of the standard devaton lead to numercal problems. Results for each of these standard devatons are reported n columns of Table 6. Parameter estmates generally have the expected sgn and tend to be statstcally sgnfcant. Those who would be expected to have greater dsutlty from factors such as congeston (.e., from havng a greater opportunty cost of tme) face a hgher mputed prce for SUS healthcare. Ths s true of older and more educated ndvduals, although once ndvduals are over the age of 60 (.e., when they begn to retre), ther mputed SUS healthcare prce falls. Indvduals wth hgher ncomes face a hgher prce, also because of a greater opportunty cost of tme, and urban ndvduals face a greater cost than rural ndvduals, possbly because congeston problems are worse n ctes. 19

20 Indvduals n the South, Southeast, and Center-West regons of Brazl face hgher prces than those n the North and Northeast, and Blacks and those n the Mxed racal category face lower prces than Whtes, whle Asans face hgher prces. Whle the magntudes of the varous effects may dffer, the sgns of each of these effects are consstent across possble values of σ. As a measure of model ft, the predcted health coverage decsons of ths model can be compared wth the decsons observed n the data. The model does well, correctly predctng the choces of 87 percent of all ndvduals rrespectve of the assumed value of σ. When the model fals to predct correctly, t tends to be n the case of ncorrectly forecastng the choces made by those ndvduals who opt for prvate health coverage;.e., hgh-ncome, more educated, and older (younger than 60 years) ndvduals. 5. Results and Polcy Analyss 5.1 Analyzng Welfare Effects of a Change n the Prce of Publc Healthcare The ntal goal of ths study was to determne whch groups would suffer the most as a result of the ncreasng congeston of the publc healthcare nfrastructure that wll lkely accompany the socodemographc trends currently observed n Brazl. In order to measure the welfare cost of ncreased watng tme for publc health provson, whch mght result from an ncrease n the number of elderly Brazlans relyng on the SUS wthout a correspondng ncrease n supply, t s necessary only to consder the effect on dfferent ndvduals n the sample f the prce of publc healthcare were to ncrease (e.g., by 50%), takng nto account the optmzng nsurance decson each person makes to ths prce ncrease. Many ndvduals who had chosen publc healthcare, for example, mght stck wth that choce and bear the brunt of the prce ncrease, whle others mght fnd t optmal to pay more and swtch to prvate healthcare. Those who had chosen prvate health coverage pror to the prce ncrease would experence no change n prce or dsposable ncome. The decsons of each ndvdual n the data set are smulated, backng-out the overall change n the prce of recevng healthcare he or she faces after all s sad and done under each of the possble values that σ mght take. The last tem consdered s the dfference n the natural logarthms of the prces ultmately faced by each ndvdual, before and after the prce change. Ths measure provdes a proportonal measure of the compensatng varaton n ncome needed to mantan the same level of utlty: 20

21 ln P H ' ln P H 1 = 1 α ' ( ln I ln I 1 H where P and I represent the prce of healthcare provson and the accompanyng requred level of ncome needed to reach the orgnal level of utlty, after the ncrease n the prce of SUS health coverage. Note that the compensatng varaton n ncome cannot be calculated drectly, because t s not possble to determne α for each ndvdual. Ths results from the fact that an ndvdual s full ncome endowment (.e., an endowment ncludng the value of avalable tme, etc.) s not observed, but only the ndvdual s monetary ncome, whch s not expended at all f SUS healthcare s employed. Ths means that t s mpossble to ultmately determne whether the dfference n log prces s attrbutable to a compensatng varaton n ncome, or to heterogenety n preferences. For the followng dscusson, the former s assumed. In order to quckly summarze the welfare mplcatons of an ncrease n the prce of SUS healthcare, lke that whch would accompany ncreasng congeston of that system, ths proportonal measure s regressed on a vector of soco-demographc attrbutes n order to determne whch groups n Brazlan socety wll suffer the most. The dfference n magntude of the effect across groups s somethng that could not be determned from the smple Probt analyss descrbed n Secton 4.1, because that analyss dd not descrbe how dfferent types of ndvduals behavors would change n response to a prce change. In all, the model (assumng σ = 1) predcts that 6.6 percent of all ndvduals consumng publc healthcare pror to the prce change would swtch from publc to prvate health coverage n response to ths smulated prce ncrease. 7 Accountng for optmzng responses s therefore mportant. The results of ths regresson, performed separately for each potental value of σ, appear n Table 7. Those n the South (.e., the excluded regon) fare worse than those n the rest of Brazl, especally the Center-West and Southeast. Blacks and those n the Mxed racal group fare worse than Whtes, whle Asans generally do better (owng to ther greater predsposton to have been usng prvate healthcare before the prce ncrease). Older ndvduals do better (as they are also more lkely to have been usng prvate healthcare n the frst place), untl they reach the age of 60, at whch pont they generally rely more on publc healthcare and do much worse. Men generally fare worse ) (5.1) 7 Note that ths number falls dramatcally as σ rses toward 3. 21

22 than women, whle those wth more educaton and hgher levels of ncome do better n the face of rsng SUS prces, agan reflectng predspostons towards usng prvate health coverage. The drectons of these effects are consstent across possble values of σ. 5.2 Analyzng the Welfare Effects of a Prvate Healthcare Subsdy The apparatus developed above also makes t possble to consder the mplcatons of counterfactual polces desgned to offset ncreasng congeston n the provson of publc healthcare, where a smple reduced-form analyss, lke that descrbed at the start of Secton 4.1, cannot. In partcular, the mplcaton can be consdered for ndvduals optmzng choces of a prvate healthcare subsdy, desgned to expand the ndvdual s budget constrant only f the ncome s used for the purchase of prvate healthcare. The welfare mplcatons of such a polcy could then (wth better data descrbng the full ncome endowment) be compared to the mplcatons of a smple ncome subsdy that could be used for any sort of consumpton, ndcatng the value of a relatvely paternalstc polcy. In the absence of such data, the welfare consequences of a smple 50% prce subsdzaton of prvate healthcare (.e., the government pays 50 cents on every 1 real spent by the ndvdual on prvate healthcare) are consdered. In order to descrbe how the resultng welfare gans (agan, a proportonal measure of the compensatng varaton n ncome, assumng homogenous preferences, after the optmzng provder of healthcare s chosen 8 ) dffer across soco-demographc groups, these gans are regressed on a vector of soco-demographc attrbutes. The results of ths regresson are descrbed n Table 8 for each of the four values of σ consdered. The drectons of each of the margnal effects are consstent across alternatve values of σ. Negatve numbers descrbe reductons n ncome that return ndvduals to ther orgnal levels of utlty (.e., ndcatng a beneft). Indvduals n the Center-West and Southeast regons seem to beneft most from ths prce subsdy, whle those n the North and Northeast beneft the least. Whtes and Asans beneft more than Blacks and those n the Mxed racal group, and those wth hgher levels of educaton beneft more than those wth less. Smlarly, rcher and older ndvduals (under the age of 60) beneft more from 8 The model (assumng σ = 1) predcts that approxmately 13.3% of all ndvduals consumng publc healthcare pror to the prce subsdy would swtch to prvate health coverage. Wth such a large ncrease n the demand for prvate healthcare, the government mght want to undertake polces to facltate entry by new prvate healthcare provders n addton to the subsdy, so as to avod new congeston costs. 22

23 the subsdy. Generally, these relatve benefts reflect a greater predsposton towards (or propensty to swtch to) prvate healthcare provson. The natural queston s how mght such a prvate healthcare subsdzaton polcy be targeted to beneft those ndvduals who would suffer most under an ncrease n the prce of publc care. To the extent that such subsdes, when appled broadly, seem to beneft hgh-ncome, hgh-educaton ndvduals n the more developed parts of Brazl, they smply represent a transfer of rents, snce those ndvduals suffer less than the poor from the ncreasng prce of publc healthcare. One possble alternatve would be to mplement the subsdy as part of an ncome tax collecton regme, where partcpaton crtera could easly be establshed so as to make the subsdy avalable only to low ncome resdents. Problems of fraud n the reportng of prvate healthcare expendtures, however, mght make ths approach dffcult. Instead, t mght be preferable to focus on the results of the frst counterfactual smulaton, and target subsdy funds geographcally so as to reach those ndvduals who lose most under the smulated ncreases n publc prces. Such s true, for example, of Black and Mxed race resdents, 9 partcularly those wth low levels of educaton and n rural areas. One possble soluton that would certanly beneft the most dsadvantaged groups would be to target subsdy funds toward lowerng the cost of prvate healthcare n rural areas, possbly by establshng new healthcare facltes n areas where none were prevously present. It s mportant to remember as well the relatvely large magntude of the negatve effect on members of the Black and Mxed racal groups of ncreasng publc healthcare prces, even n urban areas. Fnally, dealng wth the mpacts of rsng publc healthcare costs on the elderly (a major concern gven current soco-demographc trends) by subsdzng the consumpton of prvate healthcare seems especally futle, snce those over the age of 60 are predcted to beneft less than most other groups from ths polcy. Ths arses from the model s predcton that members of ths group are not as lkely to swtch to prvate health coverage even wth the change n relatve prces. Indeed, n order to lmt the adverse effects on ths group of rsng congeston n publc healthcare consumpton wthout affectng huge rent transfers to those who are less adversely mpacted, the 9 Reachng these partcular racal groups mght be dffcult, unless the subsdes took the form of mones to establsh new prvate healthcare facltes n racally segregated neghborhoods. 23

24 government wll lkely have to take steps to drectly ncrease the supply of publc healthcare provson. 6. Conclusons and Extensons The goal of ths analyss was to determne whch groups n Brazlan socety were most excluded from prvate healthcare. Prvate healthcare s generally consdered to be of a hgher qualty than ts publc counterpart; ths percepton s generally supported by the PNAD survey data. Such excluson s not of a drect form as would be racal excluson from a club, but s rather based on ndvduals facng dfferent relatve prces for publc and prvate healthcare owng to dfferences n ther observable attrbutes and preferences for healthcare consumpton. The ntal analyss of PNAD survey data documents what s generally perceved to be the case that poor, rural, Black and Mxed-race Brazlans tend to rely more on publc healthcare. Ths alone would not necessarly represent a source of socal nequty, except that the prce of ths form of healthcare s expected to ncrease n the comng decades owng to the ncreasng congeston of an already-overburdened system, and these groups are expected to suffer dsproportonately because of ther nablty to swtch to prvate health coverage. In order to determne how these prce ncreases would be dstrbuted over dfferent soco-economc groups, a more elaborate model of optmal ndvdual decson-makng s needed;.e., a model that makes t possble to determne how ndvduals would behave under current and counterfactual relatve-prce scenaros. Operatng under constrants of data avalablty, t s assumed that each ndvdual was requred to consume a sngle unt of some form of healthcare coverage (.e., publc or prvate), and that dfferences n the qualty of care across forms would be nternalzed n the prce confrontng the ndvdual. Dfferences n prce mght also arse from observable ndvdual attrbutes (.e., a drect form of dscrmnaton), or from an ndvdual s preferences for healthcare consumpton (e.g., ndvduals wth strong preferences for healthcare consumpton mght face an even hgher prce for an effectve unt of publc care than a smlar ndvdual who had weak preferences for healthcare consumpton), but avalable data do not make t possble to dentfy these effects. From a smple and stylzed model of utlty maxmzaton, t was possble to recover estmates of the prce of publc health coverage, and use those estmates to nfer whch soco-demographc groups would suffer most from an ncrease n the congeston of the publc healthcare system. The conclusons of ths analyss conform to the general perceptons regardng 24