Menno Pradhan 1,2,3. Fadia Saadah 1. Robert Sparrow 2. (Revised version September 2004)

Transcription

1 TI /2 Tnbergen Insttute Dscusson Paper Dd the Healthcard Program ensure Access to Medcal Care for the Poor durng Indonesa's Economc Crss? (Revsed verson September 2004) Menno Pradhan 1,2,3 Fada Saadah 1 Robert Sparrow 2 1 World Bank Jakarta, 2 Vre Unverstet Amsterdam, 3 Tnbergen Insttute.

2 Tnbergen Insttute The Tnbergen Insttute s the nsttute for economc research of the Erasmus Unverstet Rotterdam, Unverstet van Amsterdam, and Vre Unverstet Amsterdam. Tnbergen Insttute Amsterdam Roetersstraat WB Amsterdam The Netherlands Tel.: +31(0) Fax: +31(0) Tnbergen Insttute Rotterdam Burg. Oudlaan PA Rotterdam The Netherlands Tel.: +31(0) Fax: +31(0) Please send questons and/or remarks of nonscentfc nature to dressen@tnbergen.nl. Most TI dscusson papers can be downloaded at

3 Dd the health card program ensure access to medcal care for the poor durng Indonesa s economc crss? 1 Menno Pradhan 2, Fada Saadah 2 and Robert Sparrow 3 * September The authors would lke to thank Jan Wllem Gunnng, Maarten Lndeboom, Aparnaa Somanathan and Domnque van de Walle, and semnar partcpants at the World Bank, Tnbergen Insttute, 2001 IHEA and GDN conferences for useful comments. 2 World Bank. The vews expressed n ths paper reflect those of the authors and not necessarly those of the World Bank. 3 Vre Unverstet Amsterdam. Fnancal support from the Netherlands Foundaton for the Advancement of Tropcal Research (WOTRO) s gratefully acknowledged. * Correspondence to: Robert Sparrow, Department of Economcs, Faculty of Economcs and Busness Admnstraton, Vre Unverstet Amsterdam, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands. Emal addresses: mpradhan@worldbank.org (M. Pradhan), fsaadah@worldbank.org (F. Saadah), rsparrow@feweb.vu.nl (R. Sparrow).

4 Abstract The Indonesan Socal Safety Net (SSN) health card program was mplemented n response to the economc crss that ht Indonesa n 1997 to preserve access to health care servces for the poor. Under the program health cards were allocated to poor households, enttlng them wth subsdsed care at publc health care provders, whle the provders themselves receved budgetary support to compensate for the extra demand. Ths papers looks at the mpact of the program on outpatent care utlsaton, and, n partcular, endeavours to dsentangle the drect effect of the allocaton of health cards from the ndrect effect of the transfer of funds to health care facltes. It fnds that the program resulted n a net ncrease n utlsaton for the poor health card owners whle for non-poor health card owners the program resulted manly n a substtuton from prvate to publc provders. However, the largest effect of the program seems to have come from a general ncrease n the supply of publc servces resultng from the budgetary support receved through the SSN program. These benefts seem to have been captured manly by the non-poor. As a result, most of the benefts of the health card program went to the non-poor, even though the healthcards tself were dstrbuted pro-poor. The results suggest that n addton to the need for targetng the poor, a closer lnkage between provson of servces to the target groups and fundng would have resulted n a better-targeted program. It also ponts to potental mpact that such programs can have on the publc/prvate mx f the desgn does not take those factors nto account.

5 1. Introducton In the current debate on the provson of health care servces n developng countres, demand sde subsdes for medcal care are often argued to be more effectve n reachng the poor than supply sde nterventons. Health spendng s generally found not to be pro-poor, as publc polcy typcally lacks the ncentves for health care provders to serve the poor (World Bank, 2004). Emprcal evdence shows hgh ncome elastctes for health care, and thus large nequaltes between poor and rch, but rather low prce elastctes that tend to be larger for the poor (Jmenez, 1995; Gertler and Hammer, 1997). Targeted prces subsdes for medcal care are therefore often advocated as means to ncrease access to medcal care for the poor. The success of such targeted demand sde nterventons crtcally depends on the ablty to dentfy and reach the poor. Ths case study looks at a very partcular knd of health care nterventon that was appled n Indonesa, whch ncluded both a targeted prce subsdy and a publc spendng component. Ths combned program was part of a larger Socal Safety Net (SSN) program that was ntated to protect the poor from the effects of the Southeast Asan economc crss, whch ht the country n Households that were thought to be most vulnerable to economc shocks were allocated health cards, whch enttled all household members to the prce subsdy. Health care facltes that provded the subsdsed care receved extra budgetary support to compensate for the ncreased demand. There are some dstnct features to the SSN health program. Frst, the prce subsdy only appled to publc servce provders. Prvate sector health care provders were not ncluded n the scheme. Second, targetng and allocaton of the budgetary support to health care provders was decentralsed to dstrct commttees. However, the transfers were made drectly from Jakarta to the publc health care facltes, through specally created accounts at the post offce. Thrd, there was a loose relatonshp between the utlsaton of the health card and the compensaton that the health care provders receved n return. Compensaton was allocated to dstrcts based on the estmated number of households elgble for the health card program and not based on actual utlsaton of the health cards. 1 The SSN ncluded an educaton program, a labour creaton program and food assstance. See Ananta and Sregar (1999) and Daly and Fane (2002) for an overvew of the SSN programs. 1

6 Ths paper focuses on the effect of the Indonesan health card program on demand for prmary outpatent health care. The partcular desgn allows us to nvestgate a number of nterestng questons. Frst, t provdes the opportunty of an ex post analyss of a health care polcy change. Most studes that dscuss the effectveness of health polcy draw on smulaton based health care demand models, whch make ex ante predctons of possble polcy scenaro s gven some estmated parameters. The drawback of these smulatons s that the underlyng estmates reflect the effects of margnal changes n prce, whle the senstvty of health care demand to prce changes may well be dfferent when t concerns large dscrete umps. In effect, these smulatons often concern out of sample predcton where the forecasted nterventons le outsde the range of the observed prce data (Gertler and Hammer, 1997). Although ex post studes do not suffer from ths problem, there s relatvely lttle emprcal work that evaluates actual prcng polces n health care. Moreover, only few of these studes take account of the endogenous nature of publc nterventons n ther estmaton strategy. 2 Ths paper ams to contrbute to that lterature. Second, snce the health card only enttled the user to free servces at publc provders we can drectly nvestgate substtuton effects between prvate and publc provders. Ths s dffcult n health care demand studes, as nformaton on the prce menu offered by alternatve health care provders s often not avalable. As an alternatve to exogenous prce data many models estmate the demand for medcal care based on proxy varables derved from (endogenous) household expendture data 3 or varaton n ndrect cost measures, such as opportunty costs due to loss of work or travel tme to the nearest provder. 4 However, opportunty costs do not vary by publc or prvate provder and the same wll often hold for travel tme. For nstance, doctors workng at publc provders n Indonesa also often mantan prvate practces makng t mpossble to use travel tme varaton to estmate substtuton effects. Studes that 2 Usng data from a randomsed health nsurance and cost sharng experment n the Unted States, Mannng et al. (1987) estmate the demand for outpatent care. Gertler and Molyneaux (1997) use panel data to evaluate an experment of a user fee ncrease for outpatent servces n Indonesa. Regardng targeted health care subsdes, the Medcad program n the US s probably the most studed. Curre and Gruber (1996) and Curre and Thomas (1995) explot varaton n legslature across states to control for endogenety of the program. In an analyss of a school based health nsurance scheme n Egypt, Yp and Berman (2001) treat partcpaton as selecton on observables. 3 E.g. Gertler, Locay and Sanderson (1987), Lavy and Qugley (1993), Chng (1995), Mocan, Tekn and Zax (2000). 4 E.g., Gertler and Gaag (1990), Dow (1999). 2

7 polcy. 5 The thrd contrbuton of ths paper s that we compare the effect of a targeted do manage to dentfy prce varaton across provder types generally fnd substantal substtuton effects between publc and prvate provders as a result of publc prce prce subsdy wth that of ncreased publc health care spendng. We wll argue that the transfers made to the publc sector provders benefted all potental users whle the prce subsdy was only avalable to those who receved a health card. We make an attempt to dsentangle the two effects. In the health care demand lterature polcy scenaros such as renvestng funds (from rasng user fees, for example) nto the publc health sector s often dscussed and smulated. Whle appealng for polcy, ths requres strong assumptons about the supply response of health care provders (such as the cost structure and the performance of the government or local authortes). In case of the SSN nterventon we drectly observe effect of ncreased publc spendng wthout makng these assumptons. There are emprcal studes that use actual provder or communty data to show that an ncrease n supply and qualty of care, and especally drug avalablty at health facltes, has a sgnfcant effect on utlsaton. 6 The problem wth these qualty and supply varables s that they are often endogenous due to government polcy, and that the measured effects are lkely to capture both supply and demand effects. Whle some studes manage to control for the former problem, t s much harder to control for the latter. In ths paper we dentfy both the health card effect and the effect of the budgetary support on utlsaton, and show that the largest share of the program s effect s due to ncreased publc spendng. Fnally, we evaluate the dstrbuton of the effects of both the demand and supply sde nterventons. The lterature suggests that the poor are more senstve to prce effects than the rch. 7 But even f households receve ther health cards, there may stll be barrers to usng these benefts, such as lack of nformaton, regonal shortage of provders, or opportunty costs unabrdged by the health card. Such barrers are lkely to vary by populaton sub-group, households or even ndvdual 5 E.g., Mwabu, Answorth and Nyamete (1993); Sahn, Younger and Gencot (2003). 6 Lavy and Qugley (1993) defne qualty as the type of provder for a study n Ghana; Lavy and German (1994) fnd strong effects of supply of drugs, staff and servces; Mwabu et al. (1993), Akn, Gulkey and Denton (1995), and Akn et al. (1998) use faclty level data and fnd large effects of drug avalablty; Sahn et al. (2003) use communty level data to fnd smlarly strong effects of avalablty of drug and medcal staff. 7 E.g., Gertler et al. (1987), Mannng et al. (1987), Sauerborn, Nougtara and Latmer (1994), Chng (1995), Yp and Berman (2001), Sahn et al. (2003). 3

8 characterstcs (Blank and Card, 1991; Curre and Thomas, 1995) and are lkely to be hgher for the poor. Alternatvely, health card recpents may be reluctant to utlse ther benefts smply because of a preconcepton that subsdsed care s of nferor qualty to non-subsdsed health care (Arhn, 1994). Gven the loose relatonshp between SSN budgetary support and the actual use of health cards, t may well be that health care facltes are reluctant to provde free servces, or at least servce of smlar qualty as provded to non-subsdsed patents. In ths case the non-poor are lkely to capture a large part of the benefts from extra publc health care spendng. We fnd the effects of prce subsdy and the supply mpulse to dffer by ncome group. For lowncome groups (wth relatvely hgh prce elastcty) we fnd both a substtuton from publc to prvate care and an ncrease n total utlsaton due to the health card, but lttle effect from ncreased spendng. However, for the more wealthy groups (less senstve to prce changes) we fnd the substtuton effect to be more domnant and the supply-nduced effect of the budget ncrease to be larger, snce the rch typcally face less barrers to access to medcal care than the poor. Overall, the non-poor captured most of the beneft, despte pro-poor targetng of the scholarshps. The organsaton of the paper s as follows. The next secton gves an overvew of the data. In secton 3 we descrbe the health card program n more detal. Secton 4 focuses on the evaluaton problem and our strategy for estmatng the mpact of the health card on utlsaton of medcal servces. The results are dscussed n secton 5, whle secton 6 hghlghts some caveats and examnes the senstvty of the results to the man assumptons of the study. Secton 7 concludes. 2. The data The study s based on data from Indonesa s naton-wde soco-economc household survey (Susenas). The 1999 round of ths annual survey contaned a specal module to measure the use of the SSN nterventons, ncludng the health card program. The survey was felded n February 1999, whle the health card program started n September The results of ths analyss therefore reflect the experence of the frst months of operaton of the program. For ths reason, and data lmtatons, we lmt the analyss to the mpact of the program on the access to medcal care (n terms of utlsaton), and do not endeavour to estmate the effect on health. Health effects are lkely to take longer to materalse. The survey sampled 205,747 households and 4

9 collected a wde range of soco-economc ndcators along wth a measure of consumpton. In the area of health, the survey collected nformaton on self-reported llness, utlsaton of medcal servces, user fees and ownershp and utlsaton of the health card. We also use the 1998 Susenas as ths provdes the pre-nterventon data needed for the analyss. Ths round s also felded n February, ncludes 207,645 households and covers the same questonnare and varables as the 1999 survey, except for the SSN programs. A 1996 vllage level census (Podes) provdes pre-nterventon nformaton on accessblty and supply of health servces, and varous other communty characterstcs. The 1996 Podes ncludes 66,486 vllages (desa) and townshps (kelurahan) and can be merged wth the Susenas. Besdes the mcro data we also use admnstratve data concernng the 1998/1999 budget for the Socal Safety Net program. Ths data ncludes the budget allocated to 293 dstrcts (kabupaten) to mplement the health card program and to compensate the publc health clncs (Puskesmas) and vllage mdwfes (Bdan d desa) for the expected extra demand for health servces resultng from the health card program. The largest share of ths budget was drectly transferred to publc health care provders. The transfers were made n two to four phases, dependng on the provnce, startng n the last quarter of By the tme of the survey SSN budgets had arrved at the health centres. It provded a substantal addtonal source of fnancng for the publc health clncs. A survey conducted n June 1999 among 3,802 publc health clncs and 3,989 vllage mdwfes provdes nformaton on the way n whch the health care provders have spent the SSN funds. 3. Utlsaton of medcal servces and the health card program The economc crss ht Indonesa n the fall of 1997, exacerbated by socal and poltcal unrest n Real GDP decreased by roughly 15 percent n 1998 causng poverty to ncrease sharply. Suryahad, Sumarto and Prtchett (2003) estmate an ncrease n the poverty head count rato from 15 percent n May 1997 to 33 percent at the end of As more households moved nto poverty, nequalty n terms of household expendture also ncreased, especally at the lower end of the ncome dstrbuton (Skoufas, Suryahad and Sumarto, 2000) saw an annual ncrease n the consumer prce ndex of 78 percent. The prce of food doubled, wth rce and 5

10 staple foods experencng the most severe prce ncrease. There s lttle evdence of rsng overall unemployment durng the crss. Instead, real wages dropped by about 40 percent n the formal wage sector durng the frst year of the crss, whle agrculture seems to have absorbed part of the dsplaced labour from other sectors. (Cameron, 1999; Smth et al., 2002; Frankenberg, Smth and Thomas, 2003). The severty of the crss has undoubtedly affected households health care expendtures and utlsaton. Frankenberg et al. (2003) fnd that household consumpton declned by 20 percent n 1998, wth nvestment n human captal (.e. health and educaton) decreasng by 37 percent. Table 1 depcts observed trends n the utlsaton of medcal servces before and durng the crss. The data are based on a seres of Susenas household surveys and present utlsaton of modern health care n the month of February of each year. 8 The table ndcates a sharp decrease n the utlsaton of modern health care from 1997 to 1998, whch was largely due to declnng utlsaton of publc sector provders. A breakdown by type of provder s presented n Table 2 and shows that the declne n publc care occurs for the most part at publc health clncs. Waters, Saadah and Pradhan (2003) attrbute ths trend to a declne n the qualty of publc sector provders. The man cause for ths qualty deteroraton was the growng shortage of drugs and supples among publc facltes durng the crss, especally n rural areas (Frankenberg, Thomas and Beegle, 1999; Knowles, Perna and Racels, 1999). From 1998 to 1999 total utlsaton of modern health care provders remaned the same, but the share of the publc sector ncreased. One possble explanaton s the SSN health program, whch started durng ths perod. We wll nvestgate the emprcal foundaton of ths hypothess. 9 The SSN health program follows a decentralsed desgn, where the allocaton of health cards and funds s delegated to lower admnstratve levels. The amount of subsdy for publc health care provders to be dstrbuted across dstrcts, along wth the number of health cards to be ssued, was determned by a pre-nterventon poverty estmate. Ths poverty measure s constructed by the natonal famly plannng board (Badan Koordnas Keluarga Berencana Nasonal BKKBN) and counts the number of poor households per dstrct based on the so-called prosperty status. Under ths 8 Modern health care s here defned as publc health care provders hosptals, health clncs (Puskesmas), vllage maternty posts (Polndes) and ntegrated health posts (Posyandu) and prvate provders hosptals, doctors, clncs and paramedcal servces. Tradtonal health care s not ncluded. 6

11 defnton a household s deemed poor when they have nsuffcent funds for any one of the followng: () to worshp accordng to fath, () eat basc food twce a day, () have dfferent clothng for school/work and home, (v) have a floor not made out of earth, or (v) have access to modern medcal care for chldren or access to modern contraceptve methods. The BKKBN regularly collect ths nformaton on a census bass. Ths BKKBN prosperty measure s rather an unsutable allocaton crteron for the SSN, snce ts components are farly nflexble and napproprate for measurng economc shocks or the mpact of a crss. However, at the tme of mplementaton t was the only up to date welfare measure at hand. At the dstrct level commttees were formed to deal wth the allocaton of funds to the health clncs and vllage mdwfes. Ths allocaton was based on the BKKBN estmate of poor households elgble for a health card n the vllage or subdstrct (kecamatan) that s served by each publc provder. The transfer was not nfluenced by the actual servces provded to health card owners. The dstrct commttee allocated health cards to vllages, agan based on the BKKBN measure, where the vllage leaders headed vllage commttees. Along wth the health cards they receved gudelnes on whch crtera to use when dstrbutng the health card to households. Besdes households that were classfed as poor by the BKKBN, the vllage commttees were to consder households that were severely affected by the crss. The local leaders however mantaned a lot of leverage to dstrbute health cards accordng to ther own nsghts. Health cards were usually dstrbuted through local health centres and vllage mdwfes. The health card enttled the owner and famly members to free servces at publc health care provders consstng of (1) outpatent and npatent care, (2) contraceptves for women n chld bearng age, (3) pre-natal care and (4) assstance at brth. In ths paper we lmt ourselves to the mpact of the health card program on outpatent healthcare utlsaton. By February 1999 the health card program was already of a substantal magntude wth 10.6 percent of Indonesans reportng that ther household was allocated a health card. For the poor ths percentage s even hgher. Table 3 shows that 18.5 percent of ndvduals from the poorest quntle had a health card. For people n 9 Another explanaton for the dp n 1998 would be that households postponed preventve care, n antcpaton of the health card. But ths s unlkely because the SSN nterventons had not been announced when the 1998 Susenas survey was conducted. 7

12 the second poorest quntle (about half of whch are estmated to lve below the poverty lne at that tme) ths s 13.7 percent. So even though we are analysng the program n ts very early stages, t was already n full swng at the tme of the 1999 Susenas survey. Table 4 provdes descrptve statstcs for health card owners and others. Column 1 shows the statstcs for households wthout a health card, whle column 2 shows the characterstcs for households that dd receve a health card. It appears that households that own a health card are generally poorer, slghtly larger and work more often n agrculture compared to non-health card owners. Heads of households wth a health card have on average a lower educaton and are more lkely to be females. Utlsaton of outpatent care s hgher amongst households that own a health card, especally n case of publc servces. The utlsaton rates provded n Table 5 ndcate that 15.1 percent of the health card owners vst an outpatent provder durng a perod of 3 months, compared to 12.9 percent for the non-health card owners. Although health card owners tend to choose publc provders more often, they do not always use ther health card. 3.7 out of 10.4 percent of the health card owners report not to use the health card when seekng care at a publc provded. Also we fnd a few nstances that a health card s used whle the household head reports not to own a health card. Techncally, these type of occurrences are possble because ownershp s collected from the household head whle utlsaton s collected by ndvdual. Qualtatve research by Soelaksono et al. (1999) suggests several reasons why health card owners dd not always use ther health card for treatment. They fnd that n some publc facltes, the tme allocated to patents wth a health card was lmted, and that n remote areas the lack of access to the nearest publc faclty was a possble deterrent to use the health card. They also found strong ndcatons that patents perceved the care receved usng a health card to be of lower qualty than servces and medcnes obtaned when not usng the health card. Ownershp of health cards s dstrbuted propoor 10. The concentraton curves for ownershp and utlsaton are presented n fgure 2. The poorest 20 percent of the populaton own 35 percent of the health cards. Stll there s consderably leakage to the more wealthy households. Consderng that about 10 percent of the households receved a health card, perfect targetng would mply 8

13 that all health cards were obtaned by the poorest 10 percent of the populaton. However, we fnd that households from the wealthest 60 percent of the populaton own about 40 percent of the health cards. Utlsaton of health cards s also pro-poor but slghtly less so. Those who receved benefts were on average wealther than those who receved the card. The 1999 health faclty survey can provde some more nsght on how the SSN health funds have been used. Dsbursements to publc provders started at the end of 1998, and they were left farly free n how to utlse the funds. Table 6 shows the type of expenses for whch the health clncs chose to use the SSN health grants. The largest fracton (41 percent) of SSN health spendng concerned medcnes and 12 percent was spent on addtonal materals. In rural areas the share used for medcne s far larger than n urban areas (43 and 38 percent respectvely). The vllage mdwfes used 38 percent of the funds for medcne and 16 percent for supples, both urban and rural. Ths reflects the shortage of medcne durng the crss, suggestng that ths problem was especally relevant n rural areas. 4. Impact of Healthcard Program on utlsaton What would have been the utlsaton of outpatent health servces f the SSN health card program had not exsted? Note that ths queston comprses two effects: the effect of the health card program on the health card owners and the effect of the program on the household that dd not receve a health card. The second effect cannot be assumed to be zero as s usually assumed n an mpact evaluaton. The addtonal budgetary resources, net of what s allocated to serve health card owners at a subsdsed rate, can potentally beneft the entre populaton lvng n the area of servce of the provder. We wll analyse both effects. Our approach s to treat the two effects as two separate nterventons. One s the dstrbuton of health cards to those n need (the pure health card program), the second s a general ncrease n budgetary support to publc sector servces. The mantaned assumpton s that the frst nterventon the dstrbuton of health cards dd not have any effect on the qualty of the publc servces. It accrues 10 Followng Lanouw et al. (2002) we use the poverty lne as spatal prce deflator to control for relatve prce dfferences across regons. The argument behnd ths approach s that regonal poverty lnes capture spatal dfferences n the cost of lvng, n that they reflect the level of expenses requred for obtanng some reference level of utlty. We use the poverty lnes from Pradhan et al. (2001). 9

14 benefts only to those who actually own a health card. The second nterventon affects the whole populaton. Ths s a strong assumpton, rulng out crowdng out effects due to the health card program. We wll nvestgate the senstvty to ths assumpton later n the paper. The mpact of the frst nterventon the dstrbuton of health cards can be analysed by formng a control group from the populaton that dd not receve a health card. Snce both health card and non-health card owners benefted from the transfer of funds to health care provders, ths measures the dfferental effect of ownng a health card condtonal on the transfer program. For the second nterventon the general ncrease n the budget of publc health care provders t s not possble to create a control group from the same sample as ths nterventon affected everyone. The mpact of the total program s estmated usng a dynamc approach explotng the varaton n compensaton for the health card program to publc health clncs and vllage mdwfes across dstrcts and the fact that the allocaton to dstrcts was based on pre-nterventon poverty estmates. We analyse the utlsaton rates before the ntroducton of the health card program based on the 1998 Susenas and compare these wth the stuaton rght after the ntroducton of the health card program. The resultng mpact estmate s a result of the two nterventons actng smultaneously. The mpact of the general ncrease n fundng to publc servces s then obtaned by subtractng the former estmate from the latter. More formally, the combned average mpact of the two nterventons can be wrtten as the sum of the two mpacts separately. Let ( h q ) Y, denote the outcome for ndvdual, lvng n dstrct, as a functon of the two nterventons. If a person lves n a household that has receved a health card then h = 1, whle h = 0 for nonrecpents. q reflects the SSN budgetary support to publc health care provders n the area where the person lves (ndcated by SSN ). We want to know to what extent the observed development n utlsaton from 1998 to 1999 s due to these two nterventons. The overall mpact of the program that we want to retreve can be expressed as a weghted mean of the mpact on the populaton wth a health card (h = 1, q = SSN ) and people who dd not receve a health card, but only benefted from the budget ncrease (h = 0, q = SSN ). Assumng that utlsaton of health card owners and that of non-health card owners s ndependent, we can wrte the overall mpact as 10

15 (1) p + { E[ Y ( 1, SSN ) h = 1, q = SSN ] E[ Y ( 0,0) h = 1, q = SSN ]} ( 1 p) { E[ Y ( 0, SSN ) h = 0, q = SSN ] E[ Y ( 0,0) h = 0, q = SSN ]} where p = Pr(h = 1), the probablty of recevng a health card. [ Y (, SSN ) h = 1, q SSN ] populaton wth a health card, whle E [ Y (, SSN ) h = 0, q = SSN ] E 1 = reflects the observed average outcome for the 0 s the observed average outcome for ndvduals who dd not receve a health card. The other two terms reflect the expected counterfactual outcomes for the two groups, f the programs had not been mplemented. We can rewrte equaton (1), by addng and subtractng [ Y (, SSN ) h = 1, q SSN ] pe 0 =, as (2) p { E[ Y ( 1, SSN ) h = 1, q = SSN ] E[ Y ( 0, SSN ) h = 1, q = SSN ]} + E Y [ ( 0, SSN ) q = SSN ] E[ Y ( 0,0) q = SSN ] Here the frst two terms (weghted by p) gve the mpact of the pure health card program condtonal on the budget ncrease, for those who own a health card. We wll refer to ths as the drect effect of the program. The last two terms reflect the effect of budget ncrease for the whole populaton, whch we wll refer to as the ndrect effect of the SSN program. Frst, we concentrate on the estmaton of the drect effect of the health card nterventon. For obvous reasons, a drect comparson between health card owners and non-health card owners after the ntroducton of the program does not yeld a vald mpact estmate. The expressons above are condtonal upon selecton and snce selecton was not random, we cannot presume that E [ Y (, SSN ) h = 1, q = SSN ] E [ Y (, SSN ) h = 0, q = SSN ] 0 = 0. The health card was dstrbuted to poor households, and even wthout a health card ther utlsaton would have been dfferent from the relatvely wealther non-health card households. There are varous approaches one can take to correct for ths non-random placement of the program. A frequently used method s propensty score matchng, 11

16 whch reles on matchng on observables, and the assumpton of condtonal ndependence. 11 That s, condtonal on a set of observed characterstcs selecton nto the program can be treated as random (Heckman and Robb, 1985; Holland, 1986). Recent advances have greatly ncreased the popularty of ths method. 12 The success n reducng the systematc dfferences between the control and treatment group ncreases when more varables are used to match households. However, the more varables are used, the more dffcult t wll become to match households. Rosenbaum and Rubn (1983) proved that f t s vald to match on all of the selected varables separately, t s equally vald to match on the propensty score only. The propensty score s the probablty of obtanng treatment as a functon of the observed matchng varables. Ths result greatly reduces the dmensonalty of the problem. Instead of havng to match on several varables, t now suffces to condton on ust one varable, the propensty score. The propensty score functon can be estmated wth a logt model. The unt of our analyss s the household, as health cards were dstrbuted at ths level. Households n the treatment group are matched to households n the potental control group. Note that as a result, the sample sze of the treatment and matched control group n terms of ndvduals are dfferent as the household szes vary. The man weakness of ths method s that one cannot be sure that all systematc dfferences between the control and treatment group that nfluence utlsaton have been removed durng the match. The extent n whch the propensty score matchng wll reduce the bas depends on the specfcaton of the propensty score model and the qualty of the control varables (Heckman et al., 1997). It s therefore crucal to understand the program desgn and to nclude suffcent nformaton about the selecton procedure (at all allocaton levels) n the model. There are three sources of bas that we want to deal wth. The frst, and most obvous, s the endogenous placement of health cards wth households. Second, snce we want to estmate the pure health card effect, we want to purge t from any effects of the block 11 We expermented wth nstrumental varables but abandoned ths approach because we are not convnced that we are able to construct adequate nstruments. We used varables that measure the percepton of farness of the dstrbuton of health cards n the dstrct. But the results were very senstve to specfcaton and choce of nstrument. We also expermented wth 1997 dstrct BKKBN estmates. However, usng 1998 data we found that these varables appear to be correlated wth the level of utlsaton (but not wth changes). 12 See Imbens (2003) for a survey. 12

17 grants. Fnally, we need to take account of ncreased demand for publc servces, whch may result from the allocaton of health cards. To control for the frst stage allocaton process we nclude dstrct fxed effects. These capture any between dstrct varaton n allocaton of health cards and SSN fundng. BKKBN poverty estmates for sub-dstrcts control for allocaton of subsdy wthn dstrcts and the number of health cards ssued n the areas covered by the facltes. Thus, we are matchng households who lve n areas that enoy/suffer smlar program ntensty and smlar supply shocks n health care. At the vllage level we nclude varables from the Podes that reflect preprogram access to health care. These nclude the number of publc health clncs, auxlary health clncs and maternty facltes n the vllage, dummy varables ndcatng whether the maorty of vllage traffc s by land, and a dummy varable reflectng the vllage leaders opnon about the accessblty of health clncs. As local faclty staff dstrbutes the health cards, we nclude the number of doctors and vllage mdwfes lvng n the vllage (per 1000 nhabtants) as a proxy for nformal contacts wthn the vllage. Fnally, the level of educaton of the vllage leader s ncluded, as well as dummy varables ndcatng IDT elgblty and whether the vllage s located n a rural area. 13 For households we nclude the fve BKKBN allocaton crtera as dummy varables. Other household welfare varables refer to housng characterstcs (status of house occuped, type of roof, walls and floor, sewage, santaton and drnkng water facltes, and source of lght), sector of man source of household ncome, and employment status of the head of household. We further control for household composton (gender and age), household sze and head of household characterstcs (gender and educaton level). Per capta consumpton s endogenous snce a health card reduces health care expenses, and s therefore omtted. A household wth a health card would, on average, report a lower consumpton level than t would f t had not receved a health card. 14 If we add household expendture to the propensty score functon we would be constructng a control group that s less wealthy than the nterventon group. Consequently, we would overestmate the health card effect. 13 IDT refers to the Inpres Desa Tertnggal program, an ant-poverty program for economc less developed vllages. 14 See van de Walle (2003) for a dscusson on assumptons about behavoural responses regardng the effect of publc polcy on household consumpton. 13

18 We estmated the propensty score functon separately for fve man regons n Indonesa. 15 In ths way we restrcted the match to households lvng n the same regon. A household wth a health card lvng n Java could for nstance, never be matched wth a household wthout a health card lvng n Sumatra. The reason for dong so s that we beleve that there are unobserved characterstcs whch vary by regon that nfluence the effect that other varables have on the probablty of recevng a health card. The Pseudo R-squared for the regonal models ranged from 0.12 to Households that own a health card are matched to households wthout a health card, based on the estmated propensty score. There s a varety of matchng methods that can be appled (Dehea and Wahba, 1999; Dehea and Wahba, 2002; Imbens, 2003). We mplemented nearest neghbour matchng, the smplest matchng procedure. For each household n the treatment group we selected a control-household wth the nearest value of the propensty score. Ths way of constructng a control group bascally bols down to re-weghng the potental control group. Those households that are not matched receve a weght of zero, those who are matched once receve a weght of one, and those matched more than once receve a weght hgher than one. The choce between allowng matchng wth replacement or wthout nvolves the trade-off between ncreasng precson and reducng the bas. Matchng wth replacement wll gve the least based estmate, but reduces precson of the estmate, as the weghts for multple matched observatons ncrease the varance. The drawback of matchng wthout replacement s that t yelds a shortage of possble matches for those households wth a hgh propensty score. We used the rule that when the match obtaned wthout replacement had a propensty score that dffered more than from the propensty score of the household n the treatment group, we resorted to matchng wth replacement. If no match was found wthn a radus of we dd not match the household to a control. The qualty of match s best llustrated usng a graph. Fgure 2 graphs the dstrbuton of the propensty score for the matched households n a hstogram, whle Table 7 depcts the dstrbuton of the propensty score for the nterventon group, potental controls and households matched more than once. The number of matched 15 The 5 regons we defne are () Java and Bal, () Sumatra, () Sulawes, (v) Kalmantan and (v) Other Islands. 16 The estmaton results for the propensty score functon are avalable upon request from the authors. 14

19 household s decreases as the probablty of selecton ncreases. The regon of overlappng support ranges from to Households outsde ths range are not consdered n the matchng procedure. The matched households are very smlar on the bass of the ndvdual observed characterstcs, whch entered nto the matchng functon. Ths s evdent from Table 4, where column 2 and 3 present the descrptve statstcs for the matched samples, and columns 4 and 5 show the dfference n means of the covarates. The top panel presents varables that were ncluded n the matchng functon, and shows that the two samples are well balanced across the observed characterstcs. The second panel shows that the dstrct dummy varables managed to control for the supply shock n the matchng process. Both program ntensty varables are balanced for the matched households, whle they dffer strongly for the non-matched households. The dfferental mpact of ownershp of a health card s estmated by comparng utlsaton patterns of the treatment and matched control group. Comparng means yelds the average mpact of the pure health card nterventon on health card owners. It can easly be obtaned by estmatng the regresson (3) Y = δ + β HC + ε on the matched sample applyng sample weghts. βˆ s an unbased estmate of the pure treatment effect for those who are selected nto the program, [ Y (, SSN ) h = 1, q = SSN ] E[ Y ( 0, SSN ) h = 1, q SSN ] E 1 = n equaton (2). The pure health card effect s then ˆp βˆ selecton nto the program ( pˆ = Pr(h = 1) )., where pˆ s the estmated probablty of The overall mpact of the program, as defned n equaton (1), s obtaned by explotng regonal varaton n the fnancal compensaton for the health card program to publc health care provders. We assume that the ncrease n fundng wll capture the combned drect and ndrect effects. Later n the paper we evaluate the robustness of ths approach. To measure the varaton n SSN compensaton we use admnstratve data concernng the 1998/1999 budget that was allocated for transfers to publc health facltes. The varaton was substantal. For example, we found that the amount of compensaton, weghted by the dstrct populaton sze, n Sulawes s 15

20 29 percent hgher than n Sumatra and 34 percent hgher that n Java/Bal, but about half of what s allocated to the smaller slands (Table 8). We model the effect of the general ncrease n fundng as a lnear functon of the budget allocaton. For dstrct, n tme perod t, the utlsaton of health servces s wrtten as 5 SSN t ' (4) Yt = α + θ0dt + θ rdrdt + γ + φ W t + ε t N r = 2 t where SSN s the amount of compensaton for publc health clncs allocated to dstrct, N denotes the dstrct populaton sze. Subscrpt t ndcates tme and refers to ether the tme perod before the nterventon (1998) or the tme perod after the nterventon (1999). We nclude a tme dummy varable, takng value d t = 0 f t = 1998 or d t = 1 f t = The tme varable has been nteracted wth 5 regon specfc fxed effects, d r, n order to allow for some flexblty n capturng the tme effect. 17 In the pre-nterventon year SSN equals zero for all dstrcts. We also add a set of regonal welfare and demographc characterstcs, W t, to the model. These nclude the poverty profle of the dstrcts 18, the average age and household sze, the dstrct populaton sze, and the fracton of the populaton lvng n a rural area. Frankenberg et al. (2003) show evdence of changes n household sze, mgraton between urban and rural areas due to households restructurng ther composton n response to the crss. Whle the average household sze ncreased n (lower cost) rural areas, the number of workng age famly members ncreased n urban households. The non-random allocaton of the SSN budget s accounted for by a dstrct fxed effect, α. Ths removes any bas due to unobserved tme nvarant factors that affect geographc allocaton and are also correlated wth health care utlsaton. The fact that the SSN budget allocaton was determned by statc pre-program poverty estmates, the BBKBN classfcaton, and not on the bass of dynamc changes n poverty legtmses the fxed effects approach. Takng dfferences across dstrcts over tme gves 17 Java and Bal (regon 1) are used as reference group. 18 The poverty profle s portrayed by the poverty rate (P 0 ) and poverty gap (P 1 ), wth P = q α n 1 = 1 (1 c / pl) α, where pl s the poverty lne and q the number of ndvduals for whch c pl (Foster, Greer and Thorbecke, 1984). 16

21 5 SSN 99 ' (5) Yt = θ0 + θ rdr + γ + φ W t + ε t N r = 2 99 Estmatng (5) by OLS yelds unbased estmates under the assumpton that the allocaton of SSN funds s not correlated wth tme varant unobservables. If the geographc allocaton s correlated wth mportant dstrct-level trends that are not captured by the tme dummes or W t, then OLS estmates may stll be based. Ths s not very lkely, gven that the BKKBN ndces are badly suted for capturng the changes n welfare. Further reassurance s gven by the fact that we fnd no correlaton between SSN allocaton (per capta) and changes n utlsaton from 1998 to The overall mpact of the program s then obtaned by takng a populaton weghted average of the effects for the dstrcts J SSN N (6) γˆ = γˆ SSN N N = 1 where SSN s the average fnancal compensaton for the health card program per person across the country, and J the number of dstrcts. The estmated mpact of the supply mpulse on the utlsaton of outpatent servces (.e., the ndrect effect) s gven by the dfference between the estmate of the average total effect and the average pure health card. Insertng (6) and the estmate of β n (3) nto (2) yelds an expresson for the mpact of the general budget ncrease for publc servce provders (7) E[ Y ( 0, SSN ) q SSN ] E[ Y ( 0,0) q SSN ] γˆ SSN pˆ βˆ = = = 5. Results The estmaton results of the pure health card effect on outpatent utlsaton for health card owners (β ˆ) and the average pure effect ( p ˆβ ˆ ), are gven n Table 9. The estmate of pˆ s smply the fracton of ndvduals lvng n a household that owns a health card. The table also shows contact rates for outpatent servces for the matched 17

22 nterventon and control groups, and the percentage change relatve to the counterfactual. The effects are estmated for reported utlsaton over a one-month reference perod. 19 Health card ownershp resulted n a relatve ncrease n the use of outpatent servces of 9.1 percent, and an absolute ncrease of 1 percentage pont. Ths ncrease was due to an ncrease n utlsaton from the poorest four quntles, whle for the rcher quntle we only observe a substtuton effect from prvate to publc health care provders. The hghest ncrease, relatve to the base, s seen for the thrd quntle (16.8 percent), followed by the poorest group (14.2). For all ncome groups health card ownershp resulted n an ncrease n the use of publc sector servces and a decrease n the use of prvate sector servces. For the rchest quntle the two effects cancelled out, as we see a small, statstcally not sgnfcant, ncrease n overall utlsaton. The shft from prvate to publc care seems to have occurred n both urban and rural areas. The health card program affected utlsaton amongst women more than t dd amongst men, possbly because of the maternty servces covered under the health card program. Both the overall ncrease n outpatent vsts and the substtuton effect from prvate to publc were larger for women. Table 11 presents the estmates of γ from equaton (5), and the estmates of the overall effect of the program ( γ ˆSSN), defned n equaton (6). These estmates are also based on a one-month reference perod. The results ndcate an absolute ncrease n the use of publc sector servces of 0.5 percentage pont, whle the program does not affect the use of prvate sector servces. We fnd that the effect s larger for the wealther quntles. For the frst and thrd quntles the estmates are small and not sgnfcant. As wth the pure health card effect, the overall effect of the program on publc servces s larger for females than for males. The program had the largest mpact on the use of publc care n rural areas, whle for urban areas the estmates are not precse. Snce prvate care seems unaffected, we fnd smlar results for the overall effect on utlsaton. The ndrect effect, whch could be attrbuted to an overall supply or qualty mpulse as a result of the extra budget support n the publc sector, seems to have been 19 Each year the Core of the Susenas collects utlsaton usng a one-month reference perod. We also estmated the effects based on a three months reference perod, whch was used n the 1999 SSN module. However, these data may partly reflect pre-nterventon outcomes, so we need to be careful 18

23 a man contrbutor to the ncrease n the use of publc health care servces. Combnng the estmates n Table 11 wth those referrng to the one month reference perod n Table 9 allows us to nvestgate what share of the ncrease n the use of publc sector servces s due to the ndrect effect (as defned n equaton (7)), and to the pure health card effect. The share of the ndrect effect to the total effect s gven by ( pˆ β ˆ) /( γˆ )) 1 SSN. About 80 percent of the overall ncrease n utlsaton s a result of the ndrect effect. In the publc sector about half of the total ncrease can be attrbuted to the ndrect effect of the budget ncrease. The results also suggest that the ndrect benefts of the program ncrease wth ncome. For the rchest quntle only 7 percent of the ncreased utlsaton of publc care can be attrbuted to the health card tself, whle for the poor there s no evdence of any ndrect effect. Fnally, the supply mpulse had an above average effect n rural areas, emphassng the shortage of resources wth rural publc health care provders. So can the revval of the publc sector utlsaton be attrbuted to the Socal Safety Net Program? It appears to be. The estmates reported n Table 11 can be used to estmate the utlsaton f the health card program had not exsted. From (6) t shows that the mpact on overall utlsaton s the estmate of γ tmes the average compensaton to health care provders ( SSN ). The results ndcate that health card program ncreased outpatent contact rate by 0.55 percentage pont and the contact rate at publc facltes by 0.47 percentage pont. In Table 1, where we reported the trends n health care utlsaton, we added the counterfactual of what would have been publc and prvate sector utlsaton n absence of the health card program. From 1998 to 1999 the contact rate for publc sector servces ncreased from 5.0 to 5.3 percent, whle the contact rate for modern health care provders remaned stable at 10.5 percent. The estmates suggest that wthout the health card program publc sector utlsaton would have dropped further to 4.9 percent, and the overall contact rate would have dropped to 10.0 percent. nterpretng these results. Nevertheless, the estmates show a smlar mpact as the one-month recall perod. These results are avalable upon request from the authors. 19

24 6. Caveats and senstvty analyss Crowdng out The man assumpton underlyng our study s that utlsaton of health card owners s ndependent from that of non-health card households. Ths mples that the number of health card recpents (.e., the program ntensty) n the regon does not affect utlsaton of care for non-recpents. However, f health care supply would be nelastc, then dstrbutng health cards could lead to a crowdng out effect. Resources would be redstrbuted from non-recpents to health card recpents. In ths case the estmated drect effect of the health card wll be based upward. The dfference n utlsaton would consst of the true health card effect and the crowdng out effect. One mght argue that the crowdng out effect s lkely to be small. Snce health card coverage s 11 percent and concentrated among the poor whose health care demand s typcally low, t s unlkely that the program would serously stran the capacty of health care facltes. We can test ths argument by controllng for health card ntensty when we estmate the drect effect, by ncludng the average number of health cards dstrbuted n the dstrct. We also nclude the sub-dstrct allocaton crtera and vllage level characterstcs to capture program ntensty at lower admnstratve levels. If the estmated drect effect s ndeed based upward by crowdng out effects then we would expect the results to be senstve to these control varables. The results n Table 10 suggest that the estmated drect effect s not based due to crowdng out effects. Specfcaton (1) controls for a set of ndvdual and households characterstcs, IDT vllage and rural area dummes, and the avalablty of health facltes n the vllage. Specfcaton (2) adds the sub-dstrct BKKBN ndex, program ntensty at dstrct level, and the poverty profle (P 0, P 1 ). The fracton of the populaton wth a health card and the SSN budget per capta allocated to the dstrcts reflect program ntensty. The estmated effects do not change much, and reman wthn one standard devaton from the estmates n Table 9. Interacton effects It s possble that the benefts of the health cards depend on the sze of the SSN grants allocated to an area. The qualty of care provded to health card owners may well ncrease wth the fnancal compensaton. So far we have gnored nteracton effects 20