The Price Elasticity of Demand for Pharmaceuticals amongst High Income Older People in Australia: A Natural Experiment

Transcription

1 Unversty of Wollongong Research Onlne Faculty of Busness - Economcs Workng Papers Faculty of Busness 2008 The Prce Elastcty of Demand for Pharmaceutcals amongst Hgh Income Older People n Australa: A Natural Experment Peter M. Smnsk Unversty of Wollongong, smnsk@uow.edu.au Publcaton Detals Smnsk, P, The Prce Elastcty of Demand for Pharmaceutcals amongst Hgh Income Older People n Australa: A Natural Experment, Workng Paper 08-02, Department of Economcs, Unversty of Wollongong, Research Onlne s the open access nsttutonal repostory for the Unversty of Wollongong. For further nformaton contact the UOW Lbrary: research-pubs@uow.edu.au

2 Unversty of Wollongong Economcs Workng Paper Seres The Prce Elastcty of Demand for Pharmaceutcals amongst Hgh Income Older People n Australa: A Natural Experment Peter Smnsk Unversty Of Wollongong WP February 2008

3 The Prce Elastcty of Demand for Pharmaceutcals amongst Hgh Income Older People n Australa: A Natural Experment Peter Smnsk 1 February 2008 Abstract Ths paper estmates the prce elastcty of demand for pharmaceutcals amongst hgh-ncome older people n Australa. It explots a natural experment by whch some people ganed enttlement to a prce reducton through the Commonwealth Senors Health Card (CSHC). To the author s knowledge, ths s the frst study of the prce elastcty of demand for pharmaceutcals amongst older people that draws on a natural experment wth a control group. The preferred model s a nonlnear Instrumental Varable (IV) dfference-n-dfference regresson, estmated on natonally representatve repeated cross sectonal survey data usng the Generalsed Method of Moments. No sgnfcant evdence s found for endogenous card take-up, and so cross-sectonal estmates are also consdered. Takng all of the results and possble sources of bas nto account, the headlne estmate s -0.1, mplyng that quantty demanded s not hghly responsve to prce. JEL codes: D12; H42; I11 Keywords: prce elastcty; pharmaceutcals; Australa 1 I thank Garry Barrett and Peter Saunders for many useful dscussons and suggestons. I acknowledge the helpful comments and suggestons provded by partcpants at several semnars and conferences, partcularly Martn Ravallon, Thomas Buchmueller and Bruce Bradbury. I gratefully acknowledge the fnancal support provded by the Unversty of New South Wales and the Centre for Health Servce Development at the Unversty of Wollongong. Any errors of fact or omsson are the responsblty of the author. 1

4 1. Introducton Expendture on pharmaceutcals n Australa and n many other countres has ncreased consderably n recent years. Between 1995 and 2004, t ncreased relatve to GDP n 21 of 24 OECD countres for whch data are avalable. The Unted States had the largest relatve ncrease, from 1.2% to 1.9% of GDP (OECD, 2007: 8-9). In Australa, total pharmaceutcal expendture was A$10.9 bn n ($536 per person), havng ncreased annually by 8.9% n real terms over the prevous decade (Australan Insttute of Health and Welfare, 2006: 105; 64). These ncreases have prompted concerns over sustanablty and cost contanment of pharmaceutcal nsurance, partcularly publc nsurance such as Australa s Pharmaceutcal Benefts Scheme (PBS). The prce elastcty of consumer demand determnes how total expendture responds to prce. It s also a key parameter n assessng the optmal level of co-payments, gven the trade-off between the utlty gan of rsk-poolng and the loss assocated wth moral hazard (Arrow, 1963; Pauly, 1968; Mannng & Marqus, 1996). Older people account for a dsproportonate share of pharmaceutcal consumpton. In Australa, government PBS expendture per capta on those aged 65 and over s 7 tmes hgher than on those aged under 65 (calculated from Australan Government, 2007b: Table C2). Contnung structural ageng of the populaton wll ensure that ther share of pharmaceutcal expendture wll contnue to grow. In Australa, t s expected that people wll be ncreasngly affluent n retrement (Australan Government, 2007b: Chart C6). The am of ths paper s to present estmates of the prce elastcty of demand for pharmaceutcals amongst hgh-ncome older people n Australa. I explot a change n the ncome elgblty threshold for the Commonwealth Senors Health Card (CSHC). Holders of CSHC s, or another concesson card, pay a much lower contrbuton than general patents. Ths natural experment s assumed to represent an exogenous prce change for those who take-up the card. The remander of ths paper s organsed as follows. Secton 2 revews prevous studes of the prce elastcty of demand for pharmaceutcals. Ths s followed by a descrpton of the CSHC natural experment n Secton 3. I descrbe the methods, data and present descrptve statstcs n Secton 4. The effect of the CSHC on prce s dscussed n Secton 5. The fnal two sectons present results and a concluson. Results of alternate specfcatons are contaned n an Appendx. 2

5 2. Prevous studes The RAND health nsurance experment remans the most sgnfcant work on demand for health care (Newhouse & The Health Insurance Experment Group, 1993). Usng these data, the prce elastcty of demand was estmated to be to for health care overall and perhaps slghtly larger for outpatent care (between 0.17 and 0.31) (Mannng et al., 1987). To the author s knowledge, the prce elastcty for drugs was never calculated from the RAND data. These cannot be derved from publshed results because of the mpact of the maxmum dollar expendture ncluded n the plans. However, the predcted demand response for drugs (Lebowtz et al., 1985: Table 4) s very smlar to that of outpatent care (Newhouse & The Health Insurance Experment Group, 1993: Table 3.2). Indeed Lebowtz et al. (1985) found no statstcally sgnfcant dfference for all but one of the stes consdered. Whlst ths result can be regarded as a benchmark, there are lmtatons to what can be drawn from the results. The RAND experment was conducted around thrty years ago and t dd not nclude older people n the sample. Insttutonal dfferences between countres may also play a role. Rce & Matsuoka (2004) consder whether prce elastcty amongst senors may be dfferent to that of younger people. Determnants nclude necessty, avalablty of substtutes and the proporton of ncome spent on the product. Senors are more lkely to have chronc alments, for whch drugs are necessary and for whch there s lttle substtute treatment. These two factors would lead them to be less responsve to prce. On the other hand, they generally spend a greater proporton of ther ncome on pharmaceutcals, whch would have the opposte effect. Ths s less lkely, however, for a hgh-ncome populaton. It s therefore hypothessed that the populaton of hgh-ncome older people are less responsve to prce than younger or poorer groups. There are few studes of responses to prce n demand for pharmaceutcals for Australa and all rely on tme seres methods. The most relevant s by McManus et al. (1996) who estmated the effect of the ntroducton and ncrease n co-payments n 1990 and 1992 on the pharmaceutcal consumpton of communty patents and a group of elderly returned servcemen and women. Whlst they do not provde an elastcty estmate, ths can be calculated from ther results for the group of returned servce people. For ths group, the ntroducton of a $2.50 co-payment was assocated wth a decrease n consumpton by 3

6 around 20% for both essental and dscretonary drugs, mplyng an arc elastcty of around Ths calculaton gnores the ncome effect assocated wth the concurrent ntroducton of a pharmaceutcal allowance. But ths allowance was only $135 per year (equal to 1.7% of the servce penson) and so the resultng bas would be small f not neglgble. Explotng ncreases to the co-payment for general patents n 1986, Johnston (1991) estmated a much larger prce elastcty of 0.47 for hgh prce pharmaceutcals and 0.24 for safety net (hgh user) patents. Relyng on earler, smaller co-payment ncreases for general patents Harvey (1984) estmated an elastcty of between 0.1 and Rce & Matsuoka (2004) revewed North Amercan studes on the mpact of cost-sharng on the health and health servce utlsaton amongst senors aged 65 and over. They dentfed sxteen studes that analysed prescrpton drug use, most of whch found evdence of a declne n utlsaton assocated wth cost-sharng. Fve of these exploted natural experments, three of whch related to the same polcy change n Quebec. None of the studes revewd by Rce & Matsuoka (2004) reported estmates of prce elastcty. More recently, Contoyanns et al. (2005) estmated prce elastctes usng the same Quebec natural experment, whch were between and for the group of people aged 65 and over. However, ther study was lmted by the absence of a comparson group. It reled on tme trend terms to capture dfferences over tme. An example of an effect that could not be accounted for s the ntroducton of ncome-contngent Pharmacare premums, whch concded wth the prce change. These may have nfluenced consumpton through an ncome effect. The study also estmated elastctes for sub-populatons stratfed by ncome. For the low-ncome populaton, the elastcty was close to zero (an average of across expendture decles). In contrast, t was large (an average of -0.69) for the hgh-ncome populaton, wth the mddle-ncome populaton roughly mdway. The subject of the present study s a hgh ncome populaton. 4

7 3. The Commonwealth Senors Health Card Natural Experment The Pharmaceutcal Benefts Scheme (PBS) s Australa s unversal system of pharmaceutcal nsurance. For lsted medcatons, co-payments are capped at a fxed amount (the copayment), whch does not vary wth the full cost of the medcne. 2 The PBS s a two-tered system, wth general and concesson components. Concesson patents nclude pensoners, the unemployed and low-ncome earners. Snce 1990, all concesson cardholders have been requred to make a small co-payment, but t has remaned much smaller than the general contrbuton. Both classes of patents are also covered by a safety net. Concessonal patents who reach the expendture threshold n a gven year are not requred to make co-payments on addtonal purchases. General patents who reach ther threshold pay the concessonal prce for addtonal purchases. By way of llustraton, the resultng (non-lnear) prce schedule s shown for general and concessonal patents for 1995 (Fgure 1). 2 Two qualfcatons are necessary. A patent may be requred to pay a Brand Premum or Therapeutc Group Premum f they choose more expensve medcatons nstead of cheaper medcatons that are judged to be of equal medcnal value. Secondly, where the medcaton s full cost s lower than the notonal co-payment, the patent pays the full cost. 5

8 Fgure 1 Indcatve Prce Schedule for PBS Pharmaceutcals for General and Concessonal Patents, 1995 (AU $ per prescrpton)* Source: Australan Government Department of Health and Ageng (2007) * Ths schedule s llustratve, snce some lsted pharmaceutcals are prced below the level of the general copayment. The prce also excludes any Brand Premum (the Therapeutc Group Premum s not relevant as t was not ntroduced untl 1998). These ssues are dscussed further n Secton 5. The horzontal axs s also ndcatve, snce the safety net s nvoked after expendture crosses a threshold, rather than the actual number of prescrptons. For ths fgure, t s assumed that all prescrptons are purchased at the full co-payment prce. The Commonwealth Senors Health Card (CSHC) was ntroduced n July Its orgnal purpose was to provde a concesson to people of age penson age who met the ncome elgblty test, but who dd not receve an age penson for other reasons. The majorty of such people were excluded from the age penson due to ts assets test or resdency requrements. The reform of analytcal nterest was a large ncrease n the CSHC ncome elgblty threshold. In January 1999, the threshold was almost doubled to $40,000 per annum for sngles and $67,000 for couples. Income was defned as the prevous year s taxable ncome, adjusted for rental property losses, foregn ncome and frnge benefts. It was not ndexed to nflaton. It was ncreased nomnally n July 2000 and more substantally n July 2001, to $50,000 for sngles and $80,000 for couples (Australan Government, 2007a: Secton ). A tme seres of ths threshold for couples s shown n Fgure 2, and the 6

9 correspondng pattern for sngles has a smlar pattern. The real value of the 1995 threshold s also shown for all years. An ncome that falls between the two lnes would enttle a coupled person to a concesson card at that pont n tme, but not pror to Fgure 2 CSHC Income elgblty thresholds for couples (1995 AU $ 000s per annum) Source: Australan Government (2007a) 4. Methods, Data and Descrptve Statstcs 3 Prce elastcty of demand s defned as the percentage change n quantty demanded dvded by the percentage change n prce, other thngs equal. The formula used to estmate the arc elastcty assocated wth a dscrete prce change s the mdpont formula: C1 C0 P1 P0 E (1) C C ) / 2 ( P P ) / 2 ( Analyss was conducted usng Stata V9.2 and SAS V9. 7

10 where C 1 -C 0 s the estmated effect on consumpton of a prce change equal to P 1 -P 0. The approach taken n ths paper s to separately estmate the effect of health care card possesson on consumpton, and the effect of a health care card on prce. To reflect ths, the subscrpt notaton n (1) s changed to: CH 1 CH 0 PH 1 PH 0 E (1a) C C ) / 2 ( P P ) / 2 ( H 1 H 0 H 1 H 0 where and C H=1 and C H=0 are the expected consumpton wth and wthout a health care card, and smlarly for prce, P. All the methods descrbed below estmate Marshallan (uncompensated) own prce elastctes for pharmaceutcals. These elastctes nclude the pure prce effect and the ncome effect of a prce change. However, the compensated and uncompensated elastctes are almost dentcal n the present analyss, snce the share of total ncome spent on the relevant good (PBS pharmaceutcals) s small. To llustrate, consder the Slutsky equaton, expressed n terms of elastctes: e M e H s x P x P xe M,, x, I Where M x represents Marshallan demand and 8 H x represents Hcksan demand. Ths equaton states that the Marshallan prce elastcty of demand s equal to the Hcksan (compensated) prce elastcty of demand mnus the share of ncome spent on x multpled by the ncome elastcty of demand. The methods n ths paper drectly estmate the term on the left hand sde. The pure prce elastcty s the frst term on the rght hand sde. For the populaton studed here, the share of ncome spent on PBS pharmaceutcals s approxmately 1%. Assume that the ncome elastcty s large (say 1.3 as estmated by Moran & Smon, 2006). The two prce elastctes would dffer by 0.01 * 1.3 = The pure prce elastcty wll be slghtly smaller (slghtly less negatve) than the uncompensated elastcty. Snce the dfference s of trval magntude, ths ssue wll not be gven further attenton. The rest of ths secton s devoted to the methods used to estmate the frst term n equaton (1a). However, the non-lnear prce schedules make the second term nontrval as well. The estmated effect of the health care card on prce s dscussed n secton 5.

11 4.1 Dfference-n-Dfferences wth Instrumental Varables In the economc evaluaton lterature, the expected effect of a treatment on the treated (denoted Gan) s the dfference n the expected outcome (Y) between treated ndvduals and ther expected hypothetcal outcome n the absence of treatment. T T E( Gan) E( Y T 1) E( Y T 0) (2) where Y T s the outcome for members of the treatment group and T denotes treatment. The second term n (2) s the mssng counterfactual, snce t s unobserved. Wth panel data or repeated cross sectons, we observe the outcome at two ponts n tme. Gan can be redefned as the expected mpact on the change n outcomes over tme: T T T T E( Gan) E( Y1 Y0 T 1) E( Y1 Y0 T 0) (3) In the dfference-n-dfference model, a comparson group s selected whch s not subjected to treatment. Change over tme n the outcome for the comparson group s assumed to be equal to that of the treatment group n the absence of the nterventon: C C T T E( Y1 Y0 T 0) E( Y1 Y0 T 0) (4) Where Y t C denotes the outcome at tme t for members of the comparson group and Y t T denotes the outcome for members of the treatment group. Substtutng (4) nto (3) enables the treatment effect to be estmated as a functon of observed outcomes: T T C C E( Gan) E( Y1 Y0 T 1) E( Y1 Y0 T 0) Snce other observable characterstcs (X) may change over tme heterogeneously between groups, E(Gan) can be estmated n a lnear regresson model: Y t t G G t X t t where G = 1 f the ndvdual s n the treatment group (before or after treatment) and zero otherwse, t = 0 n the pre-nterventon observaton and 1 n the post-nterventon observaton. The parameter represents E(Gan). In the dfference n dfference model, treatment (T) s assumed to be assgned. In other applcatons, treatment s not assgned, but rather, elgblty s assgned through a polcy 9

12 change. In the case of the CSHC, relatvely hgh ncome elderly people (G=1) ganed elgblty at t=1. Not all people who were elgble took-up the card. People self-select and so treatment may be endogenous. Some members of the treatment group also possessed a card pror to treatment. If, however, there s a strong correlaton between Gt and health concesson card status (H): P(H=1 Gt=1,X) >= P(H=1 Gt=0,X) and ths polcy change can be assumed to be exogenous, then the polcy change can be used as an nstrument for health care card status. In ths approach, the estmated effect s the Local Average Treatment Effect for those who took up the card (Imbens & Angrst, 1994). Thus the lnear dfference-ndfference nstrumental varable model s: Y t b0 b1t b2g b3h X t t (5) where H G t t G X t t and hence Gt s the nstrument for H. The key assumpton n ths lnear model s that the tme trend (n levels) s common to both groups. Alternatve assumptons, such as a common trend n logs are also possble. I return to the ssue of constant trends n levels or logs n secton 4.3, by consderng two postnterventon samples. 4.2 Data The analyss was conducted on repeated cross-sectonal Natonal Health Surveys (NHS) of 1995, 2001 and The NHS s a natonally representatve survey conducted by the Australan Bureau of Statstcs. The surveys were conducted face-to-face and the sample szes were 52,838; 26,863 and 25,906 persons respectvely (Australan Bureau of Statstcs, 1996; 2003; 2006). A treatment group was selected n each year. It conssts of people aged 65 years and over whose real ncome (nflaton adjusted) would have qualfed them for a CSHC after the polcy change, but not n A frst comparson group conssts of people n the same age group, but wth ncomes that would qualfy for a concesson card n every year. A second comparson group conssts of men aged and women aged whose ncomes are n 4 The Basc Confdentalsed Unt Record Fles (CURFs) were used. 10

13 the same range as the treatment group. 5 A thrd comparson group, consstng of hgher ncome older people who would not qualfy them for a CSHC n any year was also consdered, but abandoned due to small sample sze. The groups were selected under the same crtera n each year rather than followng partcular cohorts over tme. Thus I assume no cohort specfc effects on drug consumpton. It s noted that the groups are selected wth error for several reasons. Income as recorded n each NHS corresponds to the ABS current ncome measure. Ths s derved from the amounts receved n the prevous fnancal year from busness and property and the current amount usually receved from wages and salares and other ncome (Australan Bureau of Statstcs, 1996). In contrast, ncome for the purpose of CSHC elgblty s annual ncome n the prevous year, or an estmate of annual ncome for the current year f a change n crcumstances can be demonstrated (Australan Government, 2007b: Secton ). Each member of a couple reported ther own ncome n In the other two years, one person reported ther own and ther spouse s ncome. In , ncome of couples was not dstngushable from that of other household members. Thus couples who lved wth anyone else were excluded from all years. Income s provded n ranges. However, by usng all avalable ncome varables (ncludng ncome ranges; ncome decles and equvalsed ncome decles), t was possble to utlse what appear to be rather successful approxmatons to the ncome thresholds. 6 Fgure 3 shows the deal ncome range for selectng the treatment group amongst sngle and coupled respondents and the approxmatons that were used. The boxes wth a dagonal fll pattern 5 The age elgblty threshold for women s gradually ncreasng from 60 to 65 years. The threshold was 60 years at the start of 1995 and t had ncreased to 62.5 by June Snce age s provded n fve-year categores on the fles, women aged have been excluded from all analyss. 6 In NHS 1995, the groups were selected usng a categorcal personal ncome varable for the respondent (and ther partner where applcable) and a varable for decle of equvalsed ncome of ncome unts. The equvalence scale used by ABS n the NHS 1995 fle was a smplfed Henderson scale. In NHS 2001, groups were selected usng categorcal varables for personal ncome, ncome unt ncome and decle of (modfed OECD) equvalsed ncome of ncome unts. In NHS , groups were selected usng the categorcal varables for decle of personal ncome and decle of (modfed OECD) equvalsed household ncome. ABS provded the ncome ranges whch correspond to each categorcal ncome varable. For the equvalsed varables, these ncome cut-offs were unequvalsed, thus dervng raw ncome ranges whch correspond to each category of the equvalsed varable. These cut-offs dffer by household composton (or ncome unt type) as defned by the relevant equvalence scale. 11

14 denote partal coverage for couples n The box wth a horzontal fll pattern for couples n 2001 represents an ncome range that was not used n the man analyss, but the results are not senstve to ts ncluson as reported n the Appendx. Fgure 3 Ideal and proxy ncome thresholds for selecton of treatment and comparson groups (2001 AU $ per week) 7 Ths results from two factors. One s the addton of two ncomes presented as ranges (one for each member of the couple). The other s due to the process of convertng equvalsed ncome decle cut-offs nto cash ncome. The equvalence scale used by ABS n 1995 s a smplfed verson of the Henderson Scale, whch dffers accordng to labour force status (but not age). 12

15 Table 1 shows the resultng sample sze by year and group. Whlst the overall sample s large, the number of observatons n the treatment group s consderably smaller. Table 1 also shows the percentage of people n each group who have a health care card, suggestng that the polcy change s strongly correlated wth health care card status. Health card coverage ncreased by 31 percentage ponts between 1995 and 2001 and by 36 percentage ponts between 1995 and Among the comparson groups, dfferences n concesson card coverage over tme were no greater than 4 percentage ponts. However, 43.2% of the treatment group had a health care card n Ths mples that a large proporton of the treatment group receved treatment pror to the nterventon and are hence msclassfed. Ths s not a problem for the IV approach under the assumpton that the factors causng msclassfcaton n 1995 affect the same proporton of the treatment group n other years. Thus the reasons for msclassfcaton requre scrutny. The majorty (82.2%) of ths msclassfed subgroup receved a publc penson and were hence elgble for a pensoner concesson card or a veterans treatment enttlement card. 8 The defnton of ncome for the purpose of penson elgblty s dfferent to the defnton n the NHS. 9 Gven that the number of pensoners domnates the number of hgher ncome older people, t s not surprsng that a large proporton of the hgher ncome group conssts of pensoners affected by ths defntonal ssue. It s also possble (though not nevtable) that ncome s msreported for some of these pensoners. Also, some categores of veteran s pensons are not subject to the same ncome tests, though the type of penson s not revealed n the 1995 dataset. The remanng 17.8% of ths subgroup (7.7% of the total 1995 treatment group) can be explaned by a combnaton of other factors. Some may be CSHC holders, affected by smlar ncome defnton ssues as the age pensoners dscussed above. For others, penson 8 It would hence seem natural to exclude pensoners from the treatment group n all years. However, much of the treatment group samples n 2001 and are (legtmately) pensoners. Ths s because the ncome elgblty threshold for the age penson was ncreased n July Specfcally, the taper rate was reduced from 50% to 40%, thus ncreasng the range of ncomes that qualfy for a part rate of the age penson. Thus t s mpossble to apply a consstent excluson rule across samples to address ths ssue. Agan, ths s not an ssue for the analyss under the assumpton that the msclassfcaton s consstent across years. 9 As noted above, NHS records current ncome. In prncpal, the ncome test for the age penson s an annual ncome test, though ncome over shorter perods (such as 13 weeks) may be assessed for people wth rregular ncome (see Australan Government, 2007b: Secton ). 13

16 recept or health card status may be msrecorded. All of the explanatons proposed so far are lkely to affect the treatment group n each of the three surveys. There s one potental factor, however, whch affects only the treatment group n The health care card flag ncludes safety net concesson cards n NHS 1995, but not n other years (Australan Bureau of Statstcs, 1996: 92). Ths may result n the proporton of people affected by the CSHC reform to be underestmated and hence the magntude of IV elastcty estmates to be overestmated. However, a number of factors suggest that ths s unlkely to be major factor. As dscussed above, ths ssue s one of several competng explanatons for the msclassfcaton of just 7.7% of the treatment group. ABS states that there was sgnfcant underreportng of safety net cards (Australan Bureau of Statstcs, 1996: 92). Furthermore, snce the survey was conducted throughout the calendar year, the number of people to have reached the safety net threshold before the tme of ntervew s lkely to be small, though data are not avalable to establsh ths. Fnally, safety net card holders, by defnton, have had hgh drug consumpton n the calendar year pror to ntervew. But there s no evdence of a greater dfference n pharmaceutcal consumpton between card holders and non-card holders n 1995 than n other years. Ths s shown n the Appendx (Fgures 12, 13 and 14). Table 1 Sample sze and proporton wth health care card by year and group Sample sze Total Treatment group Comparson Group 1 (poorer) 3,896 2,263 2,711 8,870 Comparson Group 2 (younger) ,961 Total 4,866 3,070 3,687 11,623 Percentage wth Health Care Card Treatment group 43.2% 73.9% 78.9% 68.8% Comparson Group 1 (poorer) 94.0% 97.2% 98.0% 96.4% Comparson Group 2 (younger) 5.9% 8.5% 8.1% 7.8% The measure of consumpton used n the analyss s the number of PBS medcatons taken n the prevous two weeks for selected condtons. 10 Each of the three surveys contans such 10 Ths varable mght not capture all possble behavoural responses to prce. A change n prce ceters parbus could be assocated wth changes n frequency or dosage of consumpton wthn a gven fortnght. It may also 14

17 data. The generc names of drugs taken are provded n each fle. The data do not nclude an ndcator for whether the drug was purchased through the PBS. Each generc drug name was manually checked aganst the PBS Schedule operatng at the tme (Australan Government, varous years). It s assumed that drugs appearng on the Schedule were purchased through the PBS. In each survey, the drugs recorded were as reported by the respondent. Intervews took place n respondents homes and respondents were encouraged to brng out the medcaton packets, bottles, etc to assst them and ntervewers n recordng complete and correct detals (Australan Bureau of Statstcs, 2003). Whlst the ABS states that ths dd not always occur, such procedures help mnmse measurement error. Data on pharmaceutcal consumpton were collected dfferently n 1995 to the other years. In 1995, data were collected on all medcatons taken (to a maxmum of twelve). In 2001 and , data were only collected for medcatons taken for specfc condtons. In 2001, the condtons were asthma, heart and crculatory condtons, dabetes and hgh sugar levels (as well as for cancer and mental wellbeng, but generc drug names were not provded). A maxmum of three drugs were recorded for each condton. Up to three heart and crculatory condtons were recorded. The data for were collected smlarly to that of 2001 wth the followng exceptons. Medcatons for arthrts and osteopoross were recorded, whle cancer was omtted. Generc drug names were provded for medcatons taken for mental well-beng. Up to fve medcatons were recorded for mental health and wellbeng, whle a maxmum of three were recorded for other condtons, as for For 2001 and , a comparable varable was created whch records the number of PBS drugs taken for asthma, heart and crculatory condtons, dabetes and hgh sugar levels. These medcatons account for approxmately 41% of PBS prescrptons and 53% of the correspondng benefts n 2001, as recorded by Medcare Australa (Australan Government, 2006). 11 The ABS has classfed medcatons nto types that are commonly used for specfc condtons, based on the WHO Anatomcal Therapeutc Chemcal Classfcaton (Australan nduce the use of out-of-date or substtute medcatons, wthout necessarly mpactng on the dependent varable. If so, the effect of prce on quantty demanded may be underestmated. Ths would result n an underestmaton of the magntude of the estmated elastcty. 11 The correspondng proporton calculated for the populaton of nterest s not avalable. However, gven the set of condtons covered, t s lkely to be consderably hgher than the 41% across all age groups. 15

18 Bureau of Statstcs, 2006: Appendx 4). Usng ths classfcaton, medcatons that are commonly taken for the condtons lsted above have been ncluded n the correspondng varable for Note that ths method does not ensure that the same drugs are ncluded n each year. Ths s justfed on the bass that treatments for these condtons change over tme. For the estmates to be unaffected by the methodologcal dfferences between years, t s suffcent to assume that they affect the treatment group and comparson groups equally. The pharmaceutcals that are ncluded n the measure are almost exclusvely for the treatment of chronc condtons. Almost all the medcatons fall nto the category of essental medcnes used n other studes (McManus et al., 1996; Tamblyn et al., 2001). One mght hypothesse that the prce elastcty of demand s smaller for essental medcnes than other drugs. However, the evdence provdes lttle support for ths hypothess. There was no dfference between essental and less-essental medcnes n the response to a prce change amongst older people n Australa (McManus et al., 1996) and only a small dfference n Canada (Tamblyn et al., 2001). The dependent varable s domnated by heart and crculatory drugs, whch make up 82% of the total volume of drugs recorded for the treatment group across years. Whlst t would be desrable to conduct analyses of varous sub-groups of drugs, the data are not rch enough to warrant these. Table 2 shows descrptve statstcs for each group n the sample. In each year, average PBS drug consumpton was hghest for comparson group 1 and lowest for comparson group 2. The number of PBS drugs taken was very smlar n 1995 and 2001, and the dfference s not sgnfcantly dfferent for any group. However, the recorded number of PBS drugs was consderably lower n for each group, despte smlar methods beng used n the last two surveys. Ths s explaned by dfferences n the medcaton classfcaton provded on the fles. In , a greater proporton of medcatons were grouped nto resdual categores, makng t dffcult to determne whch were PBS-lsted. Such medcatons were not ncluded n the count. There s a notable dfference over tme n the sex composton of the treatment group. Females accounted for 56% of the group n 1995, decreasng to 40% n

19 Table 2 Summary statstcs (mean and standard devaton) by year and group mean (standard devaton) 1995 Treatment Gp Comp Gp 1 Comp Gp 2 Number of PBS drugs taken n prevous two weeks (1.306) (1.468) (0.921) Age (4.196) (4.112) (3.597) Female (0.498) (0.491) (0.495) Personal ncome (2005 AU$ / week '00s) (2.316) (0.928) (2.661) Marred (0.478) (0.500) (0.480) Hgh blood pressure (0.486) (0.488) (0.426) Cholesterol (0.350) (0.310) (0.342) Dabetes (0.249) (0.284) (0.191) Asthma (0.272) (0.277) (0.265) Self Assessed Health - very good (0.452) (0.415) (0.486) Self Assessed Health - good (0.472) (0.461) (0.468) Self Assessed Health - far (0.366) (0.438) (0.334) Self Assessed Health - poor (0.277) (0.325) (0.146) Health Care Card (0.496) (0.237) (0.236) 2001 Treatment Gp Comp Gp 1 Comp Gp 2 Number of PBS drugs taken n prevous two weeks (1.339) (1.513) (1.066) Age (4.330) (4.139) (3.561) Female (0.501) (0.496) (0.495) Personal ncome (2005 AU$ / week '00s) (2.321) (1.242) (3.045) Marred (0.491) (0.495) (0.405) Hgh blood pressure (0.489) (0.490) (0.393) Cholesterol (0.379) (0.399) (0.330) Dabetes (0.272) (0.318) (0.226) Asthma (0.245) (0.291) (0.260) Self Assessed Health - very good (0.449) (0.403) (0.471) Self Assessed Health - good (0.454) (0.475) (0.471) Self Assessed Health - far (0.407) (0.426) (0.362) Self Assessed Health - poor (0.200) (0.315) (0.208) Health Care Card (0.440) (0.164) (0.279) Treatment Gp Comp Gp 1 Comp Gp 2 Number of PBS drugs taken n prevous two weeks (1.105) (1.191) (0.749) Age (4.408) (4.177) (3.614) Female (0.490) (0.495) (0.497) Personal ncome (2005 AU$ / week '00s) (2.708) (0.854) (2.652) Marred (0.473) (0.497) (0.482) Hgh blood pressure (0.480) (0.494) (0.406) Cholesterol (0.389) (0.422) (0.305) Dabetes (0.286) (0.359) (0.221) 17

20 Asthma (0.311) (0.296) (0.272) Self Assessed Health - very good (0.464) (0.425) (0.490) Self Assessed Health - good (0.464) (0.469) (0.456) Self Assessed Health - far (0.345) (0.417) (0.301) Self Assessed Health - poor (0.219) (0.325) (0.196) Health Care Card (0.409) (0.140) (0.273) 4.3 Common trends? The key assumpton n a dfference-n-dfference approach s that of a common trend between groups. The steady ncrease n aggregate health care consumpton s largely drven by technologcal change (Mannng et al., 1987). I propose that technologcal progress s more lkely to affect consumpton multplcatvely rather than addtvely. Over a gven perod, consumers wth health problems mght be affected by several technologcal advances, whlst those that are healthy mght be affected by none snce they do not requre health care nterventon. If so, a common trend n logs s a more approprate assumpton than a common trend n levels. One way of comparng the valdty of the competng assumptons about trends s to analyse consumpton over a perod that does not nclude the polcy nterventon. I consder changes n consumpton for each of the groups between 2001 and , the two postnterventon samples. The only notable change over ths perod was a 21% ncrease n the co-payment n January 2005, whch affected both general and concesson patents. Usng the data n Table 2, t can be shown that there s no sgnfcant dfference n the absolute or relatve level of consumpton between 2001 and for any group. Such a comparson, however, does not control for possble dfference n characterstcs between years. A dfference-n-dfference approach n a regresson framework facltates smlar comparsons whch do control for changes n the characterstcs of groups. To test the hypothess of a common trend n levels, consumpton was modelled usng OLS for each group separately. The key varable of nterest s a year dummy. Control varables nclude age, age squared, sex, personal ncome, personal ncome squared, martal status, self assessed health and bnary flags for hgh blood pressure, hgh cholesterol, dabetes and asthma. To test the hypothess of a common trend n logs, t s not possble to take the 18

21 logarthm of the dependent varable due to the large number of zeros. Instead, negatve bnomal regressons were estmated (to be dscussed further n the followng secton). Snce the negatve bnomal regresson s estmated wth a log lnk, t models the multplcatve effect of the covarates. The estmated effects of the year dummy on consumpton are shown n Table 3. The parameters of nterest, labelled Pct change are non-lnear transformaton of the estmated coeffcents of year: e -1. As n the raw comparsons, the effect of year s not sgnfcantly dfferent between the treatment group and ether comparson group usng ether method. In the lnear model, however, the effect s sgnfcantly larger (p<0.001) for the low ncome comparson group (whch has the hghest average consumpton) than the young comparson group (whch has the lowest consumpton). Ths s not the case n the negatve bnomal model. Ths result combned wth the proposton above provdes some justfcaton for the assumpton of common trends n logs. Ths s the assumpton that s made n the preferred models, but senstvty of the results s tested to the alternatve assumpton of common trends n levels. The estmated elastcty s not senstve to ths assumpton. Table 3 Modelled effect of year on consumpton by group OLS Coeffcent Robust SE Comp Gp (low ncome) Treat Gp Comp Gp (younger) NegBn Coeffcent Robust SE Pct change Delta SE Comp Gp (low ncome) % 2.28% Treat Gp % 8.88% Comp Gp (younger) % 8.46% 4.4 Model Specfcaton The dependent varable s a hghly skewed count varable. Fgure 4 shows ts dstrbuton by year. One reason to prefer a count data model to the lnear model shown n equaton (5) s a gan n effcency. The resduals n an OLS regresson estmated on count data are lkely to be non-normal and heteroskedastc. OLS s a consstent estmator under such condtons. 19

22 However, by utlsng addtonal nformaton about the lkely dstrbuton of the resduals, count data models can be more effcent. A second advantage to count data models s that the parameters usually estmate the multplcatve effect of the explanatory varables on the dependent varable. Ths allows the mplementaton of the common trend n logs assumpton. Ths assumpton cannot be mplemented n a lnear regresson model unless the dependent varable has no zero values. Fgure 4 Dstrbuton of Dependent Varable by Year, All Groups (% wthn each year) % number of PBS drugs taken Two count data models are consdered, the Posson Regresson Model (PRM) and the Negatve Bnomal Regresson Model (NBRM), followng Cameron and Trved (1998) and Long (1997). In the PRM, the dependent varable y, condtonal on covarates x, s assumed to be Posson dstrbuted: f ( Y e y x ), y = 0, 1, 2, y! y The condtonal mean s parametersed as a log-lnear functon of covarates: 20

23 E( y x ) exp( x ' ) and by the Posson process, the condtonal varance s equal to the condtonal mean. The NBRM extends the PRM, by allowng for overdsperson. In other words t allows the condtonal varance to exceed the condtonal mean. Ths extenson can be motvated by unobserved heterogenety. In ths case, the condtonal mean s a random varable. E( y ~ ' x ) exp( x ) where has a mean of zero and hence E( ~ ) The condtonal varance s greater than the expected condtonal mean and s parametersed as: Var 2 ( y x) where s estmated by the model. The PRM s thus a specal case of the NBRM where s equal to zero. Ths restrcton can be tested usng a Wald test. 12 The PRM s consstent wth dstrbutonal msspecfcaton such as an napproprate assumpton of equdsperson. The NBRM (and OLS) are also consstent wth dstrbutonal msspecfcaton and robust standard errors can be calculated whch are analogous to Huber-Whte (Sandwch or robust) standard errors n the lnear model. In the two-perod one comparson group NBRM, the model s specfed as: u exp( b0 b1t b2g b3h X ), (6) where t (0,1), G = 1 f person has ncome and age such as to be affected by the polcy change; zero otherwse H = 1 f person has a health card; zero otherwse 12 The Wald statstc s calculated as ˆ 2 ( ) / var( ˆ ) and follows a Ch Square dstrbuton wth one degree of freedom. 21

24 X s a vector of controls ncludng sex, age, age squared, martal status, personal ncome, personal ncome squared, self assessed health and bnary ndcators for hgh blood pressure, cholesterol, dabetes and asthma as long-term health condtons. If H s exogenous, consstent estmates of b 3 can be generated by estmatng (6) by Maxmum Lkelhood. If H s endogenous, however, such estmates wll be nconsstent and nstrumental varable methods are necessary, though they come at a cost to effcency. Models where endogenety s assumed are estmated by the Two-Step (effcent) Generalzed Method of Moments (GMM), usng the moment condtons proposed by Mullahy (1997) for count data models. Mullahy s approach s to treat the resduals as multplcatve rather than addtve, thereby treatng observed and unobserved characterstcs symmetrcally. See Davdson & MacKnnon (1993: Chapter 17) for a detaled ntroducton to GMM. In addton to Mullahy, see also Wndmejer & Santos Slva (1997) for a dscusson of addtve versus multplcatve resduals n count data GMM models. The exogenous polcy change (measured by the nteracton of G and t) s an nstrument for H. To test the endogenety of H, a Hausman test s performed (Hausman, 1978; Greene, 2003). Ths tests for a sgnfcant dfference n the estmated coeffcents of two competng specfcatons, where one s effcent and the other s consstent under less restrctve assumptons. In ths case, t s used to test for dfferences between the GMM model wth H treated as endogenous and the correspondng model wth H treated as exogenous. The test statstc has a 2 dstrbuton wth degrees of freedom equal to the number of hypothessed endogenous regressors (1 n ths case). The statstcal power of such endogenety tests depends on the strength of the nstruments. Statstcally sgnfcant evdence for bas may not be found gven weak nstruments or small sample sze. Nakamura and Nakamura (1998) cauton aganst mechancal use of such tests as a decson rule for whether to use IV. Takng ths on board, both IV and non-iv models are estmated even f the Hausman test does not fnd statstcally sgnfcant bas due to endogenety. There s ndeed an a pror reason to expect endogenety. The CSHC s taken up by a subset of elgble people. Condtonal on covarates, t seems probable that hgh-end consumers of pharmaceutcals are more lkely to take-up the card than others, snce they have the most to gan from a concesson. As a result, CSHC holders wll have hgher 22

25 consumpton than mpled by the prce effect alone. Thus non-iv estmates of elastcty wll be based downwards (more negatve). In the IV model, take-up s nstrumented by elgblty. It s hypothessed that IV estmates wll be hgher (less negatve) than non-iv estmates. 13 The endogenety test s dentfed through a polcy change that only affects the treatment group, whch has been defned as the set of people whose ncome and age suggest that they were affected by the polcy reform. For ths reason, the sample s restrcted to the treatment group (G=1) n the non-iv models. Under ths restrcton, the non-iv estmates have a slghtly dfferent nterpretaton to the IV results. They are estmates of the effect of the card on those who have taken t up (the estmated average effect of the treatment on the treated). The IV estmates, on the other hand, provde estmates of the Local Average Treatment Effect. Ths s the effect of the card amongst those who have taken t up as a result of the polcy change. Snce some card-holders n the treatment group already had the card pror to the treatment, the two sets of estmates are conceptually dfferent. The model s extended to enable two comparson groups and/or three tme perods. In the two-comparson group model, G s replaced wth two group dummes. In the three-perod model, t s replaced by two tme perod dummes. In ether case, the nteracton term Gt s replaced by a dummy varable that equals one for the treatment group after the polcy change, and zero otherwse. The set of nstruments s also enrched by nteractng Gt wth each exogenous regressor n the model. Note from (6) that E ( C H 1) exp( b3 ) E( C H 0). Substtutng, the frst term of equaton (1a) smplfes to a non-lnear transformaton of the estmated coeffcent of H: 13 It s also possble that ncome s endogenous. Some people may have changed ther ncome earnng behavour n response to the polcy change. If so, elgblty for the card (and the nstrumental varable) would be endogenous. Any such endogenety would result n hgh users movng nto the treatment group post treatment and the effect of prce on consumpton would be overestmated. Ths would mean that the estmated elastcty s based downwards and the unbased estmate s hgher (less negatve) than estmated. However, the behavoural response s unlkely to be great snce the value of the concesson s not large. For an average consumer n the treatment group, the value of the concesson s equal to approxmately 1% of ncome. Even for a consumer wth ten tmes the average consumpton, ts value s only 3% of total ncome (because of the safety net). 23

26 exp( b (exp( b 3 3 ) C ) C H 0 H 0 C C H H 0 0 exp( b3 ) 1 ) / 2 (exp( b ) 1) / 2 3 (7) The numerator of (7) also represents the percentage change n consumpton assocated wth the polcy change, for those who took up the card. The NBRM specfed n equaton (6) has an analogous lnear model: C b0 b1t b2g b3h X (8) Ths model s used to test the senstvty of the results to an assumed common trend n levels rather than logs. The frst stage of the lnear IV model s H G t t G X G tx (9) In the lnear model, the frst term of equaton (1a) s equal to: b 3 ( E( C H 0) b3 ) / 2 (10) Where E(C H = 0) s calculated as the average predcted value for the treatment group post-treatment, condtonal on H=0. Standard errors n all models are robust (sandwch/whte) errors. 4.5 Propensty Score Matchng Matchng s a technque for selectng a comparson group that resembles the treatment group as closely as possble on observable characterstcs. The assumpton underpnnng the matchng approach s that treatment s uncorrelated wth the outcome varable, condtonal on observed characterstcs. Ths s sometmes referred to as selecton on observables or condtonal ndependence. Ths approach requres a common support (a common range of probabltes of treatment gven observable characterstcs) to the treatment and comparson groups. It s suffcent to match on the probablty of treatment as a functon of observable characterstcs (Rosenbaum & Rubn, 1983). Such an approach s known as Propensty Score Matchng (PSM). A key strength of matchng approaches s that they do not mpose parametrc assumptons on the relatonshp between the outcome varable and the regressors. 24

27 In ths paper, a set of results are produced usng PSM. As n the non-iv regressons descrbed above, the sample s restrcted to the set of people whose ncome and age suggest that they were affected by the CSHC reform. Wthn ths sample, the treatment group s redefned as the set of people who hold a concesson card. The comparson group s the set of people who do not have a concesson card. Each observaton n the treatment group s matched wth ts fve nearest neghbours (wth replacement) from the comparson group. 14 These are the observatons that have the smallest absolute dfference between ther odds ratos and that of the observaton n the treatment group. The matched value of the outcome varable s the average of these fve observatons. Observatons n the treatment group that fall outsde of the common support are excluded. Ths approach does not explot the CSHC natural experment, just as the non-iv models do not explot t. The approach s justfed f there s no evdence found for endogenety of health care card take-up. The ssue of how to account for complex survey data n PSM has been gven lttle attenton n the academc lterature. Complex survey data are charactersed by unequal probablty of selecton. It would seem lkely that an unweghted average effect of the treatment on the treated may not be representatve of the populaton from whch the sample s drawn. It s less clear, however, whether the propensty score model (the probt stage) should be weghted. Zanutto (2006) suggests that the senstvty of results to both weghted and unweghted approaches should be shown. The man approach used n ths paper s to calculate a weghted estmate of the treatment effect. Only the weghts that correspond to treatment group observatons are used. These are appled to the treatment group outcomes, as well as to the outcomes that are matched to each treatment group observaton. The propensty score s calculated usng an unweghted probt regresson. Senstvty s tested to the use of sample weghts n both stages The choce of fve neghbours s common n appled evaluatons. Ravallon (2007: 28) suggests that usng fve neghbours produces more robust estmates than usng one neghbour. The estmates are smlar when a nearest one neghbour approach s used, but less precse, as shown n the Appendx. 15 My approach s based on the module wrtten by Leuven and Senes (2003). I have made smple modfcatons to enable the use of sample weghts. 25