The Incenve Effecs of Organzaonal Forms: Evdence from Florda s Non-Emergency Medcad Transporaon Programs Chfeng Da* Deparmen of Economcs Souhern Illnos Unversy Carbondale, IL 62901 Davd Denslow Deparmen of Economcs Unversy of Florda Ganesvlle, FL 32611 James Dewey Bureau of Economc and Busness Research Unversy of Florda Ganesvlle, FL 32611 July 2007 *We would lke o hank Sco Glber, Babak Lofna, Subhash Sharma, and semnar parcpans a Unversy of Florda, Oho Unversy, and Souhern Illnos Unversy Carbondale for helpful commens.
Absrac We analyze he ncenve effecs of organzaonal forms usng daa from Florda s Non-Emergency Medcad Transporaon (NEMT) programs. These programs dffer n he exen o whch her brokers are drecly nvolved n provdng rans servces. Based on a smple model of moral hazard, we predc ha he number of users and he number of clams per user of he program ncrease, bu cos per clam of he program decreases, as s broker s share of rans servces ncreases. The emprcal evdence suppors our heorecal predcons on he ncenve effecs of dfferen organzaonal forms. 1
1. Inroducon The opmal desgn of ncenve conracs and he opmal srucurng of organzaons are of cenral neres o economss. Alhough he heorecal leraure offers many neresng predcons, he emprcal leraure provdes few ess of hese predcons due o a lack of approprae daa. Ths paper provdes an emprcal es of he ncenve effecs of organzaonal forms, usng daa from Florda s Non-Emergency Medcad Transporaon (NEMT) programs. The Socal Secury Ac and accompanyng regulaons requre ha sae Medcad programs provde Medcad benefcares access o non-emergency ransporaon o and from medcal apponmens. Florda s NEMT programs conrac wh separae enes, commonly referred o as brokers, o conrol he coss, qualy, and ulzaon of servces. These programs dffer n he exen o whch her brokers are drecly nvolved n provdng rans servces, referred o as her organzaonal forms. We analyze he ncenve effecs of organzaonal forms on brokers performance wh a smple model of moral hazard. We show ha, gven he compensaon srucure, a broker supples more effor on boh qualy assurance and cos reducon bu less effor on screenng rp elgbly as s share of rans servces ncreases. Consequenly, he number of Medcad benefcares usng servces and he number of clams per user ncrease as he broker s share of rans servces ncreases. Moreover, for a gven number of clams, cos per clam decreases as he broker s share of rans servces ncreases. We es our heorecal proposons usng cos and ulzaon daa of Florda s NEMT programs n all sxy-seven Florda counes from fscal year 1991 o 2002. We esmae he ncenve effecs usng a wo-sep procedure o conrol for he endogeney of 2
he choce of organzaonal forms. The emprcal evdence suppors our heorecal proposons and s robus o emprcal specfcaons. Our fndngs sugges ha he choce of organzaonal form has mporan ncenve effecs on performance. Our sudy provdes an emprcal es of conrac heory. There exss a small bu growng body of evdence supporng he exsence of ncenve effecs n organzaons. Lazear (2000) and Paarsch and Shearer (1999, 2000) consder he mpac of pece raes on he performance of workers. Banker, Lee, and Poer (1996) sudy he effec of pece raes on sales n real deparmen sores. McMllan, Whalley, and Zhu (1989) and Grove e al. (1994) sudy how he changes of compensaon pracce n Chnese economc reforms have affeced performance levels. Ferne and Mecalf (1999) consder he effec of compensaon sysems on he performance of Brsh jockeys. Laffon and Maouss (1995) sudy he relaonshp beween producon and he enan s share of he produc n a sharecroppng conrac. These sudes fnd consderable effecs of compensaon on performance. Our sudy complemens her fndngs by demonsrang he ncenve effecs of organzaonal forms on performance under a gven compensaon sysem. The res of he paper s organzed as follows. Secon 2 nroduces Florda s NEMT programs. Secon 3 develops a smple model of moral hazard o analyze he ncenve effecs of dfferen organzaonal forms on a broker s effor decson, and derves emprcal mplcaons of he model. Secon 4 descrbes our daa and economerc mehod. Secon 5 presens he esmaon resuls of our economerc analyss. Secon 6 summarzes he resuls and dscusses some of he resrcons and generalzaons of our sudy. 3
2. Florda s NEMT Program The Socal Secury Ac and accompanyng regulaons requre ha sae Medcad programs provde Medcad benefcares access o non-emergency ransporaon o and from medcal apponmens. Mos saes mee he requremen by rembursng recpens for ransporng hemselves or by enrollng ransporaon provders and payng hem a fee for servce. However, he radonal, decenralzed, fee-for-servce approach o managng non-emergency Medcad ransporaon has no been very effecve n conrollng coss, or fraud and abuse, or n assurng unversal access o medcal care. The Healh Care Fnancng Admnsraon esmaed ha NEMT coss ncreased en percen annually naonwde beween 1990 and 1995. In some ndvdual saes, NEMT coss ncreased much more rapdly, e.g., n Lousana n he four years from 1990 o 1994 NEMT coss more han rpled, and n Georga from 1993 o 1994 coss more han rpled n jus one year. In recen years, many saes, ncludng he sae of Florda, have begun searchng for more effecve approaches o manage non-emergency ransporaon. An ncreasngly popular way s conracng wh separae enes, commonly referred o as brokers, who serve as gaekeepers o conrol he coss and ulzaon of servce and o assure qualy of servce and access o care. Ths approach o managng Medcad ransporaon s known as he brokerage model. By saue, Florda esablshed a saewde Transporaon Dsadvanaged (TD) program whch suppors servces for hose who canno provde her own ransporaon due o age, physcal or menal nfrmy or fnancal lmaon. The TD program ncludes 4
all ransporaon programs n Florda ha are suppored by federal, sae, or local fundng. Florda s NEMT program has parcpaed n he TD program snce FY 1996. The TD Commsson selecs a local Communy Transporaon Coordnaor (CTC) for each couny. CTCs accep calls and auhorze non-emergency ransporaon for Medcad benefcares, deermne f he benefcary has access o ransporaon oher han Medcad fnanced ranspor, verfy benefcary elgbly for Medcad, deermne ha he ransporaon s for recevng a Medcad-covered servce, and selec he mos reasonable and cos effecve mode of ranspor based on he benefcary s physcal and menal condon. They mus also selec he leas cosly ransporaon carrer, arrange ransporaon wh he approprae carrer, monor he use of ransporaon by Medcad benefcares, and assess problems relaed o rp cancellaons and no-shows, msuse of ransporaon, and abusve behavor. In each couny, he Local Coordnang Board (LCB) monors he CTC n deermnng how effecvely local needs are beng me. Furhermore, he LCB selecs he CTC va a compeve bd process based on s evaluaon of each broker s corporae experence, performance, references, resources, qualfcaons and coss. The CTC s requred o eher conrac wh ousde rans servce provders or provde some or all of he ransporaon self. Table 1 shows he hree dfferen organzaonal forms used by CTCs ha dffer n he exen he CTCs are drecly nvolved wh provdng rans servces. CTCs are normally pad a fxed fee per rp and rans provders are normally pad a fxed fee, whch vares wh ransporaon modes, plus mleage. 5
Table 1 Taxonomy of Organzaonal Forms Coordnaor Type Brokerage Only Parally Inegraed Fully Inegraed Characerscs Provdes only brokerage servce Provdes brokerage servce and some rans servces Sole source of all brokerage and rans servces 3. Theory and Implcaons In hs secon, we analyze he ncenve effecs of dfferen organzaonal forms wh a smple model of moral hazard. We hen derve he mplcaons of he ncenve effecs on he cos and ulzaon of NEMT programs. 3.1. The demand for NEMT servces. A Medcad benefcary s demand funcon for elgble rdes s j( x, q), where x s a parameer affecng he benefcary s valuaon of elgble rdes and q s he broker s effor n qualy assurance. The parameer x s dsrbued beween and x wh x0 1 dsrbuon funcon F(x). For any gven amoun of rdes, a benefcary s margnal valuaon of elgble rdes ncreases as x ncreases. On he oher hand, a benefcary s demand funcon for nelgble rdes s ( y, q, s), where y s a parameer affecng he benefcary s valuaon of nelgble rdes and s s he broker s effor n screenng user and rp elgbly. 1 The parameer y s 1 I s n he broker s bes neres o verfy a user's Medcad elgbly, as he sae wll laer verfy he rder s Medcad elgbly and wll remburse a rp only f he rder s 6
dsrbued beween and y wh dsrbuon funcon L( y). For any gven amoun of y0 1 rdes, a benefcary s margnal valuaon of nelgble rdes ncreases as y ncreases. The demands for boh elgble and nelgble rdes are ncreasng n boh he benefcary s valuaon and he broker s qualy-assurance effor,.e., ( x, q) > 0, j q ( x, q) > 0, y ( y, q, s) > 0, and ( y, q, s) > 0. Furhermore, he demand for nelgble q j x rdes s decreasng n he broker s screenng effor,.e., s ( x, q, s) < 0. Benefcares who place lle value on NEMT servces have no demand for rdes. We defne x * and y * as he values of x and y such ha a user wh an evaluaon less han x * and y * has zero demand for elgble and nelgble rdes, respecvely. Formally, j( x*, q) 0 and ( y*, q, s) 0. I can be readly shown ha boh x * and y * decrease n he broker s qualy-assurance effor bu y * ncreases n he broker s screenng effor. I suggess ha he number of benefcares usng he servces ncreases n he broker s qualy-assurance effor bu decreases n he broker s screenng effor. For he overall benefcary populaon, he demands for elgble and nelgble x rdes are J j( x, q) df( x) and I ( y, q, s) dl( y), respecvely. Therefore, he = 1 x* 1 1 overall demand for rdes s D( q, s) j( x, q) df( x) ( y, q, s) dl( y). Noe ha x y = 1 y* = + x* y y* Medcad elgbly s confrmed by he sae. Therefore, we focus our analyss on he demand of Medcad benefcares only. 7
D( q, s) = q + x 1 x* y y* dx* jq ( x, q) df( x) j( x, q) f ( x) dq dy * q ( y, q, s) dl( y) ( y, q, s) l( y) > 0, and dq 1 (1) D( q, s) y1 dy * = (,, ) ( ) (,, ) ( ) < 0 s y q s dl y y q s l y, (2) s y* ds where f (x) and l( y) are he probably densy funcons for x and y respecvely. Therefore, he demand for rdes ncreases as he broker s qualy-assurance effor ncreases, bu decreases as he broker s screenng effor ncreases. Lemma 1 summarzes he above properes regardng he demand for NEMT servces. Lemma 1. A gven user s demand for he servces, he number of benefcares usng he servces, and herefore he oal demand for servces, all ncrease n he broker s qualyassurance effor bu decrease n s screenng effor. 3.2. The broker s problem. Each broker n he NEMT program s offered a conrac { r, b, }, whch specfes he broker s share of rans servces, r, he brokerage fee, b, ha he broker receves for each clam 2, and he rans fee,, ha he rans servce provder receves for each clam. The amoun of nelgble clams deeced by he sae admnsraon, α (I ), s ncreasng n he acual number of nelgble clams, I,.e., α '( I) > 0. For each nelgble clam deeced by he sae admnsraon, he broker ncurs a loss of m. 2 A clam s a one-way rde per benefcary. 8
The oal cos of brokerage servces s H D, e ), where e s he broker s effor ( b n reducng brokerage cos. The brokerage cos s ncreasng n he number of clams and decreasng n he broker s cos-reducon effor a a decreasng rae,.e., H ( D, ) > 0, H ( D, ) < 0, H ( D, ) < 0, and H ( D, ) > 0. e e b DD e b ee e b b D e b The oal rans cos s G D, e ), where e s he broker s effor n reducng ( rans cos. As he number of clams ncreases, a broker can ranspor more benefcares wh one vehcle or beer organze clams o reduce he number of rps. Therefore, he oal rans cos s ncreasng n he number of clams a a decreasng rae,.e., G ( D, ) > 0 and G ( D, ) < 0. Furhermore, he oal rans cos s decreasng n he D e DD e broker s cos-reducon effor a a decreasng rae,.e., G ( D, ) < 0 and G ( D, ) > 0. e e ee e The broker s share of rans cos s rg D, e ), as r s he broker s share of rans ( servces. The broker s cos of effor s C(E), where E s + q + e b + e. The cos of effor s ncreasng n effor a an ncreasng rae, hus, C' ( E) > 0 and C' '( E) > 0. The Sae canno observe he broker s effor supply, and herefore canno specfy he broker s effor supply n he servce conrac. Consequenly, a moral hazard problem arses as he broker wll allocae s effors o maxmze s expeced prof. The broker s opmzaon problem s deermnng q, s, e b, e } o maxmze { Π = ( b + r) D [ H( D, e ) + rg( D, e )] C( E) α( I m. (3) b ) Denoe he broker s maxmum prof under a gven conrac as Π *. The broker wll parcpae n he conrac only f s nonnegave. Π * 0,.e., s maxmum prof under he conrac 9
The frs-order condons of he broker s opmzaon problem are gven by Π = Dq ( q, s)[( b + r) H D ( D, eb ) rgd ( D, e )] C'( E) α '( I) I q ( q, s) m = 0; (4) q Π s Π e b Π e = I s ( q, s)[( b + r) H D ( D, eb ) rgd ( D, e ) α '( I) m] C'( E) = 0 ; (5) = H e = rg ( D, e ) C'( E) = 0; and (6) e b ( D, e ) C'( E) = 0. (7) Equaons (4)-(7) deermne he broker s effor allocaon among qualy assurance, elgbly screenng, and cos reducon. From equaon (4) and by he use of he Envelope heorem, 2 Π dq q r Dq ( q, s)[ GD ( D, e ) ] = =. (8) 2 2 dr Π Π 2 2 q q 2 Π The second-order condon of he opmzaon problem requres 0. 3 Furher, 2 q snce G ( D, ) < 0, > G D, e ) mus be rue for rans servce provders o cover DD e D ( her coss. Therefore, dq > 0,.e., he broker s qualy-assurance effor ncreases as s dr share of rans servces ncreases. From equaon (5) and by he use of he Envelope heorem, 3 We assume ha he second-order condons for he broker s opmzaon problem are sasfed. 10
ds dr = I ( q, s)[ G s ( D, e ) ] D 2 Π 2 s 0, (9) 2 Π as he second-order condon of he opmzaon problem requres 0. Therefore, 2 s he broker s screenng effor decreases as s share of rans servces ncreases. Then, from Lemma 1, a gven user s demand for he servces, he number of benefcares usng he servces, and he oal demand for servces mus ncrease as he broker s share of rans servces ncreases. We presen hese fndngs regardng he demands for NEMT servces n Proposon 1. Proposon 1. A gven user s demand for servces, he number of benefcares usng he servces, and he oal demand for servces ncrease as he broker s share of rans servces ncreases. Furhermore, from equaons (6) and (7), de b = 0 ; and (10) dr de dr = G ee G ( D, e ) e ( D, e ) + C''( E) > 0. (11) The above equaons sugges ha ncreasng he broker s share of rans servces rases he broker s effor n reducng rans coss, bu has no effec on he broker s effor n reducng brokerage cos. 11
Denoe AC as he oal cos per clam,.e., AC ( H ( D, e ) + G( D, e )) D. The b / broker s share of rans servces affecs oal cos per clam n wo ways. Frs, affecs he demand for servces; second, affecs he broker s cos-reducon effor. Holdng he number of rdes consan, he second effec of he broker s share of rans servces s dac dr Ge = D de dr < 0,.e., oal cos per clam s decreasng n he broker s share of rans servces for any gven number of rdes. The overall effec of he broker s share of rans servces s dac dr ( DH H) Dr + ( DG D D = 2 D G) D r Ge + D de dr. (12) Snce HDD ( D, e b ) < 0 and GDD ( r, D, e ) < 0, DH D < H and DGD < G. Therefore, dac / dr < 0,.e., oal cos per clam decreases as he broker s share of rans servces ncreases. Noce ha he frs erm on he rgh-hand sde of equaon (12) s he effec of he broker s share of rans servces on oal cos per clam hrough he demand for servces. proposon 2. We presen he above fndngs regardng he coss of NEMT servces n Proposon 2. As he broker s share of rans servces ncreases, 1) oal cos per clam for any gven number of clams decreases; 2) oal cos per clam of he NEMT program overall also decreases. 12
We nex use daa from Florda NEMT programs o es our heorecal proposons regardng he ncenve effecs of organzaonal forms. 4. Daa and Mehods 4.1. Varables and daa source We obaned he cos and ulzaon daa of he Florda s NEMT programs from he Florda Medcad Managemen Informaon Sysem mananed by Florda s Agency for Healh Care Admnsraon. The daa nclude he oal cos, number of users, number of clams, number of benefcares, and organzaonal forms of he NEMT programs n all sxy-seven counes n Florda from fscal year 1991 o 2002. Table 2 presens defnons of all varables used n he emprcal analyss, wh dependen varables n he upper panel, and explanaory varables n he lower panel. Table 3 presens descrpve sascs for all varables. Table 4 presens he number of counes adopng dfferen organzaonal forms beween fscal year 1996 and 2002. 4.2. Economerc Mehod 4.2.1. Performance funcons We use a fxed effec panel daa framework o examne he effecs of organzaonal forms on he performance of he NEMT programs. The fxed effec specfcaon capures dfferences across programs ha are me-nvaran and dfferences over me ha are common o all programs. The relaonshps beween organzaonal forms and he cos and ulzaon of he program are esmaed usng he followng equaon: 13
ln X 67 = α1 + N = 2 72 N + α lnci α N _ CTY + α ln DOC 73 k + α FI 68 74 + α PI 69 + α ln REVN + α BO 70 75 + α ln BEN + α FY 71 + ε. (13) where s an ndex of fscal years and k s a couny ndex (k =1, 2,, 67). X represens he dependen varable for couny k n year. The dependen varable s UPB (user per benefcary) when =1, CPU (clams per user) when = 2, and CPC (cos per clam) when = 3. The symbol ln represens he naural logarhm. For example, ln X 3 represens he naural logarhm of cos per clam for he k h couny n he h fscal year. As we have shown n our analyss, boh he number of clams and he broker s cos-reducon effor affec oal cos per clam. To pnpon he effec of organzaonal form on he broker s cos-reducon effor, we also use he followng equaon o esmae he relaonshp beween oal cos per clam and organzaonal forms conrollng he number of clams: lncpc 4 4 4 = α1 + α N N _ CTYk + α68fi 4 + α lndoc 73 67 N= 2 4 4 + α lnrevn + α lnben 74 + α PI 75 4 69 4 4 + α BO + α FY + α lnci 4 70 4 + α lnclaim 76 71 72 4 + ε. (14) The explanaory varables of prmary neres n all he above equaons are he dummy varables FI, PI, and BO. FI s a dummy varable for he Fully Inegraed model, PI for he Parally Inegraed model, and BO for he Brokerage Only model. The performance under he prevous fee-for-servce approach s he bass of comparson. Therefore, he coeffcens of he dummy varables FI, PI, and BO capure he effec of organzaonal forms on performance n comparson wh he fee-for-servce approach. By dong so, we fully ulze he daa from fscal year 1991 o 1995, when he NEMT 14
program was under he fee-for-servce model, o beer conrol for me-nvaran counyspecfc facors and he rend of NEMT servces. CI s a prce ndex of ransporaon servces for each couny. The prce of ransporaon servces n a couny may no only affec he CTC s provson of rans servces, bu also nfluence benefcares usage of NEMT servces. For example, a hgher prce for ransporaon servces could drve more benefcares o use NEMT servces and a he same me compel CTCs o ry o reduce usage of he sysem. DOC s he number of docors of medcne or oseopahy per square mle n each couny. More docors n a specfc area could lead o, on average, a shorer rp per clam (and also reduce he number of he more expensve ou-of-couny rps) and less usage of NEMT servces by benefcares. REVN s he sae s per capa revenue n each fscal year whch capures he sae s budge suaon. The varable s mporan snce he sae s fscal healh could nfluence pressures on AHCA or CTCs o conrol coss. FY capures changes n condons relaed o he provson of NEMT servces over he years. N_CTY measures couny-specfc characerscs affecng he provson of NEMT servces for each couny. ClAIM s he number of clams of he NEMT program. The α erms are he coeffcens o be esmaed, and ε k s a random error ha has a zero mean and a sandard devaon equal o σ. 4.2.2. The Choce of Organzaonal Form I s possble ha he choce of organzaonal form s endogenous. Frs, CTCs may deermne he organzaonal form of NEMT programs based on some couny characerscs and broker characerscs. Second, he organzaonal form may have a 15
selecon effec on brokers. For example, brokers who chose o parcpae n a Fully Inegraed model may be more effcen n rans servces han hose who chose o parcpae n a Brokerage Only model. If ε k ncludes any of hose couny or broker characerscs ha correlae wh he choce of organzaonal form, he esmaes of performance funcons are based. To accoun for he endogeney of he choce of organzaonal form, we esmae he performance equaons usng a wo-sep procedure an nsrumenal varables mehod. Frs, we esmae he choce of organzaonal form as a funcon of demographc and polcal characerscs of a couny, usng a mulnomal log model: FORM = f ( BEN, CI, LAND, POP, POVERTY, SHMIN, PARTY, GASPR), (15) where FORM s he organzaonal form of he program. FORM equals 1 for Fully Inegraed, 2 for Parally Inegraed, and 3 for Brokerage Only. LAND s he land area of each couny; POP s he populaon of each couny. Snce here are more large-sze ransporaon frms operang n more densely populaed markes, he populaon and land area of a couny could be correlaed wh he sze and effcency of ransporaon provders. POVERTY s he share of populaon lvng n povery. SHMIN s he share of mnory populaon. Snce a large percenage of small ransporaon frms are owned by mnores, a larger presence of mnory makes more dffcul for CTC o award all servces o one large frm. PARTY s he absolue value of he share of Democras among regsered voers n each couny mnus 0.5. I measures he exen o whch he couny s conrolled by one polcal pary. I mgh be more dffcul for he CTC o gran all servces o one provder f eher polcal pary has conrol of he couny. GASPR s 16
gasolne sales per resden n each couny, whch reflecs ransporaon condons n he couny. Second, we oban he predced values of FI, PI, and BO based on he esmaed choce funcons. Thrd, we esmae he performance equaons usng he predced value of FI, PI, and BO as he nsrumens for hese varables. Fnally, we also esmae equaons (13) and (14) drecly by he mehod of ordnary leas-squares. The esmaon resuls from he wo dfferen mehods are compared as a check for he robusness of he resuls. 5. Esmaon Resuls 5.1. The choce of organzaonal form Table 5 presens he esmaes of he choce funcon wh he Parally Inegraed model as he comparson group. Conssen wh our conjecures, compared wh he Parally Inegraed model, he Fully Inegraed model s more lkely o arse n counes wh a smaller percenage of mnory populaon or a hgher populaon densy, or more domnaed by one polcal pary. On he oher hand, he Brokerage Only model s more lkely o arse n counes wh a larger percenage of mnory populaon or a lower populaon densy, or less domnaed by one polcal pary. Moreover, boh he Fully Inegraed model and he Brokerage Only model are less lkely o arse n counes wh more gasolne sales per resden. 17
5.2. The effec of organzaonal form. Tables 6 o 9 presen he esmaes of he performance funcons usng he wosep procedure. To focus on he effec of organzaonal forms on performance, we do no repor he esmaes for he couny dummy varables. Table 6 presens he regresson resuls for he effec of organzaonal form on he number of users per benefcary. The coeffcens of FI and PI are 0.1 and 0.03, whch ndcaes ha he proporon of benefcares usng NEMT servces ncreased by 10 percen n Fully Inegraed programs and 3 percen n Parally Inegraed programs, alhough he ncrease n Parally Inegraed programs s no sascally sgnfcan. The coeffcen for BO s -0.28, suggesng ha he proporon of benefcares usng NEMT servces decreased by 24 percen n Brokerage Only programs. Table 7 presens he regresson resuls for he effec of organzaonal form on he number of clams per user. The coeffcens of FI and PI are posve and hghly sgnfcan, meanng ha clams per user have ncreased under hese wo organzaonal srucures n a sascally sgnfcan way. The resuls ndcae ha, on average, clams per user have rsen by 9 percen under he Parally Inegraed model and 15 percen under he Fully Inegraed model. The coeffcen of BO s nsgnfcan boh economcally and sascally, suggesng ha clams per user under he Brokerage Only model s no sgnfcanly dfferen from hose under he prevous fee-for-servce model. The above regresson resuls sugges ha he number of users and he number of clams per user of a NEMT program ncrease as he broker s share of rans servces ncreases, as predced by Proposon 1. 18
Table 8 presens he regresson resuls for he overall effec of organzaonal form on cos per clam (Equaon (13)). The coeffcens of FI and PI are negave and hghly sgnfcan sascally, meanng ha NEMT programs wh hese organzaonal forms have reduced oal cos per clam n a sascally sgnfcan way. The resuls ndcae ha, on average, Fully Inegraed programs have reduced cos per clam by 38%, and Parally Inegraed programs have reduced cos per clam by 25%. On he oher hand, Brokerage Only programs do no show sgnfcan changes n cos per clam. Table 9 presens he regresson resuls for equaon (14) whch focuses on he effec of he organzaonal form on he broker s effor-reducon effor. The coeffcens of FI and PI are -0.44 and -0.27 respecvely, and boh are hghly sgnfcan sascally. The resuls sugges ha, holdng he number of clams consan, Fully Inegraed programs have reduced cos per clam by 36%, and Parally Inegraed programs have reduced cos per clam by 24%. In conras, Brokerage Only programs do no show sgnfcan changes n cos per clam even afer conrollng he number of clams. I s noeworhy ha he coeffcen for lnclaim s -0.16 and sascally sgnfcan, suggesng economes of scale for NEMT servces. The resuls n Tables 8 and 9 sugges ha oal cos per clam for a gven number of clams and oal cos per clam for a NEMT program overall decrease as he broker s share of rans servces ncreases, as predced by Proposon 2. Moreover, a comparson beween he resuls n Tables 8 and 9 suggess ha more han 90 percen of he overall reducon n oal cos per clam for a NEMT program s caused by he ncreased cosreducon effor under he brokerage models. 19
As a check for he robusness of he above resuls, we also esmae equaons (13) and (14) by he mehod of ordnary leas-squares. Tables 10 o 13 presen esmaes of he performance funcons usng ordnary leas-squares esmaon. These esmaes demonsrae he same effecs of organzaonal srucures on program performance as he nsrumenal varables, alhough he magnudes of he effecs are smaller. Thus he emprcal suppor for our heorecal proposons on he ncenve effecs of organzaonal forms s robus o he exac emprcal specfcaon. 6. Concluson The heorecal leraure on ncenve conracs has been well developed. However, he emprcal valdaon of he heory has long lagged behnd he heorecal work. In hs paper, we provde an emprcal es of he ncenve effecs of organzaonal forms, usng daa from Florda s Non-Emergency Medcad Transporaon (NEMT) programs. We analyze he ncenve effecs of dfferen organzaonal forms of Florda s NEMT program wh a smple model of moral hazard. The heorecal proposons are esed usng he cos and ulzaon daa of Florda s Non-Emergency Transporaon programs. We esmae he ncenve effecs usng boh a drec ordnary leas-squares mehod and a wo-sep procedure o conrol for he endogeney of he choce of organzaonal form. The emprcal evdence suppors our heorecal proposons and s robus o emprcal specfcaons. Our sudy suggess ha he choce of organzaonal forms has mporan ncenve effecs on performance. I conrbues o a small bu growng body of evdence supporng he exsence of ncenve effec n organzaons. 20
References Banker, Rajv; Lee, Seok-Young; & Porer, Gordon. 1996. A Feld Sudy of he Impac of a Performance-Based Incenve Plan, Journal of Accounng Economcs 21: 195-226 Communy Transporaon Assocaon of Amerca. 2001. Medcad Transporaon: Assurng Access o Healh Care, A Prmer for Saes, Healh Plans, Provders and Advocaes. Washngon, DC: Communy Transporaon Assocaon of Amerca. Donne, Georges; & S-Mchel, Perre. 1991. Workers Compensaon and Moral Hazard, Revew of Economcs and Sascs 73: 236-244 Ferne, Sue; & Mecalf, Davd. 1999. I s No Wha You Pay I s he Way Tha You Pay I and Tha s Wha Ges Resuls: Jockeys Pay and Performance, Labour 13: 385-411 Fama, Eugene; & Jensen, Mchael. 1983. Agency Problems and Resdual Clams, Journal of Law and Economcs 26: 327-349 Commsson for he Transporaon Dsadvanaged. 2002. Annual Performance Repor. Tallahassee, FL: Commsson for he Transporaon Dsadvanaged. Healh Care Fnancng Admnsraon and Naonal Assocaon of Sae Medcad Drecors Non-Emergency Transporaon Techncal Advsory Group. 1998. Desgnng and Operang Cos-Effecve Medcad Non-Emergency Transporaon Programs. 21
Washngon, DC: Healh Care Fnancng Admnsraon and Naonal Assocaon of Sae Medcad Drecors Groves, Theodore, e al. 1994. Auonomy and Incenves n Chnese Sae Enerprses, The Quarerly Journal of Economcs 109: 183-209. Laffon, Jean-Jacques; & Maouss, Mohamed. 1995. Moral Hazard, Fnancal Consrans and Sharecroppng n El Oulja, Revew of Economcs Sudes 62: 381-399 Lazear, Edward. 2000. Performance Pay and Producvy, Amercan Economc Revew 90: 1346-1361 Legslave Dvson of Pos Aud, Sae of Kansas. 2003. Medcad: Assessng he Cos- Effecveness of Curren Procedures for Transporng Medcad Consumers o he Servces They Need. Topeka, KS: Legslave Dvson of Pos Aud, Sae of Kansas McMllan, John; Whalley, John; & Zhu, Ljng. 1989. The Impac of Chna's Economc Reforms on Agrculural Producvy Growh, The Journal of Polcal Economy 97: 781-807. Offce of Inspecor General, Illnos Deparmen of Publc Ad. 1999. Non-Emergency Medcal Transporaon Revews (Publcaon No. OIG 99-0269). Sprngfeld, IL: Offce of Inspecor General, Deparmen of Publc Ad. 22
Offce of Inspecor General, U.S. Deparmen of Healh and Human Servces. 1997. Conrollng Medcad Non-Emergency Transporaon Coss (Repor No. OEI-04-95- 00140). Washngon, DC: Offce of Inspecor General, U.S. Deparmen of Healh and Human Servces. Offce of Program Polcy Analyss and Governmen Accounably. 1997. Revew of he Transporaon Dsadvanaged Program (Repor No. 96-43). Tallahassee, FL: Offce of Program Polcy Analyss and Governmen Accounably. Offce of Program Polcy Analyss and Governmen Accounably. 1999. OPPAGA Progress Repor: Transporaon Dsadvanaged Commsson Take Acon; Legslave Changes Needed (Repor No. 99-14). Tallahassee, FL: Offce of Program Polcy Analyss and Governmen Accounably. Paarsch, Harry & Shearer, Bruce. 1999. The Response of Worker Effor o Pece Raes: Evdence from he Brsh Columba Tree-Planng Indusry, Journal of Human Resources 34: 643-667 Paarsch, Harry & Shearer, Bruce. 2000. Pece Raes, Fxed Wages, and Incenve Effecs: Sascal Evdence from Payroll Records, Inernaonal Economc Revew 41: 59-92. 23
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Table 2. Regresson Varables Varable Defnon UPB Users per benefcary CPU Clams per user CPC Inflaon-dscouned average cos per clam FORM The organzaonal form of he NEMT program of each couny n each fscal year defned as 1 for Fully Inegraed, 2 for Parally Inegraed, and 3 for Brokerage Only. FFS A dummy varable defned as 1 f he NEMT program s under prevous fee-for-servce delvery model, and 0 oherwse BO A dummy varable defned as 1 f CTC s Brokerage Only ype, and 0 oherwse PI A dummy varable defned as 1 f CTC s Parally Inegraed ype, and 0 oherwse FI A dummy varable defned as 1 f CTC s Sole Source ype, and 0 oherwse CLAIM Number of clams n each couny n each fscal year FY Fscal year BEN Number of benefcares n each couny n each fscal year DOC Number of docors of medcne or oseopahy per square mle n each couny n each fscal year POP Populaon of each couny n each fscal year LAND k Land area of each couny CI The ransporaon prce ndex for each couny n each fscal year REVN The sae s per capa revenue n each fscal year POVERTY Share of populaon n povery n each couny n each fscal year SHMIN Share of mnory populaon n each couny n each fscal year PARTY The absolue value of share of democras among regsered voers mnus.5 n each couny n each fscal year GASPR Gas sales per resden n each couny n each fscal year N_CTY k Sxy sx dummy varables ha equal 1 for couny N=k, and 0 for all oher counes, where N = 2,, 67 25
Table 3. Summary Sascs for Key Varables Varable Mean Sd. Dev. Mn Max COST 55.20 63.36 9.22 807.00 UPB 0.10 0.04 0.03 0.30 CPU 12.61 6.06 3.88 86.00 CPC 41.74 18.41 10.35 146.42 CLAIM 30445 57467 85 676027 BEN 27201 55173 78 495045 DOC 0.59 1.24 0.00 9.39 CI 98.06 2.27 88.98 107.92 LAND 805 385 240 2025 POP 221874 369693 5659 2318845 REVN 2462.67 178.00 2065.89 2644.15 POVERTY 15.52 4.87 0.07 0.29 SHMIN 0.17 0.10 0.02 0.61 PARTY 0.18.12.00.46 GASPR 503.84 108.82 274.30 797.70 Table 4. Number of Counes Adopng Dfferen Organzaonal Forms Fscal Year Complee Brokerage Paral Brokerage Sole Source 1996 10 45 12 1997 9 45 13 1998 9 45 13 1999 9 44 14 2000 12 41 14 2001 12 41 14 2002 12 41 14 26
Table 5. Regresson Resuls for CTCs Selecon of Organzaonal Form Coeffcen Sd. Err. z P> z Fully Inegraed BEN 0.000 0.000 6.500 0.000 CI 0.153 0.081 1.890 0.059 LAND 0.002 0.001 3.330 0.001 POVERTY -0.351 0.060-5.870 0.000 GASPR -0.009 0.001-6.170 0.000 SHMIN -3.666 2.112-1.740 0.083 PARTY 1.943 1.701 1.140 0.253 POP 0.000 0.000-7.050 0.000 CONSTANT -5.264 7.880-0.670 0.504 Brokerage Only BEN 0.000 0.000-1.970 0.049 CI 0.224 0.088 2.560 0.011 LAND 0.000 0.000-0.700 0.481 POVERTY 0.107 0.041 2.640 0.008 GASPR -0.008 0.002-4.570 0.000 SHMIN 3.251 1.586 2.050 0.040 PARTY -10.903 1.893-5.760 0.000 POP 0.000 0.000 0.200 0.841 CONSTANT -19.485 8.405-2.320 0.020 Pseudo R 2 0.292 *The Parally Inegraed model s used as he comparson group. 27
Table 6. Two-Sep Procedure Esmaes of Equaon (13) (Users per Benefcary) Coeffcen Sd. Err. z P> z FI 0.099 0.058 1.710 0.087 PI 0.032 0.035 0.900 0.370 BO -0.284 0.083-3.430 0.001 ln CI 1.284 0.461 2.780 0.006 ln BEN -0.183 0.069-2.650 0.008 ln REVN 1.446 0.241 6.000 0.000 ln DOC -0.187 0.040-4.620 0.000 FY -0.066 0.005-12.240 0.000 R 2 0.780 Table 7. Two-Sep Procedure Esmaes of Equaon (13) (Clams per User) Coeffcen Sd. Err. z P> z FI 0.143 0.064 2.220 0.027 PI 0.086 0.039 2.180 0.030 BO 0.007 0.093 0.080 0.938 ln CI -0.609 0.514-1.180 0.237 ln BEN -0.355 0.077-4.590 0.000 ln REVN 0.730 0.269 2.710 0.007 ln DOC -0.021 0.045-0.470 0.642 FY 0.040 0.006 6.580 0.000 R 2 0.665 Table 8. Two-Sep Procedure Esmaes of Equaon (13) (Cos per Clam) Coeffcen Sd. Err. z P> z FI -0.486 0.063-7.770 0.000 PI -0.292 0.038-7.610 0.000 BO -0.003 0.090-0.030 0.978 ln CI 1.515 0.500 3.030 0.003 ln BEN 0.111 0.075 1.480 0.140 ln REVN -0.540 0.261-2.070 0.039 ln DOC -0.023 0.044-0.520 0.606 FY 0.022 0.006 3.840 0.000 R 2 0.724 28
Table 9. Two-Sep Procedure Esmaes of Equaon (14) (Cos per Clam) Coeffcen Sd. Err. z P> z FI -0.447 0.062-7.250 0.000 PI -0.273 0.038-7.230 0.000 BO -0.047 0.088-0.540 0.593 ln CI 1.625 0.490 3.310 0.001 ln BEN 0.186 0.075 2.480 0.013 ln REVN -0.188 0.264-0.710 0.477 ln DOC -0.056 0.043-1.300 0.195 FY 0.018 0.006 3.140 0.002 ln CLAIM -0.162 0.029-5.590 0.000 R 2 0.735 Table 10. Leas-Squares Esmaes of Equaon (13) (Users per Benefcary) Coeffcen Sd. Err. z P> z FI 0.076 0.041 1.820 0.069 PI -0.027 0.030-0.910 0.365 BO -0.086 0.043-2.020 0.044 ln CI 1.116 0.443 2.520 0.012 ln BEN -0.173 0.070-2.470 0.014 ln REVN 1.365 0.242 5.630 0.000 ln DOC -0.187 0.040-4.630 0.000 FY -0.063 0.005-11.850 0.000 R 2 0.779 Table 11. Leas-Squares Esmaes of Equaon (13) (Clams per User) Coeffcen Sd. Err. z P> z FI 0.116 0.046 2.520 0.012 PI 0.073 0.033 2.210 0.027 BO 0.056 0.048 1.190 0.236 ln CI -0.598 0.494-1.210 0.226 ln BEN -0.351 0.078-4.500 0.000 ln REVN 0.699 0.270 2.590 0.010 ln DOC -0.023 0.045-0.520 0.603 FY 0.041 0.006 6.920 0.000 R 2 0.665 29
Table 12. Leas-Squares Esmaes of Equaon (13) (Cos per Clam) Coeffcen Sd. Err. z P> z FI -0.377 0.045-8.430 0.000 PI -0.260 0.032-8.080 0.000 BO -0.116 0.046-2.520 0.012 ln CI 1.4637 0.479 3.060 0.002 ln BEN 0.110 0.076 1.450 0.146 ln REVN -0.453 0.262-1.730 0.084 ln DOC -0.018 0.044-0.420 0.673 FY 0.0167 0.006 2.910 0.004 R 2 0.725 Table 13. Leas-Squares Esmaes of Equaon (14) (Cos per Clam) Coeffcen Sd. Err. z P> z FI -0.346 0.044-7.830 0.000 PI -0.252 0.032-8.000 0.000 BO -0.121 0.045-2.680 0.008 ln CI 1.548 0.469 3.300 0.001 ln BEN 0.187 0.075 2.490 0.013 ln REVN -0.118 0.263-0.450 0.654 ln DOC -0.053 0.043-1.220 0.224 FY 0.013 0.006 2.310 0.021 ln CLAIM -0.162 0.029-5.630 0.000 R 2 0.736 30