Are Health Insurance Markets Competitive? By Leemore Dafny*

Ar Halth Insuranc Markts Comptitiv? By Lmor Dafny* To gaug th comptitivnss of th group halth insuranc industry, I invstigat whthr halth insurrs charg highr prmiums, ctris paribus, to mor profitabl firms. Such dirct pric discrimination is only fasibl in imprfctly comptitiv sttings. Using a propritary national databas of halthplans offrd by a sampl of larg, multisit firms from 1998-2005, I find firms with positiv profit shocks subsquntly fac highr prmium growth, vn for th sam halthplans. Morovr, within a givn firm, thos sits locatd in concntratd insuranc markts xprinc th gratst prmium incrass. Th findings suggst halthcar insurrs ar xrcising markt powr in an incrasing numbr of gographic markts. Th U.S. stands virtually alon among lading industrializd nations in its havy and incrasing rlianc on th privat insuranc sctor to intrmdiat halthcar for its rsidnts. 1 Th assumption undrlying this systm is that firc comptition among privat insurrs yilds mor fficint outcoms, broadly writ (Alain C. Enthovn 1978). Howvr, a comprhnsiv survy on th stat of comptition in halthcar apparing in th 1999 Journal of Economic Prspctivs concluds thr is littl mpirical vidnc on comptitiv conduct by halth insuranc firms (Martin S. Gaynor and Dborah Haas-Wilson 1999). A 2004 rport on th sam by th Fdral Trad Commission and th Dpartmnt of Justic finds most xprts bliv th markt is highly comptitiv (with th vocal xcption of groups rprsnting physicians), *Northwstrn Univrsity, Kllogg School of Managmnt, Jacobs Cntr Suit 607, 2001 Shridan Rd., Evanston, IL, 60201, and NBER (-mail: l-dafny@kllogg.northwstrn.du). I am gratful for hlpful suggstions by th ditor, thr anonymous rfrs, and William Collins, David Cutlr, Jams Dana, David Dranov, Mark Duggan, Vivian Ho, Kathrin Ho, Julian Jamison, Ilyana Kuzimko, Mara Ldrman, Jin Li, Niko Matouschk, San Nicholson, Mark Pauly, Scott Schafr, Kosali Ilaypruma Simon, Alln Stinbrg, Scott Strn, John Tatom, Robrt Town, Dal Yamamoto, and sminar participants at Columbia, Duk, Univrsity of Chicago, Univrsity of Maryland, Wharton, th NBER Summr Institut, th Amrican Economic Association Annual Confrnc, th Northwstrn Univrsity Law School, and th Sarl Cntr Rsarch Symposium on Insuranc Markts and Rgulation. Michal Loqurcio, Tamara Hayford, and Subramaniam Ramanarayanan providd xcllnt rsarch assistanc. Funding from Th Sarl Cntr on Law, Rgulation, and Economic Growth at th Northwstrn Univrsity School of Law is gratfully acknowldgd. 1 Othr notabl xcptions includ th Nthrlands and Switzrland. Both countris rquir individuals to purchas an approvd halthplan from a privat insurr. 1

although nw rsarch on th subjct is scarc and plagud by data and idntification issus (s Dnnis P. Scanlon, Michal E. Chrnw and Woolton L 2006 for a thorough rviw). 2 Manwhil, continud faith in comptitiv markts is manifst in th rapid incras in outsourcing of public insuranc to th privat sctor (Mark G. Duggan 2004; Duggan and Fiona M. Scott Morton 2008), as wll as lax antitrust nforcmnt during two dcads of xtnsiv insurr consolidation. Only thr combinations hav bn challngd by th Dpartmnt of Justic, and ths only in slct markts. 3 This study valuats whthr and whr local insuranc markts ar comptitiv by tsting for vidnc of conduct that can only occur in imprfctly comptitiv markts. I invstigat whthr firms with highr profits pay highr halth insuranc prmiums, controlling as bst as possibl for diffrncs in th plans slctd, mploy populations, and markt conditions. Th xtnt to which carrirs ar abl to xtract mployr-spcific rnts offrs a glimps into comptitiv intractions in this important sctor, as a comptitiv industry would b charactrizd by uniform pricing at (mployr-spcific) cost. Although a markt conduct paramtr (i.. a masur ranging from 0 to 1, with 0 rprsnting prfct comptition and 1 monopoly) cannot b drivd from stimats of rnt xtraction, diffrncs in rnt xtraction across markts provid a usful indicator of th rlativ comptitivnss of ths markts. Using a propritary panl databas on fully-insurd halthplans offrd by a sampl of larg, multi-sit mployrs btwn 1998 and 2005, I find firms with positiv profit shocks subsquntly fac largr prmium incrass, vn for th sam halthplans. Morovr, this incras is gratst in markts with th fwst insuranc carrirs (particularly 6 or fwr). Thus, a multi-sit firm with high profits in a givn yar will subsquntly fac significantly highr halth insuranc prmiums, but only at sits srvd by a concntratd insuranc markt. This 2 Improving Halth Car: A Dos of Comptition, A Rport by th Fdral Trad Commission and th Dpartmnt of Justic (July 2004). 3 Ths challngs wr satisfid through consnt dcrs rquiring divstitur in th markts with substantial ovrlap (Tucson and Bouldr in th cas of th UnitdHalth-PacifiCar mrgr in 2005; Houston and Dallas in th cas of th Atna-Prudntial mrgr in 1999; and Las Vgas (Mdicar Advantag plans only) in th cas of th pnding UnitdHalth-Sirra mrgr in 2008). Complaint, Unitd Stats v. Atna Inc., N0.3-99CV 1398-H, par. 19 and 20 (N.D. Tx. Jun 21, 1999); Final Consnt Ordr, Unitd Stats v. Atna Inc., No.3-99CV 1398-H (N.D. Tx. Dc. 7, 1999); Complaint, Unitd Stats v. UnitdHalth Group Incorporatd & PacifiCar Halth Systms, Inc., No. 1:05CV02436 (Dc. 19, 2005); Final Judgmnt, Unitd Stats v. UnitdHalth Group Incorporatd & PacifiCar Halth Systms, Inc., No. 1:05CV02436 (May 23, 2006). Final Judgmnt, Unitd Stats V. UnitdHalth Group Incorporatd and Sirra Halth Srvics, Inc. No. 1:08CV00322. 2

rsult contradicts th lading altrnativ mpirical xplanation for my finding, namly that firms with high profits fac highr prmium incrass bcaus thy incras bnfits in dimnsions I do not obsrv. (If this is th xplanation, it should occur uniformly across all sits.) To dtrmin why insuranc carrirs ar abl to xtract highr prics from profitabl firms in concntratd insuranc markts, I combin insights from fild intrviws with a modl of bilatral bargaining, as larg mployrs and insurrs bargain annually ovr insuranc contracts. Th vidnc suggsts mployrs ar rluctant to switch halthplans during good tims, i.. profits incras willingnss-to-pay for incumbnt halthplans. Th fact that, conditional on th sam profit shock, prmiums incras th most in markts srvd by a concntratd insuranc industry could b xplaind by a) largr profit-inducd incrass in switching costs in concntratd insuranc markts (i.. thr is mor nw rnt to xtract in ths markts), b) gratr bargaining (or markt) powr of insurrs in ths markts, or both. Rturning to th data, I find no support for a): conditional on th sam profit shock, firms in markts with fwr insuranc carrirs ar mor likly to switch carrirs, suggsting switching costs do not incras mor for profitabl mployrs in ths markts. Rathr, it appars that th strong bargaining position of insurrs in concntratd markts nabls thm to captur mor of th xtra surplus gnratd by profit shocks. (Bcaus prics ar ultimatly th rsult of bargaining btwn mployrs and carrirs, I gnrally us th trm rnt xtraction in plac of pric discrimination, which is typically rsrvd for sttings in which th sllr has commitmnt powr, i.., maks a singl tak it or lav it offr. This tchnicality notwithstanding, th practic I invstigat is akin to first-dgr pric discrimination, in which th sllr sts individual prics to xtract th surplus of ach buyr. In th cas of a monopoly supplir, consumr surplus is wholly xtractd. 4 Howvr, consumrs rtain som of th surplus in oligopoly sttings (Danil F. Spulbr 1979; Mark Armstrong 2006). 5 4 Th trm pric discrimination is typically rsrvd for sttings in which th sllr has commitmnt powr, i.., maks a singl tak it or lav it offr. For this rason, I us th trm rnt xtraction in its stad, although th outcoms ar th sam. 5 Spulbr s modl assums ach firm facs a downward-sloping rsidual dmand curv and has th ability to prfctly discriminat. Th pur-stratgy Nash quilibrium is charactrizd by marginal-cost pricing; social surplus is thrfor maximizd. Th rsidual dmand curvs bcom mor lastic as comptition incrass, nabling consumrs to captur an incrasing shar of surplus. 3

Th rsults offr th strongst vidnc to dat linking privat halth insuranc prmiums to th markt powr of insurrs. Th data also indicat that an incrasing shar of th population is purchasing covrag in th last comptitiv markts. As of 2005, 23 prcnt of mploys in my sampl (which is rprsntativ of Amricans covrd by larg firms, who account for roughly on-third of th insurd nonldrly) rcivd covrag in markts with 6 or fwr major carrirs (in which rnt xtraction is most pronouncd), up from 7 prcnt in 1998. 6 Du to rcnt consolidations, this figur is crtainly gratr today. Th findings complmnt rcnt work by Kathrin Ho (2009) on th upstram bargaining btwn insurrs and hospitals. Ho finds insurrs in som markts succssfully xtract th rnts of hospitals in thir ntworks, and hospitals in turn diffrntiat thmslvs to avrt this. Collctivly, th rsults imply th full bnfits of a comptitiv marktplac ar not bing ralizd by a larg sgmnt of th privatly-insurd. Gratr scrutiny of proposd consolidations in this sctor may also b warrantd, with particular attntion to consolidations in markts with 6 or fwr major insuranc carrirs, and whr switching costs of customrs ar high (.g. if carrirs ar highly diffrntiatd). Th papr procds in six sctions. Sction I provids background on th privat halth insuranc industry and summarizs prior rsarch. Sction II dscribs th data in dtail. Sction III prsnts th main mpirical analysis of rnt xtraction, togthr with ky robustnss chcks and xtnsions. Th modl is dscribd in Sction IV, and analyss of halthplan switching ar prsntd in Sction V. Sction VI concluds. I. Th U.S. Halth Insuranc Industry A. Ky Facts Figur 1 graphs th prcntag of nonldrly Amricans covrd by privat insuranc from 1998-2005, sparatd by whthr th covrag was mploymnt-sponsord or individually- 6 Th stimat of th numbr of insurd nonldrly Amricans covrd by larg firms (1000+ mploys) was constructd by th author using stimats from th MEPS-IC (gnrously providd by Kosali Simon) and th Employ Bnfits Rsarch Institut (http://www.bri.org/pdf/brifspdf/ebri_ib_10a-20061.pdf). 4

purchasd. Covrag from both sourcs dclind slightly during th study priod, but rmaind high, with 70 prcnt of th nonldrly obtaining insuranc through th privat sctor in 2005. Ths figurs undrstat th fraction of th nonldrly nrolld in privat plans, as th majority of Mdicaid bnficiaris ar also nrolld in such plans (61 prcnt in 2005). Among th ldrly, 95 prcnt ar nrolld in Mdicar, and narly 13 prcnt of ths rcivd thir car in 2005 through a privat-sctor Mdicar Advantag plan. An additional 59 prcnt of th ldrly had privat supplmntary covrag in 2005. 7 FIGURE 1 ABOUT HERE National statistics on privat halthplans ar availabl from th annual Employr Halth Bnfits survy, sponsord jointly by th Kaisr Family Foundation (KFF) and th Halth Rsarch and Educational Trust (HRET). 8 This survy documnts two ky trnds that ar corroboratd in my data. Th first is th rapid incras in halth insuranc prmiums. Figur 2 illustrats ths incrass for 1998-2005, basd on figurs for a family of four. Annual growth (for slf and full-insurd plans) pakd at 13.9 prcnt in 2003, dclining to a still-imprssiv 9.3 prcnt in 2005. Ths figurs likly undrstat th trnd as mployrs hav adjustd to rising costs by rducing th gnrosity of bnfits providd. FIGURE 2 ABOUT HERE Th scond trnd is th growth in th shar of mploys covrd by slf-insurd rathr than fully-insurd plans (Figur 3). Many larg mployrs choos to slf-insur, outsourcing 7 Sourc: http://www.bri.org/pdf/publications/books/databook/db.chaptr%2036.pdf. Ths figurs do not rflct Mdicar Part D, th prscription drug program introducd in 2006. Mdicar Part D is administrd ntirly by th privat sctor and currntly covrs ovr 90 prcnt of Mdicar bnficiaris. Many providrs ar pharmacy bnfit managmnt firms rathr than halth insuranc carrirs. 8 Th KFF/HRET survy randomly slcts public and privat mployrs to obtain national data about mployrsponsord halth insuranc; approximatly 2000 mployrs rspond ach yar. Th data ar not publicly availabl, nor is th sampl dsignd to provid stimats at th markt lvl. (KFF/HRET Employr Halth Bnfits 2006 Summary of Findings, documnt 7528). Sinc 1996, th Agncy for Halthcar Rsarch and Quality (AHRQ), a division of th Dpartmnt of Halth and Human Srvics, has also conductd an annual survy of mployrs in conjunction with th Mdical Expnditur Panl Survy (MEPS). MEPS follows housholds ovr tim, and th Insuranc Componnt survys mployrs of houshold mmbrs to gathr data on halthplans. Th micro data ar availabl on-sit at Cnsus Rsarch Cntrs to thos with appropriat claranc, but thy do not constitut an mployr-plan-lvl panl. Th most rcnt data availabl is for 2003. 5

bnfits managmnt and/or claims administration but paying ralizd costs of car. Such mployrs can sprad risk across larg pools of nrolls, and may purchas stop-loss insuranc to limit thir rmaining xposur. Pr ERISA (th Employ Rtirmnt Act of 1974), ths plans ar also xmpt from stat rgulations and stat insuranc prmium taxs. According to th KFF/HRET survy, th shar of larg-firm mploys nrolld in slf-insurd (as opposd to fully-insurd) plans incrasd from 65 prcnt in 1998 to 82 prcnt in 2005. Th incras among mploys in all firms was much smallr: 50 to 54 prcnt. 9 FIGURE 3 ABOUT HERE My primary study sampl includs only fully-insurd plans. Rportd prmiums for slf-insurd plans ar actually th mployr s stimat of outlays for th avrag nroll in th plan-yar. Ths forcasts ar usd for budgting purposs and to mak dcisions about nroll contributions and stop-loss covrag. Thy ar not dirctly comparabl to prmiums for fullyinsurd plans, which ar st prospctivly and always includ risk prmiums. Slf-insurd projctions may includ a partial risk prmium if th mployr purchass stop-loss covrag; whthr stop-loss covrag is purchasd is not capturd in th data. I mak us of th slfinsurd sampl, howvr, for a numbr of supplmntal analyss. Prmiums for fully-insurd plans dpnd on th actuarial halth risk of mploys, dtails of plan dsign (.g., copays, covrd bnfits, disas managmnt programs), and gnral carrir charactristics (.g., providr ntwork, spd and accuracy of claims procssing, rputation). Th mployrs rprsntd in my sampl typically solicit bids vry yar from on or mor halthplans in all of th markts in which thy oprat. Many us bnfits consultants to srv as brokrs in this procss. According to th brokrs I intrviwd, aftr som back-andforth on plan dtails (.g. copays, drug formularis, tc.), a final round of ngotiation ovr th prmium for a fixd plan dsign may tak plac. Th nt rsult is that pricing of fully-insurd halthplans is anything but transparnt, rndring th stting rip for diffrntial pricing across mployr groups. 9 Th ris in slf-insuranc, though byond th scop of this papr, is an intrsting subjct for furthr rsarch. Early work by Coopr and Simon (2007) rvals that firms ar mor likly to slf-insur if thy hav multipl locations, a larg numbr of workrs, and high avrag wags. 6

Contracts ar signd 3 to 6 months prior to th start of th bnfit yar, which is gnrally th calndar yar. Thus, an mployr will typically bgin slcting 2010 plans and rats arly in 2009. To th xtnt that firm profits affct ths agrmnts, th rlvant profit figur will rflct data for 2008 (assuming data is availabl annually). 10 B. Prior Rsarch A 2006 survy by Scanlon, Chrnw and L finds 35 studis that invstigat th impact of comptition among halth insurrs on halthcar outcoms. Of ths, 7 us som masur of prmiums as an outcom. Most find a ngativ association btwn comptition and prmiums, but ths studis suffr from considrabl data problms and idntification issus. For xampl, on of th most carful studis (Douglas R. Wholy, Rogr D. Fldman, and Jon B. Christianson 1995) rlis on annual HMO-lvl data from 1988-1991. Prmiums ar stimatd using avrag rvnu pr mmbr pr month, and th dgr of comptition facd by ach HMO is stimatd as a wightd avrag of th HMO pntration rat (th prcnt of insurd individuals nrolld in an HMO) in all of th countis in which th HMO oprats. PPOs ar not considrd, although in rcnt yars courts hav found HMOs and PPOs (as wll as th variants in btwn) to b in th sam product markt. 11 Summarizing th shortcomings in this litratur at larg, Scanlon, Chrnw and L mphasiz a poor corrspondnc btwn masurs of markt comptition and actual comptitiv conditions. No studis addrss ndognity of th concntration masurs. Two rcnt studis by Jami C. Robinson (2004, 2006) dscrib th high and incrasing lvl of concntration in local insuranc markts. Th first study uss a databas of stat rgulatory filings to study stat-lvl markt structur ovr 2000-2003. By th nd of this study priod, narly 40 stats had a dominant carrir srving ovr on-third of th privat markt. Robinson also documnts incrass in prmium rvnus and oprating margins during th sam 10 Ginsburg t al. (2006) find vidnc of a similar lag (18 months) btwn prmiums rportd by KFF/HRET and th cost of halthcar srvics (.g., providr chargs). 11 Th cas law is summarizd in Improving Halth Car: A Dos of Comptition, ibid. Som cass in which sparat markts for HMOs and PPOs hav bn rjctd includ Blu Cross & Blu Shild v. Marshfild Clinic (65 F.3d 1406 (7 th Cir. 1995)) and Ball Mmorial Hospital v. Mutual Hospital Ins., Inc.(784 F.2 nd 1325 (7 th Cir. 1986)). 7

priod. Of cours, a causal link btwn concntration and prmiums cannot b stablishd through th coincidnc of ths trnds. In addition, a commntary publishd alongsid th pic highlights concrns ovr th markt dfinition: an ntir stat is not a rlvant gographic markt, [hnc] th xistnc of high HHIs in that stat has no comptitiv (or probativ significanc) (David A. Hyman and William E. Kovacic 2004). Robinson (2006) documnts still highr stat-lvl concntration figurs. H also rports many insurrs ar targting th public rathr than th privat sctor for futur growth. Th following sction offrs dtails on th high-quality, micro panl data that affords m th uniqu opportunity to xamin th pricing of individual insuranc contracts in th gographic markts actually utilizd by insurrs whn ngotiating rats. Importantly, th idntification stratgy rlis on shocks to individual mployrs rathr than shocks to markt concntration. I. Data A. Th LEHID Data Th primary datast was providd on a confidntial, limitd-us basis by a major bnfits consulting firm. 12 Th unit of obsrvation is th plan-yar. A plan is dfind as a uniqu combination of an mployr, gographic markt, insuranc carrir, and plan typ (HMO, POS, PPO, and indmnity),.g., Worldwid Widgts CIGNA HMO in Phonix, Arizona. Th panl covrs 1998-2005 (inclusiv), and is unbalancd, with mployrs ntring and xiting basd on thir rlationship with th consulting firm, and spcific halthplans apparing or disapparing whn addd or trminatd, rspctivly. Not that participation is complt for any yar in which an mployr is includd in th sampl (i.., all plans offrd by that mployr ar prsnt). 13 12 Employrs of all sizs rly on xtrnal consultants whn dsigning or purchasing bnfits. Using a 1997 survy of 21,545 privat mployrs, Marquis and Long (2000) find xtrnal consultants wr mployd by narly half of th smallst firms (<25 workrs), and narly two-thirds of th largst firms (>500 workrs). Ths findings suggst th firms ngaging th srvics of my sourc ar not unusual in this rgard, strngthning th cas for th gnralizability of th rsults. 13 Som data scrubbing was ncssary to nsur that th sam ID was assignd to th sam mployr in vry yar. In th cas of mrgrs, I crat a nw mployr ID post-mrgr if both partis to th mrgr appar in th data sparatly in a prior yar. 8

Th full datast includs obsrvations from 776 mployrs and 139 gographic markts in th Unitd Stats. Th mployrs span a wid rang of industris. Th top 3 ar manufacturing and financial institutions (tid for 13 prcnt of mployrs ach), and consumr products (9 prcnt of mployrs). On avrag, 241 mployrs appar in th sampl ach yar. Th mdian mployr oprats in 47 gographic markts and insurs 9,670 activ mploys (rtirs ar not includd in th data). Th total numbr of mploys rprsntd in th sampl avrags 4.8 million pr yar. This figur dos not includ dpndnts, so th numbr of insurd individuals rprsntd by th survy is at last twic as larg. Th gographic markts ar dfind by my sourc, and thy rprsnt th markts usd by carrirs and mployrs whn ngotiating rats. 14 Th markts ar somtims dfind by stat boundaris (.g., Dlawar), but mor commonly by mtropolitan aras (.g., Kansas City (in Missouri and Kansas); Kntucky Louisvill, Lxington; Kntucky xcpt Louisvill, Lxington). Figur 4 dpicts th distribution of covrd mploys across th gographic markts. This distribution closly matchs th distribution of privatly-insurd mploys in ths markts (stimatd using county-lvl data from th Currnt Population Survy of March 2000). I will rfr to th ntir datast by th acronym LEHID, for Larg Employr Halth Insuranc Datast. B. Study Sampl Th study sampl is limitd to fully-insurd plans, for which prmiums ar dtrmind prior to th start of th calndar yar. 15 Th shift toward slf-insurd plans, highlightd in th KFF- HRET survy, is also apparnt in LEHID: th proportion of mploys nrolld in slf-insurd plans incrasd from 58 to 76 prcnt btwn 1998 and 2005. Howvr, th total numbr of mploys in fully-insurd plans is still sizabl, avraging 1.6 million pr yar. 16 14 Som carrirs with a national prsnc will ngotiat a singl rat for all mploys nationwid. S footnot 18 for a discussion of th implications of national pricing for th mpirical analysis. 15 Slf-insurd plans rport prmium quivalnts, thir prdictions of costs pr nroll. Ths figurs combin claim rimbursmnt, fs paid to carrirs, and prmiums for any stop-loss insuranc. 16 Thr is a good dal of ovrlap in th carrirs srving slf-insurd and fully-insurd groups. Among carrirs srving mor than 5 clints in LEHID, 57 prcnt hav both fully-insurd and slf-insurd plans, 41 prcnt hav 9

I rstrict th study sampl to obsrvations in gographic markts containing 20 or mor distinct mployrs; that is, 20+ mployrs must offr a fully-insurd (FI) choic in that marktyar. This rstriction is imposd to nsur accurat stimats of markt structur, namly th total numbr of carrirs srving a givn gographic markt. 17 Only 3 prcnt of th fullyinsurd mploys in my sampl ar droppd as a rsult of this rstriction. Not this LEHID- FI sampl is not th sampl usd for th rgrssion analysis; that sampl is furthr limitd to plans for which profits of th associatd mployr can b obtaind, and is dscribd blow. Figur 2 shows that prmium growth in th LEHID-FI sampl tracks th lvls and trnds publishd by KFF/HRET for FI plans fairly closly. This bods wll for th gnralizability of th data and rsults. Figur 5 graphs th distribution of markts in th LEHID-FI sampl by th numbr of carrirs in th markt. Data ar prsntd sparatly for 1998, 2001, and 2005. Th fraction of markts with fwr than 6 carrirs incrasd from 10 to 35 prcnt ovr this priod, whil th fraction with mor than 10 carrirs dcrasd from 35 to 7 prcnt. Th incras in concntration is also manifstd in othr masurs such as th HHI and th 4-firm concntration ratio. Howvr, ths masurs ar mor pron to masurmnt rror du to th siz and nonrandom natur of th sampl. FIGURE 5 AROUND HERE only fully-insurd plans, and 2 prcnt hav only slf-insurd plans. Th smallr carrirs (<=5 clints) ar mor likly to b pur plays, with 11, 54, and 35 prcnt in ths catgoris, rspctivly. Figurs ar tabulatd using th carrir-yar as th unit of obsrvation. 17 Attmpts to stimat th numbr of carrirs from altrnativ sourcs wr unsuccssful. Thr ar thr potntial sourcs of nationwid data for th study priod: th Ara Rsourc Fil, Intrstudy (a privat firm that compils data on HMOs from stat rgulatory filings and various othr sourcs), and wb sarchs. Th Ara Rsourc Fil rports th numbr of HMOs hadquartrd in ach county, clarly a vry poor stimat of th dsird variabl. Intrstudy provids information on th numbr and nrollmnt of HMOs by MSA. Howvr, th Intrstudy data is prohibitivly xpnsiv, xcluds PPOs (which clarly compt with HMOs) in most yars covrd by this study, and has bn roundly criticizd for th mthods it uss to attribut nrollmnt to diffrnt gographic aras (Scanlon t al 2006). Wb sarchs also provd fruitlss for svral rasons. It is difficult to find tim-sris data for all markts, and to accuratly captur th srvic ara for ach halthplan from th limitd dscriptions availabl onlin. Som insurrs idntifid in ths sarchs only srv particular markt sgmnts (.g. th individual markt or th Mdicaid markt), and this analysis is concrnd with th larg, fully-insurd group markt. Using th LEHID data itslf (aftr applying th stringnt 20+ critrion) should yild th most accurat stimat of th numbr of carrirs srving th customr sgmnt and gographic markt of intrst. 10

Th ky indpndnt variabl for th analysis is th oprating profit of mployrs. To obtain profit data, I cratd a crosswalk fil to match LEHID-FI mployrs to companis apparing in Compustat, a databas of financial statistics. Th matchs wr idntifid by hand using company nams, industry, locations, and numbr of mploys. Extnsiv wb rsarch was rquird to vrify matchs for som obsrvations, spcially in cass of subsidiaris, non- U.S. firms, and firms involvd in mrgrs and acquisitions. Profit is masurd by th aftr-tax rturn on assts, dfind as (arnings bfor xtraordinary itms + intrst xpns) / (gross assts (including dprciation/amortization)). 18 Bcaus Compustat is limitd to larg, publiclytradd firms, th LEHID FI-Compustat sampl omits public-sctor, nonprofit, and privatly-hld mployrs, as wll as mployrs that do not appar in Compustat or lack data for th variabls usd to calculat oprating profits. Of th 1678 mployr-yars in th LEHID FI sampl, I am abl to calculat laggd profit for 1151, or 69 prcnt of obsrvations. To control for local conomic conditions and halthcar utilization trnds, I add data on th unmploymnt rat (rportd by th Burau of Labor Statistics) and th Avrag Adjustd Pr Capita Cost for Mdicar nrolls (abbrviatd AAPCC and rportd by th Cntr for Mdicar and Mdicaid Srvics). Both masurs ar availabl at th county-yar lvl, whras LEHID markts ar dfind by my sourc using 3-digit zipcods. Th corrspondnc is gnrally on-to-on in major mtropolitan aras, whr most LEHID mploys ar locatd. For thos countis blonging to mor than on markt cod, I assign wights in proportion to th shar of th population in ach markt cod accountd for by th zipcods within that county. Tabl 1 prsnts dscriptiv statistics for th LEHID FI-Compustat sampl in ach yar. Th ky variabls includ annual prmium, nrollmnt, dmographic factor, plan dsign, plan typ, and laggd profit. 19 Annual prmium combins mployr and mploy contributions, and is a pr-mploy avrag. It rflcts both th faturs of th plan slctd (.g., insuranc 18 Compustat provids fiv altrnativ dfinitions of th aftr-tax rturn on gross assts. This dfinition corrsponds most closly to th masur of firm profitability usd in Disapparing dividnds: changing firm charactristics or lowring propnsity to pay? (Fama and Frnch 2001). Rsults using th four othr masurs ar xtrmly similar (s Onlin Appndix for dtails). 19 Prmiums ar rportd in nominal dollars. All spcifications us ln(prmium) as th dpndnt variabl and includ yar fixd ffcts, so nationwid dflators will not affct th cofficints of intrst. 11

carrir, bnfit dsign, tc.) as wll as th charactristics of th insurd population (.g., dmographics and risk profil). TABLE 1 ABOUT HERE Dmographic factor is a summary masur that rflcts family siz, gndr, and ag. Plan dsign capturs th gnrosity of bnfits, including th lvl of copaymnts rquird of nrolls. Th xact formula usd to calculat ths factors wr not disclosd to m. It is worth noting, howvr, that my sourc uss ths factors to normaliz and thn compar prmiums across plans and firms, and thy ar an industry ladr in halthplan slction and dsign. Th dclin in plan dsign during th study priod is also notworthy, as it is consistnt with rports that mployrs hav rducd bnfits in an ffort to contain cost growth (so-calld bnfit buybacks ). Four plan typs ar rprsntd in th data. Ordrd by th rstrictivnss of th providr ntwork for ach plan, ths ar: Indmnity (all providrs covrd), PPO (prfrrd providrs fully covrd, non-prfrrd providrs covrd in part), POS ( point of srvic plan: car is managd as in an HMO, and if approval for a srvic is obtaind prfrrd providrs ar covrd in full and non-prfrrd providrs in part), and HMO (car is managd and prfrrd providrs ar fully covrd). Approximatly 90 prcnt of th plans in th LEHID FI-Compustat sampl ar HMOs. As discussd abov, profit is laggd two yars to rflct th timlin for plan slction. Thus th 2001 rcssion is apparnt in th summary statistics for 2003. Th rcssion had varying impacts across firms and sctors, as vidncd by th larg incras in th standard dviation in 2003. This is prcisly th typ of variation that idntifis th ffct of intrst. Th LEHID FI-Compustat sampl includs an avrag of 144 mployrs and 102 markts pr yar. Th dclin in obsrvations during th last two yars rflcts both th trnd away from 12

FI plans, and a gnral dclin in th numbr of mployrs in th LEHID sampl. 20 Ths trnds ar apparnt in Appndix Tabl 1, which givs th numbr of mployrs includd in LEHID in vry yar, togthr with th shar with at last 1 FI plan and at last 1 SI plan. II. Do Profitabl Firms Pay Mor For Halth Insuranc? A. Main Analysis My mpirical stratgy rlis on th assumption that mployrs ar willing to pay mor for halth insuranc whn profits ar high (why is th subjct of Sctions 5 and 6). If tru, insuranc carrirs may xploit this circumstanc by adjusting prmiums accordingly. Th ky rgrssion rlats plan prmiums to laggd mployr profits. Rcall a plan is an mployr-gographic markt- insuranc carrir-plan typ combination, dnotd by th subscript mcj. Th first spcification can b xprssd as follows: (1) ln(prmium) mcjt = α + γ1 profit margin, t 2 + ξ [ +ρ + ν mcj m + ψ ] [ + X c mt + η j + δ β] [ +φ mt t + γ + ω ] + ε 2 jt dmographics mcjt + ς m mcjt Equation (1) includs fixd ffcts for ach mployr, markt m, carrir c, plan typ j, and yar t. Employr fixd ffcts hlp to captur unobsrvd, tim-invariant diffrncs in th composition of th population covrd, bnfit dsign, and usag pattrns for a givn mployr, all of which affct plan prmiums. Markt fixd ffcts captur diffrncs in mdical costs (.g., du to local wags) and practic. Thr is a litratur that documnts substantial diffrncs in mdical practic and utilization (though, intrstingly, not in outcoms) across gographic markts (.g., John E. Wnnbrg, Elliot S. Fishr, and Jonathan S. Skinnr (2002)). Plan typ fixd ffcts captur avrag pric diffrncs for ths broad product groups, and carrir fixd ffcts captur avrag pric diffrncs across carrirs du to tim-invariant 20 Th dclin is hightnd by th sampl rstriction that drops all obsrvations in markt-yars with fwr than 20 mployrs offring at last 1 fully-insurd plan. In sction 6, I confirm th rsults ar similar whn this rstriction is liftd. 13

charactristics such as rputation. Finally, yar fixd ffcts absorb annual growth in prmiums nationwid. Thr ar nin scond-ordr intractions that could thortically b includd in this spcification, howvr it is nithr computationally fasibl nor conomically snsibl to includ thm all in th baslin modl. 21 I rly on institutional knowldg to slct two to includ in all spcifications: plan typ-yar ffcts ( ω jt ) and mployr-markt ffcts ( ς m ). (Th rmaining 7 will vntually b includd in modls discussd blow.) Th plan typ-yar ffcts absorb diffrnt prmium growth pattrns across plan typs, such as th wll-known incras in HMO prmiums associatd with a loosning of HMO rstrictions during this ra of managd car backlash. Th mployr-markt intractions captur prmium diffrntials associatd with diffrncs in th composition of mploy populations and/or unobsrvd plan gnrosity across markts,.g. hadquartrs vs. rtail locations. Ths intractions will also captur prmium diffrntials associatd with mployrs who ar xpanding vrsus contracting th numbr of markts in which thy oprat. To th xtnt xpanding mployrs ar both mor profitabl and mor gnrous with insuranc bnfits (in dimnsions not capturd by th covariats alrady in th modl), th cofficint on profits could b upward-biasd in th absnc of ths intractions. Adding additional intraction trms to th modl (whthr scond-ordr or gratr) rducs th possibility of omittd variabls bias but also liminats potntially xognous variation that can b usd to idntify γ 1. In rcognition of this tradoff, I prsnt rsults for spcifications with and without th bracktd trms in quation 1. I bgin by introducing fixd ffcts for ach mployr-markt-plan typ-carrir combination ( ρ mcj ). Onc ths plan fixd ffcts ar includd, γ 1 is idntifid by within-plan changs in prmiums and changs in th profits of affiliatd mployrs (du to th inclusion of mployr fixd ffcts). Th ky advantag of including plan fixd ffcts is th limination of cross-sctional variation as a sourc of idntification for γ 1. For xampl, if firms xprincing positiv profit shocks tnd to choos gnrous bnfit packags (within a givn plan typ and carrir), in th 21 Not mployr-yar fixd ffcts cannot b includd, as this is th lvl of variation of th xplanatory variabl of intrst. 14

absnc of plan fixd ffcts γ 1 will rflct ths omittd factors. Howvr, som of this crosssctional variation may b dsirabl bcaus compting plans act as a constraint on th pricing of incumbnt providrs. Facd with an xcssiv pric incras, som mployrs may switch plans to obtain bttr pricing. Plan fixd ffcts liminat any variation in pric du to such switching. Thus, th baslin modl rvals whthr mployrs facing profit shocks nd up paying highr prmiums on avrag (rgardlss of switching bhavior), whil th modls with plan fixd ffcts rval whthr ths mployrs pay mor for th sam plans. Not th plan fixd ffcts also subsum 5 of th rmaining 7 scond-ordr intraction trms. 22 Th final two, markt-yar fixd ffcts and carrir-yar fixd ffcts, ar addrssd blow. Nxt, I add markt-yar masurs of conomic conditions (th unmploymnt rat) and costs (th pr-nroll avrag Mdicar xpnditur, known as th AAPCC) to captur changs in conomic conditions and halthcar trnds that may b corrlatd with both mployr profits and prmiums. Ths ar dnotd by X mt inclusion of ths covariats, markt-yar fixd ffcts (dnotd. If th cofficints of intrst ar snsitiv to th φ mt ) ar advisabl. Onc includd, γ 1 is idntifid by diffrncs in within-plan prmium growth for plans oprating in th sam markt. To clarify this sourc of idntification, considr as a hypothtical xampl th Chicago-basd halthplans offrd by Boing and Unitd Airlins in 2003. In th wak of th trrorist attacks in Sptmbr 2001, Unitd fild for bankruptcy whil Boing s fortuns soard. Controlling for th avrag prmium growth in Chicago, as wll as th avrag prmium growth for spcific plan typs nationwid, I xpct prmium incrass to b highr for Boing if γ 1 is positiv. 23 Of cours, a cost of including markt-yar intractions is that variations in avrag firm profits in a givn markt cannot hlp to idntify th cofficint of intrst. For xampl, many California-basd firms bnfitd from th tchnology boom in 1999-2000. Th xtnt to which insurrs wr abl to captur ths rnts will not b rflctd in th stimats obtaind from modls with markt-yar fixd ffcts. (On th othr hand, nithr would th ffct of (hypothtically) fastr-than-normal cost growth in California b mislabld as rnt xtraction. Of cours, th impact of th conomic controls on th profit cofficint will rval th liklihood 22 Th fiv intractions ar: mployr-carrir, mployr-plantyp, markt-carrir, markt-plantyp, and carrirplantyp. Plan fixd ffcts also subsum th mployr-markt fixd ffcts includd in all spcifications, so tchnically thy captur 6 of th 9 possibl scond-ordr intraction trms. 23 Not this final modl ffctivly includs all nin scond-ordr intraction trms. 15

of such a bias.) For th sak of compltnss, I also confirm th snsitivity of th rsults to th inclusion of carrir-yar intraction trms, although ths ar unlikly to gnrat bias in th cofficint of intrst. 24 Bcaus prmium rats for th sam plan (i.. mcj combination) ar likly to b srially corrlatd ovr tim, I prform a formal tst as dscribd by Jffry M. Wooldridg (2001). 25 I rjct th null hypothsis of no srial corrlation with a p-valu smallr than.001. Givn th unbalancd natur of th panl, I cannot implmnt a fully robust stimator (i.. FGLS that allows for any htroskdasticity and srial corrlation in th rror trms), howvr I can and do corrct for AR(1) corrlation in th rrors using an FGLS stimator dsignd for this circumstanc by Badi H. Baltagi and Ping X. Wu (1999). 26 Tabl 2 prsnts rsults for th 4 spcifications rprsntd by quation (1). Th stimats of γ 1 ar all positiv, similar in magnitud, and statistically significant. Th point stimat incrass upon inclusion of plan fixd ffcts, and is unaffctd by th markt-yar covariats. This suggsts local conomic conditions and/or changs in halthcar utilization ar unlikly to b driving th rsults. Controlling for diffrncs in prmium growth across markts (column 7) rducs th magnitud of ˆγ 1 a bit, but this diffrnc is not statistically significant. Though not rportd in th tabl, adding carrir-yar intractions has virtually no impact on th cofficint stimats. Th rsults imply an mployr with a 10-prcntag point incras in profits can xpct to pay approximatly 0.3 prcnt mor in halth insuranc prmiums, ctris paribus. TABLE 2 ABOUT HERE 24 Carrir-yar intractions will b significant prdictors of prmiums if carrir-spcific financial conditions impact prmium incrass. Howvr, xcluding ths intractions will only bias th cofficint of intrst if mployrs with high or low profit shocks ar disproportionatly rprsntd in th customr bas of insurrs xprincing systmatically good or bad yars. Particularly aftr markt-yar intraction trms ar includd in th spcification, such a scnario is difficult to nvision. 25 This tst consists of running th first-diffrncd vrsion of quations (1) or (2) and rgrssing th rsulting rsiduals on thir on-priod lag. A cofficint significantly diffrnt from -0.5 implis srial corrlation. 26 Th Baltagi-Wu stimator is implmntd by th stata command xtrgar. For modls without plan fixd ffcts, th analogous command is xtpcs. An altrnativ (though infficint) approach is to us OLS and clustr th standard rrors by plan. Th point stimats ar similar, but th standard rrors tnd to b largr (as xpctd). 16

Nxt, I considr th possibility of bias du to changs in unobsrvd plan charactristics, such as providr ntworks, prscription drug formularis, and copaymnts. An altrnativ xplanation for th positiv stimat of γ 1 is that firms with positiv profit shocks rspond by incrasing bnfits for workrs, and mor bnfits com with a highr pric tag. As a first tst of this hypothsis, I add plan dsign to ach spcification. Th rsults ar rportd in columns 2, 4, 6, and 8 of Tabl 2, alongsid th corrsponding baslin spcifications. Th cofficint on plan dsign is always positiv and highly significant, suggsting it dos captur th gnrosity of bnfits. Howvr, th stimats of γ 1 rmain significant, and actually incras a bit (countr to th hypothsizd dirction of any omittd variabls bias). To th xtnt that othr omittd, timvarying plan charactristics ar corrlatd with this composit masur, this tst provids som rassuranc that ths omittd factors ar not gnrating th positiv stimats of γ 1. As a scond tst of this altrnativ xplanation, I considr how th stimat of γ 1 varis by th markt structur of th local insuranc industry. If γ 1 rflcts rnt xtraction by insuranc carrirs, it should b largr whr comptition is lss firc. If instad it rflcts th prdilction of profitabl mployrs to provid mor gnrous bnfits, it should b insnsitiv to th markt structur of th insuranc industry: thr is no obvious rason why multisit firms with high profits would incras bnfits most in th sits srvd by a concntratd insuranc sctor. 27 I stimat modls basd on th following quation: (2) ln(prmium) mcjt = α + + γ 2 + ω jt 5 γ NC= 1 m 1, NC 1( NC) dmographics + ς [ +ρ mcj m mcjt * profit margin + γ ] [ + X 3 mt plan dsign β] [ +φ mt, t 2 mcjt ] + ε + mcjt 4 NC NC= 1 + ξ λ + ν 1( NC) m + ψ mt c + η j + δ t whr NC stands for numbr of carrirs. I us 5 rangs for numbr of carrirs: 1-4, 5-6, 7-8, 9-10, and 11+. (As indicatd in Figur 5, ths catgoris captur th distribution of numbr of carrirs fairly wll; unfortunatly thr is insufficint data to subdivid th 1-4 catgory furthr.) 1(NC) mt is an indicator variabl that taks a valu of 1 if th obsrvation is from a markt-yar with NC carrirs. Thus, γ 1,3 is stimatd from obsrvations in markt-yars with 7-8 carrirs. 27 Similarly, profitabl firms could rspond to profit shocks by hiring mor xprincd mploys who ar oldr and costlir to insur. 17

Although an imprfct proxy for markt comptitivnss, th numbr of carrirs is th most accurat masur of markt structur availabl to m givn th non-random natur of th sampl. (In th Onlin Appndix, I confirm th rsults ar robust to rplacing ths catgoris with quintils for HHI.) Equation (2) also includs th numbr of carrir indicators to control for any markt-wid rlationship btwn ntry and xit and prmiums. Tabl 3 illustrats that th magnitud of ˆγ 1, NC dclins as th numbr of carrirs incrass. T-tsts rjct th null hypothsis γ ˆ ˆ 1,1 = γ1, 5 in favor of γˆ ˆ 1,1 > γ1, 5 in all spcifications with p-valus of.07 or lss. Th rlationship btwn profits and prmiums in th most comptitiv markts is not significant in any of th spcifications. Th point stimats ar affctd littl by th addition of markt-yar covariats, indicating that diffrncs in local conomic and halthcar utilization trnds ar unlikly to b gnrating th obsrvd snsitivity of prmiums to profits in markts with fw carrirs. Th cofficint on markts with 5-6 carrirs dclins in th spcification with markt-yar fixd ffcts, but othrwis th rsults rmain similar vn in this stringnt spcification, as wll as in th unrportd spcification that adds carrir-yar fixd ffcts. 28 TABLE 3 ABOUT HERE Th stimats indicat that profitabl firms pay mor for thir halth insuranc, ctris paribus. This ffct is only significant in markts with 10 or fwr major carrirs, and is most pronouncd in markts with 6 or fwr carrirs. In such markts, a profit incras of 10 prcntag points (roughly th standard dviation of profits during th 2001 rcssion) is associatd with an incras in halth insuranc prmiums of 1.2 prcnt. 29 Th vidnc that supplirs njoy significant markt powr vn whn up to 10 comptitors ar prsnt is consistnt with rlatd rsarch in industrial organization. Although a 28 Th cofficint stimats for th numbr of carrir indicators ar availabl upon rqust. Ths ar idntifid by changs in th numbr of carrirs within a givn markt ovr tim du to ntry, xit, and masurmnt rror. Th rsults ar robust to th xclusion of th numbr of carrirs indicators. 29 I obtain this stimat using th avrag of th rlvant cofficints in th spcification with plan fixd ffcts and markt-yar covariats (column 3, Tabl 3): xp(((.145+.092)/2)*.1) =1.012. 18

much smallr numbr of firms is ndd to achiv prfct comptition in a homognous product markt (Timothy F. Brsnahan and Ptr C. Riss 1991), th numbr in a diffrntiatd product markt can b a good dal largr. David Dranov, Ann Gron and Michal J. Mazzo (2001) rport vidnc that th sixth HMO in an MSA arns supracomptitiv profits, on avrag. (Estimats for ntrants byond th sixth ar not rportd.) Onc thy catgoriz th HMOs by whthr thy hav national ntworks, thy find stpr dclins in profits with additional ntrants of th sam typ, although thy do not rport th maximal numbr of ach typ associatd with positiv profits. Givn th many dimnsions along which insuranc carrirs ar diffrntiatd, th rsult that 10 or mor ar ndd, on avrag, to inhibit customr-spcific rnt xtraction is in lin with thortical and mpirical prdictions. a. Altrnativ Explanations In this sction, I considr altrnativ xplanations for th ky findings. Th first altrnativ xplanation is that profitabl firms incras th gnrosity of thir plans mor in mor concntratd insuranc markts, and this phnomnon xplains th diffrntial prmium incras. To xamin this possibility, I r-stimat th modls abov using plan dsign as th dpndnt variabl. Although changs in plan dsign itslf will not impact th stimats I rport bcaus it is includd as a control in th ky spcifications, to th xtnt plan dsign is corrlatd with unobsrvabl gnrosity this analysis will xpos th fasibility of this altrnativ xplanation. Th rsults, rportd in th Onlin Appndix as Tabls OA1 and OA2, show that mployrs xprincing positiv profit shocks do not tnd to incras plan quality nationwid (rathr, thy dcras it), nor do thy incras quality rlativly mor in mor concntratd insuranc markts. A scond, rlatd concrn is that insurr markups for plan quality may b highr in mor concntratd markts. A highr markup for quality in concntratd markts could yild a similar pattrn of rsults vn if th incras in quality is th sam across all markts. Morovr, to th xtnt that concntratd insuranc markts coincid with concntratd halthcar providr markts, such a pattrn of markups could rflct th xrcis of markt powr by th lattr (or prhaps som combination of th two). To considr this altrnativ xplanation dirctly I r- 19

stimat th spcifications rprsntd by quation (2) with th addition of intractions btwn numbr of carrir catgoris and plan dsign. Th stimats ar prsntd in Tabl 4. Th cofficints and standard rrors on th intractions btwn markt structur and laggd profits ar virtually unchangd. In addition, thr is littl vidnc that th markup for plan quality is highr in mor concntratd markts. Th point stimats ar only largr for mor concntratd markts in on of th four spcifications (th modl without plan fixd ffcts), and vn in this spcification th diffrnc btwn th cofficint on plan dsign for th most and last concntratd markts is not statistically distinguishabl from zro. TABLE 4 ABOUT HERE Th prcding analysis raiss th qustion: ar thr othr factors corrlatd with insurr concntration that could b producing th obsrvd pattrn of findings? Tabl OA3 in th Onlin Appndix prsnts dscriptiv statistics for th markt-yars in ach catgory. Th tabl shows that th most concntratd markts hav smallr populations, lowr incom pr capita, and ar lss urban than th last concntratd markts. Howvr, it is important to rcogniz that th analysis of rnt xtraction dos not xamin th rlationship btwn markt structur and prmium lvls, which could crtainly b affctd by ths othr charactristics. Rathr, th study invstigats how individual insuranc contracts ar rvisd to rflct changs in individual customr charactristics. It is difficult to conciv of a mchanism whrby diffrncs in th undrlying attractivnss of a markt or in any othr markt-spcific charactristics - could gnrat th obsrvd bhavior. 30 For xampl, on unobsrvd markt charactristic is providr concntration. Evn if providr concntration is corrlatd with insurr concntration, th formr cannot pric-discriminat across spcific mployrs whn insurrs srv as intrmdiaris. Finally, th impact (on pric lvls) of any diffrncs across markt-yars in dmographics or providr concntration is controlld for in spcifications with markt-yar fixd ffcts. 30 On rfr offrd th following possibility: suppos firms with positiv profit shocks bcom mor costly to insur bcaus thir mploys utiliz mor mdical car. (This may occur, for xampl, if mploys of profitabl firms bcom lss concrnd about missing work to tnd to mdical issus.) Furthrmor, suppos th marginal cost of car is highr in markts srvd by a small numbr of insurrs. Although th data cannot rul out this altrnativ xplanation, it sms unlikly as it would rquir insurrs to corrctly prdict incrasd utilization by profitabl firms (as wll as gographic diffrncs in marginal costs, which insurrs may wll know). Not also that avrag Mdicar costs pr capita tnd to b lowr in concntratd markts. 20

b. Robustnss and Extnsions I prformd svral robustnss chcks and additional analyss to corroborat and xtnd th ky rsults. First, I usd th first-diffrncs (FD) stimator in plac of th FGLS stimator for modls that includ plan fixd ffcts. Although th FD stimator is infficint du to th srial corrlation in th rror trms, it should b unbiasd. 31 I rorganizd th data into firstdiffrncs (whr th unit of obsrvation is a plan) and stimatd th following spcification: (3) ln(prmium) mcj( t, t 1) = α + ϑ profit margin t 3 1 ϑ dmographics δ + ω jt + [ +φ mt mcj( t, t 1) ] + ε ( t 2, t 3) mcj(t,t-1) + ϑ plan dsign. 4 + mcj( t, t 1) + This spcification corrsponds to spcification (1) aftr plan dsign and plan fixd ffcts ar includd (i.., Tabl 2, columns 4 and 8). I also stimatd analogous modls with th numbr of carrir dummis*profit margin intractions. Th rsults, prsntd in Tabl 5, ar fairly similar to th FGLS rsults. Although th cofficint stimats ar smallr, th ky cofficints rmain statistically significant at p<.05. 32 TABLE 5 ABOUT HERE Anothr important robustnss chck concrns th implicit assumption that prmiums for ach plan-yar ar st indpndntly. Multisit firms ngotiating with multimarkt insurrs may agr to prmiums for many sits at onc. To th xtnt this occurs in my sampl, th stimats I obtain in Tabl 3 ar consrvativ bcaus pric changs for ths firms will not vary with th concntration of local insuranc markts. Unfortunatly, thr is no dirct indicator of multisit 31 Two additional advantag of th FGLS stimator ar: (1) it nabls comparisons of stimats with and without plan fixd ffcts; (2) it rtains mor data points givn th unbalancd natur of th panl. 32 I also usd th first-diffrncd data to s whthr th rnt xtraction paramtr diffrs for mployrs xprincing positiv vs. ngativ profit shocks. I addd th trm ϑ2 profit margin( t 2, t 3) 1 ( profit margin( t 2, t 3) > 0) to quation (3), whr 1 ( profit margin ( t 2, t 3) > 0 is an indicator for a positiv profit shock. Th rsults wr inconclusiv, i.. I am unabl to rjct th null of symmtric rnt xtraction paramtrs. 21

contracts in th data. 33 I thrfor pursu a consrvativ approach to idntifying jointlyngotiatd contracts. I idntify mployr-carrir-plantyp combinations that ar th sam across multipl markts, and assum any that shar th xact sam valu for plan dsign (a continuous masur) ar jointly-ngotiatd. Thn, I includ only on randomly-slctd obsrvation for this st of plans in th stimation sampl. 34 As xpctd, th rsults (rportd in th Onlin Appndix as Tabls OA4 and OA5) ar gnrally strongr, although th sampl siz falls by narly on-half and th standard rrors incras accordingly. Th Onlin Appndix also includs tabls of rsults from svral additional analyss. I valuat th impact of ach of th following changs in turn: (1) wighting ach obsrvation by th numbr of nrolls; (2) dropping data from 2004 and 2005, th yars in which th numbr of markts in th sampl dclins substantially du to th rstriction that 20+ mployrs b sampld in ach markt-yar; (3) xpanding th stimation sampl to includ all markt-yars (not just thos with 20+ mployrs); (4) rstricting th sampl to HMOs only, which account for mor than 90 prcnt of fully-insurd plans; (5) using altrnativ profit masurs; (6) using quintils of th HHI as a masur of markt concntration (rathr than th numbr of carrirs); (7) using diffrnt approachs to counting th numbr of carrirs. All ky pattrns rmain statistically significant, and ar oftn strongr, whn any of ths changs is implmntd. 35 Nxt, I mak us of th data on slf-insurd (SI) plans to prform a falsification xrcis, and to xamin whthr substitution toward SI affcts th main findings. 36 Bcaus rportd prmiums for SI plans includ xpctd fs chargd by th carrirs who administr ths plans, vidnc of rnt xtraction may b apparnt in th SI data. Howvr, th rlationship should b wakr than that obsrvd in th fully-insurd markt bcaus f structurs for 33 Rgrttably, th prmium variabl cannot b usd to infr which plans ar part of such a contract. I obsrv th avrag prmium pr plan-yar. Evn if Company X s Atna HMO chargs th sam prmium, by family siz, across all markts, th avrag prmium will tak on diffrnt valus across ths markts du to diffrncs in avrag family siz at ach sit. 34 For xampl, suppos Company X offrs a BCBS PPO in 30 markts. If plan dsign a continuous masur that capturs th gnrosity of copays and covrag is th sam across ths markts, I includ only 1 of ths plans in th stimation sampl. If it is th sam across 10 of th markts, thn I includ 1 of ths 10 plans and all of th rmaining 20 plans in th sampl. 35 I also confirm th rsults ar wakr whn using on-yar laggd profits, which ar corrlatd with two-yar laggd profits but lss likly to b obsrvd at th tim prmiums ar ngotiatd. Whn both ar includd in th sam modl only th two-yar laggd profits (and intractions with markt indicators) ar statistically significant. 36 I thank Mark Pauly for suggsting this falsification xrcis. 22

administrativ srvics ar far mor transparnt than pricing for fully-insurd plans, and thr ar mor comptitors in th slf-insurd markt. 37 Using th sampl of slf-insurd plans in th sam markt-yars includd in th analysis of fully-insurd plans, I stimat modls (1) and (2) from sction 4.1 (i.., th lvls spcifications). Th dpndnt variabl is th log of th mployr s stimat of outlays for ach plan-yar, ln( prmium ). Th indicators for numbr of carrirs still rfr to FI carrirs. Using th FI markt structur is th liklist way to rval whthr th main rsults ar spurious. In addition, th slf-insurd markt is lss concntratd, prcluding idntification of γ 1, NC in markts with small numbrs of SI carrirs. Th rsults show a ngativ rlationship btwn laggd profits and stimatd outlays. Dcomposing th rlationship by markt structur rvals no stady pattrn. To th xtnt th projctd costs of SI plans ar an appropriat countrfactual for FI plans, ths findings suggst th main rsults ar not spurious. Givn thr is no vidnc of rnt xtraction in th SI markt, w might xpct to s mor substitution toward SI (and away from FI) by profitabl firms. To th xtnt this occurs, my stimats of rnt xtraction in th FI markt ar consrvativ, and th pattrn of cofficints on th intractions with markt structur undrstatd. 38 To xplor this possibility, I us data on all plans offrd by mployrs in th LEHID-FI-Compustat sampl, rgardlss of whthr an FI plan is offrd in a particular yar. I aggrgat th data to th mployr-markt-yar lvl and stimat modls using both prcnt slf-insurd and ln(avrag prmium ) as dpndnt variabls, whr prmium rflcts both full-insuranc prmiums and xpctd outlays for slfinsurd nrolls. A dtaild discussion of th data, togthr with dscriptiv statistics and tabls of rsults ar givn in Appndix A. I find no vidnc that mployrs ar mor likly to rly on slf-insurd plans in th wak of profit shocks. In concntratd insuranc markts, avrag prmiums ris with profit shocks, vn whn incorporating possibl substitution toward slfinsurd plans. 37 Mor transparnt pricing should limit th ability of insurrs to pric-discriminat. Although contract structur varis, it typically spcifis fs pr nroll and/or pr claim.) 38 Profitabl mployrs in concntratd insuranc markts fac th largst prmium incrass and thrfor th strongst incntiv to substitut toward SI. This slction bias should thrfor hav th strongst impact on th rnt xtraction stimat in ths markts. 23

Thr ar svral possibl rasons profitabl mployrs ar not mor likly to switch toward slf-insuranc in spit of th pric incrass thy fac rlativ to lss profitabl mployrs. Th timfram for making a dcision to switch to slf-insuranc may b lngthy. Th right vndors must b idntifid and contracts writtn. Slf-insurd firms must maintain adquat financial rsrvs to pay claims as thy ar ralizd, and thy must bar th risk of unprdictabl mdical xpnss. Prhaps most important: profitabl firms may b rluctant to mak any major changs to thir plan portfolios for rasons I dscrib in th following sction. III. Intrprting th Rsults: Combining Practitionr Intuition and Bargaining Thory A. Practitionr Intuition Th rsults thus far imply that firms ar willing to pay mor for halth insuranc whn tims ar good, and in concntratd insuranc markts carrirs succssfully xtract som (or all) of this incrasd willingnss-to-pay. This bgs th qustion of why firms fail to minimiz costs rgardlss of profit lvl. Although cost minimization is a ky assumption of noclassical conomics, th businss prss is rplt with ancdotal vidnc of profligat spnding during booms and infficint cost-cutting during busts. Ths infficincis hav also bn corroboratd in rsarch by Svrin Bornstin and Josph Farrll (2007). 39 Bornstin and Farrll find stock markt valuations of gold mining firms ar concav in th pric of gold. Givn th prfctly comptitiv output markt, this rsult is consistnt with a dcras in cost fficincy whn profits ar high. 39 Writing in BusinssWk in March 2008, formr Gnral Motors had Jack Wlch and co-columnist Suzy Wlch advis firms to trim th fat to cop with th conomic slump. Yars of sustaind growth practically guarant som padding, thy not, citing as xampls xcssiv ovrhad, non-ssntial consulting projcts, and th quality of company gathrings. (3/3/2008, p. 88). 24

A potntial sourc of cost infficincis in fat firms is rnt-sharing with workrs, or to b mor prcis, rnt-sharing that is not part of an optimal labor contract. 40 Bornstin and Farrll do not find vidnc of rnt-sharing in th mining sctor, but it has bn documntd in a numbr of industris and countris (.g., William T. Dickns and Lawrnc F. Katz 1987, Katz and Lawrnc H. Summrs 1989, and David G. Blanchflowr, Andrw J. Oswald, and Ptr Sanfry 1996). Although mpirical vidnc of rnt-sharing focuss on wags, th rlationship with fring bnfits such as halth insuranc may b similar, as thr is som vidnc that bnfits and wags ar intrchangabl (.g., Jonathan Grubr 1994 and Mark V. Pauly 1998). Whn prsntd with my findings, industry xprts suggstd prcisly such an xplanation. 41 Th argumnt proffrd by th xprts is linkd to th high switching costs mploys must incur whn changing halthplans. Ths costs includ: larning about changs in bnfit covrag and dsign and potntially adjusting halthcar consumption as a rsult; idntifying providrs that blong to th nw plan s ntwork; if formr providrs ar not part of th ntwork, schduling and undrgoing nw patint visits (which may lad to a disruption in car and associatd mdical consquncs), transfrring mdical rcords and prscriptions, and, for plans with gatkprs (such as HMOs or POS plans) navigating through a gatkpr in ordr to s spcialists; figuring out th claims rimbursmnt systm. For mployrs to obtain th bst pricing on plans, thy must b willing to chang carrirs. Howvr, a plan switch is a tough sll in good tims, to paraphras an xcutiv from my data sourc. Workrs ar willing to tolrat such actions (along with, say, th holiday party in th offic confrnc room), but only whn viwd as ncssary. Thus profitabl firms may shar rnts with workrs by rtaining xisting plans. Whil this hypothsis may xplain why insurrs can xtract highr rnts from mor profitabl firms on avrag, it dos not xplain why this xtraction is mor succssful in markts whr fwr insurrs compt. To obtain som intuition for this rsult, I formulat a simpl bargaining modl that capturs th ky lmnts of this stting. 40 Rnt-sharing may of cours b optimal, particularly if workrs and firms ar risk-avrs (Blanchflowr 1996) or if spcific invstmnts ar rquird for both partis. 41 This xplanation was proposd by an xcutiv from my data sourc, and subsquntly corroboratd in intrviws with a larg insuranc brokr/formr insuranc xcutiv (phon intrviws, 10/9/2007 and 10/10/2007), and a CFO at a lading halth insurr (phon intrviw, 10/25/2007). All sourcs rqustd anonymity. 25

B. A Bargaining Modl Assum ach mployr purchass insuranc from only on insurr i, both partis hav full information, and th transaction pric is dtrmind through Nash bargaining. (A mor ralistic modl would accommodat th possibility of multipl contracts, as wll as asymmtric information on both sids, but this is byond th scop of this papr.) Dnot th mployr s valu of purchasing insuranc from i (that is, th mployr s willingnss-to-pay) by v i. function of mploy dmographics and risk profils charactristics X, mployr profits π, insurr v is a i X i, plan dsign q, and an additiv i.i.d. rror trm u i that rprsnts idiosyncratic variation in th mployr s valuation of its halthplan in a givn yar (.g. du to th prfrncs of a nw bnfits managr, or bad publicity surrounding a particular insurr). (5.21) v = [ g( X, π, X, q) + u ] i i i Th mployr s valu of th nxt-bst option ( v i ) is similarly constructd, howvr I rplac X i with N, th numbr of insurrs. N is arguably a rasonabl proxy for th attractivnss of th nxt-bst option, as mor choics should incras th liklihood of a good match. Th cost of insuring is assumd constant across insurrs (this assumption is not ncssary for th rsults that follow and is imposd in th intrst of parsimony). Th surplus from trad btwn and i, dnotd S i, can b writtn (5.22) S = [ v v ] = [ g( X π, X, q) + u ] [ h( X, π, N, q) u ] i i,. i i i + i Undr th assumption of prfct information, trad will tak plac whn surplus is positiv. Th division of surplus is dtrmind by 0 α(n) 1; this paramtr rflcts th insurr s bargaining powr. Dnoting th amount of surplus going to th insurr by P (for pric or prmium), w hav 26

(5.23) P = α( N ) S ( X, π, X, q, N, u, u ) i *. i i i i In words, prmium is dtrmind by rlativ bargaining powr, mploy dmographics and risk profils, mployr profits, th mployr s choic of plan quality, and th xtnt of comptition in th marktplac. 42 Most of th rgrssion spcifications focus on changs in prmiums for th sam i pair. Thus, idntification in ths modls drivs from changs in dmographics, profits, and plan quality, all intractd with bargaining powr (which itslf may vary if thr is ntry and xit). 43 I us this modl to driv th implications of a chang to mployr profits. Thr ar two radily-availabl outcoms to considr: pric and th probability of trad. It is asy to s that prmiums for obsrvd contracts only incras in profits, i.. P / π > 0 (th mpirical rsult i of sction 3), if g / π > h / π. In light of th rsults prsntd thus far, this condition implis profits incras th mployr s rlativ valu of rmaining with an incumbnt. This could b vidnc of infficint cost-minimization practics (i.. inrtia) associatd with profits (a la Bornstin and Farrll s "fat firms"), or of a profit-inducd shock to switching costs (as suggstd by th industry xprts). In ithr cas, ths rlativ changs in willingnss-to-pay will not rsult in highr prmiums unlss insurrs hav positiv bargaining powr, i.. α > 0. Nxt, considr th ffct of a profit shock on th probability that an mployr and an insurr who tradd in a prior priod (i.. th incumbnt insurr-mployr combination, for which S i was positiv) part ways. Dnoting th cumulativ probability distribution of ( u u ) (assumd to b twic diffrntiabl), w hav i by F i (5.24) 42 It would b mor straightforward to includ trms for insurr charactristics in th modl, but using th numbr of comptitors provs far mor convnint whn driving th rsults. 43 Although th mpirical modls do not xplicitly includ intractions btwn dmographics and markt structur, th rsults ar robust to ths trms. 27

Prob ( ) = F( h( X, π, q, N ) g( X, π q, X )) ( S ) = Prob u u < ( h( X, π, q, N ) g( X, π, q, X )) i < 0 i i i, i and (5.25) F ( h( X π, q, N ) g( X, π q, X ))/ π = f h( X, π, q, N ) g( X, π, q, X ) ( )*( h / π g / π ).,, i i Givn that a probability dnsity function is wakly positiv vrywhr, and th mpirical rsults indicat th scond trm is ngativ, w hav th first additional mpirical prdiction: th probability that an mployr and an insurr part ways should dclin in profits. Nxt, considr how ths prdictions vary by th numbr of insurrs in th markt, bginning with pric : 2 2 (5.26) P / π N = α / N * ( g / π h / π ) α * ( h / π N ) 2 From th mpirical rsults, w know / π N < 0 g P and ( / π / π ) > 0 h. Thus, ithr insurr bargaining powr dclins in th numbr of insurrs ( α / N < 0 ), th ffct of profit shocks on th valu of th mployr s outsid option incrass in th numbr of insurrs 2 ( h / π N > 0 ), or both. 44 2 If h / π N can b shown to b ngativ, thn w can dfinitivly conclud that insurr bargaining powr dclins in th numbr of insurrs. Unfortunatly, I do not dirctly obsrv ach mployr s bst outsid option. Howvr, I obtain som additional insight by xamining how th numbr of insurrs affcts th prdictions vis-à-vis match dissolution: 44 Tchnically, of cours, othr combinations ar possibl, but not intuitiv. 28

(5.27) 2 F ( h( X, π, q, N ) g( X, X )) π N i = f + f ( h( X, π, q, N ) g( X, π, q, X )) 2 h * π N h h g ( h( X, π, q, N ) g( X, π, q, X ))* * i i N π π This cross-partial can b signd mpirically by sing how th rat of match dissolution with rspct to profits varis with N. This is th scond mpirical tst I prform in th nxt sction. Although th scond of th two trms on th right-hand-sid is of indtrminat sign bcaus f () 2 cannot b signd, an mpirical finding that ( )/ π N < 0 F is consistnt with 2 h / π N < 0. That is, if profitabl firms ar lss likly to switch carrirs in mor comptitiv insuranc markts, this suggsts that th ffct of profits on th outsid option dcrass in N. Rturning to (5.26), this strngthns th cas for α / N < 0. To summariz, th modl provids th following insights: (1) th rnt-xtraction rsult of sction 3 appars to b du to a combination of insurr bargaining powr (i.. α > 0) and mployr inrtia or switching costs; (2) mployrs with profit shocks should b lss likly to switch carrirs; (3) th fact that rnt xtraction is wakr in markts with mor insurrs is consistnt with two xplanations: lowr insurr bargaining powr in such markts, and/or lss of an incras in profit-inducd inrtia or switching costs in ths markts; (4) if mployrs with profit shocks ar lss likly to switch in markts with larg numbrs of carrirs, th scond xplanation is lss likly to b driving th rsults. V. Th Rlationship btwn Plan Switching and Employr Profits This sction tsts th prdictions rgarding th propnsity of firms to switch halthplans. I bgin by invstigating whthr switching is lss likly whn firms ar profitabl, controlling for othr factors that may b associatd with th propnsity to switch. To analyz switching bhavior, I crat a datast of mployr-markt-yar obsrvations and stimat linar probability modls of th following form: 29

(4) switch α + ϕprofit margin + τ [ +φ ] [ +ξ ] [ +ς ] + ε m ( t, t 1) = t 2 t mt m mt. I dfin two vrsions of switch: carrirswitch and planswitch. carrirswitch taks a valu of 1 if thr is an addition or dltion of insuranc carrirs by an mployr in a givn markt btwn t- 1 and t. Planswitch taks a valu of 1 if thr is an addition or dltion of carrir-plantyps. Planswitch will ovrstat switching,.g., if a firm switchs from a UnitdHalthcar HMO to a UnitdHalthcar POS, it will b codd as having mad a switch whn no matrial switch has occurrd. carrirswitch will undrstat switching,.g., if a firm offrs an Atna HMO, Atna PPO, and UnitdHalthcar PPO, and liminats th Atna PPO, it will not b codd as having mad a switch. For this rason, I prsnt stimats using both masurs. 45 Th baslin modl capturs th association btwn laggd profits and th propnsity to switch, controlling for national trnds. Th nxt spcification adds markt-yar intractions to control for gnral uphaval in a markt-yar du, for xampl, to mrgrs or xits of insuranc carrirs. Absnt ths intractions, th stimat of φ will rflct such activity if it is corrlatd with markt-lvl changs in laggd profits of mployrs. Employr fixd ffcts ar addd nxt; ths control for mployr-spcific tndncis to switch, which may also b corrlatd with profit lvls and hnc bias th stimat of φ. For xampl, mployrs in sctors with high labor turnovr may switch halthplans mor oftn bcaus thir mploys ar lss likly to hav a continuous rlationship with a halthplan and/or its associatd providrs. If such mployrs also tnd to rport lowr profits, th stimat of φ could b biasd downward in th absnc of mployr fixd ffcts. Not also that aftr mployr fixd ffcts ar includd, φ is idntifid by within-mployr changs in profits. Last, I add mployr-markt fixd ffcts, which allow for diffrnt baslin switching lvls across mployr-markts. For xampl, mploys of a larg rtail chain may diffr across locations, with hadquartrs mploys xpcting stady bnfits and rtail clrks in all othr markts willing to tolrat switchs mor radily. 45 To rduc masurmnt rror, th switch variabls ar dfind only whn data from two adjacnt yars is availabl. 30

I stimat th switching spcifications on th ntir sampl of mployr-markt-yar obsrvations with Compustat data, and on th subst of obsrvations with at last on fullyinsurd plan and locatd in markts with 20+ mployrs offring a fully-insurd choic. Thr is no thortical rason to rstrict th switching analysis in this way; I prsnt rsults using this subsampl to maintain consistncy with th rnt xtraction analysis. Th dscriptiv statistics for th switching variabls in both sampls ar givn sparatly by yar in Tabl 6; 1998 is omittd as th switching variabls can only b dfind for mployr-markts with data in th prcding yar. Just ovr on-third of th obsrvations in th total sampl hav a carrir switch, and 45 prcnt hav a plan switch. Th figurs ar vn highr in th fully-insurd sampl, with 47 prcnt of obsrvations switching carrirs and 56 prcnt switching plans. In both sampls, thr is a markd dclin in switching ovr tim. This rflcts, at last in part, th dclining numbr of options availabl. TABLES 6 AND 7 ABOUT HERE Th rsults of th switching analysis (Tabl 7) strongly support th hypothsis that mor profitabl firms ar lss likly to switch carrirs or plans. Th point stimats ar slightly largr for carrirswitch, and givn th lowr man lvls of carrirswitch this translats into largr proportional ffcts. For xampl, a 10-prcntag-point incras in profit margins in yar t is associatd with a rduction of roughly 4 prcntag points in th propnsity to switch carrirs btwn t+1 and t+2. Givn th man lvls of carrirswitch, this corrsponds to a dclin of mor than 10 prcnt. Th planswitch modls yild somwhat smallr stimats, but both rsults ar quit robust to altrnativ spcifications as wll as th diffrnt data sampls. Th advantag of th linar probability modls is th ability to control for a varity of fixd ffcts. Howvr, a binary outcom masur dos not prmit a distinction among typs of switching. Plan dltion should b much mor rsponsiv to profits than plan addition, which should not gnrally impos a cost on mploys (apart from thos rsponsibl for bnfits administration). To rfin th analysis, I thrfor stimat multinomial logit modls using two multivalud outcom masurs, carrirchang and planchang, which corrspond dirctly to carrirswitch and planswitch. Th outcoms ar no chang (th bas outcom), add only, drop 31

only, and add and drop. To th xtnt profitabl firms avoid carrir and/or plan changs in gnral all thr outcoms will b lss likly for such firms. Howvr, if th mchanism dscribd abov is corrct, changs that includ dltions should b th most snsitiv to profits. In ths modls, I includ only laggd profits and yar fixd ffcts as xplanatory variabls. Estimating cofficints for additional fixd ffcts is nithr computationally fasibl nor concptually appropriat givn th data. An mployr fixd ffct, for xampl, would control for th propnsity for vry mployr to slct vry outcom, laving only withinmployr, within-outcom variation to idntify th paramtrs for ach choic. Givn th switching rsults prsntd in Tabl 7 ar gnrally insnsitiv to th inclusion of various fixd ffcts, th pattrn of cofficints and prdictd outcoms for a parsimonious multinomial modl should yild accurat qualitativ conclusions. TABLE 8 ABOUT HERE Tabl 8 rports th rsults in th form of risk ratios for ach outcom rlativ to th bas outcom of no chang, using carrirchang in th top panl and planchang in th bottom panl. Both modls ar stimatd on th combind SI and FI sampl (rsults ar similar with th FI sampl, and availabl upon rqust.) All of th ratios ar significantly lss than 1, indicating that mor profitabl firms ar lss likly to mak any changs to thir carrirs or plans. Howvr, th rlativ risk ratio for adding is four to fiv tims as grat as that for dlting or adding and dlting, which ar fairly clos in siz; this diffrnc is also statistically significant. To put th rsults into th contxt of outcom probabilitis, at th bottom of ach panl I prsnt th ralizd probabilitis togthr with th man of prdictd probabilitis assuming a profit shock of.10 for ach mployr. Using th rsults from th carrirchang modl, th probability of adding a plan dclins from.090 to.085 (6 prcnt), th probability of dlting a plan dclins from.105 to.083 (21 prcnt), and th probability of adding and dlting a plan dclins from.160 to.133 (17 prcnt). Ths rsults suggst mployrs ar spcially rluctant to drop halthplans whn profitabl, a finding that supports th hypothsis that profits act to rais mployrs switching costs. 32

Nxt, I turn to th qustion of how th propnsity of profitabl firms to switch halthplans varis by th markt structur of th local insuranc industry. Conditional on th sam positiv profit shock, if firms in markts with a gratr numbr of insurrs ar mor likly to switch, th shock to switching costs may b lowr in ths markts. Undr this scnario, th fact that insurrs xtract lss of th profit shock in such markts may b attributabl to a smallr ffct of th profit shock on switching costs in ths markts. Th rsults in Tabl 9 suggst th xact opposit: firms in mor comptitiv markts ar lss likly to switch carrirs in th wak of a profit shock. 46 (Rsults ar prsntd for linar probability modls using carrirswitch as th dpndnt variabl and stimatd using th ntir sampl; rsults for othr sampls, dpndnt variabls, and modls ar similar.) As dmonstratd by th modl, this rsult suggsts that highr bargaining powr of insurrs is th liklir sourc of gratr rnt xtraction in markts with small numbrs of carrirs. Th rsult is also consistnt with th rnt-xtraction finding: profitabl firms fac th gratst prmium incrass in concntratd insuranc markts, and ar liklist (ctris paribus) to shop around in ths markts. TABLE 9 ABOUT HERE Th Onlin Appndix prsnts th rsults of an additional analysis xamining th bnfits to mployrs of switching. If switching costs ar th main rason profitabl mployrs ar willing to pay mor for halth insuranc, thn among th st of mployrs who do switch profit shocks should not b associatd with highr prmiums, ctris paribus. Th analysis is consistnt with this hypothsis: nw plans ar chapr than old plans, and among this st of switchrs, thr is a ngativ rlationship btwn profit shocks and prmium growth. 47 VI. Discussion and Conclusions Th U.S. halthcar systm rlis havily on privat insuranc companis to manag halthcar consumption and paymnts to providrs. Privat insurrs shar of halth xpnditurs in th 46 In all spcifications prsntd Tabl 8, two-sidd t-tsts asily rjct quality of th cofficints on laggd profits*(1-4 carrirs) and laggd profits*(>10 carrirs). 47 It is important to not that th switching dcision cannot b assumd xognous to th nw prmiums. That is, mployrs who switch probably do so in ordr to gt attractiv dals. Th rsults of this supplmntal analysis suggst profitabl mployrs may insist on particularly attractiv dals in ordr to switch. 33

U.S. stood at 35 prcnt in 2000, mor than twic that of th nxt-highst shar (15 prcnt in Th Nthrlands). 48 In 2007, xpnditurs by privat insurrs wr stimatd at $676 billion, up from $295 billion in 1993. 49 Although advocats of th privat insuranc systm usually appal to th virtus of comptition, to dat thr is littl mpirical vidnc to support th assumption of robust comptition among insuranc carrirs. 50 Prior studis ar limitd by poor data quality, inaccurat masurs of comptition (typically limitd to a broad masur of HMO activity), a lack of xognous variation in ths masurs, and inappropriat markt dfinitions. With th bnfit of high-quality micro panl data on a larg sampl of fully-insurd group halthplans, I find insurrs hav sufficint markt powr to ngotiat highr prmiums disproportionatly for firms xprincing positiv profit shocks. This rsult stands in stark contrast to that prdictd in th comptitiv stting, whr privat insurrs vying for ach contract bid down th prmium until it has no rlation to th mployr s willingnss to pay. Indd, I find this d facto pric discrimination is most pronouncd in markts with a small numbr of insuranc carrirs. Additional analyss rval mployrs ar lss willing to switch insurrs aftr thy xprinc positiv profit shocks, a phnomnon that affords incumbnt insurrs th opportunity to ngotiat largr pric incrass whr comptition is scarc. Collctivly, th rsults challng th assumption that U.S. halth insuranc markts ar highly comptitiv. Th wlfar implications of th spcific bhavior I documnt ar likly to b ngativ. In a homognous product markt, if quantity transactd dos not incras and consumr and 48 OECD Halth Data, 2003, 2 nd dition. 49 Sourc: Cntrs for Mdicar and Mdicaid Srvics, Offic of th Actuary, National Halth Statistics Group. http://www.cms.hhs.gov/nationalhalthexpnddata/downloads/proj2007.pdf. Ths figurs do not includ stimats of insurr profits and costs, i.., thy do not rprsnt total prmiums collctd. Data on total prmiums is not radily availabl. 50 As insurr consolidation continus apac, concrns ar mounting. For xampl, in 2006 th Kaisr Family Foundation s Annual Survy of Employr Halth Bnfits askd mployrs to rat th rol of highr insuranc company profits in contributing to halth insuranc prmiums; this is th first tim insuranc company profits hav bn includd in th list of choics. 45 prcnt of firms rportd th contribution to b a lot, scond only to highr spnding for prscription drugs (66 prcnt). (Kaisr Family Foundation and Halth Rsarch and Educational Trust Employr Halth Bnfits 2006 Annual Survy, Exhibit 12.3) 34

producr surplus ar qually valud, pric discrimination rducs wlfar. In th stting I considr, th quantity of insuranc consumd is unlikly to hav changd much. Larg firms almost always offr insuranc, and takup by mploys in ths firms is xtrmly insnsitiv to changs in th prmiums thy ar chargd (Grubr and Ebonya Washington 2005). Of cours, this stting dviats from th homognous stting in many ways and thortically surplus gains from discrimination rmain possibl (.g. mploys in unprofitabl firms may bnfit mor from th rduction in thir prmiums than mploys in profitabl firms los from th incrass thy fac). Of gratr intrst ar th broad wlfar implications of markt powr in th halth insuranc industry, of which pric discrimination is but on manifstation. Although th analysis I prform dos not lnd itslf to th quantification of markt powr, th point stimats suggst it is nontrivial. In markts with 6 or fwr carrirs, a 10-prcntag-point incras in th aftr-tax rturn on assts (approximatly th standard dviation of this masur during th 2001 rcssion) is followd by a 1.2-prcnt incras in halth insuranc prmiums. Givn oprating margins for insurrs ar gnrally lss than 5 prcnt, this figur is rathr imprssiv. 51 Importantly, in my sampl th shar of covrd mploys in markts with 6 or fwr carrirs incrasd dramatically ovr tim, from 7 prcnt in 1998 to 23 prcnt in 2005. Concntration has only incrasd sinc. Thus, th vidnc indicats halth insurrs ar xrcising markt powr in an incrasing numbr of gographic markts. Quantifying th dgr of markt powr and assssing its impacts on halthcar outcoms and costs is an important agnda for futur rsarch. Th most immdiat implications of this analysis ar twofold. First, fdral and stat govrnmnts may want to carfully assss th dgr of comptition in th rlvant insuranc markts bfor xpanding th rol of th privat sctor in halth-insuranc provision. Scond, proposd consolidations in this industry may warrant gratr scrutiny by antitrust nforcmnt agncis than has takn plac to dat. In particular, th bargaining strngth of insurrs vis-à-vis 51 Citing rsarch by Sanford Brnstin, an invstmnt rsarch firm, Th Economist rportd that 2003 oprating margins wr 5.1 prcnt, possibly an all-tim high as of th tim of rporting (6/12/2004, p. 71). Insurrs driv a sizabl shar of total profits (which xcd oprating margins) via th float: thy arn intrst on prmium dollars bfor thy ar paid to rimburs claims. 35

mployrs appars to b spcially strong whr 6-8 or fwr major carrirs ar prsnt. Th rsults also suggst analyss of mployr switching costs ar critical inputs for assssmnts of th comptitiv ffcts of combinations in this sctor. Rmdis that rduc switching costs, such as prohibitions on multi-yar, xclusiv contracts btwn insurrs and halthcar providrs, may lssn th comptitiv impact of consolidations in concntratd markts. Finally, rsarch on th xtnt to which uncomptitiv markts ar contributing to highr halthcar costs and potntially mor important to slowr innovation in halthcar managmnt and dlivry of car would hlp to inform th public dbat ovr halthcar rform. 36

Rfrncs Armstrong, Mark (2006), Rcnt Dvlopmnts in th Economics of Pric Discrimination, Advancs in Economics and Economtrics: Thory and Applications, Ninth World Congrss, ds. Blundll, Nwy and Prsson, Cambridg Univrsity Prss. Baltagi, Badi H. and Ping X. Wu (1999), Unqually Spacd Panl Data Rgrssions with AR(1) Disturbancs, Economtric Thory 15: 814-823. Blanchflowr, David G., Andrw J. Oswald, and Ptr Sanfry (1996), Wags, Profits, and Rnt-Sharing, Quartrly Journal of Economics, Vol. 111(1): 227-251. Bornstin, Svrin and Josph Farrll (2007), Do Invstors Forcast Fat Firms? Evidnc from th Gold Mining Industry, RAND Journal of Economics, 38(3): 626-647. Brsnahan, Timothy F. and Ptr C. Riss. (1991), Entry and Comptition in Concntratd Markts, Journal of Political Economy, 99(5): 977-1009. Coopr, Philip and Kosali I. Simon (2007), Trnds and Dtrminants of Slf Insuring Employr Halth Bnfits, 1997-2004, Cornll Univrsity mimo. Dranov, David, Ann Gron, and Michal J. Mazzo, "Diffrntiation and Comptition in HMO Markts," Journal of Industrial Economics, LI(4): 433-454. Dickns, William T. and Lawrnc F. Katz (1987), Intr-Industry Wag Diffrncs and Thoris of Wag Dtrmination, in K. Lang and J. Lonard, ds., Unmploymnt and th Structur of Labor Markts (Blackwll), 48-89. Duggan, Mark G. (2004), Dos Contracting Out Incras th Efficincy of Govrnmnt Programs? Evidnc from Mdicaid HMOs, Journal of Public Economics, Dcmbr 2004: 2549-2572. Duggan, Mark G. and Fiona Scott Morton (2008), Th Effct of Mdicar Part D on Pharmacutical Prics and Utilization, NBER Working Papr 13917. Enthovn, Alain C. (1978), Consumr-Choic Halth plan (scond of two parts). A nationalhalth-insuranc proposal basd on rgulatd comptition in th privat sctor, Nw England Journal of Mdicin: 298(13): 709-20. Fdral Trad Commission and Dpartmnt of Justic (2004), Improving Halth Car: A Dos of Comptition: A Rport by th Fdral Trad Commission and th Dpartmnt of Justic. Gaynor, Martin S. and Dborah Haas-Wilson (1999), Chang, Consolidation, and Comptition in Halth Car Markts, Th Journal of Economic Prspctivs: 13(1): 141-64. 37

Ginsburg, Paul B., Bardly C. Strunk, Michll I. Bankr, and John P. Cookson, Tracking Halth Car Costs: Continud Stability But at High Rats in 2005, Halth Affairs wb xclusiv, 25, no. 6 (2006): w486-w495 Grubr, Jonathan (1994), Th Incidnc of Mandatd Matrnity Bnfits, Amrican Economic Rviw, 84(3): 622-641. Grubr, Jonathan and Ebonya Washington (2005), Subsidis to Employ Halth Insuranc Prmiums and th Halth Insuranc Markt, Journal of Halth Economics, 24(2): 253-276 Ho, Kathrin (2009), Insurr-Providr Ntworks in th Mdical Car Markt, Amrican Economics Rviw, forthcoming. Hyman, David A. and William E. Kovacic (2004), Monopoly, Monopsony, and Markt Dfinition: An Antitrust Prspctiv On Markt Concntration Among Halth Insurrs, Halth Affairs, 23(6): 25-28. Katz, Lawrnc F. and Lawrnc H. Summrs. 1989. Industry rnts and industrial policy. Brookings paprs on conomic activity: Microconomics, 209 75. Marquis, M. Susan and Stphn H. Long (2000), Who Hlps Employrs Dsign Thir Halth Insuranc Bnfits? Halth Affairs, 19(1): 133-138. Pauly, Mark (1998), Halth Bnfits at Work: An Economic and Political Analysis of Employmnt-basd Halth Insuranc. Ann Arbor: Univrsity of Michigan Prss, 1997. Robinson, Jami C. (2004), Consolidation and Th Transformation Of Comptition In Halth Insuranc, Halth Affairs, 23(6): 11-24. Robinson, Jami C. (2006), Th Commrcia1 Halth Insuranc Industry in an Era of Eroding Employr Covrag, Halth Affairs, 25(6): 1475-1486. Scanlon, Dnnis P., Michal E. Chrnw and Woolton L (2006), Comptition in Halth Insuranc Markts: Limitations of Currnt Masurs for Policy Analysis, Mdical Car Rsarch and Rviw, 63(6): 37S-55S. Spulbr, Danil F. (1979), Noncooprativ Equilibrium with Pric Discriminating Firms, Economic Lttrs, 4:221-227. Stol, Lars (2005), Pric Discrimination in Comptitiv Environmnts, forthcoming in Armstrong, M. and Portr R.H. (ds), Handbook of Industrial Organization vol.3 (North-Holland, Amstrdam). Wnnbrg, John E., Elliot S. Fishr, and Jonathan S. Skinnr (2002), Gography and th Dbat Ovr Mdicar Rform, Halth Affairs 21(2) wb xclusiv: W96-W114. 38

Wholy, Douglas R., Rogr D. Fldman, and Jon B. Christianson (1995), Th Effct of Markt Structur on HMO Prmiums, Journal of Halth Economics 14: 81-105. Wooldridg, Jffry M. (2001), Economtric Analysis of Cross Sction and Panl Data. Cambridg: MIT Prss. 2001. 39

Figur 1. Nonldrly Population with Privat Insuranc Covrag, 1998-2005 Sourc: Enploy Bnfit Rsarch Institut stimats using th Currnt Population Survy, March 1998-2006 Supplmnts. 40

Figur 2. Growth in Annual Halth Insuranc Prmiums, 1999-2005 Nots: KFF/HRET growth basd on avrag prmiums for a family of four, as rportd by survy participants. FI dnots fully-insurd plans, whil SI dnots slf-insurd plans. Prmiums for SI plans rflct mployrs stimats of th cost of covrag. LEHID figurs ar basd on avrag prmiums pr prson-quivalnt, i.. prmium/dmofactor. Each obsrvation is wightd to rflct th numbr of covrd mploys in th undrlying plan. 41

Figur 3. Prcnt of Workrs Covrd in Fully-Insurd Halth Plans, 1998-2005 Sourc: KFF/HRET Survy of Employr-Sponsord Halth Bnfits, authors tabulations of LEHID Nots: KFF/HRET Larg Firms hav mor than 5,000 mploys 42

Figur 4. Gographic Distribution of Employs in LEHID Sampl Nots: Data rflcts avrags across th priod 1998-2005. Canyons and othr inhabitabl aras ar outlind in gray. 43

Figur 5. Distribution of Markts by Numbr of Full Insuranc Carrirs, 1998-2005 Sourc: Author s tabulations, LEHID-FI sampl. Th numbr of markts is 108 (1998) 113 (2001) and 76 (2005). 44

Tabl 1. Dscriptiv Statistics, LEHID FI-Compustat Sampl 1998 1999 2000 2001 2002 2003 2004 2005 Prmium ($) 3686 3964 4172 4670 5445 5959 6808 7222 1016 923 957 1104 1378 1450 1885 2124 Enrollmnt (# mploys) 170 174 167 189 191 170 182 203 487 491 416 535 516 387 553 616 Laggd profit margin 0.050 0.054 0.059 0.061 0.061 0.028 0.028 0.043 0.036 0.041 0.052 0.050 0.060 0.114 0.102 0.051 Dmographic factor 2.28 2.26 2.21 2.25 2.29 2.28 2.41 2.36 0.43 0.39 0.37 0.38 0.38 0.40 0.40 0.43 Plan dsign 1.12 1.13 1.11 1.13 1.12 1.11 1.10 1.07 0.05 0.03 0.04 0.03 0.04 0.04 0.08 0.06 Plan typ HMO 88.9% 91.8% 93.2% 92.0% 91.0% 93.5% 91.1% 92.1% Indmnity 2.2% 0.3% 0.0% 0.1% 1.4% 0.0% 1.0% 0.2% POS 6.9% 6.6% 4.6% 4.9% 2.7% 3.7% 3.6% 4.8% PPO 2.0% 1.4% 2.2% 3.1% 4.9% 2.8% 4.3% 2.8% Unmploymnt Rat 0.044 0.041 0.039 0.047 0.058 0.060 0.055 0.051 0.016 0.014 0.010 0.010 0.010 0.011 0.011 0.010 AAPCC ($) 5299 5213 5548 6017 6541 6859 7302 7744 923 885 966 1032 1155 1168 1146 1216 Numbr of mployrs 125 136 129 149 156 184 135 137 Numbr of markts 108 117 109 113 110 101 83 76 Numbr of Obsrvations 7016 8320 6870 7306 6864 6201 4041 3599 Nots: All statistics ar unwightd. Th unit of obsrvation is th mployr-markt-carrir-plan typ-yar. Standard dviations in italics. Prmiums ar rportd in nominal dollars. Profit margin = aftr-tax rturn on assts and is laggd two yars. Dmographic factor rflcts ag, gndr, and family siz for nrolls. Plan dsign masurs th gnrosity of bnfits. Both ar constructd by th data sourc and xact formula ar not availabl. Th unmploymnt rat and Avrag Adjustd Pr Capita Cost (AAPCC) pr Mdicar bnficiary ar rportd at th county-yar lvl by BLS and CMS, rspctivly, and matchd to th markt-yar as dscribd in th txt. 45

Tabl 2. Th Rlationship btwn Employr Profits and Halth Insuranc Prmiums Dpndnt variabl=ln(annual prmium); N=50,217 (1) (2) (3) (4) (5) (6) (7) (8) Laggd Profits 0.024*** 0.026*** 0.043*** 0.052*** 0.043*** 0.051*** 0.030** 0.040*** (0.009) (0.009) (0.014) (0.014) (0.014) (0.014) (0.014) (0.014) Family Siz 0.317*** 0.317*** 0.297*** 0.297*** 0.297*** 0.297*** 0.299*** 0.298*** (0.003) (0.003) (0.005) (0.005) (0.005) (0.005) (0.005) (0.005) Plan Dsign 0.362*** 0.411*** 0.413*** 0.451*** (0.024) (0.032) (0.032) (0.032) Plan Fixd Effcts N N Y Y Y Y Y Y Markt-Yar Covariats Unmploymnt Rat 0.023 0.002 N/A N/A (0.185) (0.184) Ln(Avrag Mdicar Costs) 0.073** 0.084*** N/A N/A (0.033) (0.032) Markt-Yar Intractions Y Y * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Modls ar stimatd using th LEHID FI-Compustat Sampl. Th unit of obsrvation is th mployr-markt-carrir-plan typ-yar. Spcifications corrspond to quation (1) in th txt, and ar stimatd by FGLS to account for srial corrlation of rrors among obsrvations of th sam mployr-marktcarrir-plan typ (or plan ). All spcifications includ fixd ffcts for mployr, markt, carrir, plan typ, yar, plan typ-yar, and mployr-markt. 46

Tabl 3. Th Rlationship btwn Employr Profits and Halth Insuranc Prmiums, By Markt Structur of th Insuranc Sctor Dpndnt variabl=ln(annual prmium); N=50,217 (1) (2) (3) (4) Laggd Profits* <=4 carrirs 0.151*** 0.148** 0.145** 0.168** (0.058) (0.072) (0.072) (0.075) 5-6 carrirs 0.047* 0.092** 0.092** 0.060 (0.027) (0.042) (0.042) (0.043) 7-8 carrirs 0.034*** 0.056*** 0.055*** 0.042** (0.012) (0.018) (0.018) (0.018) 9-10 carrirs 0.013** 0.043** 0.042** 0.034* (0.014) (0.019) (0.019) (0.019) >10 carrirs 0.011 0.035 0.034 0.027 (0.015) (0.024) (0.024) (0.024) Dmographic Factor 0.317*** 0.297*** 0.297*** 0.298*** (0.003) (0.005) (0.005) (0.005) Plan Dsign 0.363*** 0.413*** 0.415*** 0.451*** (0.024) (0.032) (0.032) (0.032) Plan Fixd Effcts N Y Y Y Markt-Yar Covariats Unmploymnt Rat -0.109 N/A (0.185) Avrag Mdicar Costs 0.078** N/A (0.033) Markt-Yar Intractions N N N Y p-valus from H 0 : γ 1, 1 = γ 1,5 H 1 : γ 1, 1 > γ 1,5.01.07.07.04 * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Modls ar stimatd using th LEHID FI-Compustat Sampl. Th unit of obsrvation is th mployr-markt-carrir-plan typ-yar. Spcifications corrspond to quation (2) in th txt, and ar stimatd by FGLS to account for srial corrlation of rrors among obsrvations of th sam mployrmarkt-carrir-plan typ (or plan ). All spcifications includ fixd ffcts for mployr, markt, carrir, plan typ, yar, numbr of carrir catgory, plan typ-yar, and mployr-markt. 47

Tabl 4. Th Rlationship btwn Employr Profits and Halth Insuranc Prmiums, By Markt Structur of th Insuranc Sctor Controlling for Diffrncs in Markup for Plan Dsign Dpndnt variabl=ln(annual prmium); N=50,217 (1) (2) (3) (4) Laggd Profits* <=4 carrirs 0.154*** 0.143** 0.141** 0.162** (0.058) (0.072) (0.072) (0.075) 5-6 carrirs 0.046* 0.091** 0.092** 0.059 (0.027) (0.042) (0.042) (0.043) 7-8 carrirs 0.034*** 0.056*** 0.055*** 0.041** (0.012) (0.018) (0.018) (0.018) 9-10 carrirs 0.013** 0.043** 0.042** 0.034* (0.014) (0.019) (0.019) (0.019) >10 carrirs 0.011 0.035 0.034 0.027 (0.015) (0.024) (0.024) (0.024) Plan Dsign* <=4 carrirs 0.429*** 0.328*** 0.333*** 0.280** (0.071) (0.092) (0.092) (0.109) 5-6 carrirs 0.422*** 0.419*** 0.420*** 0.448*** (0.048) (0.055) (0.055) (0.061) 7-8 carrirs 0.380*** 0.401*** 0.405*** 0.436*** (0.034) (0.041) (0.041) (0.043) 9-10 carrirs 0.323*** 0.435*** 0.434*** 0.482*** (0.034) (0.041) (0.041) (0.042) >10 carrirs 0.358*** 0.415*** 0.417*** 0.462*** (0.039) (0.051) (0.051) (0.054) Dmographic Factor 0.317*** 0.297*** 0.297*** 0.299*** (0.003) (0.005) (0.005) (0.005) Plan Fixd Effcts N Y Y Y Markt-Yar Covariats Unmploymnt Rat -0.111 N/A (0.185) Avrag Mdicar Costs 0.077** N/A (0.033) Markt-Yar Intractions N N N Y p-valus from H 0 : γ 1, 1 = γ 1,5 H 1 : γ 1, 1 > γ 1,5.01.07.08.04 * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Modls ar stimatd using th LEHID FI-Compustat Sampl. Th unit of obsrvation is th mployr-markt-carrir-plan typ-yar. Spcifications corrspond to quation (2) in th txt, and ar stimatd by FGLS to account for srial corrlation of rrors among obsrvations of th sam mployrmarkt-carrir-plan typ (or plan ). All spcifications includ fixd ffcts for mployr, markt, carrir, plan typ, yar, numbr of carrir catgory, plan typ-yar, and mployr-markt. 48

Tabl 5. Robustnss Chck: First Diffrncs Spcifications Δ Laggd Profits 0.026*** 0.021** (0.010) (0.013) Dpndnt variabl=δ ln(annual prmium); N =25,514 (1) (2) (3) (4) *I(<=4 carrirs) 0.128** 0.152*** (0.055) (0.057) *I(5-6 carrirs) 0.036*** 0.012 (0.013) (0.029) *I(7-8 carrirs) 0.036*** 0.030** (0.013) (0.013) *I(9-10 carrirs) 0.011 0.008 (0.014) (0.015) *I(>10 carrirs) 0.023 0.017 (0.016) (0.017) Dmographic Factor 0.289*** 0.290*** 0.289*** 0.290*** (0.005) (0.004) (0.005) (0. 004) Plan Dsign 0.332*** 0.360*** 0.342*** 0.381*** (0.031) (0.032) (0.031) (0.032) Markt-Yar Intractions N Y N Y * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Spcifications corrspond to quation (3) in th txt. Modls ar stimatd using th LEHID FI- Compustat Sampl. Th unit of obsrvation is th mployr-markt-carrir-plan typ. All spcifications includ yar and plan typ-yar fixd ffcts. Spcifications (3) and (4) also includ fixd ffcts for th numbr of carrir catgoris. Robust standard rrors, clustrd by mployr-markt-carrir-plan typ, ar in parnthss. 49

Tabl 6. Dscriptiv Statistics (Switching Analysis) FI and SI combind 1999 2000 2001 2002 2003 2004 2005 Carrirswitch 42% 45% 37% 37% 32% 33% 25% Planswitch 51% 53% 50% 47% 41% 44% 34% Laggd profits 0.06 0.06 0.06 0.06 0.04 0.03 0.04 0.05 0.06 0.04 0.05 0.09 0.10 0.06 Numbr of mployrs 142 138 159 168 213 162 166 Numbr of markts 136 136 137 137 137 137 137 Numbr of obsrvations 5787 6009 5927 7213 8235 6741 6634 FI only Carrirswitch 55% 56% 49% 48% 41% 36% 32% Planswitch 64% 64% 58% 59% 50% 47% 41% Laggd profits 0.05 0.06 0.06 0.06 0.03 0.03 0.04 0.04 0.06 0.04 0.06 0.09 0.10 0.05 Numbr of mployrs 136 129 149 156 184 135 137 Numbr of markts 117 109 113 110 101 83 76 Numbr of obsrvations 3051 3115 2860 3093 2989 1929 1706 Nots: All statistics ar unwightd. Th unit of obsrvation is th mployr-markt-yar. Standard dviations in italics 50

Tabl 7. Switching Analysis Dpndnt Variabl carrirswitch planswitch carrirswitch planswitch carrirswitch planswitch carrirswitch planswitch FI + SI Combind (N=46,546) Laggd Profits -0.580*** -0.516*** -0.584*** -0.523*** -0.406*** -0.234*** -0.340*** -0.162** (0.033) (0.034) (0.033) (0.034) (0.057) (0.059) (0.063) (0.064) Markt-Yar FEs N N Y Y Y Y Y Y Employr FEs N N N N Y Y N/A N/A Employr-Markt FEs N N N N N N Y Y FI Sampl (N=18,743) Laggd Profits -0.528*** -0.423*** -0.534*** -0.432*** -0.405*** -0.207** -0.418*** -0.167 (0.054) (0.054) (0.054) (0.054) (0.054) (0.054) (0.104) (0.103) Markt-Yar FEs N N Y Y Y Y Y Y Employr FEs N N N N Y Y N/A N/A Employr-Markt FEs N N N N N N Y Y * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Spcifications corrspond to quation (4) in th txt. All modls includ yar fixd ffcts. Th unit of obsrvation is th mployr-markt-yar. 51

Tabl 8. Switching Analysis, by Typ of Switch Carrir Changs Add Drop Add and Drop Laggd Profits.236***.038***.062*** (.060) (.008) (.012) Sampl Probability.090.105.160 Prdictd Probability with 10% Laggd Profit Shock.085.083.133 Plan Changs Add Drop Add and Drop Laggd Profits.335***.063***.094*** (.085) (.013) (.016) Sampl Probability.101.108.244 Prdictd Probability with 10% Laggd Profit Shock.099.090.212 * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Entris corrspond to rlativ risk ratios (standard rrors) from a multinomial logit modl stimatd using th carrir chang outcom (top panl) and plan chang outcom (bottom panl) on th combind FI& SI sampl (N=46,546). Both modls includ yar fixd ffcts. 52

Tabl 9. Switching Analysis, By Markt Structur of th Insuranc Sctor Dpndnt variabl=carrirswitch; (N=46,546) (1) (2) (3) (4) Laggd Profits* <=4 carrirs -0.187* -0.179* -0.085 0.128 (0.104) (0.105) (0.110) (0.170) 5-6 carrirs -0.644*** -0.623*** -0.373*** -0.082 (0.083) (0.084) (0.094) (0.126) 7-8 carrirs -0.584*** -0.583*** -0.448*** -0.251*** (0.055) (0.056) (0.070) (0.088) 9-10 carrirs -0.586*** -0.594*** -0.414*** -0.499*** (0.067) (0.068) (0.081) (0.103) >10 carrirs -0.737*** -0.750*** -0.521*** -0.760*** (0.075) (0.076) (0.088) (0.119) Markt-Yar FEs N Y Y Y Employr FEs N N Y N/A Employr-Markt FEs N N N Y * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Modls ar stimatd using th FI & SI combind sampl. All spcifications includ fixd ffcts for yars and numbr of carrir catgoris. Th unit of obsrvation is th mployr-markt-yar.. 53

Appndix Tabl 1. Numbr of Employrs in LEHID Data, 1998-2005 Total At last 1 FI plan At last 1 SI Plan % At last 1 FI Plan 1998 194 181 180 93% 1999 205 197 193 96% 2000 199 185 191 93% 2001 242 226 233 93% 2002 255 226 248 89% 2003 330 274 315 83% 2004 246 194 238 79% 2005 262 203 257 77% 54

Appndix A. Substitution btwn Full and Slf-Insuranc To xamin th ffct of profit shocks on substitution btwn full and slf-insuranc, I bgin with th ntir sampl of halthplans in th markt-yars includd in th LEHID-FI sampl. I drop mployr-markts that xclusivly slf-insur in all yars, as ths mployrmarkts nvr appar in th LEHID-FI sampl. I also rstrict th sampl to mployr-yars with data on laggd profits. I collaps th data to th mployr-markt-yar lvl, crating mploy-wightd avrags for all masurs. Thus, prmium is now th avrag xpctd outlay pr nroll (whthr in an FI or SI plan). I also construct masurs such as th numbr of plans offrd, th prcnt of nrolls in slf-insurd plans, and th prcnt of nrolls in ach plan typ. Th final sampl contains 38,290 obsrvations from 409 uniqu mployrs. Dscriptiv statistics ar prsntd in Tabl A1 blow. Tabl A1. Dscriptiv Statistics, Employr-Markt-Yar Sampl 1998 1999 2000 2001 2002 2003 2004 2005 Prmium ($) 3932 4079 4385 4854 5573 6301 6952 7463 973 914 944 993 1174 1202 1546 1684 Enrollmnt (# mploys) 616 546 511 583 556 528 554 570 1865 1620 1458 1792 1726 1325 1391 1439 Laggd profit margin 0.050 0.053 0.059 0.063 0.060 0.030 0.028 0.039 0.038 0.045 0.054 0.051 0.057 0.111 0.105 0.061 Dmographic factor 2.32 2.28 2.24 2.26 2.31 2.30 2.36 2.35 0.43 0.37 0.35 0.35 0.36 0.36 0.36 0.37 Plan dsign 1.07 1.07 1.05 1.07 1.07 1.05 1.04 1.00 0.06 0.05 0.06 0.05 0.05 0.06 0.08 0.07 Plan Composition % in slf-insurd plans 45.7% 44.9% 48.7% 52.9% 55.0% 61.7% 65.1% 69.6% % offring slf-insurd plan 76.2% 83.4% 84.6% 85.3% 84.2% 88.4% 87.6% 91.7% # Fully-insurd plans 1.66 1.65 1.49 1.39 1.27 1.08 1.00 0.90 # Slf-insurd plans 1.19 1.26 1.33 1.38 1.41 1.57 1.62 1.64 % HMO 47.5% 51.8% 50.7% 47.8% 47.6% 44.8% 43% 50.5% % Indmnity 14.5% 12.0% 8.2% 5.7% 4.9% 3.1% 2.6% 1.8.% % POS 21.6% 16.7% 19.1% 17.7% 13.2% 12.1% 13.4% 11.2% % PPO 16.4% 19.5% 22.0% 28.8% 34.3% 40.0% 41.0% 46.5% Numbr of mployrs 128 137 132 151 160 193 146 150 Numbr of markts 108 117 109 113 110 101 83 76 Numbr of Obsrvations 4222 5029 4624 5255 5384 5718 4047 4011 Nots: Standard dviations in italics. 55

I bgin by stimating th following spcifications (rsults in Tabl A2): (A1) % slf - insurd mt = α + γ profit margin + τ + ς [ +φ ] + ε 1, t 2 t m mt mt and (A2) % slf - insurd mt = α + + τ t 5 NC= 1 + ς γ m 1, NC [ +φ 1( NC) mt ] + ε m mt * profit margin, t 2 + 4 λ NC NC= 1 1( NC) mt Th stimat of γ1is ngativ and marginally significant: firms with profit shocks rly lss on slf-insurd plans. Dcomposing this by th markt structur of FI carrirs rvals no stady pattrn or significant diffrncs across diffrnt markt typs. Thus, in spit of th pric incrass profitabl firms fac, thy ar lss likly to switch toward slf-insuranc than ar lss profitabl firms, ctris paribus. This rsult is not surprising givn th switching analysis, which illustrats th rluctanc of profitabl firms to mak changs to thir plan portfolios. Nxt, I stimat spcifications using th log of prmium (i.. xpctd outlay pr nroll) as th dpndnt variabl (rsults in Tabl A3): (A3) and ln(" prmium" ) mt = α + γ profit margin j J 1 j,t 2 + μ %plantyp j + ψ mt + γ j J 2 dmographics jt mt + γ 3 plan dsign mt (%plantyp jmt * τ t ) + ς m [ + φ ] + εmt mt + τ t (A4) ln(" prmium" ) mt = α + + γ 2 + ψ j J 5 1,NC NC= 1 dmographics jt γ 1(NC) m mt * profit margin + γ 3 plan dsign,t 2 mt + τ (%plantyp jmt * τ t ) + ςm [ + φ ] + εmt + mt t 4 λ NC NC= 1 + μ j J 1(NC) j mt %plantyp j mt Givn th lvl of aggrgation, this spcification cannot includ as rich a st of covariats as that includd in th spcifications using plan-yar data (.g. thr ar no controls for th carrirs usd, and th plan dsign masur is an avrag across plan typs). Howvr, th similarity of th cofficint stimats for plan dsign and dmographic factor is rassuring. On avrag, th rlationship btwn profit shocks and prmiums is positiv and statistically insignificant, but this aggrgat cofficint blis significant associations in concntratd 56

markts. Th magnituds ar quit similar to thos obtaind using only th fully-insurd sampl. Givn fully-insurd plans account for lss than half of nrollmnt in th typical mployr-markt-yar, and slf-insurd plans did not xhibit similar pattrns of prmium incrass in th falsification xrcis, it would sm th cofficint magnituds should b smallr. Howvr, a dirct comparison cannot b mad bcaus th ffctiv wighting schm in th two analyss is quit diffrnt. In th main analysis, ach fully-insurd planyar counts qually; in this supplmntal analysis, ach mployr-markt-yar (som of which do not vn appar in th main analysis) count qually. Th conclusion that mrgs from ths rsults is that profitabl mployrs do nd up paying mor for halth insuranc for th avrag nroll in concntratd insuranc markts, vn onc xpctd outlays from slf-insurd nrolls ar incorporatd into th calculation. Tabl A2. Effct of Profits on Slf-Insuranc Rat Dpndnt variabl=% slf-insurd; N =38,290 (1) (2) (3) (4) Laggd Profits -0.058* -0.057* (0.031) (0.030) *I(<=4 carrirs) -0.096 0.021 (0.172) (0.175) *I(5-6 carrirs) -0.104-0.080 (0.074) (0.075) *I(7-8 carrirs) -0.074* -0.065 (0.042) (0.042) *I(9-10 carrirs) -0.019-0.009 (0.048) (0.048) *I(>10 carrirs) -0.056-0.096* (0.055) (0.056) Markt-Yar Intractions N Y N Y * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Th unit of obsrvation is th mployr-markt-yar. Spcifications corrspond to quations (A1) and (A2), and ar stimatd by FGLS to account for srial corrlation of rrors among obsrvations from th sam mployr-markt. 57

Tabl A3. Th Rlationship btwn Employr Profits and Expctd Halth Insuranc Outlays, By Markt Structur of th Insuranc Sctor Dpndnt var=ln(xpctd outlays); N=38,290 (1) (2) (3) (4) Laggd Profits 0.016 0.014 (0.013) (0.013) *I(<=4 carrirs) 0.152** 0.134** (0.062) (0.064) *I(5-6 carrirs) 0.072** 0.068** (0.030) (0.031) *I(7-8 carrirs) 0.025 0.024 (0.017) (0.017) *I(9-10 carrirs) 0.021 0.023 (0.019) (0.019) *I(>10 carrirs) -0.040* -0.045** (0.022) (0.022) Dmographic Factor 0.415*** (0.025) 0.434*** (0.026) 0.414*** (0.025) 0.433*** (0.026) Plan Dsign 0.321*** (0.005) 0.321*** (0.005) 0.322*** (0.005) 0.321*** (0.005) Markt-Yar Intractions N Y N Y p-valus from H 0 : γ 1, 1 = γ 1,5 H 1 : γ 1, 1 > γ 1,5 N/A N/A.00.00 * p <0.10, ** p < 0.05, *** p < 0.01 Nots: Th unit of obsrvation is th mployr-markt-yar. Spcifications corrspond to quations (A3) and (A4) and ar stimatd by FGLS to account for srial corrlation of rrors among obsrvations from th sam mployrmarkt. 58