Essays on Adverse Selection and Moral Hazard in Insurance Market

Transcription

1 Gorgia Stat Univrsity Gorgia Stat Univrsity Risk Managmnt and Insuranc Dissrtations Dpartmnt of Risk Managmnt and Insuranc Essays on Advrs Slction and Moral Hazard in Insuranc Markt Jian Wn Cntral Univrsity of Financ and Economics Follow this and additional works at: Rcommndd Citation Wn, Jian, "Essays on Advrs Slction and Moral Hazard in Insuranc Markt." Dissrtation, Gorgia Stat Univrsity, This Dissrtation is brought to you for fr and opn accss by th Dpartmnt of Risk Managmnt and Insuranc at Gorgia Stat Univrsity. It has bn accptd for inclusion in Risk Managmnt and Insuranc Dissrtations by an authorizd administrator of Gorgia Stat Univrsity. For mor information, plas contact [email protected].

2 Prmission to Borrow In prsnting this dissrtation as a partial fulfillmnt of th rquirmnts for an advancd dgr from Gorgia Stat Univrsity, I agr that th Library of th Univrsity shall mak it availabl for inspction and circulation in accordanc with its rgulations govrning matrials of this typ. I agr that prmission to quot from, or to publish this dissrtation may b grantd by th author or, in his/hr absnc, th profssor undr whos dirction it was writtn or, in his absnc, by th Dan of th Robinson Collg of Businss. Such quoting, copying, or publishing must b solly for scholarly purposs and dos not involv potntial financial gain. It is undrstood that any copying from or publication of this dissrtation which involvs potntial gain will not b allowd without writtn prmission of th author. Studnt s Nam: Jian Wn

3 Notic to Borrowrs All dissrtations dpositd in th Gorgia Stat Univrsity Library must b usd only in accordanc with th stipulations prscribd by th author in th prcding statmnt. Th author of this dissrtation is: Nam: Jian Wn Addrss: 39 South Collg Rd, Haidian District Bijing, China, 0008 Th dirctor of this dissrtation is: His/Hr Nam: Martin F. Grac Dpartmnt: Risk Managmnt and Insuran Dpartmnt Addrss: PO Box 4036, Gorgia Stat Univrsity Atlanta, GA 3030

4 ESSAYS ON ADVERSE SELECTION AND MORAL HAZARD IN INSURANCE MARKET BY JIAN WEN A Dissrtation Submittd in Partial Fulfillmnt of th Rquirmnts for th Dgr of Doctor of Philosophy in th Robinson Collg of Businss of Gorgia Stat Univrsity GEORGIA STATE UNIVERSITY ROBINSON COLLEGE OF BUSINESS 00 3

5 Copyright by Jian Wn 00 4

6 ACCEPTANCE This dissrtation was prpard undr th dirction of th candidat s Dissrtation Committ. It has bn approvd and accptd by all mmbrs of that committ, and it has bn accptd in partial fulfillmnt of th rquirmnts for th dgr of Doctor in Philosophy in Businss Administration in th Robinson Collg of Businss of Gorgia Stat Univrsity. Dissrtation Committ: Dr. Martin F. Grac Chair Dr. Robrt W. Klin Dr. Mary Bth Walkr Dr. Zhiyong Liu H. Fnwick Huss Dan Robinson Collg of Businss 5

7 ABSTRACT ESSAYS ON ADVERSE SELECTION AND MORAL HAZARD IN INSURANCE MARKET By JIAN WEN July 30, 00 Committ Chair: Major Dpartmnt: Dr. Martin F. Grac Dpartmnt of Risk Managmnt and Insuranc Essay On xamins th asymmtric information problm btwn primary insurrs and rinsurrs in th rinsuranc industry and contributs uniquly to th sparation of advrs slction from moral hazard, if both ar prsnt. A two-priod principal-agnt modl is st up to idntify th signals of advrs slction and moral hazard gnratd by th actions of th primary insurr and to provid a basis for corrsponding hypothss for mpirical tsting. Using data from th National Association of Insuranc Commissionrs NAIC and A.M. Bst Company, th mpirical tsts show that th problm of advrs slction xists in th rinsuranc markt btwn th affiliatd insurrs and non-affiliatd rinsurrs, and vn btwn closly rlatd affiliatd insurrs and rinsurrs. Thr is no vidnc indicating th prsnc of moral hazard in th rinsuranc markt. To addrss th issu of soaring proprty insuranc prmiums and covrag availability in stats that ar subjct to hurrican risks, stat and fdral govrnmnts hav not only rgulatd th privat insuranc markt but hav also intrvnd dirctly into markts by stablishing govrnmnt-fundd insuranc programs. With coxisting public and privat insuranc 6

8 mchanisms and pric rgulation, th risk of cross subsidization and a subsqunt moral hazard problm may aris. By using data from th Florida Citizns Insuranc Corporation, th Florida Hurrican Catastroph Fund, th Flood Insuranc and th privat homownr insuranc markt in Florida from 998 to 007, th scond ssay xamins th moral hazard problms arising from govrnmnt rgulation and involvmnt in th privat insuranc sctor. In sum, th provision of national flood insuranc is found to b positivly rlatd to th population growth in th stat of Florida, which shows that stat immigrants can tak advantag of th lowr cost of flood insuranc whn rlocating in highr-risk aras. Furthr, w find that national flood insuranc and th catastroph fund complmnt th dvlopmnt of th privat insuranc sctor, whil th rsidual markt hindrs th dvlopmnt of privat proprty insuranc markt. 7

9 Essay On Distinguishing Diffrnt Effcts of Asymmtric Information: Evidnc from Proprty and Liability Rinsuranc Markt 8

10 Abstract This ssay xamins th asymmtric information problm btwn primary insurrs and rinsurrs in th rinsuranc industry and contributs uniquly to th sparation of advrs slction from moral hazard, if both ar prsnt. A two-priod principal-agnt modl is st up to idntify th signals of advrs slction and moral hazard gnratd by th actions of th primary insurr and to provid a basis for corrsponding hypothss for mpirical tsting. Using data from th National Association of Insuranc Commissionrs NAIC and A.M. Bst Company, th mpirical tsts show that th problm of advrs slction xists in th rinsuranc markt btwn th affiliatd insurrs and non-affiliatd rinsurrs, and vn btwn closly rlatd affiliatd insurrs and rinsurrs. Thr is no vidnc indicating th prsnc of moral hazard in th rinsuranc markt. 9

11 . Introduction Sinc th middl of th last cntury, th study of th problm of asymmtric information has bcom important in th fild of conomics and insuranc Akrlof, 970; Arrow 965; Rothschild & Stiglitz, 976. Much progrss has bn mad from both a thortical and an mpirical prspctiv. Bfor conomists took th qustion of information transparncy into considration, thy commonly assumd th prsnc of complt information. Th concpt of complt information implis that all th information is transparnt and qually known to both partis. Convrsly, th concpt of asymmtric information implis that th information known to on party may b unknown or only partially known or availabl to anothr. Of th two concpts, th lattr, asymmtric information, coms closst to dscribing or rflcting th ral conomic world. Prdictably, assuming th prsnc of asymmtric information could lad to outcoms that would diffr significantly from thos rsulting from an assumption of complt information. Insuranc pricing is a good xampl of this. Th insurr sts th prmium basd on actuarial data on th prvious loss xprinc within a normal population. In th long run, th company will brak vn, if th risk is at th avrag lvl as prsumd. Unfortunatly, popl who, in fact, rprsnt a highr-than-avrag risk lvl, may b abl to purchas insuranc covrag against thir mor frqunt or mor svr futur losss at a favorabl pric that was originally basd on th lowr, avrag, risk. This disconnct may occur bcaus insurrs lack sufficint information on th prcntag of th pool with highr risk and th xact risk lvls rprsntd, vn though th insurd is fully awar of th risk lvl. Thrfor, this asymmtric information situation may lad to highr losss for th insurr. 0

12 Th xistnc of asymmtric information normally ntails two complmntary problms: advrs slction and moral hazard. Th trm advrs slction rfrs to circumstancs which prmit an insurd with highr risk to buy insuranc at a prmium calculatd to srvic th avrag risk lvl. Th trm moral hazard rfrs to th tndncy of insurrs to xrcis lss prcaution than thy should, stablishing inadquat incntivs to control th risks rprsntd by thos to whom thy provid covrag. Advrs slction and moral hazard both contribut to th potntial for highr losss than th insurr may hav xpctd. Whn asymmtric information is known to xist, th optimal risk-sharing schm and pricing may wll nd to dviat from thos that would b institutd if complt information wr availabl Rothschild & Stiglitz, 976. In th prsnc of srious asymmtric information, th insurr may xprinc a much highr loss than xpctd; and in th worst cas, th insuranc markt itslf may totally fail Akrlof, 970. Thrfor, th dtction of possibl asymmtric information, including th discovry of prviously unknown risk, has th potntial to bnfit both th insurr and th insurd. For xampl, halth and lif insuranc undrwriting rquirs physical xamination and applis dductibls, coinsuranc and pricing tid to diffrnt risk lvls of th insurd. Common sns would conclud that such procdurs would hav th ffct of uncovring possibl risks, factoring ths risks into th covrag, and thrby rducing th dangr of asymmtric information. Whil th thortical analysis of asymmtric information in th insuranc markt was introducd almost half a cntury ago, mpirical tsting did not appar until th 980s. Now, from th xamination of lif, halth, annuity and automobil insuranc markts, w can s vidnc that, compard to othr insuranc markts, lif insuranc has lss of a problm of

13 asymmtric information du to strict rquirmnt of physical xamination to dtrmin th risk status of th insurd. As th insuranc for th insuranc companis, th rinsuranc industry furthr distributs th risks poold by th primary insurrs. It is not unusual for rinsuranc companis to b run nationally or intrnationally, which buffrs th advrs ffct of hug losss to th whol insuranc markt and ultimatly lowrs th prmium paid by individuals. With th catastrophic vnts in th past dcads, th proprty and liability rinsuranc markt hav xhibitd an incrasing ability to absorb big losss and stabiliz th whol insuranc markt in th U.S. Cummins, 007. Thrfor th proprty and liability rinsuranc markt is not only a critical part of th insuranc markt, but also an indispnsabl factor in stabilizing th conomy. Howvr, asymmtric information xisting btwn primary insurrs and th rinsurrs may still pos a srious thrat to th rinsuranc markt. Th ffct of asymmtric information on th rinsuranc markt can b analyzd from th prspctivs of advrs slction and moral hazard. For rinsuranc, advrs slction would b vidncd by high-risk firms gtting similar or vn bttr trms for thir rinsuranc purchas than low-risk firms. In contrast, moral hazard xists whn th primary insuranc companis loosn thir undrwriting critria, lading ultimatly to highr losss than xpctd. Both advrs slction and moral hazard would mak th actual loss highr than thos stimatd by th rinsuranc company, with ngativ consquncs for th insuranc markt. This xamination of asymmtric information shds light on challngs in th rinsuranc businss. Bttr knowldg of asymmtric information btwn th primary insurr and th rinsurr can hlp improv risk allocation and pricing in th rinsuranc markt. For th primary insuranc company, managing risk through purchasing rinsuranc is a much mor complx

14 mattr du to factors such as risk divrsification, progrssiv tax and financial nds than risk managmnt at th lvl of individual policy holdrs. This ssay xamins th asymmtric information problms btwn th rinsuranc and primary companis in th proprty and liability rinsuranc markt in th U.S. Rcntly, Jan- Baptist and Santomro 000 addrssd th asymmtric information problms which affct th fficincy of risk allocation btwn th primary insuranc companis and thir rinsurrs. Thy showd that long-trm contracts btwn th two will improv th allocation of risk by including and factoring in nw risk information ovr tim. Thy prdictd that th us of long-trm rinsuranc contracts will incras th dmand for rinsuranc, incras primary insurr s profits and lowr th probability of bankruptcy. Empirically, Dohrty and Smttrs 005 and Garvn and Grac 007 providd th vidnc of asymmtric information in th rinsuranc markt. Dohrty and Smtttrs 005 tstd th potntial moral hazard problm btwn th rinsurr and th primary company. Thy found that loss-snsitiv pricing was mainly usd to control moral hazard btwn th nonaffiliatd rinsurrs and insurrs, whil monitoring was widly usd to control moral hazard btwn th affiliatd rinsurrs and insurrs whr th monitoring cost was rlativly lowr. Garvn and Grac 007 xplord th advrs slction problm basd on th thortical prdictions by Jan-Baptist and Santomro 000. Thir findings ar consistnt with and supportiv of th thortical prdictions. Nvrthlss, ach of ths two works only focuss on on sid of th asymmtric information issu whil ignoring th xistnc and th ffcts of th othr on. 3

15 For xampl, Dohrty and Smttrs 005 assumd moral hazard as th only ffct of th asymmtric information; Garvn and Grac 007 only attributd th ffcts of th asymmtric information to advrs slction. Furthr, an intrsting rsarch qustion ariss: do advrs slction and moral hazard xist at th sam tim to b part of th asymmtric information problm? Th answr to this qustion is th contribution of this ssay, which distinguishs advrs slction from moral hazard, as thy xist btwn th primary insurr and th rinsurr. Th rason for sparating ths two factors of th asymmtric information is that thy lad to highr losss through diffrnt mchanisms. Accordingly diffrnt contract faturs ar rquird to corrct thm. Manwhil, affiliatd and non-affiliatd rinsurrs ar discussd sparatly, as th affiliatd rinsurrs blong to on financial group and non-affiliatd rinsurrs ar indpndnt companis with rspct to th primary insurr. Du to th varying rlationship btwn risnurrs and insurrs, asymmtric information is xpctd to prsnt diffrnt pattrns. Th ssay procds as follows: in th scond sction, rlatd litratur is rviwd. Thn, th two-priod principal-agnt modl is st up in th third sction. In th fourth sction, basd on th hypothsis drivd from th thortical modl, an mpirical tst is conductd on th panl data for th affiliatd and non-affiliatd proprty and liability rinsuranc markt from 99 to Litratur Rviw A sris of sminal paprs Akrlof, 970; Borch 96; Holmstrom, 979; Raviv, 979; Rothschild & Stiglitz, 976 built up th thortical foundation of asymmtric information studis in conomics. Akrlof 970 suggstd that markt quilibrium may not xist, du to th 4

16 xistnc of asymmtric information btwn th participants, in contrast to th quilibrium that would b xpctd if complt information wr availabl Mossin, 968. Furthrmor, Rothschild and Stiglitz 976 analyzd th comptitiv markt in which imprfct information, spcifically advrs slction, was considrd. Thy found out that low-risk individuals wr ngativly affctd by th prsnc of high-risk individuals, whil high-risk individuals bnfitd from th prsnc of low-risk individuals. Thy also found that singl pric quilibrium dos not xist and that th structur and xistnc of a possibl quilibrium dpnd upon particular assumptions. Holmstrom 979, on th othr hand, invstigatd th imprfct information problm in a principal-agnt modl with th considration of moral hazard. H concludd that th optimal contract is scond-bst du to th agnt s unobsrvd action, but additional information, lik monitoring or managrial accounting, will improv th fficincy of th contract. Thrfor, th dtction of asymmtric information and th corrsponding contract dsignd to addrss this issu ar critical to improving fficincy in th insuranc markt. In this cas, th principal-agnt modl provids a framwork for how to allviat th agncy problm, and, consquntly, dcrass th occurrnc of asymmtric information. Lambrt 983 charactrizd th optimal long-trm contract, dsignd to control th moral hazard of th agnt, as on in which th agnt s compnsation dpnds on not only th currnt priod but also th prvious priod. In addition, Laffont and Tirol 987 drivd th optimal dynamic incntiv mchanism undr th possibl monitoring of th agnt, and thy showd th xistnc of th possibl continuation quilibrium. Th mpirical tsts of asymmtric information on insuranc markts validat and supplmnt th thortical prdictions. Th mpirical hypothsis against th xistnc of 5

17 asymmtric information is statd as th positiv rlation btwn th risk lvls of thos who purchas insuranc covrag and th actual risk typ rvald aftr losss occur s Pulz & Snow, 994. Howvr, mixd rsults ar rportd in diffrnt businss lins of insuranc: th insignificanc of positiv rlation of insuranc quantity purchas and mortality risk of individuals in lif insuranc markt suggstd that information can b tratd as complt undr th currnt tst Cawly & Philipson, 997. For th annuity markt, Finklstin and Potrba 004 found a systmic rlationship btwn th x post mortality and th timing of annuity paymnts, consistnt with th prsnc of advrs slction. Pulz and Snow 994 and Chiaporri and Salani 000 rportd mixd rsults rgarding th prsnc of asymmtric information in th automobil insuranc markt. Th prvalnt xplanation attributs this mixd vidnc to th application of long-trm contract and risk classification in diffrnt insuranc businss lins. Bcaus insuranc prmiums ar contractd ovr multipl trms, and factors such as xprinc rating or risk slction ar usd to dtrmin th ral risk typ, th ffcts of asymmtric information can b modratd ovr tim. For instanc, th absnc of asymmtric information in lif insuranc can b attributd as th adoption of mdical xamination as part of undrwriting to rval th tru halth status of th insuranc applicants. Rinsuranc is also subjct to th asymmtric information problm btwn th insurrs and th rinsurrs. In comparison to th individual insurd, th incntiv for th insurr to purchas rinsuranc is mor complicatd. Th dcision to rinsur involvs issus such as risk managmnt, incrasing capability or th pursuit of tax bnfits. Basd on its own firm charactristics, th insurr has its own dgr of dmand for rinsuranc. As Mayr and Smith 990 pointd out, th ownrship structur, firm siz, gographic concntration and businss lins concntration hav significant ffcts on th dmand for rinsuranc. 6

18 Manwhil, th complicatd risk structur of th insurrs may rflct in multipl dimnsions in undrwriting, oprating and financing managmnt. As a rsult, it s costly for th rinsurr to collct complt information which would rval th tru risk of th insurr bfor th transaction is don. Consquntly, advrs slction occurs whn a high-risk firm concals information and rcivs bttr trms from th rinsurrs than thy would hav othrwis rcivd. Thrfor, long-trm contracts and th practic of rtrospctiv rating, which adjusts prmiums basd on th loss incurrd during th prvious policy priod, ar widly applid in th rinsuranc industry to solv th asymmtric information problm. Jan-Baptist and Santomro 000 showd that th nw information includd in pricing of both futur and past rinsuranc covrag for long-trm rinsuranc contracts can nhanc th ffctivnss of risk allocation btwn th primary insuranc companis and rinsuranc companis. Thy statd thr hypothss: Othr things bing qual, long-trm rinsuranc contracting rlationships will b associatd with highr lvls of rinsuranc covrag; Othr things bing qual, long-trm rinsuranc contracting rlationships will b associatd with highr insurr profits; 3 Othr things bing qual, long-trm rinsuranc contracting rlationships will b associatd with lowr lvls of bankruptcy. Garvn and Grac 007 did mpirical tsts of th abov hypothsis to s if thr is any advrs slction in th rinsuranc markt and, furthr, if th asymmtric information problm is solvd ovr tim. With panl data consisting of U.S proprty-liability insuranc firms, which rportd to th National Association of Insuranc Commissionrs NAIC during th priod 995 to 000 and A.M. Bst financial ratings for insuranc companis, thy found vidnc supporting th thortical prdictions by Jan-Baptist and Santomro. Ths findings imply that longr 7

19 rinsuranc rlationships lad to mor rinsuranc covrag, highr profitability, and lowr bankruptcy risk. Dohrty and Smttrs 005 tstd moral hazard in th rinsuranc markt with a multipriod principal-agnt modl of th rinsuranc transaction. Thy drivd prdictions on prmium dsign, monitoring, loss control and insurr risk rtntion. Thy found that a losssnsitiv prmium is usd to control moral hazard whn insurr and rinsurr ar not affiliats, whil monitoring is mphasizd whn th insurr and rinsurrs ar affiliats. Th problm of asymmtric information in rinsuranc markts has bn invstigatd in othr countris bsids th Unitd Stats. Adam and Diocon 006 tstd th asymmtric information problm in th UK proprty-liability rinsuranc markt. Two rlationships ar mainly tstd in thir papr. On is th rlationship btwn gross losss and th amount of rinsuranc purchasd by a primary insuranc company; th othr rlationship xamind is btwn th rinsuranc prmiums paid and th gross losss and rinsurd claims rcovrd by th primary insurr. Th lattr is a dmonstration of claim-contingnt pricing which charactrizs th rinsuranc transaction. Th Hausman ndognity tst undr th Hckman two-stag modl can sparat advrs slction from moral hazard; thy found that information asymmtry dos xist in th rinsuranc markt btwn th affiliatd insurrs and rinsurrs. Spcifically, advrs slction xists in th automobil and third party insuranc markts, and moral hazard appars in th miscllanous and pcuniary insuranc markts. In contrast, for th non-affiliatd insuranc companis, th claim-contingnt pricing rducs th problm of asymmtric information. 8

20 3. Thortical Modl Basd on th modl proposd by Dohrty and Smttrs 005, a two-yar principalagnt modl is st up to captur th asymmtric information btwn th insurrs and th rinsurrs in th rinsuranc markt. Dohrty and Smttrs 005 dvlop a two-priod principal-agnt modl from which to driv prdictions on prmium dsign, monitoring, loss control and insurr risk rtntion to idntify moral hazard in rinsuranc transactions. Th agnt, or primary insurr, pays a prmium Pt in priod of t to th rinsurr for a rinsuranc contract which is subjct to a dductibl or risk rtntion of S t. Undr this contract, th indmnity to th primary insurr in priod t is max[ 0, Lt St ], whr L t is incurrd dirct loss in priodt. Action a is takn by th primary insurr whn undrwriting businss, handling claims and controlling risks. Th action is not obsrvd by th principal, th rinsurr, whras it is assumd that action a gnrats a signal m that is imprfctly corrlatd with a, but still convys valuation information to th principal. Consquntly, th incurrd loss and signal dpnd on action by th primary insurr who writs insuranc businss to th insurd customr dirctly. On th othr hand, th principal, th rinsurr, rcivs prmium Pt in priod t and indmnifis th primary insurr with max[ 0, L S ] if th incurrd loss xhausts th stop loss. To rduc th moral hazard problm t t which may occur on th sid of th primary insurr, th rinsurr pays a cost of c to monitor th primary insurr. Th rinsurr picks prmiums for yar and yar to maximiz total profit subjct to th primary insurr s incntiv constraint and participation constraint. Th optimal prmium structur is thn drivd from th first-ordr conditions, and thn th modl prdicts th rlations btwn th rinsuranc prmium and dirct loss control, rtrospctiv rating, 9

21 xprincd rating and monitoring. Spcifically, th rinsuranc prmium P t is prdictd to b ngativly rlatd to th invrs of total dirct losss by th primary insurr in priod t, ngativly rlatd to th invrs of th amount of rinsurd losss in priod t, ngativly rlatd to th invrs of th amount of total dirct losss by th primary insurr in priod t, incrasing in th signal of m Dohrty & Smttrs,005, p 384. Th modl abov only focuss on th moral hazard of th asymmtric information problm. To captur th possibl advrs slction problm, on mor signal s, which signifis th opration quality of th primary insurr, is incorporatd into th modl abov in this ssay. Basically, th signal s is xpctd to rval th ral risk typ of th primary insurr to th rinsurr. Hnc, a masur of th loss volatility of th primary insurr, or a masur indicating thir ovrall financial capability, can provid th information rlativ to th risk typ of th insurr. Compard to signal s, anothr signal m in th modl convys th ffort xrtd by th primary insurr to th rinsurr, and signal m is imprfctly corrlatd to fforts undr th rinsuranc covrag. Anothr nw contract fatur considrd in this modl is th covrag cap, A, of th rinsuranc contract. This is dfind in th xcss of loss rinsuranc, whrby th primary insurr covrs th amount of ach claim up to th rtntion lvl and th rinsurr rpays th loss byond th rtntion lvl to th covrag cap to th insurr. Th diffrnc btwn rtntion lvl and th covrag cap is th actual rinsuranc covrag purchasd by th primary insurr. 3. Th Primary Insurr s Problm Assum th primary insurr is strictly risk-avrs, and its utility function is U w, ' '' whru w > 0, U w < 0, w is th surplus at th bginning of th contract. Th argumnts for this risk-avrs assumption ar th contxts of th progrssiv tax, th undrinvstmnt problm, 0

22 high bankruptcy costs and asymmtric information in th rinsuranc markt. Ths markt frictions mak th insurrs risk-avrs vn if th company is widly hld by public sharholdrs. At th bginning of on priod, th primary insurr pays prmium P to purchas on xcss-ofloss rinsuranc policy with th rtntion lvl of D, and covrag cap of A. Assum th incurrd loss ovr this priod is L. Th amount of rcovrd loss paymnt rcivd from th rinsurr dpnds on th amount of th incurrd losss. If th incurrd loss is lss than th rtntion lvl, L D th rinsurr dos not pay anything to th primary insurr. If th incurrd loss falls btwn th rtntion lvl and covrag cap, D L A th rinsurr pays th amount of L D to th primary insurr. If th actual loss is byond th covrag cap, A L th obligation of th rinsurr is th amount of A D. During th contract priod, th primary insurr xrts an ffort of to undrwrit businss from th insurd, control loss and assss th claims. W argu that this ffort is abl to gnrat signals to th rinsurr about ral oprational quality and incntivs of th primary insurr in th sns that th prformanc of th primary insurr nvrthlss rflcts th ffort it taks. W dnot signal s as th indication of th opration quality, which is th ral risk typ, of th primary insurr. W thn dnot signal m as th indication of th incntiv of th primary insurr. As a rsult, th conditional joint probability dnsity function of actual loss and signals ar rprsntd as f s, m, L. A two-yar framwork is considrd. In th first yar, th rinsuranc prmium is a function of actual loss, rtntion lvl, covrag cap and signals of th primary insurr s ffort: P = P L, D, A, s, m. For th scond-yar pricing, th actual loss of th first yar is also takn into account, as ar th scond yar losss, th rtntion lvl, th covrag cap and th signals in th scond-yar priod: P = P L, L, D, A, s,. m

23 For th simplicity of computation, a zro risk-fr rat is assumd in this rinsuranc modl. Dfin an insurr s nd-of-priod walth,π as a random variabl. Thn th insurr s walth as nd of th first yar isπ, and th walth as nd of th scond yar isπ. For i =, W i Pi Li if Li Di π i = W i Pi Di if Di < Li Ai W i Pi Li + Ai Di if Ai < Li Th xpctd utility of th insurr for two yars ar E U π and E U π, rspctivly. So th total xpctd utility of th primary insurr from taking th rinsuranc transaction is E U = E U π + E U. Th calculation of xpctd utility by intgration rfrs to th π appndix. Bcaus incurrd losss dpnd on ffort as f s, m, L, th primary insurr picks fforts and to maximiz its xpctd utility in two yars. 3. Th Rinsurr s Problm Th rinsurr incurs a monitoring cost of c and c to analyz tru risk typ of th insurr by obsrving th information dlivrd in th two priods, rspctivly. Th rinsurr maks th profit out of th prmium incom aftr dduction of loss rpaymnts and monitoring costs. Dfin th rinsurr s profit I i, i =, as a random variabl. Thn th rinsurr s profit in th first yar is I and its profit in th scond yar is I. Th profit Ii is dfind as follows. Pi if Li Di I i = Pi Li + Di if Di < Li Ai Pi Ai + Di if Ai < Li Rinsurrs will monitor th primary, among which long-trm contracts ar usually applid. Th application of monitoring ncourags th primary insurrs to tak appropriat masurs to control thir risks, thrfor rducs th potntial losss of risnurrs. Also s Dohrty 997.

24 Th rinsurr chooss th prmium P and P in two yars to maximiz th total profit I = E I + E. Th calculation of total profit by intgration rfrs to th appndix. I Th optimization problm is to maximiz th total profit of th principal, which is th rinsurr in this cas, subjct to th participation constraint and incntiv constraint by th agnt, th primary insurr. To solv this optimal problm, th optimal valus of P, P ;, } ar obtaind. Th optimization problm is statd as follows. Subjct to max P, P,, I E U U 3 E U = 0 4 E U = 0 5 { Equation 3 is th participation constraint of th primary insurr, whr U th rsrvation is th xpctd utility of th primary insurr that it would hav without rinsuranc. Equation 4 and 5 ar first-ordr conditions with rspct to th fforts in th two priods. Th incntiv constraints nsur that th primary insurrs mak fforts to maximiz thir xpctd utility. To simplify th joint probability dnsity function of actual loss f s, m, L, signal s and m ar assumd to b indpndnt of actual loss L as suggstd by Holmstrom 979. Furthr, signals s and m ar assumd to b indpndnt from ach othr, in that signal s is usd to addrss advrs slction, whil signal m is adoptd to captur moral hazard problm, rspctivly. Thrfor, th joint probability dnsity function of actual loss is writtn as f s, m, L = k s g m h L. 3

25 4 Lt,, γ γ λ dnot th Lagrangian multiplirs for constraints 3-5, th first-ordr conditions ar rducd as follows: ' ' ' ' D L if L h L h m g m g s k s k L P W U = γ λ 6 ' ' ' ' A L D if L h L h m g m g s k s k D P W U < = γ λ 7 ' ' ' ' L A if L h L h m g m g s k s k D A L P W U < = + γ λ 8 ' ' ' ' ' ' ' D L if L h L h L h m g m g m g s k s k s k L L h L h m g m g s k s k L P W U = γ γ λ 9 ' ' ' ' ' ' ' A L D if L h L h L h m g m g m g s k s k s k L L h L h m g m g s k s k D P W U < = γ γ λ 0 ' ' ' ' ' ' ' L A if L h L h L h m g m g m g s k s k s k L L h L h m g m g s k s k D A L P W U < = + γ γ λ whr ' s k, ' m g, and ' L h ar th drivativ functions of s k, m g, and L h with rspct to th ffort.

26 To mak Lagrangian multiplirs λ, γ, γ b positiv, w mak th following assumptions ' on th liklihood ratio by Lambrt 983: h L / h L is dcrasing in L ; ' h L /[ h L * h L ] is dcrasing in L. Equations 6- dfin th risk-sharing structur btwn th primary insurr and th rinsurr in th two-priod framwork. Th modl prdictions ar similar to th ons drivd by Dohrty and Smttrs 005. For xampl, both modls show that th rinsuranc prmium is not only rlatd to th concurrnt dirct loss by th primary insurr but also to th dirct incurrd loss in th last priod. Howvr, our modl uniquly incorporats th signals to rval th possibl advrs slction and moral hazard problm to th rinsurr ovr tim and gnrat sparat tstabl prdictions for mpirical studis. This modl allows us to distinguish advrs slction from moral hazard, if any, in th rinsuranc markt. Furthrmor, th modl taks into considration th covrag cap in th xcss-of-loss rinsuranc policy, a factor which Dohrty and Smttrs 005 dos not addrss. Th covrag cap and rtntion lvl togthr st th actual rinsuranc covrag purchasd by th primary insurr. Th modl prdictions and drivd hypothsis ar discussd as follows. 3.3 Modl Prdictions Concurrnt dirct loss: With th incras of th concurrnt loss, ' h L / h L dcrass basd on th modl assumption. According to th utility function of U th insurr in th first priod, P ' U =, U L ' U = ' ' U U so > 0. Th modl shows that L P th rinsuranc prmium is positivly rlatd to th concurrnt dirct loss. Th indpndnc of signals of advrs slction and moral hazard is assumd, and th distinctiv sparation of two ffcts is obtaind. Howvr, thy can b corrlatd which is discussd latr. In this cas, th two ffcts can still b distinguishd, but with diffrnt impacts on th rinsuranc dmand. 5

27 Signal for advrs slction: Th modl shows that th rinsuranc prmium incrass with th obsrvation of signal s. Ovr tim, signal s is xpctd to rval th tru typ of th primary insurr, such as its oprational quality, to th rinsurr, in ordr to mitigat a possibl advrs slction problm. Signal for moral hazard: Th modl suggsts that rinsuranc prmiums incras with th obsrvation of signal m. Signal m is xpctd to dtct th ffort incntiv drivn by th primary insurr with th rinsuranc covrag. With th prdictions drivd from th modl, w ar now abl to do th mpirical tst. 4. Th Empirical Analysis This sction prsnts an mpirical analysis basd on th thortical modl abov, along with th corrsponding rsults. First, th mpirical hypothss ar drivd from th thortical modl and th stimatd quations ar constructd. Scondly, th data st usd for th mpirical analysis and th construction of tstabl variabls ar introducd. Aftr considring th rlatd conomtric issus, th tst rsults for affiliatd, non-affiliatd proprty and liability insurrs and insurrs ar discussd and compard. 4. Hypothss From th thortical modl in sction thr, w drivd th mpirical hypothsis rgarding rinsuranc purchas and th signals of advrs slction and moral hazard. Th variabl corrsponding to advrs slction is xpctd to rval th tru risk typ of th primary insurr in trms of its ovrall opration quality and financial strngth. A.M. Bst ratings on primary insurrs, ar widly usd to rank and compar lvls of financial strngth among insuranc companis. Ths rankings appar as lttr ratings A++, A+, A-, B+, tc., and 6

28 th company with A++ has highst lvl of financial strngth. Bcaus A.M. Bst considrs th financial capability, loss xprinc, oprational and managrial risks into rating insuranc companis, th financial rating can b a good indicator of th tru risk typ of th companis. Th logic follows that highr rating of th insurr associats with lowr risk. In th contxt of advrs slction in rinsuranc markt, an insurr with lowr ratings is prdictd to dmand mor rinsuranc bcaus of thir insufficint financial capability or poor loss xprinc. Thrfor, th hypothsis with rspct to th advrs slction in th asymmtric information problm is statd as follows. Hypothsis : Othr things bing qual, a lowr A.M. Bst financial rating on primary insurrs is associatd with highr rinsuranc purchas. Th signal of moral hazard is dfind as th prcntag of rcovrd losss in th last priod. Th logic bhind this dfinition follows that th rcovrd losss from th rinsurr in th last priod has an impact on th insurr s incntiv to purchas rinsuranc nxt priod. Th mor th insurr rcovrs form th rinsuranc company, th highr incntiv to purchas rinsuranc. Manwhil, th insurr may not xrt mor ffort to control its risk than it would hav othrwis. Th hypothsis with rspct to moral hazard is statd as follows: Hypothsis : Othr things bing qual, a highr prcntag of rcovrd losss in th prvious priod will b associatd with highr rinsuranc purchas. To simplify calculation, w assum that advrs slction and moral hazard xist indpndnt of ach othr. Howvr, w hav also found that in most cass thy can b corrlatd. It is rasonabl to xpct that a primary insurr, who concals unfavorabl risk information and buys rinsuranc undr ths fals prtnss, may pos srious moral hazard to th rinsurr. In cass whr ths two factors do corrlat, any stimats mad undr th 7

29 assumption of indpndnc will b biasd. In cas of a positiv corrlation, th stimats for th ffcts of advrs slction and moral hazard would b highr than thy should hav bn othrwis, whil th stimats would b lowr than thy should hav bn othrwis in th cas of ngativ corrlation. 4. Estimatd Equations Following th hypothsis abov, th stimatd quation is statd as: REINS i, t L P α γ X + u R R K i, t i, t D = + βrati, t + βlvi, t + β3 + β LR D 4 + β 0 R 5 i, t + Li, t Li, t j= j i, j, t i, t Whr REINS i, t = Rinsuranc purchas for th primary insurr i in yart ; RAT i, t = A. M. Bst s rating for th primary insurr i in yart ; LV, = Loss volatility of th primary insurr i in yart ; i t L L R i, t D i, t = Prcntag of rcovrd loss out of th total dirct loss for primary insurr i in yar t ; P L R i, t R i, t =Proxy for th rinsuranc pric in which P R i, t is th cdd rinsuranc prmium and R Li t, is th rcovrd loss for th primary insurr i in yar t ; LR, =Loss ratio dfind as D i t L D i, t D i, t DPW in which L D i, t is th dirct loss and DPW, D i t is dirct writtn X i j, t prmium for th primary insurr i in yart ;, = Th jth control variabl for th primary insurr i in yar t. A st of control variabls includ log of total assts, liquidity, lvrag, rturn on quity, dummy variabl for a stock company, product Hrfindahl indx, gographic Hrfindahl indx, prcnt of 8

30 businss lins with long tail liabilitis 3, rinsuranc sustainability indx, ffctiv tax rat, prcntag of homownr writtn prmium in coastal stats 4, and masur of intrnal rinsuranc; u i, t = rror trm in quation for th primary insurr i in yart. Equation is th stimation of advrs slction with th incorporation of th ffct of moral hazard. Th indpndnt variabl RAT i, t rprsnts th financial strngth of th primary insurr, whrby th highr rating indicats strongr financial ability 5. Intuitivly, th mor vulnrabl primary insurr with lowr A.M. Bst rating is mor likly to purchas rinsuranc to protct against futur possibl advrs vnts. As a rsult, th stimatd cofficint sign of RAT i, t is xpctd to b ngativ with th prsnc of advrs slction aftr controlling for additional moral hazard. Anothr variabl for controlling advrs slction is LV, i t which capturs th loss volatility of th primary insurr. It is calculatd as th diffrnc of th losss incurrd ovr th two yars dividd by th dirct prmiums writtn. Compard to A. M. Bst ratings, this variabl mainly rvals th loss xprinc of th company and its risk typ in insuranc opration. Highr loss volatility mans this company is mor risky compard to th ovrall proprty and liability markt. Thrfor, th stimatd cofficint of b positiv in th prsnc of advrs slction. LV i, t is xpctd to 3 W follow th dfinition of long tail lins by Phillips, Cummins and Alln 998 and Garvn and Grac 007 and adopt th sam dfinition as wll. Long tail lins includ Farmownrs Multipl Pril, Homownrs Multipl Pril, Commrcial Multipl Pril, Ocan Marin, Mdical Malpractic, Intrnational, Rinsuranc, Workrs Compnsation, Othr Liability, Products Liability, Aircraft, Boilr and Machinry and Automobil Liability. 4 Th inclusion of prcntag of writtn prmiums in th coastal aras rflcts th significant impact of hurrican risks on th homownr insuranc markt. Furthr, rinsuranc plays an indispnsabl rol in th proprty insuranc markt in th coastal stats. 5 Th construction of variabl RAT i, t is xplaind in dtail latr in this sction. 9

31 Th prcntag of rcovrd losss from th last priod rflcts th impact of moral R Li, t hazard on th rinsuranc dmand. Th stimatd cofficint of D L with th prsnc of moral hazard. 4.3 Economtric Issus i, t is xpctd to b positiv Fixd Effct vrsus Random Effct: Th individual ffct can b controlld using fixd ffct or random ffct approachs. A fixd ffct modl assums that th individual ffct is corrlatd with th indpndnt variabls in th modl, whil a random ffct modl assums that thr is no corrlation btwn th individual ffct and th indpndnt variabls. Hausman 978 proposs a tst to chck a mor fficint modl against a lss fficint, but consistnt, modl. Undr th null hypothsis, both fixd ffct and random ffct stimats ar consistnt, but a random ffct stimat is mor fficint; whras, undr th altrnativ hypothsis, th fixd ffct stimat is consistnt, but th random ffct stimat is not consistnt. In this papr th Hausman tst shows that fixd ffct modl is appropriat for affiliatd, non-affiliatd and all companis togthr. Endognous Variabl: With th prsnc of moral hazard, th rinsuranc covrag may mak insurr tak lss prcaution controlling risks, which lads to highr incurrd losss. Hnc th right-hand sid xplanatory variabl of LR i, t is ndognous. It is corrlatd with th rror trm of th quation. To corrct th ndognity, th first stag stimation quation 3 is usd: LR D D i, t = α 0 + βreinsi, t + βreinsi, t + β3lri, t + β 4 ln DPW i, t + ε i, t 3 REINS =On lag of rinsuranc purchas for th primary insurr i in yar t ; i, t ε i,t =rror trm in quation 3 for th primary insurr i in yart. 30

32 From Wooldridg 00, th OLS stimators will b biasd if th ndognous variabls ar includd in th stimatd modl. To conduct an ndognity tst, a st of suitabl instrumnt variabls IV hraftr is ndd for this potntial ndognous variabl. Th rgrssion-basd approach introducd by Wooldridg 00 is applid. An appropriat IV nds to b corrlatd to th ndognous variabl and uncorrlatd with th rror trm in th modl. Intuitivly, th dirct loss is positivly rlatd to th dirct writtn prmium by th primary insurrs, and th dirct writtn prmium can srv as an IV pr s. Thrfor, log of dirct writtn prmium is usd as on IV for loss incurrd. In addition, on and two lags of rinsuranc purchas ar includd in th modl as on instrumntal variabl. This inclusion can b usd to tst its ffct on th concurrnt losss incurrd which may aris du to moral hazard with th rinsuranc covrag. Th rducd form of dirct incurrd loss is stimatd by using all th indpndnt variabls in th stimation and four IVs as th indpndnt variabls. Aftr th rsidual of this stimat is obtaind, th dpndnt variabl, th rinsuranc purchas in th quation, is rgrssd on all th indpndnt variabls and th obtaind rsidual, as wll. Th insignificant robust t-statistic of stimatd cofficint for th rror trm indicats that th dirct incurrd loss is not an ndognous variabl in th stimation and th corrsponding rsults ar unbiasd. Th corrsponding p-valu is 0.00 which implis that th variabl of concurrnt loss incurrd is ndognous in th stimation quations, and th OLS stimators ar biasd. W nd to apply IVs to fix th ndognity issu. In addition, quation 3 partly rflcts th potntial of moral hazard on th part of th primary insurr. With th prsnc of moral hazard, th highr lvl of rinsuranc purchas in th prvious priod will b associatd with th highr lvl of concurrnt dirct loss for a 3

33 primary insurr if othr firm charactristics ar controlld. Hnc, th stimatd cofficint of lag of rinsuranc purchas is xpctd to b positiv if moral hazard dos xist in th rinsuranc markt. Htroskdasticity: If th rror trms do not hav constant varianc with ach obsrvation, th htroskdasticity problm ariss. In this cas, th OLS stimators ar unbiasd and consistnt but infficint bcaus th assumption of th constant varianc for rror trms is violatd. In th prsnc of htoroskdasticity, th varianc of th cofficints obtaind from OLS tnds to b undrstimatd, so th OLS standard rror is not valid for constructing confidnc intrvals and t statistics. To solv this problm, Wightd Last Squar WLS stimators or robust standard rrors ar usually adoptd to improv fficincy. In th stimation, th Whit tst is mployd to dtct th possibl htroskdasticity problm. Th Whit tst statistics is 6.4 and corrsponding p-valu is This rsult rjcts th null hypothsis that th rsiduals in th modl ar homoskdasticity. Thrfor, th htroskdasticity issu occurs whn stimating th modl, and th stimators ar unbiasd and consistnt but infficint. In addition, th normal standard rrors ar invalid to construct th confidnc intrvals and th t -statistics. Thrfor, th robust standard rrors ar usd instad to improv th stimator fficincy in th prsnc of htroskdasticity. Individual Effct vrsus Poold OLS: Th rror trm u i, t in quation can b dcomposd as u i, t ai + ν i, t =, whr a i is calld individual ffct, ν i, t is idiosyncratic rror and u i, t is composit rror. Th individual ffct is usually unobsrvabl. If th unobsrvd individual ffct is corrlatd with othr indpndnt variabls in th modl, th poold OLS stimators ar biasd and inconsistnt. If th individual ffct is a random variabl and is uncorrlatd with othr indpndnt variabls, th poold OLS stimator is unbiasd and consistnt but infficint. 3

34 As a rsult, th prsnc of th individual ffct to choos th appropriat stimation mthod nds to b tstd. Brusch and Pagan 979 driv th Lagrang Multiplir LM tst to dtct th prsnc of individual ffct. Basd on th rsiduals from th quation, th LM tst statistics is 57.6, which rjct th null hypothsis of th absnc of individual ffct. In th prsnc of individual ffct, th poold OLS stimation is not appropriat for our modl. Ovridntifying Tst: To tst th modl idntification, Andrson Canon and Cragg- Donald tsts ar undrtakn by using STATA cod of xtivrg. Th small p-valu of ths tsts shows th modl proposd is idntifid. 4.4 Data Dscription and Variabls Construction A panl data st rprsnting th proprty and liability rinsuranc markt in th Unitd Stats from 99 to 006 is constructd to tst th hypothss. Th data includs th rinsuranc prmium, dirct loss, financial strngth ratings and othr firm charactristics of th primary insurrs. Th data ar collctd from NAIC annual statmnts and A.M. Bst Company for th corrsponding yars. Each insuranc company is rquird to rport its undrwriting businss, claims, profitability, rsrvs and othr rquird oprational and financial information to th stat commissionr vry yar, so th NAIC annual statmnts compris an xtnsiv and rliabl rsourc for th study of th insuranc and rinsuranc markt in th Unitd Stats. A.M. Bst Company is a privat rating agncy and, accordingly, th A.M. Bst rating is an indpndnt opinion on th company s ovrall financial strngth. Th ratings ar valuatd quantitativly and qualitativly basd on th company s balanc sht, oprating prformanc and othr businss information. In th contxt of insuranc industry, a company which is assignd a highr rating is blivd by invstors to hav nough financial rsourcs and xprtis to dal with th risks it is facing, including undrwriting risk, oprational risk and dfault risk. Thrfor, th ratings can 33

35 b indicators of risk status of primary insurrs. A.M. Bst ratings ar an indicator of financial strngth of companis, and th highr th rating, th strongr financial ability of th company 6. Insuranc companis can b catgorizd as affiliatd and non-affiliatd, which apply quit diffrnt risk managmnt stratgis du to thir financial structurs. For xampl, affiliatd insurrs can divrsify thir risks through th us of both xtrnal and intrnal rinsuranc within th group. Non-affiliatd insurrs only buy rinsuranc from othr outsid rinsurrs. Th data on affiliatd, non-affiliatd insurrs ar collctd sparatly. Tabl 3 and Tabl 5 list th dscriptiv statistics for th affiliatd, non-affiliatd and all proprty and liability insurrs from 990 to 006, rspctivly. Construction of Dpndnt Variabl Prvious studis apply diffrnt dfinitions for th rinsuranc variabl. For xampl, Mayrs and Smith 990, Garvn and Lanmm-Tnant 003 and Col and McCullough 006 us th following construction to masur th rinsuranc purchas: Intrnal & Extrnal cdd rinsuranc Rinsuranc = Dirct prmium writtn + int rnal + xtrnal assumd rinsuranc whr intrnal cdd rinsuranc rfrs to th intrcompany pooling or non-pool rinsuranc within affiliations. Garvn and Grac 007 us anothr ratio to dfin th rinsuranc purchas: Extrnal cdd rinsuranc xtrnal assumd rinsuranc Rinsuranc = Dirct prmium writtn + int rnal + xtrnal assumd rinsuranc Thy tstd advrs slction in th rinsuranc markt with th mphasis on unaffiliatd insuranc companis. Th numrator of th ratio is th nt cdd rinsuranc by th primary 6 For mor dtails on A.M. Bst rating, s 34

36 insurr. Thrfor, this crats a continuous variabl ranging from - to +. A ngativ rinsuranc purchas mans that this primary insurr actually acts as a rinsurr in th markt. Evn though Garvn and Grac 007 spcifically tstd advrs slction for th nonaffiliats in th rinsuranc markt and obtaind supporting vidnc in lin with th thortical prdictions, w ar still intrstd in how th rsults will chang if w considr th affiliation issu. To tst th simultanous ffcts of advrs slction and moral hazard in th rinsuranc markt, mpirical studis for affiliation and non-affiliats ar prformd, rspctivly. For affiliats, th rinsuranc purchas is dfind as: Intrnal cdd rinsuranc Pr mium REINS = Dirct prmium writtn + total assumd rinsuranc For non-affiliats, th rinsuranc purchas is dfind as: Extrnal cdd rinsuranc Pr mium REINS = Dirct prmium writtn + total assumd rinsuranc Construction of Indpndnt Variabls and Control Variabls A.M. Bst Rating: Th variabl of RAT, is constructd from th A.M. Bst financial i j strngth ratings as discussd bfor. Tabl lists A.M. Bst rating scals and associatd dscriptions. Mayr and Smith 990 transfr th lttr scals to numrical scals from 0 to 6, whil Dohrty and Phillips 00 convrt th various A.M. Bst financial strngth ratings to numrical scors ranging from 0 to 4. If th firm is ratd A++ or A+, it is assignd a scor of 4, 3 if th firm is ratd A, if it is ratd A-, if it is ratd B++ or B+, and 0 if it is ratd B and lowr. Bcaus this ssay attmpts to xamin th ffct of advrs slction on th rinsuranc purchas by diffrnt primary insurrs with diffrnt risk lvls, it is mor appropriat to brak ths ratings into dtaild subgroups to dscrib th risk typ of primary insurrs. Consquntly th sam approach by Mayr and Smith 990 is adoptd in this ssay. Accordingly, svn sub- 35

37 groups ar cratd from th lttr scals. If th firm is ratd A++ or A+, it is assignd 6; 5 if th firm is ratd A or A-; 4 if it is ratd B++ or B+; 3 if it is ratd B or B-; if it is ratd C++ or C+; if it is ratd C or C-, and 0 if it is ratd D and lowr. Tabl tabulats th transformd numrical scals and th associatd lttr scals. Loss Volatility: Two masurs of loss volatility ar applid: Loss volatility can b dfind as th diffrnc btwn th currnt losss incurrd and th prvious yar s losss incurrd, dividd by th currnt writtn prmiums, an approach proposd by Li and Schmit 008; To allow for volatility ovr a long tim priod, th scond masur of loss volatility is calculatd as th diffrnc btwn concurrnt losss incurrd and th avrag losss incurrd ovr th last thr yars, dividd by th currnt dirct writtn prmiums. Th ffcts of both loss volatility masurs on th dmand for rinsuranc ar tstd and compard. Th highr loss volatility indicats a mor risky opration of th insuranc company. Togthr with th A.M. Bst financial ratings, loss volatility is usd to rval th insurr s tru risk typ, furthr confirming th prsnc of advrs slction. Prcntag of Rcovrd Losss in th Prior Priod: As th signal of moral hazard, this variabl is constructd as th prcntag of rcovrd loss from th rinsuranc out of th total losss incurrd from th last yar. D Li, t Loss Ratio: Th variabl is calculatd as DPWi D, t. Th rinsuranc purchas is rlatd to th dirct gross loss, L D i, t by th primary insurr. Th sign of th cofficint of loss ratio is xpctd to b positiv, which mans that a gratr dirct gross loss will induc incrasd rinsuranc purchas. 36

38 Rinsuranc Pric in Prior Priod: This variabl is computd as rinsuranc prmium dividd by th rcovrd loss. Th highr th rinsuranc prmium, th lowr th amount of rinsuranc dmandd. Rinsuranc Purchas in th Prior Priod: This variabl is rprsntd as REINS. In i t practic, th rinsuranc usually involvs a long-trm contract to allow for th collction of nw information ovr tim to monitor th primary insuranc companis. In th prsnc of moral hazard, th incrasd purchas of rinsuranc in th prvious priod may rduc th managrial incntivs of th primary insuranc company to control risks, and incras th dirct incurrd loss in th nxt yar. Siz: Th Log of th firm s total assts is includd to control th siz factor of a company. Firms with big siz ar assumd to b mor financially capabl and xpctd to dmand lss xtrnal rinsuranc accordingly. Organization Typ: To control for th ffct of th organization typ on th dmand for rinsuranc, a dummy variabl for a stock company is includd. If th insurr is a stock company, th dummy is qual to ; othrwis it is qual to 0. Diffrnt organization typs affct th risk divrsification of th companis. For xampl, a public tradd firm is abl to sprad its oprating risks across its numrous stockholdrs, whil a mutual company has only limitd rsourcs to dal with its risks. It follows that rinsuranc is in highr dmand for mutual companis than for stock companis whn divrsifying risks fficintly. Liquidity: Liquidity of a primary insuranc company masurs its capacity to sttl claims in a timly mannr. Lowr liquidity implis mor dmand for rinsuranc is ndd to rliv tight financial constraints., 37

39 Lvrag: Lvrag dscribs how much dbt is includd in th total assts. A highr lvrag ratio mans a highr dpndnc on th dbt out of th total assts. A firm with highr lvrag is xpctd to dmand mor rinsuranc sinc it nd th xtrnal rsourcs to boost its undrwriting capabilitis. Rturn on Equity: Th rturn on th quity masurs how much rturn a primary insuranc company arns on its quity. A ngativ rlation btwn th rturn on quity and rinsuranc dmand is xpctd bcaus a profitabl firm is abl to handl thir risks mor asily without much rinsuranc covrag. Product Hrfindahl indx: This variabl is usd to captur th product divrsity of an n DPWl insuranc company. Product Hrfindahl indx is dfind as, whr DPWl dnots TDPW th dirct prmiums writtn from businss lin l and TDPW is th total dirct prmiums writtn for an insuranc company. Th smallr th indx, th mor divrsifid th businss lins of th company. An indx of mans this company has no divrsification in its products, with all its businss in on lin. Gographic Hrfindahl indx: This variabl capturs th gographic divrsification of an 50 DPWs insuranc company s oprations. Th Gographic Hrfindahl indx is dfind as TDPW whr DPW s is th dirct prmiums writtn in stat s and TDPW is th total dirct prmiums writtn for an insuranc company. Th smallr th indx, th mor gographically divrsifid th company. An indx of mans this company has no divrsification in its businss locations, concntrating all its businss on on stat. l= s=, 38

40 Prcntag of long tail businss lins: From th prvious litratur for xampl, Garvn & Grac, 007, w larn that th xistnc of long tail businss lins incrass a primary insurr s dmand for rinisuranc. In this ssay, this variabl is includd as on of th control variabls usd to prdict th rinsuranc dmand. Prcntag of dirct writtn prmiums in coastal aras: Th catastrophic risk xposurs and insuranc covrag in th coastal aras pos svr challngs to th opration of insurrs. Rinsuranc is highly dmandd for th insurrs who undrwrit such hurrican risks in th coastal stats to combat th trmndous losss. Thrfor th prcntags of dirct writtn prmiums in coastal stats, such as Florida, Txas, Alabama, Louisiana, North Carolina, South Carolina and Mississippi, ar includd to b xplanatory variabls in th modl. Masur of Intrnal Rinsuranc: Th variabl of Intrnal is dfind as Intrnal = int rnal cdd rinsuranc int rnal assumd rinsuranc as in Garvn and Grac xtrnal cdd rinsuranc xtrnal assumd rinsuranc 007. This ratio is th prcntag of th nt intrnal cdd rinsuranc out of th nt xtrnal cdd rinsuranc. It is xpctd that th highr th ratio, th lss th dmand for xtrnal rinsuranc. Intrnal rinsuranc is not availabl to non-affiliatd insurrs, as discussd arlir. Contract Sustainability: Th contract sustainability, which dpicts how frquntly insurrs chang rinsurrs, rflcts an important fatur of a long-trm rinsuranc contract. Garvn and Grac 007 showd that this variabl is positivly associatd with th xtrnal rinsuranc purchas. Th variabl is dfind as th prcntag of prmiums cdd ovr a thryar priod to xtrnal rinsurrs which ar prsnt in all thr yars. In th analysis, fiftn thr-yar windows ar considrd: , , , tc. Hnc valu of sustainability of 99 is basd on windows. 39

41 Effctiv Tax Rat: To control th ffct of tax on th rinsuranc dmand, th variabl of NIi, t ffctiv tax rat is constructd as, whr NI is aftr-tax nt incom and BTNI is BTNI i, t bfor-tax nt incom. 4.5 Estimation Rsults Primary insurrs in th rinsuranc markt ar catgorizd into affiliatd and nonaffiliatd companis. Bcaus of thir diffrnt managrial structurs, affiliatd and nonaffiliatd insurrs tnd to us rinsuranc as a risk managmnt tool at diffrnt ways. For affiliatd insurrs, in addition to any rinsuranc thy may purchas from othr non-affiliatd insurrs, thy can cd part of thir risk to th othr companis in th group with which thy ar affiliatd. In this scnario, rinsurrs from th sam group possss or hav accss to mor information about th cding companis, and thus hav mor control ovr th risk managmnt procss. Consquntly, w would xpct th natur of th information problm btwn affiliatd insurrs and rinsurrs to b diffrnt from that btwn non-affiliatd insurrs and rinsurrs. Empirical analysis is undrtakn at two lvls. First, th dmands for total rinsuranc for affiliatd and non-affiliatd insurrs ar tstd rspctivly, in which two masurs of loss volatility ar usd altrnativly to tst th robustnss of th modl. Scond, th rinsuranc purchass for affiliats ar analyzd individually to s if thr is any diffrnt information problm. Furthr, dpnding on how much rinsuranc is bought from affiliatd rinsurrs, th data ar dividd into thr subgroups and rinsuranc dmand of affiliatd insurrs is xamind in dtail Empirical Rsults for Affiliatd Proprty and Liability Insurrs Advrs Slction 40

42 First, th total rinsuranc dmand for affiliatd insurrs is analyzd. Hypothsis suggsts a ngativ rlationship btwn A.M. Bst ratings and th xtrnal rinsuranc purchas. Th rgrssion rsults with two dfinitions of loss volatility ar summarizd in Tabl 6 and Tabl 7, rspctivly. Th fixd ffct modl rsults show that th A.M. Bst ratings hav a significant and ngativ ffct on th purchas of xtrnal rinsuranc at % significanc lvl as rportd in Tabl 6A and 7A. This ngativ association with th rinsuranc purchas is robust to th diffrnt loss volatility masurs. In this cas, th A.M. Bst rating srvs as an ordinal indx. Th magnitud of this cofficint is -0.03, which only implis th highr th rating, th lowr th xtrnal rinsuranc purchas all ls bing qual, sinc A. M. Bst rating is an ordinal indx. Th rsults show that nithr of th cofficints of loss volatility masurs is statistically significant. Th ngativ cofficint of th A.M. Bst rating supports Hypothsis which stats that thr is advrs slction in th rinsuranc transaction. Th cofficints for th loss ratio in two cass ar significantly positiv, implying that th insurrs with highr loss ratio purchas mor total rinsuranc. Howvr, th findings suggst that advrs slction xists in rinsuranc transactions initiatd by affiliatd insurrs, which runs countr to th common xpctation or spculation. Affiliatd insurrs ar xpctd to suffr fwr information problms bcaus thy hav th opportunity to buy rinsuranc within th sam group. Th rasoning would b that, with mor information availabl, advrs slction could disappar btwn th affiliatd insurrs and rinsurrs. So, to undrstand this mor accuratly, I dcompos th total rinsuranc purchass into purchass from affiliatd rinsurrs and purchass from non-affiliatd rinsurrs, and thn prformd a dtaild analysis. Tabl 8 lists th rgrssion rsults of rinsuranc dmand of th affiliatd insurrs from affiliatd, non-affiliatd and all rinsurrs. Th column undr th titl of affiliatd rinsurrs 4

43 includs th ffcts of all th indpndnt variabls on th rinsuranc purchasd from affiliatd rinsurrs. Th column in th middl shows th ffcts on rinsuranc purchass from outsid non-affiliatd rinsurrs and th ffcts on th total rinsuranc dmand ar listd in th last column. Th loss volatility dfinition two is usd in this scnario. Th rsults show that A.M Bst ratings ar not statistically significant in xplaining rinsuranc purchass btwn th affiliatd insurrs and rinsurrs. On th contrary, for non-affiliatd insurrs and rinsurrs, A.M. Bst ratings ar shown to b significantly and ngativly rlatd to th rinsuranc dmand of Th findings suggst that th insurrs with lowr A.M. Bst ratings would lik to sk mor rinsuranc from th rinsurrs outsid of thir group. Loss volatility, anothr indicator for advrs slction, prsnts opposit ffcts for affiliatd and non-affiliatd rinsurrs. Whn th insurrs and rinsurrs ar affiliatd in on group, th stimatd cofficint of th loss volatility is , implying that prcnt incras of loss volatility is associatd with 3.8 prcnt dcras of rinsuranc dmand from its own financial group. Whn considring rinsuranc from outsid of th group, th cofficint of loss volatility is stimatd to b 0.03, which suggsts that prcnt incras of loss volatility is associatd with 3. prcnt incras of rinsuranc dmand from th affiliatd rinsurrs. Thrfor, th vidncs abov suggst that advrs slction problm xists btwn affiliatd insurrs and non-affiliatd rinsurrs as xpctd, and is not found btwn affiliatd insurrs and rinsurrs within a financial group. Som affiliatd insurrs choos to transfr most of thir risks to thir affiliatd companis within thir group, but othr affiliatd insurrs may cd most prmiums to non-affiliatd rinsurrs. Consquntly, an information problm may b prsnt in diffrnt ways for thos affiliatd insurrs. According to th prcntag of cdd prmiums paid to affiliatd rinsurrs, thr subgroups ar cratd. Tabl 9A summaris th rgrssion rsults for affiliatd insurrs 4

44 with mor than 75 prcnt cdd prmiums paid to affiliatd rinsurs; Tabl 9B lists th rsults with mor than 50 prcnt cdd prmiums paid to affiliatd rinsurrs; Tabl 9C summarizs th rsults with lss than 0 prcnt cdd prmiums paid to affiliatd rinsurrs. For th affiliatd insurrs which transfr most of thir risks to thir affiliatd mmbrs, an advrs slction problm is prsntd with th significantly ngativ cofficint of A.M. Bst ratings and th positiv cofficint of loss volatility s Tabl 9A. For th affiliatd insurrs which mostly buy rinsuranc from non-affiliatd companis, thr is no vidnc showing th xistnc of advrs slction s Tabl 9C. This comparison indicats that information asymmtry is still a problm vn within a singl group, spcially whn affiliatd insurrs cd most of thir prmiums to thir affiliatd rinsurrs. In summary, thr is supporting vidnc of th prsnc of advrs slction btwn affiliatd insurrs and non-affiliatd rinsurrs. Nvrthlss, whn affiliatd insurrs purchas most of thir rinsuranc from thir affiliatd rinsurrs, thr is still an advrs slction problm. Moral Hazard Rcall Hypothsis stats that th prcnt of rcovrd losss in th prvious yar is positivly associatd with th rinsuranc purchas with th prsnc of moral hazard. From Tabl 6A w can s that th stimatd cofficint of th prcnt of rcovrd losss in th prvious priod is significantly positiv. Th cofficint of 0.09 implis that prcnt incras of prcnt of rcovrd losss from th last priod is associatd with around 0. prcnt incras in rinsuranc dmand. With th changd masur of loss volatility, th prcntag of rcovrd losss in th prior priod is no longr statistically significant as shown in Tabl 7A. In th first stag stimation, th stimatd cofficint for th on and two lag of rinsuranc purchas ar 43

45 significantly positiv to th loss ratio, which mans th highr th rinsuranc purchas of prvious yars th highr th loss ratio in th currnt priod. Whn affiliatd insurrs cd prmiums to non-affiliatd rinsurrs, th stimatd cofficints of th prcnt of rcovrd loss in th last yar is 0.44, which is statistically significant at prcnt lvl, as shown in Tabl 8. Ovrall, it is not clar if thr is a moral hazard problm for affiliatd insurrs basd on ths mixd rsults. Tabl 9A, 9B, and 9C list rgrssion rsults for affiliatd insurrs in thr subgroups. Th stimatd cofficints of lag of rcovrd losss ar not significantly positiv in ths cass, which dos not support th hypothsis of th xistnc of moral hazard for affiliatd insurrs. In summary, thr is no consistnt supporting vidnc of th xistnc of moral hazard for affiliatd insurrs. On possibl xplanation could b that affiliatd insurrs still manag thir risks ffctivly and diligntly vn aftr transfrring part of thir risks to affiliatd rinsurrs, bcaus thy hav consistnt intrst within a financial group. Estimation of Othr Control Variabls Rinsuranc-spcific factors, sustainability indx, th rinsuranc pric in th last priod and intrnal rinsuranc prcntag, hav diffrnt ffcts on th dmand for rinsuranc. As prdictd, th prcntag of intrnal rinsuranc is ngativly and significantly corrlatd to th dmand for xtrnal rinsuranc. Affiliatd insurrs will dmand lss xtrnal rinsuranc onc thy tak part in an intrnal insuranc risk managmnt pool or othr similar arrangmnts. Surprisingly, th stimatd cofficint for rinsuranc pric is significantly positiv. On possibl xplanation could b that th affiliatd insurr rtains th good risks for its own group, and purposly cds th bad risks to xtrnal rinsurrs with lss considration of pric. Howvr, th rinsuranc sustainability indx has no significant ffct on th dmand for 44

46 rinsuranc, which also can b attributd to th dpndnc on th intrnal rinsuranc arrangmnts among th group. Othr firm-spcific factors also hav ffcts on th dmand for th affiliatd insurrs. Th stimatd cofficints of loss ratio and lvrag ar significantly positiv as xpctd. Highr loss and highr lvrag ncourag th insurr to buy mor rinsuranc to divrsify risks and stabiliz businss prformanc. As xpctd, log of total assts and th gographic Hrfindahl indx ar ngativly rlatd to th dmand for rinsuranc. Strongr financial capability and gographical divrsification incras th insurrs own ability to control risks, rducing th dmand for xtrnal rinsuranc covrag. Intrstingly, th stimatd cofficints of th prcntag of homownr writtn prmiums in Alabama, Louisiana, North Carolina, South Carolina and Mississippi ar significantly ngativ, whil th stimatd cofficints for stats of Florida and Txas ar insignificant Empirical Rsults for Non-Affiliatd Proprty and Liability Insurrs Th rgrssion rsults for non-affiliatd insurrs ar prsntd in th middl column in Tabl 6A and 7A. Rcall that Hypothsis stats that th lowr A.M. Bst ratings ar associatd with highr rinsuranc dmand with th prsnc of advrs slction. Th loss volatility is xpctd to b positivly rlatd to th rinsuranc purchas to divrsify insurrs risks. From Tabl 6A, w can s that th stimatd cofficint for th A.M. Bst rating is significantly positiv, which implis that th insurrs with highr ratings purchas mor rinsuranc. Th stimatd cofficint of loss volatility is significantly ngativ. This vidnc shows that mor stabl non-affiliatd insurrs with bttr ratings ar associatd with th highr dmand for rinsuranc, which rjcts th null hypothsis of xistnc of advrs slction for non-affiliatd insurrs. 45

47 In trms of moral hazard, th mixd rsults ar prsntd in Tabl 6A and 7A whn two loss volatility masurs ar usd altrnativly. Th stimatd cofficint of th prcntag of th rcovrd losss out of th total losss incurrd is not statistically significant in Tabl 6A, whil it is significantly positiv of whn scond loss volatility dfinition is applid in Tabl 7A. Taking th rlation of loss ratio and th rinsuranc purchas in th last priod in th first stag xamination, th rlationship is not significantly positiv. Ovrall, no consistnt supporting vidnc is found on th xistnc of advrs slction or moral hazard for th non-affiliatd insurrs in th proprty and liability rinsuranc markt. Th rgrssion rsults also show that rinsuranc sustainability indx, loss ratio, lvrag, liquidity and prcntag of homownr-writtn prmiums in Florida ar positivly rlatd to th purchas of rinsuranc. As tstd in Garvn and Grac 007, th long-trm rinsuranc rlationship is rlatd to th highr purchas of rinsuranc, and th positiv cofficint stimation of sustainability indx is consistnt with thir findings. As xpctd, th non-affiliatd insurr with highr lvrag purchass mor rinsuranc. Bsids, th product Hrfindahl indx and gographic Hrfindahl indx ar ngativly rlatd to th rinsuranc dmand, which is consistnt with th rsults by Garvn and Grac 007. Onc insurrs hav divrsifid thir risks in product lins and gographic distributions, th nd for rinsuranc is dcrasd. Sinc homownr insuranc in th Florida markt facs hug catastrophic hurrican risks, insurrs in this markt dmand mor rinsuranc. Th stimatd cofficint of th prcntag of homownr-writtn prmiums in Florida in th rgrssion quation is significantly positiv, which indicats that th undrwriting of homownr insuranc in Florida incrass th dmand for rinsuranc for th non-affiliatd insurrs. This rsult is opposit to th findings for th affiliatd insurrs in th coastal stats, which indicats th businss lin of homownr insuranc 46

48 is insignificant or is significantly ngativ to th rinsuranc purchas. From this comparison w could infr that affiliatd and non-affiliatd insurrs apply rinsuranc in diffrnt ways to divrsify catastrophic hurrican risks. Th non-affiliatd insurrs prsnt a strong dmand for xtrnal rinsuranc for thir homownr insuranc businss in th high risk aras, whil th affiliatd insurrs may rly on othr financial capabilitis within a group rathr than th xtrnal rinsuranc in this cas Rgrssion Rsults for All Proprty and Liability Insurrs To tst th asymmtric information for th whol rinsuranc markt, th rgrssion is run on th panl data including all th affiliatd and non-affiliatd proprty and liability insurrs from 99 to 006. Thr is no supporting vidnc on th prsnc of advrs slction or moral hazard problm in th rinsuranc markt. From Tabl 6A w can s that th stimatd cofficint of A.M. Bst rating is not statistically significant, whil th loss volatility is shown to b statistically significant and ngativly rlatd to rinsuranc purchas. With th scond loss volatility masur, this variabl prsnts a significantly positiv rlationship to th xtrnal rinsuranc dmand which is shown in Tabl 7A. Ths mixd findings fail to support th null hypothsis of th xistnc of advrs slction in th rinsuranc markt. In trms of moral hazard, th stimatd cofficints for th lag of rcovrd losss ratio is not statistically significant in Tabl 6A and 7A. In th first stag rgrssion, th stimatd cofficints of rinsuranc purchass in th last priod ar in Tabl 6A, which is statistically significant and positiv. This may suggst moral hazard problm ariss bcaus th purchas of rinsuranc in th last priod looss th primary insurrs incntivs to control risks, lading to a highr loss ratio in th currnt priod. Howvr, this finding is not robust to th 47

49 changs of loss volatility masur, and this stimatd cofficint turns out to b insignificant in Tabl 7A. From ths mixd vidnc w may infr that th moral hazard problm dos not prvail in th rinsuranc markt. Among th control variabls includd, loss ratio and lvrag ar positivly rlatd to th dmand for th rinsuranc as xpctd. Product Hrfindahl indx, gographic Hrfindahl indx and prcntag of homownr writtn prmium in Alabama, Louisiana, North Carolina, South Carolina and Mississippi ar ngativly rlatd to rinsuranc dmand, if all insurrs ar considrd. Th rgrssion rsults for all th insurrs in th rinsuranc markt ar mor similar to th rsults for th affiliatd insurrs, whr th affiliatd insurrs account for 40 prcnt of all insurrs. 5. Conclusion As an ffctiv risk managmnt tool, rinsuranc mts th corporat dmand for insuranc by divrsifying risks, obtaining xprtis from th rinsurr, incrasing capacity and lowring taxs. Thus th rinsuranc markt is an important and supplmntary part of th primary insuranc markt. Howvr, th asymmtric information problm may xist btwn th rinsurr and th primary insurr, and such a problm may damag th insuranc markt. Basd on an xtndd thortical modl, this papr mpirically tsts th asymmtric information problm in th proprty and liability insuranc markt by sparating advrs slction from moral hazard. Using th panl data from NAIC and A.M. Bst Company, advrs slction is shown to xist btwn affiliatd insurrs and non-affiliatd rinsurrs. Whn affiliatd insurrs mostly us rinsuranc within thir groups, advrs slction problms aris among thos group mmbrs. For non-affiliatd insurrs, thr is no supporting vidnc found 48

50 on th xistnc of asymmtric information including advrs slction or moral hazard. Ovrall, th rsults provid supporting vidnc of th prsnc of advrs slction and mixd vidnc of moral hazard in th rinsuranc markt. Whil th findings ar consistnt with th rsults of Garvn and Grac 007, a dtaild invstigation is ndd. It is intrsting that th advrs slction dos xist btwn affiliatd insurrs and non-affiliatd rinsurrs, vn in an affiliatd financial group which is contrary to th initial xpctations. Howvr, thr is no advrs slction issu among non-affiliatd insurrs and rinsurrs. Ths phnomna may b xplaind by th long-trm rinsuranc contracts btwn th non-affiliatd insurrs and outsidr rinsurs which rval th risk typ of insurrs ovr tim. For affiliatd insurrs and rinsurrs within a financial group, th lack of such risk dtction for cding companis nvrthlss lad to this asymmtric information problm. On th othr sid, moral hazard problm is not found in th rinsuranc markt no mattr in th affiliatd or non-affiliatd insurrs, which may suggst that rinsurrs control th moral hazard problm by monitoring or loss-snsitiv prmiums. Th rsults imply that mor attntion should b paid to th asymmtric information btwn affiliatd insurrs and rinsurrs within a financial group. 49

51 Rfrncs Abbring, J. H., Hckman, J. J., Chiappori, P. A., & Pinqut, J Advrs Slction and Moral Hazard in Insuranc: Can Dynamic Data Hlp to Distinguish. Journal of th Europan Economic Association, Vol., No. -3, Pags 5-5. Adam, M. B., & Diacon, S. R Tsting for Information Asymmtris in th Unitd Kingdom Markt for Proprty-Liability Rinsuranc. Amrican Risk and Insuranc Association 006 annual mting working papr. Akrlof, G. A Th Markt for Lmons : Quality Uncrtainty and th Markt Mchanism. Quartrly Journal of Economics, 84, Arrow, K. J Aspcts of th Thory of Risk Baring. Yrjo Jahnsson Lcturs, Hlsinki. Rprintd in Essays in th Thory of Risk Baring 97, Chicago: Markham Publishing Co. Arrow, K. J Highr Education as a Filtr. Journal of Public Economics,, Bajari, P., Hong, H., & Khwaja, A Moral Hazard, Advrs Slction and Halth Expnditurs: A Smiparamtric Analysis. NBER working papr. Baptist, E. J. & Santomro, A. M Th Dsign of Privat Rinsuranc Contract. Journal of Financial Intrmdiation, 9, Borch, K. 96. Equilibrium in a Rinsuranc Markt. Economtrica, 30, Brusch, T., & Pagan, A. R A Simpl Tst for Htroscdasticity and Random Cofficint Variation. Economtrica, 475, Chassagnon, A., & Chiappori, P. A Insuranc undr Advrs Slction and Moral Hazard: th Cas of Pur Comptition. Papr prsntd at 3rd confrnc of Gnva Association. 50

52 Chiappori, P. A., & Hckman, J Tsting Moral Hazard on Dynamic Insuranc Data: Thory and Economtric Tsts. Papr prsntd at sminars in UCLA, Yal, Chicago and Northwstrn. Chiappori, P.A., & Salani, B Tsting for Asymmtric Information in Insuranc Markts. Journal of Political Economy, Vol.08, No Fb., 000, Col, C. R., & McCullough, K. A A Rxamination of th Corporat Dmand for Rinsuranc. Journal of Risk and Insuranc, 73, Dionn, G. Eds Handbook of Insuranc. Boston/Dordrcht/London: Kluwr Acadmic Publishr. Dionn, G., Mauric, M., Pinqut, J., & Vanass, C. 00. Th Rol of Mmory in Long-Trm Contracting with Moral Hazard: Empirical Evidnc in Automobil Insuranc. Working papr. Dionn, G., Michaud, P. C., & Dahchour, M Sparating from Moral Hazard from Advrs Slction in Automobil Insuranc: Longitudinal Evidnc from Franc. Working papr Canada Rsarch Chair in Risk Managmnt, HEC Montral. Dohrty, N. A., & Smttrs, K Moral Hazard in Rinsuranc Markts. Journal of Risk and Insuranc, 73, Dohrty, N.A Financial Innovation in th Managmnt of Catastroph Risk. Cntr for Financial Institutions Working Paprs. Dohrty, N.A., & Posy, L. L Availability Criss in Insuranc Markts: Optimal Contracts with Asymmtric Information and Capacity Constraints. Journal of Risk and Uncrtainty, 5,

53 Dohrty, N.A., & Tinic, S. 98. A Not on Rinsuranc undr Conditions of Capital Markt Equilibrium. Journal of Financ, 36, Eckhoudt, L., & Gollir, C Risk: Evaluation, Managmnt and Sharing. Harvstr Whatshaf, Hrtfordshir G. B.. Finklstin, A., & McGarry, K Privat Information and Its Effct on Markt Equilibrium: Nw Evidnc from Long-Trm Car Insuranc. National Burau of Economic Rsarch working papr Finklstin, A., & Potrba, J. 004 Advrs Slction in Insuranc Markts: Policyholdr Evidnc from th U.K. Annuity Markt. Journal of Political Economy,, Garvn, J. R., & Grac, M. F Advrs Slction in Rinsuranc Markt. Papr prsntd at Amrican Risk and Insuranc Association 007 annual mting. Garvn, J. R., & Lamm-Tnnant, J Th Dmand for Rinsuranc: Thory and Empirical Tsts. Insuranc and Risk Managmnt, 7, Grac, M. F., Klin, R. W., & Klindorfr, P. R Homownr Insuranc with Bundld Catastroph Covrag. Journal of Risk and Insuranc, Vol. 7, No.3, Hausman, J.A Spcification Tsts in Economtrics. Economtrrica, 466, 5-7. Holmstrom, B Moral Hazard and Obsrvability. Th Bll Journal of Economics, 0, Jan-Baptist, E. L., & Santomro, A. M Th Dsign of Privat Rinsuranc Contracts. Journal of Financial Intrmdiation, 9, Johnson, R. E., 977. Rinsuranc: Thory, th Nw Applications, and th Futur. Journal of Risk and Insuranc, Vol. 44, No.. Mar., 977,

54 Laffont, J. J., & Tirol, J Comparativ Static of Optimal Dynamic Incntiv Contract. Europan Economic Rviw, 3, Lambrt, R.A Long-trm Contracts and Moral Hazard. Th Bll Journal of Economics, 4, Li, Y., & Schmit, J Factors Influncing th Dmand for Rinsuranc in th Mdical Malpractic Insuranc Markt: A Focus on Organizational Form. Papr prsntd at Amrican Risk and Insuranc Association 008 annual mting. Mayrs, D., & Smith, C. W On th Corporat Dmand for Insuranc: Evidnc from th Rinsuranc Markt, Journal of Businss, 63, Mossin, J Aspcts of Rational Insuranc Purchasing. Journal of Political Economy, 76, Pulz, R., & Snow, A Evidnc on Advrs Slction: Equilibrium Signaling and Crosssubsidization in th Insuranc Markt, Journal of Political Economy, Vol.0, No. Apr., Raviv, A Th Dsign of an Optimal Insuranc Policy, Amrican Economic Rviw, 69, Rily, J. G Comptitiv Signaling. Journal of Economic Thory, 0, Rothschild, M., & Stiglitz, J Equilibrium in Comptitiv Insuranc Markts: An Essay on th Economics of Imprfct Information, Quartrly Journal of Economics, 80, Spnc, M Job Markt Signaling. Th Quartrly Journal of Economics, 873,

55 Tabl A. M. Bst Financial Strngth Rating Catgoris Catgory Associatd Dscription A++, A+ Suprior; A, A- Excllnt; Scur B++, B+ Good B, B- Fair; C++, C+ Marginal; C, C- Wak, D Poor; Vulnrabl E Undr Rgulatory Suprvision; F In Liquidation; S Rating Suspndd Data sourcs: Tabl Constructd Numrical Scals and Associatd Lttr Scals Lttr Scal Numrical Scals A++, A+ Suprior 6 A, A- Excllnt 5 B++, B+ Good 4 B, B- Fair 3 C++, C+ Marginal C, C- Wak D Poor 0 E Undr Rgulatory Suprvision 0 F In Liquidation 0 S Rating Suspndd 0 S Mayr and Smith

56 Tabl 3. Dscriptiv Statistics for th Affiliatd Proprty and Liability Insurrs Variabls Numbr of Obsrvations Man Standard Dviation Minimum Maximum Rinsuranc Purchas 4, A.M.Bst Ratings 4, Loss Volatility Dfinition On 4, Loss Volatility Dfinition Two, Lag of Ratio of Rcovrd Losss 3, Rinsuranc Sustainability Indx 4, Loss Ratio 4, Lag of Rinsuranc Pric 3, Intrnal Rinsuranc Prcntag 4, Log of Total Assts 4, Stock Indicator 4, Rturn on Equity 4, Lvrag 4, Liquidity 4, Effctiv Tax Rat 4, Product Hrfindahl Indx 3, Gorgraphic Hrfindahl Indx 4, Prcntag of Homownr Writtn Prmium in Florida 4, Prcntag of Homownr Writtn Prmium in Txas 4, Prcntag of Homownr Writtn Prmium in AL, LA, MC, NC and MS 4, Prcntag of Long Tail Businss Lins 4, Loss Volatility Dfinition On = L D t - L D t- /DPW t. Loss Volatility Dfinition Two = L D t - L D t- +L D t- +L D t-3 /3/DPW t 55

57 Tabl 4. Dscriptiv Statistics for th Non-Affiliatd Proprty and Liability Insurrs Variabls Numbr of Obsrvations Man Standard Dviation Minimum Maximum Rinsuranc Purchas 5, A.M.Bst Ratings 5, Loss Volatility Dfinition On 5, Loss Volatility Dfinition Two, Lag of Ratio of Rcovrd Losss 4, Rinsuranc Sustainability Indx 5, Loss Ratio 5, Lag of Rinsuranc Pric 4, Intrnal Rinsuranc Prcntag N/A N/A N/A N/A N/A Log of Total Assts 5, Stock Indicator 5, Rturn on Equity 5, Lvrag 5, Liquidity 5, Effctiv Tax Rat 4, Product Hrfindahl Indx 4, Gorgraphic Hrfindahl Indx 5, Prcntag of Homownr Writtn Prmium in Florida 5, Prcntag of Homownr Writtn Prmium in Txas 5, Prcntag of Homownr Writtn Prmium in AL, LA, MC, NC and MS 5, Prcntag of Long Tail Businss Lins 5, Loss Volatility Dfinition On = L t D - L t- D /DPW t. Loss Volatility Dfinition Two = L t D - L t- D +L t- D +L t-3 D /3/DPW t 56

58 Tabl 5. Dscriptiv Statistics for th Proprty and Liability Insurrs Variabls Numbr of Obsrvations Man Standard Dviation Minimum Maximum Rinsuranc Purchas 9, A.M.Bst Ratings 9, Loss Volatility Dfinition On 7, Loss Volatility Dfinition Two 5, Lag of Ratio of Rcovrd Losss 7, Rinsuranc Sustainability Indx 9, Loss Ratio 9, Lag of Rinsuranc Pric 7, Intrnal Rinsuranc Prcntag 9, Log of Total Assts 9, Stock Indicator 9, Rturn on Equity 9, Lvrag 9, Liquidity 9, Effctiv Tax Rat 8, Product Hrfindahl Indx 8, Gorgraphic Hrfindahl Indx 9, Prcntag of Homownr Writtn Prmium in Florida 9, Prcntag of Homownr Writtn Prmium in Txas 9, Prcntag of Homownr Writtn Prmium in AL, LA, MC, NC and MS 9, Affiliation indicator 9, Prcntag of Long Tail Businss Lins 9, Loss Volatility Dfinition On = L D t - L D t- /DPW t. Loss Volatility Dfinition Two = L D t - L D t- +L D t- +L D t-3 /3/DPW t 57

59 Tabl 6A. Estimatd Cofficints on Rinsuranc Purchas for th Proprty and Liability Insurrs Dpndnt Variabl: Rinsuranc Scond Stag Rgrssion Purchas Non- All P/L Variabls Affiliation Affiliation Insurrs A.M.Bst Ratings *** *** Loss Volatility Dfinition On *** *** Lag of Ratio of Rcovrd Losss *** Rinsuranc Sustainability Indx * Loss Ratio *** *** *** Lag of Rinsuranc Pric *** *** Intrnal Rinsuranc Prcntag *** *** Log of Total Assts ** *** *** Stock Indicator Rturn on Equity ** ** Lvrag *** *** *** Liquidity *** Effctiv Tax Rat Product Hrfindahl Indx *** *** Gorgraphic Hrfindahl Indx *** ** *** Prcntag of Homownr Writtn Prmium in Florida * Prcntag of Homownr Writtn Prmium in Txas Prcntag of Homownr Writtn Prmium in AL, LA, NC, SC and MS *** *** Prcntag of Long Tail Businss Lins Affiliation indicator Squar of Log of Total Assts *** *** *** 58

60 Continud First Stag Rgrssion Endognous Variabl: Loss Ratio On Lag of Rinsuranc Purchas *** *** Two Lag of Rinsuranc Purchas ** * On Lag of Loss Ratio *** *** *** On Lag of Log Dirct Prmium Writtn ** *** *** F-stat F409,790 =.75 F540,65 =4.39 F964,4864 =6.4 Obsrvations,36 3,6 5,54 R-squard Fixd ffct modl on panl data is usd for affiliatd, non-affiliatd and all proprty and liability insurrs basd on Hausman tst.. Rgrssion rsults of yar dummis ar not rportd in this tabl. 3. Th rgrsion rsults of othr instrumntal variabls includd in th first stag rgrssion ar not shown in this tabl. 4. Rgrssion rsults ar shown as cofficint and standard dviation. Th figurs on th top ar th stimatd cofficints and th figurs in th parnthsis ar standard dviations. 5. *, ** and *** dnot significanc at 0%, 5% and % lvl rspctivly. Marginal Effcts Masurd at th Mans Variabls Affiliation Log of Total Assts *** Non- Affiliation *** All P/L Insurrs *** 59

61 Tabl 6B. Comparison of Expctd Cofficints Signs and Rgrssion Rsults Variabls Exp. Sign Affi. Sign Non-affi. Sign Signal of Advrs Slction A.M.Bst Ratings Loss Volatility Dfinition On Signal of Moral Hazard Lag of Rcovrd Losss Ratio + + Rinsuranc-spcific Factors Rinsuranc Sustainability Indx + + Lag of Rinsuranc Pric Intrnal Rinsuranc Prcntag Firm-spcific Factors Loss Ratio Log of Total Assts Stock Indicator - Rturn on Equity Lvrag Liquidity - + Effctiv Tax Rat + Product Hrfindahl Indx Gorgraphic Hrfindahl Indx Prcntag of Homownr Writtn Prmium in Florida Prcntag of Homownr Writtn Prmium in Txas Prcntag of Homownr Writtn Prmium in AL, LA, NC, SC and MS Prcntag of Long Tail Businss Lins + Instrumntal Variabls for Loss Ratio On Lag of Rinsuranc Purchas Two Lag of Rinsuranc Purchas On Lag of Loss Ratio On Lag of Log Dirct Prmium Writtn This is th marginal ffct masurd at th man. All P/L Sign 60

62 Tabl 7A. Estimatd Cofficints on Rinsuranc Purchas for th Proprty and Liability Insurrs Dpndnt Variabl: Rinsuranc Scond Stag Rgrssion Purchas Non- All P/L Variabls Affiliation Affiliation Insurrs A.M.Bst Ratings *** ** Loss Volatility Dfinition Two * *** Lag of Ratio of Rcovrd Losss *** Rinsuranc Sustainability Indx * Loss Ratio *** ** Lag of Rinsuranc Pric Intrnal Rinsuranc Prcntag *** *** Log of Total Assts *** *** *** Stock Indicator Rturn on Equity *** ** *** Lvrag ** *** *** Liquidity *** *** *** Effctiv Tax Rat * ** Product Hrfindahl Indx ** *** * Gorgraphic Hrfindahl Indx *** ** *** Prcntag of Homownr Writtn Prmium in Florida Prcntag of Homownr Writtn Prmium in Txas Prcntag of Homownr Writtn Prmium in AL, LA, NC, SC and MS *** *** Prcntag of Long Tail Businss Lins ** Affiliation indicator Squar of Log of Total Assts *** *** *** 6

63 Continud First Stag Rgrssion On Lag of Rinsuranc Purchas * Two Lag of Rinsuranc Purchas On Lag of Loss Ratio *** *** *** On Lag of Log Dirct Prmium Writtn * F-stat F35,363 =.78 F474,0 =5.4 F808,3537 =.9 Obsrvations,749,67 4,38 R-squard Fixd ffct modl on panl data is usd for affiliatd, non-affiliatd and all proprty and liability insurrs basd on Hausman tst.. Rgrssion rsults of yar dummis ar not rportd in this tabl. Endognous Variabl: Loss Ratio 3. Th rgrsion rsults of othr instrumntal variabls includd in th first stag rgrssion ar not shown in this tabl. 4. Rgrssion rsults ar shown as cofficint and standard dviation. Th figurs on th top ar th stimatd cofficints and th figurs in th parnthsis ar standard dviations. 5. *, ** and *** dnot significanc at 0%, 5% and % lvl rspctivly. Marginal Effcts Masurd at th Mans Variabls Affiliation Log of Total Assts *** Non- Affiliation *** All P/L Insurrs *** 6

64 Tabl 7B. Comparison of Expctd Cofficints Signs and Rgrssion Rsults Variabls Exp. Sign Affi. Sign Non-affi. Sign Signal of Advrs Slction A.M.Bst Ratings Loss Volatility Dfinition Two Signal of Moral Hazard Lag of Rcovrd Losss Ratio + + Rinsuranc-spcific Factors Rinsuranc Sustainability Indx + + Lag of Rinsuranc Pric - + Intrnal Rinsuranc Prcntag Firm-spcific Factors Loss Ratio Log of Total Assts +/ Stock Indicator - Rturn on Equity Lvrag Liquidity Effctiv Tax Rat + - Product Hrfindahl Indx Gorgraphic Hrfindahl Indx Prcntag of Homownr Writtn Prmium in Florida + Prcntag of Homownr Writtn Prmium in Txas + Prcntag of Homownr Writtn Prmium in AL, LA, NC, SC and MS Prcntag of Long Tail Businss Lins + Instrumntal Variabls for Loss Ratio On Lag of Rinsuranc Purchas Two Lag of Rinsuranc Purchas + On Lag of Loss Ratio On Lag of Log Dirct Prmium Writtn This is th marginal ffct masurd at th man. All P/L Sign 63

65 Tabl 8. Estimatd Cofficints on Rinsuranc Purchas for th Affiliatd Proprty and Liability Insurrs Scond Stag Rgrssion Dpndnt Variabl: Rinsuranc Purchas Variabls Affiliatd Rinsurrs Non- Affiliatd All Rinsurrs A.M.Bst Ratings *** *** Loss Volatility * ** Lag of Ratio of Rcovrd Losss ** Rinsuranc Sustainability Indx Loss Ratio *** *** Lag of Rinsuranc Pric ** Intrnal Rinsuranc Prcntag *** *** Log of Total Assts *** ** *** Stock Indicator Rturn on Equity *** *** *** Lvrag *** *** ** Liquidity *** *** *** Effctiv Tax Rat * Product Hrfindahl Indx *** ** Gorgraphic Hrfindahl Indx ** *** Prcntag of Homownr Writtn Prmium in Florida Prcntag of Homownr Writtn Prmium in Txas Prcntag of Homownr Writtn Prmium in AL, LA, NC, SC and MS *** Prcntag of Long Tail Businss Lins ** ** Squar of Log of Total Assts *** ** *** 64

66 Continud First Stag Rgrssion On Lag of Rinsuranc Purchas ** Two Lag of Rinsuranc Purchas On Lag of Loss Ratio *** *** *** On Lag of Log Dirct Prmium Writtn F-stat F3,090 =.64 F35,363 =.79 F35,363 =.78 Obsrvations,434,749,749 R-squard Fixd ffct modl is usd for th affiliatd insurrs cd to affiliatd, non-affiliatd and all rinsurrs basd on Hausman tst.. Rgrssion rsults of yar dummis ar not rportd in this tabl. Endognous Variabl: Loss Ratio 3. Th rgrsion rsults of othr instrumntal variabls includd in th first stag rgrssion ar not shown in this tabl. 4. Rgrssion rsults ar shown as cofficint and standard dviation. Th figurs on th top ar th stimatd cofficints and th figurs in th parnthsis ar standard dviations. 5. *, ** and *** dnot significanc at 0%, 5% and % lvl rspctivly. Marginal Effcts Masurd at th Mans Affiliatd Variabls Rinsurrs Log of Total Assts *** Non- Affiliatd ** All Rinsurrs *** 65

67 Tabl 9A. Estimatd Cofficints on Rinsuranc Purchas for th Affiliatd Proprty and Liability Insurrs with Mor than 75% Cdd Prmium Paid to Affiliatd Rinsurrs Scond Stag Rgrssion Dpndnt Variabl: Rinsuranc Purchas Affiliatd Non-Affiliatd All Variabls Rinsurrs Rinsurrs Rinsurrs A.M.Bst Ratings *** *** *** Loss Volatility * * ** Lag of Ratio of Rcovrd Losss *** Rinsuranc Sustainability Indx Loss Ratio ** * ** Lag of Rinsuranc Pric * Intrnal Rinsuranc Prcntag *** *** Log of Total Assts * Stock Indicator Rturn on Equity Lvrag *** Liquidity *** *** *** Effctiv Tax Rat *** ** Product Hrfindahl Indx ** Gorgraphic Hrfindahl Indx ** *** * Prcntag of Homownr Writtn Prmium in Florida Prcntag of Homownr Writtn Prmium in Txas Prcntag of Homownr Writtn Prmium in AL, LA, NC, SC and MS * Prcntag of Long Tail Businss Lins *** * *** Squar of Log of Total Assts

68 Continud First Stag Rgrssion On Lag of Rinsuranc Purchas Two Lag of Rinsuranc Purchas *** On Lag of Loss Ratio *** *** *** On Lag of Log Dirct Prmium Writtn *** ** ** F-stat F60,38 =6.6 F8,548 =3.0 F,555 =.93 Obsrvations R-squard Fixd ffct modl is usd for th affiliatd insurrs cd to affiliatd, non-affiliatd and all rinsurrs basd on Hausman tst.. Rgrssion rsults of yar dummis ar not rportd in this tabl. Endognous Variabl: Loss Ratio 3. Th rgrsion rsults of othr instrumntal variabls includd in th first stag rgrssion ar not shown in this tabl. 4. Rgrssion rsults ar shown as cofficint and standard dviation. Th figurs on th top ar th stimatd cofficints and th figurs in th parnthsis ar standard dviations. 5. *, ** and *** dnot significanc at 0%, 5% and % lvl rspctivly. Marginal Effcts Masurd at th Mans Variabls Affiliation Log of Total Assts * Non- Affiliation All P/L Insurrs

69 Tabl 9B. Estimatd Cofficints on Rinsuranc Purchas for th Affiliatd Proprty and Liability Insurrs with Mor than 50% Cdd Prmium Paid to Affiliatd Rinsurrs Scond Stag Rgrssion Dpndnt Variabl: Rinsuranc Purchas Affiliatd Non-Affiliatd All Variabls Rinsurrs Rinsurrs Rinsurrs A.M.Bst Ratings * *** ** Loss Volatility Lag of Ratio of Rcovrd Losss *** ** *** Rinsuranc Sustainability Indx ** Loss Ratio Lag of Rinsuranc Pric Intrnal Rinsuranc Prcntag *** *** Log of Total Assts *** Stock Indicator Rturn on Equity Lvrag *** ** Liquidity *** ** *** Effctiv Tax Rat ** ** Product Hrfindahl Indx ** Gorgraphic Hrfindahl Indx *** *** Prcntag of Homownr Writtn Prmium in Florida *** *** Prcntag of Homownr Writtn Prmium in Txas Prcntag of Homownr Writtn Prmium in AL, LA, NC, SC and MS Prcntag of Long Tail Businss Lins *** *** Squar of Log of Total Assts *** 68

70 Continud First Stag Rgrssion Endognous Variabl: Loss Ratio On Lag of Rinsuranc Purchas Two Lag of Rinsuranc Purchas On Lag of Loss Ratio *** *** *** On Lag of Log Dirct Prmium Writtn ** F-stat F8,548 =3.0 F,555 =.93 F,555 =.96 Obsrvations R-squard Fixd ffct modl is usd for th affiliatd insurrs cd to affiliatd, non-affiliatd and all rinsurrs basd on Hausman tst.. Rgrssion rsults of yar dummis ar not rportd in this tabl. 3. Th rgrsion rsults of othr instrumntal variabls includd in th first stag rgrssion ar not shown in this tabl. 4. Rgrssion rsults ar shown as cofficint and standard dviation. Th figurs on th top ar th stimatd cofficints and th figurs in th parnthsis ar standard dviations. 5. *, ** and *** dnot significanc at 0%, 5% and % lvl rspctivly. Marginal Effcts Masurd at th Mans Variabls Affiliation Log of Total Assts *** Non- Affiliation All P/L Insurrs *** 69

71 Tabl 9C. Estimatd Cofficints on Rinsuranc Purchas for th Affiliatd Proprty and Liability Insurrs with Lss than 5% Cdd Prmium Paid to Affiliatd Rinsurrs Scond Stag Rgrssion Dpndnt Variabl: Rinsuranc Purchas Affiliatd Non-Affiliatd All Variabls Rinsurrs Rinsurrs Rinsurrs A.M.Bst Ratings ** *** Loss Volatility Lag of Ratio of Rcovrd Losss ** Rinsuranc Sustainability Indx Loss Ratio ** ** Lag of Rinsuranc Pric Intrnal Rinsuranc Prcntag *** *** Log of Total Assts ** Stock Indicator Rturn on Equity *** *** Lvrag *** *** *** Liquidity ** *** Effctiv Tax Rat ** Product Hrfindahl Indx ** Gorgraphic Hrfindahl Indx ** ** Prcntag of Homownr Writtn Prmium in Florida Prcntag of Homownr Writtn Prmium in Txas *** Prcntag of Homownr Writtn Prmium in AL, LA, NC, SC and MS Prcntag of Long Tail Businss Lins Squar of Log of Total Assts *

72 Continud First Stag Rgrssion On Lag of Rinsuranc Purchas Two Lag of Rinsuranc Purchas On Lag of Loss Ratio *** *** *** On Lag of Log Dirct Prmium Writtn F-stat F4,84 =0.73 F65,53 =0.86 F65,53 =0.87 Obsrvations R-squard Fixd ffct modl is usd for th affiliatd insurrs cd to affiliatd, non-affiliatd and all rinsurrs basd on Hausman tst.. Rgrssion rsults of yar dummis ar not rportd in this tabl. Endognous Variabl: Loss Ratio 3. Th rgrsion rsults of othr instrumntal variabls includd in th first stag rgrssion ar not shown in this tabl. 4. Rgrssion rsults ar shown as cofficint and standard dviation. Th figurs on th top ar th stimatd cofficints and th figurs in th parnthsis ar standard dviations. 5. *, ** and *** dnot significanc at 0%, 5% and % lvl rspctivly. Marginal Effcts Masurd at th Mans Variabls Affiliation Log of Total Assts ** Non- Affiliation All P/L Insurrs

73 7 Appndix Th xpctd utility of a primary insurr from taking rinsuranc transactions in two yars is as follows: } = + 0 0,,,,,,,,,, dm dl ds m s L f L dm ds dl L m s L f L P W U dm dl ds m s L f D A L P W U dm dl ds m s L f D P W U dm dl ds m s L f L P W U U E D A A D D } +,,,, dm dl ds m s L f L dm ds dl L m s L f D P W U A D } + +,,,, dm dl ds m s L f L dm ds dl L m s L f D A L P W U A Th first part, which intgrats from zro to D for th actual loss, is th primary insurr s utility if th primary insurr rtains th actual loss to itslf; th following intgral btwn D and A is th primary insurr s utility with th rcovrd loss of D L by th rinsurr; th third part intgratd from A to th infinity is th primary insurr s utility with th rcovrd loss of D A by th rinsurr; th ffort is subtractd from th xpctd utility for th first yar to obtain th nt xpctd utility. Th nxt intgral part is th calculation for th xpctd utility of th primary insurr for th scond yar. Th total profit for a rinsur in two yars is:

74 = 0 0,,,,,,,,,,,,,,,,,, A A D D A A D D dm dm ds dl ds dl m s L f L m s L f D A P dm dm ds dl ds dl m s L f L m s L f D L P dm dm ds dl ds dl m s L f L m s L f P c dm dl ds m s L f D A P dm dl ds m s L f D L P dm dl ds m s L f P I Th first part, which intgrats from zro to D, is th rinsurr s prmium incom if th rinsurr maks no paymnt to th insurr. Th scond intgral btwn D and A is th rinsurr s profit whn it pays D L to th primary insurr and its incom bcoms D L P +. Th third part intgratd from A to th infinity is th rinsurr s profit if th rinsurr pays D A to th primary insurr and th rinsurr s incom is D A P +. Th monitoring cost c is dductd from th xpctd profit for th first yar to obtain th nt xpctd profit. Th nxt intgral part is th calculation for th xpctd profit for th scond yar.

75 Essay Two Moral Hazard undr Govrnmnt Intrvntion: Evidnc from Florida Homownr Insuranc Markt 74

76 ABSTRACT To addrss th issu of soaring proprty insuranc prmiums and covrag availability in stats that ar subjct to hurrican risks, stat and fdral govrnmnts hav not only rgulatd th privat insuranc markt but hav also intrvnd dirctly into markts by stablishing govrnmnt-fundd insuranc programs. With coxisting public and privat insuranc mchanisms and pric rgulation, th risk of cross subsidization and a subsqunt moral hazard problm may aris. By using data from th Florida Citizns Insuranc Corporation, th Florida Hurrican Catastroph Fund, th National Flood Insuranc and th privat homownr insuranc markt in Florida from 998 to 007, this ssay xamins th moral hazard problms arising from govrnmnt rgulation and involvmnt in th privat insuranc sctor in Florida. In sum, th provision of national flood insuranc is found to b positivly rlatd to th population growth in th stat of Florida, which shows that stat immigrants can tak advantag of th lowr cost of flood insuranc whn rlocating in highr-risk aras. Furthr, w find that national flood insuranc and th catastroph fund complmnt th dvlopmnt of th privat insuranc sctor, whil th rsidual markt hindrs th dvlopmnt of privat proprty insuranc markt. 75

77 . Introduction Hurrican Andrw and th svr storm sasons dramatically changd Florida s proprty insuranc markt. Privat insurrs hav rspondd to th changd markt nvironmnt by rstricting th supply of covrag and incrasing prics. Undr political prssur from votrs, both lgislators and insuranc rgulators bcam concrnd about how to provid sustainabl and affordabl insuranc to proprty ownrs. Thrfor, govrnmnt intrvntion has takn diffrnt approachs, focusing on pric rgulation and as wll as th us of govrnmntfundd insuranc programs such as th National Flood Insuranc Program Flood Insuranc, 7 th Citizns Proprty Insuranc Corporation Florida Citizns, and th Florida Hurrican Catastroph Fund CAT Fund. This ssay answrs th qustion of how wll govrnmnt intrvntion has workd by xamining th ffcts of public policis on dmographic changs and th homownr insuranc markt in Florida, which has significant implications for public policy studis and insuranc markt analysis undr catastrophic risks. Th population of Florida has grown rapidly sinc th 980s at a rat significantly abov th national growth rat, with th immigration accounting for about 85 prcnt of th incras Economics and Dmographic Rsarch, 009. In addition to conomic prosprity and nic wathr, othr factors that may contribut to immigration to Florida ar xamind within th contxt of insuranc. In sharp contrast to th highr insuranc prmiums chargd by privat insurrs, th rlativly lowr cost of th rsidual, or high risk, markt in a risk adjustd sns and flood insuranc may ncourag popl to rlocat to th stat and to high risk aras. This ssay xamins th intractions btwn govrnmnt insuranc programs and th dmographic changs in th last dcad. 7 Th NFIP is fundd by th fdral govrnmnt. It is not a program supportd by th stat of Florida. Th NFIP prdats Florida's incrasd hurrican incidnc. Howvr, it fills in covrag that is not providd by th privat markt nor by any othr stat program. 76

78 In th Florida homownr insuranc markt, th introduction of govrnmnt insuranc programs, such as th Florida Citizns, th Flood Insuranc, and th CAT Fund, is mant to fill th covrag gap lft by privat insurrs. Howvr, th govrnmnt's involvmnt may induc diffrnt typs of infficincis, such as crowding-out ffct and moral hazard. Crowding out is any rduction in privat consumption or invstmnt that occurs bcaus of an incras in govrnmnt spnding. In this papr, it mans th supplanting of privat insuranc covrag by th covrag providd by govrnmnts. Moral hazard rfrs to th tndncy of insurrs to xrcis lss prcaution than is socially optimal by stablishing inadquat incntivs to control, undrwrit or manag th risks of homownrs. By using data on th Florida Citizns, th CAT Fund, th Flood Insuranc and homownr insuranc in Florida from 998 to 007, this ssay xamins th moral hazard problm arising from govrnmnt rgulation and involvmnt in th privat insuranc sctor. In sum, th provision of national flood insuranc is found to b positivly rlatd to population growth in th stat of Florida, which shows that nw rsidnts hav takn advantag of th lowr cost of flood insuranc whn rlocating in highr-risk aras. In addition, w find that national flood insuranc and th catastroph fund complmnt th dvlopmnt of th privat insuranc sctor, whil th rsidual markt discourags th proprty insuranc markt. Morovr, th vidnc shows that nw ntrants to th Florida homownr insuranc markt tak on xcssiv xposurs, which may b byond th insurrs capacitis to bar risk. Thus, th moral hazard problm xists in which som lss liquid and lss capabl 8 insurrs tak mor insurd xposurs as a rsult of subsidis from th stat govrnmnt. Finally, this ssay tsts how govrnmnt 8 Liquidity and capability ar th two issus hr. Capacity, surplus and rinsuranc can b incrasd by th subsidis rcivd, such as takout bonuss, grants and th support of th guaranty association, from govrnmnts. 77

79 intrvntion and involvmnt hav influncd th provision of insuranc in th privat markt in Florida. Th rst of this papr procds as follows. Sction summarizs th volution of homownr insuranc markt and govrnmnt involvmnt in managing hurrican risks in th past two dcads. Th conomics of govrnmnt rgulation and intrvntion ar analyzd in th subsqunt sction. Sction 4 dvlops th hypothss for mpirical tsts and rports th rsults, which is followd by a conclusion in Sction 5.. Evolution of th Florida Homownr Insuranc Markt. Aftr Hurrican Andrw Th frquncy and svrity of both natural and man-mad disastrs hav incrasd substantially in rcnt yars Insuranc Information Institut, 008. Natural catastrophs includ vnts such as arthquaks, hurricans and floods. Man-mad disastrs rfr to trrorism, xplosions and aviation collisions, tc. Figur plots top most costly disastrs in th Unitd Stats history. From this figur w can s tn of th twlv most xpnsiv disastrs of all typs wr causd by hurricans, and ight of tn most xpnsiv hurricans in US history hav occurrd in th past fiv yars. Th stat of Florida, surroundd by Gulf of Mxico and Atlantic Ocan, has bn rpatdly struck by hurricans in th past thr dcads. Eight of th tn most costly hurricans vr to mak landfall in U.S. history hit Florida from 980 to 006, causing mor than $60 billion in 007 dollars insurd losss Insuranc Information Institut, 008. Figur plots Florida s tn costlist hurricans and total insurd losss from 980 to 007. Most of hurricans hav occurrd in th past fiftn yars, with a fw in th 980s. Sinc thr is a diffrnc btwn th risk of hurricans and thir actual occurrnc, th occurrnc of mor 78

80 hurricans in th past fiftn yars in Figur is th vidnc of incrasd risk. Th upward trnd has imposd trmndous challngs to proprty insurrs, along with th rapidly population growth and conomic dvlopmnt in th coastal aras in rcnt yars... Markt Structur Sinc Hurrican Andrw in 99, significant changs had takn plac in th Florida s proprty insuranc markt. Markt concntration, barrirs to ntry and xit and insurrs gographic divrsification ar svral important aspcts of insuranc markt structur. Concntration not only affcts markt prformanc and comptition, but also signifis insurrs vulnrability to svr losss from catastrophs. Gratr concntration implis that som insurrs hav largr amounts of xposurs to catastroph losss. Concntration ratios at th top firms markt shars, such as top four-firm CR4, ight-firm CR8 or twnty-firm CR0, and Hrfindahl-Hirschman Indx HHI ar normally usd to masur th concntration lvl of a markt. HHI is th sum of th squard markt shars of all firms in th markt and can rang from 0 to 0,000 qual to a 00% markt shar by on insurr. Highr indics rflct gratr markt concntration, which may nhanc fficincy through th conomy of scal. Lss concntration, on th othr hand, could promot comptition as wll as gratr risk divrsification. Tabl shows th homownrs insuranc markt concntration in Florida from 99 to 007. From th tabl w can s that CR4 was 59.3 prcnt and HHI was 440 as of 99, indicating that th Florida homownr insuranc markt was rlativly concntratd in th yar Hurrican Andrw occurrd. Th markt concntration had rmaind stabl until middl of th 990s, and th combind markt shar for top insurr groups dcrasd thraftr. Th combind markt shar of top four groups CR4 fll from 59.3 prcnt in 99 to 36 prcnt in 79

81 007, whil CR0 dcrasd from 85. prcnt to 65.9 prcnt in 007. Also, th HHI indx fll significantly from 440 to 6 in 007. This suggsts that thr is a gratr disprsion of xposurs covrd by insurrs in Florida fiftn yars aftr Hurrican Andrw, which signifis a gratr divrsification of risks among insurrs in Florida homownr insuranc markt. Th changs of lading insurrs markt shars in Florida in 99, 003, 005 and 007 ar summarizd in Tabl 3. Th markt shar of th largst two insurrs, Stat Farm and Allstat dcrasd from 50.8 prcnt in 99 to 6. prcnt in 007. Whil big insurrs had rtrnchd from th Florida homownr insuranc markt, th othr rlativly smallr insuranc companis took on mor xposurs in this markt. For xampl, AIG was rankd 8 th in 007 from rank of 53 rd in 99, with a markt shar incras from 0. prcnt to.5 prcnt. Southrn Farm Burau also significantly incrasd its pntration to Florida s homownr insuranc markt. Th chang of markt concntration indicats that som smallr or nw insurrs s opportunitis to grow and hopfully prospr in th markt, whil othr big insurrs s dangr and nd to rtrnch bcaus of thir high xposurs subjct to hurrican risks. According to th Florida Offic of Insuranc Rgulation FLOIR, 40 insurrs hav ntrd th Florida proprty insuranc markt sinc 005. Most of th nw ntrants in th markt ar small rgional or singl-stat companis. Klin 009a dmonstratd this by looking at th ratio of an insurr s Florida homownrs prmiums to its combind homownrs insuranc prmiums in all stats. In 99, th man Florida/Countywid prmium ratio was 6.6 prcnt and th mdian ratio was 8.4 prcnt among insurrs writing homownrs insuranc in Florida. In 007, th man ratio had incrasd to 63. prcnt and th mdian ratio had incrasd to 90.3 prcnt; 4 of th 9 insurr groups in th Florida homownrs insuranc markt wrot 00 prcnt of thir prmiums in Florida. Thos rgional insurrs ar subjct to catastroph risk du 80

82 to th lack of risk divrsification. Po and Towr Hill groups ar good xampls. Po was hit hard in 004 and 005 storm sasons and bcam insolvnt in 006. Th liquidation gnratd approximatly $988 million in paymnts by th Florida Insuranc Guaranty Association for 46,6 claims for Po s policyholdrs Florida Insuranc Association, 007. Towr Hill was struck by 004 and 005 storm sasons as wll and was downgradd by A. M. Bst Company. Homownrs had difficultis in finding insurs to provid covrag and paying incrasd prmiums du to th rstructuring of insuranc markt xposd to hurrican risk. Sinc som insurrs rtrnchd from th markt, homownrs ndd to find nw insurrs to undrwrit thir covrag, and othrs wr forcd into th rsidual markt. Also prics incrasd significantly, spcially in th high-risk coastal aras. Manwhil, many policyholdrs had to accpt highr dductibls prcnt to 5 prcnt of thir dwlling covrag limit to b covrd in voluntary markt covrag and mak thir prmiums mor affordabl Insuranc Information Institut, 008 Prics Prior to Hurrican Andrw in 99, insurrs paid littl attntion to th risk posd by hurricans, so insuranc was rlativly chap and radily availabl. Th insurrs did not us catastroph modls and did littl to control thir catastroph xposurs. Hurrican Andrw was a wak-up call to th insuranc industry. Using nw and rlativly crud catastroph modls to stimat thir risks, insurrs sought to rais thir rats and adjust thir xposurs to rflct th nw rality. Many insurrs hav fild and implmntd substantial pric incrass to rflct th highr dgr of risk and rinsuranc cost aftr Hurrican Andrw Klin, 008. In addition, prmiums in th coastal aras ar as xpctd to b significantly highr and xprincd largr rat 8

83 incrass than intrior aras within th stat bcaus of th additional risk brought by coastal xposurs. To masur th sub-stat diffrncs and changs in prics among countis, th avrag rats pr $000 of covrag by county ar calculatd. Though this approach still confounds othr policy trms with rats, it is lss affctd by changs in th amount of insuranc. I mployd this approach with county-lvl data availabl for Florida in 997, 000, 003, 006 and 007, and th rsults of rprsntativ countis ar plottd in Figur 3 and Figur 4. Monro, Dad and Franklin rprsnt th high risk aras in Florida, whil Lon and Clay ar th rprsntativ countis in th intrior aras within th stat. From 997 to 000, Monro xprincd th gratst incras from its rat of $8.98 to $8.95, and its rat fll to $5.6 in 003. On rason for this trnd is that Hurrican Andrw in 99 producd $0.6 billion in undrwriting losss, which mad th cumulativ insurrs profit ngativ from 99 to 003 NAIC Rport on Profitability by Lin by Stat, 006. Othr countis in th coastal aras, such as Dad and Franklin, had rlativly small rat incrass during this priod. Lon and Clay, which ar xposd to lss catastrophic risks, had lowr rats around $.50 for $000 covrag which rmaind stabl aftr Hurrican Andrw occurrd. Th striking rsults rflct th high lvl of risk in coastal aras which includs th Florida Kys, and insurrs rassssmnt to hurrican risks. Right Aftr th proprty insuranc industry mad vn until 003, insurrs xprincd hug losss again in th storm sasons. As a rsult, high pric incrass wr dmandd by insurrs, spcially to th insurds in hurrican-pron zons. For xampl, homownrs insuranc rat pr $000 covrag in Monro doubld in 006 to around $35 from 003. Th rat incrasd a littl bit to $37 in 007. For th othr intrior countis in th stats rlativ to th coastal aras, th avrag rat pr $000 had kpt stabl during th priod. Profitability 8

84 Profitability rflcts th ovrall prformanc of a firm in a markt. Indicators of profitability includ loss ratios, undrwriting profit, profits on insuranc transactions PIT, rturn on nt worth. Each masur has its own advantags and disadvantags, rvaling spcific financial aspcts of a firm. Undrwriting gains losss aftr Hurrican Andrw to 007, as a bas to masur profitability, ar prsntd first. Th analysis of PIT and rturn on nt worth during this priod follows to xamin th profitability of Florida homownr insuranc markt. Figur 6 and Figur 7 rspctivly plot th undrwriting gains losss and accumulativ undrwriting gains losss of th Florida homownr insuranc markt from 99 to 007. Th graph clarly tlls us that th trmndous undrwriting losss of $0.50 billions strok th insuranc industry in Florida, which took nin yars to mak vn until 003. Th undrwriting analysis focuss on th insurrs prformanc on thir principl businss, providing covrag to inurd risks, whil ignoring othr financial activitis, such as invstmnt incom. Taking into account of invstmnt incom, profit on insuranc transactions PIT and rturn on nt worth provid mor financial information on th prformanc of insuranc industry. Thos two masurs ar obtaind from National Association Insuranc Commissionrs NAIC profitability annual rports. PIT rflcts xpnss, taxs and invstmnt incom, as wll as losss, attributabl to th undrwriting of a particular lin of insuranc in a stat. Th rturn on nt worth includs invstmnt incom attributabl to insurrs surplus, as wll as profits on insuranc transactions. It also rquirs th formula-basd allocation of surplus by lin and stat. Th high PIT and rturn on nt worth indicat high profitability of a firm. Tabl 4 lists PIT and rturn on nt worth of Florida insuranc industry in th lin of homownr multipl prils from 985 to 007. In 99, th PIT and rturn on nt worth wr prcnt and prcnt, rspctivly. Thr wr still ngativ profits and rturn on nt worth in 993 du to th 83

85 continuing claims paymnt aftr Hurrican Andrw. From 994 to 003, positiv profits wr gnratd with th avrag of 0 prcnt of PIT during this priod without hug catastroph losss. This obsrvation suggsts that th proprty insuranc industry in Florida is significantly influncd by catastroph vnts which may caus billions of insurd losss, and profitability is closly linkd to th climat changs and associatd hurrican striks... Rgulation and Public Involvmnt As w hav discussd abov, Hurrican Andrw dramatically changd th Florida homownr insuranc markt in trms of markt structur, availability of insuranc covrag and insuranc pric. Facing big challngs posd by th futur potntial catastrophic losss, insurrs rstrictd thir xposurs in high risk aras and fild for rat incrass. Hnc, th voluntary markt shrank -- rsidnts had difficulty obtaining insuranc covrag for thir proprtis. Furthr, stat rgulators wr rluctant to allow prics to ris. This in turn cratd an availability crisis as insurrs rducd thir prsncs in high risk aras. To fix this markt failur, and provid th availability of insuranc covrag to proprty ownrs, stat rgulation of prics and markt xit, and public insuranc ntry into th privat markt hav bcom th norm in th Florida proprty insuranc markt. Bsids rat rgulation, which artificially lowr th cost of insuranc, stat facilitis also lowr insuranc cost as wll as sk to incras th availability of insuranc. Insuranc rgulatory functions can b dividd into two primary catgoris: solvncy rgulation and markt conduct rgulation. Solvncy rgulation aims to protct policyholdrs against th risks that insolvnt insurrs fail to mt thir financial obligations. Markt conduct rgulation sks to maintain fair and rasonabl prics, products and trad practics. Daling with th unavailability of covrag and pric spiks, lgislators and rgulators in Florida imposd 84

86 th binding constraints on th markt conduct of insurrs, with th rsult bing pric supprssion prics blow actuarially fair valu and comprssion diffrnc btwn high and low risk aras. With th strict pric rgulation, th stat still saw continud availability problms and thus dcidd to incrass its prsnc by stablishing a stat-ownd company to provid insuranc to th vry high risk aras and to st up a fund to provid rinsuranc with blowmarkt prmiums to primary insurrs. Pric Rgulation Pric rgulation has significant implications for th insurrs ability to charg what thy bliv to b adquat rats, which in turn, can affct th supply and dmand of insuranc. Pricing constraints can b dividd into two catgoris: pric supprssion and pric comprssion. Pric supprssion rfrs to a ciling on th ovrall rat lvl that insurrs can charg, whil pric comprssion rducs th rat diffrntials across various gographic aras of th stat, normally btwn high and low risk aras. Th two kinds of pric rgulations ar closly rlatd. Rgulators intnd to cap rats in high risk aras, whil thy kp th rlativly stabl rats in low risk aras. As a rsult, pric comprssion may lad to an ovrall rat lvl that is inadquat to covr th total cost of risk. Aftr Hurrican Andrw, rgulators rsistd larg immdiat rat incrass and only allowd insurrs to gradually rais rats ovr th dcad. Figur 8 lists th Insuranc Srvic Offic ISO advisory loss cost filings in Florida for th priod of 99 to 000. Th ISO is a rat advisory organization which provids advisory prospctiv loss cost, including incurrd losss as wll as loss adjustmnt xpnss. Figur 8 prsnts th indicatd rats, fild rats and 85

87 implmntd rats 9 in rspctiv yars. Prior to Hurrican Andrw, th ISO fild for a 3.3 prcnt dcras in 99 and. prcnt dcras in 99, and rgulators approvd both rat dcrass. In 995, th ISO fild for a rat incras of 7. prcnt to incorporat catastroph loss stimats. Th rgulators only approvd 48.7 prcnt incras. Th sam trnd continud in 996 that th ISO fild an incras of 77.5 prcnt and th rgulators only allowd a rat incras of 3. prcnt. Until 000, incrasd rats wr blivd to rflct actual losss cost that th ISO fild a rat dcras of.8 prcnt. Howvr, th rgulator imposd a 4.7 prcnt dcras. This suggsts that rgulators in Florida supprssd rats undr th actuarially fair costs. At th sam tim, pric comprssion prvaild for most of th dcad, and rats in high risk aras wr mor constraind than in low risk aras Muslin, 996. Pric comprssion worsnd supplyavailability problms bcaus insurrs wr concrnd about substantial rat inadquacy Grac, Klin & Klindorfr, 004. Howvr, th rat supprssion conflicts th rgulators attmpts to sustain an adquat availability of covrag. Insurrs ar rluctant to tak on risk xposurs by mploying supprssd rats undr actual costs, and thy ar forcd to do so as thy ar constraind by a moratorium nactd aftr Hurrican Andrw. Th moratorium only allowd insurrs to shd xposurs through cancllation and non-rnwals initiatd by insurd, unlss insurrs ngotiatd with insuranc rgulators, and it ndd on Jun, 00. Aftr th moratorium xpird, th policy trmination incrasd as insurrs rducd thir risk xposurs in high risk aras. Consquntly, th rsidual markt has bn rapidly growing whil voluntary markt shrank undr rgulatory pric supprssion and comprssion. Th Rsidual Markt 9 Th indicatd rat is th comparabl rat that ISO calculats basd on th actuarially fair cost; th fild rat rfrs to th rat insurs fil to th rgulation authority; th implmntd rat prtains th rat that ISO approvs and implmnt. 86

88 Stat-run rsidual markt mchanisms ar important componnts of public policis towards catastroph risks daling with th covrag availability problm. Th rsidual markt provids insuranc covrag to proprty ownrs who ar unabl to buy insuranc from th voluntary markt. Rsidual markt mchanisms includ assignd risk plans, windstorm and bach pools, joint undrwriting associations, and rinsuranc pools. As a scondary sourc of covrag, th rsidual markt should charg adquat rats and rmain rlativly small. Whn dficits incur, th rsidual markt asssss against all insurrs in rlation to thir voluntary markt prmiums for rlvant lins of insuranc, which mans that th voluntary markt bars mor risks than th policis thy writ. In such cas, insurrs ar discouragd to ntr and ncouragd to xit th markt that lads to a shrinking markt. Consquntly, ths mchanisms provid covrag at th xpns of dvlopmnt of th voluntary markt. In Novmbr 993 aftr Hurrican Andrw, th Florida Rsidntial Proprty and Casualty Joint Undrwriting Association JUA was stablishd to provid covrag to homownrs who wr unabl to obtain covrag from th voluntary markt. Th plan xtndd to crtain commrcial proprty covrag apartmnts and condos in 995 Marltt & Eastman, 998. Figur 9 prsnts th policis numbrs and xposurs of th JUA from 993 to 00. From th graph w can s that th JUA had grown rapidly with th pak of 850,000 policis in 995 and xposurs of $78 billions in 996. An aggrssiv dpopulation had bn undrtakn to shd th JUA to a shadow of its formr itslf. As of 00, it only had 67,30 policis. Sinc th insurrs, who took out of th JUA, only committd to provid covrag for thr yars, th improvmnt had rvrsd aftr 000. Th policis JUA wrot climbd to 0,700 by th nd of 00 Insuranc Information Institut, 008. Morovr, ths policis concntratd in th 87

89 coastal aras of th stat, lik Dad, Broward, Monro and Palm Bach countis. It suggsts that a significant portion of catastroph risk is insurd through th stat-sponsord mchanism. Th Florida Windstorm Undrwriting Association FWUA assumd th wind risk for many homs in coastal aras in Florida. Figur 0 plots th policy numbrs and xposurs of th FWUA from 990 to 000. FWUA continud to grow until 998. It pakd at mor than 500,000 policis and $9. billions in xposurs at th nd of 998. It dclind marginally to 398, policis by th nd of January 003, although xposurs wr vn highr at $08.5 billion Insuranc Information Institut, 008. Du to Florida s uniqu xposurs to hurrican risk, th Florida lgislators cratd th Florida Citizns to scur th availability of proprty insuranc covrag to Florida rsidnts, by mrging th JUA and th FWUA and on May 4 th, 00. Th Florida Citizns provids full covrag or wind covrag for rsidntial proprtis, and has xprincd a significant growth in th rcnt yars. Figur plots Florida Citizns xposurs from 00 to 008. Th xposurs of Florida Citizns jumpd to $ billions in 006 as many proprty ownrs wr not abl to obtain insuranc covrag from voluntary markts aftr th storm sasons As of Sptmbr 30 th, 009, th Florida Citizns had 636,39 prsonal lins account policis and 49,60 high risk account policis. 0 Th total numbr of th Florida Citizns policis has falln from its high of.4 million in Octobr 000 to undr. million in Sptmbr, 009. Florida rgulators hav sought to dpopulat th Florida Citizns by ncouraging small insurrs to tak policis out th Florida Citizns. Th FLOIR had approvd th takout policis from th Florida Citizns by 7 insurrs as of January 0 th, 009. Th trm approvd rfrs to th potntial numbr of policis that may b rmovd by an insurr basd on a consnt agrmnt with th FLOIR. Th Florida Citizns rports that.3 million policis hav bn 0 Information obtaind from Florida Citizns wbsit at 88

90 rmovd sinc 003, with 765,9 policis rmovd sinc 005. Howvr, th dpopulation schm is opn to qustions as th nw small insurrs ar not financially strong with only limitd amounts of capital. Th insolvncis cost of thos companis will ultimatly fall back on consumrs and taxpayrs through th stat s guaranty fund. Th Florida Citizns incurrd larg funding shortfalls of $.6 billion for 004 and ovr $ billion in 005. Th 004 dficit rsultd in a 6.8 prcnt surcharg on all homownrs prmiums in th stat. To covr 005 shortfall, $75 million was appropriatd by th Florida lgislatur to rduc th Florida Citizns assssmnts. Th rmaindr of th dficit will b collctd ovr a 0-yar priod in mrgncy assssmnt on prmium writtn statwid that will b passd on as surchargs to policyholdrs. Florida Hurrican Catastroph Fund Th CAT Fund was cratd by Florida lgislatur in 993 aftr Hurrican Andrw, which is tax-xmpt and provids catastroph rinsuranc to participating insurrs in th stat. Th CAT Fund is fundd by prmiums paid by th participating insurrs and invstmnt incom, and it can apply mrgncy assssmnt if ncssary to rpay dbt. Th mrgncy assssmnt applis to all businss lins xcpt workrs compnsation, accidnt and halth, mdical malpractic and national flood insuranc prmiums. Th CAT Fund was facd with a shortfall in rsourcs to rimburs insurrs from th 005 hurrican sason, and issud $.35 billion in rvnu bonds in 006. An mrgncy assssmnt of prcnt for approximatly six yars on all policis issud or rnwd aftr January, 007 was lvid to financ th post-vnt bonds. Sinc th CAT Fund s cash balanc for paying claims had bn xhaustd, th CAT Fund took stps in 006 and 007 to crat 89

91 liquidity for paying futur claims by issuing pr-vnt liquidity financings of $.8 billion in July 006 and $3.5 billion in Octobr 007 Florida Hurrican Catastroph Fund, 007. Thr is a significant dbat about th function and conomic fasibility for CAT Fund, th stat-sponsord mchanism. Th proponnts contnd that th CAT Fund is hlpful to fill a supply gap in privat rinsuranc markt at a lowr pric. On th othr hand, th opponnts ar concrnd with crowding out privat rinsuranc and financial shortfall which lads to assssmnt on all th policyholdrs across th stat. In th lattr cas, this stat CAT Fund may rais th cross subsidization issu, and furthr moral hazard problm in th insuranc markt. National Flood Insuranc Program Thr ar a coupl of fdral insuranc programs to covr risks which privat insurrs ar rluctant or unabl to covr, including national flood insuranc, crop insuranc and trrorism insuranc. Du to its vulnrability to hurrican risks, th Florida rsidnts hav bnfitd a lot by participating in th national flood insuranc program to covr th flood risk which is xcludd from th rgular homownr insuranc. Administrd by Fdral Emrgncy Managmnt Agncy FEMA, Flood Insuranc provids fdrally backd flood insuranc, which is not providd by privat insurrs, to homownrs, rntrs and businss by rquiring th participating communitis to nforc floodplain managmnt ordinancs to rduc flood losss. Currntly thr ar around 0,000 communitis hav joind this program nationwid. Guaranty Fund To provid scurity and honor claim paymnt to insurds in cas of insurrs bcom insolvnt, th Florida Guaranty Association FIGA was stablishd to procss covrd claims undrwrittn by insolvnt or liquidatd insurrs in th stat. Th FIGA funding coms from four 90

92 sourcs: stat distribution, rcovris from CAT Fund, invstmnt incom and assssmnt from mmbr companis. Th FIGA is partly fundd by assssmnt on proprty liability insuranc prmiums in th stat which ar limitd to prcnt annually. Whil no assssmnt has bn lvid in som yars fr of catastrophic losss, full prcnt of assssmnts wr applid aftr Hurrican Andrw in 99 and tropical storm sasons. For Hurrican Andrw, not only prcnt of proprty-casualty insuranc prmiums wr assssd, but additional prcnt wr borrowd to covr its capacity shortfall. It took fiv yars for FIGA to pay off all its dbts from Hurrican Andrw. FIGA has bn procssing th outstanding claims rcivd as a rsult of fiv insolvncis in th 004 and 005 hurricans, and claims from catastroph losss accountd for 60 prcnt of opn claims by nd of 008 FIGA, 008. Th funding schms of guaranty association rval its financial vulnrability to catastroph in Florida and th sprad-out risks to all insurrs and insurd and taxpayrs. From this mchanism, th insolvnt or liquidatd insurrs transfr thir obligations to stat-run program, which ultimatly advrsly affct th bnfits of various stakholdrs.. Evolvmnt of Lgislation Hurrican Andrw dvastatd th insuranc industry in th stat, and Florida Dpartmnt of Insuranc found that th xisting ruls and rgulations inadquat to addrss th xtraordinary circumstancs. Th insuranc commissionr and rprsntativs from larg insurrs workd togthr closly to find appropriat rcovry solutions Florida Dpartmnt of Insuranc, 993. A sris of mrgncis ruls wr fild to dal with th claims and stabiliz th markt. Th dpartmnt of insuranc issurd a total of 7 mrgncis ruls in 99 and 30 in 993, which showd a strong hands-on approach adoptd by rgulators Mittlr, 997. For instanc, mrgncy rul 4ER9- stablishd procdurs for th withdrawal of any insuranc company 9

93 from th stat of Florida and it mandatd that at last 90 days prior to commncing any stps dirctd toward withdrawal, an insuranc company must fil a writtn statmnt of intnt containing dtails of th rasons for its actions. Emrgncy rul 4ER9-5 activatd JUA on a tmporary basis to provid rsidntial proprty covrag to policyholdrs of insurrs that bcam insolvnt as a rsult of Hurrican Andrw Florida Dpartmnt of Insuranc, 994. Sinc 99, a numbr of stat lgislatur and spcial sssions wr passd to addrss th proprty insuranc crisis Florida Hous Committ on Insuranc, 993, 995; Florida Snat Committ on Banking and Insuranc, 997. Th fist lgislation, Hous Bill No. 33-A, took ffct on Dcmbr 5, 99. Th bill containd thr important lmnts. First, it ratifid th mrgncy fix stablishd by th dpartmnt of insuranc whn th lgislatur activatd JUA; Scond, it authorizd crtain municipalitis and countis to issu up to $500 million in tax fr municipal bonds to fund th shortfall in th FIGA causd by th storm-rlatd insolvncis Third, JUA was cratd to b an insurr of last rsort for prsons unabl to obtain covrag in th voluntary markt Florida Hous Committ on Insuranc, 993; Mittlr, 997. Th lgislatur changd th proprty insuranc markt in th stat. Th CAT Fund was stablishd aftr nactmnt of th 993 law with a tax xmption. Thrby th fund has grown without having to pay taxs on its rcipt of annual prmiums and invstmnt arnings, stimatd to b 35 prcnt of th total Florida Hous Committ on Insuranc, 995. Th CAT Fund is dsignd to provid chapr rinsuranc to insurrs, and insurrs ar xpctd to lowr prmiums chargd to insurds du to th CAT Fund covrag. Anothr issu was about insurrs intntion to cancl or non-rnw policis in high risk countis, and th moratorium phas-out was st up and xtndd. Th moratorium, which took ffct on Novmbr, 4, 993, prohibitd an insurr from cancling or non-rnwing mor than 5 prcnt of its homownrs policis in 9

94 th stat in any -month priod and 0 prcnt of its policis in any county Florida Hous Committ on Insuranc, 995. Ovr th volvmnt and nactmnt of lgislation ovr a dcad aftr Hurrican Andrw, th govrnmnt-run insuranc programs, such as th Florida Citizns, hav contributd to th rstoration of th markt whil arguably bcom compting to th privat insuranc sctors Klin, lgislatur furthr acrbatd th situation. It xpandd th CAT Fund covrag for th 007, 008 and 009 sasons, and providd an additional amount of CAT covrag of up to $0 million dollars at a 50 prcnt of prmiums discount to small and nw insurrs. Eligibl insurrs for such covrag purchas includd limitd apportionmnt companis that bgan writing businss in 007 and insurrs approvd to participat in 006 or 007. Accordingly, insurrs ar xpctd to fil thir rats rflcting th savings or rduction in loss xposur du to th xpandd CAT Fund. Th lgislatur also rscinds th approval rat incras that took ffct January, 007 and rquird Citizns to provid rfunds to prsons who hav paid this rat. It also imposd up to a 0 prcnt of prmium assssmnt on all nonhomstad policyholdrs if a dficit occurs until 008 Florida Offic of Insuranc Rgulation, 008. With th prsnc of big catastrophic hurrican risks as wll as rgulation and lgislatur favorabl to rsidnts, th dmographic changs in Florida has xhibitd th trnd which will b introducd in th following sction..3 Population Growth Influncd by th Risks, Insuranc and Rgulation As w discussd abov, th rgulation on proprty insuranc markt subjct to catastroph hurrican risks has significantly impactd th privat markt by largly xpanding govrnmnt-run insuranc programs. Subsidization from low risk aras to high risk aras at th 93

95 xpns of tax-payrs mony may aris in th cas. Prciving th govrnmnt s gnrous financial support to hurrican-pron zons, th rsidnts and/or migrants to Florida may hav strongr incntivs to tak advantag of this favorabl public policy by moving to such aras without baring th corrsponding risks. Sinc th 980s, th stat of Florida has xprincd rapid population growth significantly abov th national population growth rat. Th National Ocan and Atmosphr Administration 008 documntd th largst rat of population chang 980 to 003 occurrd in coastal countis. Flaglr County locatd in th southast of Florida incrasd 470 prcnt, followd by Oscola County at 38 prcnt during th priod. As th offic of Economics and Dmographic Rsarch EDR rportd, th stat growth rats wr narly 33 prcnt and 3.5 prcnt in th 80s and 90s, rspctivly. From 000 to 009, Florida s population grw by 7.7 prcnt ovr th ight-yar priod to 8,85,975. Currntly, Florida rmains th fourth largst stat bhind California, Txas and Nw York EDR, 009. Natural population incras and migration contribut to population incras. Natural incras rfrs to th diffrnc btwn births and daths, whil domstic and intrnational migration also contribut to population growth. According to th EDR s Florida dmographic summary, in th priod from April, 000, to April, 008, th natural incras accountd for 4.4 prcnt of Florida s growth, and nt migration accountd for 85.6 prcnt. Furthr about 35. prcnt of Florida s total nt migration is du to intrnational migration stimatd by th Cnsus Bura, which could b xplaind by th labor forc movmnt from Mxico and South Amrica countris to Florida du to its conomic prosprity and convnint location. Gnrally, big citis in th coastal aras that offr plnty of job opportunitis, such as Miami and Palm Bach, hav attractd mor immigrants to rlocat thr. In trms of ag, th population agd 85 94

96 and oldr has grown fastst in th last two dcads, incrasing by 6. prcnt during th 90s and forcastd to incras by 55.8 prcnt btwn 000 and 00 EDR, 009. Florida has incrasingly bcom a rtirmnt magnt as a migratory dstination for rtirs in rcnt dcads Fry, 003. Th abov statistics show that th population in Florida has bn growing significantly ovr th past dcads whras migration plays an important rol to th population growth. With rspctiv to hurrican risks, th availability of insuranc covrag and insuranc pric has bn a big issu for both migrants and rsidnts. In this cas, th govrnmnt rgulation or financial support to insurds may hav ffct on individuals dcision stay or mov in or mov out of Florida. Thr is grat dal of litratur on th ffct of public policis on population growth or migration, which will b introducd in th flowing sction. 3. Economics of Govrnmnt Rgulation and Intrvntion 3. Comptitiv Markt and Markt Failur In conomic thory, a prfct comptitiv industry rquirs larg numbrs of sllrs and buyrs, a homognous commodity, fr ntry and xit, prfct information, and prics dtrmind by th intraction of supply and dmand. In th long-run quilibrium stat of a comptitiv industry, th marginal cost of production is qual to th pric, conomic profits ar zro; and ach firm oprats at th lowst unit cost. Thus, rsourcs ar mployd at maximum production fficincy undr comptition. Comptition dcntralizs and disprss powr btwn buyrs and sllrs. Th rsourc is allocatd through th intraction of supply and dmand on th markt, and not through th conscious xrcis of powr hld in privat hands.g., undr monopoly or govrnmnt hands i.., undr stat ntrpris or govrnmnt 95

97 rgulation. Hnc, comptitiv markt procsss solv th conomic problm imprsonally, and not through th prsonal control of ntrprnurs or buraucrats. A comptitiv markt systm sts no barrirs for ntris and xits, which ntails frdom of opportunity for individuals. Individuals can frly choos what to trad, only constraind by thir own talnts, abilitis and financial capitals Schrr, 979. In rality prfct comptition can not b ralizd, but workabl comptition can b attaind, which functions wll and provids most of th bnfits of a prfct comptition Schrr, 979. A workably comptitiv markt gnrally is charactrizd by numrous sllrs and buyrs, low ntry and xit barrirs, good information, and th absnc of artificial rstrictions on comptition. Workabl comptition rasonably approximats th conditions for prfct comptition to th dgr that littl rgulation is rquird to achiv an fficint allocation of rsourcs Schrr & Ross, 990. Cummins and Wiss 99 analyzd th structur and conduct of proprty-liability insuranc industry and showd that this markt is comptitivly structurd, with numrous firms compting for businss in most lins and low ntry barrirs. Howvr, markt failurs occur undr crtain markt conditions, such as markt powr, xtrnalitis, incomplt information, transaction costs, tc. s Bator, 958; Williamson, 97. In th contxt of insuranc industry, givn its rlativly lowr markt concntration and lowr ntry barrirs Cummins & Wiss, 99, markt failurs includ svr asymmtric information problms and principal-agnt conflicts, which imply that th information problms arguably ar th industry s most important markt imprfctions. Asymmtric information problms xist whn on party to a transaction hav suprior information that th othr dos not hav. Insuranc consumrs, particularly individuals and S Pauly 968, Pauly 974, and Akrlof 970, Rothschild and Stiglitz

98 housholds, fac significant challngs in judging th financial conditions of insurrs du to thir limitd knowldg and lack of profssional xprtis. Also, som individuals may hav difficulty proprly undrstanding th complx insuranc contracts and products. On th othr hand, insuranc consumrs hav bttr information about thir risks, and high risk buyrs hav mor incntivs to purchas insuranc, which advrs slction problm ariss. Th insuranc markt may fail in this cas Akrlof, 970. Principal-agnt problms aris whn insuranc consumrs hav difficulty monitoring and controlling th bhavior of insurrs aftr thy purchas policis and pay prmiums. Th insurr might mak high risk invstmnts that ar hazardous to policyholdrs intrsts by failing to fulfill its obligations to policyholdrs. In cas of insurr insolvncy, it is vry difficult for policyholdrs to rcovr funds or forc th insurr to mt its obligations. Morovr, th problm can b xacrbatd bcaus of unqual rsourcs and bargaining powr btwn insurrs and individual consumrs. Bsids incomplt information, markt powr can also lad to markt failur. Markt powr is th ability of on or a fw sllrs or buyrs to influnc th pric of a product or srvic. In th insuranc contxt, for instanc, on or svral big insurrs in crtain businss lins could xrcis collusion pric to consumrs for xcssiv rturns, which lads to an infficint allocation of rsourcs and harm consumrs bnfits. To fix th abov markt failurs, thoris of rgulation and govrnmntal intrfrnc hav bn proposd and applid to nhanc conomic prformanc, which will b introducd in th nxt part. A dtaild rviw of ths thoris may not b ncssary, but it is important to undrstand th implications to stakholdrs in insuranc markts, including insurrs, policyholdrs, lgislators and rgulators. 97

99 3. Thoris of Govrnmnt Rgulation Economic analysis of govrnmnt rgulation has procdd rapidly. Thr ar svral xplanations for rgulation, ach mirroring a fact of rality. On is th "pubic intrst thory", whr rgulation is rquird to corrct mattrs and srv th public intrst in cas markt failurs occur s Bonbright, 96. In th insuranc contxt, th public intrst argus that th rgulation of insurr solvncy is usd to addrss th infficincy causd by costly information and agncy problm Munch & Smallwood, 98. Insurrs hav diminishd incntivs to maintain a high lvl of financial safty bcaus thir prsonal assts ar not at risk for unfundd obligations to policyholdrs that would aris from insolvncy. It is costly for policyholdrs to assss an insurr s financial condition. Insuranc is a tchnical and complicatd subjct, and th tru financial strngth of an insuranc company can only b dtrmind by xprt xamination. Thr is also mbddd principl-agnt problm insurrs can incras thir risk aftr policyholdrs hav purchasd policy and paid prmiums. A scond hypothsis stats that rgulation occurs bcaus thr ar wll-organizd vstd intrsts xpcting to bnfit from rgulation s Jordan, 97; Pltzman, 976; and Stiglr, 97. This "intrst group prssur" thory suggsts that rgulation is acquird by groups with thir own intrsts and is dsignd and opratd primarily for groups bnfit. Undr this scnario, rgulators ar motivatd to maximiz political support rathr than conomic fficincy. Mir 988 furthr st up a modl to xplain th idological motivation of rgulators. In his modl of th political conomy of insuranc rgulation, h hypothsizd that th insuranc industry should favor rgulatory policis that bnfit it and oppos policis that rstrict it. Mir obsrvd that th insuranc industry is not a monolith and that diffrnt sgmnts of th insuranc may hav diffrnt viws with rspct to crtain rgulatory issus. Th ability of th For xampl, s Alfrd 970, and Schmalns

100 industry to influnc rgulation is hypothsizd to b a function of its political rsourcs, including its siz and walth. Insuranc is important to th wlfar of th individuals, housholds, firms and th ovrall conomy, and it warrants clos govrnmnt attntion. It also implis that th public intrst should b th paramount considration in guiding govrnmnt intrvntion, though rgulators ar also influncd by political factors. Hnc, th rational for govrnmnt intrvntion in cas of markt failurs is basd on promoting or rstoring conomic fficincy. Optimal rgulation should b dirctd by an idal st of policis that attmpt to rplicat th conditions of a comptitiv markt and maximiz social wlfar. Anothr aspct of insuranc rgulation in practic is how social prfrncs impact th public policy usd to nhanc fficincy in a fr markt conomy. For xampl, th public would prfr lowr prmiums in gnral rgardlss th ral risk status. Lowr prics supprssd by rgulation might bnfit consumrs in th short-run until firms lav th markt and th supply of insuranc contracts. This artificially-inducd unavailability of insuranc sms against th public intrst in th long-run, but thr is strong political support for low prics. In this sns, th rgulation or public polics influncd by votrs or spcial intrst groups may divrg from th conomic rational, rsulting advrs consquncs or govrnmnt failurs. 3.3 Potntial Problms Causd by Rgulation and Intrvntion Not all markt failurs may b corrctd by govrnmnt rgulation and intrvntion. Th crowding out ffct is on of infficincis causd by govrnmnt intrvntion in th markt, which mans govrnmnt spnding will crowd out privat ntrpriss. If govrnmnt spnding is financd through tax incrass, that will rduc individuals aftr-tax incom and thn rduc thir spnding. If govrnmnt spnding is through borrowing, th highr govrnmnt dmand 99

101 for saving will driv up intrst rats which, in turn, will thwart privat invstmnt. In th insuranc markts, th stablishmnt of govrnmnt insuranc programs, such as rsidual markts and stat-run insuranc providrs, can mak privat firms xit th markt if th govrnmnt providrs sll blow th actual costs. Thus, privat insurrs with highr capital costs and othr xpnss ar unabl to provid a comptitiv pric and ar forcd to lav th markt. Anothr potntial problm inducd by govrnmnt intrvntion is cross subsidization, which prtains to th practic of charging highr prics to on group to subsidiz lowr prics for anothr group. Faulhabr 975 analyzd th issu of cross-subsidization in ntrpriss with conomis of joint production. H found that subsidization of prics in an othrwis comptitiv markt would lad to infficint ntry and instability of th joint ntrpriss. Th Florida insuranc rsidual markt providr, th Florida Citizns is a good xampl in this cas. To mak insuranc covrag availabl to vry applicant, th stat of Florida provids protction in th form of subsidizd prics to high risk rsidnts who ar ithr unabl to purchas insuranc from voluntary markt or ar rluctant to pay privat markt prics. Th Florida Citizns has bn stablishd to hlp allviat availability problms and, in som cass, to charg rlativly lowr prics to its policyholdrs. Whn th Florida Citizns losss xcd its claims-paying capacity in a singl yar, it is rquird by stat law to impos a statwid assssmnt on most lins of businss in th stat. By law, insurrs my rcoup th amount from all policyholdrs as part of th homownrs insuranc rat-making procss in th stat, 3 whr low risk policyholdrs subsidiz th high risk policyholdrs. Also, stat gnral rvnu funds may b appropriatd to offst th 3 To covr 004 s shortfall, Citizns imposd a 6.8 prcnt surcharg on policyholdrs, amounting to about $00 pr $500 in prmiums Insuranc Information Institut,

102 dficit. 4 This divrgnc of pric and cost lads to infficincy with th suboptimal allocation of rsourcs. A moral hazard problm may also aris with th provision of govrnmnt insuranc programs as wll. Hansn and Imrohoroglu 99 studid th potntial wlfar loss of unmploymnt insuranc with liquidity constraints and moral hazard. Th authors found that if th rplacmnt ratio can b arbitrarily st, insurds may incur moral hazard by choosing not to work with th covrag of unmploymnt insuranc. As a rsult, unmploymnt insuranc can b actually harmful to th conomy rathr than improv it. Pauly 974 analyzd conditions to attain th comptitiv quilibrium whn both provision and comptitiv markting of supplmntary covrag ar prmittd to xist sid by sid. Sinc supplmntary purchass rais th probability of loss and hnc rais th xpctd loss of th purchasr within th public program as wll as th loss in any privat insuranc, a prmium for public insuranc should b assssd on thos who buy supplmntary covrag, vn if th public insuranc wr providd through gnral taxs. Using this rasoning, a moral hazard problm may aris in th Florida homownr insuranc markt whr stat-run and privat rinsuranc coxist in th markt at th sam tim. Furthr, catastroph rinsuranc is sold by th stat and availabl for all insurrs to purchas at lowr prics compard to othr privat rinsuranc in th markt. With rinsuranc purchasd from th Florida CAT Fund at rlativly lowr costs, insurrs ar xpctd by lgislators and rgulators to provid mor covrag to insurds at lowr prics Florida Hous Committ on Insuranc, 995; Florida Snat Committ on Banking and Insuranc, 997; Florida Offic of Insuranc Rgulation, 008.Whil possibly crowding out privat rinsuranc, th provision of th low cost rinsuranc fund may ncourag insurrs, which ar not at good 4 To offst Citizns 005 dficit, hurrican insuranc bill SB 980 was passd by th stat lgislatur in May 006, providd for a $75 million appropriation of stat gnral rvnu dollars to th fund Insuranc Information Institut,

103 financial conditions, to ntr or stay in a risky markt. Thus, w s th possibility of statfundd insuranc programs inducd moral hazard. 3.4 Migration and th Effct of Public Programs A numbr of studis hav xamind th incntivs for population, and spcifically th rlationship btwn th migration and public policis for xampl, Conway & Houtnvill, 998; Davis, 00; Sjaastad, 96; Rosnzwig & Wolpin, 988. Human migration has its costs and rturns, and it can b tratd as a mans in promoting fficint rsourc allocation whn it is rlatd to corrct incom disparitis Sjaastad, 96. Mony rturns and non-mony rturns, such as climat, cultural nvironmnt, could attract popl to mov to anothr county or stat across th country. In trms of mony rturns, th public policis or programs, which may influnc incom or bnfits rcivd by rsidnts, may impact popl s dcision to rlocat. For xampl, Rosnzwig and Wolpin 988 mployd a conditional logit approach to stimat th modl of intrstat migration in th Unitd Stats from 986 to 996. Thy found that th variabls of population, distanc, pr capital incom and unmploymnt rat had ffcts on th population migration. It is worth noticing that th cofficints of pr capital incom and unmploymnt rat changd substantially ovr th study priod according to findings. In addition, Conway and Houtnvill 998 invstigatd whthr ldrly migrants wr affctd by stat fiscal policis and discussd th possibl consquncs. In thir modl, th migration flows wr stimatd as a function of th stats amnitis, cost of living composition of govrnmnt spnding and altrnativ spcification of th tax systm. Thy concludd that ldrly migration was influncd by stat fiscal policy. In th contxt of th migration to Florida, this papr attmpts to analyz th 0

104 ffct of th govrnmnt-run insuranc programs on th dmographic chang ovr th study priod. In sum, th rsidual markt and govrnmnt intrvntion in th Florida s homownr insuranc markts, which ar applid to corrct th allgd privat insuranc markt s failur, may induc diffrnt typs of infficincis, such as crowding-out of privat risk baring activitis, cross subsidis and moral hazard. In th nxt sction I propos th hypothsis to analyz th ffcts of pric rgulation and govrnmnt intrvntion on th privat insuranc markt and dmographic movmnts. Furthr, w assss th intraction of privat markts and govrnmnt rgulation mpirically in th nxt sction. 4. Empirical Tsts 4. Hypothss Th significant growth in population and conomic dvlopmnt in coastal aras arguably hav bn attributabl to th incrass in hurrican losss in rcnt yars. In crtain high risk aras, howvr, subsidizd homownr insuranc and flood insuranc ar radily availabl in th markt to proprty ownrs at a lowr cost. Migrants, who prciv th bnfits of govrnmnt insuranc, could hav mor incntivs to mov to highr risk aras bcaus insuranc prmiums ar blow thir social costs. This slctivity trnd may indicat th moral hazard which ariss among migrants du to th favorabl public policy. Hnc, Hypothsis I is drivd as follows: Hypothsis I: Migration to Florida's high risk aras is positivly associatd with subsidis from govrnmnt insuranc programs. 03

105 With rspctiv to insurrs in privat insuranc markt, th prsnc of govrnmnt-run program, such as th Flood Insuranc and th CAT Fund, may ntail moral hazard problm in th markt. Rathr than masur risks actuarially and tak on appropriat amount of risks with adquat surplus, insurrs may b ncouragd to ovr-undrwrit risks byond thir capacitis. In contrast to th goal of corrcting markt failur by govrnmnt intrvntion, infficincy is causd in this cas. Thrfor, Hypothsis II is statd as follows: Hypothsis II: Insurrs in th privat sctor assum mor risks in hurrican-pron aras with th provision of th CAT Fund and Flood Insuranc. Manwhil, th Florida Citizns may crowd-out th privat insurrs du to its lowr subsidizd prmiums. Compard to th CAT Fund and th Flood Insuranc, th prsnc of th Florida Citizns could dcras th insuranc purchas from privat insurrs. So Hypothsis II is proposd to stimat insurrs ovrall markt rsponss to th public policis in th Florida s homownr insuranc markt subjct to hug catastrophic losss. 4. Data A panl data covring privat proprty insuranc companis, govrnmnt-run insuranc programs and dmographic changs in Florida from 997 to 007 is constructd to tst th hypothss stablishd abov. Th Florida population information by county by yar is obtaind from th Florida Dmographic Estimating Confrnc and Florida Dmographic Forcast, 5 and thn th population growth is calculatd accordingly. Sinc nt migration accountd for 85.6 prcnt of total population growth of Florida from April 000 to April 008 EDR, 009 and information on nt migration is not availabl at county lvl, th population growth rat is applid to rflct th dmographic changs in countis across Florida during th study priod. Florida population 5 S 04

106 in 000 and 007 and homownr insuranc xposurs in 007 ar prsntd in Tabl 6. W s that Flaglr, Sumtr and Oscola ar th thr fastst-growing countis, with growth rats of 87.8 prcnt, 68.3 prcnt and 40.6 prcnt rspctivly. Monro County, which is th southwstrn most county in Florida which includs th Florida Kys, has xprincd ngativ population growth of -0.8 prcnt from 000 to 007. Howvr, Palm Bach, a county on th South Eastrn coast, has th growth rat of 4 prcnt, incrasing from. million to.3 million. In sum, significant population growth has bn obsrvd for som countis rlativly far away from costal zons, whil population has dcrasd for som placs most clos to th ocans. It may imply that th potntial hug losss from hurricans hampr th population growth in som risky aras. With th county incom data from Burau of Economic Analysis in th Dpartmnt of Commrc, 6 pr capital incom at county lvl in Florida is calculatd. Th QUASR databas provids homownr insuranc information by firm by county from 997 to 007. Th phras of QUASR is th abbrviation of th QUArtrly Supplmntary Rports, which ar prpard by th insurrs doing businss in Florida and rportd to th stat's Offic of Insuranc Rgulation. 7 Homownr insuranc dirct writtn prmiums, xposurs and policy numbrs in forc by firm, by county and by yar within th study priod ar availabl in th databas. Th markt shar of Florida Citizns in trms of xposurs, dirct writtn prmiums and policy numbrs in forc ar calculatd accordingly. Th CAT Fund rinsuranc purchas by privat insurrs, which is masurd by th prcntag of CAT Fund rinsuranc out of th total rinsuranc purchass, is computd from annual rports by NAIC for ach insurr in ach yar. In th datast, th man of CAT Fund purchas is 8.3 prcnt, suggsting an insurr on avrag cds 8.3 prcnt of its businss 6 S 7 S 05

107 portfolio to th CAT Fund, laving almost 90 prcnt of businss to th privat rinsuranc markt. 8 In trms of Flood Insuranc in Florida, th information on th dirct writtn prmiums, policy numbrs in forc, th amount of covrag, claims numbrs and th amount paid by county by yar ar obtaind from Fdral Emrgncy Managmnt Agncy that oprats th program. To control for firm charactristics, firm-spcific variabls of assts, rturn on quity, liquidity and lvrag ratios ar collctd from A.M. Bst Company. 9 Th amount of assts signals th siz of an insuranc company; rturn on quity indicats th profitability of a firm; liquidity rfrs to th ability of an asst to b convrtd into cash quickly and without a pric discount; lvrag masurs th ability of a firm to mt its financial obligations. This is a thr-dimnsional datast at firm, county and yar lvls, which allows th mpirical tsts to b applid from diffrnt prspctivs. Th variabl dfinitions and data sourc ar listd in Tabl 5, and th dscriptiv statistics of variabls will b discussd in th following part Estimatd Equations With th panl data on insuranc companis, privat and govrnmnt insuranc purchass and claims in th Florida homownrs insuranc markt from 997 to 007, th proposd hypothss on th ffct of govrnmnt rgulation and intrvntion on th privat insuranc sctor, i.. if thr ar any moral hazard problms rlatd to public policis, ar tstd blow. Hypothsis I Tst - Estimatd Equations 3 PG EXP COV i, t = α 0 + βfc i, t + βfi i, t + β3d + β4d + β5d3 + β6incomi. t + β7crimi, t + ε i, t 8 It is important to not that th NAIC data dos not allow on to sparat rinsuranc purchass by lin of primary businss or by stat of primary insuranc sals. Thus, w look at th prcntag of rinsuranc from th Florida CAT fund as bing solly from Florida risks. 9 Sinc NAIC annual rports do not dirctly provid financial ratios of insurrs, such as rturn on quity, liquidity and lvrag, in annual rports, w us ths ratios from A.M. Bst Company, which computs financial ratings and ratios basd on th spcifid formula. 06

108 PG PG DPW DPW i, t = α 0 + β FC i, t + βfi i, t + β3d + β4d + β5d3 + β6incomi, t + β7crimi, t + ε i, t PIF PIF i, t = α 30 + β3fc i, t + β3fi i, t + β33d + β34d + β35d3 + β36incomi, t + β37crimi, t + ε i, t 3 whr PG, = Population growth in county i at yar t ; FC EXP i, t = Markt shar of Florida i t Citizns in xposurs in county i in yar t ; dirct writtn prmiums in county i in yar t ; DPW FC i PIF FC i, t is th markt shar of Florida Citizns in, t is th markt shar of Florida Citizns in policy numbrs in forc in county i in yar t ; FI COV i, t = Log of flood insuranc covrag in county i in yar t ; FI DPW i, t = Log of flood insuranc dirct writtn prmiums in county i in yar t ; FI PIF i, t = Log of flood insuranc policy numbrs in forc in county i in yar t ; D = Dummy variabl for South Atlantic ara; D = Dummy variabl for Gulf Coast ara; D 3 = Dummy variabl for Panhandl ara; Crim i, t = Non-violnt crim rat for county i in yart. Incom i, t = Pr capital county incom for county i in yar t ; ε i, t = Error trm for county i in yar t ; Th population migration in Florida is of our intrst to tst th possibl ffcts of public policis in th proprty insuranc on th dmographic changs subjct to catastrophic hurrican risks. Furthr, nt migration rats for ach county in th stat could b appropriat masurs for such dmographic changs du to th potntial subsidization btwn high and low risk aras in this cas. Th nt migration rat, howvr, is not availabl at county lvl, so th population growth rat is usd instad in my study bcaus th migration accountd for 85.6 prcnt of population growth from April, 000 to April, 008 according to Economic Dmographic Rsarch EDR, 009. As discussd in sction 3, a numbr of studis xamind th incntivs for population growth, and spcifically th rlationship btwn th migration and public policis for xampl, Conway & Houtnvill, 998; Davis, 00; Sjaastad, 96; Rosnzwig 07

109 & Wolpin, 988. Som conomic and socital masurs wr xamind to b rlatd to th population migration, such as pr capital incom, unmploymnt rat and tax rat. Sinc th mpirical tst in this papr is dsignd at th county lvl with an intntion to s th microstructur of migration in Florida spcially btwn high and low risk aras, th corrsponding variabls at county lvl ar thrfor ndd. In trms of unmploymnt and tax rat, such variabls ar only availabl at stat lvl. To approximat ths conomic masurs, th non-violnt crim rat at county lvl is adoptd instad. Th participation of th Florida Citizns and Flood Insuranc ar masurd by dirct writtn prmiums, xposurs and policy numbrs in forc, which ar includd in rgrssions 3 rspctivly. Risk ara dummis indicat th rlativly catastrophic risk lvl of a county with rspctiv to its distanc to ocans. Figur 5 shows th trritoris for ach risk ara in th stat map of Florida, and Tabl lists th countis which blong to ach risk ara. Tabl 7. summarizs th dscriptiv statistics of variabls includd in quations 3. Thr ar 670 obsrvations in total for 67 countis from 998 to 007. Th maximum population growth rat in Florida is 3.3 prcnt, whil it can b as low as -4.4 prcnt. Th Florida Citizns accounts for 35 prcnt of th total homownrs insuranc markt at maximum and dos not covr som crtain countis, rsulting an avrag markt shar of around prcnt. Flood insuranc covrag, xposurs and policy numbrs in forc ar takn logarithm to mak commnsurabl to othr variabls in rgrssion quations. To control for population siz, ths thr variabls ar normalizd by population. On avrag, pr capital county incom is around $460 and th nonviolnt crim rat pr 00 population is around 7 prcnt. Rcall that Hypothsis I stats that population migration, which is rflctd by population growth, is positivly rlatd to th provision of govrnmnt insuranc programs, such as th 08

110 Florida Citizns and th Flood Insuranc, with th prsnc of moral hazard problm. Thus, th cofficints of Florida Citizns and Flood Insuranc ar xpctd to b positiv, which suggsts that popl ar inclind to mov to hurrican-pron aras with subsidizd insuranc providd by stat or fdral govrnmnts. Morovr, th positiv cofficints of risk ara dummis indicat that ths high-risk aras ar diffrnt from th intrior parts of th Florida stat. 0 In trms of potntial moral hazard problm in th privat markt rlatd to govrnmnt rgulation and intrvntion, risky insurrs, spcially which ar lss liquid and mor lvragd, ar hypothsizd to aggrssivly undrwrit homownrs insuranc with th prsnc of Flood Insuranc and CAT Fund. Thrfor, th stimatd quations for Hypothsis II ar statd as follows: Hypothsis II Tst - Estimatd Equations 4 6 HO EXP k, i, t EXP COV = α40 + β4fc i, t + β4fi i, t + β43ptcfk, t + β D + β D + γ 45 4,3 46 Lvrag k, t + β D + γ 47 4,4 3 + β Incom 48 Liquidity k, t + ε i, t k, i, t + γ + β 4, 44 Siz APCT k, t + γ i, t 4, ROE k, t 4 HO DPW k, i, t DPW DPW = α 50 + β5fc i, t + β5fi i, t + β53ptcfk, t + β D + β D + γ 55 5,3 56 Lvrag k, t + β D + γ 57 5,4 3 + β Incom 58 Liquidity k, t + ε i, t k, i, t + γ 5, Siz + β k, t 54 + γ APCT 5,, i, t ROE k, t 5 HO PIF k, i, t PIF PIF = α60 + β6fc i, t + β6fi i, t + β63ptcfk, t + β D + β D + γ 65 6,3 66 Lvrag k, t + β D + γ 67 6,4 3 + β Incom 68 Liquidity k, t + ε i, t k, i, t + γ + β 6, 64 Siz AP k, t k, i, t + γ 6, ROE k, t 6 whr EXP HO k i, t, = Log of xposurs of homownrs insuranc for insurr k in county i in yar DPW t ; HO k, i, t = Log of dirct writtn prmiums of homownrs insuranc for insurr k in county i in yar t ; EIF HO k i, t, = Log of policy numbrs in forc of homownrs insuranc for insurr k in 0 South Atlantic, Gulf Coast and Panhandl aras ar dfind as high risk aras whrby th rst of aras rfr to th intrior part. S Tabl for risk ara catgoris dfinition. 09

111 county i in yar t ; yar t ; FC yar t ; FC DPW i PIF i EXP FC i, t = Markt shar of th Florida Citizns in xposurs in county i in, t = Markt shar of th Florida Citizns in dirct prmium writtn in county i in, t = Markt shar of th Florida Citizns of policy numbrs in forc in county i in yar t ; FI COV i, t = Log of th Flood Insuranc covrag in county i in yar t ; FI DPW i, t = Log of th Flood Insuranc dirct writtn prmiums in county i in yar t ; FI PIF i, t = Log of th Flood Insuranc policy numbrs in forc in county i in yar t ; PTCF k, t = Prcntag of th CAT Fund rinsuranc purchas out of total rinsuranc for insurr k in yar t ; APCT i, t = Proxy of homownrs insuranc pric which is calculatd as total prmiums dividd by total covrag in county i in yar t ; AP k, i, t = Proxy of insurr k s homownrs insuranc pric which is calculatd as prmiums dividd by covrag for insurr k in county i in yar t ; Incom i, t = Control variabl for county i at yar t ; D = Dummy variabl for South Atlantic ara; D = Dummy variabl for Gulf Coast ara; D 3 = Dummy variabl for Panhandl ara; Siz, = Log of k t total assts for insurr k in yar t ; ROE, = Nt incom to quity for insurr k in yar t ; k t Lvrag k, t = Dbt to capital for insurr k in yar t ; k t Liquidity, = Proportion of liabilitis covrd by cash and short-trm invstmnt for insurr k in yar t ; ε k, i, t = Error trm for insurr k in county i in yar t. Th lags of th Flood Insuranc and th CAT Fund from prvious priods ar adoptd in th rgrssions, bcaus th ffcts of thos two programs on th dmand for homownrs insuranc ar prcivd to pass to th nxt priod. For xampl, proprty ownrs mak thir dcisions whthr and to whom to purchas homownrs insuranc basd on th historical claim paymnts rcords of Flood Insuranc in thir communitis. 0

112 Th variabls indicating govrnmnt intrvntions, including th Florida Citizns markt shars, th Flood Insuranc and th CAT Fund purchas, ar applid to xamin th ffcts on insurrs risk-taking bhaviors in th homownrs insuranc markt. Commnsuratly, th xposurs, dirct writtn prmiums and policy numbrs in forc of th Florida Citizns ar mployd into rgrssions 4 6, rspctivly. In quation 4, th variabl of APCT i, t proxis th homownr insuranc pric as total dirct writtn prmiums dividd by total xposurs insurd for a county in a yar. It masurs an avrag lvl of insuranc prmium at a county lvl. Th firm charactristics of siz, rturn on quity, lvrag and liquidity ar applid as control variabls. As suggstd by th crowding-out ffct of th rsidual markt, th cofficints on Florida Citizns ar xpctd to b ngativ, which mans th rsidual markt hindrs th dvlopmnt of th privat sctor. In trms of stat fundd catastroph rinsuranc, it is xpctd to incras th covrag availability by privat insurrs as it provids rlativly chapr rinsuranc and rducs th undrwriting costs of primary insurrs. Th provision of flood insuranc is xpctd to b positivly associatd with th amount of Florida s homownr insuranc for th flood insuranc can b complmnts of homownr insuranc. Th inclusion of firm factors, such as lvrag and liquidity, ar abl to rflct what kind of firms ar taking mor risk xposurs in th markt undr govrnmnt subsidy and involvmnt. Firms with lowr lvrag and highr liquidity signify thir sound financial capability, and will rstor th markt comptition and nhanc fficincy which prfctly mts th goal of govrnmnt s rgulation. If firms with highr lvrag and lowr liquidity ar obsrvd to aggrssivly undrwrit high risks by filling covrag gaps lft by othr big rtrnching insurrs and cding businss to

113 catastroph fund at lowr prmiums, w may infr that govrnmnt intrvntion and cross subsidization ntails moral hazard problm in th markt. Tabl 7. lists th dscriptiv statistics of th variabls in quations 4 6. Th man of th CAT Fund purchas is 8.3 prcnt for a firm, which shows that, on avrag, insurrs obtain most of rinsuranc covrag from th privat markt. Th variabl of Citizns markt shars appar to b volatil, sinc th man of markt shar in xposurs is.5 prcnt with th standard dviation of 4.4 prcnt. Furthr, th maximum Citizn markt shar in xposurs is 33 prcnt. Th markt shar in dirct writtn prmiums and policy numbrs in forc follow th similar pattrn, which implis that som countis with high hurrican risks ar mor covrd by th Florida Citizns compard to othr countis. 4.4 Rsults 4.4. Rsults of Hypothsis I Tst Rcall that Hypothsis I stats that migration to Florida high risk aras ar positivly associatd with a subsidy from govrnmnt programs, such as th Florida Citizns and th National Flood Insuranc Program. With lowr prmiums providd by th govrnmnt insuranc programs in rlativly high risk aras, popl could obtain homownrs insuranc covrag at lowr prics. Thn rsidnts could b mor attractd to rlocat to Florida s high risk aras all othr things bing qual. With th inadquat insuranc prmiums and incrasing xposurs in ths aras, th homownrs insuranc markt may incur dvastating losss onc hurricans hit th stat. In th xtrm cas, th privat markt may collaps and th govrnmnt taks ovr th markt. Th rlationship btwn th population growth, th provision of th Florida Citizns and th Flood Insuranc in th Florida homownrs insuranc markt ar xamind from 998 to

114 007. Th mpirical tsts ar prformd at thr lvls: xposurs, dirct writtn prmiums and policy numbrs in forc. Tabl 8. summaris th mpirical rsults whn th Florida Citizns markt shar in xposurs and th Flood Insuranc covrag ar takn into account as th xplanatory variabls. Four random ffct modls with various sts of xplanatory variabls ar applid according to Hausman tst and prsntd in ordr. In Modl A th variabl of th Flood Insuranc covrag is statistically significant with th stimatd cofficint of 0.385, whil Modl A uss th lag of Flood Insuranc covrag instad which shows a smallr ffct on th population incras. Th rsults can b xplaind as prcntag incras of th Flood Insuranc covrag is associatd with around 0.04 prcnt of population incras ovrall all othrs bing qual. To control th population siz ffct, th Flood Insuranc covrag is normalizd by dividing th population. Th cofficints of th normalizd Flood Insuranc covrag and th corrsponding lag variabl ar still statistically significant as shown in Modl C and D, which rconfirms that th provision of govrnmnt programs is positivly rlatd to th population incras in th stat of Florida. Th Citizns markt shar in xposurs, howvr, is not statistically significant to population changs in all four modls as shown in Tabl 8.. In addition, th control variabl of incom is statistically significant, and positivly rlatd to th population incras, which is consistnt with th prvious litratur. Thus, th highr th incom pr capital, th highr th population growth rat is. In thr scnario tsts, th cofficints of th dummy of th South Atlantic ara ar significantly ngativ, which implis that th South Atlantic ara xprincs a low rat of population growth compard to th innr aras of Florida during th study priod. Tabl 8. provids th rgrssion rsults whn th govrnmnt intrvntion is masurd as dirct writtn prmiums. Modl B-B4, fixd ffct or random ffct modls basd on 3

115 Hausman tst, ar applid taking account into th dirct writtn prmiums of Flood Insuranc, normalizd dirct writtn prmiums and lags of thos two variabls, rspctivly. Among th four masurs of th Flood Insuranc provision, only th lag of th Flood Insuranc dirct writtn prmiums is statistically significant and positivly rlatd to th population growth. Th stimatd cofficint is 0.53, which mans that prcnt incras of Flood Insuranc prmium in th prvious yar is associatd with prcnt of population growth. Tabl 8.3 shows th rsults whn th Citizns markt shars in policy numbrs and Flood Insuranc policy numbrs in forc ar xamind. In this cas, only th variabl of Flood Insuranc policy numbrs is statistically significant, and th positiv cofficint implis a positiv rlationship btwn th Flood Insuranc policy numbrs and population growth. To look into th county ffct on th population growth in dtail in lin with othr variabls of intrst, 67 countis ar includd in th rgrssion to xamin th spcific ffct of ach county on th population growth. Th omittd or dfault county in th rgrssion is st to Miami-Dad County, and th othr 66 countis ar cratd as dummy variabls. Tabl 8.4 provids th stimatd cofficints on county population growth rat with county dummis. Th sam as prvious tsts, lag of th Flood Insuranc covrag and th corrsponding normalizd variabl ar significantly positiv, vn to a larg xtnt, at.8 and.399. Th variabl of incom is positivly associatd with th population growth as wll. With rspctiv to th county dummis, surprisingly, most cofficints ar statistically significant and positiv, which mans that ths countis xprinc a highr population growth compard to Miami-Dad. As discussd abov, a coupl of factors, such as th xistnc of rsidual insuranc and Flood Insuranc, can contribut to th population changs upon th occurrnc of hurricans. A structural brak of growth rat bfor and aftr hurricans, thrfor, is xpctd in such 4

116 circumstancs. Th ffcts on population growth rats of Florida two yars bfor and aftr hurrican sasons ar xamind accordingly by using Chow tst. Th rsults vary with or without inclusion of county dummis. Whn county dummis ar omittd from othr xplanatory variabls, th structural brak dos not xist by failing to rjct th null hypothsis that ffcts of xplanatory factors on growth rats ar sam bfor and aftr hurrican sasons. Th addition of county dummis, howvr, gnrats a contrary rsult that suggsts indpndnt variabls hav diffrnt ffcts on growth rats bfor and aftr hurricans. In sum, th supportiv vidncs on Hypothsis I ar found that migration within Florida is associatd with th National Flood Insuranc Program during th study priod bcaus th stimatd cofficints of th variabl of Flood Insuranc ar statistically significant and positiv. Manwhil, th prsnc of th Florida Citizns dos not impos th significant ffct on th population growth Rsults of Hypothsis II Tst Hypothsis II stats that insurrs in th privat sctor assum mor risks in hurricanpron aras with th provision of th CAT Fund and th Flood Insuranc. This tst is dsignd to xamin th ffcts of govrnmnt-fundd insuranc programs on th risk-taking bhaviors of proprty insuranc companis in Florida from 998 to 007. Tabl 8.5 provids th stimatd cofficints on homownr insuranc xposurs whn th Citizns markt shar, CAT Fund purchass and Flood Insuranc covrag ar takn into account. Modls D to D4 account for th xplanatory variabls of Flood Insuranc covrag, normalizd Flood Insuranc covrag and lags of Flood Insuranc covrag. All four modls show that th prsnc of th Citizns is ngativly rlatd to th homownr insuranc xposurs, and th provision of th CAT Fund 5

117 and th Flood Insuranc ar positivly associatd with th privat homownrs insuranc xposurs covrd. Th stimatd cofficint of th Citizns markt shar in trms of xposurs is statistically significant and ngativ at -0.04, which mans that prcnt of Citizns xpansion will rduc th privat markt in trms of xposurs by 0.04 prcnt all othrs bing qual. Non of th prvious litratur, to my bst knowldg, has mpirically xamind th ffct of th rsidual markt on th privat sctor, although a numbr of scholars indicat that th Florida Citizns has bcom mor and mor aggrssiv in its pricing and has discouragd th dvlopmnt of th privat markt Grac & Klin, 007; Klin, 008. Th stat-fundd rinsuranc program, th CAT Fund, plays a significant rol in boosting th privat insuranc markt as prcnt of catastroph fund purchas lads to 4 prcnt incras in xposurs covrd all othrs bing qual. Th rsults also show that national flood insuranc supplmnts th dvlopmnt of th homownr insuranc markt to a lssr xtnt compard to th catastroph fund. Th insuranc pric variabl at th county lvl, which is dfind as homownr insuranc prmiums dividd by xposurs by county, is statistically significant and ngativ whn th rgrssor of th Flood Insuranc covrag is normalizd by population. Th highr th pric chargd in a county, th lowr th insurd xposurs. County incom is shown to b positivly associatd with homownr insuranc xposurs, which suggst that walthy countis hav mor xposurs covrd. In addition, Kunuthr t al 009 showd that th incom lasticity was positiv for homownrs insuranc in Florida. Firm charactristic variabls dscribing firms financial capacity and stability, such as assts and lvrag, show a positiv ffct on th insurrs undrwrittn xposurs. Highr lvrag ratio implis firms borrow mor dbts to financ thir businss and may ncountr 6

118 financial problms whn thy fail to rpay th dbts on tim. In this sns, th firms with highr lvrag ratio can b rgardd as financially risky insurrs. Thrfor, th vidnc that th variabl of lvrag ratio is positiv to xposurs covrd shows that risky firms aggrssivly undrwrit in th markt with th provision of govrnmnt insuranc programs. This finding supports th hypothsis of moral hazard problm arising from insurrs. With rspct to location ffcts, th South Atlantic ara is statistically diffrnt from th intrior parts of th stat, and has a ngativ rlationship with th homownr insuranc xposurs. Tabl 8.6 summarizs th rgrssion rsults on homownr insuranc dirct writtn prmiums. Th variabls of th Flood Insuranc prmiums, lag of th Flood Insuranc prmiums, normalizd and lag of normalizd Flood Insuranc ar includd in Modl E to E4 rspctivly. Th prsnc of th CAT Fund and th Flood Insuranc ar tstd to b statistically significant and positiv to th homownr insuranc prmiums. With rspctiv to firms charactristics, th variabls of siz, rturn on quity, lvrag and liquidity ar shown to b statistically significant. Whil th siz, rturn on quity and lvrag ar positivly rlatd to th homownr insuranc prmiums, th variabl of liquidity is ngativly associatd with th homownr insuranc prmiums. Sinc liquidity capturs how rapidly firms convrt assts into cash, lowr liquidity indicats th insurrs may hav difficulty in paying claims causd by catastrophic losss whn thy ar not abl to convrt assts into cash quickly. Hnc, th ngativ rlationship btwn th liquidity and th homownr insuranc prmiums implis that firms with lowr liquidity, surprisingly, ar undrwriting mor homownr insuranc. This finding supports th hypothsis of moral hazard problm that risky insurrs advrsly undrwrit mor homownr insuranc with th provision of govrnmnt insuranc programs, such as th CAT Fund and th Flood 7

119 Insuranc. Tabl 8.7 prsnts th rsults whn th homownr insuranc policy numbrs in forc ar xamind in rgrssions, which gnrat similar rsults as shown in Tabl 8.6. To xamin th spcific ffcts of ach county on homownr insuranc, 66 county dummis ar includd in th mpirical tsts. Th rgrssion rsults ar prsntd in Tabl 8.8, Tabl 8.9 and Tabl 8.0. Th omittd county is Miami-Dad, and th stimatd cofficints of ach county show th rlativ ffct on th homownr insuranc purchas with rspct to Miami-Dad. To b concis, ight countis from four risk catgoris in th stat ar slctd, and th stimatd cofficints of ths rprsntativ countis ar rportd in th tabls. As rportd in Tabl 8.8, th stimatd cofficints of County Clay and Volusia in North Atlantic ara, Sarasota in Gulf Coast, and Franklin in Panhandl ara ar statistically significant and positiv to th homownrs insuranc xposurs. It implis that mor xposurs ar likly to b covrd in ths aras in th stat of Florida rlativ to Miami-Dad. This finding is consistnt with th obsrvation of Klin 008 that insurrs had rtrnchd from th hurrican-pron zons aftr catastrophic losss in th last two dcads. Th pattrn, howvr, is not obvious whn homownr insuranc prmiums and policy numbrs in forc ar considrd. In sum, th county ffct on th homownr insuranc sms to b mixd in this cas. To invstigat th spcific firm ffct on th privat insuranc markt, firm dummis ar includd in th rgrssion analysis. Thr ar 54 firms in th datast in total, which wr in businss in Florida from 997 to 007. Stat Farm is st as th omittd firm, and th othr 53 firms ar dnotd as dummis. Tabl 8. prsnts th stimation rsults with th slctd countis and firms dummis. Four rprsntativ insurrs ar chosn basd on th firm siz and th tim thy ar in businss: Allstat Insuranc Company, a big insurr; Lumbrmns Mutual Casualty Company, a mdium-sizd company; 3 Mrastar Insuranc Company, nw 8

120 ntrant sinc 000; and 4 Auto Club South Insuranc Company, a nw insurr sinc 005. Allstat shows no statistically significant ffct on th homownrs insuranc xposurs compard to Stat Farm, which could b xplaind by th similar big siz of thos two firms. Th stimatd cofficints of Lumbrmns and Auto Club ar statistically significant and positiv, implying thos two insurrs ar mor willing to undrwrit businss in Florida compard to Stat Farm. It is worth noticing that, as a rgional insurr with a short businss history, Auto Club aggrssivly undrwrits in hurrican-pron aras. From th mpirical rsults, th Florida Citizns is obsrvd to compt with th privat insuranc markt by rducing th homownr insuranc markt to a limitd xtnt. Th provision of govrnmnt-run insuranc programs has promotd th xpansion of th insuranc markt in Florida partly as hopd by rgulators and lgislators. Manwhil, lss liquid insurrs and nw insurrs in th markt sk to undrwrit mor homownr insuranc in th markt with th subsidy from th govrnmnt, whr moral hazard may b th cas. 5. Conclusion Th stat of Florida has suffrd from a numbr of larg hurrican losss for yars. How to provid stabl and sustainabl insuranc to proprty ownrs in th stat has bn of intrst to lgislators and rgulators. Florida Citizns, as wll as othr govrnmnt-fundd insuranc programs, such as th CAT Fund and th Flood Insuranc, wr stablishd to addrss th issu of covrag availability. This ssay xamins th ffcts of thos public policis on Florida s population growth and th privat insuranc markt from 998 to 007 by stting up two hypothss and carrying on mpirical tsts,. Th supporting vidnc suggsts that th public 9

121 policis, which impos havy insuranc rgulation and involvmnt in th privat markt, may crat moral hazard problms in th homownr insuranc markt in Florida. To tst th ffct of public policis on th popl s incntivs to mov to high-risk aras, th migration to Florida is hypothsizd to b positivly associatd with th implmntation of govrnmnt insuranc, such as th Florida Citizns or th Flood Insuranc. Du to th major contribution of migration to population growth and data limitation, th annual population growth rats by county in Florida ar usd instad. I find that th provision of th Flood Insuranc is positivly associatd with th population growth in th stat of Florida, whil th cofficint of Citizns is not statistically significant. Th risk of flood is xcludd from th rsidntial insuranc policis bcaus of its uninsurabl charactristics, but th insuranc covrag for such risk is critical to th financial scurity of rsidnts in hurrican-pron aras in Florida. By providing Flood Insuranc to proprty ownrs in th high risk zons, th fdral govrnmnt fills th gap which may howvr ntail cross subsidization btwn high and low risks. Th rsults suggst that flood insuranc lurs mor popl to liv in highr-risk aras than thy would othrwis, which could b xplaind by moral hazard problm that migrants tak advantag of subsidizd insuranc providd by th fdral govrnmnt at lowr prmiums. In trms of homownr insuranc markt, privat insuranc companis ar hypothsizd to assum mor risks in th hurrican-pron aras with th provision of th CAT fund and th Flood Insuranc, whil th Citizns may compt with th dvlopmnt of th privat markt. Th rsults show that th CAT fund and th Flood Insuranc ar positivly associatd with th xposurs of insurrs, and th Florida Citizns is ngativly rlatd to th undrwriting of insurrs. Bsids, th incom lasticity of homownrs insuranc dmand is positiv, which is consistnt with th prvious litratur. Th location of countis, howvr, dos not hav strong 0

122 ffct on th risk-taking bhavior of privat insurrs. Howvr, insurrs with lss liquidity and high lvrag ar found to undrwrit mor homownr insuranc, which imposs a svr moral hazard issu in th homownr insuranc markt. Manwhil, som nw ntrants, small rgional insurrs, to th markt ar found to aggrssivly writ businss compard to th big insuranc companis such as Allstat and Stat Farm. Ths nw playrs hav filld th covrag gap lft by th rtrnching companis as xpctd to insuranc rgulators and lgislaturs, but thir lack of undrwriting xprincs and financial capability may mak thm fail to mt thir obligations whn hurrican striks th stat of Florida.

123 Rfrncs Alfrd, E.K. 970 Th Economics of Rgulation: Principls and Institutions, Th MIT Prss. Akrlof, G Th Markt for Lmons : Quality Uncrtainty and th Markt Mchanism, Th Quartrly Journal of Economics, 843, Bator, F.M Th Anatomy of Markt Failur, Th Quartrly Journal of Economics, 73, Brnstain, Marvr H Rgulating Businss by Indpndnt Commission Princton Univrsity Prss. Brgr, L. J., Cummins, J.D., and Tnnyson, S. 99. Rinsuranc and th Liability Crisis. Journal of Risk and Uncrtainty, 5, Bonbright, J.C. 96. Principls of Public Utility Rats. Columbia Univrsity Prss, Nw York. Col, C.R., McCullough, K.A., and Powll, L Rgulation of Rinsuranc Rcovrabl: Protction or Protctionism? Working papr at Florida Stat Univrsity. Conway, K.S. and Houtnvill, A.J Eldrly Migration and Stat Fiscal Policy: Evidnc from th 990 Cnsus Migration Flows, Aging Studis Program Papr No. 3, Cntr for Policy Rsarch Maxll School of Citiznship and Public Affairs, Syracus Univrsity. Cummins, J.D Should th Govrnmnt Provid Insuranc for Catastrophs? Fdral Rsrv Bank of St. Louis Rviw, 88, Cummins, J.D Rinsuranc for Natural and Man-Mad Catastrophs in th Unitd Stats: Currnt Stat of th Markt and Rgulatory Rforms. Risk Managmnt and Insuranc Rviw, 0, Cummins, J.D., and Wiss, M.A. 99. Th Structur, Conduct, and Rgulation of th Proprty-Liability Insuranc Industry, in: r. Kopck and R. Randall, ds., Th Financial

124 Condition and Rgulation of Insuranc Companis Boston: Fdral Rsrv Bank of Boston. Davis, P.S., Grnwood, M.J. and Li, H. 00. A Conditional Logit Approach to U.S. Stat- To-Stat Migration, Journal of Rgional Scinc, 4: Faulhabr. G.R. 975, Cross-Subsidization: Pricing in Public Entrpriss, Th Amrican Economic Rviw, 655, Florida Dpartmnt of Insuranc, 993. Hurrican Andrw s Impact on Insuranc in th Stat of Florida. Fbruary, 993. Florida Dpartmnt of Insuranc, 994. Hurrican Andrw Emrgncy Ruls and Hurrican Andrw Emrgncy Rul Summary. Tallahass, FL: Florida Dpartmnt of Insuranc. Florida Hous of Rprsntativs. Committ on Insuranc, 993. Final Bill Analysis & Economic Impact Statmnt, HB89-B. Prpard by Lonard Schult, Staff Attorny, and Brian J. Dffnbaugh, Staff Dirctor. Jun 8. Tallahass, FL: Florida Hous of Rprsntativs. Committ on Insuranc. Florida Hous of Rprsntativs. Committ on Insuranc, 995. Final Bill Analysis & Economic Impact Statmnt, HB79. Prpard by Lonard Schult, Staff Attorny, and Brian J. Dffnbaugh, Staff Dirctor. March 8. Tallahass, FL: Florida Hous of Rprsntativs. Committ on Insuranc. Florida Snat. Committ on Banking and Insuranc, 997. Snat Staff Analysis and Economic Impact Statmnt, SB794. Prpard by Grn, Staff Analyst, and Brian J. Dffnbaugh, Staff Dirctor. March 5. Tallahass, FL: Florida Snat. Committ on Banking and Insuranc. 3

125 Florida Offic of Insuranc Rgulation, 008. Summary of Confrnc Committ Rport on Hurrican Prpardnss and Insuranc. Fry, W. H Boomrs and Sniors in th Suburbs: Aging Pattrns in Cnsus 000. Washington D.C: Th Brookings Institution, Cntr on Urban and Mtropolitan Policy. Froot, K. A On th Pricing Intrmdiatd Risks: Thory and Application to Catastroph Rinsuranc. Papr prsntd at th National Burau of Economic Rsarch, Novmbr -3. Gorgia Stat Univrsity, Wharton School, and Insuranc Information Institut, 007. Managing Larg-Scal Risks in a Nw Era of Catastrophs Philadlphia, PA Grac, M. F., Klin, R.W., and Klindorfr, P. R Th Dmand for Homownrs Insuranc with Bundld Catastroph Covrags. Journal of Risk and Insuranc, 7, Grac, M. F., and Klin, R.W Facing Mothr Natur. Rgulation, 303, Grac, M. F., and Klin, R.W. 008a. Th Prfct Storm: Hurricans, Insuranc and Rgulation. Working papr at Cntr for Risk Managmnt and Insuranc Rsarch, Gorgia Stat Univrsity. Grac, M. F., and Klin, R.W. 008b. Th Post and Futur of Insuranc Rgulation: Th McCarran-Frguson Act and Byond post-symposium rvision Rsarch Symposium on Insuranc Markts and Rgulation. Grac, M.F., Klin, R.W., Klindorfr, P.R. and Murray, M.R. 003 Catastroph Insuranc: Consumr Dmand, Markts and Rgulation, Kluwr Acadmic Publishr, Boston/Dordcht/London. 4

126 Grac, M.F., Klin, R.W., Liu, Z. 005 Incrasd Hurrican Risk and Insuranc Markt Rsponss, Journal of Insuranc Rgulation, 5, 3-3. Hansn, Gary D. and Imrohoroglu, Ays. 99. Th Rol of Unmploymnt Insuranc in an Economy with Liquidity Constraints and Moral Hazard, Th Journal of Political Economy, 00, 8-4. Harrington, Scott E., 000 Rthinking Disastr Policy, Rgulation, 3, Insuranc Information Institut Profits: Florida Proprty Insuranc and Profitability, Nw York, August. Jordan, William. 97. Producr Protction, Prior Markt Structur and th Effcts of Govrnmnt Rgulation, Journal of Law and Economics, 5, Klin, R. W. 009a. Hurrican Risk and Proprty Insuranc Markts: An Updat and Extnsion. Wharton Extrm Evnts Projct, April st, 009. Klin, R. W. 009b. Hurricans and Rsidual Markt Mchanisms. Wharton Extrm Evnts Projct, May 9 th, 009. Klin, R. W. 009c. Hurrican Risk and th Rgulation of Proprty Insuranc Markts. Wharton Extrm Evnts Projct, July 7 th, 009. Klin, R. W Catastroph Risk and th Rgulation of Proprty Insuranc. Papr prsntd at Amrican Risk and Insuranc Association 008 annual mting, August Klin, R. W Insuranc Rgulation in Transition, Th Journal of Risk and Insuranc, 63, Klin, R.W., and Klindorfr P. R Th Supply of Catastroph Insuranc undr Rgulatory Constraints. Working papr in Financial Institutions Cntr at Wharton School. 5

127 Klin, R. W., and Wang S Catastroph Risk Financing in th Unitd Stats and th Europan Union: A Comparison of Altrnativ Rgulatory Approachs. Papr prsntd at th Nw Forms of Risk Sharing and Risk Enginring: A SCOR-JRI Confrnc on Insuranc, Rinsuranc, And Capital Markt Transformations, PARIS, Sptmbr 0-, 007. Kolko, Gabril Railroads and Rgulation Princton Univrsity Prss. Lai, L.H., and Hsih, H.Y Assssing th Dmand Factors for Rsidntial Earthquak Insuranc in Taiwan: Empirical Evidnc on Spatial Economtrics. Contmporary Managmnt Rsarch, 34, Lnzi, A, and Millo, G Rgional Htrognity and Spatial Spillovrs in th Italian Insuranc Markt. Working papr. Lwis, C. M., and Murdock K. C Th Rol of Govrnmnt Contracts in Discrtionary Rinsuranc Markts for Natural Disastrs. Journal of Risk and Insuranc, 63, Mir, K.J Th Political Economy of Rgulation: Th Cas of Insuranc Albany: Stat Univrsity of Nw York Prss. Mittlr, E A Cas Study of Florida s Homownrs Insuranc Sinc Hurrican Andrw, working papr 96 in Univrsity of Colorado at Bouldr. Munch, P. and Smallwood, D.E. 98 Thory of Solvncy Rgulation in th Proprty and Casualty Insuranc Industry, in: Gary Fromm, d., Studis in Public Rgulation Cambridg, Mass: MIT Prss. Musgrav, R.A. and Musgrav, P.B. 984 Public Financ in th Thory and Practic, McGraw-Hill Companis. 6

128 Muslin, R.T. 996 Proprty Insuranc Markt Crisis, Prsntation to th Institut for Intrnational Rsarch, Nw York, NY. National Ocan Srvic, National Ocan and Atmosphric Administration 008 Population Trnds along th Costal Unitd Stats: Offic of Economics and Dmographic Rsarch 009. Florida Dmographic Summary. Pauly, M.V.968. Th Economics of Moral Hazard: Commnt, Th Amrican Economic Rviw, 583: Pauly, M.V.974. Ovrinsuranc and Public Provision of Insuranc: Th Rols of Moral Hazard and Advrs Slction, Th Quartrly Journal of Economics, 88, Pltzman, Sam Toward a Mor Gnral Thory of Rgulation, Journal of Law and Economics, 9, -40. Rosnzig, M.R. and Wolpin, K.I Migration Slctivity and th Effcts of Public Programs, Journal of Public Economics, 37: Rothschild, M. and Stiglitz, J.E. 976 Equilibrium in Comptitiv Insuranc Markts: An Essay on Imprfct Information, Th Quartrly Journal of Economics, 904, Schrr, F.M Industrial Markt Structur and Economic Prformanc, scond dition, Houghton Mifflin Company, Boston, Dallas, Gnva, Hopwll, N.J., Palo Alto, London. Schrr, F.M. and Ross, D.S., 990. Industrial Markt Structur and Economic Structur, Boston: Houghton-Mifflin. Schmalns, R Th Control of Natural Monopolis, Lxington, Mass. Sjaastad, L.A. 96. Th Costs and Rturns of Human Migration, Th Journal of Political Economy, 705: Invstmnt in Human Bings:

129 Skippr, H.D. and Klin, R.W., 999 Insuranc Rgulation in th Public Intrst: Th Path Towards Solvnt, Comptitiv Markts, Coordinating Committ on Intrnational Insuranc Issus Coalition of Srvic Industris. Stiglr, Gorg J. 97. Th Thory of Economic Rgulation, Bll Journal of Economics and Managmnt Scinc,, 3-. Williamson, O.E. 97. Th Vrtical Intgration of Production: Markt Failur Considrations, Th Amrican Economic Rviw, 6, -3. 8

130 $50.0 $45.0 $40.0 $35.0 $30.0 $5.0 $0.0 $5.0 $0.0 $5.0 $0.0 $4.0 Jann 004 Figur Insurd Losss of Costlist Disastrs in U.S. History 007 $Billions $5.0 Francs 004 $6.00 $7.00 $7.80 $8.0 Rita 005 Hugo 989 Ivan 004 Charly 004 $0.70 $0.90 $0.90 Ik 008* Wilma 005 Northridg 004 $.00 $.90 9/ Attacks 00 * PCS stimats as of /5/08. Sourcs: ISO/PCS; AIR Worldwid, RMS, Eqcat; Insuranc Information Institut inflation adjustmnts, 008. Figur Insurd Losss* of Florida's 0 Costlist Hurricans, $Billions Andrw 99 $43.60 Katrina 005 $5.00 $.0 $0.00 $5.00 $0.90 $0.00 $8.0 $5.00 $- $0.48 $0.58 $0.9 Erin 995 Katrina 005 Dnnis 005 $.90 Opal 995 $3.30 Jann 004 $4.70 $4.70 Francs 004 Ivan 004 Charly 004 Wilma 005 Andrw 99 *Florida losss only Sourcs: Insuranc Information Institut inflation adjustmnts, 008. Figur 3 9

131 Comparison of Homownrs Insuranc Rat pr $000 by County Florida: 997, 000 and 003 $35.00 $30.00 $5.00 $0.00 $5.00 $0.00 $5.00 $- Monro Dad Franklin Lon Clay 997Q 000Q 003Q Figur 4 Comparison of Homownrs Insuranc Rat pr $000 by County Florida: 003, 006 and 007 $40.00 $35.00 $30.00 $5.00 $0.00 $5.00 $0.00 $5.00 $- Monro Dad Franklin Lon Clay 003Q 006Q4 007Q4 30

132 Figur 5 Florida Stat County Map 3

133 Figur 6 Undrwriting Gains Losss of Florida Homownr Insuranc* $Billions $6.00 $4.00 $.00 $- $.00 $4.00 $6.00 $8.00 $0. $0.69 $0.43 $0.86 $.08 $.3 $.8 $.43 $.5 $.38 $.76 $3.77 $.96 $3.40 $0.00 $.00 $0.60 $ *Dos not includ Citizn Proprty Insuranc Corporation Sourc: Insuranc Information Institut Figur 7 Accumulativ Undrwriting Gains Losss of Florida Homownr Insuranc* $Billions $.0 $- $0.5 $.0 $4.0 $6.0 $8.0 $0.0 $.0 $4.0 $5. $6.5 $7.8 $8.8 $0. $9.7 $0.6 $0.8 $3.8 $.7 $.3 $8.8 $.6 $ $6. *Dos not includ Citizn Proprty Insuranc Corporation Sourc: Insuranc Information Institut 3

134 Figur 8 ISO Loss Cost Filings: Florida Homownrs Insuranc 99, 99, 995, 996 and % 7.% Prcntag Chang 50.0% 00.0% 50.0% 0.0% -50.0% -3.3% -3.3% -3.3% -.% -.% -.% 9.3% 77.5% 55.% 48.7% 3.% -0.% -.8%-4.7% Indicatd Fild Implmntd Sourc: Insuranc Srvic Offic Figur 9 Florida Rsidntial Proprty and Casualty Joint Undrwriting Association Policy Numbrs and Exposurs from 993 to Policis 000s Exposurs $B Sourc: FRPCJUA Policis 000s Exposurs $B 33

135 Figur 0 Florida Windstorm Undrwriting Association Policy Numbrs and Exposurs: Policis 000s Exposurs $B Policis 000s Exposurs $B Sourc: Insuranc Information Institut, Florida Insuranc Council Figur Florida Citizns Exposurs to Losss Billions $ $ $ $ $ $50.00 $00.00 $50.00 $00.00 $50.00 $- $ $454.0 $ $95.50 $06.70 $0.60 $ * 008** *Florida Citizns data, as of March 3, 007. **As of April, 30, 008. Sourc: PIPSO; Florida Citizns; Zurich Amrican Insuranc Co; Insuranc Information Institut Tabl 34

136 Risk Aras Catgoris in Florida Aras Numbr Countis North Atlantic ara 5 Bakr, Bradford, Brvard, Clay, Duval, Flaglr, Lak, Nassau, Orang, Oscola, Putnam, Sminol, St. Johns, Union, Volusia South Atlantic ara 8 Broward, Dad, Indian Rivr, Martin, Monro, Okchob, Palm Bach, St. Luci Gulf Coast ara Alachua, Charlott,Citrus, Collir, Dsoto,Dixi, Gilchrist, Glads, Hard, Hndry, Hrnando, Highlands, Hillsborough, L,Lvy, Manat, Marion, Pasco, Pinllas, Polk, Sarasota, Sumtr Panhandl ara Bay, Calhoun, Columbia, Escambia, Franklin, Gadsdn, Hamilton, Holms, Jackson, Jffrson, Lafaytt, Lon, Librty, Madison, Okaloosa, Santa Rosa, Suwann, Taylor, Wakulla, Walton, Washington Tabl Homownrs Insuranc Markt Concntration Forida: Yar CR4 CR8 CR0 HHI % 70.9% 85.%, % 7.6% 85.6%, % 7.9% 86.7%, % 7.% 87.4%, % 7.5% 87.0%, % 63.8% 8.9%, % 64.9% 83.% % 6.7% 80.0% % 6.% 78.7% % 60.% 78.4% % 59.% 79.6% % 59.9% 8.7% % 6.4% 83.8% % 60.0% 78.7% % 54.5% 75.6% % 48.5% 65.9% 6 Sourc: NAIC Financial Databas; author's calculation 35

137 Tabl 3 Changs in Lading Insurrs' Markt Shar Florida -- 99, 003, 005, Nam Rank DPW MS% Rank DPW MS% Stat Farm,560,467,34.0%,75,850,37 0.7% USAA 379,397,00 5.4% 6 53,944, % Towr Hill 3 3,833,5 4.5% 4 85,94, % Allstat 4 88,83,830 4.% 495,663, 8.7% Nationwid 5 50,339, % 5 74,96, % Librty Mutual 6 39,55, % 7 7,70, % ARX Holding Corp Grp 7 7,663,690 3.% 6,834,63.% AIG 8 75,568,06.5% 0 9,7,708.% Univrsal Ins Grp 9 73,79,567.5% 5 8,50,.4% Chubb & Son 0 64,855,44.3% 9 4,90,363.% Hartford 33,95,58.9% 7,478,875.% Travlrs 09,65,75.5% 8 4,905,507.% Southrn Farm Burau 3 08,5,804.5% 6 78,785,58.4% st Cntury Holding Grp 4 00,48,479.4% 7 77,53,454.4% Zurich 5 9,934,700.3% 9 65,03,55.% Homwis 6 75,08,968.% Cyprss Holdings Grp 7 74,980,353.% 0 6,995,348.% Allianz 8 74,980,353.% 54,853,987.0% GoVra Holdings Inc Grp 9 7,59,89.0% 3,695,87.0% Northrn Capital Grp 0 56,09,06 0.8% Nam Rank DPW MS% Rank DPW MS% Stat Farm 90,469, % 653,47, % USAA 3 0,975,40 5.% 3 95,7,08 4.4% Towr Hill 3 73,39,48.9% Allstat 437,8,38.4% 436,39,66 0.3% Nationwid 4 9,647, % 5 88,595,495 4.% Librty Mutual 8,34,96 3.% 3,534,99.5% ARX Holding Corp Grp 5 65,45,493.7% AIG 78,866,93.0% 53 3,77,785 0.% Univrsal Ins Grp Chubb & Son 9 0,35,909.6% 6 6,874,90.9% Hartford 0 93,95,838.4% 9 49,88,47.3% Travlrs 7 35,849,59 3.5% 4 89,664,45 4.% Southrn Farm Burau 4 68,07,879.8% 7,78,096 0.% st Cntury Holding Grp 5 9,446, % Zurich 0 38,74,883.0% 50 3,404,647 0.% Homwis Cyprss Holdings Grp 8 50,99,77.3% Allianz 9 47,65,74.% 6,658,63 0.5% GoVra Holdings Inc Grp Northrn Capital Grp Sourc: NAIC Financial Databas; author's calculation 36

138 Tabl 4 Profitability of Florida Homownr Insuranc Yar Profit on Insuranc Transactions Rturn on Nt Worth % -4.8% % 3.% %.3% % 7.0% % 6.% % 3.3% % 6.9% % -74.9% % -6.% 994.8% 35.4% % 3.% 996.0% 33.6% 997.% 3.5% 998.% 9.3% 999.% 8.6% % 3.3% 00 5.% 3.% 00 9.% 9.0% % 35.7% % -83.3% % -53.4% % 3.% % 39.0% Avrag -7.6% -.7% Sourc: NAIC 37

139 Tabl 5 Variabls Dscriptions and Data Sourc Variabl Labl Dfinition Sourc Population Growth in Prcntag PG Population growth rat in prcntag Florida Dmographic Databas HO Exposurs HO EXP Log of xposurs of homownr insuranc QUASR databas by Florida OIR HO Prmiums HO DPW Log of dirct writtn prmiums of QUASR databas by Florida OIR homownr insuranc HO Policy Numbrs HO PIF Log of policy numbrs in forc of QUASR databas by Florida OIR homownr insuranc Citizns Markt Shar in Exposurs FC EXP Florida Citizns' markt shar in xposurs NAIC financial databas Citizns Markt Shar in Prmiums FC DPW Florida Citizns' markt shar in dirct NAIC financial databas writtn prmium Citizns Markt Shar in Policy Numbrs FC PIF Florida Citizns' markt shar in policy NAIC financial databas numbrs in forc CAT Fund Purchas in Prcntag PTCF Th prcntag of FHCF purchas out of NAIC financial databas total rinsuranc arrangmnts Flood Insuranc Covrag FI COV Log of covrags of flood insuranc FEMA Flood Insuranc Dirct Writtn Prmiums FI DPW Log of dirct writtn prmiums of flood FEMA insuranc Flood Insuranc Policy Numbrs in Forc FI PIF Log of policy numbrs in forc of flood FEMA insuranc Flood Insuranc Covrag Normalizd by FI COV Logcovrags of flood FEMA Population insuranc/population Flood Insuranc Dirct Writtn Prmiums FI DPW Th dirct writtn prmiums of flood FEMA Normalizd by Population insuranc dividd by population Flood Insuranc Policy Numbrs pr 00 FI PIF Th policy numbrs in forc of flood FEMA Population insuranc pr 00 population Pric Proxy at Firm Lvl AP Homownr insuranc dirct writtn prmiums dividd by xposurs for a firm NAIC financial databas Pric Proxy at County Lvl APCT Homownr insuranc dirct writtn NAIC financial databas prmiums dividd by xposurs in a county Pr Capital County Incom Incom County incom dividd by population Rgional Economic Information Systm, Burau of Economic Analysis, U.S. Dpartmnt of Commrc Crim Rat pr 00 Population Crim Indx crim and offns pr 00 population Florida Dpartmnt of Law Enforcmnt* Siz Siz Log of toal asssts of a firm A.M. Bst Company Rturn on Equity ROE Nt incom dividd by quity of a firm A.M. Bst Company Lvrag lvrag Consolidatd balanc sht dbt-to-capital A.M. Bst Compnay ratio unadjustd** Liquidity Liquidity Currnt liquidity masurd as th A.M. Bst Company proportion of liabilitis covrd by ncumbrd cash and unaffiliatd invstmnts*** * accssd May 30, 009 ** accssd May 30, 009 *** accssd May 30,

140 Tabl 6 Florida Population and Exposurs by County 007 Prcnt Amount of Insuranc 007 Prcnt Amount of Insuranc County 000 Cnsus Estimat Chang % in Forc 007 County 000 Cnsus Estimat Chang % in Forc 007 Alachua 7,955 47,56 3.6% 7,87,40,80 Madison 8,733 9, % 76,895,38 Bakr,59 5,63 5.%,348,378,8 Manat 64,00 35, % 798,75,45 Bay 48,7 67,63 3.%,586,77,068 Marion 58,96 35,03 5.5% 37,737,346,676 Bradford 6,088 9,055.4%,33,397,00 Martin 6,73 43, % 9,899,53,95 Brvard 476,30 55,09 5.9% 57,08,66,488 Miami-Dad,53,779,46,9 9.3%,38,80,053 Broward,63,08,765, % 5,90,869,84 Monro 79,589 78, % 893,437,40 Calhoun 3,07 4,477.% 550,949,3 Nassau 57,663 69, % 7,793,853,6 Charlott 4,67 64,584 6.% 4,066,309,445 Okaloosa 70,498 96, % 8,70,00,644 Citrus 8,085 40,4 8.7% 6,84,847,33 Okchob 35,90 39, %,454,039,365 Clay 40,84 84,644 3.% 8,64,380,45 Orang 896,344,05, % 0,868,39,437 Collir 5, , % 49,55,058,778 Oscola 7,493 66,3 54.3% 6,70,935,648 Columbia 56,53 65, % 3,638,539,54 Palm Bach,3,9,95, % 33,9,45,49 DSoto 3,09 33, % 00,454,59,030 Pasco 344, ,45 6.0% 4,57,776,403 Dixi 3,87 5, %,03,87,749 Pinllas 9, ,99.5% 80,6,478,554 Duval 778, ,597 5.% 577,64,99 Polk 483,94 58,058 0.% 5,908,43,583 Escambia 94,40 3, % 7,740,574,34 Putnam 70,43 74,799 6.% 4,070,00,0 Flaglr 49,83 93, % 9,968,9,375 St. Johns 3,35 73, % 4,56,30,578 Franklin 9,89,49 4.6% 3,080,503,79 St. Luci 9,695 7,96 4.% 44,357,89,98 Gadsdn 45,087 49, % 594,90,097 Santa Rosa 7,743 4,44 0.7% 48,83,600,5 Gilchrist 4,437 7,06 8.5%,3,470,770 Sarasota 35,96 387,46 8.9% 9,996,94,88 Glads 0,576, % 799,006,340 Sminol 365,99 45, % 5,78,70,76 Gulf 4,560 6,85 5.5% 54,94,963 Sumtr 53,345 89, % 9,003,57,48 Hamilton 3,37 4, % 746,673,34 Suwann 34,844 39, %,03,769,854 Hard 6,938 7,50.% 456,693,400 Taylor 9,56,56 6.9%,06,78,303 Hndry 36,0 39,65 9.5%,48,93,667 Union 3,44 5,7 7.0% 444,55,39 Hrnando 30,80 6,93 4.0%,758,60,77 Volusia 443, ,04 4.6% 46,88,533,388 Highlands 87,366 98,77 3.0% 8,060,699,830 Wakulla,863 9,47 8.7%,79,589,546 Hillsborough 998,948,9,86 9.4% 9,49,94,909 Walton 40,60 57, % 4,763,9,44 Holms 8,564 9, %,445,467,95 Washington 0,973 3,79 3.%,8,885,047 Indian Rivr,947 39, % 745,80,78 Total 5,98,84 8,680, %,63,443,885,844 Jackson 46,755 50,46 7.8% 6,880,80,30 Sourc: QUASR databas from Florida Offic of Insuranc Rgulation Jffrson,90 4,494.3%,457,765,9 Florida Dmographic databas. Lafaytt 7,0 8,5 7.0% 95,876,58 Lak 0,57 86, % 7,354,636 L 440,888 65, % 35,57,37,79 Lon 39,45 7, % 75,54,88,89 Lvy 34,450 40,045 6.% 3,603,547,36 Librty 7,0 7,77 0.7%,04,996,007 39

141 Tabl 7 Dscriptiv Statistics in Rgrssion Equations Tabl 7. Dscriptiv Statistics for Equations 3 Variabl Numbr of Obsrvations Man Standard Dviation Minimum Maximum Population Growth in Prcntag Citizns Markt Shar in Exposurs Citizns Markt Shar in Prmiums Citizns Markt Shar in Policy Numbrs Flood Insuranc Covrags Flood Insuranc Prmiums Flood Insuranc Policy Numbrs Flood Insuranc Covrags Normalizd by Population Flood Insuranc Prmiums Normalizd by Population Flood Insurnac Policy Numrs pr 00 Population Incom Crim Rat pr 00 Population Tabl 7. Dscriptiv Statistics for Equations 4 6 Variabl Numbr of Obsrvations Man Standard Dviation Minimum Maximum HO Exposurs 5, HO Prmiums 53, HO Policy Numbrs 53, CAT Fund Purchas in Prcntag 35, Citizns Markt Shar in Exposurs 55, Citizns Markt Shar in Prmiums 55, Citizns Markt Shar in Policy Numbrs 55, Flood Insuranc Covrags 55, Flood Insuranc Prmiums 55, Flood Insuranc Policy Numbrs 55, Flood Insuranc Covrags Normalizd by Population 55, Flood Insuranc Prmiums Normalizd by Population 55, Flood Insuranc Policy Numrs pr 00 Population 55, Pric Proxy at County Lvl 55, Pric Proxy at Firm Lvl 5, Incom 55, Siz, Rturn on Equity, Lvrag, Liquidity,

142 Tabl 8. Random Effcts Estimats of Govrnmnt Intrvntion Masurd in trms of Exposurs, Dpndnt variabl is County Population Growth Rat in Prcntag trms Random-Effct Indpndnt Variabls Modl A Citizns Markt Shar in Exposurs Flood Insuranc Covrag *** Lag of Flood Insuranc Covrag ** Flood Insuranc Covrag Normalizd by Population Random-Effct Modl A Random-Effct Modl A ** Random-Effct Modl A Lag of Flood Insuranc Covrag Normalizd by Population *** Incom Crim Rat Dummy for South Atlantic ara *** *** *** *** Dummy for Gulf Coast Dummy for Panhandl ara Obsrvations R-squard Th stimation of fixd and random ffcts ar basd on Hausman tst.. Th rsults of yar dummis ar not rportd in th tabl. 3. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 4

143 Tabl 8. Fixd and Random Effcts Estimats, Govrnmnt Intrvntion Masurd in trms of Dirct Writtn Prmiums, Dpndnt variabl is County Population Growth Rat in Prcntag trms Fixd-Effct Indpndnt Variabls Modl B Citizns Markt Shar in Dirct Writtn Prmiums Flood Insuranc Dirct Writtn Prmiums Lag of Flood Insuranc Dirct Writtn Prmiums * Flood Insuranc Dirct Writtn Prmiums Normalizd by Population Random-Effct Modl B Fixd-Effct Modl B Lag of NFIP Prmiums/Population Random-Effct Modl B Incom *** Crim Rat Dummy for South Atlantic ara *** ** *** Dummy for Gulf Coast Dummy for Panhandl ara Obsrvations R-squard Th stimation of fixd and random ffcts ar basd on Hausman tst.. Th rsults of yar dummis ar not rportd in th tabl. 3. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 4

144 Tabl 8.3 Fixd and Random Effcts Estimats, Govrnmnt Intrvntion Masurd in trms of Policy Numbrs in Forc, Dpndnt variabl is County Population Growth Rat in Prcntag trms Fixd-Effct Indpndnt Variabls Modl C Citizns Markt Shar in Policy Numbrs Flood Insuranc Policy Numbrs ** Lag of Flood Insuranc Policy Numbrs Flood Insuranc Policy Numbrs Normalizd by Population in Prcntag Random-Effct Modl C Fixd-Effct Modl C Random-Effct Modl C Lag of Flood Insuranc Policy Numbrs Normalizd by Population in Prcntag Incom *** Crim Rat Dummy for South Atlantic ara *** *** ** Dummy for Gulf Coast Dummy for Panhandl ara Obsrvations R-squard Th stimation of fixd and random ffcts ar basd on Hausman tst.. Th rsults of yar dummis ar not rportd in th tabl. 3. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 43

145 Tabl 8.4 Estimatd Cofficints on County Population Growth Rat with County Dummis Indpndnt Variabls Modl A5 Modl A6 Modl B5 Modl C5 Citizns Markt Shar in Exposurs Lag of Flood Insuranc Covrag *** Lag of Flood Insuranc Covrag Normalizd by Population *** Citizns Markt Shar in Dirct Writtn Prmiums Lag of Flood Insuranc Dirct Writtn Prmiums Citizns Markt Shar in Policy Numbrs Lag of Flood Insuranc Policy Numbrs Incom *** *** *** *** Crim Rat * Dummy for County Clay *** *** *** *** Dummy for County Volusia *** *** *** *** Dummy for County Broward Dummy for County Monro *** *** *** *** Dummy for County Hndry *** *** *** *** Dummy for County Sarasota *** *** *** *** Dummy for County Franklin *** *** *** *** Dummy for County Lon ***.8.743*** *** *** Obsrvations R-squard Miam-Dad is st as th dfault county in th rgrssion. Th othr ight county dummis from four risk trritoris as rportd: North Atlantic ara: Clay and Volusia; South Atlantic ara: Broward and Monro; 3 Gulf Coast ara: Hndry and Sarasota; 4 Panhandl ara: Franklin and Lon. Most of th rmaining county dummis which ar not rportd ar statistically significant.. Th rsults of yar dummis ar not rportd in this tabl. 3. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 44

146 Tabl 8.5 Estimatd Cofficints on Homownrs Insuranc Exposurs Dpndnt Variabl = Log Homownr Insuranc Exposurs Indpndnt Variabls Modl D Modl D Modl D3 Modl D4 Citizns Markt Shar in Exposurs *** * *** *** CAT Fund Purchas in Prcntag *** *** *** *** Flood Insuranc Covrag *** Lag of Flood Insuranc Covrag *** Flood Insuranc Covrag Normalizd by Population *** Lag of Flood Insuranc Covrag Normalizd by Population *** Homownr Insuranc Prmiums ovr Exposurs at County Lvl *** *** Log of County Incom *** *** *** *** Siz *** *** *** *** Rturn on Equity Lvrag *** *** *** *** Liquidity Dummy for South Atlantic Ara *** *** *** *** Dummy for Gulf Coast * * Dummy for Panhandl Ara Obsrvations 7,0 7,054 7,0 7,054 R-squard Th rsults of yar dummis ar not rportd in this tabl.. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 45

147 Tabl 8.6 Estimatd Cofficints on Homownrs Insuranc Dirct Writtn Prmiums Dpndnt Variabl = Log Homownr Insuranc Prmiums Indpndnt Variabls Modl E Modl E Modl E3 Modl E4 Citizns Markt Shar in Prmiums * CAT Fund Purchas in Prcntag *** *** *** *** Flood Insuranc Prmiums *** Lag of Flood Insuranc Prmiums *** Flood Insuranc Prmiums Normalizd by Population *** Lag of Flood Insuranc Prmiums Normalizd by Population *** Homownr Insuranc Prmiums ovr Exposurs at County Lvl ** *** Log of County Incom *** *** *** *** Siz *** *** *** *** Rturn on Equity *** *** ** Lvrag *** *** *** *** Liquidity * * * * Dummy for South Atlantic Ara Dummy for Gulf Coast *** *** *** *** Dummy for Panhandl Ara ** ** *** ** Obsrvations 4,37 4,86 4,37 4,86 R-squard Th rsults of yar dummis ar not rportd in this tabl.. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 46

148 Tabl 8.7 Estimatd Cofficints on Homownrs Insuranc Policy Numbrs in Forc Dpndnt Variabl=LogHomownr Insuranc Policy Numbrs Indpndnt Variabls Modl F Modl F Modl F3 Modl F4 Citizns Markt Shar in Policy Numbr CAT Fund Purchas in Prcntag *** *** *** *** Flood Insuranc Policy Numbr *** Lag of Flood Insuranc Policy Numbr *** Flood Insuranc Policy Numbrs/Population in Prcntag Lag of Flood Insuranc Policy Numbrs/Population in Prcntag Homownr Insuranc Prmiums ovr Exposurs at Firm Lvl Log of County Incom *** *** *** *** Siz *** *** *** *** Rturn on Equity *** *** *** *** Lvrag *** *** *** *** Liquidity ** * ** ** Dummy for South Atlantic Ara *** *** *** *** Dummy for Gulf Coast * *** ** ** Dummy for Panhandl Ara ** ** ** Obsrvations 6,08 5,985 6,00 4,54 R-squard Th rsults of yar dummis ar not rportd in this tabl.. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 47

149 Tabl 8.8 Estimatd Cofficints on Homownrs Insuranc Exposurs with County Dummis Dpndnt Variabl=LogHomownr Insuranc Exposurs Indpndnt Variabls Modl D5 Modl D6 Citizns Markt Shar in Exposurs * * CAT Fund Purchas in Prcntag *** *** Flood Insuranc Covrag *** Lag of Flood Insuranc Covrag Homownr Insuranc Prmiums ovr Exposurs at County Lvl Incom *** *** Siz *** *** Rturn on Equity Lvrag *** *** Liquidity Dummy for County Clay.46.3** Dummy for County Volusia ** * Dummy for County Broward ** Dummy for County Monro Dummy for County Hndry Dummy for County Sarasota *** ** Dummy for County Franklin * * Dummy for County Lon *** Obsrvations 7,0 7,054 R-squard Miam-Dad is st as th dfault county in th rgrssion. Th othr ight county dummis from four risk trritoris as rportd: North Atlantic ara: Clay and Volusia; South Atlantic ara: Broward and Monro; 3 Gulf Coast ara: Hndry and Sarasota; 4 Panhandl ara: Franklin and Lon. Most of th rmaining county dummis which ar not rportd ar statistically significant.. Th rsults of yar dummis ar not rportd in this tabl. 3. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 48

150 Tabl 8.9 Estimatd Cofficints on Homownrs Insuranc Prmiums with County Dummis Dpndnt Variabl=LogHomownr Insuranc Prmiums Indpndnt Variabls Modl E5 Modl E6 Citizns Markt Shar in Prmiums CAT Fund Purchas in Prcntag *** *** Flood Insuranc Prmiums Lag of Flood Insuranc Prmiums Homownr Insuranc Prmiums ovr Exposurs at County Lvl Incom *** *** Siz *** *** Rturn on Equity *** *** Lvrag *** *** Liquidity * * Dummy for County Clay Dummy for County Volusia Dummy for County Broward Dummy for County Monro Dummy for County Hndry Dummy for County Sarasota **.808.4** Dummy for County Franklin * Dummy for County Lon Obsrvations 4,37 4,86 R-squard Miam-Dad is st as th dfault county in th rgrssion. Th othr ight county dummis from four risk trritoris as rportd: North Atlantic ara: Clay and Volusia; South Atlantic ara: Broward and Monro; 3 Gulf Coast ara: Hndry and Sarasota; 4 Panhandl ara: Franklin and Lon. Most of th rmaining county dummis which ar not rportd ar statistically significant.. Th rsults of yar dummis ar not rportd in this tabl. 3. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 49

151 Tabl 8.0 Estimatd Cofficints on Homownrs Insuranc Policy Numbrs in Forc with County Dummis, Dpndnt Variabl=LogHomownr Insuranc Policy Numbr in Forc Indpndnt Variabls Modl F5 Modl F6 Citizns Markt Shar in Policy Numbrs CAT Fund Purchas in Prcntag *** *** Flood Insuranc Policy Numbrs Lag of Flood Insuranc Policy Numbrs Homownr Insuranc Prmiums ovr Exposurs at Firm Lvl Incom *** Siz *** *** Rturn on Equity *** *** Lvrag *** *** Liquidity *** *** Dummy for County Clay * Dummy for County Volusia ** ** Dummy for County Broward * ** Dummy for County Monro Dummy for County Hndry Dummy for County Sarasota *** ** Dummy for County Franklin * * Dummy for County Lon.43.43* Obsrvations 4,053 4,0 R-squard Miam-Dad is st as th dfault county in th rgrssion. Th othr ight county dummis from four risk trritoris as rportd: North Atlantic ara: Clay and Volusia; South Atlantic ara: Broward and Monro; 3 Gulf Coast ara: Hndry and Sarasota; 4 Panhandl ara: Franklin and Lon. Most of th rmaining county dummis which ar not rportd ar statistically significant.. Th rsults of yar dummis ar not rportd in this tabl. 3. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 50

152 Tabl 8. Estimatd Cofficints on Homownrs Insuranc Exposurs with County Dummis and Firm Dummis, Dpndnt Variabl=LogHomownr Insuranc Exposurs Indpndnt Variabls Modl D7 Modl D8 Citizns Markt Shar in Exposurs *** *** CAT Fund Purchas in Prcntag *** *** Flood Insuranc Covrag *** Lag of Flood Insuranc Covrag Homownr Insuranc Prmiums ovr Exposurs at County lvl Incom *** *** Siz *** *** Rturn on Equity *** *** Lvrag *** *** Liquidity *** *** Dummy for County Clay ** Dummy for County Broward *** Dummy for County Sarasota ** Dummy for County Lon ** ** F=Allstat Gnral Insuranc Company F=Lumbrmns Mutual Casulty Company ** F3=Mrastar Insuranc Company F4=Auto Club South Insuranc Company ** Obsrvations 6,03 5,989 R-squard Four rprsntativ insurrs ar rportd in this tabl as Allstat Gnral Insuranc Company big firm, Lumbrmns Mutual Casulty Company mid-siz firm, Mrastar Insuranc Company nw ntrant sinc 000, and Auto Club South Insuranc Compnay nw ntrant sinc Miam-Dad is st as th dfault county in th rgrssion. Th othr four county dummis from four risk trritoris as rportd: Clay in North Atlantic; Broward in South Atlantic; Sarasota in Gulf Coast; Lon in Panhandl ara. 3. Th rsults of yar dummis ar not rportd in this tabl. 4. *, ** and *** dnot significanc at 0%, 5% and % lvls rspctivly. 5