Workng Paper/Documen de raval 2008-21 The Cos of Equy n Canada: An Inernaonal Comparson by Jonahan Wmer www.bank-banque-canada.ca
Bank of Canada Workng Paper 2008-21 July 2008 The Cos of Equy n Canada: An Inernaonal Comparson by Jonahan Wmer Fnancal Markes Deparmen Bank of Canada Oawa, Onaro, Canada K1A 0G9 jwmer@bankofcanada.ca Bank of Canada workng papers are heorecal or emprcal works-n-progress on subjecs n economcs and fnance. The vews expressed n hs paper are hose of he auhor. No responsbly for hem should be arbued o he Bank of Canada. ISSN 1701-9397 2008 Bank of Canada
Acknowledgemens I would lke o hank Ton Gravelle, Teodora Palgorova, Zhaoxa Xu, Sco Hendry, Lore Zorn, Greg Bauer, and semnar parcpans a he Bank of Canada for helpful commens and advce.
Absrac Ths paper calculaes an mpled cos of equy for 19 developed counres from 1991 o 2006. Durng hs perod, here has been a declne n he cos of equy of abou 10-15 bps per year, whch can be parally arbued o declnng governmen yelds and declnng nflaon. Analys forecas naccuracy, a proxy for frm-level earnngs opacy, s posvely relaed o he cos of equy. If hs varable capures dfferences n dsclosure across frms, hen mprovemens n dsclosure regulaon may benef frms by lowerng her cos of equy. I also nclude counrylevel varables ha measure dsclosure requremens, drecor lably, and he ably for shareholders o sue drecors. Hgher levels of hese measures are assocaed wh a lower cos of equy. Prevous sudes [e.g., Hal and Leuz (2006a)] have found a smlar relaon, bu my sudy s unque n ha uses a dfferen measure of nvesor proecon, whch may beer reflec regulaory dfferences across counres, and shows hs relaon holds for developed counres. Afer conrollng for he characerscs of frms ha analyss choose o cover n each counry, dfferences n he properes of analys forecass across counres, and dfferences n accounng sandards across counres, Canada s cos of equy s sascally dfferen from a handful of counres and s abou 20 o 40 bps hgher han ha of he Uned Saes. Lowerng Canadan frms cos of equy by hs amoun would have large economc benefs gven he sze of Canada s capal markes. JEL classfcaon: G30, G38 Bank classfcaon: Fnancal markes; Inernaonal opcs Résumé L aueur calcule le coû mplce des capaux propres dans 19 pays développés de 1991 à 2006. Duran cee pérode, le coû des capaux propres a dmnué d envron 10 à 15 pons de base par année, en pare sous l effe de la basse des rendemens sur les oblgaons d Éa e du recul de l nflaon. Les erreurs de prévson des analyses, une varable d approxmaon à l égard de l opacé enouran les profs des socéés, son en relaon posve avec le coû des capaux propres. S cee varable rend ben compe des dsparés dans la communcaon de l nformaon fnancère des frmes, l sera alors possble que l améloraon de la réglemenaon en la maère bénéfce aux enreprses en ndusan une réducon du coû des capaux propres. L aueur nègre en oure des varables naonales afn de quanfer les exgences relaves à la communcaon fnancère, la responsablé des consels d admnsraon e la laude des aconnares à poursuvre ces derners. Le coû des capaux propres es relavemen bas lorsque ces varables son élevées. Des éudes anéreures (p. ex., Hal e Leuz, 2006a) avaen éabl un len analogue,
mas l éude de l aueur se dsngue à double re : elle exploe une mesure dfférene de la proecon des nvessseurs, laquelle révèle peu-êre meux l écar enre les réglemenaons naonales, e elle monre que ce len vau pour les pays développés. Une fos que son prses en compe les caracérsques des socéés que les analyses chosssen de raer dans chaque pays, ans que les dfférences enre les propréés des prévsons formulées d un pays à l aure e enre les normes compables naonales, l apparaî que le coû des capaux propres au Canada dffère sasquemen de celu de cerans pays e dépasse de quelque 20 à 40 pons de base celu que supporen les enreprses amércanes. Dmnuer dans ce ordre de grandeur le coû des capaux propres des frmes canadennes apporera des avanages économques mporans vu la alle des marchés fnancers au Canada. Classfcaon JEL : G30, G38 Classfcaon de la Banque : Marchés fnancers; Quesons nernaonales v
1. Inroducon There has been recen neres n denfyng ways o reduce Canadan frms cos of equy fnancng, snce hs would enable hem o become more compeve n oday s global capal markes and should ulmaely ncrease Canadan economc growh. For he mos par, he focus has been on comparng Canadan frms cos of equy o ha of he Uned Saes. 1 However, oher jursdcons, lke he Uned Kngdom, have become an aracve desnaon for foregn frms o rase capal, and hs could mply he Uned Kngdom has a lower cos of equy han n he Uned Saes. Therefore, n hs paper, I calculae he mpled cos of equy for nonfnancal frms across 19 developed counres o deermne he characerscs ha affec he cos of equy and o provde a broader range of benchmarks for whch o compare Canada s cos of equy. I also denfy a se of frm-level and counry-level facors ha affec he cos of equy. I measure he mpled cos of equy - he dscoun rae ha equaes he dscouned value of analys forecass of frms fuure earnngs o he curren sock prce - usng four dfferen varaons of he dvdend dscoun model. A handful of prevous sudes have examned he mpled cos of equy across developed and developng counres, bu her focus s no on examnng counry-level esmaes of he cos of equy. Indeed, very few sudes acually provde counry-level cos of equy esmaes. Insead, hese sudes fnd ha frms ha face sronger legal nsuons, he enforcemen of nsder radng, and more exensve dsclosure, have a lower cos of equy. However, dfferences n accounng rules, and n he selecon of frms ha analyss cover, could mpac he cos of equy across frms, counres, and me. Ths sudy accouns for hese laer dfferences by focusng only on developed counres, where he dfferences n he srengh of legal nsuons and enforcemen are less, and uses more ndependen varables reflecng accounng and analys forecas dfferences ha may have an effec on cos of equy esmaes. Afer measurng he mpled cos of equy for 19 developed counres from 1991 o 2006, I fnd a declne n he cos of equy of abou 15 bps per year on average across hese 19 jursdcons, whch can be mosly arbued o declnng governmen yelds and declnng nflaon. When measurng a real cos of equy, and conrollng for hs declne n real 1 See, for example, he Capal Markes Leadershp Task Force Repor (2006), he Task Force o Modernze Secures Regulaon n Canada (2006), and Wmer and Zorn (2007). 1
governmen yelds, hs rae of declne s much smaller. There s also a small, posve relaon beween he real cos of equy and real governmen bond yelds, llusrang he mpac ha fscal and moneary polcy may have on he real cos of equy. Several varables are shown o be relaed o he cos of equy. Mos noably, analys forecas naccuracy, a poenal proxy for frm-level earnngs opacy, s posvely relaed o he cos of equy. If hs varable capures dfferences n dsclosure across frms, hen mprovemens n dsclosure regulaon would benef frms by lowerng her cos of equy. Afer conrollng for he characerscs of frms ha analyss choose o cover n each counry, dfferences n he properes of analys forecass across counres, and dfferences n accounng sandards across counres, Canada s cos of equy s sascally dfferen from a handful of counres and he magnudes of hese dfferences are economcally sgnfcan. For example, n several specfcaons he cos of equy for he Uned Saes s below ha of Canada by a sascally sgnfcan 20 o 40 bps. Reducng marke frcons n Canada and lowerng Canadan frm s cos of equy by hs amoun would have large economc benefs gven he sze of Canada s capal markes. Counry-level dfferences n he cos of equy may be relaed o counry-level facors such as secures regulaon, enforcemen, measuremen error, or oher varables no conrolled for. Therefore, n leu of he counry dummy varables, I nclude counry-level measures of dsclosure requremens, drecor lably, and he ably for shareholders o sue drecors. Hgher levels of hese measures are assocaed wh a lower cos of equy. Prevous sudes [e.g., Hal and Leuz (2006a)] have found a smlar relaon, bu my sudy s unque n ha uses a dfferen measure of nvesor proecon, whch may beer reflec regulaory dfferences across developed counres, and shows ha hs relaon does n fac hold for developed counres, whereas resuls from prevous sudes usng oher varables may have been drven by large dfferences beween developed and developng counres. The res of he paper s organzed as follows. In Secon 2, I brefly revew earler sudes ha have calculaed a cos of equy a an nernaonal level. Secon 3 descrbes he daase whle Secon 4 emprcally examnes he cos of equy and s drvers for nernaonal frms. I explore he robusness of he resuls n Secon 5 and conclude n Secon 6. 2
2. Inernaonal Sudes on he Impled Cos of Equy Mos recen research on nernaonal mpled cos of equy has concenraed on relang a counry s mpled cos of equy o counry-level nsuonal varables, such as legal nsuons, enforcemen of nsder radng, dsclosure, and corporae governance. These counry cos of equy esmaes are eher measured as he medan or mean of frm-level cos of equy esmaes, or are calculaed usng aggregae sock ndex daa. 2.1. Cos of Equy Esmaes derved from Frm-level Daa: Hal and Leuz (2006a) esmae a counry medan of he frm-level cos of equy (measured n local currency) usng four dfferen models for 40 counres from 1992-2001. Afer conrollng for several frm and counry facors, hey fnd ha counres wh weak legal nsuons have a hgher cos of equy han hose wh sronger nsuons. However, hey nclude boh developng and developed counres n her sample, and s plausble o hnk ha he relaon beween he cos of equy and legal nsuons s sronger for developng counres. Frs, developed counres are more negraed wh global capal markes, makng easer for frms from hese counres o op-n o he regulaon of oher counres va a cross-lsng, so dfferences n a counry s legal nsuons would be more lkely o have an mpac on a frm s cos of equy n developng counres. Second, he effec of legal nsuons on he cos of equy may be non-lnear, n ha he effec of mprovng very weak legal nsuons may be sronger han he effec of mprovng srong legal nsuons. Ths also would sugges a sronger effec n developng counres snce developng counres score lower on he measures used by Hal and Leuz (2006a). Claus and Thomas (2001) also generae counry cos of equy esmaes usng frm-level daa for a handful of counres. The purpose of her paper s o show ha her mpled cos of equy mehodology may be able o generae lower esmaes of equy rsk prema, compared wh equy prema esmaes generaed from hsorc reurns daa. Ther sudy focuses mosly on he Uned Saes, bu hey also provde cos of equy esmaes usng her mehodology for fve oher counres o valdae her U.S. resuls. There are wo sudes on he nernaonal mpled cos of equy ha relae a frm-level cos of equy o frm-level varables. Francs, Khurana, and Perera (2005) esmae a frm s mpled 3
cos of equy usng he Eason (2004) mehodology. They examne he relaon beween a frm s cos of equy and s volunary dsclosure levels, whch s measured as he dfference beween he frm s CIFAR score (a measure of dsclosure n he frm s annual repors) and he mnmum CIFAR score n he frm s counry. Unforunaely, he auhors only have CIFAR scores for he 1991 and 1993 fscal years, and her sample conans only 274 frms. Noneheless, hey fnd ha frms n ndusres wh greaer exernal fnancng needs have hgher volunary dsclosure levels, and ha an expanded dsclosure polcy for hese frms leads o a lower cos of boh deb and equy capal. A second paper by Hal and Leuz (2006b) sudes he mpac of a U.S. cross-lsng on foregn frms cos of equy. They fnd ha cross-lsng on a U.S. exchange s assocaed wh an economcally sgnfcan decrease n he cos of equy, and ha hs decrease s more pronounced n frms from counres wh weaker legal nsuons. 2.2. Cos of Equy Esmaes derved from Sock Index Daa: Sudes n hs caegory measure he counry s cos of equy by applyng he Gordon dvdend growh model o daa from he counry s major sock ndex. Under he Gordon model, he counry cos of equy s calculaed as he sum of he sock ndex s dvdend yeld and he growh rae n s dvdends, whch s ypcally measured usng he ndex s hsorcal dvdend growh rae. Bhaacharya and Daouk (2002) look a a specfc secury law across 103 counres, namely, nsder radng. Afer conrollng for several oher varables, hey show ha a counry s cos of equy, measured usng sock ndex daa, s no affeced by he nroducon of nsder radng laws; however, here s a decrease n he cos of equy afer he frs prosecuon of nsder radng. Unforunaely, mos developed counres examned here have had her frs nsder radng prosecuon pror o he begnnng of he sample perod, so hs varable s no used n he analyss. For example, hey denfy Canada s frs nsder radng prosecuon as occurrng n 1976. Oher sudes usng sock ndex daa have also found ha he counry cos of equy esmae decreases wh boh ncreased dsclosure and beer qualy dsclosure. For example, Bhaacharya, Daouk, and Welker (2003) measure a counry cos of equy usng sock ndex daa and fnd a posve relaon beween earnngs opacy and mpled cos of equy, showng ha counres wh poorer dsclosure have a hgher cos of equy. Daouk, Lee, and Ng (2006) consruc a capal marke governance varable for each counry ha ncorporaes he 4
enforcemen of nsder radng laws, earnngs opacy, and shor-sellng resrcons whn ha counry. They esmae he cos of equy for 22 dfferen counres usng sock ndex daa and conclude ha mprovemens n capal marke governance are assocaed wh an economcally sgnfcan decrease n he cos of equy afer conrollng for oher facors. 2.3. Summary of Prevous Sudes: In mos of hese prevous sudes, he explanaory varables of neres are eher dscree or dummy varables. Canada s enforcemen ndex scores are, n several cases, he hghes of all he counres n her analyss, whch s conrary o he percepon by some ha Canada has dffcules n s prosecuon of nsder radng. 2 Hal and Leuz (2006a) fnd ha hgher levels of hese scores are relaed o a lower cos of equy, bu snce Canada s he hghes of all counres n several of hese scores, here may be lle room for mprovng cos of equy n Canada by mprovng hs score. Anoher concern s ha he heory underlyng he measuremen of he mpled cos of equy measures has assumed U.S. accounng rules and sandards. Chen, Jorgensen, and Yoo (2004) queson wheher hese assumpons are vald n an nernaonal conex. Specfcally, mpled cos of equy esmaes derved from Resdual Income Valuaon Models (RIV) assume he clean surplus accounng relaon. The auhors examne seven developed counres and show ha he European counres n her sample have more of a dry surplus relaon. Moreover, hey fnd ha RIV models underperform oher mpled cos of equy measures n European counres, whle he oppose holds rue for he Uned Saes, Canada, Ausrala, and Japan. Ths suggess ha accounng rules could have an mpac on he level of cos of equy across counres, so I nclude varables o accoun for some of hese dfferences. Few of he nernaonal sudes on he mpled cos of equy provde counry cos of equy esmaes and, moreover, he cos of equy esmaes by counry vary across sudes, gven ha hese sudes cover a dfferen me perod, nclude a dfferen sample of frms n her analyss, and calculae he cos of equy usng dfferen mehods and n dfferen currences (.e., local currency vs. a USD bass). The mpled cos of equy esmaes from hree pror sudes are dsplayed n Fgure 1 and he only defnve concluson across counres s ha Japan has eher 2 For example, Bhaacharya commens ha Canada s a frs-world counry wh second-world capal markes and hrd-world enforcemen. Source: Onaro Secures Commsson Pahec Exper Say, Torono Sar, December 1, 2007. 5
he lowes or second lowes cos of equy n all hree sudes. The sudy by Daouk, Lee, and Ng, whch examnes he longes me perod, has a large varaon n cos of equy across counres (rangng from 5.4% o 14.2%). Ther sudy esmaes he cos of equy usng sock ndex daa, whch s heavly weghed o he larges frms n each counry, and uses he Gordon Dvdend Growh Model, whch s very dependen on he esmae of he long-erm growh rae n dvdends. Asde from Japan, he counry cos of equy esmaes for he oher wo sudes, whch use frm-level daa o generae he counry cos of equy, are relavely close wh mos esmaes n he 10-11% range; however, one canno deermne from he daa provded wheher hese counry esmaes are sascally dfferen from one anoher. Moreover, he nen of hese sudes was no o deermne wheher here are cos of equy dfferences across counres hese cos of equy esmaes are jus a summary of he daa n each of he sudes. Therefore, he esmaes avalable n hese curren sudes should no be used o compare across counres snce hey do no accoun for dfferences n frm or counry characerscs. 2.4. Conrbuon o he leraure: Ths paper makes hree conrbuons o hs leraure. Frs, I nclude addonal frm-level varables and use a Fxed Effecs analyss o examne he mpac of hese varables on he cos of equy a a frm level, and I examne how he relaon beween he mpled cos of equy and hese frm-level varables dffer across counres. Prevous sudes eher use a counry-level panel daase 3, or use a frm-level daase whn he Uned Saes. The benef of hs sudy s ha akes advanage of whn counry and whn frm varaon n he varables o esmae her relaon wh he cos of equy. I nclude addonal frm-level varables o accoun for dfferences n accounng frameworks across frms (e.g., Hsorcal Cos Accounng vs. Modfed Hsorcal Cos and IASB vs. Home counry Accounng Sandards) and dfferences n analys opmsm (e.g., analyss are more opmsc for frms ha are no profable). Also, Bhaacharrya, Daouk, and Welker (2003) sugges ha... fuure research could develop echnques o assess earnngs opacy a he 3 For example, Hal and Leuz (2006a) measure a counry s cos of equy as he medan of he frm-level cos of equy n each year, hen regress hs counry cos of equy on he (counry-year) medan of oher frm-level varables, as well as several counry-level nsuonal varables. 6
ndvdual frm level, and hen es for lnks beween earnngs opacy and equy marke varables a he frm level raher han a he counry level. I do so by ncludng Analys Forecas Inaccuracy as a proxy for frm-level earnngs opacy [See Hope (2003)] and fnd ha frms cos of equy s hgher when hs proxy for earnngs opacy s hgher. Second, I measure counry-level effecs on he cos of equy afer conrollng for frm-level and counry-level facors ha may affec he cos of equy. Moreover, I measure he cos of equy n wo dfferen ways for comparably: 1) n USD and 2) n real nsead of nomnal erms. In dong so, I can compare he cos of equy across counres and ge a sense of he precson of he counry-level cos of equy esmaes (.e., wheher counry-level cos of equy esmaes are sascally dfferen from one anoher). 4 Thrd, hs paper adds o hs leraure by ncludng nvesor proecon ndces reflecng nvesor proecon agans self-dealng by corporae nsders [World Bank (2008), Djankov e al (2008)] and by only focusng on developed counres n order o elmnae he nfluence ha developng counres may have on he resuls. These ndces measure he exen of dsclosure, exen of drecor lably, and ease of shareholder sus n each counry. The auhors repor: Ths heorecally-grounded ndex predcs a varey of sock marke oucomes, and generally works beer han he commonly used ndex of an-drecor rghs [by La Pora e al (1997)]. 5 Canada s no he bes performng counry accordng o hese ndces, whch makes easer o argue ha mprovemens can be made o he cos of equy n Canada, and beer reflecs he wdely-held belef of problems n enforcemen n Canada. 6 Moreover, I purposefully focus on developed counres only, snce he effecs of regulaon on he cos of equy n prevous papers may be drven by he developng counres. Therefore, I can beer deermne he srengh of he relaon beween he cos of equy and regulaon n developed counres. 4 However, he sandard errors of hese counry-level cos of equy esmaes are probably larger han repored n hs paper gven ha here could be measuremen error a he counry-level (.e., n exchange rae and nflaon forecass) ha s no accouned for. 5 Some auhors have denfed problems n he ADRI ndex. For example, Spamann (2006) fnds nconssences n he La pora e al Index. He re-codes La Pora e al s (1998) An-Drecor Rghs Index (ADRI) o be conssen across counres usng he same defnons and fnds ha he ADRI s unlkely o be a vald measure of shareholder proecon. 6 Davd Dodge, n hs speech o he Economc Club of Torono on Improvng Fnancal Sysem Effcency: The Need for Acon, suggess... here sll s a percepon, boh n Canada and abroad, ha Canadan auhores aren' conssen n her effors o enforce he rules agans nsder radng and oher offences, nor ough enough n roong ou and punshng fraud., December 11, 2006. 7
3. Daa I esmae he mpled cos of equy for ndvdual frms n 19 counres over each year of he sample (1991-2006) usng frm-level daa. The mpled cos of equy n hs paper s calculaed as he average of four mpled cos of equy models, each based on he dvdend dscoun model: r_c [Claus and Thomas (2001)]; r_lns [Lee, Ng, and Swamnahan (2004)]; r_oj [Ohlson and Juener-Nauroh (2000)]; and r_mpeg [Eason (2004)]. For deals on he calculaons underlyng each of hese models, please see he appendx. For a more dealed dscusson, he reader s referred o Wmer and Zorn (2007). 3.1. Daa Requred for Cos of Equy Measures: Ths sudy focuses on frms from developed OECD counres (GNP per capa greaer han $20,000) whch have a leas 100 frm-year observaons on he cos of equy. My sample covers OECD nonfnancal frms covered by I/B/E/S and Compusa over he perod 1991-2006. The wo daases are merged ogeher usng company names, and I use he I/B/E/S forecas ha s made sx monhs before he fscal year-end snce he pror-year earnngs resuls should be avalable by hs me. COMPUSTAT daa s for he year endng pror o he dae of he I/B/E/S forecas. Also, frm-level daa for a counry are excluded f he cos of equy canno be calculaed for a mnmum of 10% of he frms whn ha counry, whn ha year. 7 Ths s o ensure ha he observaons represen a broad enough cross-secon of frms whn ha counry, and o mnmze forecas bas whch may arse when analyss cover only he op frms whn a counry. However, even afer applyng hs fler, analys coverage bas wll sll exs o he exen ha analyss sysemacally cover frms ha have hgher qualy nformaon envronmens 8 or frms ha hey feel have favorable fuure performance [e.g., McNchols and O Bren (1997)]. Afer applyng hs fler, I have daa for frms from he 19 counres lsed n Table 1. 7 Ths screen mosly elmnaes Japanese frms n he early 1990s, when I measure a cos of equy for only abou 5% of Japanese frms n he COMPUSTAT sample. 8 For example, Boubaker and Labegorre (2007) examne French-lsed frms and fnd lower coverage among frms ha are managed by a conrollng famly member. However, hey also show ha analyss are more lkely o cover frms owned hrough pyramd srucures or have shares wh dfferen vong rghs relave o cash flow rghs, suggesng ha analys coverage may be n demand when here s a hgher lkelhood of expropraon. For a more dealed dscusson of analys coverage bas and s poenal effec on he cos of equy, see Wmer and Zorn (2007) 8
The mpled cos of equy s calculaed usng he followng varables: curren share prce (P 0 ); one-year and wo-year ahead earnngs per share forecass convered o U.S.D. (e 1 and e 2 ); payou rao (d/e); book value per share (bv 0 ); and he long-erm growh rae n earnngs per share (g L ). The curren share prce and he medan earnngs per share forecass (n local currency) are from I/B/E/S, and are convered no U.S.D. by assumng a random walk so ha fuure earnngs forecass n U.S.D. are calculaed by mulplyng local currency forecass by he curren exchange rae. Ths s also robus o dfferen converson mehods [See Wmer and Zorn (2007)]. Each frm s book value of equy s aken from Compusa and s convered o a per share fgure by dvdng by he number of shares from I/B/E/S. The payou rao, also from Compusa, s he average hsorc payou rao over he prevous hree year perod, 9 resrced o be beween zero and one; oherwse, s reaed as mssng. The frm s fuure payou rao s assumed o equal he frm s average payou rao over he pror hree years. If he frm s payou rao s mssng for each of he pror hree years, he fuure payou rao s assumed o equal he counry s mean payou rao n ha year. As n Claus and Thomas (2001) and Hal and Leuz (2006a, 2006b), I se he long-erm growh rae n earnngs per share o he expeced nflaon rae. Snce I am meausurng a cos of equy n U.S.D., I use he U.S. expeced nflaon rae, aken from he IFO World Economc Survey (hrough Daasream), whch quarerly polls economc expers abou he expeced fuure developmen of nflaon. 3.2. Daa Requred for Conrol Varables: In he regresson analyss, I nclude several varables o accoun for dfferences n he characerscs of frms across counres, ncludng frm sze and leverage. As well, I also examne a se of varables ha aemp o conrol for dfferences n analys forecas properes across counres snce hey could bas he calculaed cos of equy esmaes f hey hemselves are based. Therefore, n addon o year and ndusry dummy varables 10 (seven ndusry groupngs based on 2 dg SIC codes), he followng varables are ncluded: 9 The payou rao s calculaed as dvdends earnngs per share. Dvdends are Compusa Daa#26 and earnngs per share are Compusa Daa#58. If dvdends are mssng, I assume ha he frm pays $0 n dvdends n ha year. 10 Year dummy varables are ncluded o conrol for me effecs n he mpled cos of capal, as well as changes n analys coverage of frms hrough me. For example, here s a large ncrease n analys coverage n he lae 1990s around he do-com boom. 9
Frm Sze: A larger frm sze should be assocaed wh a lower cos of equy. I s welldocumened ha larger frms end o have lower expeced reurns [Fama and French (1993), Banz (1981)], whch could be due o he fac ha larger frms are generally more lqud and end o be more ransparen and have a greaer analys followng. Frm sze s measured as he logarhm of he frm s book value of oal asses (Compusa Daa#89). Fnancal Leverage: Greaer fnancal leverage should be assocaed wh a hgher cos of equy. 11 Fnancal leverage s measured usng he frm s deb/equy rao (Compusa Daa#106/Compusa Daa#135). 12 The cos of equy of a levered frm should be hgher han he cos of equy of an unlevered frm and be ncreasng n he frm s deb/equy rao. Forecas Dsperson: Greaer forecas dsperson should be assocaed wh a hgher cos of equy. In hs sudy, he cross-seconal sandard devaon of analyss earnngs per share esmaes (from I/B/E/S), scaled by book value per share, s used as a proxy for frm-level earnngs varably [Gebhar, Lee, and Swamnahan (2001)]. However, forecas dsperson may also capure effecs relaed o he qualy of he frm s nformaon envronmen [Lang and Lundholm (1996)]. Forecas Inaccuracy: Greaer forecas naccuracy should be assocaed wh a hgher cos of equy. Several sudes have found ha ncreased, beer qualy dsclosure s assocaed wh a lower cos of equy. 13 In hs sudy, he absolue value of he prevous year s forecas error (expeced earnngs per share mnus acual earnngs per share), scaled by book value per share, s used as a proxy for dsclosure, wh a lower forecas naccuracy represenng beer frm-level dsclosure. Ths measure of dsclosure s movaed by he resuls n Hope (2003), Basu, Hwang, and Jan (1998), and Khanna, Palepu, and Chang (2000) who fnd ha forecas accuracy s posvely relaed o frm-level dsclosures. 14 11 See Modglan and Mller (1958). 12 To elmnae he mpac of oulers, we exclude observaons above he 99 h percenle for he followng varables: Deb/Equy Rao, Forecased Growh Rae (g S ), and Forecas Dsperson. 13 For heorecal work, see Lamber, Leuz, and Verreccha (2006). Emprcal sudes examnng he relaon beween dsclosure and he cos of equy nclude hose by Bhaacharya, Daouk, and Welker (2002); Boosan (1997); Boosan and Plumlee (2003); Berger, Chen and L (2006); Chua, Eun, La (2006); Hal and Leuz (2006a), Gebhard, Lee, and Swamnahan (2001), Gezmann and Ireland (2005), and Gode and Mohanram (2003). 14 However, sudes by Lang and Lundholm (1996), Adrem (1999), and Eng and Teo (2000) fnd no sascal relaon beween forecas accuracy and dsclosure. 10
Curren Loss Dummy varable: Frms experencng losses should be assocaed wh a hgher calculaed cos of equy. Ang and Cccone (2001) examne analys forecas properes across 42 counres and fnd ha frms wh losses are assocaed wh hgher forecas error and forecas opmsm across all counres. Earnngs esmaes for frms wh losses exceed ex-pos acual earnngs 87% of he me on average, whle earnngs esmaes for frms wh profs exceed ex-pos acual earnngs 52% of he me on average. Ths should generae a hgher fuure earnngs yeld f he sock prce does no reflec hs opmsm of analyss; ha s, he sock prce reflecs nvesors expecaons and nvesors adjus analyss expecaons of fuure earnngs o accoun for hs opmsm. All else equal, a hgher level of opmsm for hese frms wll resul n a hgher calculaed cos of equy gven he posve relaon beween he mpled cos of equy and fuure earnngs yelds and growh. The loss dummy varable akes he value of 1 f he laes fscal year s earnngs (Compusa Daa#32) are negave. Forecas Bas: Counres wh hgher analys forecas bas may have more based forecass, whch would resul n a hgher calculaed mpled cos of equy. I s welldocumened ha analyss ypcally are based [McNchols and O Bren (1997), O Bren, McNchols, and Ln (2005)] and ha hs bas could be dfferen across counres [Ang and Cccone (2001)]. Gven he posve relaon beween he mpled cos of equy and fuure earnngs and growh, a posve bas n earnngs forecass would resul n a posve mpled cos of equy bas [e.g., Hal and Leuz (2006a)]. In each counry-year, he aggregae forecas bas s measured as he prevous year s medan frm forecas error (expeced earnngs per share mnus acual earnngs per share), scaled by book value per share. Alhough smlar n consrucon, here s only a small posve correlaon beween hs measure and Forecas Inaccuracy. Accounng Dummy varables: Dfferences n accounng mehods may also have an mpac on he calculaed cos of equy. Gven ha he mpled cos of equy measures are calculaed usng esmaes of accounng earnngs, dfferences n accounng mehods may have an mpac on he cos of equy calculaon. Tha s, frms usng accounng mehods ha are more uncondonally conservave would, all else equal, have a lower calculaed mpled cos of equy. Two dfferen accounng dummy varables are used. The frs dummy varable, ACCOUNTING, akes he value of 1 f he frm uses hsorcal cos based accounng 11
(Compusa Daa Iem AMTHD = H). The second varable, IASB, s a dummy varable ndcang wheher he frm uses Inernaonal Accounng Sandards. These varables are mean o conrol for, as bes as possble, dfferences n frm and nsuonal characerscs across counres. However, even afer conrollng for he above varables, dfferences n accounng, or n analys forecas properes, may sll no be fully accouned for. Therefore, he counry-level effecs examned laer can be nerpreed, or explaned, as measurng hese dfferences, as well as dfferences n corporae governance, legal envronmens, currency rsk, sock marke segmenaon, or oher facors no ncluded n hs analyss. 3.3. Descrpon of Daa: Table 1 provdes a summary for each of he conrol varables for he 19 counres n he daase. The Uned Saes accouns for over half of he frm-year observaons, whle Canada, France, Germany, Grea Bran, Ausrala, Neherlands, and Japan are he only oher counres wh a leas 1000 observaons. Snce he sample frms are seleced as a funcon of analys coverage and daa avalably, hese sample sascs may no represen acual dfferences n he populaon of frms n hese counres. However, hey may be useful n explanng observed dfferences n he sample counry-level cos of equy. Noneheless, Japan, Ialy, Span, Swzerland, and he Uned Saes have he hghes medan frm sze, all wh a book value of oal asses over $500M. The medan Brsh frm s much smaller a abou $275M n oal asses. The medan frm sze n mos oher counres les somewhere n hs range wh Canada beng almos drecly n he mddle. Mos counres have a relavely small medan frm leverage. New Zealand s medan Deb/ Equy rao of.48 s he hghes of all counres n he sample. There s consderable varaon n he medan Forecas Dsperson across counres. The U.S. exhbs he lowes medan Forecas Dsperson of.005, whle oher counres, lke Norway, have a Forecas Dsperson ha s fve mes hs magnude. The medan Canadan frm has a Forecas Dsperson measure ha s jus over wce ha of he Uned Saes. The able also dsplays he medan Forecas Inaccuracy for each counry n he sample. Agan, he Uned Saes s lowes on hs measure, whereas oher counres, such as Sweden and Fnland, have a hgh Analys Forecas Inaccuracy. Canada Forecas Inaccuracy les beween hese exremes. 12
Fgure 2 examnes he medan cos of equy by counry for my sample of frms before accounng for any frm-level or counry-level facors. A a op-level, s n-lne wh prevous sudes, showng ha Japan has he lowes cos of equy. The cos of equy for Canada s hgher han n oher developed counres lke he Uned Saes, France, Germany and Grea Bran, bu s lower han n many Scandnavan counres. These dfferences could be due o nsuonal dfferences across counres as well as dfferences n he arbues of he sample of frms n each counry. As a frs cu, Fgure 3a plos he medan counry-year cos of equy agans medan counry-year Forecas Dsperson and appears ha here s a srong posve assocaon beween hese wo varables. Tha s, counres wh hgher forecas dsperson, or dsagreemen amongs analyss, also have a hgher cos of equy. Fgure 3b repeas hs analyss wh cos of equy ploed agans medan frm sze, and shows a negave relaon beween hese varables, as expeced. In Fgure 3c, here s a posve relaon beween en year yelds and he cos of equy, alhough he slope of he lne s less seep hen expeced (.e., here s no a one-for-one ncrease n he cos of equy wh an ncrease n en year yelds). 4. Emprcal Analyss Cos of equy dfferences across counres are esmaed usng a frm-level fxed effecs panel regresson model ha conrols for: frm sze, as measured by he logarhm of book value of asses (BVA); fnancal leverage (LEV); a loss ndcaor dummy varable (LOSS); analys forecas dsperson (DISP); analys forecas bas (FBIAS), analys forecas naccuracy (FINACCURACY), an accounng sandards ndcaor dummy (IASB); a me rend (), as well as busness cycle effecs by ncludng year (YEAR) dummy varables. For hs regresson analyss, a Hausman (1978) es suggess ha he Fxed Effecs model s preferable o a Random Effecs. The model sandard errors are clusered by frm and he full model s wren below: COE LOSS IASB 2006 = α + β = 1991 LOSS IASB YEAR _ YEAR FBIAS + µ + ε FBIAS BVA BVA LEV FINACCURACY LEV DISP DISP FINACCURACY (1) 13
Snce he fxed effecs regresson elmnaes any me-nvaran varables, n a second sage, he frm fxed effec coeffcen ( µˆ ) s regressed agans he counry (COUNTRY), ndusry (IND), and accounng mehod (ACCOUNTING) dummy varables, as well as he frm averages of he me-varyng ndependen varables 15. Bascally, hs exracs he average frm fxed effec by counry, afer conrollng for ndusry and accounng dfferences. The averages of he me-varyng ndependen varables are ncluded o conrol for correlaon beween hese varables and he frm fxed effecs. 16 The counry group dummy varables ndcae he company s counry of ncorporaon (from COMPUSTAT). Counres wh a small number of observaons are grouped ogeher or wh smlar larger counres, gven ha here s lmed sascal power o fnd evdence of sascal sgnfcance n counres wh few observaons. Therefore, from he nneeen counres, here are egh counry group dummy varables: USA, JAPAN, GREAT BRITAIN and IRELAND, NORDIC counres, AUSTRALIA and NEW ZEALAND, FRANCE, GERMANY, and OTHER EUROPEAN. 17 There s no counry dummy varable for Canada snce wll be used as he bass for comparson 18 : ˆ µ = ω + + YEAR _ = 1991 1 2006 γ FBIAS β COUNTRY FBIAS YEAR COUNTRY BVA FINACCURACY + BVA K k = 1 β IND _ k LEV IND LEV k FINACCURACY ACCOUNTING DISP DISP IASB IASB ACCOUNTING LOSS + v LOSS (2) 15 Ths s based on he Krshnakumar (2003) model. The coeffcens and her sandard errors for he me-nvaran varables are dencal o hose from a beween effecs regresson. I use weghed leas squares n hs second sage regresson o accoun for unbalanced panels. However, OLS s also conssen and yelds smlar resuls. 16 There are dfferen mehods for esmang me-nvaran models n a panel seng ha make dfferen assumpons abou he error srucure n he panel daase. One such mehod for exracng me-nvaran varables from a fxed effecs regresson does no use he averages of he me nvaran varables n he second sage [e.g., Polacheck and Km (1994), Oaxaca and Gesler (2003)]. Resuls excludng hese me-nvaran varables yeld slghly larger dfferences beween Canada and oher counres such as he Uned Saes. Oaxaca and Gesler (2003) show ha usng a GLS esmaon procedure n he second sage yelds resuls dencal o pooled OLS for he menvaran varables. Oher regresson mehods, such as Pooled OLS, wll be presened laer n he paper. 17 NORDIC counres nclude Fnland, Norway, Sweden, and Denmark. OTHER EUROPEAN ncludes Ausra, Belgum, Ialy, Neherlands, Span, and Swzerland. From here on, hese counry group dummy varables wll smply be referred o as counry dummy varables. 18 Laer, hese counry-level varables wll be replaced wh counry-level ndces ha measure facors such as nvesor proecon n each counry. 14
The resuls from he Fxed Effecs regresson are dsplayed n Table 2, Panel A, and he second sage regresson resuls are dsplayed n Panel B. The frs model n Table 2 regresses he cos of equy on frm sze and leverage, and ncludes ndusry, year, and counry dummy varables as well as a me rend. The coeffcens on frm sze and leverage are boh sgnfcan and have he expeced sgn. The overall cos of equy has declned over he sample perod by abou 14 bps a year, as ndcaed by he me rend varable. In Panel B, a number of he coeffcens on he counry dummy varables are sascally sgnfcan. Specfcally, he Uned Saes, France, and Japan boh have a cos of equy ha s lower han n Canada, whle Ausrala, New Zealand, Germany, and Nordc counres have a cos of equy ha s hgher han n Canada. The coeffcen on he USA dummy varable ndcaes a cos of equy n he Uned Saes ha s abou 40 bps lower han n Canada, whch s n lne wh prevous resuls [Hal and Leuz (2006a); Wmer and Zorn (2007)]. In Model (1) Japan s cos of equy s abou 95 bps lower han n Canada. As Fgure 1 shows, mos sudes ypcally fnd ha Japan has a much lower cos of equy han n oher counres. Dfferences n nflaon and n governmen bond yelds may explan par of hs dfference, whch wll be examned laer. However, hs dfference could also be due o dfferences n accounng or n analys forecas bas, especally gven he fac ha he analys forecasng envronmen s very dfferen n Japan n ha managemen also provdes earnngs forecass for mos frms [Kao, Sknner, and Kunmura (2006)]. In Model (2), Analys Forecas Dsperson s added o he regresson and has a large, posve effec on he cos of equy for frms. The effec of he sze varable s less pronounced (and s no sascally sgnfcan), gven ha larger frms end o have lower Forecas Dsperson. Ths varable has a mnor mpac on he coeffcens of he counry dummy varables. In Model (1), U.S. frms had a 41 bps lower cos of equy, whle n Model (2) hs dfference s 16 bps and s no sascally sgnfcan. Model (3) adds Analys Forecas Inaccuracy as a proxy for frm-level dsclosure and hs varable has a sascally sgnfcan, posve mpac on he cos of equy. Analys Forecas Inaccuracy may capure boh volunary and nvolunary aspecs of frm dsclosure. Ths varable may suffer from endogeney n ha frms may need or wan o dsclose more nformaon when hey are rasng exernal capal, and frms ha are rasng exernal capal may be he ones ha 15
have a lower cos of equy. Regardless, hese resuls sugges ha enablng analyss o make more accurae forecass hrough mproved dsclosure regulaon may conrbue o a lower cos of equy for frms. The fourh model ncludes varables ha accoun for dfferences n accounng and analys forecas properes across counres. The Loss Dummy coeffcen s posve and sascally sgnfcan, ndcang ha frms wh losses have a cos of equy ha s 163 bps above profable frms. Agan, hs varable s mean o conrol for analys forecas opmsm, gven ha analyss are overly opmsc on he fuure earnngs of loss frms across mos counres. The coeffcen on Forecas Bas s no sascally sgnfcan. Fnally, he IASB dummy varable s posve and s sascally sgnfcan. Therefore, frms usng hs accounng sandard seem o have a slghly hgher calculaed cos of equy. However, wh he excepon of he Forecas Inaccuracy varable, hese hree varables do no have much of an effec on he magnude or sgnfcance of he oher coeffcens n hs regresson. Forecas Inaccuracy changes because hs varable s correlaed wh he Loss Dummy varable. 4.1. Conrollng for Rsk-free Raes: Cross-counry dfferences n he cos of equy can also be mpaced by cross-counry dfferences n rsk-free raes, so he above analyss s repeaed o accoun for dfferences n rskfree raes across counres. For hs analyss, nsead of converng cash flows o U.S. dollars o calculae a U.S.D. cos of equy, a real cos of equy s calculaed. Frs, forecased local currency earnngs per share are convered no real erms by deflang by he expeced nflaon rae (from he IFO World Economc Survey) n each counry. Then, a real cos of equy s calculaed, assumng zero percen long-erm growh n real earnngs per share. 19 Some sudes equae he equy rsk premum wh he real cos of equy [e.g., Joron and Goezmann (2000)], so n hs sense he real cos of equy here may be closely relaed o he equy rsk premum. However, I also nclude local counry governmen Real Ten Year Yelds as an explanaory varable, whch are measured by subracng he expeced nflaon n local currency from he nomnal en year yelds. The coeffcen on he Real Ten Year Yeld varable 19 Ths s conssen wh earler calculaons of a nomnal USD cos of equy, whch assumed long-erm growh as he rae of US nflaon. Resuls are smlar f a nomnal cos of equy s calculaed n local currency (assumng long-erm growh equals expeced nflaon n ha counry), and hen converng no a real cos of equy by subracng expeced nflaon. 16
s posve and sascally sgnfcan. However, s coeffcen s only abou 0.2 o.25, much smaller han one. Ths could be he case f he cos of equy esmaes are nosy, f he equy rsk premum s no consan, or f underlyng governmen bond yelds hemselves conan a me-varyng rsk premum. The oher resuls here are broadly smlar o wha was repored earler, gven ha he coeffcens on he conrol varables have only changed slghly. Alhough he me rend s sll negave and sascally sgnfcan, s coeffcen s abou one-hrd he sze of he me rend coeffcens examned Table 2, suggesng ha mos of he declne n he nomnal cos of equy can be arbued o declnng governmen yelds and nflaon. Afer ncludng governmen yelds, he Japan counry dummy s much less negave. In all models examned n Table 3, he U.S. dummy varable s sascally sgnfcan and negave, so ha U.S. frms have a lower cos of equy han ha of Canadan frms. 4.2. Examnng counry-level Regulaon Varables: Prevous sudes have concenraed on relang he cos of equy o counry-level varables reflecng dfferen aspecs of regulaon and dsclosure across developed and developng counres. As dscussed earler, he effecs found n hese papers may be drven by large dfferences beween developed and developng counres, n whch case may be dffcul o relae o he regulaon n developed counres. Moreover, Canada s he bes performng counry along many measures used n hese sudes, whch makes dffcul o prescrbe enhanced regulaory measures o mprove he cos of equy n Canada, and may no reflec he wdely-held belef of problems n enforcemen n Canada. Ths paper adds o hs leraure by ncludng dfferen measures reflecng nvesor proecon agans self-dealng by corporae nsders [Djankov e al (2008)] and by only focusng on developed counres n order o elmnae he nfluence ha developng counres may have on he resuls. I use he World Bank s (2008) Invesor Proecon Indces, whch are adaped from Djankov e al (2008). These ndces are based on a hypohecal ransacon beween wo companes n whch he owner has conrollng sakes, and measures he exen of dsclosure, exen of drecor lably, and ease of shareholder sus n relaon o he ransacon. Each of hese ndces s measured on a scale of 0 o 10 (wh 10 represenng more dsclosure, more drecor lably, or more ably for shareholders o sue), and are also averaged o develop an overall Invesor 17
Proecon Index. On he overall Invesor Proecon Index, Canada scores an 8.3 whereas he maxmum score among our sample of counres s 9.7. On he Dsclosure Index, Canada scores an 8 whle oher counres (such as Grea Bran France, and New Zealand) score 10, so here s room for Canada o mprove on hs measure. Smlarly, Canada scores an 8 on he Shareholder Lawsus Index, whereas he maxmum score for our sample of counres on hs score s 10. As a frs cu, Fgure 4 shows he relaon beween he counry medan cos of equy and he Invesor Proecon Index. Overall, here seems o be a slgh negave relaon beween hs ndex and he real cos of equy. However, here are some oulers, whch could be due o frm characerscs or oher facors affecng he counry medan cos of equy. Therefore, I es wheher counres ha score hgher on hese measures have a lower cos of equy. To do so, I repea he wo sage Fxed Effecs regresson from earler. In he frs sage, I run he same regresson as n he las column n Table 3, Panel A. Then, n a second sage regresson, I regress he frm Fxed Effecs on he Invesor Proecon Measures as well as ndusry and accounng conrols and he frm averages of he me-varyng ndependen varables: ˆ µ = ω + YEAR _ = 1991 2006 LOSS PROTECTION γ LOSS YEAR PROTECTION + FBIAS BVA BVA FBIAS K k = 1 β IND _ k LEV LEV FINACCURACY IND k DISP ACCOUNTING DISP FINACCURACY ACCOUNTING IASB IASB + v (3) The resuls for four regressons (one on each of he ndvdual Indces) are presened n Table 4. All of he coeffcens on he Indces are negave and sascally sgnfcan ndcang more exensve nvesor proecon measures are assocaed wh a lower cos of equy. The Invesor Proecon measure, for nsance, shows a 12 bps drop n he cos of equy assocaed wh each un ncrease n hs measure. If Canada were o ncrease s performance along hs ndex o mach he op-performng counry along hs measure, could represen a poenal decrease of abou 20 bps n he cos of equy. 5. Robusness Tess 18
I perform hree dfferen ses of robusness checks. Frs, I run fxed effecs whn each counry o examne how he relaon beween he cos of equy and he frm-level varables dffer across counres. Some varables, such as leverage, he loss dummy, and forecas dsperson, are relavely conssen n he sgn and sascal sgnfcance level of her coeffcens across counres. However, here are some dfferences n he relaon beween he cos of equy and oher frm-level varables across counres. Second, I esmae he counry dummy varables usng dfferen economerc mehods for dealng wh me-nvaran varables whn a daase. The counry dummy varables n hese models are smlar n magnude and / or sascal sgnfcance n a majory of hese oher models, so her resuls appear o be relavely robus o dfferen economerc specfcaons. Thrd, I check he sensvy of he effec of he counry level nsuonal varables on he cos of equy by performng regressons usng he counryyear medans of all varables, nsead of performng he analyss a a frm level, and he resuls are smlar o wha was repored earler. 5.1. Counry Level Fxed Effecs Regressons: The panel regresson seup used up o hs pon has assumed common coeffcens across all counres. Ths may parcularly be a problem gven ha U.S. frms comprse more han half of he sample. To verfy wheher coeffcens may vary across counres, I run fxed effecs regressons whn each of he counry groups usng he real cos of equy measure. Alhough hs does no formally es wheher coeffcens are sgnfcanly dfferen from each oher, does deermne wheher he coeffcens have he correc sgn whn each counry. 20 For Canada, all of he coeffcens have he same sgn as he fxed effecs regressons wh counres pooled ogeher (See Table 5). The forecas dsperson effec s much weaker n Canada han n he pooled regressons. The coeffcen on frm fnancal leverage s posve across all counry groupngs, and s sascally sgnfcan n fve of he nne groups. The same holds for he forecas dsperson coeffcen: s posve n all bu one counry and sascally sgnfcan n fve of he nne counres. Sze s only negave and sascally sgnfcan n he Uned Saes and Canada and has a negave coeffcen n only four of he nne groupngs. I s posve and sgnfcan n four counry groups. However, hs effec may be arbuable o a 20 Mos coeffcens are sascally dfferen from each oher across counres when usng a sngle equaon and neracng he counry coeffcens wh each of he varables. 19
smaller sample sze, as well as correlaons beween sze and oher varables such as forecas dsperson. 21 The Real 10Yr Governmen Yelds coeffcen for Canada s 0.195, smlar o he resul wh all counres pooled ogeher. Ths coeffcen s posve n egh of he nne groups, beng sascally sgnfcan n seven of he groups. 5.2. Oher Economerc Mehods: A number of economerc mehods have been used n he leraure o measure he mpac of me nvaran varables (e.g., he counry dummy varables) n a panel seng. These mehods make dfferen assumpons abou he srucure of he regresson error erms (and n parcular he relaon beween he unobservable frm fxed effecs and he oher explanaory varables). I es wo oher economerc mehods ha can be used o measure he effecs of me nvaran varables n a panel seng: 1) Fama-Mcbeh (1973) regressons, and 2) Pooled OLS regressons. 5.2.1. Fama-Mcbeh Regressons: I run Fama-Mcbeh regressons, whch produce unbased sandard errors n he presence of a me effec, alhough he ncluson of year dummy varables n he earler analyss may also adjus properly for a me effec [Peersen (2007)]. In he Fama Macbeh (1973) approach, I frs run 15 cross-seconal regressons, one for each year n he sample: COE K = ω + β COUNTRY, COUNTRY + 1 k = 1 LEV, LEV ACCOUNTING, DISP, DISP ACCOUNTING LOSS, + ε β IND _ k, LOSS IND k BVA, FGROWTH, BVA FGROWTH YIELD YIELD (4) The Fama-Mcbeh coeffcen esmae s he average of he 15 cross-seconal coeffcen esmaes. For example, he Fama-Mcbeh esmae of he leverage coeffcen would be: 2006 ˆ β = β (5) LEV, FM = 1991 LEV, 21 Also, n a random effecs esmaon he sze coeffcen s negave across all counres, conssen wh larger frms havng a lower cos of equy. 20
The Fama-Mcbeh resuls are repored n he hrd column of Table 6. Wh he excepon of Forecas Bas, all of he coeffcens on he conrol varables have he expeced sgn and four are sascally sgnfcan. As well, mos are smlar n magnude o he resuls from random effecs and fxed effecs esmaon. However, he coeffcen on he Real 10Yr Governmen Yeld s 0.21 n he Fxed Effecs esmaon, and s 0.09 (and no sascally sgnfcan) n he Fama-Mcbeh esmaon. Ths ndcaes ha, over me, an ncrease n he frm s local Real 10Yr Governmen Yeld by 100 bps would be assocaed wh an ncrease n s real cos of equy of 21 bps. Conversely, n he cross-secon, he relaon beween Real 10Yr Governmen Yelds and he cos of equy s weaker. In he Fama-Mcbeh se-up, he sandard errors of he counry dummy varables are much hgher. Ths may be parally due o he fac ha he sample of frms whn each counry s changng over me, and so ha years when here s a small sample of frms whn a counry are gven he same wegh as years when here s a much larger sample. Ths mpacs he counry coeffcens because when analys coverage s less broad, s lkely ha hey focus on he beer frms ha have a lower cos of equy. Therefore, he Fama-Mcbeh (2003) esmaes may exacerbae he analys coverage bas, and produce less relable resuls relave o he oher mehods. Also, counry dummy varable sandard errors are larger due o changng sample composon and only wo counry dummy coeffcens are sascally sgnfcan: he USA dummy coeffcen and he Japan dummy coeffcen. Nowhsandng he above, hese wo esmaes provde some valdaon o he USA and Japan coeffcens from he Fxed Effecs esmaon snce hey are boh smlar o hese earler esmaes n sze and sascal sgnfcance. 5.2.2. Pooled OLS: I also run a Pooled OLS analyss o examne he me nvaran varables. Oaxaca and Gesler (2003) show ha he me nvaran coeffcens from Pooled OLS are dencal o he coeffcens from a wo sage Fxed Effecs Model, where GLS s used n he second sage o adjus for heeroskedascy n he dagonal and off-dagonal elemens of he varance/covarance marx (I performed he earler second sage regresson usng GLS o accoun for heeroskedascy n he dagonal elemens, and also ncluded means of he me-varyng varables). Agan, sandard errors are adjused o accoun for cluserng by frm: 21
COE K 2006 = ω + β COUNTRY COUNTRY + β IND _ k IND k + 1 k = 1 = 1991 BVA FBIAS BVA FBIAS LEV LEV ACCOUNTING DISP DISP ACCOUNTING LOSS LOSS IASB β YEAR _ IASB FINACC YEAR FINACC YIELD YIELD + ε (6) The resuls from hs mehod are encouragng snce he counry-level dummy varables are smlar o my orgnal specfcaon, n ha hese esmaes are lle changed (5-15 bps) and have smlar sgnfcance o he orgnal resuls. Overall, he resuls across he models are generally conssen wh he earler resuls n Table 3. Across he dfferen economerc mehods, boh he USA and Japan dummy coeffcens are sascally sgnfcan and negave n all hree models. The France coeffcen s negave n all hree models, wh sascal sgnfcance n wo models. Conversely, he Nordc dummy varable s posve n all models and s sascally sgnfcan n wo of he hree models. For oher counres, here s sparse evdence n favour of a sascally sgnfcan dfference, parally because of a smaller sample sze relave o he Uned Saes. 5.3. Counry Medan Regressons: Prevous sudes examnng he effec of counry-level nsuonal varables on he cos of equy [e.g., Hal and Leuz (2006a)] argue for usng counry medans of all varables o elmnae he nfluence of one counry (.e., he Uned Saes) on he regresson resuls. Therefore, I run OLS regressons nvolvng counry-year medans of all varables. As a resul of usng a counrylevel analyss, frm-specfc nose s removed and hence he r-squareds n hese regressons are much larger, rangng from.44 o.46 (See Table 7). However, he drawback o hs approach s ha he sample sze s much smaller (N < 250), and nformaon from he cross-seconal varaon whn counres s no ulzed. Alhough he sze coeffcen s negave, s no sascally sgnfcan n mos models. However, counres wh a hgher level of analys forecas dsperson have a hgher cos of equy, as evdenced by hs coeffcen. Moreover, he magnude of hs varable s more han wo mes larger han n prevous regressons. The coeffcen on governmen yelds s sascally sgnfcan and s smlar o wha was repored n prevous regressons. Forecas Inaccuracy, a proxy for Dsclosure, has a sascally sgnfcan, posve coeffcen ha s much larger han wha was repored earler. Agan, f more exensve dsclosure requremens can help 22
earnngs forecass become more accurae, hen hey may also help n reducng he cos of equy. Models (2) hrough (5) nclude each of he ndvdual Shareholder Proecon Indces. Three ou of four are negave, and he Dsclosure Index s sascally sgnfcan, whch also shows ha more exensve dsclosure requremens are assocaed wh a lower cos of equy. 6. Concluson From a hgh level, Canada s cos of equy s slghly hgher han he medan of he cos of equy of he 19 counres examned n hs paper; s hgher han n counres such as he Uned Saes, Japan, and Grea Bran, and lower han n counres lke Norway, Fnland, and Sweden. However, hese op-level cos of equy esmaes are nfluenced by facors such as he characerscs of frms ha analyss choose o cover n each counry, dfferences n he properes of analys forecass across counres, and dfferences n accounng sandards across hese counres. Afer employng a regresson analyss o accoun for hese facors, Canada s cos of equy s sascally sgnfcanly dfferen from a handful of counres. Frms from he Uned Saes have a cos of equy ha s abou 20 o 40 bps lower han ha of Canadan frms n mos models, and lowerng Canadan frm s cos of equy by hs amoun would have large economc benefs gven he sze of Canada s capal markes. However, even afer conrollng for he above facors, dfferences n accounng, or n analys forecas properes, may sll no be fully accouned for. Therefore, he counry-level effecs can be nerpreed, or explaned, as measurng hese unmodeled dfferences, as well as dfferences n corporae governance, legal envronmens, currency rsk, sock marke segmenaon, or oher facors no ncluded n hs analyss. There s a sascally sgnfcan, posve relaon beween analys forecas naccuracy and he cos of equy. Analys forecas naccuracy should be a proxy for he marke s ably o forecas frm-level earnngs, and f mproved ransparency or accounng dsclosure regulaon can mprove hs ably, may also resul n a lower frm-level cos of equy. The good news s ha he nomnal cos of equy has declned over me by abou 10 o 15 bps per year snce he begnnng of he sample perod. Ths declne can be mosly arbued o he reducon n governmen yelds and nflaon, snce he declne n he cos of equy s much 23
smaller when examnng he real cos of equy wh real governmen yelds as a rgh hand sde varable. 24
References Adrem, A.H. 1999. Essays on Dsclosure Pracces n Sweden Causes and Effecs. Ph.D. Dsseraon, Lund Unversy, Sweden. Ang, J. S. and S.J. Cccone. Inernaonal Dfferences n Analys Forecas Properes. Unversy of New Hampshre. Mmeo. Banz, R. 1981. The relaonshp beween Reurn and Marke Value of Common Socks. Journal of Fnancal Economcs 6: 103-126. Basu, S., L.Hwang and C. Jan. 1998. Inernaonal varaon n Accounng measuremen rules and analyss earnngs forecas errors. Journal of Busness Fnance and Accounng 24 (9): 1207-1247. Berger, P.G., H. Chen, and F. L. 2006 Frm Specfc Informaon and he Cos of Equy Capal. Mmeo. Bhaacharya, U. and H. Daouk. 2002. The World Prce of Insder Tradng. Journal of Fnance 57: 75-108. Bhaacharya, U., H. Daouk and M. Welker. 2003. The World Prce of Earnngs Opacy. The Accounng Revew 78: 641-678. Bhushan, R. 1989. Frm Characerscs and Analys Followng. Journal of Accounng and Economcs 11: 255-274. Borz, J.E. 2006. Mananng Qualy Capal Markes hrough Qualy Informaon. Capal Markes Leadershp Task Force Dscusson Paper. Boubaker, S. and F. Labegorre. 2007. Ownershp Srucure, Corporae Governance and Analys Followng: A sudy of French-lsed frms.. Journal of Bankng and Fnance. Boosan, C.A. 1997. Dsclosure Levels and he Cos of Equy Capal. The Accounng Revew 72: 323-349. Boosan, C.A. and M.A. Plumlee. 2000. Dsclosure Level and Expeced Cos of Equy Capal: An Examnaon of Analyss Rankngs of Corporae Dsclosure and Alernave Mehods of Esmang he Expeced Cos of Equy Capal. Unversy of Uah. Mmeo. Chen, F., B.N. Jorgensen, and Y.K. Yoo. 2004. Impled Cos of Equy Capal n Earnngsbased valuaon: Inernaonal Evdence. Chua, C. T., C.S. Eun, and S. La. 2007. Corporae Valuaon around he World: he Effecs of Governance, Growh, and Openness Journal of Bankng and Fnance 31(1): 35-56. 25
Claus, J. and J. Thomas. 2001. Equy Prema as Low as Three Percen? Journal of Fnance 56: 1629-1666. Daouk, H., C.M.C. Lee, and D.T. Ng. 2006. Capal Marke Governance: How do Secury Laws affec Marke Performance? Journal of Corporae Fnance 12: 560-593. Djankov, S., e al. 2008. The law and economcs of self-dealng. Journal of Fnancal Economcs. Eason, P. 2004. PE Raos, PEG Raos, and Esmang he Impled Expeced Rae of Reurn on Equy Capal. The Accounng Revew 79: 73-95. Eng, L.L., and H.K. Teo. 2000. The relaon beween annual repor dsclosures, analyss earnngs forecass and analys followng: Evdence from Sngapore. Pacfc Accounng Revew 11 (2): 219-239. Fama, E.F. and J. Mcbeh. 1973. Rsk, Reurn, and Equlbrum: Emprcal ess. Journal of Polcal Economy 81: 607-636. Fama, E.F. and K.R. French. 1993. Common Rsk Facors n he Reurns on Socks and Bonds. Journal of Fnancal Economcs 33: 3-56. Francs, J., I. Khurana and R. Perera. 2005. Dsclosure Incenves and effecs on cos of capal around he world. The Accounng Revew 80: 1125-1162. Gebhard, W.R., C.M.C. Lee, and B. Swamnahan. 2001. Toward an Impled Cos of Capal. Journal of Accounng Research 39: 135-176. Gezmann, M. and J. Ireland. 2005. Cos of Capal, Sraegc Dsclosures and Accounng Choce. Journal of Busness Fnance & Accounng 32: 599 634. Gode, D. and P Mohanram. 2003. Inferrng he Cos of Capal Usng he Ohlson-Juener Model. Revew of Accounng Sudes 8: 399-431. Gordon, M.J. 1962. The Invesmen, Fnancng, and Valuaon of he Corporaon. Homewood, Illnos: Irwn. Hal, L. and C. Leuz. 2006a. Inernaonal Dfferences n he Cos of Equy Capal: Do Legal Insuons and Secures Regulaon Maer? Journal of Accounng Research 44: 485-531. Hal, L. and C. Leuz. 2006b. Cos of capal effecs and changes n growh expecaons around U.S. cross-lsngs. Workng Paper. Heckman, J. 1979. Sample Selecon Bas as a Specfcaon Error. Economerca 47(1): 153-161. 26
Hope, O. 2003. Dsclosure Pracces, Enforcemen of Accounng Sandards and Analyss Forecas Accuracy: An Inernaonal Sudy. Journal of Accounng Research 41(2). Joron, P. and W.N. Goezmann. 2000. A Cenury of Global Sock Markes. Naonal Bureau of Economc Research Workng Paper 7565. Kao, K., D. Sknner, and M. Kummura. 2006. When Volunary Dsclosure Isn Volunary: Managemen Forecass n Japan. Osaka Unversy of Economcs Workng Paper Seres 2005-09. Khanna, T., K.G. Palepu, and J.J. Chang. 2000. Analys acvy around he World. Harvard Unversy Workng Paper. Krshnakumar, J. 2003. Tme Invaran Varables and Panel Daa Models. Panel Daa Economercs: Theorecal Conrbuons and Emprcal Applcaons. Eded By B. Balag. p 119-132. La Pora, R., Lopez-de-Slanes, F., Shlefer, A., and R.W. Vshny. 1998. Law and Fnance. Journal of Polcal Economy 106, 1113-1155. Lamber, R, C. Leuz, and R.E. Verreccha. 2006. Accounng Informaon, Dsclosure, and he Cos of Capal. The Wharon School. Unversy of Pennsylvana. Mmeo. Lang, M.H. and R. Lundholm. 1996. Corporae Dsclosure Polcy and Analys Behavour. Accounng Revew71(4): 467-492. Lee, C., D. Ng, and B. Swamnahan. 2004. Inernaonal Asse Prcng: Evdence from he Cross Secon of Impled Cos of Capal. Cornell Unversy. Mmeo McNchols, M. and P.C. O Bren. 1997. Self-Selecon and Analys Coverage. Journal of Accounng Research 35: 167-199. Modglan F. and M. Mller. 1958. The cos of capal, corporaon fnance, and he heory of nvesmen. Amercan Economc Revew 48: 261-297. Oaxaca, R.L. and I. Gesler. 2003. Fxed Effecs Models wh Tme Invaran varables: A Theorecal Noe. Economcs Leers 80: 373-377. O Bren, P.C., M.F. McNchols, and H-W Ln. 2005. Analys Imparaly and Invesmen Bankng Relaonshps. Mmeo. Ohlson, J. and B. Juener-Nauroh. 2000. Expeced EPS and EPS Growh as Deermnans of Value. New York Unversy. Mmeo. 27
Peersen, M. 2007. Esmang Sandard Errors n Fnance Panel Daa Ses: Comparng Approaches. Kellogg School of managemen. Mmeo. Polachek, S.W. and M. Km. 1994. Panel esmaes of he Gender Earnngs Gap: Indvdual Specfc Inercep and Indvdual-specfc Slope Models. Journal of Economercs, 61: 23-42. Spamann, H. 2006. On he Insgnfcance and/or Endogeney of La Pora e al s An-Drecor Rghs Index Under Conssen Codng. John M. Oln Cener for Law, Economcs, and Busness Fellows Dscusson Paper Seres. Task Force o Modernze Secures Regulaon n Canada. 2006. Canada Seps Up. Wmer, J. and L. Zorn. 2007. Esmang and Comparng he Impled Cos of Equy for Canadan and U.S. Frms. Bank of Canada Workng Paper 2007-48. World Bank. 2008. Dong Busness 2008. 28
Fgure 1: Prevous work on Cos of Equy. Ths graph summarzes resuls from 3 prevous sudes ha have provded cos of equy esmaes a a counry level. The Claus and Thomas (2001) sudy ulzes her cos of equy mehodology, and hey repor he cos of equy n local currency Hal and Leuz (2006a) esmae he cos of equy usng an average of four mehods and also repor resuls n local currency. Daouk, Lee, and Ng (2006) measure he cos of equy usng he Gordon Growh Model appled o ndex level prces and dvdends. 29
Fgure 2: Cos of Equy by Counry. Ths graph dsplays he mean of he USD nomnal cos of equy for each counry n he sample. 30
Fgure 3: Scaer Plos. These graphs plo he medan nomnal cos of equy (by counry-year) agans he medan forecas dsperson (3a), medan frm sze (3b), and he medan real cos of equy agans real governmen yelds n 3c. Squares represen observaons on Canada, damonds represen observaons on Japan, and sold crcles represen observaons on Uned Saes. 31
Fgure 4: Real Cos of Equy vs Invesor Proecon. Ths graphs plos he medan real cos of equy (by counry) agans he World Bank s (2008) Invesor Proecon Index, adaped from Djankov e al (2008). Ths ndex s based on a hypohecal ransacon beween wo companes n whch he owner has conrollng sakes, and measures he exen of dsclosure, exen of drecor lably, and ease of shareholder sus n relaon o he ransacon. Each of hese ndces s measured on a scale of 0 o 10 (wh 10 represenng more dsclosure, more drecor lably, or more ably for shareholders o sue), and are averaged o develop an overall Invesor Proecon Index. 32
Table 1: Summary Sascs (Medans). Ths able presens medans for key varables for each counry n our sample. N ndcaes he number of observaons, or frm-years, by counry. Toal Asses s calculaed usng book values from Compusa and s convered no USD. Leverage s he Deb/ Equy rao and s also calculaed usng book values. Forecas dsperson s he cross-seconal sandard devaon of analys earnngs forecass, scaled by book value per share. % Frms wh Losses s he percenage of frms n each counry n our sample wh a cos of equy esmae who experenced losses n he prevous fscal year. Forecas Bas s he counry average forecas error (forecased earnngs mnus predced earnngs, scaled by book value per share) n he prevous year. Forecas Inaccuracy s he absolue value of he analys forecas error n he prevous year. Counry N Toal Asses ($M) Leverage Forecas Dsperson % Frms wh Losses Accounng Mehod Forecas Bas Forecas Inaccuracy AUSTRALIA 1,420 383.38.0096.09.12.015.029 AUSTRIA 151 452.32.015.11.99.013.032 BELGIUM 349 457.35.015.1.52.019.033 CANADA 3,057 421.37.011.1 1.00026.03 DENMARK 526 320.28.011.049.41 -.0052.032 FINLAND 582 350.34.017.077.47 -.0016.045 FRANCE 1,929 499.32.014.076.69.01.027 GERMANY 1,385 459.17.014.11 1.0095.036 GREAT BRITAIN 6,082 275.22.0086.089.39.005.037 IRELAND 308 393.44.0056.078.19 -.0046.028 ITALY 501 631.31.017.072.13.011.033 JAPAN 3,651 779.22.0064.11.81.0028.026 NETHERLANDS 1,084 441.31.015.046.79.013.027 NEW ZEALAND 216 144.48.011.074.25 -.0014.043 NORWAY 454 280.45.025.16.75.027.052 SPAIN 544 753.33.015.029.18.0053.022 SWEDEN 958 317.3.016.092.64.0095.044 SWITZERLAND 768 640.28.012.074.8 -.003.031 USA 23,679 656.35.0051.1 1.0037.026 Toal 47,644 532.31.0073.096.81.0037.029 33
Table 2: Fxed Effecs Regressons COE, All Counres. PANEL A: Ths panel presens resuls for dfferen specfcaons of he followng fxed effecs regresson nvolvng he USD nomnal cos of equy (assumng a random walk exchange rae): COE LOSS IASB 2006 = α + β = 1991 LOSS IASB YEAR _ YEAR FBIAS + µ + ε FBIAS BVA BVA LEV FINACCURACY LEV DISP DISP FINACCURACY Absolue value of z sascs are n parenheses and are adjused for heeroskedascy of errors a a frm level (*sgnfcan a 10%; ** sgnfcan a 5%; *** sgnfcan a 1%). (1) (2) (3) (4) Ln(Asses) -0.187-0.012 0.039 0.010 (3.87)*** (0.25) (0.67) (0.18) Leverage 0.891 0.750 0.673 0.650 (18.66)*** (15.39)*** (12.28)*** (12.36)*** -0.142-0.150-0.125-0.130 (11.33)*** (11.77)*** (9.95)*** (10.30)*** Forecas Dsperson 26.955 25.349 26.320 (13.54)*** (10.97)*** (11.51)*** Forecas Inaccuracy 3.091 0.436 (12.88)*** (1.58) Loss Dummy 1.633 (16.58)*** Forecas Bas -0.571 (0.31) IASB Dummy 0.351 (2.80)*** Consan 13.842 12.387 11.460 11.687 (45.50)*** (38.04)*** (32.26)*** (33.34)*** Observaons 47153 43209 37024 37024 Number of frms 8102 7520 6829 6829 Year Dummes YES YES YES YES Overall R-squared 0.06 0.07 0.07 0.10 Whn R-squared 0.06 0.07 0.08 0.09 Beween R-squared 0.05 0.07 0.06 0.10 34
PANEL B: Ths panel presens resuls for dfferen specfcaons of he followng second sage regresson nvolvng fxed frm-level effecs ( µˆ ) esmaed n Panel A: ˆ µ = ω + + 1 YEAR _ = 1991 LOSS β 2006 COUNTRY γ LOSS COUNTRY YEAR FBIAS + BVA FBIAS K k = 1 β BVA IND _ k LEV FINACCURACY k ACCOUNTING IASB IASB + v NORDIC counres nclude Fnland, Norway, Sweden, and Denmark. OTHER EUROPEAN ncludesausra, Belgum, Ialy, Neherlands, Span, and Swzerland.Absolue value of z sascs are n parenheses (*sgnfcan a 10%; ** sgnfcan a 5%; *** sgnfcan a 1%). (1) (2) (3) (4) USA -0.415-0.164-0.229-0.192 (3.93)*** (1.56) (2.09)** (1.81)* JAPAN -0.943-1.002-1.091-1.179 (6.52)*** (6.92)*** (7.35)*** (8.12)*** GBR & IRELAND 0.091-0.012-0.171 0.083 (0.75) (0.10) (1.34) (0.58) NORDIC 0.979 0.588 0.524 0.657 (6.62)*** (3.93)*** (3.32)*** (4.03)*** AUSTRALIA & NZ 0.325 0.303 0.205 0.380 (1.95)* (1.83)* (1.17) (1.98)** FRANCE -0.273-0.607-0.640-0.610 (1.70)* (3.79)*** (3.65)*** (3.40)*** GERMANY 0.439 0.117 0.342 0.256 (2.47)** (0.65) (1.72)* (1.22) OTHER EUROPEAN 0.220-0.095-0.033 0.070 (1.60) (0.69) (0.23) (0.45) Accounng Dummy 0.140 (1.42) Consan 3.746 4.486 4.294 3.728 (5.25)*** (6.45)*** (10.02)*** (8.67)*** Indusry Dummes YES YES YES YES Observaons 8102 7520 6829 6829 R-squared 0.19 0.21 0.22 0.23 IND LEV DISP DISP FINACCURACY ACCOUNTING 35
Table 3: Fxed Effecs Regressons Real COE, All Counres. PANEL A: Ths panel presens resuls for dfferen specfcaons of he followng fxed effecs regresson nvolvng he real cos of equy: COE LOSS IASB 2006 = α + β = 1991 LOSS IASB YEAR _ YEAR FBIAS YIELD FBIAS YIELD BVA BVA + µ + ε FINACCURACY LEV LEV DISP DISP FINACCURACY Absolue value of z sascs are n parenheses and are adjused for heeroskedascy of errors a a frm level (*sgnfcan a 10%; ** sgnfcan a 5%; *** sgnfcan a 1%). (1) (2) (3) (4) (5) Ln(Asses) -0.100-0.110 0.016 0.021 0.005 (2.59)*** (2.81)*** (0.39) (0.46) (0.11) Leverage 0.681 0.677 0.571 0.525 0.508 (17.33)*** (17.31)*** (14.30)*** (11.69)*** (11.64)*** -0.067-0.038-0.041-0.047-0.053 (6.60)*** (3.64)*** (3.81)*** (4.35)*** (4.86)*** Real Gov Yelds 0.209 0.218 0.203 0.209 (9.72)*** (9.98)*** (8.74)*** (8.95)*** Forecas Dsperson 22.155 21.173 21.693 (13.74)*** (11.27)*** (11.65)*** Forecas Inaccuracy 2.161 0.518 (11.44)*** (2.39)** Loss Dummy 1.005 (13.55)*** Forecas Bas 1.051 (0.72) IASB Dummy 0.454 (4.39)*** Consan 9.931 9.123 7.959 7.909 8.007 (40.96)*** (34.83)*** (28.37)*** (25.28)*** (25.69)*** Observaons 47887 46807 42875 36710 36710 Number of frms 8198 8013 7441 6761 6761 Year Dummes YES YES YES YES YES Overall R-squared 0.04 0.05 0.06 0.07 0.09 Whn R-squared 0.05 0.05 0.07 0.07 0.08 Beween R-squared 0.03 0.05 0.06 0.06 0.08 36
PANEL B: Ths panel presens resuls for dfferen specfcaons of he followng second sage regresson nvolvng fxed frm-level effecs ( µˆ ) esmaed n Panel A: ˆ µ = ω + + 1 YEAR _ = 1991 LOSS β 2006 COUNTRY γ LOSS COUNTRY YEAR FBIAS + BVA FBIAS K k = 1 β BVA IND _ k LEV k FINACCURACY ACCOUNTING IASB IASB YIELD YIELD + v Absolue value of z sascs are n parenheses (*sgnfcan a 10%; ** sgnfcan a 5%; *** sgnfcan a 1%). (1) (2) (3) (4) (5) USA -0.508-0.413-0.250-0.338-0.288 (5.75)*** (3.36)*** (2.05)** (2.67)*** (2.31)** JAPAN -0.565-0.409-0.434-0.591-0.598 (4.71)*** (2.17)** (2.27)** (3.01)*** (3.05)*** GBR & IRELAND -0.026 0.040-0.042-0.199-0.007 (0.25) (0.34) (0.36) (1.61) (0.05) NORDIC 0.928 0.973 0.750 0.709 0.746 (7.47)*** (7.43)*** (5.62)*** (5.02)*** (5.05)*** AUSTRALIA & NZ 0.198 0.247 0.228 0.088 0.212 (1.40) (1.67)* (1.54) (0.56) (1.22) FRANCE -0.112-0.026-0.248-0.306-0.303 (0.83) (0.18) (1.72)* (1.94)* (1.86)* GERMANY 0.360 0.406 0.212 0.441 0.310 (2.41)** (2.52)** (1.29) (2.44)** (1.62) OTHER EUROPEAN 0.359 0.476 0.296 0.270 0.315 (3.10)*** (3.33)*** (2.08)** (1.79)* (1.97)** Accounng Dummy 0.116 (1.33) Consan 3.615 4.301 5.056 4.366 3.925 (6.08)*** (6.43)*** (7.69)*** (9.44)*** (8.26)*** Indusry Dummes YES YES YES YES YES Observaons 8198 8013 7441 6761 6761 R-squared 0.21 0.20 0.20 0.21 0.21 IND LEV DISP DISP FINACCURACY ACCOUNTING 37
Table 4: Regresson wh Counry Level Index Measures Ths able presens resuls for dfferen specfcaons of he followng second sage regresson nvolvng fxed frm-level effecs ( û ) esmaed n Table 3, Panel A (Fnal Column): uˆ = ω + YEAR _ = 1991 LOSS IP _ INDEX 2006 γ LOSS IP _ INDEX YEAR FBIAS + BVA FBIAS K k = 1 β BVA IND _ k LEV k FINACCURACY ACCOUNTING IASB IASB YIELD YIELD + v Absolue value of z sascs are n parenheses (*sgnfcan a 10%; ** sgnfcan a 5%; *** sgnfcan a 1%). IND LEV DISP DISP FINACCURACY ACCOUNTING (1) (2) (3) (4) Dsclosure -0.100 (5.78)*** Drecor Lably -0.035 (2.65)*** Shareholder Lawsus -0.059 (2.47)** Invesor Proecon -0.117 (4.89)*** Accounng Dummy -0.173 0.021-0.000 0.022 (2.56)** (0.29) (0.01) (0.33) Consan 3.641 3.314 3.585 3.947 (9.07)*** (8.23)*** (7.97)*** (9.16)*** Observaons 6761 6761 6761 6761 R-squared 0.20 0.20 0.20 0.20 38
Table 5: Fxed Effecs Regressons by Counry. Ths able presens resuls for counry-level fxed effecs regressons nvolvng he real cos of equy, and he second sage regresses he frm fxed effecs on means of he me-varyng varables as well as he me nvaran varables. Absolue value of sascs are n parenheses and are adjused for heeroskedascy of errors a a frm level (* sgnfcan a 10%; ** sgnfcan a 5%; *** sgnfcan a 1%). COE = α BVA LEV LOSS DISP YIELD FINACCURACY IASB + µ + BVA LEV LOSS DISP YIELD FINACCURACY IASB ε CANADA USA GBR & IRELAND FRANCE GERMANY NORDIC OTHER EUROPE JAPAN AUSTRALIA & NEW ZEALAND Ln(Asses) -0.312-0.108 0.038 0.792 1.494 0.854 1.311-0.068-0.196 (1.77)* (2.76)*** (0.35) (3.91)*** (3.89)*** (3.74)*** (5.87)*** (0.24) (0.88) Leverage 1.007 0.539 0.336 0.116 0.411 1.003 0.209-0.181 1.270 (4.16)*** (10.08)*** (2.47)** (0.59) (1.04) (4.09)*** (1.03) (0.75) (3.68)*** Real 10Yr Gov Yeld 0.195 0.141-0.130 0.274 0.127 0.291 0.284 1.460 0.212 (3.41)*** (6.16)*** (3.22)*** (3.12)*** (0.80) (4.49)*** (4.21)*** (12.16)*** (3.46)*** Forecas Dsperson 7.035 35.710 16.430 9.324 7.218 13.399 13.474 63.773-2.203 (1.05) (10.74)*** (3.91)*** (1.38) (0.79) (3.02)*** (2.88)*** (8.49)*** (0.30) Forecas Inaccuracy 0.631 0.494 0.692 2.826 1.402 0.432 0.389-0.818-0.219 (0.62) (1.67)* (1.27) (2.34)** (0.98) (0.51) (0.45) (0.69) (0.26) Loss Dummy 0.992 1.056 0.791 1.012 1.389 1.902 1.811 0.531 0.356 (3.12)*** (11.03)*** (3.58)*** (2.53)** (3.13)*** (5.28)*** (4.57)*** (2.21)** (0.96) IASB Dummy 0.000 0.000-0.429 0.252-0.182-0.261-0.102 0.000 0.081 (.) (.) (2.49)** (0.91) (0.58) (1.29) (0.44) (.) (0.13) Consan 9.795 8.050 8.922 1.658-1.416 2.934-0.528 5.870 9.367 (7.93)*** (26.73)*** (12.06)*** (1.02) (0.52) (1.98)** (0.34) (2.94)*** (6.57)*** Observaons 2223 19559 4319 1288 871 1810 2338 3077 1225 Number of frms 444 2992 817 279 253 385 469 890 232 Overall R-squared 0.05 0.12 0.02 0.00 0.03 0.01 0.01 0.11 0.03 Whn R-squared 0.06 0.07 0.05 0.09 0.09 0.10 0.09 0.15 0.05 Beween R-squared 0.05 0.15 0.00 0.01 0.05 0.00 0.01 0.06 0.02 39
Table 6: Panel Regressons All Counres Real COE. Ths able presens resuls usng dfferen economerc mehods. The frs column, Fxed Effecs, re-presens he resuls from he las column of he prevous able (coeffcens from boh sages n he regresson are dsplayed for brevy and comparson purposes). Absolue value of sascs are n parenheses and are adjused for heeroskedascy of errors a a frm level. The second column presens coeffcens from Fama-Mcbeh (1973) regressons, whch are he average of coeffcens for 15 cross-seconal regressons (one for each year): COE K = ω + β COUNTRY, COUNTRY + 1 k = 1 YIELD YIELD FGROWTH, LEV, FGROWTH LEV β DISP, ACCOUNTING, IND _ k, DISP IND k LOSS, ACCOUNTING Fnally, he resuls of a Pooled OLS regresson are dsplayed n he las column. COE BVA FBIAS YIELD LEV ACCOUNTING DISP LOSS IASB BVA, LOSS K 2006 = ω + β COUNTRY COUNTRY + β IND _ k IND k + β YEAR _ 1 k = 1 = 1991 BVA FBIAS YIELD + ε LEV DISP ACCOUNTING LOSS IASB BVA + ε FINACC + YEAR FINACC Agan, sandard errors are adjused for heeroskedascy of errors a a frm level (*sgnfcan a 10%; ** sgnfcan a 5%; *** sgnfcan a 1%). 40
Table 6: Panel Regressons All Counres Real COE (Connued). Fxed Effecs Fama-Mcbeh Pooled OLS Ln(Asses) 0.005-0.264-0.299 (0.11) (7.33)*** (18.57)*** Leverage 0.508 0.643 0.575 (11.64)*** (8.18)*** (14.49)*** -0.053-0.069 (4.86)*** (6.73)*** Real Gov Yelds 0.209 0.085 0.163 (8.95)*** (0.64) (6.69)*** Forecas Dsperson 21.693 27.626 23.494 (11.65)*** (7.03)*** (12.95)*** Forecas Inaccuracy 0.518 0.187 0.348 (2.39)** (0.83) (1.52) Loss Dummy 1.005 1.547 1.442 (13.55)*** (17.54)*** (18.81)*** Forecas Bas 1.051-2.733-0.139 (0.72) (0.32) (0.09) IASB Dummy 0.454-0.391 0.423 (4.39)*** (0.87) (3.73)*** Accounng Dummy 0.116 0.007 0.002 (1.33) (0.08) (0.02) USA -0.288-0.339-0.232 (2.31)** (1.74) (1.91)* JAPAN -0.598-0.537-0.578 (3.05)*** (2.02)* (3.92)*** GBR & IRELAND -0.007-0.075-0.016 (0.05) (0.41) (0.11) NORDIC 0.746 0.248 0.633 (5.05)*** (1.07) (3.78)*** AUSTRALIA & NZ 0.212 0.278 0.082 (1.22) (1.26) (0.41) FRANCE -0.303-0.060-0.407 (1.86)* (0.26) (2.43)** GERMANY 0.310-0.074 0.182 (1.62) (0.34) (0.94) OTHER EUROPEAN 0.315 0.073 0.217 (1.97)** (0.23) (1.34) Year Dummes YES YES YES Indusry Dummes YES YES YES Observaons 36710 36710 36710 41
Table 7: Counry Medan Regressons. Ths able repors he resuls of an OLS regresson of he counry-year medan real cos of equy agans he counry-year medans of oher explanaory varables. Robus sascs are n parenheses (* sgnfcan a 10%; ** sgnfcan a 5%; *** sgnfcan a 1%) (1) (2) (3) (4) (5) Ln(Asses) -0.132-0.239-0.125-0.121-0.197 (0.65) (1.25) (0.64) (0.56) (1.03) Leverage 2.274 2.470 2.426 2.209 2.614 (3.04)*** (2.82)** (2.57)** (2.41)** (2.79)** Real Gov Yelds 0.175 0.204 0.173 0.175 0.187 (2.53)** (3.20)*** (2.70)** (2.48)** (2.84)** Forecas Dsperson 63.927 53.523 57.951 65.970 50.622 (2.83)** (2.40)** (2.56)** (2.40)** (2.26)** Forecas Inaccuracy 22.082 21.304 22.704 21.894 22.674 (2.94)*** (2.85)** (3.15)*** (2.89)*** (3.00)*** Loss Dummy 1.785 2.043 1.949 1.740 2.113 (1.55) (1.74)* (1.75)* (1.53) (1.92)* Forecas Bas -5.730-4.932-5.641-5.691-5.418 (1.13) (0.97) (1.11) (1.13) (1.05) Dsclosure -0.077 (2.08)* Drecor Lably -0.044 (0.62) Shareholder Lawsus 0.014 (0.16) Invesor Proecon -0.097 (1.42) Consan 6.422 7.487 6.606 6.279 7.333 (5.24)*** (5.94)*** (5.61)*** (3.95)*** (5.81)*** Observaons 219 219 219 219 219 R-squared 0.44 0.46 0.45 0.44 0.45 42
Appendx: Summary of Impled COE Calculaons r_c: Claus and Thomas (2001) mpled COE s he value of r ha solves: g L e3(1 ) dp * e1 dp * e2 roe3 e3 P0 = + +, where roe 2 2 3 = 1+ r (1 + r) (1 + r) ( r g ) bv + ( e + e2)(1 dp) L 0 1 r_lns: Lee, Ng, and Swamnahan (2004) mpled COE s he value of r ha solves: 15 dp * e1 dp * e2 dp * e e16 P0 = + + 2 + 15 1+ r (1 + r) (1 + r) r(1 + r) 2 g 13 L 3 3 g L For > 3: e + 1 = e (1 + g S ) and dp = (1 ) dp + (1 ) g S 13 13 r Earnngs growh s faded owards he long-run earnngs growh and he dvdend payou rao s faded owards he long-run dvdend payou rao by year 16. = 3 r_oj: Ohlson and Juener-Nauroh (2000) mpled COE s he value of r ha solves: dp * e1 e1 ( g S g L ) P0 = + ( r g ) r( r g ) L L r_mpeg: Eason (2004) mpled COE s he value of r ha solves: dp * e1 e1 g S P0 = + 2 r r Varables across all models (for COE calculaon n USD): P 0 = Curren marke prce. e = Expeced fuure earnngs per share perods ahead. (In he CT and LNS model, e 3 = e 2 * (1+g S )). g S = Shor-erm growh rae, or (e 2 -e 1 )/ e 1 g L = Long-erm growh rae n earnngs per share, usng he U.S. expeced nflaon rae, aken from he IFO World Economc Survey (hrough Daasream). dp = Dvdend payou rao, usng he average hsorc payou rao (dvdends plus repurchases, dvded by earnngs) over he prevous hree years. If unavalable, he mean counry payou rao n ha year s used. bv 0 = Curren book value per share. 43