Scienific Annals of he Alexandru Ioan Cuza Universiy of Iaşi Economic Sciences 62 (2), 2015, 221-239 DOI 10.1515/aicue-2015-0015 BOND YIELD SPREADS IN THE EUROZONE Denisa PROKSOVÁ * Mária BOHDALOVÁ ** Absrac Euro Area sovereign bond yield spreads fell significanly afer he creaion of he moneary union and moved in unison unil he recession of 2008, when invesors risk pricing changed considerably. Rising bond yield spreads caugh he aenion of economiss who ried o find he facors influencing heir size. Evoluion of bond spreads was mosly relaed o various macroeconomic facors as well as he soundness of he counries banking secors and a general level of risk aversion in he financial markes. Analysis presened in his paper compares bond yield spreads of Euro Area member counries and relaes hem o heir deb levels as well as he liquidiy of he securiies and a general level of risk aversion. Apar from he usual variables, we also analysed differences in purchasing power o assess he impac of he common moneary policy in he pre-crisis period. Afer adjusing he model o beer explain movemens of linear regression residuals, we could no prove a sysemaic assessmen of he above-menioned facors excep for ime periods of high marke volailiy. We explain sudden changes in he imporance of idiosyncraic facors as consequences of policies of he European Cenral Bank and oher European Union insiuions following such ime periods, which, as our analysis suggess, disored pricing of risk in he markes. Keywords: bond spread, bond yield, Euro Area, moneary union, EMU JEL classificaion: E42, G15 1. INTRODUCTION Increased bond yields of cerain Euro Area counries afer he sar of he morgage and financial crisis caused serious problems for many governmens and even gave rise o quesions abou several members exiing he common currency block. The financial and economic siuaion in he region promped several governmens o resign o various bailou schemes organized by he EU and he IMF. Yield spreads among governmen bonds, which had been minimal since he sar of he moneary union, were once again relaively large, reflecing differen risk premium. Invesors risk pricing changed afer he onse of he morgage and financial crisis when spreads of individual Euro Area counries widened. Economiss focused * Faculy of Managemen, Comenius Universiy, Braislava, Slovakia; e-mail: denisa.proksova@fm.uniba.sk. ** Faculy of Managemen, Comenius Universiy, Braislava, Slovakia; e-mail: maria.bohdalova@fm.uniba.sk.
222 Denisa PROKSOVÁ, Mária BOHDALOVÁ on idenifying he facors ha caused his rise in yield spreads, esing he imporance of facors heoreically relevan in deermining bond yield spreads and assessing he exac size of heir impac on spreads. In imes of global financial uncerainy, invesors seek securiies wih lower credi risk and higher liquidiy, driving spreads of lower-qualiy bonds up. This was also he case in he Euro Area, whose common moneary policy and low inflaion risk decreased differenials in sovereign bond yields of is member counries o a minimum, bu deerioraion in heir public finances raised heir risk premiums back o previous levels; however, his ime moneary policy remained ouside of heir conrol. Euro Area sovereign bond yields used o move in unison bu sared o be influenced by differen facors from 2008 on. Economiss ried o find he facors influencing he developmens in Euro Area bond markes and he price for risk assigned o hem by he markes. Mos empirical sudies sress he imporance of credi risk, illiquidiy, and global risk aversion as drivers of sovereign bond spreads bu also include variables which capure oher relevan facors, such as he siuaion in he banking secor of individual Euro Area members. Their findings poin ou o disinc differences beween risk pricing before he financial crisis and aferwards. Risk pricing afer he sar of he financial crisis seems o be more in line wih he heory bu also appears o price in various risks ha are no jusified by heoreical assumpions. These sudies es he relevance of credi risk, liquidiy, and inernaional risk aversion as he main drivers of increasing bond yields. These variables ener as endogenous variables in linear regression while he dependen variable is bond spreads o Germany. The resuling coefficiens differ significanly depending on he ime period; macroeconomic variables ofen showing lile relevance before 2007/2008. The aim of his paper is o analyse and show he imporance of several facors mos commonly lised by lieraure as deermining bond yield spreads hroughou a longer ime period and compare he resuls wih he resuls of oher auhors. The paper is organized ino four chapers. The second chaper reviews relaed lieraure. I liss a few oher papers wih common analyses and briefly commens on heir findings. The hird chaper describes our daa and mehodology which includes variables commonly used in oher auhors regressions as well as a few oher variables. The fourh chaper describes our findings and he las chaper hen commens on our findings as well as he findings of oher auhors. I ries o compare hem, find similariies, and explain he differences. 2. LITERATURE REVIEW In his secion we aim o review some lieraure relaed o he issue of Euro Area Bond Yield Spreads. We describe mehods and resuls of oher auhors and compare hem. Mos of hese auhors use similar mehodology bu analyse slighly differen ime periods and facors influencing bond spreads. We will focus our aenion on hree papers: Barrios e al. (2009); Barbosa and Cosa (2010) and Afonso e al. (2012). We will describe he resuls of hese auhors more in deph bu we will also briefly describe some new findings of oher auhors. We begin his chaper wih a descripion of he mehodology used by oher auhors, which can hen be compared o our mehodology. All he above-menioned auhors used linear regression analysis in order o assess he influence of several variables on bond spreads of Euro Area counries. The mos imporan variables in hese regressions are credi risk, liquidiy, and risk aversion. While he wo former variables can be assessed relaively easily, he las one is someimes hard o esimae. These auhors herefore use principal componen analysis o find common paerns in
Bond Yield Spreads in he Eurozone 223 financial markes which could be aribued o differen levels of risk aversion in inernaional financial markes. Apar from his, many auhors also analyse common paerns in he movemen of European bond spreads. This analysis was applied by Barrios e al. (2009) and Afonso e al. (2012). Barrios e al. (2009), compared he firs componens of 2 principal componen analyses: he firs principal componen of Euro Area sovereign bond yield spreads and he firs principal componen of 4 various risk indicaors: corporae bond spreads in AAA- and BBB- bonds, euro-yen exchange rae volailiy and sock price volailiy. The laer was used as a measure of global risk aversion in inernaional markes. The wo resuling firs principal componens proved a close relaion beween risk aversion and bond spreads from June 2005 o Sepember 2008. However, when comparing he wo componens, here was a sudden divergence of he wo firs componens a he sar of he financial crisis. Unil he sar of he financial crisis, boh of he componens moved in unison, reacing similarly o exernal shocks, bu his changed afer he sar of he financial crisis when here was a relaive increase in he price of risk for European sovereign bonds wihou a corresponding increase in risk aversion. Afonso e al. (2012) also used PCA o idenify common paerns in Euro Area bond yield spreads. The firs componen included similar loadings for all he included counries bu he second componen showed posiive values only for he core counries and negaive values for counries hi by he deb crisis. The second componen was herefore idenified as measuring ransmission effecs of he deb crisis o he so-called core counries. I explained around 15% of he variance, whereas he res of he componens did no seem o affec he evoluion of bond spreads srongly. The second principal componen, which was calculaed by Barrios e al. (2009) for a slighly shorer ime period (Jan 2005 Jul 2009), resuled in negaive weigh for all he counries excep for Ireland, Greece, and Ausria whose banking sysems were already influenced by he crisis a he ime of wriing; suggesing a similar finding. Barrios e al. (2009), found general risk percepion o be he mos imporan bu no he only facor in deermining he size of sovereign spreads in he Euro Area. The daa seems o sugges ha while relevance of domesic fiscal indicaors is higher in imes of heighened risk aversion, i is especially heir ineracion wih higher risk aversion ha raised bond spreads. They sudied weekly changes in bond spreads o Germany and, like many oher auhors hey also used linear regression o find he price for risk assigned o various risk facors, boh idiosyncraic and oher. Independen variables enering he regression analysis were expressed in relaion o Germany and included changes in CDS spreads as a measure of credi risk and changes in bid-ask spreads as an esimae of liquidiy. The firs principal componen of risk indicaors was also included as an esimae of general risk percepion. Finally, hey included a crisis variable equal o one from Sepember 2009 onwards and zero oherwise. Credi risk was significan in case of Ausria, Ialy, Porugal, Spain, and Greece, whereas liquidiy was imporan in deermining yield spreads of France, Greece, and Ialy. Risk aversion, on he oher hand, was relevan mainly for Belgium, France, Ialy, and Porugal. The above-menioned crisis-effec variable was significan for all counries excep Spain and Ialy. Calculaing coefficiens for separae ime periods, before and afer he sar of he financial crisis, showed a limied effec of idiosyncraic facors on bond spreads before he sar of he financial crisis and significanly lower explanaory power. However, risk aversion indicaor was significan for all counries excep for Ausria. Anoher sudy of his kind is Barbosa and Cosa (2010) which analyzed bond yield spreads beween January 2007 and May 2010. The counries included in heir analysis were
224 Denisa PROKSOVÁ, Mária BOHDALOVÁ he iniial Euro Area members excep for Luxembourg. They used securiies wih residual mauriy of around 5 and 10 years; using CDS premiums and a weighed average of forecass of macroeconomic variables relaed o public finances and counries exernal posiion as measures of credi risk. The auhors concluded ha forecass of inernaional insiuions explain changes in credi risk premiums beer han observed daa. Barbosa and Cosa s measures of liquidiy are expressed in relaion o Germany and include a wide range of variables; such as ransacions coss, rading volumes, and ousanding amouns. Inernaional risk appeie was measured using he firs principal componen of several measures of risk aversion: corporae bond spreads, CDS premiums, marke volailiy, ec. Their findings sugges a significan increase in he imporance of idiosyncraic facors afer he collapse of Lehman Brohers. Their imporance was smaller during he ime period leading up o he sar of he financial crisis when he main deerminan of sovereign bond yield spreads was global risk aversion. The imporance of credi risk and liquidiy increased afer Sepember 2008. Liquidiy condiions proved o be relevan especially in case of securiies wih shorer residual mauriy; securiies wih longer residual mauriy, on he oher hand, displayed higher conribuion of credi risk. Macroeconomic variables were relevan in deermining bond yield spreads boh in case of variables describing recen rends as well as heir baseline posiion. Credi risk was relevan especially in case of Greece, bu also Ialy and Porugal. Liquidiy did no seem o affec big economies, such as Ialy and France. Afonso e al. (2012) also used linear regression o es he relevance of macroeconomic variables and inernaional risk aversion bu also included oher variables, which were no included in he former analyses: lagged spread, real exchange rae, growh of indusrial producion, and a crisis ransmission indicaor, which is he second principal componen of sovereign bond spreads o Germany. The purpose of heir analysis was o find common coefficiens for all he included counries, which included he so-called core counries as well as Souh European counries. Their regression analysis proved only lagged spread, risk percepion, liquidiy indicaor, and growh of indusrial producion significan a 1% level. The res of he variables, including crisis ransmission indicaor and macroeconomic indicaors capuring he level of indebedness, were insignifican. Inclusion of a muliplicaive erm which muliplied pas spread level and bid-ask spread (heir liquidiy indicaor) proved significance of he ineracion of spreads and liquidiy a 1% level. Including his variable made he liquidiy indicaor insignifican and close o zero while significance of he governmen budge balance changed from 1% o 5%. The former regressions were repeaed using he same variables and heir muliplicaions wih dummy variables equal o one from Augus 2007 and March 2009 on and zero oherwise in order o find any changes in marke s percepion of risk over ime. Including hese dummy variables slighly improved he explanaory power of he regression analysis. The resuls showed ha risk percepion was only relevan o deermining spreads from Augus 2007 onwards, bu no from March 2009 onwards. The variable iself wihou a muliplicaive erm was insignifican which conradics he findings of he former auhors Barrios e al. (2009) and Barbosa and Cosa (2010) who assumed risk percepion o be he main driver of bond spreads before he financial crisis bu who also used a slighly differen approach. All of he auhors used marke volailiy as measures of risk percepion bu he former auhors also included daa from bond spreads in heir risk aversion indicaors. This difference in daa and mehodology migh have been he reason of differen findings. Coefficien of he crisis ransmission o he core counries, which was insignifican in he firs analysis, was significan when muliplied by he March 2009 dummy variable.
Bond Yield Spreads in he Eurozone 225 While muliplicaion by he Augus 2007 dummy variable resuled in a coefficien wih higher significance, he coefficien was negaive. There seems o be a compensaion for his afer March 2009 when he coefficien is posiive and higher, which makes also he sum of boh of he coefficiens posiive. Significance of macroeconomic fundamenals rose; budge balance was significan and deb-o-gdp was significan afer March 2009. Liquidiy, which was insignifican in he former analyses, was significan when muliplied by he March 2009 dummy variable. The share of long-erm governmen deb in he overall sock of deb was also insignifican when added o he former analysis bu exhibied quie a high significance afer being muliplied by boh of he dummy variables. The coefficien for March 2009 is negaive, and he sum of he 2 coefficiens is also negaive, which he auhors inerpreed as he abiliy o successfully place long-erm deb priced wih lower spreads by he markes. Spread muliplied by he bid-ask spread was only significan afer inclusion of he March 2009 dummy variable; however, negaive. Overall, he above-menioned auhors found ha he markes did no price in macroand fiscal fundamenals in sovereign spreads unil he sar of he morgage crisis; he role of liquidiy also seems o be limied during his ime period. Many cied auhors assume inernaional risk aversion o be he main driver of bond spreads in his ime period, Barrios e al. (2009) and Barbosa and Cosa (2010) among hem. Credi risk seems o be relevan; wih cerain sovereigns exhibiing permanenly higher spreads irrespecive of heir fiscal posiion. However, credi risk premium did no seem o be affeced by marke volailiy and marke uncerainy ha much. Slighly higher risk premiums seemed o reflec differenials in bond yields from before he sar of he moneary union. These differenials (before 1999) arose mosly because of higher inflaion raes of cerain counries. These counries managed o fulfil he Maasrich crieria and decrease he level of inflaion bu kep higher levels of inflaion because of increasing produciviy raes even afer he sar of he moneary union. High inflaion raes in an environmen wih equal nominal ineres raes made he real ineres raes of hese counries relaively low, which had adverse effecs on heir banking sysems. Mody and Sandri (2011) in heir paper sress he imporance of he soundness of he banking sysem for economic growh. Their analysis proves is imporance in deermining he level of spread and shows ha i became a significan risk facor afer he sar of he morgage crisis in 2007. The auhors compared he raio of a financial secor equiy index and an overall sock marke index of Euro Area members o 10-year sovereign spreads. Then hey used his daa in regression analyses o prove and calculae he exac size of is influence on bond spreads. The influence of he soundness of he banking secor on bond spreads was obvious. Since we assumed ha he banking secor was affeced by equaliy of ineres raes across he whole region, we decided o include variables ha could capure some implicaions of his equaliy: counry-specific inflaion raes, real exchange raes, and loss of purchasing power. These variables were no included in he former analyses, which mosly focused on differen kinds of variables insead. The nex chaper deals wih he daa and mehodology used in our own analysis o deermine he influence of several facors on he size of bond yield spreads o Germany. A firs we lis he variables included in our model and jusify heir inclusion. In he second par of he chaper we describe our daa and he deails of our model as well as an adjused model which does no give auocorrelaed residuals. Adjusing he model led o low explanaory power, which is why we decided o ake on a differen approach and analyse various ime periods o find any changes in he paerns of risk pricing. Our approach showed ha some variables were only significan during cerain ime periods, which suppors he idea ha risk
226 Denisa PROKSOVÁ, Mária BOHDALOVÁ pricing of sovereign bonds changed a a cerain poin in ime under he impac of he financial and economic crisis. 3. DATA AND METHODOLOGY We used a very similar mehodology o he mehodologies of he above-menioned papers. We analysed he influence of credi risk, liquidiy and risk aversion during he whole ime period of 2002 o 2013 using regression analysis and repeaed his analysis for differen ime periods. Counries included in he analysis were Euro Area members wih he excepion of smaller counries and new member saes: Belgium, Ireland, Greece, Spain, France, Ialy, he Neherlands, Ausria, Porugal, and Finland. Sovereign yield on German bonds was used as he risk-free rae for he Euro Area. Each of he counries was analysed separaely, based on monhly daa. Spread beween he respecive counry s yield on is 10- year sovereign bonds over German bond yields (European Cenral Bank, 2014) was used as he dependen variable. The whole ime period of he analysis is January 2002 o December 2013, which accouns for 144 observaions. We decided o analyse ime periods wih differen risk pricing separaely o be able o observe any changes in invesors risk percepion. The overall ime period was herefore divided ino 2 shorer ime periods: ime period before he financial crisis ha sared in Sepember 2008 (80 observaions) and ime period afer he sar of he financial crisis (64 observaions). The influence of credi risk, liquidiy and risk aversion was analysed for wo disinc ime periods: January 2002 o Augus 2008 and Sepember 2008 o December 2013. The analysis of he ime period before he financial crisis was hen compared wih a similar analysis including inflaion and real ineres raes, which is in line wih he assumpion ha high inflaion levels damaged he European banking secor, which laer proved o play a significan role in deermining he size of he spread afer he sar of he financial crisis Mody and Sandri (2011). High inflaion raes made real ineres raes oo low for cerain counries, which increased heir growh and made borrowing cheaper for boh he governmen and he banking secor. As a resul, counries ha had had high raes of inflaion and paid relaively high ineres raes before joining he moneary union could finance heir deb more easily afer joining he moneary union due o lower ineres raes. They managed o mee he Maasrich crieria bu heir economies required slighly higher ineres raes han ineres raes imposed by he European Cenral Bank afer he joining he moneary union. Inflaion also influences balance of rade hrough price adjusmen, which leads o differen levels of boh public and privae deb. We assumed ha real ineres raes migh have already been priced in bond spreads and repeaed he analysis using boh inflaion and real ineres raes. Then we subsiued hese variables wih he loss in purchasing power relaive o Germany since he sar of he currency union and irrevocable fixing of ineres raes. We included inflaion raes in our 2002 o 2008 regression bu did no do so for he res of he regressions because spreads seem o reac o slow economic growh, high deb, and budge cus which are associaed wih low inflaion and deflaion. The resuling regression would herefore reflec influence of economic growh on spreads raher han suppor our hypohesis. European counries experienced quie differen inflaion raes during he 2002 o 2008 ime period; he difference someimes being even 2% beween 2 Euro Area regions. Their produciviy and purchasing power changed over ime and differed more bu heir nominal ineres raes and nominal exchange raes were equal for all he regions. This had implicaions for heir growh raes as well as heir abiliy o service deb. While his migh have improved
Bond Yield Spreads in he Eurozone 227 growh raes in many cases, i made heir growh unequal over ime. We assumed ha low real ineres raes would increase indebedness of all of he secors (as opposed o jus he public secor expressed in he deb/gdp variable) and hus migh capure endency o creae more deb. Moreover, high inflaion induces o dissave and when i suddenly decreases, he counry s abiliy o service is deb is hreaened. Counry-specific inflaion raes and individual counry spreads are posiively correlaed a cerain ime periods (usually when growh raes are also relaively high) and negaively correlaed a oher ime periods (mosly in imes of slower growh). They are hardly ever close o zero see Figure no. 1. Source: ECB Saisical Daa Warehouse (2014a, 2014b, 2014c, 2014d), Soxx (2014), own calculaions Figure no. 1 Spread/Inflaion Correlaion Similarly o he above-menioned analyses, we supposed ha credi risk, liquidiy, and risk aversion would be he main drivers of bond spreads, and included hese variables in our regressions 1. Credi risk was measured as governmen deb o GDP (European Cenral Bank, 2014), which capures a large par of he governmen s abiliy o mees is liabiliies. Unforunaely, his daa is no available on a monhly basis. Therefore we used quarerly daa published by he ECB. Second independen variable in our regression was liquidiy. Lieraure liss muliple measures of liquidiy condiions in he markes. These measures usually depend on he value of ransacions, ousanding amouns, and ransacion coss. We used he value of ousanding amouns published by he ECB (European Cenral Bank, 2014) on a regular basis. These included he value of long-erm governmen deb, which was compared o he value of ousanding amouns of long-erm governmen deb of Germany. We creaed a raio of values of Germany o he values of each counry in order o capure he differen liquidiy condiions in comparison wih he benchmark bonds. This approach is differen from he one used in credi risk. Credi risk was no compared o Germany, alhough heighened credi risk in comparison wih he benchmark should raise spread. Even hough many sudies express credi risk in relaion o Germany, we did no do so, as here does no seem o be a srong relaion beween spread and relaive credi risk. Markes seem o price credi risk based on acual daa insead.
228 Denisa PROKSOVÁ, Mária BOHDALOVÁ Risk aversion was measured based on volailiy in he sock marke as well as in he money markes. Sock marke daa was rerieved from he STOXX Global 3000 index (Soxx, 2014), which included sock prices from all over he world, and hus beer capures risk percepion refleced in price movemens in inernaional sock markes. Daa from he money markes was rerieved from he ECB (European Cenral Bank, 2014), which publishes daily daa on he EUR/USD exchange rae. We calculaed monhly variaion coefficiens based on daily daa of boh of hese daa ses, ou of which we creaed a moving average a he lengh of 7 monhs. This daa was hen used in principal componen analysis Bohdalová and Greguš (2012) in calculaion of he firs principal componen, which should reflec common paerns in variance in boh of he markes. Heighened variance in sock and foreign exchange markes is usually due o higher inernaional risk percepion. We assumed herefore ha he firs principal componen ou of his daa would capure global risk aversion. The firs principal componen explains 95.6% of he variance of he daa. The resuls of he 2002-2008 analysis were hen compared o he resuls of he same analysis ha included also oher variables: inflaion 2, real ineres rae 3, and an overall change in purchasing power 4 since he sar of he moneary union. Inflaion raes were aken from he European Cenral Bank (European Cenral Bank, 2014) and used in he nex regression model, which included real ineres raes, calculaed based on ECB main refinancing raes (ECB Saisical Daa Warehouse, 2014b) and ineres raes. Since hese regressions resuled in auocorrelaed residuals, we adjused he model furher using differences and naural logarihms of our variables 5. Our independen variables were almos all insignifican for he chosen ime periods. Therefore we decided o ake on a differen approach and use his model wih daa of various ime lenghs. All of he used ime periods sared in January 2002 and wen furher ino he fuure unil he las analysis which ended in December 2013. We decided o analyse ime periods wih differen risk pricing separaely o be able o observe any changes in invesors risk percepion. The purpose of hese analyses was o find when changes in risk pricing occurred as he markes evolved under he changing economic environmen, deb crisis, persising banking secor issues, exremely low ineres raes, and an alering balance of rade. In line wih he hypohesis ha he markes sared o price in idiosyncraic facors only afer he sar of he financial crisis of 2008 or laer on, we repeaed he analysis wih an increasing number of observaions o find when his change in risk pricing occurred. Our daa sars in January 2002 and ends in December 2013. The shores ime period of our analysis conains 50 observaions, which corresponds wih he ime period beween January 2002 and February 2006. The following analyses include more observaions. The longes ime period accouns for 144 observaions. The nex chaper describes our resuls and commens on our findings. I also ries o compare our resuls wih he resuls of oher auhors. Even hough our mehodology, daa, ime period of analysis, ec. were slighly differen, we did find boh similariies as well as differences in he resuls. Our analysis confirmed ha counry-specific facors were imporan mosly afer he sar of he financial crisis, and hey did no influence bond spreads of European governmen deb o a grea exen before he crisis. We found ha risk aversion affeced bond spreads hroughou he whole ime period of our analysis, and i also seems ha changes in purchasing power and heir differences across he whole region migh have played a role in deermining he cos of governmen deb before he crisis. The resuls of he adjused models sugges ha markes perceived differen facors as deermining o sovereign bond yields, and ha he imporance of hese facors evolved over ime differenly for each counry.
Bond Yield Spreads in he Eurozone 229 4. RESULTS The resuls of he regression analysis (1) are shown in Table no. 1. Significance of he analysis is quie high, wih he excepion of Ausria and Finland, where he explanaory power is limied. These counries did no face high public deb nor high sovereign bond yields. On average, he linear regression did no explain he size of he spread of counries wih low borrowing coss o such a grea exen as i was in he case of counries wih high borrowing coss, whose bond yields were affeced by he level of heir deb and he overall siuaion in he region s economy. Table no. 1 Bond Yield Spreads from 2002 unil 2013 Spread 2002-2013 Belgium Ireland Greece Spain France Ialy Neherlands Ausria Porugal Finland muliple R 0.86 0.80 0.77 0.86 0.87 0.92 0.86 0.57 0.85 0.66 consan -12.83 1.64-21.95-7.71-6.41-23.54-2.05-6.77-11.29-1.52 p value 0.00 0.21 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -sa -17.81 1.26-9.85-3.09-7.44-21.61-13.52-6.76-4.79-8.98 lower inerval (95%) -14.26-0.94-26.35-12.64-8.11-25.69-2.35-8.75-15.96-1.85 upper inerval (95%) -11.41 4.23-17.54-2.78-4.71-21.38-1.75-4.79-6.63-1.18 credi risk 6.43 3.30 21.58 10.35 3.76 10.32 1.97 5.04 12.77 1.62 p value 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -sa 14.09 4.09 11.63 6.76 16.53 18.04 18.69 7.83 16.03 7.65 lower inerval (95%) 5.53 1.70 17.91 7.32 3.31 9.19 1.76 3.77 11.20 1.20 upper inerval (95%) 7.33 4.89 25.24 13.38 4.22 11.45 2.18 6.31 14.35 2.03 liquidiy 1.53-0.08-0.06 1.08 3.22 13.24 0.20 0.43 0.19 0.04 p value 0.00 0.02 0.57 0.05 0.00 0.00 0.00 0.00 0.17 0.00 -sa 17.77-2.44-0.57 2.00 5.36 11.99 8.78 5.06 1.38 9.43 lower inerval (95%) 1.36-0.15-0.28 0.01 2.03 11.06 0.16 0.26-0.08 0.03 upper inerval (95%) 1.70-0.02 0.15 2.14 4.41 15.42 0.25 0.60 0.46 0.05 risk aversion 5.67 9.87 9.48-4.78 2.17 15.23 1.72 3.28 18.93 2.82 p value 0.00 0.06 0.54 0.07 0.00 0.00 0.00 0.00 0.00 0.00 -sa 4.64 1.92 0.62-1.80 3.33 6.60 4.88 2.96 2.97 5.27 lower inerval (95%) 3.25-0.32-20.91-10.01 0.88 10.67 1.02 1.09 6.34 1.76 upper inerval (95%) 8.09 20.06 39.86 0.46 3.46 19.79 2.41 5.46 31.52 3.87 Noe: Coefficiens are significanly differen from zero a 95% level if heir p-values are equal o 0.05 or lower (Wonnaco and Wonnaco, 1990, p. 125) Source: ECB Saisical Daa Warehouse (2014a, 2014b, 2014c, 2014d), Soxx (2014), own calculaions Excep for a few coefficiens, all he variables have he expeced sign. Negaive sign was found in he coefficien of liquidiy for Ireland and Greece; however, liquidiy was insignifican for Greece. I seems ha credi risk was so imporan in deermining he size of he spread for Greece ha i made he res of he variables insignifican and almos unimporan. The negaive sign migh have resuled from he fac ha we measured liquidiy using he value of ousanding amouns, which rises wih higher deb. This migh have slighly affeced also oher calculaed coefficiens. The coefficien of risk aversion of Spain is also negaive, bu is significance is quie weak. Risk aversion variable did no differ across counries and he size of he coefficiens can be easily compared. Is significance is saisfacory excep for Ireland, Greece, and Spain. Is imporance can be ruled ou for Greece, whereas is significance in case of Ireland and Spain can sill be aken ino accoun. The size of he significan coefficiens ranges from he minimum value of 1.72 in he Neherlands o 18.93 in Porugal (see Table no. 1).
230 Denisa PROKSOVÁ, Mária BOHDALOVÁ Inernaional risk aversion seems o have a small impac on he size of he spread of France, he Neherlands, Ausria, and Finland, while i affecs highly-indebed counries, such as Ialy and Porugal bu also Ireland. The resuls seem o sugges ha risk aversion affeced mosly counries wih higher deb. Liquidiy was significan for all he counries excep for Porugal and Greece. The significance of Ireland s coefficien is lower bu sill saisfacory; however he coefficien is negaive, which migh sugges ha liquidiy did no affec is spread. Liquidiy coefficien is excepionally large for Ialy, and is relaively high for France, Belgium, and Spain. Overall, liquidiy seems o have affeced mosly larger economies. All of he credi risk coefficiens were significan, and heir size seems o depend no only on he indebedness of he counries bu also on he siuaion in he banking secor. The mos affeced counry seems o be Greece, followed by Porugal, Spain, and Ialy. The coefficiens for Belgium and Ausria are also relaively high. The size of he coefficiens seems o poin o an ineracion of credi risk and risk aversion, excep for Greece and Spain where risk aversion is insignifican. Counries wih generally less sound banking secors, such as Ireland, Spain, and Ausria feaured higher coefficiens han would have normally been expeced judging by heir level of public deb. Source: ECB Saisical Daa Warehouse (2014a, 2014b, 2014c, 2014d), Soxx (2014), own calculaions Figure no. 2 Conribuion o Spread (2002-2013) Credi risk and liquidiy daa is differen for each of he counries and can be compared more easily when shown graphically: see Figure no. 2 and Figure no. 3. Ireland was excluded from Figure no. 2 because i would dwarf he daa of oher counries. The char shows he conribuion of he average size of each of he daa ses based on he calculaed coefficiens. The resuling size of he columns is he average size of he spread during he ime period of he analysis. The char suggess ha credi risk is he mos imporan facor, followed by liquidiy condiions, while he imporance of risk aversion seems o be limied. Credi risk clearly conribues o he spread of highly-indebed counries more han counries wih low deb. Moreover, he size of he calculaed coefficiens also shows ha he yields of
Bond Yield Spreads in he Eurozone 231 hese counries are more sensiive o changes in he level of heir public deb. In general, hey also face higher yields in imes of worse liquidiy condiions. The resuls of he January 2002 o Augus 2008 analysis are a lo lower in significance (Table no. 2). Credi risk coefficiens are eiher insignifican or negaive. The only excepion is Ireland whose credi risk coefficien is posiive and significan a he same ime. The resuls for liquidiy are similar. The only posiive and significan coefficien was Ialy s liquidiy coefficien. Risk aversion, on he oher hand, was significan for mos of he counries. Insignifican were only he Neherlands, Ausria, and Porugal. These counries also exhibied relaively low coefficiens. These coefficiens are very similar in size, especially when compared o he previous analysis for 2002 o 2013 (Table no. 1). A slighly higher coefficien was assigned o Greece, while he res of he counries coefficiens were beween 1 and 2. Low significance of he credi risk and liquidiy variables and imporance of global risk percepion are in line wih he previous analysis of Barrios e al. (2009) and Barbosa and Cosa (2010) bu slighly conradics he findings of Afonso e al. (2012). The former auhors assumed risk aversion o be he mos imporan deerminan of bond yield spreads before he financial crisis, and our resuls suppor hese findings. Low significance of idiosyncraic facors in his analysis migh sugges ha here were oher facors affecing sovereign spreads, since hey coninued o differ slighly even afer he creaion of he moneary union. Table no. 2 Bond Yield Spreads from 2002 unil 2008 Spread 2002-2008 Belgium Ireland Greece Spain France Ialy Neherlands Ausria Porugal Finland muliple R 0.56 0.65 0.76 0.60 0.45 0.48 0.52 0.62 0.69 0.67 consan 2.00-0.20 0.75 0.13 0.17-0.43 0.71 2.02 1.52 0.54 p value 0.01 0.45 0.12 0.88 0.74 0.60 0.09 0.00 0.00 0.02 -sa 2.80-0.76 1.59 0.15 0.34-0.52 1.72 4.31 3.17 2.46 lower inerval (95%) 0.57-0.73-0.19-1.59-0.83-2.06-0.11 1.09 0.56 0.10 upper inerval (95%) 3.42 0.33 1.70 1.86 1.17 1.21 1.54 2.96 2.47 0.98 credi risk -1.20 1.20 0.27-0.45 0.81-0.45-1.11-1.48-0.13-1.06 p value 0.00 0.00 0.42 0.52 0.02 0.45 0.03 0.00 0.71 0.00 -sa -2.99 2.96 0.81-0.65 2.31-0.76-2.27-4.80-0.37-2.98 lower inerval (95%) -2.01 0.39-0.39-1.81 0.11-1.62-2.08-2.09-0.84-1.76 upper inerval (95%) -0.40 2.01 0.93 0.92 1.51 0.72-0.14-0.87 0.58-0.35 liquidiy -0.18 0.00-0.14 0.03-0.53 1.20-0.02-0.12-0.09 0.00 p value 0.03 0.51 0.00 0.87 0.07 0.00 0.54 0.00 0.00 0.27 -sa -2.28-0.66-5.19 0.17-1.87 3.77-0.61-3.28-4.88-1.12 lower inerval (95%) -0.33-0.02-0.19-0.31-1.09 0.56-0.09-0.19-0.12-0.01 upper inerval (95%) -0.02 0.01-0.08 0.36 0.03 1.83 0.05-0.05-0.05 0.00 risk aversion 1.37 1.98 2.28 1.79 1.04 1.77 0.41 0.45 0.55 1.50 p value 0.00 0.00 0.00 0.00 0.00 0.00 0.06 0.17 0.27 0.00 -sa 4.16 3.54 7.19 6.54 3.79 3.64 1.92 1.39 1.11 5.85 lower inerval (95%) 0.71 0.86 1.65 1.24 0.49 0.80-0.02-0.19-0.43 0.99 upper inerval (95%) 2.02 3.09 2.92 2.33 1.59 2.74 0.84 1.09 1.53 2.01 Noe: Coefficiens are significanly differen from zero a 95% level if heir p-values are equal o 0.05 or lower (Wonnaco and Wonnaco, 1990, p. 125) Source: ECB Saisical Daa Warehouse (2014a, 2014b, 2014c, 2014d), Soxx (2014), own calculaions Regression analysis of he 2008 o 2013 ime period (Table no. 3) had a relaively high significance for several counries, where is explanaory power was comparable o or even higher han in he previous analysis including daa from 2002 o 2013. However, he significance of he analysis was a lo lower for several oher counries, namely Greece, Ireland, and he Neherlands.
232 Denisa PROKSOVÁ, Mária BOHDALOVÁ Table no. 3 Deerminans of Bond Spreads from 2008 unil 2013 Spread 2008-2013 Belgium Ireland Greece Spain France Ialy Neherlands Ausria Porugal Finland muliple R 0.80 0.51 0.49 0.79 0.71 0.92 0.56 0.64 0.74 0.56 consan -17.38-4.97-27.62-12.39-9.26-26.32-1.03-5.47-17.99 0.23 p value 0.00 0.10 0.04 0.00 0.00 0.00 0.22 0.00 0.00 0.81 -sa -8.78-1.66-2.13-3.10-5.93-11.15-1.23-4.59-3.61 0.24 lower inerval (95%) -21.34-10.96-53.52-20.38-12.38-31.05-2.69-7.86-27.96-1.63 upper inerval (95%) -13.42 1.02-1.73-4.39-6.13-21.60 0.64-3.08-8.02 2.08 credi risk 5.79 6.67 23.73 12.33 5.26 5.71 1.84 5.09 18.97-0.08 p value 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.92 -sa 4.42 3.94 3.22 5.42 7.55 3.47 3.19 4.26 6.89-0.10 lower inerval (95%) 3.17 3.28 9.01 7.78 3.86 2.42 0.69 2.70 13.46-1.59 upper inerval (95%) 8.41 10.06 38.45 16.88 6.65 8.99 3.00 7.49 24.47 1.43 liquidiy 2.57-0.02-0.01 2.23 4.38 21.96-0.01 0.24-0.05 0.00 p value 0.00 0.86 0.98 0.02 0.00 0.00 0.94 0.02 0.91 0.97 -sa 9.51-0.17-0.03 2.31 4.27 13.78-0.07 2.46-0.12 0.04 lower inerval (95%) 2.03-0.19-0.42 0.30 2.33 18.77-0.20 0.05-0.84-0.05 upper inerval (95%) 3.12 0.16 0.41 4.16 6.43 25.15 0.18 0.44 0.74 0.05 risk aversion 16.11 110.21 101.48 19.25 11.70 15.32 10.09 19.80 163.79 7.15 p value 0.00 0.00 0.44 0.29 0.01 0.14 0.00 0.00 0.00 0.00 -sa 3.20 3.06 0.77 1.07 2.76 1.51 5.05 5.45 3.64 3.00 lower inerval (95%) 6.04 38.19-160.46-16.68 3.20-4.97 6.10 12.53 73.71 2.38 upper inerval (95%) 26.18 182.23 363.42 55.18 20.19 35.60 14.09 27.07 253.86 11.91 Noe: Coefficiens are significanly differen from zero a 95% level if heir p-values are equal o 0.05 or lower (Wonnaco and Wonnaco, 1990, p. 125) Source: ECB Saisical Daa Warehouse (2014a, 2014b, 2014c, 2014d), Soxx (2014), own calculaions Credi risk s significance was very high wih he excepion of Finland. Liquidiy was significan for Belgium, Spain, France, Ialy, and Ausria, and did no seem o affec he res of he counries a all. Again, liquidiy coefficiens are higher for bigger counries, namely Ialy, bu also France. Similarly o he 2002 o 2013 analysis, he highes credi risk coefficiens are found in Greece, Porugal, and Spain. On he oher hand, Belgium, Ireland, France, Ialy, and Ausria show slighly lower coefficiens, whereas he dependency of sovereign spreads on deb o GDP did no seem ha srong for he Neherlands. An excepionally high risk aversion coefficien was found in Porugal and Ireland. The res of he counries share quie similar coefficiens. Risk aversion was insignifican for Greece, Spain, and Ialy, so we could no confirm ineracion of risk aversion and credi risk any more. The resuls show differences in comparison o he previous analysis. Liquidiy in general is no as imporan o deermining he size of he spread as for he whole 2002-2013 period. Deb crisis made spreads more sensiive o credi risk han o liquidiy risk. The size of he risk aversion coefficiens also suggess ha spreads were affeced by inernaional risk aversion o a much greaer exen han during he 2002-2008 period. Table no. 4 Deerminans of Bond Spreads from 2002 unil 2008 including inflaion Spread 2002-2008 Belgium Ireland Greece Spain France Ialy Neherlands Ausria Porugal Finland muliple R 0.79 0.70 0.86 0.67 0.76 0.80 0.64 0.79 0.69 0.74 consan 0.15 0.31-0.06 0.81 0.39-2.41 0.22 1.73 1.64-0.37 p value 0.80 0.31 0.88 0.34 0.29 0.00 0.58 0.00 0.00 0.23 -sa 0.26 1.02-0.15 0.97 1.06-3.96 0.56 4.60 3.19-1.21 lower inerval (95%) -1.02-0.30-0.86-0.85-0.35-3.62-0.56 0.98 0.61-0.99 upper inerval (95%) 1.32 0.93 0.74 2.46 1.13-1.20 1.01 2.48 2.66 0.24 credi risk -0.05 0.32 0.50-0.93 0.34 0.85-0.66-0.95-0.19 0.57
Bond Yield Spreads in he Eurozone 233 Spread 2002-2008 Belgium Ireland Greece Spain France Ialy Neherlands Ausria Porugal Finland p value 0.89 0.51 0.06 0.16 0.20 0.05 0.15 0.00 0.60 0.28 -sa -0.14 0.66 1.87-1.41 1.29 1.96-1.45-3.71-0.52 1.09 lower inerval (95%) -0.72-0.65-0.03-2.24-0.19-0.01-1.56-1.46-0.93-0.48 upper inerval (95%) 0.62 1.30 1.03 0.38 0.87 1.71 0.25-0.44 0.54 1.61 liquidiy -0.04-0.02-0.09-0.14-0.54 1.48 0.02-0.14-0.09 0.01 p value 0.56 0.02 0.00 0.38 0.01 0.00 0.52 0.00 0.00 0.22 -sa -0.59-2.35-3.88-0.88-2.59 6.68 0.65-4.91-4.85 1.24 lower inerval (95%) -0.16-0.03-0.13-0.47-0.95 1.04-0.04-0.20-0.13 0.00 upper inerval (95%) 0.09 0.00-0.04 0.18-0.12 1.93 0.08-0.08-0.05 0.02 risk aversion 1.48 1.47 1.26 1.35 0.69 1.34-0.29 0.33 0.64 1.16 p value 0.00 0.01 0.00 0.00 0.00 0.00 0.26 0.21 0.22 0.00 -sa 5.97 2.61 4.20 4.73 3.34 3.94-1.14 1.27 1.25 4.64 lower inerval (95%) 0.98 0.35 0.66 0.78 0.28 0.66-0.81-0.18-0.38 0.66 upper inerval (95%) 1.97 2.59 1.85 1.92 1.10 2.02 0.22 0.83 1.67 1.66 inflaion 0.06 0.07 0.09 0.04 0.05 0.14 0.04 0.07-0.01 0.05 p value 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.51 0.00 -sa 7.73 2.92 6.54 3.46 8.03 9.14 4.21 6.75-0.66 3.95 lower inerval (95%) 0.04 0.02 0.06 0.02 0.04 0.11 0.02 0.05-0.05 0.02 upper inerval (95%) 0.07 0.11 0.12 0.06 0.06 0.17 0.06 0.08 0.02 0.07 Noe: Coefficiens are significanly differen from zero a 95% level if heir p-values are equal o 0.05 or lower (Wonnaco and Wonnaco, 1990, p. 125) Source: ECB Saisical Daa Warehouse (2014a, 2014b, 2014c, 2014d), Soxx (2014), own calculaions Table no. 5 Deerminans of Bond Spreads from 2002 unil 2008 including real ineres rae Spread 2002-2008 Belgium Ireland Greece Spain France Ialy Neherlands Ausria Porugal Finland muliple R 0.67 0.76 0.76 0.61 0.45 0.49 0.57 0.65 0.74 0.70 consan 0.89-0.96 0.67-0.12 0.18-0.07 0.35 2.25 1.71 0.05 p value 0.20 0.00 0.18 0.89 0.72 0.94 0.42 0.00 0.00 0.87 -sa 1.30-3.51 1.36-0.13 0.36-0.07 0.81 4.76 3.75 0.16 lower inerval (95%) -0.48-1.50-0.31-1.90-0.82-1.95-0.51 1.31 0.80-0.53 upper inerval (95%) 2.26-0.41 1.65 1.66 1.19 1.81 1.21 3.19 2.62 0.63 credi risk -0.64 2.46 0.33-0.19 0.82-0.56-0.97-1.67-0.39-0.46 p value 0.10 0.00 0.34 0.79 0.02 0.36 0.04 0.00 0.26 0.27 -sa -1.67 5.75 0.96-0.26 2.33-0.93-2.05-5.29-1.13-1.11 lower inerval (95%) -1.40 1.61-0.36-1.63 0.12-1.78-1.92-2.29-1.08-1.29 upper inerval (95%) 0.12 3.32 1.02 1.25 1.53 0.65-0.03-1.04 0.30 0.37 liquidiy -0.07 0.01-0.14 0.08-0.56 1.01 0.02-0.14-0.08 0.00 p value 0.31 0.06 0.00 0.65 0.06 0.01 0.51 0.00 0.00 0.71 -sa -1.03 1.90-5.19 0.45-1.95 2.51 0.67-3.82-4.82 0.38 lower inerval (95%) -0.22 0.00-0.19-0.27-1.13 0.21-0.05-0.21-0.12-0.01 upper inerval (95%) 0.07 0.02-0.08 0.42 0.01 1.81 0.10-0.07-0.05 0.01 risk aversion 1.92 1.66 2.34 1.66 1.11 1.47 0.21 0.54 0.45 1.58 p value 0.00 0.00 0.00 0.00 0.00 0.02 0.35 0.09 0.34 0.00 -sa 6.00 3.39 7.04 5.67 3.77 2.34 0.95 1.71 0.96 6.31 lower inerval (95%) 1.28 0.68 1.68 1.08 0.52 0.22-0.24-0.09-0.48 1.08 upper inerval (95%) 2.55 2.63 3.01 2.25 1.69 2.72 0.66 1.18 1.37 2.08 real ineres rae 0.003-0.003 0.000-0.001 0.001-0.002 0.002 0.003-0.003 0.005 p value 0.00 0.00 0.53 0.26 0.52 0.44 0.02 0.04 0.00 0.01 -sa 4.43-5.14 0.63-1.14 0.64-0.78 2.39 2.07-3.24 2.52 lower inerval (95%) 0.00 0.00 0.00 0.00 0.00-0.01 0.00 0.00 0.00 0.00 upper inerval (95%) 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.01 Noe: Coefficiens are significanly differen from zero a 95% level if heir p-values are equal o 0.05 or lower (Wonnaco and Wonnaco, 1990, p. 125) Source: ECB Saisical Daa Warehouse (2014a, 2014b, 2014c, 2014d), Soxx (2014), own calculaions
234 Denisa PROKSOVÁ, Mária BOHDALOVÁ Since none of he variables from he 2002-2008 regression analysis could explain he size of he sovereign spreads sufficienly, we decided o include oher variables. The nex analysis (2) includes inflaion, which feaures he highes significance of all he variables and increased he significance of he regression analysis. The only insignifican inflaion coefficien of his regression analysis was he one calculaed for Porugal. Including inflaion in he analysis made he significance of he res of he idiosyncraic variables a lo lower, while he risk aversion coefficiens reained heir significance. All of he risk aversion coefficiens were significan, excep for he Neherlands, Ausria, and Porugal. Despie he resuls i was mos probably no inflaion risk ha invesors were pricing in. Especially in moneary unions, where exchange raes are fixed and nominal exchange raes are equal, counries wih higher economic growh usually face higher inflaion raes. Eurozone members wih he highes inflaion raes prior o he financial crisis were Greece, Spain, Ireland, bu also Porugal, and Ialy. These counries exhibied high inflaion raes even before joining he moneary union, and heir economic growh was faser han he economic growh of he res of he counries afer hey joined he moneary union unil he financial crisis of 2008. The ineres raes imposed by he European Cenral Bank were oo low for hem, which resuled in higher inflaion raes. However, heir economic growh did no ranslae ino a beer abiliy o service deb as perceived by he invesors in he financial markes. This level of ineres raes was damaging o heir economies and made heir growh more uneven, which showed afer he sar of he financial crisis when he economic growh of hese counries was lower han ha of mos of he oher members of he currency union. I is possible ha he effec of he oo-low ineres raes had already been priced in even before he economic crisis hi he region. The banking secors of hese counries were affeced by he level of ineres raes he mos and is soundness urned ou o be a very imporan risk facor during he financial and economic crisis. If invesors had been pricing in he slowly deerioraing siuaion in he banking secors of hese counries, ha would have made heir sovereign yields higher. So he resuls of he regression analysis should no be inerpreed as compensaion for inflaion risk bu migh be inerpreed as a compensaion for he risks implied by being a par of he moneary union and is consequences for cyclical developmen of he economy. I could also be argued ha he higher yields before he financial crisis were sor of a coninuaion of he higher yields before he currency union (despie he fac ha hey no longer carried a higher inflaion risk han he sovereign bonds of he res of he member counries). In he case of a break-up of he moneary union or in case one of is members lef he moneary union, is cenral bank would deermine he level of ineres raes in heir economy again, and here is a high probabiliy ha is policy would be similar o he one conduced before joining he currency union. Tha would no only influence he level of ineres raes bu also nominal exchange raes. Apar from he reasons menioned above, higher spreads for high-inflaion counries could also be he resul of a compensaion for inflaion risk by local invesors, since many invesors sill did no seek foreign invesmens a he ime. There has been an increase in he holdings of foreign bonds in Eurozone bu here is sill a cerain preference for domesic bonds which, as a resul, back hen refleced domesic inflaion raes and he need for a compensaion for inflaion risk. The res of he regression analysis includes oher variables relaed o cos of borrowing and loss of purchasing power. We did no repea his analysis wih he 2008-2013 ime periods, since low inflaion as a resul of low economic growh decreased governmen
Bond Yield Spreads in he Eurozone 235 revenues and heir abiliy o mee heir deb obligaions. Including inflaion in his regression analysis may hus lead o he wrong conclusion. Real ineres raes provide a beer esimae of he cos of borrowing given he purchasing power. The lower he real ineres raes, he higher he incenive o borrow. The resuls of he regression analysis (3) aking ino accoun real ineres raes were no as significan as as he resuls of he regression which ook inflaion ino accoun. Greece, Spain, France, and Ialy were insignifican. The coefficiens for Porugal and Ireland, whose economies required slighly higher ineres raes han imposed by he European Cenral Bank, were negaive, suggesing ha higher real ineres raes raised heir spreads, as opposed o Belgium, he Neherlands, Ausria, and Finland. Higher real ineres raes were probably he resul of lower inflaion during phases of slower economic growh, which migh have raised he spreads of Porugal and Ireland, whereas slower economic in he Euro Area migh have eniced invesors o inves ino he safer counries, such as Belgium, he Neherlands, Ausria, and Finland. Our las analysis (4) akes ino accoun he loss of purchasing power (Table no. 6). The daa is expressed relaive o Germany. This is an expression of how much he economy has changed since he nominal ineres raes were fixed. This gives us a cerain idea abou he real exchange rae adjusmen since he nominal exchange raes were fixed. This real exchange rae adjusmen affeced counries rade balance which in urn affeced he overall level of deb (including privae deb). Table no. 6 Deerminans of Bond Spreads from 2002 unil 2008 including overall change in inflaion relaive o Germany Spread 2002-2008 Belgium Ireland Greece Spain France Ialy Neherlands Ausria Porugal Finland muliple R 0.60 0.89 0.77 0.68 0.65 0.59 0.61 0.63 0.70 0.71 consan 1.51-2.14 1.23-4.42-0.58 0.74 0.37 1.83 1.63 0.39 p value 0.04 0.00 0.02 0.00 0.20 0.37 0.36 0.00 0.00 0.08 -sa 2.08-8.96 2.33-3.06-1.28 0.90 0.92 3.54 3.40 1.78 lower inerval (95%) 0.06-2.62 0.18-7.29-1.48-0.91-0.43 0.80 0.68-0.05 upper inerval (95%) 2.97-1.67 2.28-1.54 0.32 2.39 1.16 2.87 2.59 0.83 credi risk -1.01 3.36 0.54 5.19 2.84-0.29-0.15-1.51-0.76-1.66 p value 0.01 0.00 0.13 0.00 0.00 0.60 0.78 0.00 0.17 0.00 -sa -2.51 10.63 1.52 3.20 5.86-0.53-0.28-4.86-1.40-4.14 lower inerval (95%) -1.81 2.73-0.17 1.96 1.87-1.38-1.20-2.13-1.84-2.46 upper inerval (95%) -0.21 3.99 1.24 8.41 3.80 0.80 0.90-0.89 0.32-0.86 liquidiy -0.27 0.02-0.22 0.41-0.31-1.56 0.01-0.14-0.08 0.00 p value 0.00 0.00 0.00 0.03 0.21 0.06 0.69 0.00 0.00 0.72 -sa -3.15 4.16-4.26 2.21-1.25-1.91 0.40-3.21-4.62 0.35 lower inerval (95%) -0.45 0.01-0.33 0.04-0.80-3.18-0.05-0.22-0.12-0.01 upper inerval (95%) -0.10 0.03-0.12 0.77 0.18 0.06 0.08-0.05-0.05 0.01 risk aversion 1.32 2.54 2.12 1.69 0.64 2.27 0.05 0.63 0.83 1.16 p value 0.00 0.00 0.00 0.00 0.01 0.00 0.81 0.10 0.12 0.00 -sa 4.12 7.27 6.56 6.69 2.59 4.81 0.24 1.65 1.59 4.25 lower inerval (95%) 0.68 1.84 1.48 1.19 0.15 1.33-0.39-0.13-0.21 0.62 upper inerval (95%) 1.96 3.23 2.76 2.20 1.13 3.21 0.50 1.38 1.87 1.71 overall inflaion 0.48 0.10-0.05 0.21-0.64 0.60-0.11 0.31 0.06 0.22 p value 0.03 0.00 0.06 0.00 0.00 0.00 0.00 0.38 0.13 0.01 -sa 2.25 11.17-1.93 3.78-5.34 3.63-3.56 0.89 1.52 2.81 lower inerval (95%) 0.05 0.08-0.10 0.10-0.88 0.27-0.18-0.39-0.02 0.06 upper inerval (95%) 0.90 0.12 0.00 0.32-0.40 0.92-0.05 1.02 0.14 0.37 Noe: Coefficiens are significanly differen from zero a 95% level if heir p-values are equal o 0.05 or lower (Wonnaco and Wonnaco, 1990, p. 125) Source: ECB Saisical Daa Warehouse (2014a, 2014b, 2014c, 2014d), Soxx (2014), own calculaions