i
STRESS TESTING: ASSESSING POSSIBLE IMPACTS
OF COVID-19 PANDEMIA ON THE CREDIT
DEFAULT IN PORTUGAL
Rena a Baião Se a Be na do Da Sil a
Disse a ion p esen ed as pa ial equi emen o ob aining
he Mas e ’s deg ee in In o ma ion Managemen
ii
NOVA In o ma ion Managemen School
Ins i u o Supe io de Es a ís ica e Ges ão de In o mação
Uni e sidade No a de Lisboa
STRESS TESTING: ASSESSING POSSIBLE IMPACTS OF COVID-19 PANDEMIA ON THE CREDIT DEFAULT
IN PORTUGAL
by
Rena a Baião Se a Be na do Da Sil a
Disse a ion p esen ed as pa ial equi emen o ob aining he Mas e ’s deg ee in S a is ics and
In o ma ion Managemen , wi h a specializa ion in Risk Analysis and Managemen
Ad iso : P o esso Ca los Ra ael San os B anco
Decembe 2021
iii
DEDICATION
To my babies boys,
A u and F ancisco.
To my husband Tomé,
Fo uncondi ional suppo and dedica ion.
And God!
i
ACKNOWLEDGEMENTS
Disse a ion is a long jou ney, which includes a se e al challenges, unce ain ies, g ea happiness, and
i is a soli a y p ocess ha who p oposes is des ined. Despi e o his jou ney was no done en i ely
alone, he e was some people o suppo me, gi e me ene gy and s eng h, whom I should
acknowledge.
I would like o app ecia e my ad iso , PhD. Dou o Ca los Ra ael San os B anco, o suppo ,
coo dina ed and his c i ical and imely iew.
I should like o hank my husband, Tomé, o his uncondi ional psychological and physical suppo o
ake ca e o ou babies.
A supe hank you o pa en s o my husband, o helping us o ake ca e o ou babies, in his e y
oubled pandemic ime.
He e I mus exp ess my deepes g a i ude o Ma a Hei o , Che na Gokaldas, Ri a Figuei edo, Sónia Jin,
João Ca alho, Hen ique Sil a, Ped o Ba bosa, o linguis ic e ision o pa s o his disse a ion.
I would like o con ey my hanks o P o esso Te esa Ve dasca o he comp ehensi e linguis ic e iew
o his p ojec .
Also, I hank my babies, pa en s and sis e o being pa o my li e.
Finally, las bu no leas , o hank you o my Colleagues, Ri a Ma ins, Luz Dias and head o my
Depa men , Ma ia Te esa Paulo, o encou aging me o inish he p esen disse a ion.
ABSTRACT
The cu en heal h c isis is shaking he economic and inancial wo ld and Po ugal was no excep ion.
The p esen disse a ion main goal is o assess he c edi isk impac by he cu en si ua ion due o
COVID-19 pandemic in Po ugal.
The key objec i e is o e alua e c edi inhe en isk, in o de o be able o in e ene in ad ance and
o mi iga e possible isks, as well as p edic likely de aul s.
In o de o p edic possible se ious e ec s in e ms o c edi de aul ha ing, he p esen disse a ion
has as i s objec he s udy o he impac o mac oeconomic a iables and hei in luence on c edi
de aul . An explo a o y quan i a i e app oach was used in he empi ical s udy, complemen ed wi h a
quali a i e app oach, ocused undamen ally on he desc ip ion o he esul s ob ained wi h he SPSS
so wa e.
Linea eg ession models we e es ed, which we e de ined as independen a iable o c edi de aul .
As dependen a iables he indica o s o c edi isk managemen ; UR, LR, LMC, LCC, LBC, EUR, GDP,
PSI, DIG, CPI, ER and CP. Among all hese indica o s o c edi isk managemen used, he ones ha
had he g ea es impac we e he LR, LMC, UR, GDP, CPI and CP ha e mo e signi ican e ec .
Howe e , he a iable CP does no sugges he exis ence o a di ec and eliable ela ionship be ween
he independen a iable, bu ecen s udies e e o i as one o he mos impo an o be
conside ed.
As no ed in wo ld his o y, he impac s o inancial disas e s, ein o ce he need o sys ema ic
analysis and e ec i e inancial s abili y ins umen s. In o de o o ecas hose si ua ions, s ess
es ing will be used o p edic possible scena ios o induced inancial c isis by he cu en heal hy
c isis, such as c edi isk, in speci ic. To be able o o esee, a coun y mac oeconomic analysis is
needed, by me ging se e al c edi componen s, as es ablished by he Basel ag eemen s. The da a
he ein as e e ence has aken om Banco de Po ugal, INE, S ooq and oecd, since he 2003 o 2020,
in o de o be p o isions ega ding economic.
KEYWORDS
C edi De aul , S ess Tes ; Scena io; C edi Risk; COVID-19

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INDEX
1. In oduc ion .................................................................................................................. 1
1.1. Backg ound ............................................................................................................ 1
1.1.1. P oblem Jus i ica ion ...................................................................................... 2
1.1.2. P oblem .......................................................................................................... 3
1.1.3. Objec i es ....................................................................................................... 3
1.1.4. Main objec i e ................................................................................................ 3
1.1.5. Speci ic objec i es .......................................................................................... 4
1.1.6. S udy ele ance and impo ance ................................................................... 4
2. Li e a u e e iew .......................................................................................................... 5
2.1. SECTION I Regula ion, C edi Risk and mac oeconomic componen s .................. 5
2.1.1. F amewo k his o y and egula ion - Basel Commi ee on Banking Supe ision
5
2.1.2. C edi Risk ....................................................................................................... 8
2.1.3. C edi Risk Componen s ................................................................................. 9
2.1.4. Mac oeconomic componen s a e in luenced c edi isk ............................. 10
2.2. SECTION II S ess Tes .......................................................................................... 13
2.2.1. A b ie his o y o s ess es ing on banks ..................................................... 13
2.2.2. Banking sys em o e iew ............................................................................. 14
2.2.3. How o use s ess es esul s ...................................................................... 15
2.2.4. Main objec i e o S ess Tes ....................................................................... 16
2.2.5. Subjec i e s objec i e p obabili ies ............................................................ 17
2.2.6. Imp o emen s ess es o assess he esilience o he bank ..................... 17
2.2.7. Scena io analysis .......................................................................................... 18
2.2.8. S ess es ing and Value a Risk .................................................................... 20
2.3. SECTION III COVID-19 Pandemic ......................................................................... 22
2.3.1. F amewo k COVID-19 Pandemic .................................................................. 22
2.3.2. Recommenda ions by Eu opean Cen al Bank ............................................ 22
2.3.3. Recommenda ion by Eu opean Baking Au ho i y ........................................ 24
2.3.4. Mac o- inancial models used o calib a e shocks and p oduce scena ios .. 27
2.4. Clima e s ess es ing pilo exe cise .................................................................... 28
3. Me hodology .............................................................................................................. 30
3.1. Resea ch Me hodology ....................................................................................... 30
3.2. Hypo hesis ........................................................................................................... 30
ii
3.3. Resea ch Ques ion............................................................................................... 31
3.4. Sample and Da a Collec ion ................................................................................ 31
3.5. Model Type .......................................................................................................... 32
3.6. Linea Reg ession Model ..................................................................................... 33
3.7. Au o eg essi e Dis ibu ed Lag Model ................................................................ 34
3.7.1. The maximum Lag ........................................................................................ 34
3.8. Speci ic es .......................................................................................................... 35
3.8.1. Du bin-Wa son and B eusch-God ey .......................................................... 35
3.8.2. Tes - and Tes -F ........................................................................................... 36
3.9. Model Va iables ................................................................................................... 36
3.9.1. S ess Tes ..................................................................................................... 36
3.9.2. Unemploymen a e ..................................................................................... 36
3.9.3. Loans ............................................................................................................. 37
3.9.4. TBA – Eu ibo in e es a e ........................................................................... 38
3.9.5. Nominal GDP g ow h a e ............................................................................ 38
3.9.6. PSI 20 ............................................................................................................ 38
3.9.7. Disposable Income G ow h .......................................................................... 38
3.9.8. Consume P ice Index ................................................................................... 38
3.9.9. Exchange a e ............................................................................................... 39
3.9.10. Ca bon P ice .......................................................................................... 39
3.10. Ini ial Model .................................................................................................. 39
3.11. Scena io analysis ........................................................................................... 40
4. Resul s and discussion ................................................................................................ 41
4.1. Resul s Analyses .................................................................................................. 41
4.1.1. P ac ical example ......................................................................................... 41
4.1.2. Va iables ....................................................................................................... 41
4.2. Selec ion and analysis o a iables ...................................................................... 42
4.2.1. Dependen a iable ...................................................................................... 42
4.2.2. Independen a iable ................................................................................... 43
4.2.3. S a iona y Tes .............................................................................................. 44
4.2.4. Da abase desc ip ion .................................................................................... 45
4.2.5. Model pe o mance e alua ion ................................................................... 46
4.2.6. Speci ica ion o model a iables .................................................................. 47
4.3. Robus Tes .......................................................................................................... 49
4.3.1. Co ela ion Ma ix ........................................................................................ 49
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4.3.2. E alua ion o he mul icollinea i y ............................................................... 50
4.4. Scena io analysis.................................................................................................. 50
4.5. Final Model Quali y ............................................................................................. 51
4.6. Tes ing The S udy Hypo hesis ............................................................................. 53
5. Conclusions ................................................................................................................. 61
6. Limi a ions and ecommenda ions o u u e wo ks ................................................. 63
7. Bibliog aphy ................................................................................................................ 64
8. Appendix ..................................................................................................................... 67
8.1. Appendix A – S a iona y es ............................................................................... 67
8.2. Appendix B – Desc ip i e S a is ics ..................................................................... 73
8.3. Appendix C – Model Summa y ............................................................................ 73
8.4. Appendix D – ANOVA .......................................................................................... 73
8.5. Appendix E – Coe icien s .................................................................................... 74
8.6. Appendix F -Co ela ions ..................................................................................... 74
8.7. Appendix G – Desc ip i e S a is ics (Model 2) .................................................... 75
8.8. Appendix H – Model Summa y (Model 2) ........................................................... 75
8.9. Appendix I – ANOVA (Model 2) ........................................................................... 75
8.10. Appendix J – Coe icien s (Model 2) ............................................................. 75
8.11. Appendix L – Co ela ions (Model 2) ............................................................ 76
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LIST OF FIGURES
Figu e 1 Global Economic P ospec s - June 2020 (Sou ce: The Wo ld Bank (Le )); Pu chasing
Manage s Index – (Sou ce: IHS Ma ki e Re ini i . (Righ )) .............................................. 27
4
1.1.5. Speci ic objec i es
In o de o achie e he gene al objec i e, he speci ic objec i es a e as ollows:
I. Li e a u e e iew ega ding c edi isk, s ess es s and known mac oeconomic ac o s;
II. P opose a model o de aul a es;
III. Tes he model;
IV. E alua e he esul s.
1.1.6. S udy ele ance and impo ance
P esen s udy may con ibu e o policies and ma ke in o de o p e en an a ainable c isis, iden i ying
he main ac o s o de aul a he mac oeconomic le el.

5
2. LITERATURE REVIEW
2.1. SECTION I REGULATION, CREDIT RISK AND MACROECONOMIC COMPONENTS
2.1.1. F amewo k his o y and egula ion - Basel Commi ee on Banking Supe ision
The e a e same impo an c isis in ou his o y. The i s one is G ea Dep ession o 1929. The second
one is Subp ime C isis, when in Sep embe 2008, US au ho i ies decided no o sa e in es men bank
Lehman B o he s, wi nessing u he de e io a ion economic ac i i y and he inancial sys em. In 2008
was ma ked by he c isis in he in e na ional inancial ma ke s and by he economic slowdown global
le el, ansla ing in o a pa icula ly ad e se amewo k o he pe o mance o he ac i i y o banks.
Acco ding o he In e na ional Mone a y Fund he high le e age, le els insu icien capi al and
inadequa e con ingency plans we e ac o s ha con ibu ed o se ious inancial p oblems.
The global p opo ions ha he inancial c isis had assumed, he Eu opean De elopmen Fund and
Eu opean Cen al Bank began o exe cise mo e ac i ely hei ole as he highes inancial supe iso y
au ho i y, p omo ing measu es o con ain he nega i e e ec s and ese e he ecessi e scena io
c ea ed in o de o p e en his c isis om assuming sys emic p opo ions.
In he 1970s, he e was g ea ins abili y in he in e na ional ma ke s, he e o e he G10
1
Cen al Banks
es ablished a Basel Commi ee on Banking Supe ision (BCBS). This was a wo ldwide o um o
discussion and coope a ion on p uden ial banking egula ion. The main goal was o ha monize he
banking supe ision s anda ds o egula o y capi al assessmen .
Cu en ly BCBS consis s o 19 na ions, 32 economies, known as he G20
2
. I s main pu pose is o c ea e
s anda d ules o all in e na ional economies belonging o he g oup, ne e heless each coun y ends
up egula ing acco ding o i s p inciples. The Basel acco ds aim o educe he likelihood o sys ema ic
isk, wi h a ocus on liquidi y, c ea ing de ense mechanisms agains possible inancial c ises.
(Vasconcelos, Pe es M., & C is  o, 2017)
The e a e 3 Basel Acco d in exis ence: Basel I, Basel II and Basel III ag eemen s. Basel I app o ed a se
o egula o y p oposals o he wo ld banking sec o in 1988, he In e na ional Con e gence o Capi al
Measu emen and Capi al S anda ds (ICCMCS). The ag eemen made i possible o measu e he
equi emen capi al o co e addi ional c edi isks in he inancial sys em and o minimize he
bank up cy isk. F om his ag eemen highligh s he es ablishmen o minimum egula o y capi al
equi emen s o ensu e he sol ency o inancial ins i u ions and he sys em obus ness p omo ion,
1
The GAB was o med in 1962, when he go e nmen s o eigh IMF membe s—Belgium, Canada, F ance, I aly, Japan, he
Ne he lands, he Uni ed Kingdom, and he Uni ed S a es—and he cen al banks o Ge many and Sweden, ag eed o make
esou ces a ailable o he IMF.
2
The G20 membe s a e A gen ina, Aus alia, B azil, Canada, China, F ance, Ge many, India, Indonesia, I aly, Japan, Mexico,
Republic o Ko ea, Russia, Saudi A abia, Sou h A ica, Tu key, he Uni ed Kingdom, he Uni ed S a es and he Eu opean Union
(EU)
6
h ough he c ea ion o a uni ied s anda d o all in e na ional banks, hus educing he compe i i e
imbalance be ween ins i u ions. (Vasconcelos, Pe es M., & C is  o, 2017)
The p og ess made wi h Basel I in egula o y amewo k was undeniable. Howe e , in iew o he
sho comings in he p e ious acco d, ega ding o capi al a bi age
3
he new Basel Acco d, known as
Basel II, was published in 2004. I de ined how o apply he new capi al equi emen s, which is mo e
sensi i e o c edi and ma ke isks. Unde he New Acco d, c edi isk measu emen app oaches a e
classi ied in o wo ypes: s anda dized and based on In e nal Ra ing Based (IRB). The in oduc ion o
IRB me hodologies, in e nal a ings, a e he main inno a ion o his acco d, aiming o make capi al
equi emen s mo e dynamic and sensi i e o isk. Fu he mo e, o imp o e c edi isk managemen ,
Basel II in oduces he ope a ional isk as a majo minimum capi al equi emen isk componen
(Vasconcelos, Pe es M., & C is  o, 2017).
BCBS ag eemen is s uc u ed on h ee pilla s:
Pilla I: de e mina ion o minimum capi al equi emen s: opics ela ed o he de e mina ion o
minimum egula o y capi al equi emen s o co e c edi , ma ke and ope a ional isks a e add essed.
Wi h he implemen a ion o his pilla , i is expec ed ha banking ins i u ions will be able o use hei
own me hodologies and mo e sensi i e isk, ul ima ely, hey can bene i om lowe isks han hose
using s anda d me hodologies.
Pilla II: supe iso y e iew: quali a i e supe ision will be ca ied ou by egula o y en i ies o in e nal
con ol o bank isk, equi ing om banking au ho i ies’ s a egies o main ain sui able le els o capi al.
In addi ion o he ein o cemen o he ex e nal supe ision, Pilla II seeks o es ablish a se o in e nal
isk managemen p ocedu es, so ha inancial en i ies could be able he capi al’s sui abili y and
su iciency. This se o p ocedu es was called he In e nal Capi al Adequacy Assessmen P ocess
(ICAAP), which includes s ess es s, which should be ca ied ou wi h he p ope equency.
Pilla III: ma ke discipline: new condi ions o public disclosu e o inancial epo s wi h in o ma ion
abou isks, wi h he pu pose o imp o ing banking isk managemen .
The Basel III: Ag eemen is a esponse o he main ulne abili ies p esen ed by he banking sec o
du ing he 2008 inancial c isis. The Basel Commi ee in oduces a se ies o changes ela ed o Basel II,
wi h emphasis on he capi al s uc u e o inancial ins i u ions, expansion o banks' esilience and
s eng h.
In his ag eemen , a se ies o s udies abou he causes and impac s o he c isis began:
• Iden i ies he main laws in he egula o y models in o ce in he Basel II ag eemen .
• Reshapes he ope a ional amewo k in o de o imp o e he abili y o inancial ins i u ions o
abso b shocks p o ided by he inancial sys em o some sec o o he economy.
• Reduces he isk o con agion in he inancial sec o .
3
A bi age is he pu chase and sale o an asse in o de o p o i om a di e ence in he asse 's p ice be ween ma ke s. I is
a ade ha p o i s by exploi ing he p ice di e ences o iden ical o simila inancial ins umen s in di e en ma ke s o in
di e en o ms.
7
A e he c isis in 2009, he Basel Commi ee made a se o measu es equi ing banks o in eg a e
ma ke isk calcula ions based on VaR models and accompanied by " igo ous and ex ensi e" s ess
es s.
In May 2009, he Basel Commi ee published he inal e sion o i s ecommenda ions on s ess es ing
p ac ices and how s ess es ing should be supe ised by egula o s (Supe ision, May 2009). The
ecommenda ions emphasize he impo ance o s ess es ing in de e mining how much capi al is
needed o abso b losses ( egula o y capi al).
These ecommenda ions highligh ed he impo ance o op managemen and he in ol emen o he
boa d. Bea ing in mind ha op managemen and he boa d o di ec o s mus be in ol ed in he
es ablishmen o s ess es objec i es, scena ios de ini ion, he discussion o he s ess es s esul s
and he e alua ion o po en ial ac ions as well as decision making. He says ha he banks ha wen
well in he mid-2007 inancial c isis we e hose in which senio managemen as a whole was ac i ely
in e es ed in he de elopmen and ope a ion o s ess es s, con ibu ing hese esul s o he s a egic
decision making. The s ess es mus be ca ied ou in all a eas o he bank as a hole.
The Basel ecommenda ions s a e ha many o he scena ios chosen be o e 2007 we e based on
his o ical da a and he e o e less se e e han wha ac ually happened. Speci ic ecommenda ions o
he banks a e:
I. The s ess es mus be an in eg al pa o he bank's cul u e and isk managemen , and so, i
mus a ec decision making;
II. The bank mus ha e a s ess es p og am ha in ol es he p omo ion and he iden i ica ion
o isk con ol, which imp o es he company's managemen on capi al and liquidi y as well as
in e nal and ex e nal communica ion;
III. I mus be aken in o accoun he s andpoin o he en i e o ganiza ion and co e a a ie y o
pe spec i es and echniques;
IV. Policies and p ocedu es mus be placed in o pape by he bank;
V. Flexible in as uc u e o accommoda e changes in s ess es s;
VI. Indi idual componen s mus be equen ly e alua ed;
VII. Co e isks o a eas o nego ia ion - in o de o p o ide a comple e isk image o he
en i e company;
VIII. The s ess es s mus co e a a ie y o p ospec i e scena ios and mus conside
in e ac ions in he sys em and i s eedback e ec ;
IX. To include a se ies o losses, aking in o accoun ha i s epu a ion mus be
main ained among he sha eholde s;
X. Conside simul aneous ma ke p essu es and ac i e asse inancing;
XI. To be e ec i e in isk mi iga ion echniques;
XII. They mus include complex and pe sonalized p oduc s;
XIII. They mus co e isks o pipelines and wa ehouses;
XIV. Imp o e s ess es ing me hodologies o cap u e he e ec o in e na ional isk;
XV. E alua e he ulne abili ies o he asse s classes.
The ecommenda ions o op managemen o senio bank manage s a e as ollows:
I. They mus egula ly e alua e he s ess es p og am;
8
II. Take co ec i e measu es;
III. Assess he se e i y o he scena ios, sensi i i y o po olios o pa ame e s;
IV. In e nal capi al assessmen and liquidi y isk;
V. Implemen s ess exe cises in common base scena ios;
VI. Iden i y sys ema ic ulne abili ies.
2.1.2. C edi Risk
The main ac i i y o banks is he g an ing o c edi , o inance consump ion o in es men by he
popula ion. The bank c edi is a ele an ins umen o le e aging economies, c i ical o possible new
p oduc i e combina ions, and hese will be a he basis o he economies dynamics. The e a e in e nal
s udies o banks in o de o p edic si ua ions o de aul . Basel I came o de ine wha c edi isk was,
de ining he p obabili ies o de aul . BCBS de ined c edi isk ope a ions, which include gua an ees and
in es men s in bank secu i ies.
“Banking c edi is a igh ha he Bank acqui es, h oughou an ini ial cash deli e y
( eal o po en ial) o a cus ome , o ecei e om ha cus ome he amoun due, on
u u e da es, one o mo e cash ins allmen s whose o al alue is equal o he ini ial
deli e y plus he p ice ixed o ha se ice (in e es and commissions). (APB, 2020)
Acco ding o Tabo da e al. (2004), ci ed by (Veloso, 2016), when we e e o bank c edi , we mus ake
in o accoun he ollowing six elemen s:
Pu pose: “wha will be acqui ed wi h he amoun p o ided by he bank and i s use” (Nunes, 2009 -
quo ed by (Veloso, 2016);
Te m: acco ding o Tabo da e al. (2004), e e enced by (Veloso, 2016), can be classi ied as:
▪ Sho e m: ma u i y <1 yea ;
▪ Medium e m: 1 yea <ma u i y <5 yea s;
▪ Long e m: ma u i y> 5 yea s.
P ice: in e es and commissions. Among o he a iables, he g ea e he isk in ol ed in he ope a ion,
he highe he p ice o be cha ged (Veloso, 2016);
Amoun : de e mined acco ding o he clien s' needs and he alue o he asse o be acqui ed (Nunes,
2009 - ci ed by (Veloso, 2016);
Po en ial loss esul ing om he c edi ope a ion (Veloso, 2016);
9
Gua an ees: hey a e a way o compensa ing he c edi o o a possible loss in he business o one
(Ama al e al. (1997), ci ed by (Veloso, 2016).
The de ini ion o c edi isk also includes o he de ini ions, as men ioned (Veloso, 2016):
Coun e pa y Risk - unde s ood as he possibili y o non-compliance, by a ce ain coun e pa y, wi h
obliga ions ela ed o he se lemen o ansac ions ha in ol e he ading o inancial asse s,
including hose ela ed o he se lemen o de i a i e inancial ins umen s;
Coun y Risk - unde s ood as he possibili y o losses associa ed wi h non-compliance wi h inancial
obliga ions unde he e ms ag eed upon by a policyholde o coun e pa loca ed ou side he coun y,
as a esul o ac ions aken by he go e nmen o he coun y whe e he policyholde o coun e pa y
is loca ed, and he isk o ans e , unde s ood as he possibili y o he occu ence o obs acles in he
cu ency con e sion o he amoun s ecei ed;
Commi men isk - unde s ood as he possibili y o disbu semen s o hono su e ies, gua an ees, co-
obliga ions, c edi commi men s o o he ope a ions o a simila na u e;
In e ene isk - unde s ood as he possibili y o losses associa ed wi h o he non-compliance wi h
inancial obliga ions unde he e ms ag eed by an in e media y o con en ion o c edi ope a ions;
Concen a ion isk - unde s ood as he possibili y o c edi losses esul ing om signi ican exposu es
o a coun e pa y, a isk ac o o o g oups o ela ed coun e pa ies h ough common cha ac e is ics.
2.1.3. C edi Risk Componen s
The Basel II ag eemen came o p o ide guidelines o measu ing capi al isk, using in e nal
pa ame e s.
The minimum equi emen s o calcula ing c edi isk capi al (IRB App oach) a e he ollowing:
De aul P obabili y (PD), pe cen age ha co esponds o he long- e m expec a ion o de aul a es,
wi h a ime ho izon o 1 (one) yea o bo owe s o a ce ain le el o c edi isk o homogeneous g oup
o isk;
Exposu e a De aul (EAD), co esponds o he alue o he ins i u ion's exposu e, whe he e ec i e
o con ingen , o he bo owe o coun e pa y a he ime o he e en o de aul , g oss o p o isions
and possible pa ial educ ions a loss;
Loss Gi en De aul (LGD), co esponds o he pe cen age, in ela ion o he obse ed EAD pa ame e ,
o he economic loss esul ing om he spli , conside ing all ele an ac o s, including discoun s
g an ed o c edi eco e y and all di ec and indi ec cos s associa ed wi h cha ging he use;
E ec i e Ma u i y Te m (M), co esponds o he emaining e m o he ope a ion weigh ed by he
cash lows o each u u e pe iod.
Financial ins i u ions, o quan i y c edi isk, a e au ho ized o use one o h ee app oaches o
me hodologies: s anda d me hodology, In e nal Ra ing Based (IRB) Founda ion me hodology (o
simple in e nal me hod) and IRB Ad anced (o in e nal me hods ad anced). (Pe ei a, 2019)

10
In he s anda d me hodology, he isk weigh s a y acco ding o he a ing gi en by he a ing agencies
ce i ied by he supe iso y au ho i ies. These a ings a y wi h he deg ee o compliance o he deb o
and by i s na u e, namely in e na ional o ganiza ion, ins i u ion, so e eigns, companies o eal es a e.
(Pe ei a, 2019)
In he IRB me hodology, he bank uses in e nal c edi isk es ima es o measu e he capi al
equi emen s. Howe e , o use he in e nal models, he ins i u ion is subjec o he app o al o he
egula o , and i is necessa y o comply wi h a se o equi emen s.
In summa y, wi hin he IRB, banks can choose a basic in e nship (Founda ion) o an ad anced
in e nship (Ad anced). In he i s , banks use in e nal es ima es o he de aul p obabili y associa ed
wi h bo owe 's ca ego y, and supe iso s p o ide o he inpu s ( isk componen s). In he second,
banks a e allowed o de elop an in e nal capi al alloca ion p ocess conside ing in e nal es ima es o
he isk componen s. (Pe ei a, 2019)
In he IRB app oach, inancial ins i u ions can assess he Expec ed C edi Losses (ECL) o hei c edi
exposu e. The pe cen age o EL is calcula ed by he p oduc o he PD wi h he LGD; when mul iplied
by EAD, he expec ed loss (EL) is ob ained in absolu e alue - acco ding o Equa ion:
𝐸𝐶𝐿𝑡=𝐿𝐺𝐷𝑡 × 𝑃𝐷𝑡 × 𝐸𝐴𝐷𝑡
The e a e h ee a iable ha can be de eloped o LGD and PD. Fo p esen disse a ion will ocus on
he PD calcula ing me hod, bu i is impo an o unde s and he concep .
The p obabili y o de aul is he p obabili y o coun e pa y de aul ing, i is meaning ha he e no be
able o make paymen s p e iously ag eed he comple ion o he c edi assignmen ag eemen . The
LGD e lec s he pe cen age o exposu e he bank expec s o lose4 i he coun e pa y de aul , and
he EAD e lec s an es ima e o ou s anding amoun in he case o he coun e pa y de aul .
The pa ame e s desc ibed abo e depend an idiosync a ic and sys ema ic componen . The sys ema ic
componen can be explained by ex e nal ac o s, such as mac oeconomic componen s.
2.1.4. Mac oeconomic componen s a e in luenced c edi isk
A pe spec i e o o ecas ing and de eloping s ess scena ios, mo i a ed by ac o s ex e nal, in o de
o espond o he challenges se ou abo e (s ess es ), banks we e o ced o de elop models in
which he de aul a iable, i can po en ially be explained by mac oeconomic ac o s, exogenous o
he dependen a iable. The o mula ion o hese econome ic models aims o y o p edic he
p obabili y o de aul , bu also ha o he a ious ansi ions be ween isk classes, ep esen ed
ypically by a ma ix o mig a ions.
Mac oeconomic s abili y is a undamen al de e minan in he banking sys em (Cha es, 2017).
Mac oeconomic a iables in luence he banking sys em, as well as a coun y's GDP g ow h, in la ion
a e, he in e es a e, loans g an ed, unemploymen a e, household disposable income, exchange
a e was in luence economy.
The e is a la ge li e a u e on c edi de aul isk and economic ac i i y, ha is e e ed o a con agious
e ec cycle, he main ac o s a e c edi isk, i s de aul and economic ac i i y. The mos s udied
hypo hesis emphasizes he ela ionship be ween he de aul a e, income and e enues being
in e connec ed, in expansiona y phases hese a iables ha e opposi e signs, low de aul a e and high
yield. Likewise, when he economy is ecession, he cha ge o inc eases and he emaining a iables
dec ease. (Cha es, 2017)
11
GDP is he business es ima e o all goods and se ices c ea ed in a e i o y in a gi en pe iod o ime.
GDP g ow h is seen as an image o p og ession, composed o he o ali y o p i a e and public
consump ion and in es men , public and p i a e. The symbols o a coun y's economic g ow h is GDP
g ow h, his is a a iable in insically linked o he de elopmen o he inancial sys em. GDP was
cha ac e ized by he business es ima e o goods and se ices c ea ed in a e i o y, du ing a pe iod o
ime, usually one yea . GDP g ow h is seen as an image o he coun y's p og ession, adding p i a e
and public consump ion, wi h public and p i a e in es men . (Yahaya & Oni, 2016)
Repullo & Salas (2011) sugges he need o a capi al cushion when he economy is high, in o de o
le e age he economy when i p esen s lowe han expec ed GDP esul s and a ecession end,
happens a he momen when deb o s ail o epay c edi s, leading o high de aul a es and majo
bank losses.
The e a e s udies ha deno ed GDP g ow h a e has a nega i e e ec on p oblema ic loans, imes o
ecession, c edi de aul s inc ease. (Cha es, 2017)
Ano he simila s udy by Amuakwa-Mensah and Boakye, ci ed by (Cha es, 2017) e e s a signi ican
empi ical e idence o a nega i e ela ionship be ween eal GDP g ow h and c edi de aul . The
nega i e ela ionship is ela ed o he ac ha wi h he inc ease in eal GDP, i gene ally ansla es
in o an inc ease in disposable income, he e may be a dec ease in cha ge o .
A heal hy economic en i onmen means an inc ease disposable income and consequen ly a educ ion
o unemploymen . Acco ding o se e al au ho s who s udied he ela ionship be ween c edi a iables
and unemploymen , hey ound a s ong posi i e co ela ion be ween c edi and unemploymen . Tha
means ha wi h he lack o employmen he bo owe s ail he paymen s. (Cha es, 2017)
Disposable income is he amoun o money ha households ha e a ailable o spending and sa ing
a e income axes. Disposable income is closes o he concep o income as gene ally unde s ood in
economics. Household disposable income is he sum o wages and sala ies, mixed income, ne p ope y
income, ne cu en ans e and social bene i s. (OECD, 2020)
In la ion occu s when he e is a pe sis en inc ease o p ices o goods and se ices wi hou an inc ease
le el o p oduc ion. I means cu ency uni is able o buy less goods and se ices om ano he
economy. This ac o is associa ed wi h an inc ease cu ency in economy. (Yahaya & Oni, 2016)
When his si ua ion occu s, o ising in la ion, mone a y egula o s y o keep up wi h he inc ease
in e es a e, in o de o con ol in la ion. This measu e has consequences on he le el o c edi ,
leading o an inc ease in bo owing cos s. In la ion also has an in luence on households' pu chasing
powe . (Cha es, 2017) I can mean an inc ease in c edi de aul . The e o e, i is expec ed ha he e
will be a posi i e ela ionship be ween in la ion and c edi de aul .
The exchange a e is alue o a na ional cu ency, in uni s o o eign cu ency. The nominal exchange
a e is exp essed in mone a y uni s, on he o he hand, he eal exchange a e exp esses he pu chasing
powe o a na ional cu ency in ol ed in o eign ansac ions o goods o be acqui ed in a coun y in
exchange o he same se in he ou side. (Yahaya & Oni, 2016)
12
The exchange a e has an e ec on he compe i i eness o domes ic p oduc s ab oad, so he
de alua ion inc eases he compe i i eness o domes ic p oduc s ab oad, which may inc ease expo s,
p oduc ion and employmen , and he e may be an inc ease in domes ic p ices causing in la ion.
(Cha es, 2017)
A de alua ion o he alue o domes ic cu ency can make impo ed goods e y expensi e, so banks
a e a high isk o de aul ing on c edi . (Cha es, 2017)
Eu ibo is meaning Eu o In e bank O e ed Ra e. The Eu ibo Ra es a e based on he a e age in e es
a es a which a la ge panel o Eu opean banks bo ow unds om one ano he . The e a e di e en
ma u i ies, anging om one week o one yea . The Eu ibo a es a e conside ed o be he mos
e e ence a es in Eu opean money ma ke . (Eu ibo , 2020)
The ela ionship be ween he de aul and he in e es a e is h ough he cos o bo owe s, when
in e es a e inc ease de aul will be also inc ease.
Ci ed by Cha es, he in e es a es on loans o he e olu ion o c edi de aul a es a e ela i ely small,
since hey only ha e an impac on he sho - e m policies es ablished by cen al banks.
13
2.2. SECTION II STRESS TEST
2.2.1. A b ie his o y o s ess es ing on banks
Be o e he inancial c isis, banks pe o med s ess es s o assess hei in e nal isks, bu i was a simple
exe cise wi h ew impac s on policies and decision-making. A e he inancial c isis, s ess es s
became an impo an ool o suppo isk managemen and assumed a leading ole in egula o y
ac i i y.
The c isis in he 1990s and he cu en inancial ins abili y ha e inc eased he impo ance o a be e
unde s anding o possible ulne abili ies in he inancial sys em o egula o s and banke s. Thus,
se e al quan i a i e echniques ha e been de eloped o assess po en ial isks in inancial ins i u ions.
These echniques a e called s ess es s. Basel Commi ee on banking supe ision sugges ed es ing in
he inancial sec o (Chowdhu y, 2010).
The i s s ess es s based on scena io analysis appea ed in he mid-1990s. Manage s began o assess
hei po olios h ough s a is ical analysis based on his o ical and hypo he ical scena ios. His o ical
scena ios a e based on pas e en s wi h a iew o he u u e. Al hough his is an essen ial ool, he
p oblem is ha pas e en s may no be epea ed in he u u e, hence he need o in oduce
hypo he ical es s, based on se ious bu plausible e en s. These hypo he ical e en s a e based on
changes in he ou look o economic g ow h. A he ime, he e was no pa e n o he use o s ess
es s, he e we e banks ha used he es s o quan i y he maximum loss o a bank in a gi en po olio,
while o he banks sough limi s on ading o quan i ied he amoun o capi al o inance a speci ic
po olio (Wes wood, Den , & Sego iano , 2016)
In 1996, he e was a change o he in e na ional egula o y capi al egime o he ma ke isk, ha is,
he isk o losses in posi ions due o changes in ma ke p ices. A e his change, banks began o use
hei in e nal models o quan i y ma ke isk o de e mine he capi al equi ed in he de aul ’s e en .
In 1999, he Basel Commi ee on Banking Supe ision (BCBS) saw li le p og ess in he echniques and
hei applica ion on he ma ke , he e o e i de eloped echniques o implemen he s ess es applied
o c edi isk.
In 2004, Basel II, a ises he i s s eps o assess c edi and ma ke isks a ise in o de o de e mine he
necessa y capi al, known as egula o y capi al. A e his s anda d, banks we e equi ed o assess hei
c edi isk s ess es s. Despi e his, Basel II had no been implemen ed by all economies be o e he
s a o he inancial c isis. Be o e he c isis, e en banks ha had he s ess es model in place we e
unable o p edic he 2009 c isis. The pu pose o hese es s is o p o ide a quan i a i e measu e o
he ulne abili y o a coun y's inancial sys em o di e en mac o- inancial scena ios and o
complemen he ideas collec ed by o he componen s o he e alua ion. This includes quali a i e
ulne abili y assessmen s and a e iew o egula o y and c isis managemen in a coun y. (Wes wood,
Den , & Sego iano , 2016)
In 2007, he Uni ed S a es expe ienced he wo s inancial c isis since he 30’s. The c isis apidly sp ead
om he Uni ed S a es o o he coun ies and om inancial ma ke s o he eal economy. Some
inancial ins i u ions ailed. Many mo e had o be bailed ou by na ional go e nmen s. The e can be
no ques ion ha he i s decade o he wen y- i s cen u y was disas ous o he inancial sec o .
Risk managemen has now assumed a much g ea e impo ance in inancial ins i u ions (Hull, 2018)
20
A undamen al aspec o any c edi isk VaR model is he c edi co ela ion. The s anda ds o di e en
companies do no happen independen ly o each o he . Du ing an economic down u n, mos
companies a e ad e sely a ec ed and become mo e likely o s op paying. When he economy is doing
well, hey a e a o ably a ec ed and less likely o de aul . This ela ionship be ween de aul a es and
economic ac o s is one o he main easons o he c edi co ela ion. I he c edi co ela ion inc eases
(as i usually does unde s essed economic condi ions), he isk o a inancial ins i u ion wi h a
po olio o c edi exposu es inc eases. (Hull, 2018)
To de e mine he VaR o ES o c edi sp ead-dependen ins umen s, he e a e wo app oaches:
To collec his o ical da a on companies' c edi sp ead a ia ions and use a his o ical simula ion
me hodology.
To model co po a e a ing ansi ions and mo emen s in a e age c edi sp eads associa ed wi h
di e en a ing ca ego ies. (Hull, 2018)
2.2.8. S ess es ing and Value a Risk
Be kowi z (2000) sugges s ha he s ess es will ha e be e esul s i hey a e in eg a ed in o he
VaR calcula ion. This can be done by assigning a p obabili y o each s ess scena io conside ed.
Suppose a inancial ins i u ion has conside ed s ess scena ios and he o al p obabili y a ibu ed o
s ess scena ios is p. Assume he e a e VaR scena ios gene a ed using his o ical simula ion in he usual
way.
Un o una ely, human beings a e no good a es ima ing a subjec i e p obabili y ha a a e e en will
occu . To make he ask o he s ess es commi ee easible, one app oach is o ask he s ess es
commi ee o alloca e each scena io o ca ego ies wi h p e-assigned p obabili ies. The ca ego ies can
be:
P obabili y = 0.05%. Ex emely unlikely. One chance ou o 2,000.
P obabili y = 0.2%. Ve y unlikely, bu he scena io mus be p esen ed in he same way as he
500 scena ios used in he his o ical analysis o he simula ion.
P obabili y = 0.5%. Unlikely, bu he scena io should be gi en mo e weigh han he 500
scena ios used in his o ical simula ion analysis.
S ess es ing in ol es e alua ing he impac o ex eme, bu plausible, scena ios ha
a e no conside ed by VaR o expec ed sho all (ES) models. I he e is one lesson o be lea ned om
he ma ke u moil ha s a ed in he summe o 2007, i is ha mo e emphasis should be placed on
s ess es ing and less emphasis should be placed on he mechanis ic applica ion o VaR and ES models.
VaR and ES models a e use ul, bu hey a e ine i ably backwa d looking (Hull, 2018).
S ess es s meaning VaR. VaR is hough o be a c i ical ool, and i can be a isk o a i m’s po olio
on a day le el and pe o mance o indi idual business uni s. VaR has been ound o be o limi ed use
o ex eme ma ke e en s. I happens because by de ini ion, such e en s occu oo a ely o be
cap u ed by empi ically d i en s a is ical models. The e a e co ela ion pa e ns be ween inancial

21
p ices ( he co ela ion ha would be es ima ed using da a om o dina y imes). S ess es s o e a
way o measu ing and moni o ing he po olio consequence o ex eme p ice mo emen s o his ype.
The bes app oach is he in eg a ion o objec i e and subjec i e p obabili ies. This means ha on he
one hand, Va and ES models mus be in eg a ed h ough his o ical and e ospec i e simula ions bu
on he o he hand, subjec i e p obabili ies mus be in eg a ed in he c ea ion o scena ios h ough
senio manage s, whe e he e is an analysis o a ious ma ke a iables, such as he economic
en i onmen and analysis o di e si ied ma ke scena ios. (Hull, 2018).
22
2.3. SECTION III COVID-19 PANDEMIC
2.3.1. F amewo k COVID-19 Pandemic
The COVID-19 pandemic is b inging a lo o ins abili y o he wo ld, and coun ies also ha e di icul y
on choosing he bes op ions o apply in hei coun y, because many o hese measu es, such as he
case o social con inemen , will ha e e y signi ican economic consequences. The mos ele an
eason is ha small and medium-sized companies and indi iduals a e being a ec ed by his public
heal h c isis, which has economic consequences, in which hey may su e om liquidi y p oblems and
di icul ies on paying hei inancial commi men s. Consequen ly, his will ha e an impac on inancial
ins i u ions and on hei c edi obliga ions. A delay in he paymen o c edi obliga ions will lead o a
la ge numbe o de aul s and an inc ease in und equi emen s o hese same ins i u ions.
The pandemic c isis has a signi ican impac on wo king, ei he o easons o illness o wo ke s and
need o suppo hei amilies o heal h secu i y and manda o y dis ance. The in e ac ion o hese
ac o s clea ly esul s a dec ease p oduc ion on companies, despi e he he e ogenei y obse ed
be ween sec o s o ac i i y. In pa allel wi h he con ex o unce ain y unde lying he e olu ion o he
pandemic all con idence o economic agen s, his led o a signi ican dec ease in he demand o goods
and se ices. A e he g adual educ ion in con ainmen measu es, and despi e some imp o emen
obse ed, he main enance o an un a o able mac oeconomic en i onmen and high unce ain y,
esul ed in an inc ease in unemploymen and a d op income, loss o con idence. Leading o an inc ease
in sa ings o easons o p ecau ion and o he weakening o consump ion and in es men .
In his con ex , in an a emp o minimize he medium and long- e m economic impac s o con ain he
pandemic COVID-19, he coun ies o he Eu opean Union ha e implemen ed a wide ange o suppo
measu es. These measu es a e in he o m o paymen s o c edi obliga ions, in o de o suppo he
ope a ional and liquidi y pa o he c edi deb o s.
2.3.2. Recommenda ions by Eu opean Cen al Bank
ECB (Eu opean Cen al Bank) has implemen ed a se ies o measu es o help he banks o deal wi h he
cu en si ua ion we a e li ing nowadays due o COVID-19, which ha e led many companies, banks and
o ganiza ions o limi hei p ocesses, ac i i ies and human esou ces. I has c ea ed an app oach called
SREP
7
- supe iso y e iew and e alua ion p ocess. This app oach aims o ensu e an e icien and
s uc u ed assessmen o he banks. Th oughou 2020, his p ocess will ocus on he banks' abili y o
7
I is a se o p ocedu es led annually by he supe iso au ho i ies ha ensu es ha each c edi ins i u ion has s a egies,
p ocesses, capi al and liquidi y app op ia e o he isks ha i may be exposed. This p ocess makes he Basel II ope a ional
in he Eu opean and Na ional egula iza ion. In he SREP i is also e alua ed he isk ha each ins i u ion is o he inancial
sys em
23
espond he cu en challenges and isks ela ed o he c isis and manage he impac in he upcoming
mon hs. Supe iso s will assess he ou undamen al Pilla :
I. Scena io design: consis s o he design o he mac o- inancial scena ios o be imposed on he
banking sec o ;
II. Top-down sa elli e models: consis s o he modules used o ansla e he scena ios in o
a iables a ec ing he alua ion o bank balance shee componen s and banks’ loss
abso p ion capaci y;
III. Balance shee module: akes he p ojec ed p o i and losses de i ed om he sa elli e
models o indi idual bank balance shee s wi h he aim o calcula ing he esul ing impac on
each bank’s sol ency posi ions;
IV. Feedback modules: akes he analysis beyond he i s - ound impac on bank capi aliza ion o
assess wha could be he de i ed second- ound e ec s o he ini ial bank sol ency impac in
e ms o con agion wi hin he inancial sys em and in e ms o eedback e ec s o he eal
economy.
The main ocus will be o assess he banks' abili y o deal wi h he c isis and manage he impac in he
coming mon hs.
ECB adop ed an ex ao dina y package in o de o help so e eign deb yields. The i s announcemen
was he pu chase o asse s in he ini ial amoun o 750 billion eu os, inc easing o 1350 billion eu os,
which will con inue un il he end o June 2021 (Pandemic Eme gency Pu chase P og am).
In e nal capi al adequacy assessmen p ocess (ICAAP
8
) and In e nal Liquidi y Adequacy Assessmen
P ocess (ILAAP
9
) a e impo an sou ces o in o ma ion o unde s anding how banks manage capi al
and liquidi y in his e y challenging ime. Supe iso s a e collec ing e idence o bank’s assessmen o
he cu en p ocesses o managing capi al and liquidi y, including he decision making, he abili y o
upda e liquidi y and inancial planning, as well as s ess es scena ios.
The ECB published a p ess elease s a ing ha banks could empo a ily ope a e below he le el o
capi al de ined by Pilla 2, capi al conse a ion and he liquidi y co e age a io.
Ano he measu e ecommended by he ECB is ha banks should no dis ibu e di idends o a iable
emune a ions and hey should use hei capi al o suppo he economy. I also poin s ou ha banks
should con inue o apply solid unde w i ing s anda ds, seek app op ia e policies in he ela ion o he
ecogni ion and co e age o non-p oduc i e exposu es, conduc a solid capi al and liquidi y planning
and ha e a s ong isk managemen .
8
The igo ous e alua ion and de e mina ion o he le el o in e nal capi al unde lying he isk p o ile o a c edi ins i u ion o
in es men company a e essen ial condi ions o he implemen a ion o sus ainable business s a egies, on he assump ion
ha hey a e suppo ed by app op ia e con ols. In pa icula , he planning o he e olu ion o in e nal capi al is conside ed
undamen al o ensu e i s adap a ion on a pe manen basis o he isk p o ile o he ins i u ions, pa icula ly in he ace o
c isis o ecession.
9
The ecen inancial c isis has shown he undamen al impo ance o liquidi y o c edi ins i u ions, gi en ha hei
insu iciency ep esen s an immedia e h ea o hei con inui y. One o he main lessons lea ned is ha liquidi y isk
managemen has o ensu e he abili y o c edi ins i u ions o mee hei paymen obliga ions a all imes, e en unde ad e se
condi ions.
24
Banks will also be able o implemen Pilla 2
10
equi emen s pa ially wi h an in e io capi al (as
addi ional ins umen s o Le el 1 o Le el 2). This an icipa es a measu e in he CRD5 ha should ha e
aken e ec in Janua y 2021 (A icle 104a) - EU banks will be able o se ice he P2R wi h 56.25% CET1
and he emaining wi h AT1 and Tie 2 capi al.
The ECB also wa ns o he need o banks o p epa e o possible nega i e e ec s caused by he sp ead
o he co ona i us.
In he eu o a ea, he ECB's announcemen a se o ex ao dina y measu es has pa ially e e sed he
inc ease in so e eign deb yields. The measu es o be highligh ed by he new eme gency asse
pu chase p og am (Pandemic Eme gency Pu chase P og am, PEPP), ini ially amoun ed o 750 billion
eu os, ollowed by he inc ease o 1350 billion eu os, which should be main ained un il he end o June
2021. In any case, he expec a ion o a longe economic con ac ion is e lec ed in a di e en alua ion
o isk p emiums o he sec o s o ac i i y and ma ke segmen s mos ulne able o he e ec s o he
COVID-19 pandemic. Con inemen measu es and limi a ions on in e na ional mobili y had a
pa icula ly signi ican impac on ai lines and ou ism- ela ed ac i i ies, whe e de alua ions o mo e
han 40% we e obse ed du ing Ma ch 2020, wi h a mo e ecen limi ed eco e y.
2.3.3. Recommenda ion by Eu opean Baking Au ho i y
EBA is one o he h ee en i ies ha a e pa o Eu opean Sys em o Financial Supe ision (ESFS).
The e mo e wo en i ies: Eu opean Secu i ies and Ma ke s Au ho i ies (ESMA) and Eu opean
Insu ance and Occupa ional Pensions Au ho i y (EIOPA). The da e o ounda ion o EBA is 1s o
Janua y o 2011.
The EBA has c ea ed guidelines o ace he c isis c ea ed by he pandemic COVID-19. The measu es a e
limi ed and a e applied only o he economic si ua ion caused by COVID-19. The bene icia ies o hese
guidelines a e sho - e m bo owe s, which include small and medium-sized en e p ises, mo gage
loans o indus ial sec o s a ec ed by his c isis. The measu es a e no applied o deb o s iden i ied
be o e he COVID-19 pandemic ou b eak, nei he o deb o s whose ma u i y has been unchanged.
New loans g an ed a e he ou b eak o COVID-19 a e also no co e ed by hese measu es.
The condi ions o hese guidelines a e o change he paymen schedule in o de o add ess he
sho age o liquidi y. Consequen ly, paymen s a e suspended, pos poned o educed, wi hin a limi ed
pe iod. This will a ec he en i e paymen schedule and may lead o an inc ease in paymen s a e he
10
Eu opean banking law de ines h ee elemen s o own unds. Common Equi y Tie 1 capi al (CET1) is he highes quali y o
own unds and is mainly composed o sha es and e ained ea nings om p e ious yea s. Addi ional Tie 1 capi al (AT1) and
Tie 2 capi al can be equi y o liabili y ins umen s and a e o lowe quali y. Pilla 2 capi al consis s o wo pa s. One is he
Pilla 2 Requi emen o P2R, co e ing isks which a e unde es ima ed o no su icien ly co e ed by Pilla 1. The o he is he
Pilla 2 Guidance o P2G, which indica es o banks he adequa e le el o capi al o be main ained in o de o ha e su icien
capi al as a bu e o wi hs and s essed si ua ions, in pa icula as assessed on he basis o he ad e se scena io in he
supe iso y s ess es s. Unde he new Capi al Requi emen s Di ec i e V (CRDV) banks can ul il Pilla 2 Requi emen s wi h
a minimum 56.25% CET1 as a gene al p inciple. The emaining P2R can be illed wi h Addi ional Tie 1 and Tie 2 ins umen s.
This law was ini ially scheduled o come in o e ec in Janua y 2021 as pa o he la es e ision o he CRDV.
25
pe iod o he special loan condi ions, in pa icula he in e es a e, in o de o a oid majo losses by
he inancial ins i u ion, and he impac on ne p esen alue o be neu alized. Howe e , his change
should no a ec in e es a es.
A inal poin o conside is ha inancial ins i u ions mus con inue o bo ow o new cus ome s.
Howe e , he new loan mus ollow no mal c edi policies and be based on an assessmen o
cus ome s' c edi wo hiness. These new loans mus be assessed agains cu en paymen capabili ies
and indi idual condi ions mus be assessed on a case-by-case basis.
The main objec i e is ha inancial ins i u ions con inue o apply isk policies, paying special a en ion
o he assessmen o deb o s mos likely o ace paymen di icul ies. EBA also ecognizes ha policies
and p ac ices ega ding he assessmen o imp obabili y o paymen may di e depending on he
po olio and he ype o deb o , aking in o accoun he a ailabili y o in o ma ion. These checks a e
expec ed o con inue o he du a ion o he paymen s and a hei comple ion.
Likewise, i is expec ed ha co po a e cus ome s, whe e he po en ial imp obabili y o paymen is
assessed manually as pa o he egula moni o ing p ocess, based on he deb o s' inancial
s a emen s and o he in o ma ion, should con inue h oughou he du a ion o he paymen s un il i s
e m.
Ins i u ions mus iden i y possible economic losses ha may su e due o he applica ion o he
guidelines, including h ough addi ional cha ges o impai men .
Financial ins i u ions mus con inue o assess he likelihood and de aul o paymen s. All go e nmen
measu es o p o ide addi ional suppo o deb o s du ing he cou se o he COVID-19 pandemic should
be e iewed, and be a ailable, so ha i he deb o is in c edi wo hiness, hey should be conside ed
in non-paymen s. Thus, he inancial ins i u ion mus mi iga e i s c edi isks, using non-paymen
assessmen s.
The isk o a gene alized downg ade o lowe le els o in es men assumes pa icula ele ance o
economic agen s who, in a p olonged con ex o low in e es a es, adjus ed he composi ion o hei
po olios looking o g ea e sea ch- o -yield. In he eu ozone, in es men was mos ly in in es men
unds, inc easing i s exposu e o lowe c edi quali y asse s and highe isk o coun e pa y. Gi en he
signi ican size o in es men unds in he Eu opean con ex and he high p opo ion o secu i ies a
he h eshold o he le el o in es men in hei po olios may imply an ab up de alua ion in he
alue o asse s, ep esen ing a sou ce o isk in Eu ope.
EBA w o e guidelines o help comba he c isis caused by COVID-19:
▪ C i e ia o c edi paymen s no o igge o he classi ica ions;
▪ P uden ial equi emen s in he con ex o de aul ;
▪ Ensu e consis en ea men o measu es and calcula ion o capi al equi emen s.
EBA also has a guidelines o s ess es , ha he main isk o assess a e:
• C edi isk;
• Ma ke isk;
• Secu i iza ion;
• Cos o unding.

26
C edi isk is meaning a possibili y o loss esul ing om a bo owe ’s ailu e o epay a loan o
ag eemen be ween wo pa s. I e e s o he isk ha a lende may no ecei e he owed p incipal
and in e es , which esul s in an in e up ion o cash low and inc eased cos s.
Ma ke isk is he isk associa ed o he possibili y ha a bank, as in es o , su e s losses due o ac o s
ha a ec ed nega i ely he pe o mance o he inancial ma ke s. This ype o isk is also called
sys ema ic.
Secu i iza ion is a complex p ocess ha uses inancial enginee ing o ans o m an illiquid asse o
g oup o illiquid asse s in o secu i ies. The isks associa ed o his p ocess inc ease when he
complexi y o he ins umen s inc ease, making ha de he analysis o he u u e secu i y pe o mance.
Secu i iza ion o e s oppo uni ies o in es o s and ees up capi al o o igina o s, bo h o which
p omo e liquidi y in he ma ke place.
Cos o unds is a e e ence o he in e es a e paid by inancial ins i u ions o he unds ha used by
business. The sp ead be ween he cos o unds and he in e es a e cha ged is one o he mos
impo an sou ces o p o i o he inancial ins i u ions. The isk in his ype o p ocess comes when
he cos o unding inc eases. I he cos o unding inc eases, he bank has h ee op ions. Fi s , cha ge
a bigge a e on loans, inding new cos ume s and making p o i in hese new loans. Second, keep he
same a e, inding new cos ume s and losing money in his new loans. Thi d, cha ge a bigge a e on
loans, bu did no ind new cos ume s, losing also money
The measu es a e aimed a suspending o pos poning paymen s o deb o s a ec ed by he COVID-19
pandemic, in which hey saw a educ ion in hei budge , allowing hem o la e esume egula
paymen s when he pandemic si ua ion is al eady sol ed.
The EBA ecommends ha inancial ins i u ions should con inue o assess and iden i y si ua ions, in
which sho - e m paymen s a e commi ed, and in he long e m ha could lead o insol ency. The
eal impac o he economic shock can only be assessed on he basis o isk a ings and measu emen s.
(Final epo - Guidelines on legisla i e and non-legisla i e mo a o ia on loan epaymen s applied in
he ligh o he COVID-19 c isis, 2020)
I should be no ed ha since he p e ious in e na ional inancial c isis, egula o y s anda ds and
supe iso y p ac ices ha e been adop ed, a na ional and in e na ional le els, in o de o inc ease
esilience in he inancial sec o . In he pa icula case o he banking sec o , hese esul ed in a
s eng hening o capi al a ios and liquidi y posi ion. This ac o is pa icula ly ele an in he cu en
pandemic con ex , since he ulne abili ies o he economies, mi iga ing he economic impac o
shocks. (Bank, 2020)
The i s e ec s o he pandemic c isis and he i s measu es adop ed o mi iga ion poin o a e y
signi ican con ac ion in wo ld economic ac i i y in 2020. Con a y o p e ious c isis, i s o igin was
ou side he inancial sec o . The i s economic impac was e lec ed in he dis up ion o dis ibu ion
and p oduc ion chai s a a global le el. The con inemen measu es adop ed by go e nmen au ho i ies
and he d op in he con idence o economic agen s, associa ed wi h unce ain y abou he e olu ion
o he pandemic c isis, caused, in a second phase, a demand shock. In his way, he cu en c isis s ands
ou om p e ious c isis due o simul aneous shocks on he supply and demand side. The con idence
o economic agen s eached his o ic lows and below ma ke expec a ions.
27
Figu e 1 Global Economic P ospec s - June 2020 (Sou ce: The Wo ld Bank (Le )); Pu chasing
Manage s Index – (Sou ce: IHS Ma ki e Re ini i . (Righ ))
As he sp ead o he SARS-CoV-2 i us ook on a global dimension, he unce ain y and he expec a ion
o economic e ec s we e e lec ed in inc ease isk p emiums and an ab up de alua ion o inancial
asse s. This e ec was especially isible in highe isk asse s, namely sha es and deb secu i ies o lowe
c edi quali y, as he p essu e o sell hese ins umen s and he sca ci y o liquidi y was e lec ed in
he inc ease in ola ili y o his o ic highs.
2.3.4. Mac o- inancial models used o calib a e shocks and p oduce scena ios
Mac oeconomic scena io is exogenous shocks, should e lec he unde lying sys emic isks o be
analysed. A mapping sys emic isks in o exogenous shocks has a simula ion ools a e employed o
de e mine he ele an shock sizes and p o iles. The shocks can be used by da a base on his o ical
dis ibu ions and o compu e a 1 % Value -a -Risk measu e he en i e y o ma ke s unde sc u iny.
In wha conce ns COVID-19 i is s ill ha d o p edic wha will happen since i is a new si ua ion, a new
and an unknown i us. The go e nmen has o ake measu es o p e en a U o L b eak and y o ha e
he V shape, hence he impo ance o analyzing scena ios.
In gene al, he e ec s o he pandemic and he consequen ab up and signi ican educ ion in
economic ac i i y a in e na ional and na ional le els, pose addi ional challenges o non- inancial
companies in Po ugal. The dec ease o ac i i y, and he alling o e enues ake o consequen
meaning o insol ency si ua ion and de aul obliga ions in he sho e m. The con inemen measu es
and limi a ions on in e na ional mobili y had a signi ican impac on ai lines and ou ism ac i i ies.
Consequen ly, he e we e b eaks in he o de o 40% du ing Ma ch 2020.
A he inancial le el, unlike o he sec o s o ac i i y, i con inues o eco d a e y s ong de alua ion,
app oxima ely 40%, since he beginning o he COVID-19 pandemic in Eu ope. In e es a es on he
lowes isk asse s a e egis e ed, combined wi h he mos ecen de alua ion o he asse s o which i
is exposed. A possible consequence is an inc ease in he de aul o c edi g an ed o he non- inancial
sec o .
Ins i u ions expec a conside able educ ion in he demand o c edi by indi iduals, ha ing al eady
seen a d op in he i s qua e , a dec ease in consume con idence and a de e io a ion in expec a ions
o he e olu ion o housing p ices. The un a o able e olu ion o hese ac o s could be accen ua ed
28
in a s ong economic ecession, inc easing unemploymen and a e y unce ain economic eco e y.
The i s e ec o he pandemic on he inancial ma ke s was an inc ease in isk p emiums, and a
de alua ion o hese secu i ies.
The pandemic c isis cons i u es a mac oeconomic shock wi h subs an ial impac s no only on he
economic c isis, bu also wi h long- e m nega i e e ec s. The cu en c isis will end o imply
pe manen losses in e ms o p oduc i e capaci y. This esul will be associa ed wi h he des uc ion
o less accumula ion o physical and human capi al and he in e up ion o comme cial and knowledge
ne wo ks.
The long- e m mac oeconomic shock calls o join Eu opean Union esponse measu es in o de o
a oid an asymme ic economic eco e y, and possible asymme ic consequences o na ional banking
sec o s.
In sho , he pandemic c isis has c ea ed a si ua ion o exace ba ed unce ain y, which is pa icula ly
challenging o inancial s abili y a na ional and in e na ional le els. The cu en pandemic c isis is a
es o he inancial sec o 's esilience. In u n, he na u e and implica ions o he pandemic c isis
equi e a coo dina ed esponse a Eu opean le el.
2.4. CLIMATE STRESS TESTING PILOT EXERCISE
Eu opean Cen al Bank and Bank o England will conduc clima e s ess es ing exe cises on he basis
o he same scena ios p o ided by Ne wo k o G eening he Financial Sys em (NGFS), while he Basel
Commi ee is ad ancing on i s s a egy o in eg a e clima e inancial isks in o banking p uden ial
egula ion.
The e a e some limi a ions due o he pionee ing na u e o his exe cise which o aising awa eness
on clima e- ela ed inancial isk. The u u e is o es a clima e s ess ha banks and insu e s will
ha e o gain expe ise in clima e scena io modeling, unde s anding clima e isk ansmission
channels and ely on be e o wa d-looking da a and imp o ed me hodologies. Clima e change is
expec ed o ha e agg ega e inancial impac s ha a e pe asi e in na u e. The main impo an is o
build a exposu e analysis, which in ol es mapping millions o i m and add ess-le el clima e isk
d i e s o inancial balance shee s. On inancial sys em losses could inc ease by almos 10% in he
e en o c edi a ing downg ades o high-emi ing om apid ises in he ca bon p ice o ensu e
alignmen wi h Pa is Ag eemen le els.
The p esen exe cise in ol es s essing he balance shee s banks and insu e s wi h a se o common
hypo heses:
• A long ime ho izon (2050), he use o ansi ion and physical isk scena ios b oken down in
sec o s and a dynamic balance shee ;
• Pa icipan s we e subjec o h ee ansi ion isk scena ios: ze o emission, once physical isk
scena io and based on a 30 yea s ime ame.
Physical isks lead o a signi ican inc ease in sinis ali y and insu e s balance shee s. The exposu es
o banks and insu e s o ansi ion isk is deemed as mode a e, wi h an inc ease cos o isk be ween
30% and 40% o co id-19 c isis inc eased i by 100%.
Physical isk in he banking sys em a e i ms exposed o high o inc easing isk. A ound 10,6% o bank
c edi exposu es o high o inc easing lood isk, 1,4% o coas al loods/ sea le el ise, 11,2% o hea
29
s ess, 12,2% o wa e s ess and 4,8% o wild i es. The dis inc ion be ween haza d p obabili y and
in ensi y becomes impo an when ansla ing haza d in o economic damage. (ECB/ESRB, 2021)
The banking sec o is exposed o i ms ansi ion isk by c edi and ma ke isk. The main analysis
sugges s ansi ion isks o he banking sys em a e p edominan ly om c edi isk. These exposu es
a e ela ed o 14% in o al balance shee a e isks o inancial s abili y appea b oadly manageable.
The eu o a ea banking sys em may be exposed o ail isk in he e en o sudden changes in ca bon
p ices i i ms do no educe hei emissions.
Scena ios ely on a decoupling be ween emissions and GDP g ow h, since GDP g ow h each
emissions neu ali y. This implies ha a apid educ ion o emissions could be achie ed wi hou a
signi ican impac on GDP ha s ess es conduc ed by he EBA equi e scena ios based on h ee
consecu i e yea s o GDP con ac ion. Consequen ly, banks c edi exposu es a e subjec o a ia ions
in p ices om he ajec o y o a ca bon ax and p oduc i i y o ac o s.
Scena io analysis equi es hypo he ical bu plausible scena ios o highligh he impac o clima e isks
on he inancial sys em. I could help cen al banks and supe iso s o in eg a e clima e isk in o
inancial s abili y moni o ing. Mi iga ion policies can be in oduced ei he immedia ely, la e on, o
emain insu icien and include a numbe o echnological assump ions, o ins ance ega ding he
a ailabili y o ca bon dioxide emo al echnologies. (ECB/ESRB, 2021)
The banking sec o is a in e media ing unds o co po a es and is he eby exposed o i ms ansi ion
isk. Bank loan exposu es o clima e sec o s, a ound hal o o al loans. Eu opean Union Membe
S a es exposu es o he housing (36%) and ene gy-in ensi e sec o s amoun (8%) o o al loans
ac oss he eu o a ea.
Mainly concen a ed sec o s o exposu es in he eu o a ea a e manu ac u ing, elec ici y,
anspo a ion and cons uc ion sec o s, con ibu e o a ound wo- hi ds o bank loan-weigh ed
emissions in ensi y.
36
The eg ession es o DW es is augmen ed by explana o y a iables o he o iginal model
𝑋𝑡,1,𝑋𝑡,2,…,𝑋𝑡,𝑘. The s a is ic es is ob ained by 𝑅2 o auxilia eg ession.
3.8.2. Tes - and Tes -F
The simples e sion signi icance es s a e es - ( o indi idual signi icance) and es -F ( o global
signi icance). The es -F is adap a ion o he es - . Conside ing he Linea eg ession equa ion:
𝑦=𝛽1+𝛽2𝑥2+𝛽3𝑥3+⋯+𝛽𝑘𝑥𝑘
In his case, hypo hesis null o es - can be 𝐻0: 𝛽𝑖=0 and hypo hesis null o es -F can be 𝐻0: 𝛽𝑖=
0,𝑤ℎ𝑒𝑟𝑒 𝑖 =1,…,𝑘. The s a is ic es o an indi idual signi icance es can be gi en by:
𝑡 = 𝛽
󰆹
𝜎𝛽
√𝑛
⁄
Whe e 𝛽
󰆹 is model OLS es ima o , 𝜎𝛽
 is he s anda d de ia ion es ima e o he OLS es ima o and 𝑛 is
numbe o obse a ions.
In he case o es -F, i is necessa y o es ima e an auxilia eg ession, imposing by es ic ions es
and all coe icien s is equal o ze o. The s a is ic es can be gi en by ollowing equa ion:
𝐹 = 𝑅𝑈𝑅
2−𝑅𝑅
2
𝑞
1−𝑅𝑈𝑅
2
𝑇−𝑝
Whe e 𝑅𝑈𝑅
2 is measu e by 𝑅2un es ic ed model, 𝑅𝑅
2 is he model wi h imposed es ic ions, 𝑞 is he
numbe o es ic ions o be es and 𝑇−𝑝 numbe o deg ees o eedom
3.9. MODEL VARIABLES
3.9.1. S ess Tes
The dependen a iable, c edi de aul , o he model is he s ess es s esul s. C edi de aul is a
dummy a iable and i he esul is equal o 1, c edi de aul will be ail in pe iod . Howe e , i he
esul s is equal o 0, c edi de aul in Po ugal will no be ail, so deb o s can pay hei mo gages o
loans.
3.9.2. Unemploymen a e
The unemploymen a e is he pe cen age o he o al labo o ce ha ’s unemployed and ac i ely
seeking wo k. The unemploymen a e is an impo an measu e o economic heal h. I goes up du ing
a c isis pe iod o economic when demand o goods and se ices is low. The unemploymen a e is
one o he de e minan s o he non-pe o ming loans, because households unemployed ha e less
income and he e o e he p obabili y is goes up o hei loans paymen s, so de aul c edi is inc ease
and economic will ail.

37
When unemploymen a e is highe , he e o e de aul c edi is highe . So, i is expec ed ha 𝛽2𝑈𝑅𝑡
will has a posi i e sign, since he unemploymen a e is posi i ely co ela ed wi h he dependen
a iable.
3.9.3. Loans
C edi is an ag eemen be ween a c edi ins i u ion (lende ) and a cus ome (deb o ), who is obliged
o eplay he amoun an ag eed pe iod, wi h in e es cha ge and o he cos s.
Loans o deposi s a io is he a io be ween he o al loans and he o al deposi s o he bank.
Deposi s as deb issuance and sha eholde s equi y a e main sou ces o unds o a bank, being
deposi s he mos s able sou ce o unding. Bigge loans o deposi s a io, means ha deposi s,
inc easing he c edi isk. Also, Sil a ci ied Ape gis and Payne ha i is expec ed ha 𝛽3𝐿𝑅𝑡 p esen s
a posi i e sign, since loans o deposi s a io is posi i ely co ela ed wi h he dependen a iable.
Only c edi ins i u ions and ce ain inancial companies egis e ed in Banco de Po ugal can g an
c edi . The h ee mos impo an ca ego ies used by cus ome s a e: mo gage c edi , consume
c edi and business c edi .
3.9.3.1. Mo gage c edi
Mo gage c edi is an ag eemen be ween wo pa s ha he main pu pose is a acquisi ion o
cons uc ion o pe manen , seconda y o en al house. I also includes c edi con ac s o he
acquisi ion o main enance o p ope y igh s. This ype o c edi is a long- e m loan, he mo gage is
gi en as a gua an ee o epaymen .
C edi con ac s ha no co esponding o a mo gage loan, a e gua an eed by a mo gage o by
ano he equi alen gua an ee commonly used on eal es a e, such as consolida ed c edi o c edi in
which pu pose is no de ined. I is expec ed ha 𝛽4𝐿𝑀𝐶𝑡 p esen s a posi i e sign, since Mo gage
C edi o deposi s a io is posi i ely co ela ed wi h he dependen a iable.
3.9.3.2. Consume c edi
Consume c edi is a speci ic ype o pe sonal c edi in which specialized inancial ins i u ion a ailable
o a indi idual p i a e, ce ain amoun o goods o se ices. Also included consume c edi ca ego y
a e c edi ca ds and sala y accoun s. Rega ding he paymen e ms o consume c edi s a e gene ally
in a sho - e m, a mos up 5 o 6 yea s. I is expec ed ha 𝛽5𝐿𝐶𝐶𝑡 p esen s a posi i e sign, since
Consume C edi o deposi s a io is posi i ely co ela ed wi h he dependen a iable.
3.9.3.3. Business C edi
Business c edi is a speci ic c edi o a business’s accoun s and ac i i y o a business c edi . Business
c edi is used o Small Business Adminis a ion, business’s insu ance p emiums, c edi limi om
endo s and supplie s, o aise money om in es o s and con ac s wi h o he o ganiza ions.
38
I is expec ed ha 𝛽6𝐿𝐵𝐶𝑡 p esen s a posi i e sign, since Business C edi o deposi s a io is posi i ely
co ela ed wi h he dependen a iable.
3.9.4. TBA – Eu ibo in e es a e
TBA – EURIBOR in e es a e is he combina ion o he wo ds Eu o In e bank O e ed Ra e. Eu ibo
a es a e based on he a e age in e es a e on eu o in e bank loans by a la ge numbe o p ominen
Eu opean banks ( he Banking panel). Fo he de e mina ion o Eu ibo a es, 15 pe cen o bo h he
highes and he lowes epo ed pe cen ages a e excluded. E e y business day, a 11:00 am Cen al
Eu opean Time, Eu ibo in e es a es a e eleased and ansmi ed o all pa icipa ing pa ies and
he p ess. I is expec ed ha 𝛽7𝐸𝑈𝑅𝑡 p esen s a nega i e sign, since TBA – Eu ibo in e es a e
co ela ed wi h he dependen a iable.
3.9.5. Nominal GDP g ow h a e
GDP g ow h is one o he kay indica o s o economic heal h. I he economy is g owing, he e is less
isk o a bank ailu e. GDP ep esen s he sum (in mone a y alues) o all goods and se ices
p oduced in egion, o e a pe iod o ime. In coun ing GDP, goods and se ices a e conside ed,
excluding in e media e consump ion goods, a oiding he p oblem o double coun ing. Nominal GDP
e e s o he alue calcula ed in e ms o cu en p ices, ha is, in he yea in which he p oduc was
p oduced and ma ke ed.
In 2018, Sil a ci ed Mayes and S emmel ha ound GDP g ow h has a good p edic i e powe and a
nega i e e ec when p edic ing banks dis ess. So, i is expec ed ha 𝛽8𝐺𝐷𝑃𝑡 p esen s a nega i e
sign, since GDP g ow h is nega i ely co ela ed wi h he dependen a iable.
3.9.6. PSI 20
P ice S ock Index 20 is a index agg ega es he la ges 20 companies lis ed on Eu onex Lisbon. The
main pu pose o PSI 20 is an indica o o he e olu ion o Po uguese s ock ma ke and o suppo
he nego ia ion o u u es and op ions. The PSI 20 index has a cha ac e is ics ha i was a good
indica o o Po uguese s ock ma ke and consequen ly he Po uguese economy. I is expec ed ha
𝛽9𝑃𝑆𝐼𝑡 p esen s a nega i e sign, since he PSI 20 index is nega i ely co ela ed wi h he dependen
a iable.
3.9.7. Disposable Income G ow h
Rep esen s he amoun o money ha households ha e a ailable o spending and sa ing a e
income axes. Gene ally, a dec ease in disposable income, consequen ly he e is less money a ailable
o he same hings. I is expec ed ha 𝛽10𝐷𝐼𝐺𝑡 p esen s a nega i e sign, since he disposable income
3.9.8. Consume P ice Index
The Consume P ice Index measu es he a e o in la ion by de e mining p ice changes o a
hypo he ical baske o goods, such as ood, housing, clo hing, medical ca e, appliances, au omobiles,
and so o h, bough by a ypical household. The CPI a e used o assess p ice changes associa ed wi h
in la ion o de la ion and i is a majo concep in mac oeconomics. Banks gene ally p o i in
39
en i onmen s o in la ion, so p obabili y o a bank ailu e dec ease. I is expec ed ha 𝛽11𝐶𝑃𝐼𝑡
p esen s a nega i e sign, since he in la ion a e is nega i ely co ela ed wi h he dependen a iable.
3.9.9. Exchange a e
The exchange is he ope a ion o change one cu ency o ano he , he exchange a e is he p ice a
which his exchange is made, ha is, he alue o a cu ency in mone a y uni s o ano he cu ency. I
is expec ed ha 𝛽12𝐸𝑅𝑡p esen s a nega i e sign, since he exchange a e is nega i ely co ela ed
wi h he dependen a iable.
3.9.10. Ca bon P ice
The banking sys em is exposed o ail isks in he e en o sudden changes in ca bon p ices i i ms do
no educe hei emissions, bu he impac would be con ained wi h mo e g adual o e icien
emissions educ ions by i ms. This a iable is o analysis he exposu es o loans in Po ugal. I ca bon
p ice changes i will be impac on i ms, consequen ly his i ms ha e loans and u n an impac on
p obabili ies o de aul . I is expec ed ha 𝛽13𝐶𝑃𝑡 p esen s a posi i e sign, since he ca bon p ice a e
is posi i ely co ela ed wi h he dependen a iable.
3.10. INITIAL MODEL
Acco ding o he heo e ical basis men ioned abo e, he ollowing equa ion se es as he basis o
he model:
𝐶𝐷=𝛽1+𝛽2𝑈𝑅𝑡+𝛽3𝐿𝑅𝑡+𝛽4𝐿𝑀𝐶𝑡+ 𝛽5𝐿𝐶𝐶𝑡+ 𝛽6𝐿𝐵𝐶𝑡+ 𝛽7𝐸𝑈𝑅𝑡+ +𝛽8𝐺𝐷𝑃𝑡+𝛽9𝑃𝑆𝐼𝑡
+𝛽10𝐷𝐼𝐺𝑡+𝛽11𝐶𝑃𝐼𝑡+𝛽12𝐸𝑅𝑡+ 𝛽13𝐶𝑃𝑡
Whe e:
: ep esen he qua e ly da a pe iod de = 01/2003 ... 12/2020
𝛽1: Cons an ha ep esen s he o dina e a he o igin o he model.
𝛽2,…,𝛽13: ep esen he coe icien s associa ed wi h he espec i e a iables.
CD: C edi De aul coe icien is he dependen a iable ep esen ed by he speci ic
de aul a e index
UR: Rep esen s he unemploymen a e in Po ugal.
LR: Rep esen s he a e o loans g an ed in Po ugal
LMC: Rep esen s he a e o loans – Mo gage C edi g an ed in Po ugal
LCC: Rep esen s he a e o loans – Consume C edi g an ed in Po ugal
LBC: Rep esen s he a e o loans – Business C edi g an ed in Po ugal
40
EUR: I ep esen s he a e age in e es a e on in e bank loans in he eu o a ea.
GDP: Rep esen s he nominal alue o GDP.
PSI: Rep esen s he a e o he alue o he 20 la ges companies in Po ugal.
DIG: Rep esen s he nominal alue a e disposable income g ow h.
CPI: Rep esen s he a e o in la ion alue.
ER: Rep esen s he exchange a e agains he US dolla .
CP: Ca bon P ice a e.
3.11. SCENARIO ANALYSIS
The main objec i e o scena io analysis is o o e a lexible me hodological amewo k which can
ake in o accoun he o wa d-looking isks. I can p o ide a sys ema ic way o making s uc u ed
assump ions abou di e en possible u u es o explo e he isks. The p esen s udy, he scena io
analysis equi es hypo he ical bu plausible scena ios i clima e isks ha e impac on inancial
ins i u ions and ano he a iable.
The i s elease o clima e scena ios was in oduced in June 2020, include elemen s o bo h
ansi ion and physical isks. The p esen s udy i included ca bon dioxide emo al echnologies.
The i s phase o scena io analysis consis ed on mo o iza ion o mac oeconomic a iables s udied, as
s a ed in Pilla II, which consis s o s eng hening ex e nal supe ision o help mi iga e he isks
inhe en in he banking sys em.
The scena io analysis was based on he linea eg ession model p e iously s udied, in o de o p edic
he ou pu a iable o c edi de aul . Banco de Po ugal and ECB ha e p ojec ions o some o he
a iables s udied, and hese made p ojec ions will be used o he analysis o di e en scena ios, Banco
de Po ugal and ECB ha e some in o ma ion a ailable ha he explo e does no ha e, he asymme ic
in o ma ion. Va iables ha e no a p ojec ion in Banco de Po ugal we e p ojec ed acco ding o
his o ical da a, undamen ally in main aining he beha io and ajec o y obse ed in he a iables
o iginally epo ed by Banco De Po ugal.
41
4. RESULTS AND DISCUSSION
4.1. RESULTS ANALYSES
In p esen chap e he case s udy is p esen ed wi h he applica ion o he me hodology in he p e ious
chap e , o ganized in wo pa s: a i s pa ha consis s on measu ing he a iables ha d aw he
model, a second pa ha consis s on he de elopmen o he applica ion o he esul s o ob aining
base and s ess scena ios in he con ex o he cu en pandemic.
All da a ex ac ion and ea men we e pe o med in SPSS and Mic oso Excel.
4.1.1. P ac ical example
The model was aken om se e al sou ces o in o ma ion, such as Banco de Po ugal, S ooq and OECD.
The model o be buil is based on he coun y's his o ical da a om 2003 o he las qua e o 2020,
in o de o be able o co e a majo c isis and hus be able o make u u e p ojec ions o he cu en
si ua ion we li e due o he e ec o COVID -19.
The main goals o he analysis is he occu ence o c edi de aul by cus ome s and i s e ec on he
economy. As he e is a possible con agion e ec o c edi isk, he lack o supply (labo ) may lead o a
up u e in demand, o in he cu en si ua ion, bo h b eak simul aneously, he analysis co e s all
impo an c i e ia o he analysis, such as Unemploymen , nominal GDP, nominal disposable income
g ow h, CPI in la ion a e, psi20 index, Loans, Exchange a e, TBA - 3-mon h Eu ibo and ca bon p ice
a e.
The dis ibu ions o losses es ima ed using he model will be e lec ed in mac oeconomic e ms, in
o de o assis in he cons uc ion o policies and s a egies o isk mi iga ion in ad e se
ci cums ances.
4.1.2. Va iables
Due o he pandemic si ua ion ha Po ugal and he wo ld a e expe iencing, he clima e change , i is
necessa y o eso o some mac oeconomics a iables, in o de o obse e which o hese a iables
ha e he g ea es impac on un a o able economic en i onmen ha could lead o an inc eased isk
o c edi de aul , leading o a e y ulne able si ua ion. In his way, i becomes pe inen o analyze
he selec ed a iables, assess how hey may a ec he c edi de aul and wha a e he bes policies o
implemen .

42
The p esen s udy has a pu poses e idence o he ela ionship be ween c edi isk (dependen a iable)
and mac oeconomics a iables ha is explana o y a iables.
4.2. SELECTION AND ANALYSIS OF VARIABLES
4.2.1. Dependen a iable
The dependen a iable is he de aul c edi a e, whose alue has been aken by Banco de Po ugal’s
da abase. The de aul c edi a e is a a io be ween he amoun o c edi ha e been aken by
companies and pa icula s, bu he o al amoun o c edi a ibu ed o hese wo ca ego ies o
economic agen s a e epaymen is doub ul.
Figu e 4 p esen s he his o ic e olu ion o c edi de aul a e in Po ugal. The las in e na ional inancial
c isis was o igina ed in he USA, de i ed om he p oblems wi h housing loans, he well-known
subp ime c isis, in he summe o 2007. The Ame ican economy eached a c i ical poin in 2008 wi h
he bank up cy o Lehman B o he s, one o he main banking ins i u ions in he coun y. The e ec s o
he ecession in he Ame ican economy ha e sp ead globally, causing a sha p d op in c edi de aul .
Po ugal was s uggling wi h a s agnan economy and a ising unemploymen . Al hough Po ugal ell
in o a se ious ecession, e lec ing a c i ical poin be ween 2012 o 2015 in c edi de aul . Po ugal ell
in o a se ious ecession, e lec ing a c i ical poin be ween 2012 o 2015 in c edi de aul .
43
Figu e 2 – E olu ion o c edi de aul since 2003Q1 o (sou ce: p epa ed by he au ho wi h da a base
o Banco de Po ugal.)
4.2.2. Independen a iable
All a iables men ioned abo e a e impo an o cons uc ion model, as hey all in luence he de aul
a e in Po ugal. In his way, he model uses all a iables, such as Unemploymen Ra e (UR), Loans Ra e
(LR), Mo gage C edi (LMC), Consume C edi (LCC), Business C edi (LBC), Th ee Mou h TBA –
EURIBOR (EUR), Nominal GDP G ow h Ra e (GDP), Po ugal S ock Index 20 (PSI), Disposable Income
G ow h Ra e (DIG), Consume P ice o In la ion Ra e (CPI), Exchange Ra e (ER) and Ca bon P ice (CP).
0,00%
5,00%
10,00%
15,00%
20,00%
25,00%
30,00%
35,00%
Qua e
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
4
2
yea 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020
C edi De aul Ra e [%]
C edi De aul Ra e [%]
44
4.2.3. S a iona y Tes
The i s s ep is o analyse whe he he se ies is s a iona y o no , in o de o choose absolu e alues
o lag alues. A s a iona y se ies ci cula es be ween wo bands (a maximum and a minimum) loa ing
uni o mly a ound a midpoin – p ocess I(0). A non-s a iona y se ies has no band, since he p obabili y
o 1 exceeds i and does no luc ua e a ound a midpoin – p ocess I(1). The e a e wo cha ac e is ics
o a s a iona y se ies: hei p ope ies a e cons an and ha e ze o mean and cons an a iance. Thus,
i is necessa y o dis inguish p ocesses I(0) and I(1). S a iona y es s a e used o unde s and he ex en
o which he se ies has a endency, and hus emo e hem in o de o obse e he eal luc ua ions o
he a iable. The main objec i e is o obse e he eal luc ua ions o he a iable. The e a e se e al
es s o s a iona i y such as he Augmen ed Dickey-Fulle (ADF) and Philips-Pe on (PP) es s, Ellio ’s
ADF-GLS es s, Ro henbe g and S ock es , M es s o Ng and Pe on, KPSS es s, among o he s.
(Rod igues, 2013)
The chosen es s we e he ADF es s, de eloped by Dickey and Fulle , p io o he uni oo es s, o
ind ou whe he he obse ed ime se ies p esen a s ochas ic end o e he ime o , i on he o he
hand, he se ies p esen a de e minis ic end, wi h s a iona y luc ua ions o e ime. (Fe ei a, 2013)
The ADF model is illus a ed using he ollowing model:
𝑌𝑡=𝜙∗𝑌𝑡−1 +𝜀𝑡
whose, 𝜀𝑡~𝑁(0,𝜎2).
The main objec i e is o es ima e he alue o 𝜙. I 𝜙 =1, i means ha he se ies ha e a uni a y oo ,
he e o e is no s a iona y. Nex s ep is o manipula ed se ies in o de o e e se s a iona y and i is
consis ing o ha di e ences is manda o y. I 𝜙 ≠1 means ha se ies is le el s a iona y, i can be used
wi hou ans o ma ion o es ablish a linea eg ession wi h ano he s a iona y a iable. The e a e wo
al e na i e hypo heses o checking s a iona y:
𝐻0:𝜙=1, he e a e uni a y squa e, means, se ies is no s a iona y
𝐻1:𝜙<1, he e a e no uni a y squa e, means, se ies is s a iona y.
The p esen s udy was based on he p obabili y’s alues calcula ed in Mic oso Excel a signi icance
le el o 5%, in o de o each a conclusion ega ding he s a iona i y o he se ies. I he alue is less
han 5%, he hypo hesis 𝐻0 is ejec ed and hypo hesis 𝐻1 o se ies s a iona i y is accep ed. Appendix
on able A p esen s all esul s o ADF s a iona y es o all a iables in absolu es alues and di e en
lags. In same way o ADF es , PP es s consis s o e i y i null hypo hesis ha e a uni a y oo (𝐻0:𝜙=
1). The decision c i e ion de ines ha , i 𝑡1<𝑟𝑐𝑟𝑖𝑡, he null hypo hesis will be ejec ed, we used
S anda d C i ical Values o signi ican s a is ical le el o 5%, wi h = - 1,65.
The esul s ob ained show ha a iable Business C edi has lagged wi h ρ=0,0001, Nominal GDP has
lagged wi h ρ<0,0001, Nominal Disposable Income has lagged wi h ρ<0,0001, CPI in la ion has lagged
wi h ρ<0,0001, PSI20 has lagged wi h ρ<0,0001, Exchange Ra e has lagged wi h ρ=0,001735 and Ca bon
p ice wi h ρ<0,0001, meaning ha hese a iables ejec ed null hypo hesis and accep hypo hesis 𝐻1
se ies is s a iona i y, all absolu es alues will be used on linea eg ession. All o he a iables p esen ed
only e eal o be s a iona y a di e en lagged, and he e u n alues a e used in he es ima es.
45
Wi h he se ies ans o med in o s a iona y se ies and using le els ha ha e al eady been shown o
be s a iona y, he eg ession is es ima ed be ween he a ious endogenous and explana o y a iables.
4.2.4. Da abase desc ip ion
The da abase used s a s in Janua y 2003 and o 2021, e alua ed by qua e s.
Analyzing he se ies o he collec ed da a, i should obse e he main cha ac e is ics o cen al
endency and a iables o he s udy is dispe sion. Appendix B shows alues o he desc ip i e s a is ics
o all a iables collec ed by he absolu e alues and lagged di e ences.
Rega ding s anda d de ia ion can be obse ed ha he e is no nega i e alue, as expec ed and all
a iables ha e a low s anda d de ia ion alue, his means ha alues a e a ound he a e age wi h ew
de ia ions. The a iables wi h he highes s anda d de ia ion a e ER (Exchange a e), ha ha e a
s anda d de ia ion o 0,1244, and PSI (Po uguese S ock Index) wi h a s anda d de ia ion o 0,1111,
al hough i is no a cause o isk.
Skewness is a measu e o he symme y o a dis ibu ion. In an asymme ical dis ibu ion, a nega i e
skew indica es ha he ail on he le side is longe han on he igh , con e sely a posi i e skew
indica es he ail on he igh side is longe han on he le . Asymme ic dis ibu ions occu when
ex eme alues lead o a dis o ion o he no mal dis ibu ion. (Encyclopedia, 2021) F om he s a is ical
skewness alues ob ained, he one ha is closes o he symme ical alues o he no mal dis ibu ion
is he c edi de aul ( he alue is 0,307). As c edi de aul indica ed LR (loans a e) ( he alue is 0,281),
LMC (Mo gage c edi ) he alue is 0,307, LBC (Business C edi ) he alue is 0,331, EUR (TBA – 3 mon hs
Eu ibo ) he alue is 0,852, UR (Unemploymen a e) he alue is 0,796, DIG (Disposable Income
G ow h) he alue is 0,153, CPI (Consume P ice Index) he alue is 0,018, ER (exchange a e) he alue
is 0,1217, he a iables ha e a longe ail on he igh han on he le side. I means ha he e a e
mo e a ia ions in alues o e a pe iod o ime, e en hough hey a e low. The a iables wi h mo e
a ia ions a e EUR and UR. On he o he hand, LCC (Consume C edi ) he alue is -0,147, CP (Ca bon
P ice) is a alue o -0,673, PSI (Po ugal S ock Index) he alue is -0,693 and GDP (Nominal GDP a e) is
alue is -2,564, his means ha i has a longe le ail han he igh . This measu e indica es ha he
obse ed alues ha e emained homogeneous o e a long pe iod o ime like, o ins ance, he GDP.
Ku osis measu es whe he a se ies has peaks (peaked) o is cons an ( la ) ela i e o he alues o he
no mal dis ibu ion. In he e en ha a a iable has a e y high ku osis alue, i ends o ha e a e y
high peak alue a ound he mean and i dec eases apidly, wi h e y hea y ails. I a se ies shows lowe
ku osis alues, i ends o ha e a la op close o he mean ins ead o an acu e peak. The expec ed
alues o ku osis in a s anda d no mal dis ibu ion a e alues ha end o o a e close o ze o, in his
case all a iables a e cons an CD(-1,308), LR(-0,959), LMC(-1,119), LBC(0,280), LCC(-0,775), EUR(-
0,263), UR(-0,557), DIG(-0,044), CPI(-1,072) PSI (0,017) and ER(-0,585), wi h he excep ion o GDP
which has a peak alue o 8,439 and CP he alue is 5,104.
52
The c edi isk assessmen exe cises a e based on h ee mac oeconomic scena ios, hey include a
baseline ha e lec s he expec ed ajec o y o c edi de aul o wo s uggling scena ios.
Baseline scena io: This is he scena io ha has he e e ence and aims o cap u e he expec ed
e olu ion o economic ac i i y wi h eg ession s udied and p ojec ions by EBC and Banco de Po ugal,
called by baseline.
Scena io 1: This scena io is c ea ed causing a dec ease by 0,5 pe cen age poin s o 4 consecu i e
qua e s, alls 1 pe cen age poin o 2 consecu i e qua e s and goes down o 2 pe cen age poin s in
he las qua e o 2023 on Unemploymen a e, loans and Ca bon P ice, called by pessimis scena io.
Scena io 2: This scena io is c ea ed causing a wo sening in all 5% pe cen age poin s o 4 consecu i e
qua e s, alls 5 pe cen age poin s in he las qua e o 2023 in he same a iables o scena io 1, called
by ex eme pessimis scena io.
G aphic 1 - Analyses Scena ios - combina ion mac oeconomics ac o s wi h Cha ge O (sou ce:
p epa ed by he au ho )
The p ojec ed scena ios con i m ha he e may be a la ge inc ease in c edi de aul , he e o e
con i ming he need o apply imp o emen ac ions. G aphic 1 shows he base, pessimis and ex eme
pessimis p o ision o he 3 scena ios wi h he combina ion o he calcula ed mac oeconomic a iables
wi h he coe icien s ound esul ing in he C edi De aul alue.
F om he p e ailing in o ma ion ha is cu en ly in o ce, ega ding c edi de aul , he lag in he
escala ion o he a iables was applied and e lec s a possible inc ease in c edi de aul a e he end
o mo a o ium c edi . The ex eme pessimis scena io ale s o le els o c edi de aul ne e eached
in Po ugal be o e.
The ollowing g aphics p o ide o ecas s o he a ious mac oeconomic a iables analyzed combined
wi h he planned C edi De aul . C edi De aul is calcula ed using all indica o s pe o med in he

53
analysis o scena ios, o his eason, CD will be he same in all g aphics p esen ed, and is be ween 25%
o 26% in he upcoming yea s. Cha ge o is o conside as a loss a deb ha will p obably no be paid.
Re u ning o he pandemic si ua ion, elabo a ed p o isions a e o an inc ease o unemploymen in
Po ugal in he upcoming yea s. The cu en ly unemploymen a e has no eached e y high le els
due o policies applied in Po ugal, such as he layo , so he e is a sho all in he impac o he
employmen c isis, wi h i s peak expec ed in 2022.
Layo is he empo a y suspension o pe manen e mina ion o employmen o an employee o a
g oup o employees o a business easons, in his case, cause by a pandemic si ua ion. The e is a
signi ican dec ease o wo k in any o ganiza ion, in some cases he e is no business.
Measu es o c edi de aul ha e been implemen ed, i leads o an ex ended paymen en , in a pe iod
o ime, o banks. The e o e, he e is no sha p d op in c edi de aul . Banks con inue o g an loans,
helping o p omo e p i a e consump ion and in es men .
4.6. TESTING THE STUDY HYPOTHESIS
The p esen disse a ion had as he mean goals o s udy he c edi de aul in Po ugal and sough o
answe he esea ch ques ion: Wha is he in luence o mac oeconomic ac o s on c edi de aul in
Po ugal, du ing he managemen o he pandemic caused by COVID-19 and he clima e change c isis?
To es he hypo heses o he s udy, a conside a ion was gi en o he analysis o linea eg ession,
which was c i ical o he accep ance o ejec ion o he hypo heses p oposed in he s udy. In o de o
op imize he model we op ed o elimina ion same explana o y a iable which i is no s a ically
signi ican . Th ough his p ocedu e, he inal models a e composed o six explana o y a iables, such
as LR, LMC, UR, GDP, CPI and CP.
Hypo heses 1: The loans a e in luence nega i ely c edi de aul a e.
The p esen analyses sugges ha 96,4% o C edi De aul a ia ion may be explained by second model
o a linea ela ionship. The esul s sugges s ha coe icien s we e ob ained by linea eg ession LR
had β=-0,215 ha means loans con ibu e nega i ely o impac on ou pu a iable, mo e speci ic a
inc ease on LR o dec ease 21,5% on CD. Pea son co ela ion is con i med wi h ρ=-0,914 and he e is
no mul icollinea i y wi h VIF bellow 10. Thus alida ing he hypo hesis 1, he nega i ely in luence o
loans on C edi De aul .
The esul s collec ed go agains ou ini ial expec a ions, we can obse e ha he whole pe iod unde
analysis he momen s in which he e was a low a e o c edi de aul , he e was a g ea e supply o
c edi h ough banking ins i u ions, and in pe iods o high de aul , like he case be ween 2012 and
2016 ha o igina ed he subp ime c isis in he USA, which was e lec ed in Po ugal yea s la e , was
pa icula ly ma ked by a con ac ion in c edi supply. This pe iod was pa icula ly ma ked by a high
a e o c edi de aul , on he o he hand, his pe iod was also ma ked by a con ol on he bank's pa
in he p o ision o loans, as can be seen in g aph s. The g an ing o c edi has ad e sa ial signs on he
de aul o c edi .
54
The ECB allowed he ins i u ions o supe ise he ope a ion empo a ily wi h a lowe le el o own unds
guidance (PILLAR 2) and ha o he combined own unds ese e, and wi h liquidi y le els below he
liquidi y co e age equi emen . In his way, i is possible o ee inancial esou ces om economic
ac i i y, hus p ese ing inancial s abili y. I should be no ed ha he ECB and he Bank o Po ugal
ha e decided o ecommend banks no o dis ibu e di idends o he yea s 2019 and 2020, in o de
o p omo e hei pe o mance in inancing he economy and he capaci y o abso b po en ial losses.
(Po ugal, Financial S abili y Repo , June 2020)
Hypo heses 2: The mo gage c edi in luence de aul c edi a e.
Simila ly wi h hypo heses 1, mo gage c edi is s a is ically signi ican on model 1 and his a iable is
included on model 2. Mo gage C edi has an e ec nega i e on C edi De aul (CD) wi h a coe icien
on model 2 [𝛽3=-0,715; =-2,122; ρ=0,038], ha is meaning o each uni inc ease in Mo gage C edi ,
he e is an dec ease o 71,5 % in C edi De aul . The s a is ical is signi ican o CD is <0,001, his sugges s
ha o he a ia ion in C edi De aul can be p edic ed 96,4% by Mo gage C edi , his sugges s ha
he a iable is s a is ically signi ican . S anda dized coe icien s e lec s ha he a iable wi h he
g ea es impac on c edi de aul was Mo gage C edi . Pea son coe icien s was con i med in he same
way, wi h 𝜌 = -0,929 and p- alue=<0,0001 and he e is no mul icollinea i y wi h VIF bellow 10.
Mo gage C edi is he a iable acco ding o he model s udied, wi h he g ea es in luence on c edi
de aul , and o his eason i is an ale a iable. The compe en en i ies ha e also his a iable as
c ucial one in he o m o isk mi iga ion, o his eason hey ha e implemen ed some p e en i e
measu es. Thus alida ing he hypo hesis 2, he nega i ely in luence o loans on C edi De aul .
The Po uguese go e nmen , like o he Eu opean coun ies, de ined Dec ee-Law no. 10-J / 2020, o
Ma ch 26, wi h a e m ha will emain in o ce un il Ma ch 31, 2021, es ablishes a se o ex ao dina y
measu es o p o ec deb o s and payees:
1. The ex ension o a pe iod equal o he e m o he mo a o ium measu e, o c edi s wi h
paymen o capi al a he end o he con ac .
2. The suspension o c edi s wi h pa ial epaymen o capi al o wi h pa ial ma u i y o o he
cash bene i s, du ing he pe iod in which he measu e o capi al paymen , en s and in e es
wi h e ec i e ma u i y is in e ec un il he end o ha pe iod.
3. The p ohibi ion on he e oca ion o c edi lines con ac ed and loans g an ed in he amoun s
con ac ed a he da e o en y in o o ce o he Dec ee-Law.
Mo a o iums ep esen a undamen al measu e, which aims o econcile he con inui y o business
ac i i y a e he immedia e impac o he heal h c isis, a oiding cash low p oblems om u ning in o
insol encies, and on he o he hand, he sa egua ding o he economy's inancing capaci y by he
banking sys em, minimizing i s consump ion o capi al. (Po ugal, Financial S abili y Repo , June 2020)
The ques ion ha a ises is wi h he end o hese a ea s, he de aul o c edi can inc ease quickly, and
o ha eason, he possible impac was s udied in he s ess es . Th ough he a ec ed s udy, he
a iable ha can mi iga e hese isks is o ac on he unemploymen a iable, in o de o pa icula s o
con inue ul illing hei obliga ions.
55
Hypo heses 3: The consume c edi in luence c edi de aul a e.
Rega ding hypo hesis 3, he esul s o he s udy sugges ha he co ela ion be ween C edi De aul
and he LCC is no s a is ically signi ican . No alida ing hypo hesis 3, he in luence o consume
c edi on c edi de aul . Al hough, his esul is no consis en wi h p e ious s udies ha e e ed o
he exis ence o ela ionship be ween a iables, (Nunes, 2009 - quo ed by (Veloso, 2016), is, howe e
consis en wi h s udies ha do no con i m he exis ence o a di ec ela ionship.
Hypo heses 4: The business c edi in luence de aul c edi a e.
Rega ding hypo hesis 4, in he same way, he esul s o he s udy sugges ha he co ela ion
be ween C edi De aul and he LBC is no s a is ically signi ican . No alida ing hypo hesis 4, he
in luence o consume c edi on c edi de aul . Al hough, his esul is no consis en wi h p e ious
s udies ha e e ed o he exis ence o ela ionship be ween a iables, (Nunes, 2009 - quo ed by
(Veloso, 2016), is, howe e consis en wi h s udies ha do no con i m he exis ence o a di ec
ela ionship.
Hypo heses 5: The unemploymen a e in luence posi i ely c edi de aul a e.
The esul s ob ained om he p esen s udy he hypo heses 5 is con i ming he ini ial expec a ions o
he posi i e signals be ween a iables unemploymen and c edi de aul . Linea eg ession model
β=0,452 p esen s a g ea weigh in he ou pu a iable, c edi de aul . In he same way S anda dized
Be a on model 2, wi h all a iables, con i med ha unemploymen a e had a g ea in luence on he
c edi de aul wi h S anda dized β=0,697. The es Pea son co ela ion ca ied ou e eals a s ong
co ela ion o 𝜌 = 0,797 wi h p- alue=0,0001, his means ha he inc ease in he unemploymen a e
is ela ed o c edi de aul . This leads o an u gen need o mi iga e he possible isks o high
unemploymen and o con ol high le el o c edi de aul is o ake p e en i e measu es o con ol he
unemploymen a e.
P esen li e a u e men ion he unemploymen a e is ano he wa ning signal a iable o he inancial
si ua ion o a coun y. When unemploymen a e inc eases ansla es in o a dec ease in expec ed
ea nings, as he e a e ewe people con ibu ing o a coun y's weal h. Consequen ly, he e will be less
agg ega e demand, esul ing in a c edi de aul o indi iduals who ha e hei condi ional income and
o companies. The expec ed sign be ween he c edi de aul a iables and unemploymen a e a e
posi i e. Wi h he de e io a ion o economic and inancial condi ions, inancial agen s condi ion o
access o c edi .
The Po uguese go e nmen , like o he go e nmen s, has p omo ed layo schemes h ough, which i
seeks o main ain employmen links and con ibu ing o a p og essi e esump ion o economic ac i i y.
In his way i is possible o ealize ha his lay-o scheme may ha e been a good, adop ed measu e
o he p og essi e e u n o economic ac i i y.
Hypo heses 6: The 3-mon h Eu ibo in e es a e in luence c edi de aul a e.
Rega ding hypo hesis 6, On model 1 loans β=0,201 wi h p- alue=0,247, i is meaning ha i is no
s a is ically signi ican o le el 1%. Pea son co ela ion ein o ces he same idea, wi h a low posi i e
56
co ela ion be ween TBA-Eu ibo 3 mon hs and De aul C edi . The esul s o he s udy sugges ha
he co ela ion be ween C edi De aul and he EUR is no s a is ically signi ican . No alida ing
hypo hesis 6, he in luence o 3-mon h Eu ibo in e es a e on c edi de aul . Al hough, his esul is
no consis en wi h p e ious s udies ha e e ed o he exis ence o ela ionship be ween a iables,
Ci ed by Cha es, is, howe e consis en wi h s udies ha do no con i m he exis ence o a di ec
ela ionship.
The in e es a e has an essen ial ole, mone a y au ho i ies can manipula e he isk o s abiliza ion
pe o mance. The in e es a e is inc eased, he g ea e he isk o de aul , as bo owe s will ha e o
pay mo e o he same loan, esul ing in a disposable income dec ease.
The coun ies ha adhe ed o Eu opean cu ency, known as he eu o a ea, as in he case o Po ugal,
he issuance o bankno es is he esponsibili y o he Eu opean Cen al Bank, which is esponsible o
mone a y policy, in pa icula he con ol o he g ow h o money supply. The Cen al Bank inc eases
o dec eases he in e es a e as a measu e o con ol o he money supply, when in e es a e
inc ease, i is meaning c edi is mo e expensi e, consequen ly c edi o s ind i mo e di icul o mee
hei obliga ions. On he o he hand, when in e es a e dec eases economic agen s look o o he
al e na i es o he applica ion o hei deposi s. Fo his eason, he ECB con ols he in e es a e
acco ding o he o he economic a iables o esea ch a balance in economy.
The esul s ob ained go agains ini ial expec a ions, e lec ing an opposi e e ec on he ela ionship
be ween TBA-Eu ibo and c edi de aul . This opposi e e ec is explained by he p e en i e measu es
applied by he Eu opean Cen al Bank, since he way o mi iga e he isks o de aul is h ough
measu es o educe he in e es a e.
Hypo heses 7: Nominal GDP g ow h a e in luence nega i ely c edi de aul a e.
The esul s sugges s ha nominal GDP has lagged wi h ρ<0,0001, meaning ha hese a iables ejec ed
null hypo hesis and accep hypo hesis 𝐻1 se ies is s a iona i y, di e en lag is used on linea eg ession.
The esul s sugges s ha coe icien s we e ob ained by linea eg ession GDP had β=-0,149 ha means
GDP con ibu e nega i ely o impac on ou pu a iable. Pea son co ela ion is con i med wi h ρ=-
0,053, indica ing a weak co ela ion and he e is no mul icollinea i y wi h VIF bellow 10. The p esen
analyses sugges ha 96,4% o C edi De aul a ia ion may be explained by second model o a linea
ela ionship. On model 2, goes agains ini ial expec a ions wi h con adic o y signals. Rein o cing he
idea con eyed in he sub-chap e speci ica ion o he model a iable, his can be explained by he
e ec o c edi de aul on la e yea s, in which he e was a g ea e de aul o c edi , be ween 2012 and
2016, p og ess in economic GDP s a ed o make p og ess. Since, acco ding o he his o ical da a
analyzed, he e ec s o a shock can ake abou 2 yea s o be e lec ed. The GDP had a long pe iod o
ime wi h nega i e alues, be ween 2008 (con agious e ec o he subp ime c isis) and 2013. The
e ec on he c edi de aul a iable only wo sened be ween 2012 and 2016. This may explain he
posi i e signs be ween he a iables, despi e ha , GDP has li le impac on he ou pu a iable due o
he ime lag ha he impac on GDP has on he a iable dependen on c edi de aul .
The dec ease in GDP is due o he pandemic si ua ion COVID-19, cha ac e ized by he in e ac ion o
supply and demand shocks, oge he wi h he high deg ee o unce ain y abou how he economic
si ua ion will e ol e, accompanied by a all in p oduc i i y, due o he closu e pa ial o o al o
companies. A he same ime, consump ion and in es men le els we e also a ec ed, wi h nega i e
consequences on job sea ch.
57
Con ex ualizing he economic heo y ha ansla es in o a phase o expansion, he e is a dec ease
c edi de aul . This expansion phase is cha ac e ized by a endency o economic agen s o bo ow,
because he e is mo e disposable income a p esen . Bu his expansiona y phase usually b ings a
consequen ecession phase, called economic cycles. Second phase o ecession is e i ied by a end
owa ds a c edi de aul inc ease. Fo his eason, he heo y explains ha he e is a nega i e
associa ion be ween c edi isk and he GDP g ow h a e.
In he coming yea s, GDP is expec ed o eco e due o he e olu ion o global p oduc i i y, leading o
an inc ease in expo s. This scena io is based on he non-adop ion o con ainmen measu es.
Thus alida ing he hypo hesis 7, he nega i ely in luence o GDP on C edi De aul .
Hypo heses 8: The P ice S ock Index o he bes wen y companies in Lisbon in luence c edi de aul
a e.
Rega ding hypo hesis 8, he esul s o he s udy sugges ha he co ela ion be ween C edi De aul
and he PSI is no s a is ically signi ican . No alida ing hypo hesis 8, he in luence o P ice S ock Index
on c edi de aul . The Since he coe icien ob ained h ough linea eg ession was nega i e, wi h
β=0,013 o model 1 and ρ=0,047, i means ha PSI and CD had a weak co ela ion. Al hough he e is
a weak co ela ion be ween PSI 20 and ou pu a iable, he s ock p ice index allows o know he
in luence o he inancial condi ions o companies lis ed on he Lisbon s ock exchange on c edi isk.
An inc ease in he s ock ma ke index can ansla e in o good inancial heal h o lis ed companies,
which can con ibu e o educing he isk o c edi de aul . The heo e ical poin o iew is no he
expec ed ela ionship o he a iables, o a posi i e sign be ween c edi de aul and PSI20.
Hypo heses 9: The nominal Disposable Income g ow h in luence nega i ely c edi de aul a e.
Rega ding hypo hesis 9, he esul s o he s udy sugges ha he co ela ion be ween C edi De aul
and he DIG is no s a is ically signi ican . The es o he co ela ion be ween he a iables con i ms
ha he e is a nega i e weak co ela ion be ween he wo ac o s o 𝜌 = -0,090, meaning when inc ease
disposable income will lead o a dec ease in C edi De aul . DIG had a β=0,019. The e o e, when he e
a e le els o sa ings on he pa o indi iduals and companies, in si ua ions wi hou liquidi y agen s can
use sa ings o ul il obliga ions, o his eason, an inc ease in he inc ease in DIG has a dec easing
impac on c edi de aul .
The disposable income o amilies is also expec ed o all, because o he go e nmen measu es
applied, speci ically he lay-o sys em in which he wo ke o e s an income o 100%, as well as, o he
sel -employed wo ke s, in o de o main ain nominal disposable income le el o amilies. O he cases
a e COVID pa ien s, who, in con as o indi iduals in p ophylac ic isola ion who o e hei income in
he o de o 100%, COVID pa ien s ha e hei sala y in he o de o 55%, in he i s 30 days o he
disease (Social, 2020). Consequen ly, he e is a d op in pu chasing powe . Likewise, he e is no
p o ision o any go e nmen policy o deal wi h he loss o income.
Disposable income is limi ed by bo owing, since pu chasing powe is los o mee commi men s.
Disposable income exp esses he alue a ailable, his means ha a high alue ansla es in o g ea e
sa ings o consume s. Lowe le els o sa ings mean g ea e isks o de aul .

58
Hypo heses 10: The Consume P ice Index in luence posi i ely c edi de aul a e.
The p esen analyses sugges ha 96,4% o C edi De aul a ia ion may be explained by second model
o a linea ela ionship. The esul s sugges s ha coe icien s we e ob ained by linea eg ession CPI
had β=-0,762 ha means CPI con ibu e nega i ely o impac on ou pu a iable, mo e speci ic a
dec ease on CPI o inc ease 76,2% on CD. Pea son co ela ion is con i med wi h ρ=-0,395 and he e is
no mul icollinea i y wi h VIF bellow 10. Thus alida ing he hypo hesis 10, he nega i ely in luence o
CPI on C edi De aul .
Rega ding he in la iona y impac on c edi isk, om a heo e ical poin o iew, in la ion occu s when
he e is a pe sis en inc ease in he p ices o goods and se ices wi hou a co esponding inc ease in
he le el o p oduc ion. When he e is an inc ease in in la ion in he economy, mone a y egula o s
accompany he inc ease in in e es a es, as a con ac iona y measu e o con ol in la ion. This
measu e, as a gene al ule, leads o an inc ease in he cos o bo owing. (Yahaya & Oni, 2016) Despi e
his, Cas o ci ed by (Rod igues, 2013) says ha a highe in la ion a e can make deb se ice easie by
educing he eal alue o loans in o ce. The signal be ween he CPI and he c edi de aul isk is
inde e mina e om a heo e ical poin o iew, in his pa icula case he signal is nega i e.
Hypo heses 11: The exchange a e in luence c edi de aul a e.
Rega ding hypo hesis 11, he esul s o he s udy sugges ha he co ela ion be ween C edi De aul
and he ER is no s a is ically signi ican . No alida ing hypo hesis 11, he in luence o exchange a e
on c edi de aul . Al hough, his esul is no consis en wi h p e ious s udies ha e e ed o he
exis ence o ela ionship be ween a iables, he e ec i e eal exchange a e is he measu e o he
Po uguese economy's compe i i eness han a ou side wo ld. Theo e ically, a dec ease in he
exchange a e ep esen s a dep ecia ion o he local cu ency, ansla ing in o mo e compe i i e goods
and se ices p oduced in Po ugal, consequen ly he e is g ea e income o ul il obliga ions.
Al hough, on model 1 i can be e i ied wi h heo ical li e a u e, he inc ease o 1,4% on exchange a e
dec ease on CD, wi h β=-0,014. Despi e o hypo hesis being e i ied; i is concluded i is no s a is ically
signi ican o c edi de aul .
Hypo heses 12: The e is a ela ionship be ween c edi and mac oeconomics a iables.
Rega ding o hypo heses 12, he esul s o model 2 sugges an imp o emen in he quali y i same
measu es is o applied wi h de aul ing cus ome s, such as LR, LMC, UR, GDP, CPI and CP.
Hypo heses 13: The ca bon p ice index in luence c edi de aul a e.
Rega ding hypo hesis 13, he esul s o he s udy sugges ha he co ela ion be ween C edi De aul
and he CP is no s a is ically signi ican . No alida ing hypo hesis 13, he in luence o ca bon p ice on
c edi de aul . Al hough, his esul is no consis en wi h p e ious s udies ha e e ed o he
exis ence o ela ionship be ween a iables, he clima e change is e y impo an (ECB, 2021). Fo his
eason, CP was es ima ed o model 2. The esul s sugges ha inc ease on Ca bon P ice, will be a
inc ease on 1,7% C edi De aul .
59
In iew o he hypo heses p esen ed, i is necessa y o analyze he main objec i e o he
in es iga ion. Check h ough he assessmen and managemen model o c edi isk, Wha is he
in luence o mac oeconomic ac o s on c edi de aul in Po ugal, du ing he managemen o he
pandemic caused by COVID-19 and he clima e change c isis?
A e he s udy ca ied ou , i was ime o e lec ion and discussion, in which he ocus o he wo k
de eloped is ela ed o he economic impac on inancial sec o , speci ically in c edi de aul , bu
which s a ed in heal h, wi h he con inemen measu es o con ol he ansmission o he i us.
The e ha e been o he economic luc ua ions in his o y, bu he cu en c isis equi es new
ins umen s and ac ions, since in Po ugal we had wo con inemen s. The companies had o eadjus ,
and hose ha ailed o do so ha e high le els o indeb edness, consequen ly, he insol ency o he
companies. In companies he e is a lo o human capi al ha has no been ealloca ed, some
ine i ably wen o he layo , o he s we e en olled in he unemploymen und. S ill, he e a e sec o s
such as ou ism and ai anspo ha ha e g ea e di icul y in eadjus ing business, bu he e a e
c ea i e solu ions o he sec o s in ques ion. Fo example, eadjus ing ooms o ecei e
elecommu ing employees a mo e a o dable p ices, ensu ing daily meals, ei he o gues s o wi h
wo ke s om a ce ain company, making ooms a ailable o people on he on lines, examples o
ill he weak demand.
As i was e i ied, he measu es o he i s con inemen led o a d op in GDP o a ound 16% in he
qua e co esponding o he i s con inemen . a e y se ious eason o ale ing he inancial sec o .
The e a e s udies ha indica e ha he wo ld economic c isis is mo e se ious han he g ea
dep ession o 1930. The measu es o social con inemen , he es ic ions o ci cula ion and he loss
o wo king hou s a e limi ing he global p oduc ion, he chains global ade and se ices sec o .
The Eu opean Cen al Bank app o ed a p og am called he Pandemic Eme gency Pu chase P og am
ha was launched o comba he economic e ec s o he pandemic, such as he case o loan de aul .
The cu en economic c isis was ma ked by he all in agg ega e demand, bu which has an impac on
he supply side. Consequen ly, i d agged he co po a e ab ic, leading o signi ican billing losses,
inc easing liquidi y p oblems. These losses on he supply side a e e lec ed in unemploymen , loss o
income, e ac ion in demand, bank up cies and closu es, inancial di icul ies and he sha p ise in
unce ain y and isk.
The go e nmen 's esponse was, in he i s ins ance, o comba he heal h eme gency, hen by he
deploymen o social suppo aimed a mi iga ing he i s ele an impac s on income and
employmen and, om hen on, by he mobiliza ion o esou ces aimed a sus aining ma ke s,
companies and he economic in e en ion o he S a e i sel . This new con ex equi es a lo o
esilience om he business ab ic, as well as adap ing o his new way o being, in which ace- o- ace
wo k gi es way o elewo king. Realloca ing human capi al in ol es p o iding mo e se ices,
p o iding aining, s eng hening he business o digi al comme ce and, inally, eaching he inal
consume h ough home deli e ies.
One way o p e en c edi de aul is o ensu e liquidi y on he pa o companies and jobs, on he
pa o indi iduals, as s udied, is one o he a iables wi h he g ea es impac acco ding o ou
model. The ac ha he e is a accine agains he new co ona i us has inc eased con idence le els,
bu since he u u e is no known, i his will become he new no mal o e e yday li e, he e is an
eme gency o adap a ion. I his adjus men is no made, we will be acing a e y se ious c isis, wi h
e ec s on c edi de aul s ne e el be o e.
60
61
5. CONCLUSIONS
In his disse a ion, a s udy was execu e o he possible ela ionship be ween c edi isk and
a iables mac oeconomics in Po ugal esul ing om he pandemic. Risk is pa o he g an ing o
c edi , bu his should be minimized as much as possible, so ha lending ins i u ions ake ca e.
Howe e , i is necessa y o ake in o accoun c edi policies and mac oeconomic a iables. The
s a is ical in e ence based on linea eg ession model, highligh ed a se ies o esul s ha allow us o
d aw a conclusion abou he e olu ion o c edi isks in ela ion o he o he mac oeconomic
a iables in he Po uguese economy, whe e in he pe iod om 2003Q1 o 2021Q3, wo eg essions
we e es ima ed o he dependen a iable unde s udy.
Wi h he p esen esea ch wo k i was possible o answe he scien i ic p oblem ini ially men ioned,
he gene al and speci ic objec i es, as well as he hypo hesis. E alua ing each speci ic objec i e and
he p oposed main one:
The main objec i e p oposed was o iden i y he mac oeconomic a iables ha a ec c edi de aul .
The objec i e was ul illed. A he mac oeconomic le el, he main de e minan s o economic ac i i y
measu es s and ou : loans, mo gage c edi , unemploymen a e, GDP, consume p ice index and
ca bon p ice we e he a iables used in he analysis o he scena io, as hey a e he a iables wi h he
g ea es impac on he dependen a iable and s a is ically signi ican .
The p esen wo k had as i s i s speci ic objec i e o s udy he exis ing li e a u e ega ding c edi
isk, s ess es ing, iden i ica ion o he main mac oeconomic a iables ha a ec he economy. In
his way, we we e able o p opose a me hodology o building a s ess es in he Po uguese
economy, wi h a g ea e ocus on p e en ing c edi de aul . This was he main ocus, since all he
p e ious inancial c ises s a ed wi h c edi de aul and had a con agious e ec on he es o he
economy. Likewise, he s udied li e a u e con ibu ed o he cons uc ion o he s ess es , so ha
he me hodology would ake in o accoun he Basel ag eemen s in he connec ion be ween
mac oeconomic and c edi isk ac o s.
The e is an inc easing need o he c ea ion o isk con ol and mi iga ion ins umen s in an economy,
in o de o unde s and, p edic , manage and measu e isks in i . As we a e acing a si ua ion ne e
be o e expe ienced, COVID-19, hese ins umen s a e aluable in he pe o mance o co ec i e
measu es in u u e e en s.
The second speci ic objec i e was o c ea e a model ha de ec s he de aul a e. The objec i e was
achie ed h ough he explo a o y desc ip i e esea ch model wi h he quan i a i e app oach as a
esea ch s a egy, i was possible o collec mac oeconomic da a and om he desc ip i e s a is ics,
namely he analysis o mul iple linea eg ession, i was possible o achie e his objec i e.
The cu en si ua ion did no s a wi h c edi de aul , bu h ough he analysis o he a ious
mac oeconomic a iables, he objec i e is o p e en his si ua ion om happening. Thus, he s udy
made i possible o conduc a policy analysis on he e ec o changes in mac oeconomic isk ac o s.
The hi d objec i e was o es he model and check i s a iables. I was concluded ha he model
has a iables acco ding o he s udied li e a u e, such as he loans, mo gage c edi , unemploymen
a e, GDP, consume p ice index and ca bon p ice a e ela ed o c edi de aul . The emaining
mac oeconomic a iables s udied canno be concluded.
68
SUMMARY OUTPUT LCC
Reg ession S a is ics
Mul iple R 0,53479
R Squa e 0,286
Adjus ed R Squa e 0,2656
S anda d E o 0,013782
Obse a ions 73
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,005326 0,002663 14,01964 7,58E-06
Residual 70 0,013296 0,00019
To al 72 0,018622
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep 0,000495 0,001803 0,274334 0,784636 -0,0031 0,004091 -0,0031 0,004091
Lagged Consume C edi -0,04639 0,024733 -1,87582 0,06485 -0,09572 0,002934 -0,09572 0,002934
Di e en Lagged Consume C edi 0,473545 0,10124 4,677461 1,37E-05 0,271629 0,675462 0,271629 0,675462
SUMMARY OUTPUT LBC
Reg ession S a is ics
Mul iple R 0,62883
R Squa e 0,395427
Adjus ed R Squa e 0,369141
S anda d E o 0,005891
Obse a ions 49
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,001044 0,000522 15,04336 9,4E-06
Residual 46 0,001596 3,47E-05
To al 48 0,00264
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep -0,00064 0,000845 -0,75455 0,454362 -0,00234 0,001064 -0,00234 0,001064
Lagged Business C edi -0,15291 0,036634 -4,17406 0,000132 -0,22665 -0,07917 -0,22665 -0,07917
Di e en Laged Business C edi 0,41214 0,123997 3,323797 0,001749 0,162548 0,661733 0,162548 0,661733

69
Reg ession S a is ics UR
Mul iple R 0,659047
R Squa e 0,434342
Adjus ed R Squa e 0,418181
S anda d E o 0,005243
Obse a ions 73
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,001478 0,000739 26,87488 2,18E-09
Residual 70 0,001924 2,75E-05
To al 72 0,003402
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep 0,002298 0,001961 1,172056 0,245148 -0,00161 0,006209 -0,00161 0,006209
Lagged Unemploymen -0,02442 0,019249 -1,26842 0,208849 -0,06281 0,013975 -0,06281 0,013975
Di e en e Lagged Unemploymen 0,465432 0,064718 7,191682 5,58E-10 0,336356 0,594508 0,336356 0,594508
SUMMARY OUTPUT GDP
Reg ession S a is ics
Mul iple R 0,872981
R Squa e 0,762096
Adjus ed R Squa e 0,755201
S anda d E o 0,017412
Obse a ions 72
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,067013 0,033506 110,5167 3,06E-22
Residual 69 0,020919 0,000303
To al 71 0,087932
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep 0,001685 0,002053 0,820877 0,414543 -0,00241 0,00578 -0,00241 0,00578
Lagged GDP -0,37325 0,055931 -6,67337 5,17E-09 -0,48483 -0,26167 -0,48483 -0,26167
Di e en e Lagged GDP 0,62154 0,044767 13,88397 1,17E-21 0,532232 0,710847 0,532232 0,710847
70
SUMMARY OUTPUT DIG
Reg ession S a is ics
Mul iple R 0,980487
R Squa e 0,961354
Adjus ed R Squa e 0,960234
S anda d E o 0,01801
Obse a ions 72
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,55673 0,278365 858,2272 1,8E-49
Residual 69 0,02238 0,000324
To al 71 0,57911
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep 0,045443 0,005533 8,212873 8,16E-12 0,034404 0,056481 0,034404 0,056481
Lagged Nominal Disposible Income -0,53214 0,059734 -8,90852 4,38E-13 -0,65131 -0,41298 -0,65131 -0,41298
Di e en e Lagged Nominal Disposible Income
0,619524 0,018397 33,67536 1,46E-44 0,582823 0,656225 0,582823 0,656225
SUMMARY OUTPUT CPI
Reg ession S a is ics
Mul iple R 0,674985
R Squa e 0,455605
Adjus ed R Squa e 0,440051
S anda d E o 0,004399
Obse a ions 73
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,001134 0,000567 29,29153 5,71E-10
Residual 70 0,001355 1,94E-05
To al 72 0,002488
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep 0,001681 0,000761 2,209063 0,030445 0,000163 0,003199 0,000163 0,003199
Lagged Consume P ice Index -0,13774 0,037863 -3,63781 0,000522 -0,21325 -0,06222 -0,21325 -0,06222
Di e en e Lagged Consume P ice Index 0,477734 0,075664 6,313867 2,17E-08 0,326826 0,628641 0,326826 0,628641
71
Reg ession S a is ics PSI
Mul iple R 0,942222
R Squa e 0,887782
Adjus ed R Squa e 0,884432
S anda d E o 0,050868
Obse a ions 70
ANOVA
d SS MS F
Signi icance F
Reg ession 2 1,371541 0,68577 265,0257 1,5E-32
Residual 67 0,173367 0,002588
To al 69 1,544907
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep -0,00501 0,006112 -0,81938 0,415477 -0,01721 0,007191 -0,01721 0,007191
Lagged PSI20 -0,55533 0,061111 -9,08711 2,67E-13 -0,6773 -0,43335 -0,6773 -0,43335
Di e en Lagged PSI20 0,594371 0,025817 23,0228 1,55E-33 0,542841 0,645901 0,542841 0,645901
SUMMARY OUTPUT LR
Reg ession S a is ics
Mul iple R 0,505989
R Squa e 0,256024
Adjus ed R Squa e 0,234768
S anda d E o 0,008214
Obse a ions 73
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,001625 0,000813 12,04455 3,2E-05
Residual 70 0,004723 6,75E-05
To al 72 0,006348
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep 0,000344 0,001059 0,324959 0,746181 -0,00177 0,002456 -0,00177 0,002456
Lagged Loans -0,04996 0,022095 -2,26097 0,026871 -0,09402 -0,00589 -0,09402 -0,00589
Di e en Lagged Loans 0,464117 0,113512 4,088686 0,000114 0,237723 0,69051 0,237723 0,69051
72
SUMMARY OUTPUT ER
Reg ession S a is ics
Mul iple R 0,651539
R Squa e 0,424504
Adjus ed R Squa e 0,408061
S anda d E o 0,039336
Obse a ions 73
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,079894 0,039947 25,81707 3,99E-09
Residual 70 0,108312 0,001547
To al 72 0,188207
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep 0,033173 0,010756 3,084165 0,002921 0,011721 0,054625 0,011721 0,054625
Lagged Exchange Ra e -0,12639 0,038237 -3,30549 0,001498 -0,20266 -0,05013 -0,20266 -0,05013
Di e en Lagged Exchange Ra e 0,470453 0,077809 6,046243 6,49E-08 0,315268 0,625639 0,315268 0,625639
SUMMARY OUTPUT TBA
Reg ession S a is ics
Mul iple R 0,490641
R Squa e 0,240729
Adjus ed R Squa e 0,219036
S anda d E o 0,002909
Obse a ions 73
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,000188 9,39E-05 11,09685 6,51E-05
Residual 70 0,000592 8,46E-06
To al 72 0,00078
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep -5,3E-05 0,000425 -0,12371 0,901902 -0,0009 0,000795 -0,0009 0,000795
Lagged TBA - 3 mon hs Eu ibo -0,03049 0,021996 -1,38634 0,170044 -0,07436 0,013376 -0,07436 0,013376
Di e en Lagged TBA - 3 mon hs Eu ibo 0,477281 0,110621 4,314559 5,15E-05 0,256654 0,697908 0,256654 0,697908
73
8.2. APPENDIX B – DESCRIPTIVE STATISTICS
8.3. APPENDIX C – MODEL SUMMARY
8.4. APPENDIX D – ANOVA
SUMMARY OUTPUT CP
Reg ession S a is ics
Mul iple R 0,966597
R Squa e 0,93431
Adjus ed R Squa e 0,932378
S anda d E o 0,026918
Obse a ions 71
ANOVA
d SS MS F
Signi icance F
Reg ession 2 0,700789 0,350395 483,5819 6,24E-41
Residual 68 0,049272 0,000725
To al 70 0,750061
Coe icien s
S anda d E o
S a P- alue
Lowe 95%
Uppe 95%
Lowe 95,0%
Uppe 95,0%
In e cep 0,007775 0,003249 2,392771 0,019489 0,001291 0,014259 0,001291 0,014259
Lagged Ca bon P ice -0,70389 0,055409 -12,7035 1,27E-19 -0,81446 -0,59333 -0,81446 -0,59333
Di e en Lagged Ca bon P ice 0,625814 0,020207 30,97026 8,09E-42 0,585491 0,666136 0,585491 0,666136

74
8.5. APPENDIX E – COEFFICIENTS
8.6. APPENDIX F -CORRELATIONS
75
8.7. APPENDIX G – DESCRIPTIVE STATISTICS (MODEL 2)
8.8. APPENDIX H – MODEL SUMMARY (MODEL 2)
8.9. APPENDIX I – ANOVA (MODEL 2)
8.10. APPENDIX J – COEFFICIENTS (MODEL 2)
76
8.11. APPENDIX L – CORRELATIONS (MODEL 2)
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