Resilience and asset pricing in COVID-19 disaster

Daadmeh , Elham
A icle
Resilience and asse p icing in COVID-19 disas e
Economies
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Sugges ed Ci a ion: Daadmeh , Elham (2025) : Resilience and asse p icing in COVID-19 disas e ,
Economies, ISSN 2227-7099, MDPI, Basel, Vol. 13, Iss. 5, pp. 1-35,
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Ci a ion: Daadmeh , E. (2025).
Resilience and Asse P icing in
COVID-19 Disas e . Economies,13(5),
123. h ps://doi.o g/10.3390/
economies13050123
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A icle
Resilience and Asse P icing in COVID-19 Disas e
Elham Daadmeh
Depa men o Economics and Managemen “Ma co Fanno”, Uni e si y o Padua, 35123 Pado a, I aly;
[email p o ec ed]
Abs ac : The COVID-19 pandemic po en ially a ec ed s ock p ices in wo non-mu ually
exclusi e ways: discoun a es and cash lows. This pape ocuses on he la e and analyzes
i h ough he lens o an asse -p icing model. I shows how wo kplace esilience and
inancial esilience in e ac ed and signi ican ly a ec ed asse p ices. The model-based equi y
p emium inc eases wi h he p obabili y o a disas e . The esul s sugges he signi ican
ampli ica ion o wo kplace esilience by inancial esilience. Speci ically, he di idend
g ow h o low- esilience i ms is signi ican ly mo e esponsi e o wo kplace lexibili y and
su e s mo e se e ely han ha o high- esilience i ms.
Keywo ds: inancial esilience; wo kplace esilience; dynamic unc ional p incipal
componen s; Ma ko swi ching; COVID-19 disas e ; equi y p emium
1. In oduc ion
COVID-19 has p o oundly a ec ed he economy and induced emendous unce ain y
in he inancial ma ke s. Go e nmen s adop ed di e en ypes o social dis ancing policies
o con ol he sp ead, especially in he i s wa e and he e e pe iod o COVID (Feb ua y
o Ap il 2020). These social dis ancing ules and lockdowns e ec i ely in luenced he
wo king en i onmen and i ms’ pe o mance (Ko en & Pe ˝o,2020, among o he s). The as -
g owing li e a u e asse s ha i ms wi h ewe labo cons ain s in he lockdown- es ic ed
si ua ion ea u ed be e pe o mance (B e sche e al.,2020), as i ms wi h mo e lexibili y
in hei wo k o ce a e expec ed o be less inancially ulne able in such si ua ions, since
hey a e less likely o ace addi ional cos s due o lockdowns and social dis ancing ules.
Ko en and Pe ˝o (2020) p opose di e en dimensions o he i ms’ wo kplace lexibili y ha
played an impo an ole in hei cos o p oduc ion, as well as he luc ua ions in asse
p ices in esponse o he COVID-19 shock (Pagano e al.,2023).
In heo y, COVID-19 can a ec s ock p ices h ough wo non-mu ually independen
channels: discoun a es and cash lows. Pagano e al. (2023) ocus mainly on he impac o
he inc ease in pe cei ed isk on expec ed excess e u ns ( i s channel). Back o he s o y o
COVID, indus ies saw massi e business dis up ion due o social dis ancing and lockdowns
as a consequence o he pandemic, which a ec ed he cos o p oduc ion and especially
he ou pu o i ms wi h less lexibili y in hei wo kplace. In such a u bulen ma ke ,
conse a i e in es o s p ima ily ocus on he p ice o an equi y claim o he ou pu o
such i ms as isky asse s— ha is, he expec ed u u e cash lows. Daadmeh (2024) shows
ha isks ela ed o he wo king en i onmen o a company, including he impac o he
communica ion mode, eamwo k, and physical p esence, o which a company is exposed,
can c ea e he e ogenei y in expec ed cash lows. Acco ding o S ulz (2025), managing such
isks as consequences o he COVID pandemic c isis can po en ially a ec he alue o
i ms. This pape concen a es on he second channel and, in a no el wo k, quan i ies
expec ed cash lows no jus o ill he gap in he isk managemen li e a u e, bu o show
Economies 2025,13, 123 h ps://doi.o g/10.3390/economies13050123
Economies 2025,13, 123 2 o 35
how he impac o COVID-19 and co po a e esilience can ca y o e om cash lows o
expec ed e u ns. The cha ac e iza ion o esilience he e ogenei y in expec ed cash low
sheds ligh on how his pape b idges a gap and links he eal pa o he economy, whe e
he exogenous COVID-19 shock o igina ed, o he inancial ma ke .
This pape analyzes he asse -p icing implica ions o he COVID-19 c isis, including
i s impac on he economy and i ms’ p oduc ion cos s, in he con ex o a model wi h
(i) a ic i ious ep esen a i e in es o wi h Eps ein–Zin–Weil p e e ences, who may p e e
an ea ly esolu ion o unce ain y in disas e s
1
; and (ii) an exogenous di idend s eam
sensi i e o he consequences o he COVID-19 disas e and o i s con ac iona y e ec s on
he eal pa o he economy. This s udy conside s he c oss-sec ional ime- a ying impac
o COVID-19 on he di idend s eam as he in e ac ion o wo componen s: he c oss-
sec ional i m-le el impac o wo kplace esilience and he ime- a ying impac o agg ega e
economic con ac ion, as a con ol o he mac o ime e ec o COVID-19. Speci ically, i
shows ha he di idend g ow h o low-wo kplace- esilience i ms is signi ican ly mo e
sensi i e o wo kplace esilience and su e s mo e se e ely han ha o high-wo kplace-
esilience i ms.
Howe e , he impac o co po a e inancials was qui e complex du ing he
COVID-19
ou b eak. Fi ms s a ed aising capi al jus because o cash low d y-up ea s o o
s eng hen hei abili y o o e come di icul ies du ing he i s wa e. Meanwhile, he
p o ided c edi , especially in small i ms, could a ec he capi al s uc u e and inc ease
le e age. Consequen ly, he inancial cha ac e is ics o i ms, such as capi al s uc u e and
liquidi y, also played an impo an ole in he pe o mance o i ms and we e conside ably
in luenced by a wide ange o policies adop ed in esponse o COVID-19, om co po a e
policies o public policies, including bank-loan gua an ees and addi ional mi iga ion pack-
ages, o example, he Paycheck P o ec ion P og am, PPP loans (Fahlenb ach e al.,2020;
Pagano & Zechne ,2022). This sugges s ha hese cha ac e is ics may ha e also con ibu ed
o ampli ying he deg ee o co po a e esilience and, as a esul , he esponse o asse p ices
(Daadmeh ,2024).
Some ecen a icles ha e shed ligh on he impac o co po a e inancial ampli ica ion
on asse p ices du ing COVID-19 pe iod (Daadmeh ,2024;Ramelli & Wagne ,2020) and
ha e ound signi ican he e ogenei y in esilience in expec ed e u ns by in oducing a
new “composi e inancial esilience” index ha con ains bo h wo kplace lexibili y and
“ inancial-based esilience” (Daadmeh ,2024). The no el y o his pape lies in he ac ha
i p o ides a simple example as e idence o he ampli ica ion e ec and shows ha c oss-
sec ional and ime- a ying co po a e inancials can po en ially ampli y he o e all e ec o
exogenous consequences o COVID-19, consis en wi h he e idence ha be e - inanced
i ms be o e and du ing COVID-19 can be e o e come he side e ec s o lockdown and
he associa ed mi iga ion o COVID es ic ions (Daadmeh ,2024;Fahlenb ach e al.,2020).
Then, i quan i ies “ inancial esilience” o cap u e he oo p in s o he impac o a wide
ange o di e en policies on he inancial s a us o i ms.
This pape p oposes a new asse -p icing model wi h COVID-19 disas e embedding
wo kplace esilience and inancial esilience o in es iga e and ack he impac o i ms’
cha ac e is ics on asse -p icing implica ions. The no el y o his pape is di ec ly ela ed
o how i quan i ies he consequences o he exogenous COVID-19 c isis on he di idend
s eam ha a ec s asse p ices depending on he esilience o hese wo ypes o i ms.
In o he wo ds, i cla i ies how esilience p ac ically con ibu es o asse p icing and
cha ac e izes he esilience-he e ogeneous equi y p emium by p o iding ac able o mulas,
showing ha i inc eases wi h he p obabili y o a disas e .
In line wi h Daadmeh (2024), his a icle shows ha he e ec o inancial esilience o
i ms signi ican ly ampli ies he impac o wo kplace esilience and agg ega e economic
Economies 2025,13, 123 3 o 35
con ac ion due o COVID-19. The no el p oposed an exogenous di idend s eam, and
i s es ima ion p o ides an oppo uni y o compa e he impac o i ms’ inancial esilience
and wo kplace esilience. Meanwhile, es ima ed di idend g ow h highligh s ha he
he e ogeneous e ec o wo kplace esilience is dominan , al hough he impac o i ms’
inancial esilience is s a is ically signi ican , demons a ing he need o cha ac e iza ion o
“ inancial esilience”. The no el applica ion o Dynamic Func ional P incipal Componen
Analysis (DFPCA) enables us o dis inguish no only he main ime- a ying elemen s o
inancial esilience bu also hose ha c ea e signi ican c oss-sec ional a ia ion. Finally,
his pape empi ically p o es ha alua ion, liquidi y, and sol ency a ios play key oles in
i ms’ inancial esilience and he co esponding ampli ica ion o wo kplace esilience. The
esul s o his pa shed ligh on possible co po a e policies.
The pape is s uc u ed as ollows. Sec ion 2cla i ies how his pape con ibu es o he
li e a u e and pos pones he in oduc ion o esilience in ui ions o Sec ion 3. The model o
he economy and he assump ions abou he exogenous di idend s eam a he i m le el
a e p esen ed in Sec ion 4. The solu ion o he model appea s in Sec ion 5, whe e he closed
o m o he esilience-he e ogeneous equi y p emium is p esen ed. The esul s on bo h he
e ec o he mac oeconomic con ac ion o COVID-19 and he es ima ed di idend s eam
a e included in Sec ion 6. The pape p oposes he main componen s o inancial esilience
in Sec ion 7and hen concludes.
2. Con ibu ion o Li e a u e
As he main no el y o his pape is o in es iga e esilience he e ogenei y in expec ed
cash lows and i s ole in asse p icing, his pape con ibu es o wo main s ands o
li e a u e: (i) co po a e esilience and he impac o COVID-19 on he c oss-sec ion o s ock
e u ns, and (ii) asse p icing models wi h a e e en s.
On he one hand, his a icle a emp s o discuss he impac o wo kplace esilience and
inancial esilience as an o e all indica o o i ms’ inancial s a us. Since he eme gence o
COVID-19, many s udies ha e s a ed o explain he lexibili y o i ms o indus ies in such
a pandemic c isis, speci ically in esponse o heal h mi iga ion policies, social dis ancing
ules, and lockdowns (among all Dingel & Neiman,2020;Hens ik e al.,2020;Ko en &
Pe ˝o,2020). This pape con ibu es o hese s udies mo e om he pe spec i e o asse
p icing han om co po a e esilience and conside s wo kplace esilience in he spi i o
Ko en and Pe ˝o (2020). As a key ea u e, his pape uses he da a on wo kplace esilience
and explains how and o wha ex en i signi ican ly con ibu es o he asse -p icing model
du ing he COVID pandemic.
Meanwhile, his pape akes in o accoun inancial esilience, as he as -g owing
li e a u e has al eady emphasized he impo ance o co po a e inancials on asse p ices in
esponse o a wide ange o public and co po a e policies (Ding e al.,2021;Fahlenb ach
e al.,2020;Pagano & Zechne ,2022;Ramelli & Wagne ,2020). Daadmeh (2024) compa es
hese wo in ui ions o esilience and p o ides a measu e o co po a e esilience, called he
composi e- inancial esilience index, applicable in imes o pandemics. This c oss-sec ional
measu e allows o he ca ego iza ion o asse s in o mo e isky and less isky g oups and
enables in es o s o manage hei esou ces. She p o ides di e en e idence o esilience
he e ogenei y in expec ed e u ns and expec ed u u e cash lows ha can po en ially
o igina e om wo kplace esilience and inancial esilience as an addi ional sou ce o
a ia ion. This pape de ia es om Daadmeh (2024) and quan i ies he c oss-sec ional
“ ime- a ying” inancial esilience, al hough he aim is no o p opose an index. Con a y o
he majo pa o hese s udies in co po a e inance, his pape p oposes a mechanism o
es ima e a mixed speci ica ion o exogenous di idend s eam as an expec ed u u e cash
low. Since he e is no empi ical s udy on he link be ween hese wo ypes o esilience,
Economies 2025,13, 123 4 o 35
no heo e ical wo k o backg ound, his pape (Sec ion 3.2) s a s wi h simple empi ical
e idence o mo i a e he cha ac e iza ion o he exogenous di idend s eam as a b idge
be ween hese wo ypes o esilience.
Acco ding o he li e a u e, i is no ewo hy o men ion and cla i y he impac o he
possibili y o disas e on he mac o ime e ec o he exogenous COVID-19 pandemic as
he hi d sou ce o a ia ion. Among all, Gou io (2012), Gabaix (2012), and Wach e (2013)
decla e he ime- a ying p obabili y o disas e ha gene a es co a ia ion in he equi y
p emium. Ghade i e al. (2022) de elop he li e a u e and conside he g adual un olding
disas e s. They explain ha in es o s a e no awa e o he ue s a e o he economy and
in oduce a Bayesian lea ning amewo k showing ha upda ing in es o s’ belie s cap u es
he e ec o slowly un olding disas e s, as p ices uly eac o he consump ion decline.
They show ha upda ing he agen ’s belie acco ds wi h he ue s a e o he economy. This
pape de ia es om Ghade i e al. (2022) by conside ing disas e s a es as bad imes o he
economy. I empi ically p o es ha COVID-19 has a emendous impac on he economy
and cap u es he impac o disas e and con ols he ime a ia ion o expec ed cash lows
o mac oeconomic sensi i i y o COVID-19 using he Ma ko -Swi ching app oach. As
opposed o Wach e and Zhu (2024) who use he jump Poisson p ocess o cap u e he low
and high in ensi y o disas e ha de ines disas e s a es based on wo high and low amoun s
o disas e in ensi y, and apply a Ma ko -Swi ching simula ion o in es iga e he impac o
lea ning in asse p icing o a e disas e s, his s udy conside s disas e s a es as he bad imes
o he economy and “es ima es” he p obabili y o disas e , s a es, and he du a ion o egimes
based on mon hly GDP.
F om an asse p icing pe spec i e, his pape uses he gene al amewo k p oposed
by Ba o (2006) bu wi h a special case o EZ p e e ences. Con a y o Ba o (2006), who
p oposes economic con ac ion due o a e e en s as a “ andom a iable” and calib a es
i , his a icle conside s i as a “s ochas ic p ocess” and p o ides an es ima e o each
mon h, using he Ma ko -Swi ching app oach. The empi ical analysis on his pa shows
ha di idend g ow h was signi ican ly sensi i e o he o e all economic con ac ion due
o he COVID-19 phenomenon, wi h a condi ional p obabili y o 2 pe cen , in line wi h
Ba o (2006), who calib a es he disas e p obabili y pa ame e . Ano he main di e ence is
di ec ly ela ed o he idea o esilience.
“Resilience” in Asse P icing:
In he asse p icing li e a u e, many s udies in oduce esilience in he a e-disas e
amewo k. Gabaix (2012) conside s a de e minis ic agg ega e consump ion g ow h in
he absence o disas e ; howe e , consump ion g ow h is magni ied by a posi i e mac oe-
conomic eco e y a e when a disas e occu s. He p esen s an asse -speci ic di idend
p ocess magni ied by a posi i e a e o su i ing in a disas e pe iod. The de ini ion o ime-
a ying “ esilience” in his pape is an inc easing unc ion o he asse -speci ic su i al a e.
In he amewo k he p oposed, esilience is a linea i y-gene a ing p ocess ha sees shock,
unco ela ed wi h disas e occu ence. Since he de ini ion o esilience highly depends
on he ype o disas e , his a icle, in con as o Gabaix (2012), conside s c oss-sec ional
wo kplace esilience due o he na u al ea u e o he COVID-19 pandemic and i s e ec
on he wo k o ce and i m cos s h ough social dis ancing ules and lockdowns (simila o
Daadmeh ,2024;Pagano e al.,2023).
This pape de ia es om Pagano e al. (2023) in wo aspec s: Fi s , i uses da a
on wo kplace esilience (in he spi i o Ko en & Pe ˝o,2020) a he han conside ing
i as a pa ame e in he model. Mo eo e , his s udy conside s wo kplace esilience,
a ec ing he di idend s eam c oss-sec ionally, and quan i ies he c oss-sec ional ime-
a ying impac o co po a e inancials as an addi ional pa called inancial esilience.
Second, i p o ides mon hly es ima es o disas e p obabili y a he han heo e ical

Economies 2025,13, 123 5 o 35
in ui ion o he p obabili y o disas e as a pa ame e in he model. I should also be
no ed ha his pape p o ides an empi ical es as a p e equisi e o ha ing a pa icula
de ini ion o disas e s a e and he co esponding p obabili ies based on he in insic
cha ac e is ic o COVID-19 and he Poisson dis ibu ion, as heo e ically p oposed by
Daadmeh (2025). The s iking di e ence is di ec ly ela ed o he ole o he es ima ed
Ma ko swi ching p ocess as a con ol o he mac o ime e ec o COVID-19, a necessa y
pa as Ba o (2006) decla es.
This pape demons a es he dominan he e ogeneous e ec o wo kplace esilience,
showing ha he di idend g ow h o low- esilience i ms is mo e esponsi e o wo kplace
esilience han ha o high- esilience i ms. Meanwhile, he impac o c oss-sec ional ime-
a ying inancial esilience is no negligible and signi ican ly ampli ies he impac o COVID-
19 on i ms’ p oduc ion g ow h and di idend s eam. Sec ion 3b ie ly in oduces hese
wo in ui ions o esilience and p o ides some pieces o ini ial e idence o ampli ica ion,
which sheds ligh on he cha ac e iza ion o he di idend s eam as expec ed cash lows.
3. Resilience
This pape in es iga es how esilience a ec s asse -p ice luc ua ions in he COVID-19
pandemic. A i s glance, i seems a li le bi icky o cla i y “ esilience”. Due o he pa ho-
logical ea u es o he COVID-19 pandemic and i s se e e impac on he labo o ce and he
wo kplace, which leads o huge business dis up ions, his a icle conside s he esilience o
he wo kplace as he capaci y o abso b he dis u bance in he COVID-19 ou b eak.
3.1. Wo kplace Resilience
A e he eme gence o COVID-19, many s udies s a ed o in e p e o wha ex en
i ms’ pe o mance depends on communica ion es ic ions and social dis ancing ules
(among all Dingel & Neiman,2020;Hens ik e al.,2020;Ko en & Pe ˝o,2020). Many o hem
ied o p opose a measu e o wo kplace lexibili y. Ko en and Pe ˝o (2020) p o ide a heo y-
based measu e o he dependency o US businesses on human in e ac ion, based on h ee
dimensions o occupa ion: eamwo k in ensi e, cus ome acing, and physical p esence.
Thei model o communica ion e eals he sensi i i y o p oduc ion cos s o an inc ease in
ace- o- ace in e ac ion and de e mines i ms wi h less e icien pe o mance om home.
They explain he impac o ace- o- ace communica ion on cos s o p oduc ion, in oduce
he a e age ‘a ec ed sha e’, and in e p e ha a highe i m’s a ec ed sha e implies less
lexibili y owa ds social dis ancing es ic ions du ing he COVID-19 pandemic.
The impo an ea u e o wo kplace esilience is ha he esilience o i ms depends on
hei own wo kplace cha ac e is ics and lexibili y owa ds he new social dis ancing ules
and lockdown policies, which is no implied by he wo kplace esilience o o he i ms.
Despi e all he p ominen ea u es o his esilience measu e, Daadmeh (2024) shows he
sho coming o his ype o esilience o exhibi “signi ican ” esilience he e ogenei y in he
i m’s implied discoun a e as he p oxy o expec ed e u n.
3.2. Is Wo kplace Resilience Adequa e Enough?
Al hough he necessi y and adequacy o wo kplace esilience a e ully in es iga ed by
Daadmeh (2024) using se e al pieces o empi ical e idence, Figu e 1shows he e olu ion
o analys s’ expec a ion o u u e cash lows o high- and low- esilience
2
i ms in he
spi i o Ko en and Pe ˝o (2020) in he i s panel. They p opose a p oxy called “a ec ed
sha e” o show o wha ex en businesses ely on human in e ac ion. F om he analys s’
poin o iew, low- esilience i ms expe ienced lowe expec ed cash lows
3
compa ed o
high- esilience i ms. The i s panel e eals ha agg ega e expec a ions be e e lec he
ea nings expec a ion o low- esilience i ms, especially be o e and du ing he e e pe iod
Economies 2025,13, 123 6 o 35
o COVID-19, and sugges s ha wo kplace esilience can po en ially be an impo an sou ce
o he e ogenei y in i ms’ expec ed cash lows.
Figu e 1. The e olu ion o expec ed u u e cash lows in he e e pe iod o COVID-19 ( he impac
o wo kplace esilience and le e age): The i s panel shows he s anda dized ea nings expec a ion
(Ex EPSi,2020 −EPSi,2019)/EPSi,2019
o high- and low- esilience i ms, in he sense o wo kplace
lexibili y, o cu en iscal yea o 2020.
Ex EPSi,2020
s ands o an ea nings expec a ion o i m i
a ime (simila o Daadmeh ,2024;Ko en & Pe ˝o,2020;Landie & Thesma ,2020). Fi ms wi h
an ‘a ec ed sha e’ less han 40 a e assigned o he high- esilience g oup, and ones wi h g ea e
han 65 a e assigned o he low- esilience one. The second panel shows he s anda dized ea nings
expec a ions o i ms wi h di e en le els o le e age. Fi ms wi h highe le e age han he 80 h
pe cen ile a e assumed high-le e ed (Q5), and i ms wi h lowe han he 20 h pe cen ile a e he
low-le e ed ones (Q1). Da a sou ce: Compus a /CRSP me ged, WRDS o undamen als, and
Re ini i -Eikon (Thomson Reu e s) I/B/E/S o ecas s o daily consensus analys s’ ea nings.
Al hough his ype o esilience is in acco dance wi h he ype o pandemic c isis
and shows o wha ex en i ms can su i e when hei p oduc i i y is a ec ed by human
loss (Ko en & Pe ˝o,2020), he inancial s a us o i ms can p o ide a ype o lexibili y
o i ms o handle addi ional p oduc ion cos s. In addi ion o all he e idence p o ided
by Daadmeh (2024), he second panel o Figu e 1shows he analys s’ expec a ions o
u u e cash lows sepa a ely o high- and low-le e ed i ms and p o ides e idence o he
impo ance o capi al s uc u e and i ms’ le e age on he e olu ion o expec ed ea nings.
This panel exhibi s ha no only did ea nings expec a ions decline mo e o high-le e ed
i ms, bu also his decline o high-le e ed i ms was pe sis en and associa ed wi h highe
oscilla ions in he ollowing iscal yea s. This is consis en wi h much o he p e ious
e idence ha i ms wi h less s ong balance shee s expe ienced g ea e di icul ies du ing
Economies 2025,13, 123 7 o 35
and a e he e e pe iod o COVID-19, such as Pe enuzzo e al. (2023), which show
how le e age and cash holdings a e ela ed o i m pe o mance, especially hose wi h
less p o i abili y and lowe e enue g ow h. Each panel o his igu e emphasizes ha
wo kplace esilience and i ms’ co po a e inancials can sepa a ely explain he e ogenei y in
expec ed cash lows.
Meanwhile, i ms wi h low wo kplace esilience would be mo e capable o handling
and managing p oduc ion cos s i hey al eady ha e a sui able inancial posi ion. They see
less educ ion in he a e age ea nings expec a ions (Daadmeh ,2024); Howe e , analys s
we e qui e pessimis ic abou he ebound in ea nings o hese i ms wi h lowe inancial
s a us, as Daadmeh (2024) explains. So, i is c ucial o ind a mechanism in which hese
wo in ui ions join ly a ec he expec ed cash lows and he p ice luc ua ions o an equi y
claim o he ou pu o such i ms.
Figu e 2mo i a es and sugges s he exis ence o such in e ac ion. I shows he a -
e age ea nings expec a ions o ou ca ego ies o i ms: “high wo kplace- esilience and
high-le e ed” i ms, “high wo kplace- esilience and low-le e ed” i ms, “low wo kplace-
esilience and high-le e ed” i ms, and “low wo kplace- esilience and low-le e ed” i ms.
The e idence emphasizes wo p ominen impac s o i ms’ inancial s a us: (i) Among low-
le e ed i ms, hose wi h a mo e lexible wo k o ce no only ha e less educ ion in a e age
ea nings expec a ions bu also see less se e e luc ua ions in he ollowing mon hs a e he
onse ( i s panel). (ii) A highe le e age appea s o weaken he bene i o high wo kplace
esilience. The second panel, compa ed o he i s one, sugges s ha high le e age educes
he ea nings expec a ion su plus o high wo kplace esilience and makes luc ua ions mo e
se e e. These wo pieces o e idence highligh ha i ms’ inancial cha ac e is ics can
po en ially magni y he impac o hei wo kplace esilience on expec ed cash lows.
3.3. Financial Resilience
Mo eo e , back o he s o y o he impac o a wide ange o policies, any inancial
a ios om any ca ego y, including, e.g., p o i abili y and sol ency a ios, can be e ec i e
on all hese associa ions. This e-mo i a es o quan i y he o e all impac o all co po a e
inancials. This pape sugges s a machine lea ning de ini ion o inancial esilience based
on Dynamic Func ional P incipal Componen Analysis (DFPCA) as a solu ion o such
quan i ica ion (Sec ion 4.2.2). The ollowing sec ions show how c oss-sec ional ime- a ying
dynamic unc ional PCs con ibu e o he asse -p icing model and o wha ex en inancial
esilience elemen s in e ac a he di idend le el (Sec ion 4.2) and possibly no only ampli y
he impac o wo kplace esilience, bu also c ea e signi ican he e ogenei y in di idend
g ow h (Sec ion 6).
Figu e 2. Con .
Economies 2025,13, 123 8 o 35
Figu e 2. The e olu ion o expec ed u u e cash lows in he e e pe iod o COVID-19 (ampli ica ion
e ec ): Bo h panels show he s anda dized ea nings expec a ion,
(Ex EPSi,2020 −EPSi,2019)/EPSi,2019
,
o ou g oups o i ms du ing he e e pe iod.
Ex EPSi,2020
s ands o he ea nings expec a ion
o i m i a ime o he cu en iscal yea o 2020. Fi ms wi h an ‘a ec ed sha e’ less han 40 a e
assigned o he high- esilience g oup, and ones wi h g ea e han 65 a e assigned o he low- esilience
one. Fi ms wi h highe le e age han he 80 h pe cen ile a e assumed o be high-le e ed, and i ms
wi h lowe le e age han he 20 h pe cen ile a e he low-le e ed ones. The ca ego iza ion o i ms in o
high- and low- esilience i ms in he sense o wo kplace lexibili y is based on Ko en and Pe ˝o (2020)
and ollows Daadmeh (2024). Da a sou ce: Compus a /CRSP me ged, WRDS o undamen als, and
Re ini i -Eikon (Thomson Reu e s) I/B/E/S o ecas s o daily consensus analys s’ ea nings.
4. Model and Da a
This sec ion in oduces he s anda d asse -p icing amewo k wi h he exogenous
di idend s eam, embedding he impac o COVID-19 on i ms’ p oduc i i y. I cla i ies how
he pape quan i ies esilience as well as how i con ols he mac o ime e ec o economic
con ac ion. The da a desc ip ion is p esen ed a he end o he
co esponding subsec ions.
4.1. The Economy
The COVID-19 pandemic caused massi e business dis up ion due o social dis ancing
ules and lockdowns ha almos all go e nmen s imposed. Speci ically, i ms in some
indus ies we e a ec ed e en mo e because hey we e no eally lexible in hei wo k o ce,
o hey could no un asks in he hyb id mode, simply because such asks needed mo e
human in e ac ion o ace- o- ace communica ion wi h a highe physical p esence. All
o hese inc eased he cos o p oduc ion and a ec ed he ou pu o such low wo kplace-
esilien i ms. This si ua ion c ea ed a so o addi ional unce ain y in he ma ke , which is
qui e impo an om an asse -p icing pe spec i e. Fo a ep esen a i e consume (in es o ),
i is impo an o know wha happened o he p ice o an equi y claim o he ou pu o
hese i ms.
Following Meh a and P esco (1985) and Ba o (2006), his pape conside s ecu si e
p e e ences o Eps ein and Zin (1989) and Weil (1989) o ep esen a i e-consume Lucas’
ui - ee model o asse p icing wi h an exogenous s ochas ic di idend s eam
4
. Based
on Campbell (1993) wi h o al weal h a he beginning o +1,
W +1=W −C
as an
in e empo al budge cons ain and
M +1=β∗θ(C +1
C )−θ
ψ
as he s ochas ic discoun ac o
wi h ime discoun β∗; in pa ial equilib ium, he s anda d Eule equa ion is5:
1=E [β∗θ(C +1
C
)−θ
ψRi, +1]. (1)
Economies 2025,13, 123 15 o 35
e y high p obabili y o a disas e s a e, he e is no in e es in he isky asse , so he equi y
p emium inc eases as compensa ion o co e he addi ional isk. The hi d panel shows
ha he model-based equi y p emium is an inc easing unc ion o he p obabili y o disas e .
Mo eo e , in line wi h Ba o (2006), he equi y p emium is a dec easing unc ion o isk
a e sion
γ
. In wha ollows, he pape p esen s he es ima ion o exogenous di idend
g ow h and i s pa ame e s used in he calib a ion exe cise.
Figu e 3. Con .

Economies 2025,13, 123 16 o 35
Figu e 3. P ice- o-di idend a io, isk- ee a e, and equi y p emium: This igu e plo s he log P/D
a io, log isk- ee a e
logR
i
, and equi y p emium
logE Ri −logR
i
as a unc ion o p obabili y
o disas e . The log P/D a io, log isk- ee a e, and equi y p emium a e compu ed based on
es ima ed pa ame e s
α
,
δ
,
β1,..., βM
(Sec ion 6) and calib a ion exe cise o
γ
,
ψ
, and
σε
. Da a sou ce:
Compus a /CRSP me ged and inancial a ios, WRDS.
6. Resul s
This sec ion p esen s an es ima ed exogenous di idend s eam o model-based asse -
p icing implica ions. The i s pa (Sec ion 6.1) cla i ies ha COVID-19 is a disas e and
p o ides he es ima ion o he mac o ime e ec o COVID-19 (
ηs
) om 2013 o 2022,
he pe iod o e which he exogenous di idend s eam is es ima ed. The second s ep
(Sec ion 6.2) quan i ies he impac o inancial esilience componen s. I also es ima es
di idend g ow h (Equa ion (8)) as well as he ixed-e ec s
α
and
βm
s, which a e coe icien s
o mac oeconomic con ac ion,
ˆ
ηs
, and inancial esilience componen s,
PCi ,m
, espec i ely,
and
δ
as he he e ogeneous e ec o wo kplace esilience,
ln(φi)
, using he Res ic ed
Maximum Likelihood me hod, REML, o e 2013–2022.
6.1. Mac oeconomic Sensi i i y o COVID-19 Disas e
In he p oposed app oach, he i s s ep is o es ima e he mac oeconomic con ac ion
due o COVID-19 o con ol o he agg ega e ime e ec , as explained in Sec ion 4.2.3.
Figu e 4shows he i ed wo- egime Ma ko -swi ching (MS) model o he mon hly GDP o
he Uni ed S a es om 1960 o 2022 and speci ies he disas e egimes. This igu e p o ides
an oppo uni y o empi ically p o e ha his pandemic was a disas e wi h signi ican
mac oeconomic consequences and exhibi s he COVID-19 pandemic pe iod as a disas e
egime. Fu he mo e, acco ding o Table 1, he es ima ion o con olling he mac o ime
e ec o COVID-19, ˆ
ηs
, can be ob ained om:
ˆ
η =


100.69 +0.97ˆ
η −1
100.69 +1.03ˆ
η −1
1−p :Non −Disas e .s a e
p :Disas e .s a e
wi h he es ima ed ansi ion p obabili ies in Table 2. The signi ican swi ching AR(1)
coe icien s in Table a e a sign o se e e economic con ac ion in disas e s a es, speci ically,
Economies 2025,13, 123 17 o 35
he es ima ed coe icien in disas e s a es (1.03) shows ha such a mac o ime e ec is no
mean- e e ing in disas e s.
The LRT s a is ic p o ided in Table empi ically p o es he signi icance o nonlin-
ea wo- egime MS-AR(1). The e idence on op imal choice o he numbe o egimes is
p esen ed in Tables A1 and A2 in Appendix A.
Figu e 4. Mon hly GDP, i ed he wo- egime MS-AR(1) and he one-s ep p edic ion om 1960 o
2022: The blue columns show he disas e egimes (s a es and he du a ion). Da a sou ce: no malized
seasonally adjus ed GDP, Fede al Rese e Bank o S . Louis, Economic Resea ch Di ision.
Table 1. Es ima ed pa ame e s o MS-AR(1): This able p esen s he maximum likelihood es ima ion
o he wo- egime Ma ko -swi ching AR(1) and he condi ional p obabili y o disas e s a es. I
p o ides he Likelihood Ra io Tes o examine linea s. nonlinea wo- egime MS-AR(1). Signi ican
codes: 0 ‘***’, 0.001 ‘**’.
Nonlinea Ma ko Swi ching Coe icien s (S De ) -Value
In e cep : ρ0100.69 (0.013) 592.00 ***
AR-1: ρ(Disas e s a e) 1.03 (0.01) 65.40 ***
AR-1: ρ(Non-Disas e s a e) 0.97 (0.003) 172.00 ***
p(Disas e |Disas e ) 0.91 (0.02) 63.20 ***
p(Disas e |Non-Disas e ) 0.02 (0.005) 4.51 ***
log-likelihood s a is ics 431.80
LRT s a is ics 1102.7 **
Table 2. Es ima ed ansi ion ma ix: This able shows he condi ional p obabili y o disas e s a es
es ima ed by wo- egime MS-AR(1).
T ansi ion P obabili y Disas e S a e a Time Non-Disas e S a e a Time
Disas e s a e a ime + 1 0.91 0.02
Non-Disas e s a e a ime + 1 0.08 0.97
Economies 2025,13, 123 18 o 35
Figu e 5shows he e olu ion o he p obabili y o a disas e s a e,
p
. As can be clea ly
seen and in line wi h Figu e 1, he p obabili y o a disas e s a e inc eased o a ound 0.9 in
he e e pe iod o COVID-19, ollowed by a educ ion due o he impac o good news
abou accines. Al hough he p obabili y o a disas e s a e a ime being condi ional
on he non-disas e s a e o he p e ious mon h is 2 pe cen , which is in line wi h he
calib a ed s a ic disas e p obabili y o 1.7 pe cen p oposed by Ba o (2006), he economy
will emain in he disas e egime due o he low ansi ion p obabili y o 8 pe cen . Table 2
shows ha swi ching om disas e s a es o non-disas e ones happens wi h a p obabili y
o 0.08.
Figu e 5. E olu ion o es ima ed p obabili y o disas e s a e based on MS-AR(1), om 1960 o
2022:The blue columns show he disas e egimes (s a es and he du a ion).
In addi ion o Figu e 4, which g aphically shows he goodness o i and he app op i-
a eness o he es ima ed economic con ac ion,
ˆ
ηs
, Table A3 (in he Appendix A) e i ies
hese esul s and con ains no only he es ima ed disas e s a es
s
and he du a ion o he
egimes, bu also he e idence om he Fed epo s. I compa es he es ima ed disas e
egimes wi h he co esponding ac ual e en s. The es ima ion o disas e egimes acco ds
wi h he his o ical in o ma ion in (Bu ge ,1969;Hoxwo h e al.,1983;Supel,1978).
Mo eo e , Figu e A1 (in he Appendix A) shows he es ima ed dis ibu ion o mac oe-
conomic sensi i i y,
ηs
, and compa es he bimodal dis ibu ion wi h he co esponding no -
mal dis ibu ion. I p o ides ano he o m o e i ica ion o he numbe o
egime swi ches.
6.2. Jus i ica ion o Di idend S eam and Asse -P icing Momen s
To in e p e he impac o co po a e inancials and o in es iga e whe he and o wha
ex en he inancial s a us o i ms ampli ies he consequences o COVID-19 on asse p ices,
his pape s a s wi h a ound 70 inancial a ios o 5833 US i ms o e 2013–2022 a mon hly
equency and employs Dynamic Func ional P incipal Componen Analysis (DFPCA) o
cap u e he impac o i m’s inancial s a us, as explained in Sec ion 4.2.2.
By compu ing he il e sequences and dynamic unc ional p incipal componen s, i
is possible o p o ide he sc ee plo and decide on he numbe o componen s equi ed
o include mos o he a ia ion o igina ing om all co po a e inancials ha possibly
a ec ed di idend g ow h. Figu e 6shows he po ion o a iance explained by each
dynamic unc ional PC o all i ms, sepa a ely, in one diag am. I sugges s ha he i s
i e componen s explain he mos a ia ion (o e 90 pe cen ) induced by inancial a ios
o almos all i ms.
Based on Equa ion (8) and he i s i e dynamic p incipal componen s (PCs)
16
, he
esul s o he es ima ed di idend g ow h a e summa ized in Table 3. This able p esen s
he quan i ied e ec o wo kplace esilience and he impac o he i m’s inancial esilience
as he elas ici y o di idend g ow h o hese wo in ui ions o esilience.
Economies 2025,13, 123 19 o 35
Figu e 6. A sc ee plo o he Dynamic Func ional P incipal Componen Analysis (DFPCA) o inancial
a ios: This igu e shows he po ion o a iance explained by each componen (eigen alues). Each
colo ed line is he sc ee plo o one i m, sepa a e om o he s. The sample con ains a ound 5833 US
i ms. Da a sou ce: i m-le el inancial a ios, WRDS.
Table 3. Di idend g ow h es ima ion: This able p o ides es ima ion o coe icien s o inancial
esilience componen s and he impac o COVID-19, including he mac o ime e ec o COVID
(ln ˆ
ηs
)
and wo kplace esilience (Equa ion (8)). I p esen s he ixed-e ec s
(β1
,...,
β5)
o he i s
i e c oss-sec ional ime- a ying dynamic unc ional PCs
(PC1
,...,
PC5)
and he he e ogeneous e ec
(δ)
o wo kplace esilience
ln(φi)
, by REML es ima ing me hod. The indus y sec o codes om
“2” o “6” belong o “Mining, U ili y and Cons uc ion”, “Manu ac u ing”, “T ade, T anspo a ion
and Wa ehousing”, “In o ma ion, Finance, Managemen , and Remedia ion Se ices”, “Educa ional,
Heal h Ca e and Social Assis ance”, espec i ely. Each column shows he es ima ed esul o each
indus y sepa a ely. The numbe s in pa en heses a e s anda d de ia ions o co esponding es ima ed
coe icien s. Signi ican codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05.
Dependen Va iable: Di idend G ow h
All Indus ies
Indus y Sec o (NAICS Code)
2 3 4 5 6
PC10.0007 **
(0.0002) 0.0027
(0.0014) 0.0041 ***
(0.0003)
−0.0026 **
(0.0008)
−0.0029 ***
(0.0005) 0.0113 ***
(0.0025)
PC2−0.0029 *
(0.0004) 0.0066 **
(0.0021)
−0.0045 ***
(0.0005) 0.0052 ***
(0.0011)
−0.0022 ***
(0.0006)
−0.0082 *
(0.0032)
PC3−0.0025 *
(0.0005) 0.0010
(0.0028)
−0.0013
(0.0007) 0.0025
(0.0015)
−0.0050 ***
(0.0008) 0.0132 **
(0.0042)
PC4−0.000007 ***
(0.0022)
−0.0092 *
(0.0037)
−0.0014
(0.0008)
−0.0029
(0.0020) 0.0030 **
(0.0011) 0.0026
(0.0058)
PC50.00001
(0.0008)
−0.0060
(0.0045) 0.0002
(0.0011) 0.0055 *
(0.0025)
−0.00007
(0.0013) 0.0310 ***
(0.0069)
ln ˆ
ηs
−2.3149 ***
(0.0889)
−0.7308
(0.4882)
−1.8041 ***
(0.1191)
−2.4705 ***
(0.2832)
−3.2298 ***
(0.1399)
−3.2044 **
(0.0085)
A e age o
wo kplace esilience
(he e ogeneous e ec )
10.3690 ***
(0.4622) 2.6394 ***
(0.5561) 8.0623 ***
(0.4327) 11.2225 ***
(0.5193) 14.5646 ***
(0.3182) 14.0970 ***
(0.6553)
F-s a is ics 127.48 *** 4.013 * 79.816 *** 19.303 *** 105.565 *** 11.4737 ***
Economies 2025,13, 123 20 o 35
6.2.1. In e p e a ion o Wo kplace Resilience Impac
I can be clea ly seen ha he wo kplace esilience has a signi ican posi i e a e age
he e ogeneous e ec o 10.36 on di idend g ow h o a sample o all indus ies. Fo
indi idual indus ies, he co esponding coe icien o wo kplace esilience in he spec-
i ica ion o di idend g ow h a ies on a e age om 2 o 14, espec i ely, in “Mining,
U ili y and Cons uc ion” and “In o ma ion, Finance, Managemen , and Remedia ion
Se ices”. The key esul on he a e age he e ogeneous e ec o wo kplace esilience
can be seen in
Figu e 7
. Based on wo kplace esilience, i ms a e ca ego ized in o wo,
h ee, and ou g oups. In each case, he i s and las g oups a e conside ed low- and
high- esilience i ms, espec i ely. This igu e indica es ha he a e age he e ogeneous
e ec o wo kplace esilience o low- esilience i ms is g ea e han he one o high-
esilience i ms ( he ed line is below he blue line in Figu e 7), meaning ha he elas ici y
o di idend g ow h wi h espec o wo kplace esilience
ˆ
δ
o i ms wi h a e y low
deg ee o wo kplace esilience is much highe han he one o e y high- esilience i ms.
On he o he hand, i can be clea ly seen in Figu e 7 ha he g ea e he di e ence in
he wo kplace esilience o i ms (an inc ease in he numbe o g oups, equi alen ly),
he g ea e he di e ence in he a e aged he e ogeneous e ec o he co esponding
elas ici y (an inc ease in e ical dis ance be ween he ed poin and he blue one); as a
esul , o he same amoun o inc ease in wo kplace esilience, he e is a g ea e change
in di idend g ow h o low- esilience i ms based on Equa ion (8). Daadmeh (2025)
heo e ically p o es a simila s a emen o expec ed e u ns and shows ha an inc ease
in COVID in ensi y inc eases he expec ed e u n o low- esilience i ms much mo e han
ha o high- esilience i ms.
To sum up, Figu e 7sugges s ha in low- esilience i ms, a one-pe cen imp o emen
in wo k o ce lexibili y inc eases di idend g ow h much mo e han in he case o high-
esilience i ms, since he a e age es ima ed he e ogeneous coe icien
ˆ
δ
o low- esilience
i ms is much highe . Summa y s a is ics and empi ical esul s on he he e ogeneous e ec
o wo kplace esilience a e p o ided in Table 4. This able p o ides s a is ical es s o e eal
hese di e ences in he e ogeneous e ec ,
ˆ
δ
, o hese wo g oups o i ms. The esul s
in his able implici ly examine he signi ican di e ences in he elas ici y o di idend
g ow h o wo kplace esilience be ween high- and low-wo kplace- lexible i ms. This able
empi ically p o es ha o any numbe o g oups (K), he he e ogeneous e ec o he
wo kplace esilience o high wo kplace- esilien i ms is “signi ican ly” di e en om ha
o he low wo kplace- esilien ones. Consequen ly, he e a e signi ican disc epancies in
di idend g ow h o high- and low- esilience i ms c ea ed by he he e ogeneous e ec o
wo kplace esilience. In o he wo ds, his indica es ha di idend g ow h o low- esilience
i ms is signi ican ly mo e sensi i e o wo kplace esilience han ha o high- esilience
i ms, echnically p o ing he exis ence o signi ican esilience he e ogenei y in expec ed
cash lows.

Economies 2025,13, 123 21 o 35
Figu e 7. The a e age he e ogeneous e ec o wo kplace esilience: This igu e exhibi s how he
di e ence in wo kplace esilience o high- and low- esilience i ms changes he a e age he e ogeneous
e ec o wo kplace esilience, by so ing and equally spli ing i ms in o K g oups based on hei
wo kplace esilience. The i s g oup and he las one a e conside ed i ms wi h low and high
wo kplace esilience, espec i ely.
Table 4. The summa y s a is ics o he e ogeneous e ec o wo kplace esilience: This able p o ides
he summa y s a is ics on he he e ogeneous e ec o wo kplace esilience o high- esilience and
low- esilience i ms, including he esul s o g oup compa isons. Based on wo kplace esilience, i ms
a e so ed and spli in o K g oups. The i s g oup and he las one a e conside ed i ms wi h low
and high wo kplace esilience, espec i ely. I compa es he he e ogeneous e ec o wo g oups o
i ms using he nonpa ame ic Wilcoxon es . The he e ogeneous e ec o high- esilience i ms is
signi ican ly di e en om he low- esilience ones (a he le el o 0.001, indica ed by ***).
K Wo kplace Resilience Minimum 1s Qu. Median Mean 3 d Qu. Maximum G oup Compa ison Tes p-Values
2High 9.88 10.21 10.29 10.33 10.52 10.52 0.00 ***
Low 9.35 9.16 10.41 10.38 10.69 10.51
3High 10.05 10.05 10.22 10.19 10.22 10.33 0.00 ***
Low 9.35 10.15 10.41 10.36 10.72 11.41
4High 10.05 10.05 10.21 10.17 10.22 10.29 0.00 ***
Low 9.35 10.16 10.44 10.34 10.72 11.41
6.2.2. In e p e a ion o Mac o Time E ec o COVID-19
Table 3emphasizes he impo ance o mac oeconomic COVID sensi i i y, which
implies a signi ican educ ion in di idend g ow h no only a he le el o “All indus-
ies”, bu also wi hin each indus y, excep “Mining, u ili ies and cons uc ion”. The
es ima ed coe icien o
ln(ˆ
ηs
)
is s a is ically signi ican , showing ha all sec o s a e
signi ican ly sensi i e o he ecession caused by COVID-19, excep “Mining, U ili y and
Cons uc ion”.
Economies 2025,13, 123 22 o 35
Does he low amoun o es ima ed wo kplace esilience,
ˆ
δ
, imply such an insigni ican
e ec o mac oeconomic con ac ion due o COVID-19? In his sec o , he eason o
he lack o s a is ical signi icance o
ˆ
α
is ela ed o he low amoun o es ima ed a e age
he e ogeneous e ec o wo kplace esilience o 2.6. Fi ms in his sec o ha e a much lowe
a e age he e ogeneous e ec o wo kplace esilience compa ed o i s a e age amoun
plo ed in Figu e 7( he ed line is below he blue line in Figu e 7and he a e age amoun
o 2.6 o his indus y is much smalle han he a e age in he case o “all indus ies”,
in Figu e 7). Consequen ly, his sugges s ha i ms in his indus y a e mo e wo kplace-
esilien , on a e age. Hence, in his indus y, social dis ancing es ic ions a e no as
in usi e as hey a e in o he sec o s, so i is no su p ising o see such an insigni ican
impac o he mac o ime e ec o COVID-19.
6.2.3. In e p e a ion o Financial Resilience
Table 3also shows he esul s o elemen s o inancial esilience. The signi icance
o dynamic unc ional p incipal componen s o inancial a ios no only sugges s he
signi ican e ec o i ms’ inancial s a us on di idend g ow h bu also p o es he signi -
ican ampli ica ion o wo kplace esilience by co po a e inancials
17
,
Gi = (FRi )gi
, in
Sec ion 4. This able e eals ha inancial esilience, especially he i s wo p incipal
componen s, which con ain mos a ia ions o igina ing om inancial a ios, di ec ly
a ec s di idend g ow h and makes i s esilience mo e he e ogeneous. These small es i-
ma ed e ec s,
β1,..., βM
, is no ca as ophic in such a pandemic c isis bu is signi ican
enough. Then, o e all esilience he e ogenei y is no jus om he wo k o ce esilience
pe spec i e bu also based on wha i ms inancially expe ienced be o e and du ing
he COVID-19 ou b eak. The nex sec ion in oduces he majo elemen s wi h mo e
con ibu ion o i ms’ inancial esilience.
On op o all his, since he a e aged he e ogeneous e ec o wo kplace esilience
is g ea e han he es ima ed coe icien s o inancial esilience elemen s (PCs), di idend
g ow h is mo e elas ic and esponsi e o wo kplace esilience. Equi alen ly, he ole
o wo kplace lexibili y is mo e p ominen in explaining he esilience he e ogenei y in
di idend g ow h.
Mo eo e , he empi ical esul s in his sec ion show “ o wha ex en ” cash lows can
be esilience-he e ogeneous and he solu ion o he p oposed model in Sec ion 5, sheds
ligh on “how” such signi ican esilience-he e ogenei y, speci ically he he e ogeneous
e ec o wo kplace esilience and he ampli ica ion e ec by inancial esilience, can be
ans e ed o expec ed e u ns as well as all asse -p icing implica ions. The calib a ed
exe cise compa es model-based asse -p icing momen s wi h he co esponding alues om
his o ical da a. The model-based equi y p emium (5.269) is close o he a e age equi y
p emium om he da a (5.147). The esul holds o he isk- ee a e (1.137 s. 1.006 om
his o ical da a). The model-based s anda d de ia ion o he log isk- ee a e (2.531) is in
line wi h he co esponding amoun p esen ed by Ghade i e al. (2022) using his o ical da a
om 1950 o 201918.
7. Majo Elemen s o Financial Resilience
Sec ion 6explained he signi ican ole o inancial esilience o asse s in ampli ica ion
o he dominan he e ogeneous e ec o wo kplace esilience on exogenous di idend
g ow h, as well as asse -p icing implica ions (Sec ion 5). The key applica ion o Dynamic
Func ional P incipal Componen Analysis (DFPCA) de e mined he i s i e majo PCs as
componen s o inancial esilience
FRi
, a he i m le el o e ime, including he COVID-19
e a. This sec ion cla i ies which inancial a ios mos ly d i e luc ua ions in hese i ms’
inancial esilience componen s.
Economies 2025,13, 123 23 o 35
Figu e 8shows he weigh s o he inancial a ios o each o
PC1
,...,
PC5
. I p o ides
an oppo uni y o compa e he ela i e impo ance o inancial a ios in de e mining he
i m’s esilience. This igu e e eals majo a ios wi h o e 90 pe cen a e age weigh
(abo e he black dash line) in he speci ica ion o a leas one o he i s i e p incipal
componen s,
PCi ,m=∑k∈Zϕ′
i,mkXi, −k
, o
m=
1,..., 5. I de e mines Shille ’s Cyclically
Adjus ed P/E Ra io, P ice/Ope a ing Ea nings (Basic), P ice/Ope a ing Ea nings (Dilu ed),
P/E (Dilu ed, Excl. EI), P/E (Dilu ed, Incl. EI) and P ice/Sales ( alua ion a ios); Cash
Con e sion Cycle (liquidi y a io); and In e es Co e age Ra io (sol ency a io) as main
elemen s o dynamic unc ional PCs and inancial esilience as well.
Figu e 8. O e all weigh s o inancial a ios (a e age o il e sequences,
ϕ
, o he i s i e PCs):
This igu e shows he s anda dized weigh s o all inancial a ios ob ained by DFPCA. The sample
con ains 5833 i ms in all indus ies. The black dash line is he h eshold o 90 pe cen o weigh s.
Da a sou ce: i m-le el inancial a ios, WRDS.
Daadmeh (2024) explains o wha ex en he alua ion and liquidi y a ios a e signi i-
can ly co ela ed wi h he p oposed inancial-based esilience index and emphasizes he
necessi y o wo kplace lexibili y o de ine a no el “Composi e-Financial Resilience Index”.
The machine-based (DFPCA) choice o alua ion a ios is in line wi h Glossne e al. (2024),
who emphasize he impo an ampli ica ion ole o ins i u ional in es o s in alua ion and
he se e e p ice decline in COVID-19. Fu he mo e, ha ing a liquidi y a io as one o he
impo an a ios de e mined by DFPCA is consis en wi h Pagano and Zechne (2022),
who men ion he signi ican change in liquidi y le els o lis ed US i ms om be o e he
eme gence o he pandemic o a e he onse .
The choice o In e es Co e age Ra io is in line wi h Palomino e al. (2019), who
in e p e coun e cyclicali y and i s nega i e ela ionship wi h economic ac i i y. In wha
ollows, he e is an in e p e a ion o he ela ion be ween hese a ios, wo kplace esilience,
and i ms’ ulne abili y and iskiness.
Economies 2025,13, 123 24 o 35
7.1. Valua ion Ra ios
By de ini ion, alua ion a ios a e app op ia e o measu e he ela ionship be ween
ma ke alue and some s eam o undamen als. Figu e 9shows he ime a ia ion in
di e en ypes o alua ion a ios wi h highe han 90 pe cen weigh (a e aged
ϕ
in
Equa ion (4)) in elemen s o i ms’ inancial esilience (
PC1
,...,
PC5
) a e he onse o he
COVID pandemic, diagnosed by Dynamic Func ional PCA (DFPCA). The i s panel shows
ha he ime end o almos all o hese a ios is he same, especially di e en ypes o
p ice- o-ea nings a ios ha a e commonly used as good inancial me ics o ob ain a be e
unde s anding o he o e all pic u e, and a e accessible o a wide ange o in es o s. In his
pape , DFPCA echnically p o ed i s signi ican ole in esilience-he e ogeneous di idend
g ow h h ough he i m’s inancial esilience (Sec ion 6.2).
This igu e compa es he desc ip i e beha io o hese alua ion a ios, also sepa a ely
o high- and low- esilience i ms ( he second and hi d panels), in he sense o wo kplace
esilience. I can be clea ly seen om he second panel ha hese a ios ha e a mo e
homogeneous end o high- esilience i ms. This homogenei y is less clea in he case o
low- esilience i ms. To make a be e compa ison be ween he alua ion a ios o high-
and low- esilience i ms, one o hese a ios is selec ed as a ep esen a i e.
The Dynamic Func ional PCA de e mines “Shille s Cyclically Adjus ed P/E Ra io”
as an e ec i e main elemen o ei he
PC1
o
PC5
wi h a weigh o mo e han 90 pe cen
(Figu e 8). In pa icula , DFPCA implici ly men ions he in la ed P/E due o low o e en
nega i e ea nings du ing economic down u ns like COVID-19 and e e s o he cyclicali y
o ea nings du ing hese pe iods. I highligh s he impo ance o cyclically adjus ing P/E
and selec s “Shille s Cyclically Adjus ed P/E Ra io” as he mos p omising alua ion
a io among di e en de ini ions o P/E a io. The i s panel o Figu e 10 shows ha
he adjus ed P/E a io o low- esilience i ms is highe han ha o high- esilience i ms
du ing he COVID-19 ou b eak, excep o a sho ime a almos he end o he e e pe iod
in he i s wa e o his pandemic. The lip poin in he e e pe iod is consis en wi h
Pagano e al. (2023).
Gene ally speaking, when a i m has a high P/E a io, i implies ha in es o s a e
willing o pay a p emium o i s s ock ela i e o i s cu en ea nings. Al hough high P/E
a ios signal g ow h expec a ions, hey also in oduce isk. In es o s should ca e ully ake
hese isks in o accoun in hei in es men decisions. Simply, a i m wi h a high P/E
a io can be seen as isky o se e al easons: (i) Unce ain y: The s ock p ice may su e i
he company ails o mee hose expec a ions. (ii) Ma ke Sen imen : Any nega i e news
can lead o a sha p decline in he p ice o s ock wi h highe expec a ions. Then, in es o
sen imen plays an impo an ole. (iii) Vola ili y: The p ice o s ocks wi h high P/E a ios
eac s mo e s ongly o ma ke e en s. (i ) Missed Expec a ions: I is disappoin ing o
in es o s i he company loses i s g ow h a ge s, leading o a po en ial sell-o .
Economies 2025,13, 123 31 o 35
Table A5. Financial a ios and ca ego iza ion:Da a sou ce: Financial a ios, WRDS da abase.
Financial Ra io Va iable Name Ca ego y
Capi aliza ion Ra io capi al_ a io Capi aliza ion
Common Equi y/In es ed Capi al equi y_in cap Capi aliza ion
Long- e m Deb /In es ed Capi al deb _in cap Capi aliza ion
To al Deb /In es ed Capi al o deb _in cap Capi aliza ion
Asse Tu no e a _ u n E iciency
In en o y Tu no e in _ u n E iciency
Payables Tu no e pay_ u n E iciency
Recei ables Tu no e ec _ u n E iciency
Sales/S ockholde s Equi y sale_equi y E iciency
Sales/In es ed Capi al sale_in cap E iciency
Sales/Wo king Capi al sale_nwc E iciency
In en o y/Cu en Asse s in _ac Financial Soundness
Recei ables/Cu en Asse s ec _ac Financial Soundness
F ee Cash Flow/Ope a ing Cash Flow c _oc Financial Soundness
Ope a ing CF/Cu en Liabili ies oc _lc Financial Soundness
Cash Flow/To al Deb cash_deb Financial Soundness
Cash Balance/To al Liabili ies cash_l Financial Soundness
Cash-Flow Ma gin c m Financial Soundness
Sho -Te m Deb /To al Deb sho _deb Financial Soundness
P o i Be o e Dep ecia ion/Cu en Liabili ies p o i _lc Financial Soundness
Cu en Liabili ies/To al Liabili ies cu _deb Financial Soundness
To al Deb /EBITDA deb _ebi da Financial Soundness
Long- e m Deb /Book Equi y dl _be Financial Soundness
In e es /A e age Long- e m Deb in _deb Financial Soundness
In e es /A e age To al Deb in _ o deb Financial Soundness
Long- e m Deb /To al Liabili ies l _deb Financial Soundness
To al Liabili ies/To al Tangible Asse s l _ppen Financial Soundness
Cash Con e sion Cycle (Days) cash_con e sion Liquidi y
Cash Ra io cash_ a io Liquidi y
Cu en Ra io cu _ a io Liquidi y
Quick Ra io (Acid Tes ) quick_ a io Liquidi y
Acc uals/A e age Asse s Acc ual O he
Resea ch and De elopmen /Sales RD_SALE O he
A e ising Expenses/Sales ad _sale O he
Labo Expenses/Sales s a _sale O he
E ec i e Tax Ra e e ax P o i abili y
G oss P o i /To al Asse s GP o P o i abili y
A e - ax Re u n on A e age Common Equi y a e _eq P o i abili y
A e - ax Re u n on To al S ockholde s’ Equi y a e _equi y P o i abili y
A e - ax Re u n on In es ed Capi al a e _in capx P o i abili y
G oss P o i Ma gin gpm P o i abili y
Ne P o i Ma gin npm P o i abili y
Ope a ing P o i Ma gin A e Dep ecia ion opmad P o i abili y
Ope a ing P o i Ma gin Be o e Dep ecia ion opmbd P o i abili y

Economies 2025,13, 123 32 o 35
Table A5. Con .
Financial Ra io Va iable Name Ca ego y
P e- ax Re u n on To al Ea ning Asse s p e e _ea na P o i abili y
P e- ax e u n on Ne Ope a ing Asse s p e e _noa P o i abili y
P e- ax P o i Ma gin p pm P o i abili y
Re u n on Asse s oa P o i abili y
Re u n on Capi al Employed oce P o i abili y
Re u n on Equi y oe P o i abili y
To al Deb /Equi y de_ a io Sol ency
To al Deb /To al Asse s deb _asse s Sol ency
To al Deb /To al Asse s deb _a Sol ency
To al Deb /Capi al deb _capi al Sol ency
A e - ax In e es Co e age in co Sol ency
In e es Co e age Ra io in co _ a io Sol ency
Di idend Payou Ra io dp Valua ion
Fo wa d P/E o 1-yea G ow h (PEG) a io PEG_1y o wa d Valua ion
Fo wa d P/E o Long- e m G ow h (PEG) a io PEG_l g o wa d Valua ion
T ailing P/E o G ow h (PEG) a io PEG_ ailing Valua ion
Book/Ma ke bm Valua ion
Shille s Cyclically Adjus ed P/E Ra io capei Valua ion
Di idend Yield di yield Valua ion
En e p ise Value Mul iple e m Valua ion
P ice/Cash low pc Valua ion
P/E (Dilu ed, Excl. EI) pe_exi Valua ion
P/E (Dilu ed, Incl. EI) pe_inc Valua ion
P ice/Ope a ing Ea nings (Basic, Excl. EI) pe_op_basic Valua ion
P ice/Ope a ing Ea nings (Dilu ed, Excl. EI) pe_op_dil Valua ion
P ice/Sales ps Valua ion
P ice/Book p b Valua ion
No es
1
This ype o p e e ence could be e cap u e he in es o s’ p e e ence in an unce ain si ua ion like COVID-19. The esul s o he
calib a ion exe cise suppo his, al hough he Eule equa ion is a gene al o m o powe -u ili y unc ion wi h a speci ic e sion o
EZ p e e ences.
2Te m “ esilience” wi hou men ioning i s ype, e e s o wo kplace in ui ion o esilience.
3
This pape conside s analys s’ ea nings expec a ion as a p oxy o u u e cash lows, ollowing Daadmeh (2024) and Landie and
Thesma (2020).
4
Implici ly, i assumes
C
is equal o p oduc ion (all ou pu is consumed a each ime) and he isky asse pays
D =C
, which is a
claim o agg ega e consump ion in each pe iod .
5
Equa ion (1) is he simpli ied e sion o Equa ion (13) in Campbell (1993), wi h cons an g oss simple e u n on weal h in es ed
om pe iod o pe iod + 1, as an addi ional assump ion o be able o sol e he model analy ically (Appendix A). This can be
conside ed ealis ic due o wo sepa a e pieces o e idence: (1) Ghade i e al. (2022) show he weal h- o-consump ion a io a ies
almos no signi ican ly by ime- a ying belie s. (2) The weal h- o-consump ion a io a ies wi h in e es a es (Lus ig e al.,2013),
and in e es a es did no a ec ei he he ma ke c ash o he ma ke ebound in COVID ime (Cox e al.,2020). Mo eo e , he
model and calib a ion exe cise a e in line wi h Ba o (2006), who ully explains ha he EZW amewo k ends up as simple as he
powe -u ili y se ing, and i is in acco dance wi h a b oade se o asse -p icing ac s.
6To compu e empi ical spec al densi y, his pape conside s Ba le ke nel (e.g., B ockwell and Da is (1991)).
7
The le e ,
s
is used o emphasize ha he o e all con ac ion depends on he s a e o he economy. I is elimina ed o ease in he
es o his subsec ion.
Economies 2025,13, 123 33 o 35
8
S a is ical es s p o ided in he Appendix A(Table A1) gua an ee he exis ence o signi ican egime swi ching in he COVID-19
ou b eak. Table A1 summa izes he esul s o he Likelihood Ra io Tes (LRT) o he linea i y o he model. The null hypo hesis o
linea i y is ejec ed in a o o a nonlinea Ma ko -swi ching model wi h egime shi s.
9To cla i y, he es ima ed economic con ac ion is he i ed alues o MS-AR p ocess, η.
10 Fede al Rese e Bank o S . Louis, Economic Resea ch Di ision.
11 I is impo an o men ion he impac o he gene a ed eg esso on asymp o ic a iance.
12
Table A4 in he appendix guides s a is ical model selec ion, especially con aining he esul s o he Hausman es o e i y he
exis ence o he he e ogeneous e ec .
13 The s a is ical model is Equa ion (8).
14
Implici ly, his pape assumes asymp o ic expec ed e u n whe e he a bi a y pe iod leng h ends o ze o, simila o Ba o (2006).
15
In s anda d li e a u e, EZ pa ame e s,
γ
and
ψ
, a e in e p e ed as isk a e sion and elas ici y o in e empo al subs i u ion,
espec i ely. Howe e , his in e p e a ion may no be s ic ly sa is ied when
γ
di e s om he ecip ocal
ψ
(Ga cia e al. (2006)
and Hansen e al. (2007)). The Eule equa ion and he consequen calib a ion exe cise, as expec ed, highligh ha he model is
based on a special case o powe u ili y wi h a bi o pa ame e elaxa ion (consis en wi h Ba o (2009)).
16 In cases o in e es , he esul s based on he i s en p incipal componen s can be p o ided.
17 In line wi h he in ui ion o inancial-based esilience and i s ole in composi e- inancial esilience index in Daadmeh (2024).
18 All alues a e epo ed in pe cen age e ms.
19
The P/E a io can p esen insigh s in o in es o s’ expec a ions o a i m’s u u e g ow h p ospec s. A high P/E a io implies ha
in es o s an icipa e s ong ea nings g ow h in he u u e, which inc eases he isk o possible missed expec a ions.
20
The s anda d de ini ion o Cash Con e sion Cycle = DIO + DSO
−
DPO. Inc easing DPO, dec easing DSO, o dec easing DIO
esul s in quicke con e sion.
21 The ideal a ge a io may a y by indus y.
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