94 2018, XXI, 4
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DOI: 10.15240/ ul/001/2018-4-007
In oduc ion
The s udy o de l a ion seems o be gaining
e e mo e impo ance. Cen al banks in mos
ad anced economies, including he Eu opean
Cen al Bank and he Czech Na ional Bank,
ha e obse ed CPI in l a ion unning below hei
a ge s o e en in ou igh de l a iona y e i o y.
These cen al banks a gue ha de l a ion should
be a oided a all cos s and employ ex ao dina y
policies such as quan i a i e easing, o eign
exchange in e en ions o nega i e nominal
in e es a es o i gh agains i . As hese
policies ha e no always led o highe economic
g ow h and highe in l a ion, he e ha e been
calls o e en mo e ex ao dina y measu es.
Among hose is a p oposal o abolish cash
money in o de o allow banks o ca y o e he
nega i e in e es a es mo e e i cien ly on hei
deposi o s and s oke in l a ion (see e.g. Bui e ,
(2009) o Rogo (2014)). The e o e, a lo is a
s ake in knowing whe he de l a ion (especially
mild de l a ion) should be a oided by all means.
The e a e subs an ial p oblems wi h s udies
ha ha e ied o assess he ela ionship
be ween economic g ow h and he p ice le el.
Fi s , all o hem ha e used agg ega e da a o
coun ies such as GDP and CPI. While agg ega e
a iables p o ide in o ma ion abou he economy
as a whole, hey canno e eal he po en ial
a ia ion in ou pu and p ices ha akes place
‘inside’ he economy. As a esul , we know e y
li le abou whe he i ms and sec o s wi hin he
economy ace de l a ion and whe e i comes om.
We can also ha dly assess whe he de l a ion-
ecession heo ies hold. Second, episodes o
de l a ion in he agg ega e CPI o in he GDP
de l a o ha e been sca ce in he pas decades.
As a esul , s udies on de l a ion ha e had o
ely on his o ical da a, o en be o e Wo ld Wa I.
Wha e e hese s udies show, hei conclusions
can be c i icized as i ele an , because hey a e
based on ou da ed obse a ions.
In his pape , we ake a di e en app oach.
Ins ead o using agg ega e da a on GDP and
in l a ion, we ocus on sec o da a on p oduc ion
and p ices. Speci i cally, we use da a om he
Czech S a is ical O i ce on p oduc ion, g oss
alue added and p ices in sec o s o he Czech
economy om 1993 o 2015. This da ase has
h ee ad an ages: (1) i is ich in in o ma ion on
i ms’ ou pu and inpu s, (2) i p o ides ecen
obse a ions, and (3) i con ains nume ous
episodes o sec o de l a ion, which would on
he mac oeconomic le el be concealed unde
he agg ega e CPI o de l a o numbe s. We
hink his app oach is no el: we do no know o
ano he s udy ha would analyze de l a ion and
g ow h using sec o da a.
We i nd ha , con a y o common wisdom,
de l a iona y p essu es in he Czech economy
ha e been coming om sec o s wi h inc easing
ou pu and inc easing g oss alue added,
no om he de e io a ing ones. This shows
ha de l
a ion was mos o en g ow h-d i en,
ep esen ing ising p oduc i i y.
This ex p oceeds as ollows. In Sec ion 1,
we p esen he cu en s a e o esea ch
on de l a ion and show i s main d awbacks.
In Sec ion 2, we p esen ou sec o da a
om na ional accoun s. We i s show some
desc ip i e s a is ics in Sec ion 3. We hen
pe o m eg ession analysis in Sec ion 4, whe e
we use he i xed e ec s model and Gene al
Me hod o Momen s es ima ion o eg ess he
g ow h in p oduc ion and g oss alue added on
he g ow h o p ices plus con ol a iables. The
las sec ion concludes he pape .
1. Cu en Resea ch
1.1 Empi ical S udies
The e a e h ee main lines o easoning why
de l a ion is hough by many o be ha m ul
o economic g ow h. Fi s , he expec a ion o
alling p ices may delay spending by consume s
DEFLATION AND OUTPUT ACROSS
SECTORS: RESULTS FOR THE CZECH
REPUBLIC
Pa el Ryska, Pe Sklenář
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and businesses. Fi ms see hei e enues all
and i hey canno adjus wages and o he cos s
acco dingly, hei ma gins sh ink and hey ha e
o lay o wo ke s. Second, o a gi en nominal
in e es a e, de l a ion aises he eal in e es
a e, which in u n migh de e in es men .
Thi d, i he e is signi i can indeb edness in he
economy, de l a ion may cause bank up cies as
i inc eases he eal alue o deb .
Se e al s udies ha e a emp ed o assess
empi ically whe he he alleged link be ween
de l a ion and ecession holds. Bo do and
Redish (2003) es ic hei a en ion o he
Uni ed S a es and Canada in he pe iod 1870-
1913, which was ich in episodes o de l a ion.
They i nd ha p ices did no a ec ou pu . Bo do,
Lane and Redish (2004) add Ge many o he
sample and each a simila conclusion. O he
ecen s udies use long da ase s ha span mo e
han a cen u y and con ain many coun ies.
A keson and Kehoe (2004) conclude om hei
eg ession o ou pu g ow h on g ow h o p ices
ha in he whole sample, he co ela ion is
close o ze o. An excep ion is he subsample o
he G ea Dep ession in he 1930s, whe e he
link was posi i e. Bo io and Fila do (2004) as
well as Bo io e al. (2015) gene ally con i m his
esul . By con as , Gue e o and Pa ke (2006)
lean o he conclusion ha de l a ion is bad
o g ow h, i nding an economically small bu
s a is ically signi i can link. Acco ding o hem,
lagged de l a ion nega i ely a ec s ou pu .
Benhabib and Spiegel (2009) i nd a non-linea
ela ionship be ween de l a ion and ecession.
In ecen yea s, some esea che s ha e
ocused on he link be ween expec ed in l a ion
(o de l a ion) and consump ion. In e es ingly,
hey ha e p oduced s a kly di e en esul s.
Bachmann, Be g and Sims (2015), using ecen
da a on he US economy, e use he hypo hesis
ha he expec a ion o de l a ion leads o lowe
p esen consump ion. By con as , Ichiue and
Nishiguchi (2014) suppo his hypo hesis using
su ey da a on mode n Japan.
O e all, he exis ing empi ical wo k on
de la ion is a he limi ed – which is su p ising
gi en i s impo ance o mone a y policy – and
inconclusi e. As we explain below, he e is
a majo p oblem o applicabili y o he majo i y
o hese s udies o mode n-day mone a y policy.
1.2 ‘Good’ o ‘Bad’ De l a ion?
Two lines o hough can be aced in cu en
mains eam mac oeconomics. The i s g oup
conside s de l a ion decisi ely ha m ul and
s udies ways o a oid i . He e we can include
in l uen ial mac oeconomis s K ugman (1998),
Be nanke (2002) o S ensson (2003).
The second g oup akes a mo e de ailed look
a de l a ion. Bo do and Redish (2003) coined
he e ms ‘good’ and ‘bad’ de l a ion. De l a ion
is o he good ype i is associa ed wi h ising
ou pu . In pa icula , good de l a ion occu s when
i ms in es o dec ease uni cos s and inc ease
ou pu . As a esul , i he economy ope a es
wi h a cons an money supply, consume s buy
an inc eased ou pu wi h he same amoun o
money, so he p ice le el dec eases. This is
a synonym o an ou wa d shi in he agg ega e
supply cu e. This si ua ion is hough o ha e
been ypical o he p e-Wo ld Wa I pe iod.
By con as , bad de l a ion is associa ed wi h
alling ou pu . In his case, de l a ion esul s om
dec easing nominal demand, which canno
be immedia ely passed on o lowe p ices o
inpu s. Fi ms see hei p o i abili y dec ease
and cu p oduc ion. This was mos p obably one
o he cha ac e is ics o he G ea Dep ession o
he 1930s.
O he wo ks adhe ing o his dis inc ion
be ween good and bad de l a ion include
Beckwo h (2007), Bo do and Fila do (2005)
and o a ce ain ex en also Bo io e al. (2015).
The e ms good and bad de l a ion do no
desc ibe causali y – hey only desc ibe
co ela ions. Fo example, bad de l a ion does
no necessa ily mean ha de l a ion causes
alling ou pu . Dec easing p ices may only be
a symp om o alling demand, no he oo cause
i sel . Howe e , he e ms may be use ul in
p ac ice because policymake s y o de e mine
he ype and decide whe he hey should o
should no coun e ac i . I de l a ion esul s om
dec easing nominal demand, cen al banks
conside i undesi able and p e e o o se i
by easing policy. On he con a y, i i esul s
om cheape p oduc ion wi hou di ec link o
demand, cen al banks may be mo e willing o
le such de l a ion un i s cou se. The e o e, i we
i nd ha mos de l a ion going on in he economy
is o he good ype, i may ha e a di ec policy
implica ion.
Fo hese pu poses, he exis ing empi ical
esea ch has a clea disad an age. All he
s udies men ioned in Sec ion 1.1 use only
agg ega e mac oeconomic a iables, mos
o en he GDP and CPI in l a ion. This causes
a ade-o : he agg ega e annual da a do no
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96 2018, XXI, 4
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show almos any yea s wi h de l a ion in he las
decades o mos de eloped economies (Fo
he Czech Republic, oo, he agg ega e p ice
de l a o shows only one yea wi h de l a ion in
he pe iod 1993-2015.). When esea ches wan
o use agg ega e da a and lea n mo e abou
de l a ion, hey ha e o use p e-Wo ld Wa I da a
which a e ich in obse a ions o de l a ion. Bu
hen he esul s a e based on old obse a ions
which may ha e li le ele ance o oday
because mone a y egimes ha e changed,
he e a e s a kly di e en le els o deb , he e is
mo e i nancial in e media ion, e c.
By con as , using sec o da a, we ha e
many episodes o mode n-day de l a ion and
we ci cum en he ade-o . We a e hus be e
equipped o make judgmen s abou a po en ial
link be ween p ices and ou pu and o assess
pa icula de l a ion- ecession heo ies. (Below
we use he e ms in l a ion and de l a ion also
o he change o sec o p ices. Some may
insis ha in l a ion and de l a ion deno e only
agg ega e p ice mo emen s, bu no sec o p ice
mo emen s. Howe e , all agg ega e numbe s
ha e hei sou ces in hei componen s, and
i is p ecisely hese sou ces ha we analyse
below. Thus we use in l a ion and de l a ion in
he b oade sense.)
2. Da a
We use da a om he Czech S a is ical O i ce
(2017). I has comple e da a on 86 sec o s
o he Czech economy as de i ned in na ional
accoun s. The de i ni ion o each indus y is
based on NACE classi i ca ion and alues a e
published in he s a is ics o Na ional Accoun s.
The da a spans om 1993 o 2015.
As we use g ow h in a iables a he
han le els, one ime pe iod d ops ou , so
we ha e 22 ime pe iods. Tha gi es a o al
o 1892 obse a ions. The a iables a e
ou pu p ices (implici p ice de l a o ), ou pu ,
g oss alue added (GVA), employmen and
in e media e inpu s. Ou pu , GVA, employmen
and in e media e inpu s a e a ailable bo h in
nominal and eal e ms, bu in his a icle we
use hem in eal e ms (i.e., in cons an p ices)
as we a e in e es ed in assessing he e ec o
p ices on eal ou pu o i ms.
An impo an ea u e o he NACE
classi i ca ion is ha i does no co e only
sec o s p oducing o i nal consump ion, bu
also sec o s uppe in he p oduc ion chain
– i.e., sec o s p oducing capi al goods and
in e media e inpu s. As a esul , i ms’ ou pu
does no mean only consume goods bough
by consume s, bu also capi al goods bough by
o he i ms.
Fig. 1: P oduc ion and GVA g ow h agains change o p ices
Sou ce: Czech S a is ical O i ce (2017), own compu a ions
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3. Desc ip i e S a is ics
In ou sample, posi i e p ice g ow h p e ails
and accoun s o 80% o all obse a ions (see
Fig. 1). A he same ime, app oxima ely h ee
i hs o obse a ions ha e posi i e g ow h o
p oduc ion and g oss alue added. As a esul ,
oughly hal o obse a ions lie in he op- igh
quad an in Fig. 1. In his sec ion we ocus on
basic s a is ical ela ionships be ween he sign
o p ice change (in l a ion/de l a ion) and he
sign and g ow h a e o p oduc ion o GVA.
In pa icula , we ocus on whe he declines in
p oduc ion a e associa ed wi h de l a ion.
In Tab. 1, we epo he compa ison o
g ow h in p oduc ion and g oss alue added
unde inc easing e sus dec easing p ices.
We also isualize he compa isons wi h densi y
g aphs in Fig. 2. Ou o obse a ions wi h p ice
de l a ion, 69.7% eco ded posi i e g ow h
in eal p oduc ion, while he co esponding
pe cen age o obse a ions wi h in l a ion is only
58.8%. This is also e l ec ed in he a e ages:
he a e age g ow h a e o p oduc ion du ing
episodes o p ice de l a ion is 5.47%, which is
sizably highe han he a e age g ow h wi h
in l a ion (2.85%). The e o e, his p elimina y
obse a ion con adic s he no ion ha de l a ion
is linked o subpa ou pu g ow h. To check his
i nding, we also an a o mal es o equali y
o means. As seen in Tab. 2, he - es ejec s
he null hypo hesis ha he a e age p oduc ion
g ow h unde in l a ion is equal o ha unde
de l a ion, he eby con i ming he i nding. In
con as , he s anda d de ia ions o g ow h
a es a e simila , which is also suppo ed by he
es ing o equali y o a iances.
We pe o med he same analysis also
o eal g oss alue added (see Tab. 1). He e
he be e pe o mance unde de l a ion is
e en mo e p onounced: 77.8% o de l a iona y
obse a ions epo posi i e g ow h in g oss
alue added, while o in l a iona y obse a ions
he pe cen age is only 52.3%. The a e age
g ow h o g oss alue added is 14.1% wi h
de l a ion, while only 0.68% wi h in l a ion. The
di e ence is also con i med by he - es . The
only di e ence wi h g oss alue added as
opposed o p oduc ion is he highe s anda d
de ia ion wi h de l a ion han wi h in l a ion.
The eason o hese a he con incing
i ndings may be he p e alence o ‘good
de l a ion’ in ou sample: he sec o s ha
epo ed p oduc p ice de l a ion could be
p ecisely he ones ha in es ed mos in
p oduc ion and he e o e enabled cheape and
g ea e p oduc ion. Anyway, his p elimina y
look uns agains he claim ha de l a ion ha ms
p ospec s o g ow h.
In he Appendix, we e e se ou pe spec i e
and ask he ques ion how much g ow h in
p ices he e is unde he opposi e scena ios
o ise and all in p oduc ion and GVA.
All da a
In l a ion
De l a ion
Obse a ions 1,892
1,509
383
P oduc ion
obs. wi h p oduc ion inc ease 61.00%
58.80%
69.70%
obs. wi h p oduc ion dec ease 39.00%
41.20%
30.30%
Mean g ow h 3.38 2.85 5.47
S anda d de ia ion o g ow h 12.89 12.71
13.39
G oss alue added
obs. wi h GVA inc ease 57.50%
52.30%
77.80%
obs. wi h GVA dec ease 42.50%
47.70%
22.20%
Mean g ow h 3.40 0.68 14.10
S anda d de ia ion o g ow h 34.86 25.74
57.05
Sou ce: Czech S a is ical O i ce (2017), own compu a ions
Tab. 1: G ow h o p oduc ion and GVA unde in l a ion and de l a ion
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This complemen s ou esul he e ha slowe
p ice g ow h o ou igh de l a ion is accompanied
by quicke ou pu g ow h.
4. Reg ession Analysis
4.1 Time A e ages
As a i s look on co ela ions, we pe o med
a simple eg ession o ime a e ages. We
eg essed a e age annual ou pu g ow h in he
86 sec o s o he Czech economy o e 1993-
2015 on he co esponding a e age annual
p ice g ow h, as seen in Tab. 3.
In wha ollows below, we deno e x he
annual pe cen age change in a iable X.
Tha is, p is he g ow h in p ices, q in eal
ou pu (p oduc ion) and g a in eal g oss
alue added. We es ed he esul s in Tab. 3
o he p esence o he e oscedas ici y and
whene e i was de ec ed we used he Whi e’s
he e oscedas ici y-co ec ed co a iance ma ix.
Tes s a is ic p- alue
P oduc ion
- es o equali y o means 3.44*** <0.001
F- es o equali y o a iances 1.11 0.19
G oss alue added
- es o equali y o means 4.49*** <0.001
F- es o equali y o a iances 4.91*** <0.001
Sou ce: Czech S a is ical O i ce (2017), own compu a ions
No e: We use he Welch - es , i.e., a s anda d unpai ed and wo-sided - es o de e mine whe he he means o p odu-
c ion g ow h unde in l a ion and de l a ion a e equal o each o he . The null hypo hesis is ha he wo means a e equal.
To es he equali y o a iances, we use an F- es , whe e he null hypo hesis is ha he a io o he a iances o he
samples is equal o 1.
No e: The sign *** deno es signi i cance a 1% le el.
Tab. 2: Tes s o equali y o means and a iances
Fig. 2: Densi y o p oduc ion and GVA g ow h unde de l a ion and in l a ion
Sou ce: Czech S a is ical O i ce (2017), own compu a ions
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The eg ession coe i cien on p (pe cen age
g ow h in p ices) is -1.142, signi i can a 1%,
sugges ing ha slowe p ice g ow h has been
associa ed wi h as e ou pu g ow h. As
depic ed in Fig. 3, he e is one dis inc ou lie
on op le . This sec o is he manu ac u ing
o compu e , elec onic and op ical p oduc s.
In e es ingly, i is bo h he sec o wi h he
as es g ow h a e o p oduc ion and he only
sec o wi h a e age annual de l a ion o e 1993-
2015. We also an he eg ession wi hou his
ou lie , bu he nega i e coe i cien and high
s a is ical signi i cance emain (see Tab. 3).
We ied lea ing ou up o 10 mos ex eme
obse a ions, bu he nega i e and s a is ically
signi i can coe i cien o p emained.
We can obse e he gene al pa e n o he
sec o s in he Czech economy om Fig. 3: while
All da a Wi hou ou lie
Coe i cien p- alue Coe i cien p- alue
Reg essing q on:
In e cep 7.082*** <0.001 -6.118*** <0.001
p -1.142*** <0.001 -0.919*** <0.001
Obse a ions
86 85
Adj. R2
0.237
0.167
Reg essing g a on:
In e cep 8.996*** <0.001 8.824*** <0.001
p -1.998*** <0.001 -1.819*** <0.001
Obse a ions
86 85
Adj. R2
0.380
0.323
Sou ce: Czech S a is ical O i ce (2017), own compu a ions
No e: The sign *** deno es signi i cance a 1% le el.
Tab. 3: Time a e ages: Reg ession o a e age annual g ow h in ou pu and GVA
on in l a ion
Fig. 3: Reg essing ime a e ages: (a) Ou pu g ow h on in l a ion, (b) GVA g ow h
on in l a ion (all da a)
Sou ce: Czech S a is ical O i ce (2017), own compu a ions
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he con ac ing sec o s had bo h low and high
in l a ion, booming sec o s ended o ha e lowe
in l a ion and hose ha expanded mos quickly
– wi h g ow h a e o ou pu abo e 10% – had
exclusi ely low in l a ion o ou igh de l a ion.
The esul s sugges ha highe ou pu
g ow h is linked o slowe p ice g ow h, i.e. low
in l a ion o ou igh de l a ion. Howe e , i may
no be e iden wha happens o i ms’ p o i s
as in l a ion slows o u ns in o de l a ion. We
he e o e used g ow h in eal g oss alue added
ins ead o eal ou pu g ow h and eg essed i
on p ice g ow h. The esul s a e e y simila o
hose wi h ou pu g ow h (see Tab. 3 and Fig. 3).
O e all, his e idence oo seems o un
agains he de l a ion- ecession heo ies. In ou
sample, as e ou pu g ow h and p o i g ow h
a e associa ed wi h slowe in l a ion o ou igh
de l a ion. This could sugges ha highe
p oduc ion mos o en esul s om in es men
in o lowe -cos p oduc ion, o which consume s
eac by pu chasing mo e.
4.2 Panel Da a
Two Models
Using panel da a na u ally o e s much mo e
in o ma ion han ime a e ages because
we can make use o he en i e a ia ion o
annual obse a ions. Ou da a a e in he o m
o balanced panel da a and we use he i xed
e ec s model o es ima ion. This model allows
unobse ed sec o -speci i c e ec s o ha e any
co ela ion wi h he explici eg esso s. We
es ima ed he models below using he so-called
‘wi hin es ima ion’.
Gene ally, we use wo economic models
o es ima ion. The i s is an au o eg essi e
dis ibu ed lag (ADL) model which akes
a mac oeconomic app oach o p ices and
p oduc ion. Jus as s udies ci ed in Sec ion 1.1
eg ess GDP g ow h on p ice g ow h (in l a ion
o de l a ion), we eg ess sec o ou pu g ow h
on he espec i e g ow h in ou pu p ices o
he gi en sec o . This di ec ly add esses he
ques ion o co ela ion be ween p ices and
ou pu . We also include lagged a iables. Fo
example, we es ima e
qi = â0 + â1qi -1 + â2 pi + â3 pi -1 + ai + ui (1)
whe e qi is eal ou pu g ow h in sec o i and
yea , pi g ow h in ou pu p ices in he sec o
(bo h in pe cen e ms), ai he sec o -speci i c
unobse ed e ec and ui he e o e m.
The second model, in con as , akes
a mo e mic oeconomic, i m-le el app oach. To
p oduce ou pu , i ms mus employ wo ke s and
buy in e media e inpu s. The e o e, he model
we es ima e is
qi = â0 + b1 pi + â 2empi + â3inpi + ai + ui (2)
whe e emp is g ow h in labou employed
(measu ed in o al hou s wo ked) and inp
g ow h in he olume o in e media e inpu s in
p oduc ion.
The eg esso s include wo usual inpu s in
he neoclassical p oduc ion unc ion ( o why
we exclude capi al K, see ou discussion below)
plus a special e m – he ou pu p ice change
p. P oduc i i y, o e i ciency o p oduc ion, is
usually accoun ed o as a esidual, i.e., wha
emains unexplained in ou pu p oduced i we
ake in o accoun changes in labou , capi al
and in e media e inpu s. Fi ms ypically in es
o ake o he measu es in o de o make
p oduc ion mo e e i cien . A e hey do so, hey
can p oduce mo e and wi h lowe cos s, so
hey can o e hei p oduc s mo e cheaply and
each mo e cus ome s. I his is he case, hen
he ou pu p ice P ac s as a p oxy o e i ciency.
The lowe is he cos o p oduc ion, he lowe is
he obse ed p ice P. The e o e, p ice g ow h
p is no only a a iable ha we add o i nd ou
abou i s co ela ion wi h ou pu g ow h q, bu i
also has a conc e e economic in e p e a ion as
a p oxy o he e i ciency o p oduc ion.
Equa ion 1 abo e con ains he lagged
dependen a iable qi -1 among eg esso s.
As a esul , he i xed-e ec s es ima o is
gene ally no consis en . As Woold idge (2002)
shows, he bias alls a a a e 1/T as T g ows,
and o a ime dimension high enough, he
inconsis ency would be negligible. We hink ha
wi h ou T = 22, we do ha e a T high enough
o be su e ha mos o he bias disappea s.
Howe e , as a check we also pe o m Gene al
Me hod o Momen s (GMM) es ima ion in
equa ions whe e he e a e lagged dependen
a iables. Ou GMM es ima ion ollows A ellano
and Bond’s (1991) wo-s ep p ocedu e and
we use lags o o de 2 o 5 o he dependen
a iable as ins umen al a iables. Finally, in
he i xed e ec s models below, each eg ession
was es ed o he e oscedas ici y and se ial
co ela ion. When ei he o hese was de ec ed,
a obus a iance ma ix es ima o was used o
co ec he a iances and es s a is ics.
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101
4, XXI, 2018
Economics
Resul s: Mac oeconomic App oach
In he i s , mac oeconomic app oach, we
es ima e he e ec o in l a ion on ou pu g ow h
and GVA g ow h in an au o eg essi e dis ibu ed
lag model. Tab. 4 shows ha con empo aneous
in l a ion p is nega i ely linked wi h ou pu
g ow h, con i ming ou i ndings om Sec ion
4.1 abo e. The GMM es ima ion b ings an
es ima e o he coe i cien o p e y simila o
he i xed e ec s es ima ion (-0.303 s. -0.293)
and con i ms i s s a is ical signi i cance. By
con as , he coe i cien o p -1 is economically
and s a is ically less signi i can , bo h acco ding
o i xed e ec s es ima ion and GMM. Simila ly
o ou pu , in l a ion is nega i ely linked o he
g ow h in g oss alue added o i ms (see he
lowe hal o Tab. 4).
The only di e ence is ha he magni ude
o he coe i cien o p is bigge o g oss alue
added han o ou pu as dependen a iable.
This is unde s andable since i ms usually ha e
ope a ing le e age: a ise in ou pu ( e enues) by
1% causes a ise in g oss p o i o mo e han 1%.
Resul s: P oduc ion-Func ion App oach
In he second, mo e mic oeconomic app oach,
we use ypical inpu s in o p oduc ion unc ion
as con ol a iables o assessing he impac
o in l a ion on ou pu g ow h. These should
be mo e powe ul con ol a iables as hey
a e di ec ly linked o ou pu . We es ima e
he equa ion wi h g ow h in labou emp ( o al
hou s wo ked) and g ow h in he olume o
in e media e inpu s inp as con ols.
We ha e also added g ow h in g oss capi al
s ock k o imi a e mo e he adi ional p oduc ion
unc ion Y = (L, K). Because da a on capi al
s ock ha e poo e a ailabili y han o he da a,
we used an al e na i e sou ce om he OECD
(2016). I is bo h na owe (only 57 sec o s) and
sho e (1995-2009) han ou main da ase , so
i has much ewe obse a ions (798). Resul s
om his enla ged eg ession ha includes
k a e no ma e ially di e en om hose epo ed
in Tab. 5 and we do no epo hem he e.
As expec ed, his model shows a much
highe i as Adj. R2 is as high as 0.638 in
he ou pu eg ession in Tab. 5. And again,
in l a ion nega i ely a ec s ou pu g ow h
(-0.476) wi h high s a is ical signi i cance.
Labou and in e media e inpu s also ha e he
expec ed signs and high signi i cance. In he
GVA eg ession, in l a ion also has a nega i e
coe i cien and he coe i cien is again g ea e
in absolu e magni ude. In e es ingly, while he
labou inpu has a posi i e and s a is ically
signi i can impac on GVA, in e media e inpu s
lose hei signi i cance.
In e p e a ion
The empi ical esul s b ing, in ou iew, wo
impo an i ndings.
Fixed e ec s GMM
Coe i cien p- alue Coe i cien p- alue
Reg essing q on:
q -1 0.012 0.696 0.042 0.231
p -0.293*** 0.003 -0.303** 0.014
p -1 0.136* 0.052 0.110 0.121
Obse a ions
1,806 1,720
Adj. R2
0.017
-
Reg essing g a on:
g a -1 -0.086*** 0.002 -0.178 0.236
p -1.614*** <0.001 -1.768*** <0.001
p -1 0.614 0.173 0.393 0.617
Obse a ions
1,806 1,720
Adj. R2
0.068
-
Sou ce: Czech S a is ical O i ce (2017), own compu a ions
No e: The sign * deno es s a is ical signi i cance a 10%, ** a 5% and *** a 1% le el.
Tab. 4: ADL: Reg ession o g ow h in ou pu and GVA on in l a ion
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102 2018, XXI, 4
Ekonomie
Fi s ly, he nega i e ela ionship be ween
g ow h in ou pu and g ow h in p ices sugges s
ha obse ed de l a ion has been p edominan ly
o he ‘good’ ype. I alling p ices esul ed
om alling nominal demand, i ms would no
espond by inc easing p oduc ion – on he
con a y, hey would cu i , as he ‘bad de l a ion’
hypo hesis goes. Hence, we would obse e
a posi i e co ela ion be ween p and q.
The al e na i e hypo hesis is ha as i ms
in es and imp o e e i ciency, hey manage
o cu uni cos s and p ices. This allows
hem o sell mo e p oduc s, i.e., each new
ma ginal demand h ough lowe p ices. This
‘good de l a ion’ hypo hesis is consis en wi h
ou i ndings – we see epea edly a nega i e
ela ionship be ween p and q.
I could be a gued ha he nega i e
ela ionship be ween p and q may in some
mo e in l a iona y yea s e l ec a he he
compa ison o high e sus low in l a ion han
in l a ion e sus de l a ion. Tha may be ue.
The shi o he agg ega e demand cu e – o
example, h ough cen al bank easing – may
mo e he whole mass o obse a ions o he
igh in Fig. 3, b inging many o hem ou o
he de l a iona y sec ion. Symme ically, lack
o agg ega e nominal demand may push hem
o he le , which was he case o ins ance
in 2009 when he economy as a whole had
a 1.4% de l a ion (measu ed as ou pu de l a o ).
Howe e , a he han ocusing on he posi ion o
he mass o obse a ions, we a e in e es ed in
he slope o he eg ession line – ha is, in he
shape o he mass. I s nega i e slope sugges s
ha he endency o cu p ices o a leas ha e
slowe p ice inc eases han he a e age is
associa ed wi h g owing i ms, no declining
ones. O e all, we a e no claiming ha ‘bad
de l a ion’ does no exis o ha i canno be
ha m ul. We a e only showing e idence ha
he e is much mo e ‘good de l a ion’ han ‘bad
de l a ion’ in ou sample.
Secondly, using g oss alue added in
addi ion o ou pu , we ha e shown ha lowe
p ices a e no only associa ed wi h g ea e
ou pu , bu also wi h g ea e g oss p o i o
i ms. Ou pu in i sel is no he i ms’ goal, bu
p o i is. I i
ms in es o inc ease p oduc ion
and cu p ices, hey also succeed in inc easing
p o i s, ou esul s show. This i nding is impo an
because one line o easoning (s a ing wi h
Fishe , 1933) is ha de l a ion o oo low in l a ion
ul ima ely e odes i ms’ p o i s and leads hem o
bank up cies. Ou esul s show o he wise, again
p o iding suppo o he case ha de l a ion in
ou sample s ems om i ms’ own ini ia i es, no
om nega i e shocks ha would squeeze p o i s.
As poin ed ou in Sec ion 2, he sec o s
used a e no only hose ha p oduce consume
Fixed e ec s
Coe i cien p- alue
Reg essing q on:
p -0.476*** <0.001
emp 0.280*** <0.001
inp 0.582*** <0.001
Obse a ions
1,700
Adj. R2
0.638
Reg essing g a
on:
p -1.663*** <0.001
emp 0.889*** <0.001
inp 0.062 0.637
Obse a ions
1,700
Adj. R2
0.112
Sou ce: Czech S a is ical O i ce (2017), own compu a ions
No e: The sign *** deno es signi i cance a 1% le el.
Tab. 5: P oduc ion unc ion: Reg ession o g ow h in ou pu and GVA on in l a ion
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