A Monte Carlo method simulation of the European funds that can be accessed by Romania in 2014-2020
Abstract
The authors dealt with finding some relevant simulation solutions for the value of the European funds that can be accessed by Romania in the second budget cycle (2014-2020) of the European Union (EU), in which the national economy is participating after the 2007 accession. The article presents, in a brief conceptual introduction, the option for simulation, not only as economical and statistical alternative but also as conceptual and technical method, followed by an analysis section for the EU funds accessed by Romania in the 2007-2013 financial period and in the first three years of 2014-2020 financial period, with a role in generating hypotheses and scenarios of a type of modelling the process of accessing and specific absorption (including all types of rates, from the current absorption rate to the actual rate, with revenue in advance, etc.). A methodology section describes the rationale for selecting the method of simulation as Monte Carlo, and also the main hypotheses, detailed scenarios and integrated characteristic variables. The scenario-making eventually shaped three options by combining criteria of stability/instability, nuanced by optimistic/ pessimistic type scenarios. The analysis of the variables described by a probability distribution was conducted statistically on several types of samples simulated by the Monte Carlo method, from 100 draws to 200; 300; 400; and finally 500 and 1,000 draws. A presentation of the final simulation results and a number of major comments regarding their calibration, confrontation, clarity and statistical analysis, together with some final remarks as conclusions, limitations and perspectives, end the research approach.
Full text
19
3, XX, 2017
Economics
DOI: 10.15240/ ul/001/2017-3-002
In oduc ion
In he economic, econome ic and demog aphic
li e a u e, he e coexis a ew concep s,
seemingly simila bu signi i can ly di e en ,
whose pu poses a e p edic i e, in ended
o es uc u e and op imize, bu also om
a na u al scien i i c need o know, unde s and,
p edic o p e en p ocesses and sys ems; such
concep s as o ecas ing, es ima ion, designing,
assessing, planning, p edic ion and p ospec ing
(Să oiu, 2007, p. 351) and, las bu no leas ,
he simula ion.
P ognosis and p edic ion a ose om he
need o an icipa e he ends o e olu ion o
he e ms o a ch onological se ies o da a, and
a e e l ec ed in he examina ion o he end,
he pe iodic oscilla ions and he pu ely andom
componen , ollowing he con ou o he cycle
o he p ima y phenomenon o he pas pe iod,
and also in iden i ying he ac o s o signi i can
ac ion in he u u e. The i s concep , p ognosis,
o iginally de i ned a o m o p e-knowledge
o an icipa ion o he e olu ion in ime o
a numbe o p ocesses and sys ems, u he
cha ac e ized by mo e objec i i y and scien i i c
in eg i y, wi h p ac ically ep oducible alences,
and gene a ed an in eg a ed se o me hods
and speci i c echniques. A ecognized aspec ,
which was equen ly p o ed by he accu acy o
p ognoses o o ecas s, is ha he accu acy o i s
esul s depends on he quali y o da a analysis
and subsequen e o s, as well as he quali y o
he hypo heses. P edic ion is a e m aken o e
om F ench s a is ics and demog aphy, and
had a mo e subjec i e and in ui i e concep ual
ou line, also ha ing e en accen s o non-
ep oducibili y when de i ning he likelihood
o he subsequen eme gence o e olu ion
o p ocesses and sys ems (demog aphic,
economic, social, e c.) in he analysis o ce ain
in o ma ion owned a a ce ain ime (Kucha a y
& De Guio, 2005; 2012).
E en i one e y ca e ully chooses he
e ms o ecas , p edic ion, o p ojec ion,
he e immedia ely a ise o he necessa y
op ions, as he concep will be accompanied
by a new de i ning cha ac e is ic: explo a o y,
enden ial, oscilla o y, no ma i e, global,
analy ical, undamen al, sequen ial e c.
Planning, p ojec ion and es ima ion lend
a ious nuances o he analysis o he p ocess
and sys em, d awing on hypo heses ha a e
s uc u al o mos ly in e nal o he sys em,
and p edic ion, which „p esupposes eaching
a empo al a ge , owa ds which an economic
phenomenon con e ges“ (Să oiu, 2016),
is ocused on he ou come o he ex ended
p ocess o sys em, in ol ing he ac ion o
hei ex e nal ac o s as well. I he p ospec o
pe spec i e admi s o hold pe haps he agues
con ou o he u u e, encompassing he eal o
a signi i can ex en , no less han he po en ial
(which some imes becomes e en i c ional),
p ospec ion o p ospec ology complemen s
he sense o p edic ion o o ecas in he spi i
o quan i i ca ion and he ac ion unde aken in
o de o achie e i (wi h igo ous e alua ions o
he p ospec ing e o s).
De i ned as „scien i i c me hod, esea ch
o eaching echnique ha ep oduces ac ual
e en s and p ocesses unde es condi ions;
de eloping a simula ion is o en a highly
complex ma hema ical p ocess. Ini ially a se o
ules, ela ionships, and ope a ing p ocedu es
a e speci i ed, along wi h o he a iables“ in
Encyclopaedia B i annica (2012), simula ion
was p e e ed by he au ho s, s a ing om i s
abili y o p o ide a complex mac o- i nancial
o ecas o p obable u u e unds ( e enues),
bu also he bene i s p o ided by any so wa e
de eloped wi h he pu pose o simula ion, which
is ocused on modelling eal p ocesses, om
ma hema ical ansposi ion, and i nalized by
es ing s a is ical hypo heses and alida ions/
A MONTE CARLO METHOD SIMULATION
OF THE EUROPEAN FUNDS THAT CAN BE
ACCESSED BY ROMANIA IN 2014-2020
Gheo ghe Să oiu, Emil Bu escu, Vasile Dinu, Ligian Tudo oiu
EM_3_2017.indd 19EM_3_2017.indd 19 7.9.2017 10:34:037.9.2017 10:34:03
20 2017, XX, 3
Ekonomie
in alida ions o models o ce ain use ulness and
e ec i e op imiza ion alences, and clea u ili y
in es ablishing majo i nancial p og ams o plans,
as well as he budge s ela ed o hem (Ma e ick,
2016). The essen ial s eps o he simula ion,
which we e pu sued in his a icle, we e
connec ed wi h: a) p oblem de i ni ion, concep ual
selec ion and design o he s udy/ esea ch; b)
de i ni ion and de elopmen o he p obabilis ic
model o he economic p ocess; c) he choice
o he me hod, o mula ion o hypo heses, he
de i ni ion o a iables and e ec ing he economic
simula ion p ocess; d) he ini ial calib a ion o
he simula ion o he economic p ocess; e) he
s a is ical analysis o he simula ion (including
p edic abili y, sensi i i y and accu acy, o e o
le el); ) he implemen a ion o he esul s o he
simula ion, iden i ying he limi s o he p ocess,
also when modi ying he p ocedu al eali y, he
speci i ca ion o he need o egula ly e-de elop
he model, e c.
The eminde o he pape is classical and
qui e succinc , as a b ie concep ual in oduc ion
is ollowed by a sec ion de o ed o he unds
accessed by Romania om he Eu opean Union
(EU), as a modelled p ocess, hen he e is he
desc ip ion o he me hod o simula ion used
(i.e. Mon e Ca lo), and also he o mula ion
o hypo heses, scena ios and a iables. The
simula ion esul s a e p esen ed and discussed
sepa a ely in he a icle, and a se o conclusions,
limi a ions and pe spec i es conclude he
a icula ed app oach o he esea ch.
1. Value and Abso p ion Ra e o he
Eu opean Funds Accessed by
Romania in he Fi s Budge
Pe iod (2007-2013), and he Fi s
Two Yea s o he Second One
One o he majo p oblems o he Romanian
economy is closely linked, among o he
hings, o i s endency o abso b Eu opean
unds (Să oiu e al., 2006). In he i s i nancial
o budge pe iod o he Eu opean unds o
Romania, be ween 2007 and 2013, acco ding
o la es a ailable da a, he na ional economy
eco ded, in all he h ee indica o s o all he
speci i c abso p ion a es, alues placed well
below he EU a e age – by a ound 10% on
a e age (wi h an e ec i e a e o 79.23%,
a cu en abso p ion a e o 82.93%, and an
o e all abso p ion a e o 90.44%, which also
includes he amoun s ecei ed om he EU in
ad ance, as o 31s Janua y 2017). A he end
o 2015, he gap was mo e han 20% (69.9%,
compa ed o he Eu opean a e age o 89.9%),
and he sus ained e o s in 2016 ha e hal ed
ha gap. The e ec i e abso p ion o he i s
EU budge pe iod, de ailed by ope a ional
p og ams, is placed wi hin a ange o alues
going om 73.37% o 86% (Tab. 1). The same
s uc u e o he pe iod 2014-2020 is ma ked
by changes cen ed on he egional expansion
and human capi al de elopmen , while he e
is a con ac ion o he unds alloca ed o
compe i i eness:
2014-2020 2007-2013
Ope a ional p og ams mil. eu o Ope a ional p og ams mil. eu o
E ec i e
abso p ion
a e %
Regional de elopmen 6,600.00 Regional de elopmen 3,966.02 85.04
La ge in as uc u e
9,418.52
En i onmen 4,412.47 78.48
T anspo a ion 4,288.13 74.63
Compe i i eness 1,329.79 Compe i i eness 2,536.64 85.94
Human capi al 4,326.84 Human esou ces 3,476.14 73.37
De elopmen o adminis a i e
capaci y 553.19 De elopmen o adminis a i e
capaci y 208.00 82.00
Technical assis ance 212.77 Technical assis ance 170.23 86.00
Helping disad an aged people 441.00
To al 22,882.11 To al 19,057.65 79.23
Sou ce: own based on Annual Fiscal Repo , 2015 (h p://www.consiliul i scal. o/Rapo anualCF2015.pd )
Tab. 1: Eu opean unds alloca ed o Romania in 2014-2020 and 2007-2013
EM_3_2017.indd 20EM_3_2017.indd 20 7.9.2017 10:34:037.9.2017 10:34:03
21
3, XX, 2017
Economics
Compa ing he o e all abso p ion o he
cu en a e, he la e has mo e pola ized
s uc u al alues, namely om a minimum
o 73.37% o 113.42%, ou lining possible
hypo heses and scena ios o boos ing he
unds ha can be accessed om he EU by
Romania’s economy, in he pe iod 2014-2020
(Tab. 2).
Use ul in o ma ion o he simula ion
o annual o ecas o he unds ha can be
accessed by Romania in he u u e occu in he
abso p ion a e con on ed wi h he EU a e age
o he las pe iod 2007-2013 (Fig. 1).
The EU’s new budge pe iod, as a as he
accessing o Eu opean unds is conce ned, is
placed wi hin ends simila o he one abo e,
Ope a ional p og ams CAR EAR GAR (in ad ance)
Regional de elopmen – POR 85.04 85.04 93.50
En i onmen – POS 78.55 78.49 90.29
T anspo a ion – POS 77.31 74.63 86.88
Compe i i eness – CCE POS 105.47 85.94 95.00
Human esou ces – POS DRU 73.37 73.37 87.49
De eloping adminis a i e capaci y – PODCA 98.66 82.00 95.00
Technical assis ance – POAT 113.42 86.00 95.00
To al 82.93 79.23 90.44
Sou ces: own based on h p://www. ondu i-ue. o/21- anspa en a/s adiul-abso b iei/26-s adiul-abso b iei and
h p://www.consiliul i scal. o/Rapo anualCF2015.pd
Tab. 2: Cu en Abso p ion Ra e – CAR, E ec i e Abso p ion Ra e – EAR and Gene al
Abso p ion Ra e – GAR (2007-2013) in Romania (%)
Fig. 1: The Romanian na ional a e o abso p ion compa ed wi h he Eu opean annual
a e age in he pe iod 2007-2013 (including epo s om 2014 o 2016)
Sou ce: oown based on h p://www.consiliul i scal. o/Rapo anualCF2015.pd
No e: So wa e used EViews
EM_3_2017.indd 21EM_3_2017.indd 21 7.9.2017 10:34:037.9.2017 10:34:03
22 2017, XX, 3
Ekonomie
only i has a much lowe ini ial le el in he i s
h ee yea s, bo h in Romania and in he EU
(Fig. 2).
Some s a is ical aspec s cha ac e is ic o
he i s EU i nancial pe iod, in which Romania
is also pa icipa ing as a membe s a e,
compa ed o he speci i cs o he EU a e age,
desc ibe an annual e olu iona y he e ogenei y,
acco ding o a coe i cien o uni o mi y o he
annual abso p ion a e o 72.8%, a endency o
asymme y and a modal placemen comple ely
opposi e o he a e age abso p ion end o
he Eu opean unds (Fig. 3), in pa allel wi h
signi i can gaps, comple ely opposi e du ing he
ini ial and i nal abso p ion ( he igh -hand g aph
iden i i es a ans o ma ion o he gap in o an
ad ance, since 2013, in a ou o Romania).
Fig. 2: The Romanian annual abso p ion a e compa ed wi h he Eu opean annual
a e age in 2014-2016
Sou ce: own based on h p://www. ondu i-ue. o/21- anspa en a/s adiul-abso b iei/26-s adiul-abso b ie
RO EU
Mean 9.259000 9.300000
Median 7.350000 10.525000
Maximum 18.690000 16.100000
Minimum 2.200000 1.980000
S d. De . 6.741375 4.776861
Skewness 0.309213 -0.318353
Ku osis 1.421116 1.796645
Ja que-Be a 1.198051 0.772274
P obabili y 0.549347 0.679677
Sum 92.590000 93.000000
Sum Sq. De . 409.015300 205.365600
Obse a ions 10.000000 10.000000
Sou ce: Sou ce: The annual da a o he e ec i e a e o abso p ion o EU and RO
we e p ocessed by he au ho s wi h he so wa e package EViews
Fig. 3: Desc ip i e s a is ics o he da a se ies o annual abso p ion a e in he pe iod
2007-2016, and ecupe a i e dynamics o gaps (RO–EU)
EM_3_2017.indd 22EM_3_2017.indd 22 7.9.2017 10:34:037.9.2017 10:34:03
23
3, XX, 2017
Economics
Un o una ely, he e o o making up o he
abso p ion lags be ween RO and EU ou lines
no only wo no mal dis ibu ions ha a e
comple ely opposi e, as a dominan o small and
la ge a ios, Skewness, Ku osis and impac o
he modal a ea (Fig. 4), bu also a weak link, in
keeping wi h he alue o he speci i c a io R in
he co ela ion ma ix, wi h p edic i e alences,
be ween he dynamics o he abso p ion a e in
he EU and in RO (Tab. 3).
Al hough in alida ed by es ing (F-s a is ic
= 1.654, compa ed wi h F- heo e ical = 4.96
o α = 0.05), due o he small numbe o
yea s in he i s budge cycle (10 e ms), he
ela ionship be ween he wo a iables emains
o he ype “bidi ec ional and i e a i e, gi en by
he simul anei y o in e ac ion and adap a ion
o speci i c ac o s” (K i okapić & Jaško, 2015),
and can delinea e, in u u e, a co ela ion able
o gene a e, by using he so wa e package
EViews, an es ima ed model o p edic ion o
he na ional abso p ion o Eu opean unds
(RO) compa ed o he EU a e age, de i ned by
a linea unc ion ha appea s o be usable and
use ul:
RO = 3.826 + 0.584 EU + εi (1)
No e: In he limi ed se ies o alues in he pe iod
2007-2015 he pa ame e s a e signi i can ly
di e en (RO = -2.008 + 1.031 EU + εi), which
highligh s he posi i e dis o ion c ea ed in
2016, as an addi ional yea o making up o
he lag in he abso p ion o Eu opean unds by
Romania compa ed o he EU a e age.
Fig. 4: No malized Ke nel dis ibu ion o he wo da a se ies o he abso p ion a e
in RO (le ) and EU ( igh )
Sou ce: da a om Fig. 3 (own)
No e: So wa e used – EViews
EU RO
EU 1.000000 0.413927
RO 0.413927 1.000000
Sou ce: own
No e: So wa e used – EViews. In he es ic ed se ies 2007-2015, he alue o R is signi i can ly di e en (0.767987),
which emphasizes he impo ance o he yea 2016 as an addi ional yea o eco e y o he abso p ion o Eu opean unds
by Romania h ough a high abso p ion a e (18.69%).
Tab. 3: Co ela ion ma ix
EM_3_2017.indd 23EM_3_2017.indd 23 7.9.2017 10:34:047.9.2017 10:34:04
24 2017, XX, 3
Ekonomie
The p e ious classical model, cen ed on an
incipien co ela ion, and esul ing om a small
se o da a, is in alida ed by he s Fishe and
Du bin-Wa son es , as well as he signi i can
esidual (εi) he e ogenei y (Dob escu, 2015),
esul ing om an e olu ion abno mali y in
acco dance wi h he a e age esidual alue
o 0.645 and an S d. de . o 4.58, which,
oge he , exclude a p edic i e eco e y, by he
he e ogenei y achie ed (Tab. 4).
Gi en he expe ience o he i s i nancial
pe iod o he EU unds o Romania (2007-2013),
as a coun y which has concluded an accession
p ocess, ollowed by one o ha ing access o
he Eu opean unds, and also om a s a wi h
a gap ela i ely simila in he second budge
pe iod (2014-2020), we can make assump ions
and scena ios as o some de elopmen s, ei he
s able o uns able, op imis ic o pessimis ic, by
making use o he Mon e Ca lo me hod, and
hus shaping a complex simula ion o he le el
o EU unding ha can be accessed by he
na ional economy in he u u e.
2. The Me hod, he Hypo heses,
he Scena ios and he Va iables
o he Simula ion
The absence o a classical econome ic model
o o ecas ing ha can be ully alida ed, due
o he lack o a comp ehensi e da abase o e
an acknowledged minimum o e ms needed
(e.g. he Du bin–Wa son es , which equi es
a se ies o da a o a leas 15 e ms, being
ele an in his espec ) equi ed he au ho s
o build and make use o ano he solu ion, i.e.
he al e na i e o simula ion using he Mon e
Ca lo me hod. The p ac ical need may equi e
an es ima e, o ecas o decision in signi i can
si ua ions o unce ain y, which, acco ding o
se e al opinions and EViews o he scien i i c
li e a u e o he las wo decades (Jackel, 2002;
Glasse man, 2004; Robe & Casella, 2004;
Del Mo al, Douce , & Jas a, 2006; Mun, 2006;
C eal, 2012) conduces o he implemen a ion o
o he me hods, known as me hods o educing
a iance, and which, beyond s a is ical and
ma hema ical op imiza ion, mainly bene i om
dynamic simula ion (Ța ța ulea e al., 2016),
including he Mon e Ca lo me hod as a case
in poin . Subs i u ing a alue o he mean
ype, quan i i ed in a de e minis ic manne as
pa o he classical s a is ical hinking, wi h he
in e en ia ion, wi hin a con i dence in e al, o
a p obabilis ically simula ed a iable such as ha
o Eu opean unds accessed, clea ly ou lines –
h ough placing emphasis on gene a ing andom
samples ocused on sys ema ic d aws, alongside
he desc ip i e s a is ical p esen a ion o he
dis ibu ions esul ing om he andom d aws o
independen a iables, in es iga ed and es ed
in ela ion o he dis ibu ional conco dance
(Dinu, Să oiu, & Dabija, 2016) – he speci i cs o
applying he me hod o his a icle.
Gene a ion o samples was ini ially
pe o med wi h he pu pose o calib a ion
(samples o 100 o 200 d aws), dis ibu ionally
analyzing he esul s in e ms o dispe sion,
asymme y (skewness), aul ing (ku osis),
and especially no mali y ( he Ja que-Be a es
o J-B es ), and subsequen ly wi h he ole
o s abilizing and i nal in e p e a ion o he
simula ion (500 o 1,000 d aws). A
p e ious
analysis (2007-2013), unde gone by he au ho s,
o he phenomenon o abso p ion o Eu opean
unds by Romania (RO) has o a ce ain ex en
simpli i ed he pa allel iden i i ca ion o andom
a iables wi h g ea e sensi i i y. The op ion
o wo independen a iables, analyzed and
p obabilis ically con i gu ed in o de o do he
simula ion, was an incipien one, whose
aim was o e-check hei sensi i i y and he
ins abili y simula ion (Să oiu, Bu escu, &
Tudo oiu, 2017). The i s o he wo a iables
desc ibed and analyzed in he beginning,
named unds alloca ed (FAi – in billion eu os),
was accompanied by he abso p ion a e o
he EU unds (RAi – in coe i cien s and/o
pe cen ages), and i was i nally subjec ed o
a p ocess o disin eg a ion, which s a ed om
2007 2008 2009 2010 2011 2012 2013 2014 2015 2016
-7.32 -0.9 -0.9 0.33 2.83 3.11 4.32 6.8 2.12 -5.48
Sou ce: own
No e: So wa e used – EViews
Tab. 4: Residual e olu ion (εi) in he model ROi = 3.826 + 0.584 EUi + εi
EM_3_2017.indd 24EM_3_2017.indd 24 7.9.2017 10:34:047.9.2017 10:34:04
25
3, XX, 2017
Economics
he complex eali y o conc e e building up,
i.e. om he se en independen a iables ha
gene a e his agg ega e a iable, in keeping wi h
he ope a ional p og ammes ha a e likely o be
accessed by he Romanian economy be ween
2014 and 2020, o 2014 o 2022 (in acco dance
wi h he empo al logic o he Eu opean p ojec
in n+2 yea s): i) egional de elopmen – POR;
ii) la ge in as uc u e – PIM; iii) compe i i eness –
POC; i ) human capi al – POCU; ) de elopmen
o adminis a i e capaci y – POCA; i) echnical
assis ance – POAT; ii) helping disad an aged
people – POAD.
The simula ion by means o he Mon e Ca lo
me hod also included an index o ins abili y
o he EU unds accessed in an agg ega ion
algo i hm o TFA (To al Funds Accessed),
ocused on wo a iables, he alloca ed unds
(FAi), and he abso p ion a e o he Eu opean
unds by Romania’s economy (RAi), exp essed
acco ding o he ela ion below:
(2)
The hypo heses o he applica ion o he
Mon e Ca lo simula ion me hod o he EU unds
ha can be accessed by Romania in he budge
pe iod 2014-2020 we e di ided in o h ee
s ages o de ailed b eakdown, o disin eg a ion
o he a iables:
I.1. he es ic ed hypo hesis A (Tab. 5)
– con aining wo independen a iables wi h
Va iable Funds alloca ed
(FAi – in billion eu os)
Va iable Abso p ion a e o he
EU unds (as pe cen age)
V1 = FAi whe e i = 3 P obabili y V2 = Rai whe e i = 5 P obabili y
21.50 0.20 89.0 % 0.10
22.40 0.50 92.0% 0.20
23.00 0.30 93.0% 0.40
B eakdown o a ian s in 3/5 a io. 93.5% 0.20
In e al ex ended o a iable 2 94.0% 0.10
Sou ce: own based on h p://www. ondu i-ue. o/21- anspa en a/s adiul-abso b iei/26-s adiul-abso b iei
and h p://www.consiliul i scal. o/Rapo anualCF2015.pd
No e: Sou ces we e analysed by he au ho s and ep esen ed he benchma ks o he abso p ion a es in keeping wi h he
i s i nancial pe iod o Romania (cu en le el in 2015, 2016) and he e ec i e Eu opean a e age le el wi h ex ension
on wo le els.
Tab. 5: Baseline a iables made use o in simula ing hypo hesis 1 (I.1 o A)
Va iable Funds alloca ed
(FAi – in billion eu os)
Va iable Abso p ion a e o he
EU unds (as pe cen age)
V1 = FAi whe e i = 3 P obabili y V2 = Rai whe e i = 5 P obabili y
22.00 0.10 88.0% 0.10
22.40 0.10 90.0% 0.30
22.80 0.30 93.0% 0.40
22.90 0.30 95.0% 0.20
23.00 0.20 B eakdown o a ian s in 5/4 a io.
Sou ce: own based on h p://www. ondu i-ue. o/21- anspa en a/s adiul-abso b iei/26-s adiul-abso b iei
and h p://www.consiliul i scal. o/Rapo anualCF2015.pd
No e: Sou ces we e analysed by he au ho s and ep esen ed he benchma ks o he abso p ion a es in keeping wi h he
i s i nancial pe iod o Romania (cu en le el in 2015, 2016) and he e ec i e Eu opean a e age le el wi h ex ension
on wo le els.
Tab. 6: The ini ial a iables made use o in simula ing hypo hesis 2 (I.2 o B)
EM_3_2017.indd 25EM_3_2017.indd 25 7.9.2017 10:34:057.9.2017 10:34:05
26 2017, XX, 3
Ekonomie
di e en p obabili ies, de ailed, in an ex ended
manne , o he second a iable acco ding
o a 3/5 a io (wi h an ins umen al ole, and
ou lining calib a ion samples domina ed by 100
and e en 200 d aws);
I.2. he es ic ed hypo hesis B (Tab. 6)
– comp ising wo independen a iables wi h
di e en p obabili ies, ye wi h a mo e ex ensi e
b eakdown o he i s a iable in keeping wi h
he 5/4 a io ( he ins umen al ole is main ained,
and only calib a ion samples o 100 d aws a e
used);
I.3. he ex ended hypo hesis C (Tab. 7)
– comp ising se en independen a iables
esul ing om he disagg ega ion, by ca ego ies
o p og ams, o he EU unds in he budge pe iod
2014-2020 (wi h a dominan ole in he i nal
simula ion o he 500 and 1,000 d aws samples).
The p obabili ies o hese de ailed a iables
( unds, each FAi, and abso p ion a e RAi) we e
exp essed in a simila manne o bo h he
speci i c a ian s o he alloca ed unds (0.4
and 0.6), s a ing om ac ual le els eco ded
and upda ed, and he abso p ion a es (0.2, 0.5
and 0.3), s essing he impo ance o he ac ual
le el eached in RO and EU, in he i s budge
pe iod, i nally also including a a ian ha is
sligh ly upwa d ela i e o he i s (0.3).
Applying he Mon e Ca lo me hod
simul aneously obse ed he p inciple o
simula ion by s a is ical scena ios (Ko emann,
2017), applied, in a simila manne , o all he
hypo heses made. The scena io-making
e en ually shaped h ee op ions by combining
c i e ia o s abili y/ins abili y, nuanced by
op imis ic/ pessimis ic ype scena ios:
S1. The op imis ic scena io, ocused on
he ela i e s abili y o he gene al economic
en i onmen , will gene a e maximum alues o
anges o highes alues, d awing on a s a iona y
index o a uni a y ins abili y (w = 1 o 100%);
S2. The ealis ic scena io, ocused on an
index o ins abili y o he gene al economic
en i onmen w = 0.95 o 95%, desc ibes
a e ages o anges o a e age alues; S2
assumes he appea ance o a c isis, o
ecession, om he analysis o he Romanian
economy cyclicali y, which would in ol e
minimal losses o 3-5%, ma e ialized in educing
he w index by 0.03-0.05 in he agg ega e unds
accessed by he economy;
S3. The pessimis ic scena io, ocused on
an index o ins abili y o he gene al economic
en i onmen w = 0.8 o 80%, leads o minimum
alues, o small anges o alues; S3 admi s ha
a c isis, o e en a global ecession cumula i e
wi h he B exi p ocess ( he UK economy
accoun ing o nea ly 20% o he EU economy),
would ha e an impac o ins abili y ha could
induce losses o 15-20% o Romania, oo).
By he Mon e Ca lo me hod, he accu acy o
he simula ion o he unds ha can be accessed
is na u ally in l uenced by he complexi y o
he eal sys em (Eu opean unds alloca ed
ha e speci i c p obabili ies and abso p ion
a es), which also explains why he numbe o
independen a iables e ol ed om he o iginal
wo o he i nal se en ones, hus imp o ing he
quali y o p edic ing he possible consequences
o economic and social phenomena o g ea
di e si y, such as accessing Eu opean unds
h ough p ojec s in mode n economic eali y. In
o de no o a ec he accu acy o he esul s,
he ini ial le el o decimals was main ained up
o he i nal, and he las analysis, conduc ed
on a sample o 1,000 d aws de ailed a iables,
Disagg ega ed a iables a ca ego y le el o Eu opean unds alloca ed and abso p ion a es
FA1 - FA7 Funds alloca ed – billion eu os RA1 - RA7 Abso p ion a e – coe i cien s
POR PIM POC POCU POCA POAT POAD RA1RA2RA3RA4RA5RA6RA7
6.6 9.40 1.33 4.33 0.55 0.20 0.44 0.93 0.88 0.93 0.88 0.95 0.95 0.93
6.7 9.42 1.40 4.40 0.57 0.22 0.45 0.95 0.89 0.95 0.90 0.96 0.96 0.95
0.96 0.90 0.97 0.92 0.97 0.97 0.97
Sou ce: Eu opean unds, de ailed and ein e p e ed as access and abso p ion, by he au ho s, in acco dance wi h:
h p://www. ondu i-ue. o/21- anspa en a/s adiul-abso b iei/26-s adiul-abso b iei.
Tab. 7: The ini ial a iables made use o in simula ing hypo hesis 2 (I.3 o C)
EM_3_2017.indd 26EM_3_2017.indd 26 7.9.2017 10:34:057.9.2017 10:34:05
27
3, XX, 2017
Economics
addi ionally capi alized only one decimal, mo e
clea ly ou lining he no mali y o dis ibu ions
esul ing om sampling h ough he speci i c
ype o he no malized Ke nel cu es.
The so wa e used by he au ho s e e s
o Mic oso Excel, which is app ecia ed in
i nancial modelling (Benninga, 2008) and
EViews, which is made use o in he a icle,
especially in desc ip i e s a is ics o he
samples esul ing om he Mon e Ca lo me hod
and he p esen a ion o he Ke nel dis ibu ions
o he no malized da a se ies (Să oiu, 2013).
The esul s o his complex simula ion we e
subjec ed o a compa a i e s a is ical analysis
o he scena ios in o de o selec he bes
p edic ion o he abso p ion o Eu opean unds
by Romania o he pe iod 2014-2020.
3. Resul s and Discussion
The analysis o he alue o he a iables
desc ibed by a p obabili y dis ibu ion was
conduc ed s a is ically on se e al ypes o
samples simula ed by he Mon e Ca lo me hod
( om 100 d aws o 200; 300; 400; and i nally
500 and 1,000 d aws). In Fig. 5 and 6 one can
dis inguish he esul s o I1 (hypo hesis 1) in
he h ee scena ios (op imis ic, ealis ic and
pessimis ic). The i s no mally dis ibu ed
se ies in he simula ions done was selec ed, in
acco dance wi h he Ja que-Be a es , whe e o
a signi i cance le el α = 0.01, he J-B s a is ics,
calcula ed wi h he so wa e package EViews,
imposed a limi alue o 9.21 and a c i ical
p obabili y g ea e han he p e-se signi i cance
h eshold α.
The ealis ic and pessimis ic scena ios
o he hypo hesis 1 iden i y alues o he J-B
es ha alida e he no mal dis ibu ion o he
samples ex ac ed (5.979 acco ding o he
ealis ic scena io, and 8.734 acco ding o he
pessimis ic scena io) and p o ide a di e en
ange o a ia ion in he o al amoun o unds
accessed (based on a e ages o 19.74 and
16.6, espec i ely, as well as he S d. de .
alues o 0.53 and 0.44, espec i ely). Fig. 6
shows he s uc u e o he samples (100 d aws
in I1.S2 and 200 d aws in I2.S3) and hei
speci i c dis ibu ions, whe e he anges a y
signi i can ly.
The appea ance o he g aphical con ou o
he no malized Ke nel dis ibu ions o he h ee
scena ios a e desc ibed in Fig. 7, con i ming
he insu i cien co e age o he i s hypo hesis
by he incipien endency o abno mali y de i ed
om mul iplica ions wi h modal alences.
The I2 hypo hesis, whe e he a io o he
a iables o he wo a ian s was 5/4, gene a es
no mally dis ibu ed samples o 100 d aws
(Tab. 8) in all scena ios.
The his og ams o he scena ios in
hypo hesis I2 and he no malized Ke nel
dis ibu ions desc ibe a simila end o abno mal
dis ibu ion as in hypo hesis I1 (Fig. 8).
Wi h espec o hypo hesis I3, wi h he
same scena ios and samples o 500 d aws,
he simula ions ob ained we e e y close o he
no mal dis ibu ion as compa ed o he o he
hypo heses, i.e. I1 and I2, which ailed o pass
he J-B es , o samples la ge han 200 and
400 d aws, espec i ely. The op imal esul s as
a as he Mon e Ca lo simula ion in ela ion o
Sample 1 100 I2.S1. I2.S2. I3.S3.
Mean 20.906400 19.861400 16.725300
Median 21.050000 20.000000 16.840000
Maximum 21.850000 20.760000 17.480000
Minimum 19.360000 18.390000 15.490000
S d. De . 0.630253 0.598716 0.503034
Skewness -0.350413 -0.350238 -0.353759
Ku osis 2.242042 2.246150 2.247688
Ja que-Be a 4.440237 4.412321 4.443974
P obabili y 0.108596 0.110123 0.108394
Sou ce: made by he au ho s wi h he EViews package o p og ams
Tab. 8: Desc ip i e s a is ics o he h ee simula ions using hypo hesis I2
EM_3_2017.indd 27EM_3_2017.indd 27 7.9.2017 10:34:057.9.2017 10:34:05
34 2017, XX, 3
Ekonomie
o ecas ? Re ie ed Ma ch 1, 2017, om h p://
www.in es opedia.com/ask/answe s/051315/
wha s-di e ence-be ween- i nancial-plan-and-
i nancial- o ecas .asp.
Mun, J. (2006). Modeling Risk: Applying
Mon e Ca lo Simula ion, Real Op ions Analysis,
Fo ecas ing, and Op imiza ion Techniques
(Wiley Finance). Hoboken, NJ: John Wiley &
Sons, Inc. doi:10.1002/9781118366332.
Consiliul i scal. (2015). Rapo anual i scal.
Re ie ed Ap il 17, 2017, om h p://www.
consiliul i scal. o/Rapo anualCF2015.pd .
Robe , C. P., & Casella, G. (2004). Mon e
Ca lo S a is ical Me hods (2nd ed.). New Yo k, NY:
Sp inge P ess. doi:10.1007/978-1-4757-4145-2.
Să oiu, G. (2007). S a is ica - Un mod
ş iinţi i c de gândi e. Bucu eș i: Edi u a
Uni e si a ă.
Să oiu, G. (2013). Modela ea Economico-
Financia ă: Gândi ea econome ică aplica ă
în domeniul i nancia . Bucu eş i: Edi u a
Uni e si a ă.
Să oiu, G. (2016). Eu opean In eg a ion
h ough Economic Con e gence. Am i ea u
Economic, 18(42), 237-238.
Să oiu, G., Dima, F., Ene, S., Ma cu, N.,
& Mihailo , L. (2006). P oiec e cu i nanța e
ex e nă. Pi eş i: Edi u a Independența
Economică.
Să oiu, G., Tudo oiu, L., & Bu escu, E.
(2017). Using he Mon e Ca lo me hod o
es ima e he Eu opean unds abso bed by he
Romanian economy om he EU in 2007-2013.
Romanian S a is ical Re iew, Supplemen 3,
110-119.
Simula ion. (2012). In Encyclopaedia
B i annica Online. Re ie ed May 1, 2017, om
h ps://www.b i annica.com/science/simula ion.
Ța ța ulea (Dieaconescu), R. I., Belu, M.
G., Pa aschi , D. M., & Popa, I. (2016). Spa ial
Model o De e mining he Op imum Placemen
o Logis ics Cen e s in a P ede i ned Economic
A ea. Am i ea u Economic, 18(43), 707-725.
P o . habil. Gheo ghe Să oiu, Ph.D.
Uni e si y o Pi es i
Facul y o Economic Sciences and Law
[email p o ec ed]
Assoc. P o . Emil Bu escu, PhD
Uni e si y o Pi es i
Facul y o Economic Sciences and Law
[email p o ec ed]
P o . Vasile Dinu, PhD
The Bucha es Academy o Economic S udies
The Facul y o Business and Tou ism
[email p o ec ed]
Ec. Ligian Tudo oiu, PhD Candida e
S.C. Rone a SA Basco
and Uni e si y o C aio a
[email p o ec ed]
EM_3_2017.indd 34EM_3_2017.indd 34 7.9.2017 10:34:087.9.2017 10:34:08
35
3, XX, 2017
Economics
Abs ac
A MONTE CARLO METHOD SIMULATION OF THE EUROPEAN FUNDS THAT
CAN BE ACCESSED BY ROMANIA IN 2014-2020
Gheo ghe Să oiu, Emil Bu escu, Vasile Dinu, Ligian Tudo oiu
The au ho s deal wi h i nding some ele an simula ion solu ions o he alue o he Eu opean
unds ha can be accessed by Romania in he second budge cycle (2014-2020) o he Eu opean
Union (EU), in which he na ional economy is pa icipa ing a e he 2007 accession. The a icle
p esen s, in a b ie concep ual in oduc ion, he op ion o simula ion, no only as economical
and s a is ical al e na i e bu also as concep ual and echnical me hod, ollowed by an analysis
sec ion o he EU unds accessed by Romania in he 2007-2013 i nancial pe iod and in he i s
h ee yea s o 2014-2020 i nancial pe iod, wi h a ole in gene a ing hypo heses and scena ios o
a ype o modelling he p ocess o accessing and speci i c abso p ion (including all ypes o a es,
om he cu en abso p ion a e o he ac ual a e, wi h e enue in ad ance, e c.). A me hodology
sec ion desc ibes he a ionale o selec ing he me hod o simula ion as Mon e Ca lo, and also he
main hypo heses, de ailed scena ios and in eg a ed cha ac e is ic a iables. The scena io-making
e en ually shaped h ee op ions by combining c i e ia o s abili y/ins abili y, nuanced by op imis ic/
pessimis ic ype scena ios. The analysis o he a iables desc ibed by a p obabili y dis ibu ion was
conduc ed s a is ically on se e al ypes o samples simula ed by he Mon e Ca lo me hod, om
100 d aws o 200; 300; 400; and i nally 500 and 1,000 d aws. A p esen a ion o he i nal simula ion
esul s and a numbe o majo commen s ega ding hei calib a ion, con on a ion, cla i y and
s a is ical analysis, oge he wi h some i nal ema ks as conclusions, limi a ions and pe spec i es,
end he esea ch app oach.
Key Wo ds: Simula ion, Mon e Ca lo, Eu opean unds ea ma ked, EU unds accessed, he
cu en abso p ion a e and he ac ual a e, e enue (in ad ance).
JEL Classi i ca ion: C53, C63, E17, E27, E37, F37, F47, G17.
DOI: 10.15240/ ul/001/2017-3-002
EM_3_2017.indd 35EM_3_2017.indd 35 7.9.2017 10:34:087.9.2017 10:34:08