Nominal and Real Shocks in the EURALL Exchange Rate.
(A SVAR Guide)
BLISARD ZANI, INGRID KONOMI
Department of Finance, Faculty of Economics,
University of Tirana,
Rruga e Elbasanit, Tirana,
ALBANIA
Abstract: - Exchange rates are one of the most important topics in the economic and financial sectors. Considering
the exchange rate as the price between currencies, financial theories aim to understand the behavior of exchange
rates from a more rational viewpoint. Domestic and foreign inflation has a direct impact on the real interest rates
and the exchange rates. This paper aims to analyze the nominal and real shocks of the exchange rate between the
Euro and Albanian lek [EURALL]. As the most important foreign currency used in the Republic of Albania, the
euro is becoming more and more a stable determinant of prices and asset values in the Albanian economy. The vast
majority of import and export is dependent on the EURALL trend. That is one of the main reasons why it is so
important to study the shocks in the EURALL exchange rate. The Structural Vector Autoregressive (SVAR)
models can be used to understand the effects of imposing some long-run restrictions. In addition, some short-run
shocks play a major role and continue to have effects even in the long run. This paper takes into consideration the
monthly data of exchange rates and inflation of Albania and the Eurozone from 2016 – 2022 (the last 7 years). As
one of the most important models, SVAR models can be used in both fiscal and monetary policymaking. Studying
nominal and real exchange rates means studying inflation in the eurozone and Albania. Real shocks have a
significant impact on both nominal and real exchange rates. Meanwhile, there is no evidence that the nominal
shocks (such as institutional interventions or central bank operations) have an important impact on the nominal and
real exchange rates. Referring to that, we can conclude that policymaking institutions should be cautious about the
real exchange rate.
Keywords: - Exchange rate, real and nominal shocks, SVAR Model
Received: May 27, 2023. Revised: August 12, 2023. Accepted: September 3, 2023. Published: September 11, 2023.
1 Introduction
Exchange rates are one of the most important topics
in the economic and financial sectors. Due to its
importance, researchers and economists are often
attracted to study the role of the exchange rates in
potential economic growth, the correlation between
exchange rates and national trade balance, etc.
Meanwhile, considering the exchange rate as the
price between currencies, financial theories aim to
understand the behavior of exchange rates from a
more rational viewpoint.
Macroeconomic indicators and systematic risks
impact almost every other variable in the economy.
Due to their unavoidable presence, indicators like
inflation, unemployment, and interest rates need to be
analysed very carefully as they change the context of
the macroeconomic framework. Domestic and
foreign inflation has a direct impact on the real
interest rates and the exchange rates. This paper aims
to analyse the nominal and real shocks of the
exchange rate between the Euro and Albanian lek
[EURALL].
As the most important foreign currency used in
the Republic of Albania, the euro is becoming more
and more a stable determinant of prices and asset
values in the Albanian economy. The vast majority of
import and export is dependent on the EURALL
trend. That is one of the main reasons why it is so
important to study the shocks in the EURALL
exchange rate. Nominal and real shocks in the
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.168
Blisard Zani, Ingrid Konomi
E-ISSN: 2224-2899
1928
Volume 20, 2023
exchange rate may have an impact on both nominal
and real exchange rates. The Structural Vector
Autoregressive (SVAR) models can be used to
understand the effects of imposing some long-run
restrictions. In addition, some short-run shocks play a
major role and continue to have effects even in the
long run.
This paper takes into consideration the monthly
data of exchange rates and inflation of Albania and
the Eurozone from 2016 – 2022 (the last 7 years).
These years are chosen to have the possibility to
study some potential shocks [if happened] in a
comparison way before and after the Covid-19
pandemic situation. The methodology is based on
using the SVAR model and variance structural
decomposition of EURALL exchange rates. As one
of the most important models, SVAR models can be
used in both fiscal and monetary policymaking.
Structural vector autoregressive models have been
previously used in other papers and studies to create a
better understanding of exchange rates. A study of
the Japanese Yen and US Dollar exchange rates have
been published in 1998 to measure the effects of the
real and nominal shocks. The same Studying nominal
and real exchange rates means studying inflation in
the eurozone and Albania. Beyond quantitative
parameters, some qualitative interpretations should
be made for a deeper understanding of the nominal
and real shocks in the real exchange rate of
EURALL.
2 Understanding the Trend: Exchange
Rate and Inflation
The nominal exchange rate between the euro and the
Albanian lek is one of the most important indicators
regarded financial operations with foreign currencies
in Albania. In the last seven years, it has shown a
clear downward trend having high volatility and
moving from 120.81 lek/euro up to 138.51 lek/euro
[as a monthly average exchange rate]. Taking into
consideration some predictable moments where the
EURALL nominal exchange rate surprisingly has
risen or fallen, the other daily movements have
shown a clear trend. A better understanding
framework can be seen throughout Figure 1.
The nominal exchange rate between the euro and
the Albanian lek has had a clear downward trend
since 2016. In 2018, the European currency marked
the biggest drop against the Albanian lek. There are a
lot of reasons behind this trend. The year after has
shown the same phenomenon, but with smoother
volatility. Since the pandemic started in March 2020,
the nominal value of the EURALL exchange rate
started to rise again and at the end of 2022, the
exchange rate level stood in the same narrow interval
[2020 -2022]. The same situation but with minor
changes can be also seen in the real exchange rate.
For more than four years repeatedly (2016 – 2020),
the real exchange rate has also dropped. During the
pandemic, the real exchange rate overcame the
nominal exchange rate for the first time. This
situation changed in 2021 and 2022 as the EURALL
real exchange rate fell against the nominal exchange
rate.
Fig. 1: EUR ALL exchange rate in Albania
To determine real exchange rates, inflation in the
eurozone and inflation in the Albanian economy
should be taken into consideration. The real
EURALL exchange rate is calculated as the equation
below:
R EURALL = ϵ EURALL ∙ 󰇛󰇜
󰇛󰇜 [1]
where R EURALL – real EURALL exchange rate
ϵ EURALL – nominal EURALL exchange rate
 – inflation (%) in Albania
 – inflation (%) in the eurozone
To make a deeper analysis of the real exchange
rate, it is suggested that the study of inflation can be
useful to identify the oscillations in real exchange
rates and which of the inflation level have a greater
impact on real exchange rates. Figure 2 makes a
simple comparison between inflation in the eurozone
and inflation in Albania.
105
110
115
120
125
130
135
140
145
2016 2017 2018 2019 2020 2021 2022
EURALL exchange rate
Nominal
Real
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Volume 20, 2023
Inflation in the eurozone has experienced a
sustainable movement between 0% - 2% for more
than five years (2016 – 2020). Starting in 2021, the
inflation started to “jump” higher reaching up to 8%
(monthly average core inflation). The consequences
of the pandemic situation, energetic crisis, and
shortage in the supply chain were the main reasons
for this new trend of inflation. Furthermore, the
Russo – Ukrainian war and the dependence of
European countries on the Russian oil and gas supply
created a new double-digit level of inflation at more
than 10%. Meanwhile, the inflation in Albania has
been lower all the years, except in 2020 when it
overcame the inflation in the eurozone. It has
remained below the objective of the central bank of
Albania [2% - 4%]. The trend has been almost the
same as the pattern of inflation in the eurozone,
having a strong positive correlation at 93.1%. The
absolute difference between eurozone inflation and
Albanian inflation has a standard deviation of 1.06%.
Since 2021, the monthly inflation rate rose to 9% but
it remained lower than the euro inflation rate. Higher
inflation in Albania can be explained by some
different reasons compared to inflation in the
eurozone. Real estate high demand, an increase in
private expenses after the pandemic, and shocks in
the supply chain are some of the main reasons
causing inflation in the last two years.
Fig. 1: Inflation in Eurozone and Albania
3 Literature Review
The exchange rate has been the focus of researchers
for a long time. Policymakers, governmental
institutions, financial markets overall, and other third
parties, investors are always interested in
understanding the spirals of exchange rates and the
factors impacting them. The nominal exchange rate
expresses the de jure price of a currency compared to
other currencies. IMF defines the nominal exchange
rate as the price of a coin in terms of another, [1].
While considering inflation, there can be a slight
difference between the nominal and real exchange
rates. Xiao et. al. affirms that the real exchange rate
measures the real purchase power, and it is
considered one of the most significant relative prices
in an economy and one of the key factors influencing
economic growth, [2].
Other authors have analyzed the effects of other
factors mainly impacting the real exchange rate.
Baxter and other authors have defined the most
important factors impacting the real exchange rates.
The business cycle is one of the substantial factors
impacting the exchange rate since it is one of the
crucial macro indicators in a specific economy, [3],
[4], [5]. In addition, factors impacting the business
cycle itself tend to impact the real exchange rate.
Previous studies have generally been unable to reject
the hypothesis that the real exchange rate follows a
random walk. Meanwhile, Abuaf and Jorion doubt
the random walk hypothesis and they proclaim that
there is no tendency for purchasing power parity
(PPP) to hold in the long run, [6]. Moreover, the real
exchange rate and foreign currency can be
transformed into a burden in cases of foreign
currency mortgages, [7].
Progressively, nominal, and real shocks in
different economic situations have an important
impact on both nominal and real exchange rates.
Authors like Evans and Su Zhou have primarily
analyzed the responses of the real exchange rates to
different shocks, [8], [9]. That is, changes in the real
values of many currencies tend to persist for a very
long period. This persistence implies that fluctuations
in the real exchange rates are largely due to the long-
lasting effect of real disturbances. Lastrapes has
studied the source of fluctuations in the nominal and
real exchange rates. As imposing the long-run
restrictions, the findings indicate that real shocks
dominate nominal shocks for both exchange rate
series over short and long frequencies, [10]. Similar
studies from King et. al. suggest that the stochastic
trends and economic fluctuations should be studied
carefully as the aggregate indicators can impact the
business cycle at the same time, [11]. In one of his
papers, Kollman suggests that in a model of a small
open economy, the predicted variability of the
-2,00%
0,00%
2,00%
4,00%
6,00%
8,00%
10,00%
12,00%
2016 2017 2018 2019 2020 2021 2022
Eurozone
Albania
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Volume 20, 2023
nominal and, especially, of the real exchange rate is
noticeably higher than in standard Real Business
Cycle models with flexible prices and wages, [12].
Fiscal shocks have also been studied to measure the
effects on both nominal and real exchange rates.
Since fiscal policies tend to contribute faster to the
economy (compared to monetary policies), their
effects on the real exchange rates can be analyzed.
Benetrix and Lane, Perotti, and other authors affirm
that fiscal shocks have a palpable effect on the real
exchange rates in small open economies. Fiscal
shocks are one of the major shocks in a certain
economy, so governmental expenditures can
significantly impact the exchange rate, [13], [14]
[15], [16]. Other authors like Enders and Müller and
Scholl have analyzed the effects of technological
shocks on real exchange rates. They found that both
the real exchange rate and the terms of trade - whose
responses are left unrestricted - depreciate in
response to expansionary government spending
shocks and appreciate in response to positive
technology shocks, [17].
The discussion about the econometric models
that can be used to analyze the nominal and real
shocks in exchange rates recommends that VAR or
Structural VAR models can be used for this purpose.
Huang and Guo assert that studying exchange rates
from the econometrical viewpoint can lead to the
SVAR models as they seem to be effective and
worthwhile tools in decomposing the nominal and
real shocks. Similar studies from Wang also counsel
that SVAR models are powerful instruments to
analyze variance decompositions. In addition, he
concludes that supply chain shocks are also crucial
and with the same effects as nominal shocks, [18],
[19].
4 Methodology
One of the most frequently used methods for
explaining economic phenomena is the econometrical
one. Although these models can create a tremendous
logical framework for explaining causes and
consequences, the impact of the variables on each
other, etc., sometimes they are not able to give a
direct economic interpretation. For example, the
innovations in a reduced form of VAR do not have a
straightforward interpretation. At this point, studying
nominal and real shocks and their effects on nominal
and real exchange rates requires a more complex
model. Structural vector autoregression models
(SVAR) can be very helpful at this point.
Firstly, SVAR models rely on economic theory
to enumerate the contemporaneous link between the
variables in the model. Some assumptions are
required to fulfill the general theoretical framework.
In addition, SVAR models are used for both
monetary and fiscal policy purposes. Since this
model allows us to impose an ad-hoc structure, it will
prevent us to reach the wrong conclusions. Moreover,
imposing long-run restrictions is in full accordance
with a classical macroeconomic hypothesis (CMH).
This CMH specifies that in the long run, permanent
changes in the nominal variables do not affect real
variables. This phenomenon will be analyzed in this
paper regarding the nominal and real shocks on the
EURALL exchange rate.
The model presented in this paper will analyze
the exchange rate movements decomposition,
studying real and nominal factors. These movements
will be decomposed into the components produced by
real and nominal shocks. Nominal shocks can only
affect the exchange rate in the short run, while real
shocks can cause permanent effects on real exchange
rates.
4.1 Data Evaluation
Nominal and real exchange rates combine mixed data
of exchange rates and inflations in Albania and the
eurozone. As both indexes are economic ones, while
preparing data to evaluate the model, it is suggested
(by literature and other authors) that the best method
is to convert them into logarithm data values. After
that, the model estimation and other data tests are
evaluated as logs. Let’s assume we have a bi-variate
model for y1,t, and y2,t. We may wish to allow the y1,t
to be affected by current and past realizations of y2,t,
while y2,t is affected by past and current realizations
of y1, t. Where we also want to incorporate
autoregressive lags of the dependent variables, we
could write the equations as below:
y1,t = b10 – b1,2 y2,t + 11 y1,t-1 + 12 y2,t-1 + ε1,t
y2,t = b20 – b2,1 y1,t + 21 y1,t-1 + 22 y2,t-1 + ε2,t
To express the above structural form of the model as
a reduced-form expression, we could take all the
contemporaneous variables to the left-hand-side,
before inserting them in the vector Yt. This would
allow us to write the model above as,
Byt = Γ0 + Γ1 yt-1 + εt (1)
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where,
B = 
 , yt = 󰇣
󰇤,
Γ0 = 
, Γ1 = 󰇣 
 󰇤 and εt = 󰇣
󰇤
As this study needs to identify the long-run effects of
nominal and real shocks on nominal and exchange
rates, at least one of the variables needs to be non –
stationary because if the data analysed are stationary,
the long–run impact of shocks on the levels of the
series are always zero. Although we require at least
one of the variables to be non-stationary, when
estimating the model, the variables must be turned
into stationary.
Testing the stationarity
The time series stationarity test is the first and most
important test in the preparation and validity of the
data form. The stationarity of the time series is
estimated as follows. Augmented Dickey-Fuller
(ADF) is the most common and important test for
assessing the stationarity of time series. A variable is
non-stationary if it is a function of time. A time series
variable is stationary, i.e., stable if its mean and
variance are constant over time and the covariance
between the two values depends only on the length of
the period that separates them and not on the time
moments when they occur. The first technical
element that needs to be implemented is the
conversion of data we receive from time series into
stationary data. Once time series data have been
converted to stationary data, they can be used in
econometric models. It often happens that most of the
data for the examined variables are stationary. Even
in cases where the data is not stationary, it can be
converted to stationary by the first or second
differences of the unit root test. The stationarity test
(Augmented Dickey-Fuller) results are presented in
Table 1.
Table 1. Stationarity test (Augmented Dickey-Fuller)
Unit Root
Test
Variable
First difference (Δ)
F – stat.
p.
value
F – stat.
p.
value
log(nominal)
-1.51
0.52
-7.83
0.00
log(real)
-1.13
0.69
-7.48
0.00
From the data analysis, the time series of the
variables are not stationary, but they are turned into
stationary series of the first difference. Specifically,
nominal and real exchange rates are stationary series
in the first difference (p <0.05). Now that the series
has passed the stationarity test, the data can be used
to construct the SVAR model. The lag length
selection is presented in Table 2.
Table 2. Lag length selection
Endogenous variables:
Δ (LNominal) Δ (LReal)
Lag
LogL
LR
FPE
AIC
SC
HQ
0
585.21
NA
7.4e-10*
-15.34*
-15.28*
-15.33*
1
586.96
3.37
7.86e-10
-15.28
-15.10
-15.21
2
589.98
5.63
8.07e-10
-15.26
-14.95
-15.14
3
591.29
2.38
8.66e-10
-15.19
-14.71
-15.02
4
592.97
2.96
9.22e-10
-15.13
-14.57
-14.91
From the analysis, it is noticed that the optimal lag is
equal to zero (0). This indicates that variables must
be taken for granted that have an immediate impact
without a delayed time period. Since the data have
become stationary, we can assume that the optimal
lag can be three (3), as these variables have a strong
trimestral significance. In this model, it is chosen 3
lags as optimal lag length.
Correlograms of the variables
The correlogram represents the correlation for all
pairs of variables and it is one of the most important
tests regarding the residuals. Figure 3 shows the
correlograms for the nominal and real exchange rates
of EURALL from 2016 – 2022.
-.3
-.2
-.1
.0
.1
.2
.3
1 2 3 4 5 6 7 8 9 10 11 12
Cor(D(LN),D(LN)(-i))
-.3
-.2
-.1
.0
.1
.2
.3
1 2 3 4 5 6 7 8 9 10 11 12
Cor(D(LN),D(LR)(-i))
-.3
-.2
-.1
.0
.1
.2
.3
1 2 3 4 5 6 7 8 9 10 11 12
Cor(D(LR),D(LN)(-i))
-.3
-.2
-.1
.0
.1
.2
.3
1 2 3 4 5 6 7 8 9 10 11 12
Cor(D(LR),D(LR)(-i))
Autocorrelations with Approximate 2 Std.Err. Bounds
Fig. 2: Correlograms of the residuals
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Volume 20, 2023
As it is seen from the charts, all the residuals of the
variables are within the interval of 2 standard error
bounds, so it indicates that the model is appropriate
and there is no residual problem.
4.2 Imposing the Long Run Restriction
The identification process of nominal and real shocks
on EURALL exchange rates consists firstly in
defining what are the possible situations impacting
the exchange rate. As described by literature and
general macroeconomic theories, the nominal and
real shocks, in the long run, tend to be neutralized.
Furthermore, we expect the real shocks to have a
greater and more relevant impact on the exchange
rate, compared with the nominal ones. Imposing the
long-run restriction is expressed by the equation:

 = 󰇛󰇜󰇛󰇜
󰇛󰇜󰇛󰇜 * 󰇣
󰇤
The first 2x1 vector is the real and nominal
exchange rate variables in the first difference. The
last 2x1 vector represents the zero mean mutually
uncorrelated real and nominal shocks. Moreover, the
Bij coefficients represent the time path of the effects
of the real and nominal shocks on the real and
nominal exchange rates. The long-run restriction
implies that the cumulative effect of nominal shocks
on real exchange rates is zero. Technically we are
imposing:
󰇛󰇜 󰇛󰇜

Taking into consideration the long-run restrictions,
the charts below represent the accumulated responses
of nominal and real shock in nominal and real
EURALL exchange rates.
-.002
.000
.002
.004
.006
.008
2 4 6 8 10 12 14 16 18 20 22 24
Real shock Nominal shock
Accumulated Response of D(LNominal)
.004
.005
.006
.007
.008
.009
2 4 6 8 10 12 14 16 18 20 22 24
Real shock Nominal shock
Accumulated Response of D(LReal)
Accumulated Response to Structural VAR Innovations
Fig. 3: Accumulated responses of Log Nominal
EURALL exchange rate
-.002
.000
.002
.004
.006
.008
2 4 6 8 10 12 14 16 18 20 22 24
Real shock Nominal shock
Accumulated Response of D(LNominal)
.004
.005
.006
.007
.008
.009
2 4 6 8 10 12 14 16 18 20 22 24
Real shock Nominal shock
Accumulated Response of D(LReal)
Accumulated Response to Structural VAR Innovations
Fig. 4: Accumulated responses of Log Real EURALL
exchange rate
5 Discussion
Firstly, let’s analyze the effects of nominal shocks on
the nominal exchange rate. There is no impact of the
nominal shocks on the nominal exchange rate.
Furthermore, the effects of nominal shock in the real
EURALL exchange rate have an immediate impulse
response but tend to vanish expeditiously. We can
confirm that the nominal shocks have no significant
impact on both the nominal and real EURALL
exchange rates. Nominal shocks such as central bank
purchase of foreign currency in exchange markets,
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the usage of euro in goods and services markets, or
other central bank interventions seems to have little
or no impact on the nominal and real EURALL
exchange rate. Since the exchange market in Albania
is driven by the market demand-and-supply
mechanism, we can expect nominal shocks not to
have an impact on the nominal and real exchange
rates. A completely different framework can be seen
in the real shock effects. These shocks have an
important and statistically relevant impact on the
nominal and real EURALL exchange rates. Even
though these effects exist, real shocks have a greater
impact on real exchange rates, compared to nominal
ones. Real shocks create an immediate response that
decreases continuously. Meanwhile, the real
exchange rate is impacted more by real shocks, and
these effects seem to last longer. The drastic price of
oil fluctuations impacted by the post-Covid-19
situation and the Russo – Ukrainian conflict created a
non-stable situation in the EURALL exchange rate.
Since Albania imports more than 75% of the oil and
crude oil, these shocks have both impacted the
nominal and real exchange rates. Furthermore, the
export and import of energy (since Albania is both
importer and exporter of hydro-energy) have also
impacted the nominal and real exchange rates. In
addition, the cyclical movements of the euro supply
coming from tourism and immigrants have also
impacted the real EURALL exchange rate.
To create a complete analysis of the nominal and
real shocks, we have to analyze the structural
decomposition of the SVAR model. The structural
decomposition shows the accurate impact of the
nominal and real shocks on the EURALL nominal
and real exchange rates. It explains the percentage of
the impact that every shock has on the exchange
rates, as explained in Table 3.
Table 3. Variance decomposition of economic shocks
Shock
D(LNominal)
D(LReal)
Real
Nominal
Real
Nominal
Period
1
99.1695
0.83041
65.3772
34.6227
2
98.9474
1.05256
65.8741
34.1258
3
98.9318
1.06810
66.6132
33.3867
4
97.0988
2.90117
66.5821
33.4178
5
97.0412
2.95873
66.6048
33.3952
6
97.0464
2.95356
66.6169
33.3830
⁝
⁝
⁝
⁝
⁝
21
97.0387
2.96130
66.6132
33.3867
22
97.0387
2.96130
66.6132
33.3867
23
97.0387
2.96130
66.6132
33.3867
24
97.0387
2.96130
66.6132
33.3867
Author’s summary from E Views 10.
The EURALL nominal exchange rate is affected
by more than 97% from the real shocks in the
economy, compared to up to 3% by the nominal
shocks. Almost all the fluctuations of the nominal
exchange rate are explained by the real shocks and
there is no significant impact of the nominal
interventions on the nominal exchange rate.
Meanwhile, the real exchange rate is impacted by
both nominal and real shocks, even though the real
shocks impact more than 66% of the EURALL real
exchange rates. As the nominal shocks do not have
an impact on the nominal exchange rate, these shocks
tend to have a relevant impact on the real exchange
rates. When analyzing the EURALL exchange rate,
nominal shocks should be taken into consideration as
an effective instrument that impacts the real exchange
rate. Finally, the structural decomposition of real and
nominal shocks in the EURALL exchange rate is
presented in Table 4.
Table 4. Structural decomposition of real and
nominal shocks in the EURALL exchange rate
Shocks
[Δr
Δr]
[Δe
Δe]
r
e
r
e
3 months
66.613
33.386
99.169
0.83
6 months
66.617
33.383
97.046
2.954
1 year
66.617
33.383
97.04
2.96
2 years
66.617
33.383
97.039
2.961
Notes: Δr – the first difference of real exchange rate; Δe –
the first difference of nominal exchange rate; r – real
shock; e – nominal shock
Author’s summary from variance decomposition
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Volume 20, 2023
6 Conclusions and Recommendations
Exchange rates are one of the most important
macroeconomic indexes that indicate the relationship
between two currencies. As an exposition of the price
of a currency, the exchange rate is subject to
oscillations and fluctuations that are caused by
different economic factors, to which in this paper we
are referring as economic shocks. In this context, the
exchange rate between the euro and the Albanian lek
can be analyzed in terms of the nominal and real
exchange rates. Factors impacting the EURALL real
exchange rate are the nominal rate, inflation in the
eurozone, and inflation in Albania. Excluding the
effects of inflation, the EURALL exchange rate can
be affected by nominal and real shocks.
A Structural VAR model can be used to
decompose the effects of the nominal and real shocks
that impact the real and nominal exchange rates.
After testing the model parameters and their
significance and statistical relevance, we conclude
that SVAR econometric models can be used to
analyze these shocks in the EURALL exchange rate.
In addition, the trend of inflation in Albania has a
strong correlation with the eurozone inflation, since
the euro have also a positive correlation with the
Albanian lek.
As described in the econometric model, real
shocks have a significant impact on both nominal and
real exchange rates. Meanwhile, there is no evidence
that the nominal shocks (such as institutional
interventions or central bank operations) have an
important impact on the nominal and real exchange
rates. Referring to that, we can conclude that
policymaking institutions should be cautious about
the real exchange rate. The Albanian central bank
should also have a more active role in the foreign
exchange market to soften and minimize the
EURALL exchange rate fluctuations especially
driven by real shocks. In addition, we recommend
that the Ministry of Finance and Economy of the
Republic of Albania and other institutions impacting
the fiscal policy should make policies considering the
exchange rate as a variable that is impacted
immediately by fiscal policies. Moreover, other
qualitative studies should be made to complete the
conceptual framework of understating how the
EURALL exchange rate fluctuates.
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WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.168
Blisard Zani, Ingrid Konomi
E-ISSN: 2224-2899
1935
Volume 20, 2023
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
-Blisard Zani has worked the statistical processing
using EViews 10 software and summarizing data
about inflation and exchange rate.
-Ingrid Konomi has worked on the literature review,
economic analysis of the data’s statistical processing
results, and summarizing the conclusions.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflict of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
https://creativecommons.org/licenses/by/4.0/deed.en_
US
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2023.20.168
Blisard Zani, Ingrid Konomi
E-ISSN: 2224-2899
1936
Volume 20, 2023