Factors that Influence Economic Growth: Empirical Evidence from
Albania
ANILA (VOCI) ÇEKREZI
Department of Finance and Accounting,
“A-Xhuvani” University,
Elbasan,
ALBANIA
Abstract: - This study aimed to analyze the impact of the demographic factors and economic factors on GDP
per capita in Albania from the period 1990-2020. The variables taken into consideration were life expectancy
growth rate, fertility growth rate, labor force growth rate, unemployment rate, population growth rate, trade
balance to GDP, and real interest rate. This study used Ordinary Least Squares (OLS) regressions to identify
factors that influence GDP per capita. Before conducting the OLS regression is tested for normality,
multicollinearity, heteroscedasticity, and also if the model is correctly specified. The results of the model
suggest that there is a positive significant relationship between fertility growth rate and real interest rate and
GDP per capita, and a negative significant relationship between population growth rate and the GDP per capita.
There is not a consensus on the main factors that impact the economic growth of a country and the main
difficulties consist of a lack of empirical research on Albanian data. The life expectancy growth rate, labor
force growth rate, unemployment rate and trade balance to GDP taken into consideration have no significant
effect on the dependent variable.
Key-Words: - Economic growth, GDP per capita, theories, demographic factors, economic factors, OLS,
Albania.
Received: September 18, 2021. Revised: July 10, 2022. Accepted: July 29, 2022. Published: September 5, 2022.
1 Introduction
1.1 Background of the Study
Economic growth is one of the main issues facing
countries all over the world. Economic growth is
measured through the gross domestic product
growth rate or the gross domestic product per capita,
which takes into consideration the number of people
in the country. According to [11] economic growth
is the increase in real GDP or GDP per capita.
Factors that influence economic growth can be
divided into economic factors and non-economic
factors. According to [25] there are some factors
(culture, religion, tradition, social and political
dependence, the role of government, corruption,
etc.) that can influence the economic development
of one country. Many government policies are
focused on the reduction of employment rates,
increased investments, foreign direct investments,
trade opportunities, etc. Albania is considered a
developing country and in 1990 passed from a
centralized economy to a liberal one. During these
years there have been different economic and
political developments. Considering previous
literature on different empirical researches and
testing social and economic factors, this article is an
attempt to find out some of the factors that have
influenced economic growth in Albania.
Fig, 1: The observed GDP growth rate in Albania
during 1990-2020
Source: World Bank
According to World Bank annual data, for the years
1990 to 2020, average economic growth was at the
level of 2.84%. The years with the lowest GDP
growth rate were 1991 with -28% and 1997 with -
10.92. The year with the highest economic growth
was 1995 with 13.32%.
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1403
Volume 19, 2022
For the years 1991 to 2000, the average economic
growth was at the level of 1.59%. The year with the
biggest economic downturn was 1991, at -28%.
The year with the highest economic growth was
1995, at the level of 13.32%.
For the years 2001 to 2011, the average economic
growth was at the level of 5.21%. The year with the
largest slowdown in economic growth was 2009, at
3.35%. The year with the highest economic growth
was 2001, at 8.29%. For the years 2011 to 2020, the
average economic growth was at the level of 2.23%.
The year with the largest slowdown in economic
growth was 2020, at -3.31%. The year with the
highest economic growth was 2018, at 4.07%.
Fig. 2: The observed GDP growth rate and GDP per
capita growth rate in Albania during 1990-2020
Source: World Bank
The maximum value of GDP per capita growth rate
was in 1993 (82.578%) and the minimum negative
value is in 1991 (45.38%).
Fig. 3: The observed GDP per capita in Albania
during 1990-2020
Source: World Bank
The average value of GDP per capita during the
period of the study was $2,659. The maximum value
is in 2019 with a value of $5,296, and the minimum
value is in 1992 at $201. For the empirical study, we
used recent data on the variables selected provided
by the official site of the [43] during the 31 years
from 1990 to 2020. Table 1 shows the mean, median
standard deviation, minimum and maximum values
of GDP growth rate, GDP per capita, and growth
rate of GDP per capita during 1990-2020.
Source: World Bank
1.2 Theories of Economic Growth
Economic growth and interest rates: Different
theories are developed to explain factors that
influence economic growth. According to [38] GDP
per capita growth rates are higher in those cases
when countries first accumulate capital. Per capita
income in developing countries is expected to grow
faster than in developed countries. The theory of
irreversible investment ([1]; [5]) states that an
interest rate hike may harm a country's output (the
cost of borrowing increases) but also it may have a
positive effect on output (investment activity
increases and the economic agents receive more
income from interest rates). According to [43] Neo-
Keynesian models explain that if the economy is
dominated by creditors, it can be observed a positive
relationship between interest rates and output. This
could happen because an increase in interest rates
would increase their revenues, also consumption,
and output. And if the economy were dominated by
borrowers, the relationship would be negative.
Economic growth and population growth: The
neoclassical growth model explained by [38]
suggests a negative relationship between population
growth and per capita output growth. [14] explains
that when population growth rates are at high levels,
the capacity of the earth and its resources to
generate food and other goods is lower, especially in
counties considered low-income ones. [29] theory
shows that population growth harms well-being.
According to him, the population tends to grow in a
more rapid way than food supplies. Some models
suggest that there is a positive relationship between
population growth and per capita economic growth.
([37], p.168) shows that greater population growth
would result in a larger “stock of useful
knowledge”. This would increase per capita
economic growth.
1.3 Research Objective
This study aims to achieve the following objectives:
Table 1. Same statistics of indicators of economic
development during 1990-2020
Indicators of
economic
development
Mean
Media
n
S.D.
Min
Max
GDP growth
rate
2.84
4.07
7.99
-28.0
13.3
GDP per
capita in USD
2659
2674
1791
201.0
5296
Growth GDP
per capita (%)
9.65
9.87
25.2
-45.4
82.6
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1404
Volume 19, 2022
1. Examine demographic variables influencing the
level of GDP per capita in Albania. For this purpose
life expectancy rate growth, fertility rate growth,
labor force growth, and population growth rate are
taken into consideration.
2. Examine the effect of economic factors, including
unemployment rate, trade balance to GDP, and real
interest rates on the level of GDP per capita.
1.4 Significance of the Study
Different factors impact the GDP per capita growth
of one country. The following variables have been
analyzed in Albania: life expectancy rate growth,
fertility rate growth, labor force growth,
unemployment rate, population growth trade
balance to GDP, and real interest rate. Several
studies have been done in developed countries ([34];
[9]) and also in developing countries ([3]; [32] ;
[41]; [1]; [28]; [20]; [46]).
These study results can be useful for giving
information to policymakers on the factors that
increase GDP per capita, also by increasing
knowledge, by determining the relationship between
GDP per capita and different factors for researchers
in the same field.
Using OLS regression this study tests several factors
and suggests variables that influence economic
growth measured by GDP per capita. Many
researchers have studied determinants of economic
growth but there is not much evidence on the
Albanian economy.
The rest of this paper is as follows. Section 2
discusses the literature review. Section 3 discusses
variables, methodology, and hypothesis. Section 4
presents empirical results and econometric models.
Finally, section 5 presents the conclusions and the
study's recommendations.
2 Literature Review
Different studies are focused on searching for
determinants that influence the economy of the
countries. The research of [23] found that small and
medium-sized businesses are key determinants in
the economic growth of Eastern European countries
taken as a sample. The study of [11] was focused on
finding empirical evidence of the relationship
between external debt and economic growth in the
Western Balkan countries.
According to [24] the GDP per capita indicates the
level of productivity per person. GDP per capita is
influenced by factors that affect population and
economic factors. GDP per capita indicates how the
economy of a country is raising with its population.
Below there is a literature review on the variables
taken into consideration in this study:
GDP per capita and life expectancy: [36] study
examined the relationship between life expectancy
and per-capita GDP in Russia and Moscow in
comparison with 61 other countries through the
Preston curve. According to data between 2005 and
2015, Russia had rapid growth in per-capita GDP,
also a gain of six additional years of life expectancy.
[34] study explored the impact of life expectancy
and population growth on GDP per capita income in
G7 countries using regression analyses. They
concluded that the increase in life expectancy was
followed by an increase in Gross Domestic Product
per capita income.
GDP per capita and fertility: Previous literature
shows that economic growth harms fertility ([16];
[13]). The fertility growth rate measures the average
number of children per woman and is also an
indicator of population growth. [3] found that a
reduction in fertility raises income per capita by an
amount that some would consider economically
significant for Nigeria at a horizon of 50 years. The
study by [28] took into consideration 120
developing countries from 1970 to 2014 and found
that high fertility rates resulted in lower economic
growth. So, according to him, fertility rates harm
economic growth. [15] studied to see if they could
find evidence of a positive relationship between
fertility and economic development. They
investigated data from 20 European countries
between 1990 and 2012 and found that the negative
relationship between fertility and economic
development was weaker in many countries, and
positive among some others. [17] found that fertility
correlates negatively with GDP per capita.
GDP per capita and labor force: [12] investigated
the influence of economic development on labor
force participation rates of older men and women.
The study used national data for 134 countries and
suggests a negative relationship between per capita
income and labor force participation rates. Also,
they verified that this relationship is stronger for
older men than for older women and is most
apparent in middle-income countries. According to
[22] labor force has a positive and statistically
significant impact on economic growth (GDP). [1]
study analyzed factors that influence real gross
domestic product (RGDP) in Palestine during the
years 1994 to 2013. The results showed a positive
relationship between the size of the domestic
working labor force, real gross domestic capital
formation, real domestic exports, and real gross
domestic product (RGDP), and a negative relation
between real domestic imports, and political
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1405
Volume 19, 2022
instability, and the real growth of GDP. In
developed countries, it is noted an increase in older
age groups as a percent of the total population.
Older people are less likely to be in the labor force
contrary to younger people, causing a reduction in
overall labor force participation. [45] studied the
effect of a possible interaction between age for the
population of males and GDP per capita and labor
force: females aged 18 to 74 and region-level GDP
per capita. They were focused on labor market data
in Italy during the period 2004-2013. The results
showed a joint effect between region-level GDP per
capita and worker age. [46] used panel data for 62
developing countries from 2010 to 2018. Using
Pooled OLS model and GDP per capita as
dependent variables this study found a negative
significant relationship with the labor force growth
rate (the percentage change in labor force
participation), which is the proportion of the
population aged 15 and older.
GDP per capita and unemployment: Unemployment
is a crucial issue in developing economies and
especially in Albania. During the last years, our
country has experienced a high unemployment rate
(the maximum value was 18.06% in 2014) meaning
that labor resources are not being used efficiently.
The study of [33] measured the relationship between
the unemployment rate of a country and its
economic growth rate known as Okun's law.
According to his empirical study, if one economy
intends to decline unemployment rates by 1% the
real GDP must increase by approximately 2%
during the same period. [30] analyzed effects of
unemployment rates on per capita real GDP in Iran
during the years 1971-2006. They used an Auto-
Regressive Distributed Lag and the results imply
that the unemployment rate has a negative and
significant influence on per capita real GDP both in
the long-run and short-run. [32] study investigated
the impact, of economic growth and the
unemployment rate in Albania according to Okun's
law. The results did not explain Okun's law. If the
unemployment rate had been reduced by 1% the
GDP would have increased only by 1.11 percent,
but the impact was negative. [20] study in Jordan
during 1991-2019 showed a negative relationship
between economic growth and unemployment on
Jordan's economy during 1991-2019.
GDP per capita and population growth: [25] study
found no correlation between population growth and
growth in income per capita. Several studies have
been done to verify the influence of population
changes and GDP per capita. Empirical work on the
impact of population growth rate on a country’s
economy has concluded with contradictory results.
[4] and [44] conclude that there is a negative
relationship between population and per capita GDP
growth in China and Australia. [21] found that
current population growth harms economic growth
while lagged population growth has a positive effect
so there is no long-term relationship between these
variables. In contrast, [35] and [40] studies
conducted in India and the Eastern and Southern
Africa region, found that population growth had a
positive impact on per capita economic growth.
GDP per capita and trade: [25] found strong effects
of trade openness on growth and real income for the
developed countries, but negative effects for the
developing countries. [39] found that an increase in
exports of an economy has a positive effect on
growth. [41] studied the relationship between
export, import, and GDP in Albania for the period
from 1984 to 2012. They concluded that both
imports and exports have a significant relationship
with GDP. [6] focus on reviewing other studies on
determinants of economic growth. They have
identified some economical (natural resources,
capital goods, human resources, and technology,
and some others as public expenditure, trade
components, FDI capital formation, private or
public investment, employment rates, exchange
rates), and non-economic factors (government
efficiency, institutions, political and administrative
systems, cultural and social factors, geography and
demography). [9] studied the Granger-causal
relationships between trade openness and real
economic growth in Turkey from 1950 to 2014.
They found evidence for the relationship between
trade openness and economic growth.
GDP per capita and interest rates: [7] found
evidence that interest rate liberalization had a
positive effect on savings and economic growth.
[22] focused on the impact of the financial
liberalization index and economic growth in
Pakistan during 1971-2007. Using Auto-Regressive
Distributed Lag (ARDL) technique, they found that
the real interest rate had a negative and statistically
significant effect on economic growth (GDP). The
study of [31] examined the impact of interest rate
reforms on economic growth. He concluded that
interest rate reforms had a positive impact on GDP
growth rate through savings and investments in 15
SADC (Southern African Development
Community) countries during the period 1990-2015.
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1406
Volume 19, 2022
3 Variables, Methodology, and
Hypothesis
A descriptive study was done to analyze the
relationship between the factors chosen and Gross
Domestic Product per capita in Albania. This
section presented in detail the data used, period of
the study, descriptive statistics of the variables, and
diagnostic tests necessary to use the Ordinary Least
Square regression model.
3.1 Data and Model
The secondary data were retrieved from the
database of World Bank Indicators from 1990 to
2020 (retrieved from World Bank official site,
January 2022). The statistical package Gretl (2012)
was used to analyze the data. The pooled OLS
model [46] was used to test the influence of selected
variables on economic growth as measured through
a natural logarithm of GDP per capita. The
dependent variable is transformed to complete the
test for linearity, normality, multicollinearity,
heteroscedasticity, and Ramsey Reset Test.
Table 2 reports descriptive statistics for the
variables used in this study. It shows some of the
descriptive statistics (mean, median, standard
deviation, minimum values, and maximum values)
of the variable chosen.
Table 2. Descriptive Statistics, using the
observations 1-31 (during 1990-2020)
Table 3 shows the expected sight of each variable
chosen taking in consideration previous literature.
Table 3. Description of the variables and their
expected effects on GDP per capita
Dependent variable: GDP per capita, which is the
output of an economy divided by the number of its
total population. To fit the OLS model is taken the
natural logarithm of GDP per capita [19].
Independent variables:
1-Life expectancy growth rate (the change in the life
expectancy at birth): The life expectancy for
Albania in 2020 was 78.67 years, a 0.147% increase
from 2019. We expect a negative relationship
between the two variables because if longevity
increases, GDP per capita will decrease.
2-Fertility growth rate: The change in births per
woman was 1.58 in 2020 compared with 1.597 in
2019. If the birth rate declines, there will be a
positive impact on per capita income growth.
3-Labor force growth rate: An increase in the labor
force can cause a reduction in income per capita. A
negative relationship between labor force
participation rates and GDP per capita income is
expected.
4-Unemployment rate: Taking into consideration
other literature a negative relationship between
unemployment rates and GDP per capita is
expected. So if the unemployment rate is high, it
means that fewer persons are working and that their
incomes are lower.
5-Population growth: A negative relation between
population growth and GDP per capita is expected.
6-Trade Balance (the difference between exports
and imports to GDP). Trade growth affects
economic growth also GDP per capita. So a positive
relationship between GDP per capita and trade
balance is expected.
7-Real interest rate: A positive effect is expected
between real interest rate and GDP per capita.
Hypothesis
Ho: There is no significant relationship between
GDP per capita and the variables.
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1407
Volume 19, 2022
H1: There is a significant relationship between GDP
per capita and the variables.
3.2 Diagnostic Tests
The model was estimated using the OLS (ordinary
least square model). Diagnostic tests are undertaken
to make sure that the model is valid. To fulfill all the
tests required (Normality, Multicollinearity,
Heteroskedasticity, and Ramsey Reset Test-Stability
test) we have transformed the dependent variable by
taking the natural logarithm of GDP per capita. The
results of the tests are below:
Normality Test
The standard errors of OLS estimates won’t be
reliable if error terms are not normal. Jarque-Bera
normality test of residuals is used for linear
regression. The P-value should be greater than 0.05
([8]).
Test for normality of residual -
Null hypothesis: error is normally distributed
Test statistic: Chi-square(2) = 3.5024
with p-value = 0.1736
Jarque-Bera test = 1.9326, with p-value 0.3805
Fig. 4: Graph for Normality
Based on the results presented above, the joint p-
value of the Jarque-Bera statistic is approximately
38.05% greater than the 5%, so we have insufficient
evidence to reject the null hypothesis that the
residuals of the model are normally distributed.
Hence, it can be concluded that residuals are
normally distributed.
Multicollinearity Test
We tested the existence of multicollinearity among
the variables of the model by examining correlation
coefficients that shouldn’t be greater than 0.8 or
minor than -0.8, and also by using the variance
inflation factor.
The results of table 4 show that there isn’t evidence
of multicollinearity among the variables chosen.
When VIF is higher than 10, there is significant
multicollinearity between the variables.
Heteroskedasticity Test
The study of [8] suggests White Test for
Heteroscedasticity. OLS assumption is violated, if
errors are heteroscedastic it will be difficult to trust
the standard errors of the OLS estimates.
Table 5. Heteroscedasticity test
White's test for heteroskedasticity -
Null hypothesis: heteroskedasticity not present
Test statistic: LM = 14.5195
with p-value = P(Chi-square(14) > 14.5195) =
0.4118
The results of White's test revealed that the joint P-
value for the Chi-square Statistic of the VAR
Residual Heteroskedasticity Tests is equal to 0.4118
greater than 0.05. Therefore, we cannot reject the
null hypothesis of no-heteroscedasticity.
Table 4. Correlation coefficients, 5% critical value (two-tailed) = 0.3550 for n = 31
LNGDP
C
LIFE
FERT
LABOR
UNEMP
POPG
TRADE
RINT
Variable
VIF
1.0000
0.2574
0.6156
-0.0499
-0.5194
0.0213
0.0296
0.5871
LNGDPC
1.0000
-0.0269
-0.2148
0.2227
-0.3575
-0.1063
0.6583
LIFE
3.187
1.0000
0.1751
-0.5508
0.2054
-0.2188
0.0361
FERT
1.645
1.0000
-0.2086
0.2334
0.1011
-0.1119
LABOR
1.135
1.0000
-0.1972
0.0439
-0.1086
UNEMP
1.850
1.0000
0.1324
0.0295
POPG
1.454
1.0000
0.1876
TRADE
1.263
1.0000
RINT
2.793
Source: Author's computation
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1408
Volume 19, 2022
Ramsey Reset Test
The goodness of fit of the model can be tested using
Ramsey Reset Tests. Equation Specification Error
Test shows if fitted values of the independent
variable help explain the dependent variable [8].
Table 6. Ramsey Reset test
RESET test for specification -
Null hypothesis: specification is adequate
Test statistic: F(2, 21) = 0.6792
with p-value = P(F(2, 21) > 0.6792) = 0.5178
Finally, by conducting the Ramsey Reset test, is
concluded that at 5% significance level, the model
was correctly specified because the p-value resulted
0.5178 greater than 0.05. This result means that
independent variables can describe the variations in
the dependent variable.
4 Empirical Results and
Econometric Model
This section presents the results; the coefficients of
each dependent variable also an interpretation of
each result is given. This study used multiple linear
regression models to access the relationship between
the independent variables and the dependent ones.
This study used OLS regression [18] and through
Gretl statistical package following results are
obtained (Table 7):
The regression coefficient of the life expectancy
growth rate is negative (1.5562) and statistically
insignificant. The above results show that the
fertility growth rate is positive and statistically
significant at a 1% level of significance (column 5
of Table 7) confirming the positive relationship
between the variables. The regression coefficient is
positive (0.3499) showing that a 1% increase in
fertility growth rate will increase 0.3499 units of
LNGDP per capita. The regression coefficient of the
labor force growth rate is negative (0.0111) but
insignificant. The policy on the labor market does
not help increase economic growth. The regression
coefficient of the unemployment rate is negative and
insignificant (0.0706). The regression coefficient of
the population growth rate is negative (45.6425).
This result indicates that a 1% increase in
population growth rate results in a 45.6425 unit
decrease in LNGDPC. The coefficient is statistically
significant at a 5% level of significance (column 5
of Table 7) showing the negative relationship
between the variables. The regression coefficient of
the trade balance to GDP is positive (0.0009) but
statistically not significant. The regression
coefficient of the real interest rate is positive
(0.0388) and statistically significant at a 1% level of
significance (column 5, Table 7), showing that a 1%
increase in real interest rate GDP will increase
0.0388 units of the LNGDPC.
Through the regression analyses is found that only
three factors from seven chosen to be studied can
positively or negatively influence the variability of
GDP per capita.
The value for the R-squared in the model
demonstrates that 77.94% of the variation in the
dependent variable is explained by the independent
variables of the model. The P-value for the F-
Table 7. Results from the regression analyses (OLS, using observations 1-31, Dependent variable:
natural logarithm of GDP per capita, LNGDPC)
Coefficient
Std. Error
t-ratio
p-value
const
9.5106
0.9831
9.674
<0.0001
***
LIFE
−1.5562
1.0242
−1.519
0.1423
FERT
0.3499
0.0751
4.660
0.0001
***
LABOR
−0.0111
0.0106
−1.047
0.3061
UNEMP
−0.0706
0.0733
−0.9638
0.3452
POPG
−45.6425
24.4758
−1.865
0.0750
*
TRADE
0.0009
0.0025
0.3764
0.7101
RINT
0.0388
0.0089
4.359
0.0002
***
Mean dependent var
7.5398
S.D. dep. var
0.9613
Sum squared resid
6.1156
S.E. of regression
0.5157
R-squared
0.7794
Adjusted R-squared
0.7123
F(7, 23)
11.6101
P-value(F)
3.07e-06
Source: Author's computation
Variables statistically representative: *p<0.05; ***p<0.001
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1409
Volume 19, 2022
statistic is 3.07e-06. This value supports the validity
of the model in this study. Using Ordinary Least
Squares (OLS) we conclude with the following
econometric model:
Model:
LNGDPC=9.5106-1.5562*LIFE+0.3499*FERT-
0.0111*LABOR-0.0706*UNEMP-
45.6425*POPG+0.0009*TRADE+0.0388*RINT+
ε (1)
5 Conclusions and Recommendations
Empirical research on the main drivers of economic
growth has been of great interest to different
authors, governments, and investors. This paper
focused on establishing factors affecting economic
growth per capita in Albania from 1990 to 2020.
The CLRM assumptions and test of the model
specification have been performed to develop the
OLS estimation technique. Fertility growth rates,
population growth, and real interest rate were
factors that significantly affected GDP per capita.
Live expectancy growth rate has a negative but not
significant effect on GDP per capita. This result is
not consistent with the findings of [34] which found
a positive relationship between the two variables.
The fertility growth rate has a significant positive
effect on GDP per capita. This result is not
consistent with the findings of [16], [13], [3], [28],
and [17] which found a negative relation between
the two variables.
The labor growth rate has a negative but not
significant effect on GDP per capita. This result is
not consistent with the findings of [22] and [1]
which found a positive and significant effect on
labor and economic growth. The negative influence
of the labor force was found in the studies of [10]
and [46].
The unemployment growth rate has a negative but
not significant effect on GDP per capita. The same
relation was found in the studies of [30] and [20]
population growth rate has a negative and
significant effect on GDP per capita. This result is
not consistent with the findings of [35] and [40]
which found a positive relationship between
population and economic development. Also, it is
consistent with the findings of [4] and [20] which
found a negative relation between the variables.
Trade balance to GDP has a positive but not
significant effect on GDP per capita. This result is
not consistent with the findings of [39] study which
found a positive relationship between the variables
contrary to the study of [26] which found a negative
relation for the developed countries.
The real interest rate has a positive and significant
effect on GDP per capita. This result is consistent
with the results of [31] and [7] but is not consistent
with the findings of [22] who found a significant
negative influence on interest rates and economic
growth.
Live expectancy growth rate, labor force growth rate
and the unemployment rate can harm economic
growth per capita, especially population growth rate,
as its coefficient results are negative and statistically
significant. The study recommends that to increase
the level of GDP per capita, it is necessary to
undertake several reforms to decrease the
unemployment rate and stimulate trade. Albania as a
developing country should take advantage of access
to regional and global markets.
Governments throw different policies can increase
birth rates. They can often utilize financial
incentives; for example, birth bonuses, child
benefits, or subventions. The Albanian government
has increased birth bonuses from 1 January 2019,
but still, fertility growth rates are low.
Real interest rates influence positively GDP per
capita, especially during the period 1997-2013; the
real interest rates have been higher than 8% with an
average value of 11% showing that individuals took
advantage of high interests to invest their money.
Even though there is a vast literature on the subject,
there are still areas for completing further research
on a country's economic development. This article
can be useful as a literature review for further
studies as it lacks evidence on a developing county
such as Albania. Also, this paper's findings can be
used to evaluate economic policies useful to
improve economic growth. So as a reduction in the
fertility growth rate harms the economic
policymakers should provide incentives to the
population to increase this variable. Also, monetary
policy focusing on the interest rate can improve the
economic condition of the population.
Some other independent variables were tested, but
the regression models didn't fulfill the requirements
of the OLS linear regression model. Future research
could explore other indicators, for example, tourism
expenditure, education levels, technological
advancements, etc., or other measurements of
economic development rather than GDP per capita
could be used as the dependent variable.
The limitation of this study consists of not taking
into consideration other factors such as education
that can contribute to economic growth or if the
factors found significant are the same or different
for other countries which have similar economic and
political conditions as Albania.
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1410
Volume 19, 2022
References:
[1] Abu-Eideh, O. M. (2014). Factors of Economic
Growth in Palestine: An Empirical Analysis
during the Period of (1994-2013). International
Journal of Business and Economic
Development, 2 (2), p.70-84.
[2] Arrow, K. J. (1968). Optimal Capital Policy
with Irreversible Investment. Capital and
Growth, Papers in Honor of Sir John Hicks. p.
1-19.
[3] Ashraf, Q.H., Weil, N. D. and Wilde, J. (2013).
The Effect of Fertility Reduction on Economic
Growth. Population and Development Review,
39 (1), p. 97-130.
[4] Banerjee, R. (2012). Population Growth and
Endogenous Technological Change: Australian
Economic Growth in the Long Run. Economic
Record, 88, p. 214-228.
[5] Bertola G., Caballero R.J. (1994).
Irreversibility and Aggregate Investment. The
Review of Economic Studies, 61 (2), p. 223-
246.
[6] Boldeanu, F. T. and Constantinescu, L. (2015).
The main Determinants Affecting Economic
Growth. Bulletin of the Transylvania, Series V:
Economic Sciences, 8 (57) 2, p. 329-338.
[7] Boskin, M. J. (1978). Taxation, Saving and the
Rate of Interest. Journal of Political Economy,
86 (2), p. 3-27.
[8] Brooks, C. (2008). Introductory Econometrics
for Finance (2nd Ed.). New York: Cambridge
University Press.
[9] Çevik, E.I., Atukeren, E. and Korkmaz, T.
(2019). Trade Openness and Economic Growth
in Turkey: A Rolling Frequency Domain
Analysis. Economies, 7 (41), p.1-16.
[10] Clark, R. L., York, A. E. and Anker, R. (1999).
Economic Development and Labor Force
Participation of Older Persons. Population
Research and Policy Review, 18 (5), p. 411-
433.
[11] Dauti, B. and Voka, I (2022). External Debt
and Economic Growth in the Western Balkan
Countries, with Special Focus to Albania,
Kosovo and North Macedonia in the course of
the Pandemic COVID-19. WSEAS
Transactions on Business and Economics, 19.
p. 1303-1317.
[12] Denison, E. F. (1962). The Sources of
Economic Growth in the United States and
Alternatives before Us. CED Supplementary
Paper, No 13.
[13] Doepke, M. (2004). Accounting for Fertility
Decline during the Transition to Growth,
Journal of Economic Growth, 9 (3), p. 347-
383.
[14] Ehrlich, P. (1968). The Population Bomb. New
York, NY: Ballantine Books.
[15] Fox, J., Klüsener, S. and Myrskylä, M. (2019).
Is a Positive Relationship between Fertility and
Economic Development Emerging at the Sub-
National Regional level? Theoretical
Considerations and Evidence from Europe.
European Journal of Population, 35, p. 487-
518.
[16] Galor, O. and Weil, N. D. (1996). The Gender
Gap, Fertility, and Growth. The American
Economic Review, 86 (3), p. 374-387.
[17] Götmark, F. and Andersson, M. (2020). Human
Fertility in Relation to Education, Economy,
Religion, Contraception, and Family Planning
Programs. BMC Public Health, 20 (1), p. 265.
[18] Gujarati, N. D (1995). Basic Econometrics,
(3rd Ed.). New York: McGraw-Hill Publishing
Co Ltd.
[19] Hassan, M. R., Das-Acma, P. C. and Islam, M.
A. (2016). Per Capita GDP and Population
Growth Nexus: Facts From A Cross Country
Analysis the Cost and Management, 44 (6), p.
39-
43.file:///C:/Users/User/Downloads/PerCapita
GDPandPopulationGROWTHNEXUSFactsfro
maCrossCountryAnalysis%20(1).pdf
[20] Hjazeen, H., Seraj, M. and Ozdeser, H, (2021).
The Nexus between the Economic Growth and
Unemployment in Jordan. Future Business
Journal, 7 (42).
[21] Huang, T., Xie, Z. (2013). Population and
Economic Growth: A Simultaneous Equation
Perspective. Applied Economics, 45, p. 3820-
3826.
[22] Hye, Q.M.A. and Wizarat, S. (2013). Impact of
Financial Liberalization on Economic Growth:
A case study of Pakistan. Asian Economic and
Financial Review, 3 (2), p. 270-282.
[23] Iaroslav, P., Khmarska, I., Tkachenko, T.,
Koptieva, H. and Komandrovska, V. (2021).
The Importance оf Small and Medium
Enterprises in the Economic Development of
Eastern Europe. WSEAS Transactions on
Environment and Development, 17, p. 898-910.
[24] Kapotwe, B., Tembo, G. (2021). An Analysis
of the Factors Affecting Zambia's GDP Per
Capita. American Journal of Economics, 11
(1), p. 19-30.
[25] Kelley, A. C. (1988). Economic Consequences
of Population Change in the Third World.
Journal of Economic Literature, 26 (4), p.
1685-1728.
WSEAS TRANSACTIONS on BUSINESS and ECONOMICS
DOI: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1411
Volume 19, 2022
[26] Kim, D. H. (2011). Trade, growth and income.
The Journal of International Trade and
Economic Development, 20, p. 677-709.
[27] Letunic, S. and Dragicevic, M. (2014).
Importance of Non-Economic Factors for
Economics. DAAAM International Scientific
Book, Chapter 11, p. 145-152.
[28] Li, Y. (2015). The Relationship between
Fertility Rate and Economic Growth in
Developing Countries. Master program in
Economic Demography.
https://lup.lub.lu.se/luur/download?func=down
loadFile&recordOId=8727479&fileOId=87688
92
[29] Malthus, T. R. (1993). An Essay on the
Principle of Population. New York, NY:
Oxford Press.
[30] Meidani, A. N. and Zabihi, M. M. (2011). The
Dynamic Effect of Unemployment Rate on Per
Capita Real GDP in Iran. International Journal
of Economics and Finance, 3 (5), p.170-177.
[31] Moyo, C. and Khobai, H. 2018. Trade
Openness and Economic Growth in SADC
countries. MPRA Working Paper No. 84254.
https://mpra.ub.uni-
muenchen.de/84254/7/MPRA_paper_84254.pd
f
[32] Nikolli, E. (2014). Economic growth and
unemployment rate. Case of Albania.
European Journal of Social Sciences
Education and Research, 1 (1), p. 217-227.
[33] Okun, A. M. (1962). Potential GNP: Its
Measurement and Significance, American
Statistical Association. Proceedings of the
Business and Economics Statistics Section, 98-
104. https://doi.org/10.1016/0167-
2231(79)90009-5
[34] Rafia, Sh. and Samreen, F. (2019).
Relationship between GDP, Life Expectancy
and Growth Rate of G7 Countries,
International Journal of Sciences, 8 (6), p.74-
79.
[35] Sethy, S. K., Sahoo, H. (2015). Investigating
the Relationship between Population and
Economic Growth: An Analytical Study of
India. Indian Journal of Economics and
Business, 14, p. 269-288.
[36] Shkolnikov, V. M. Andreev, E., Tursun, R.
and Leon, D. (2019). In the Relationship
between Life Expectancy and Gross Domestic
Product in Russia in 2005-15: A Cross-
Sectional Analysis. Science Direct, 4 (4),
p.181-188.
[37] Simon, J. L. (1981). The Ultimate Resource.
Princeton, NJ: Princeton University Press.
[38] Solow, R. M (1956). A Contribution to the
Theory of Economic Growth. The Quarterly
Journal of Economics, 70 (1), p. 65-94.
[39] Tekin, R. B. (2012). Economic growth, exports
and foreign direct investment in Least
Developed Countries: A panel Granger
causality analysis. Economic Modeling, 29 (3),
p. 868-878.
[40] Tumwebaze, H. K. and Ijjo, A. T. (2015).
Regional Economic Integration and Economic
Growth in the COMESA Region, 1980-2010.
African Development Review, 27, p. 67-77.
[41] Turan, G. and Karamataj, B. (2014). An
Empirical Study on Import, Export and
Economic Growth in Albania. Academic
Journal of Interdisciplinary Studies, 3 (3), p.
428-438.
[42] Wickens M. (2008). Macroeconomic Theory: A
Dynamic General Equilibrium Approach.
Princeton University Press.
[43] World Bank, Retrieved January 15, 2022.
[44] Yao, W., Kinugasa and T., Hamori, S. (2013).
An empirical analysis of the relationship
between economic development and
population growth in China. Applied
Economics, 45, 4651-4661.
[45] Zanin, L. and Calabrese, R. (2017). Interaction
Effects of Region-Level GDP per Capita and
Age on Labour Market Transition Rates in
Italy. IZA Journal of Labor Economics, 6 (4).
[46] Zieba, M., Trang, Th-K., and Mbugua, R. Nj.
(2022). Factors Affecting Economic Growth:
Empirical Evidence from Developing
Countries.
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: 10.37394/23207.2022.19.126
Anila (Voci) Çekrezi
E-ISSN: 2224-2899
1412
Volume 19, 2022
