157
Factors affecting the economic development of
Azerbaijan
Musayeva Fargana Phd, Leading Researcher of the Institute of
Economics of Azerbaijan National Academy of Sciences
Abstract: Economic development of a country reflects the overall economic outlook of a country and
each country can utilize the existing opportunities for faster economic development by better
planning and a systematic approach. In this regard, it is important to study factors affecting the
economic development of any country and since it plays a key role in advancement of society, it has
attracted numerous researchers' attention. Therefore, the main aim of this study is to investigate the
factors affecting the economic development of Azerbaijan during the years of 1990-2015 as well as
examining the short and long-run correlation of variables based on ARDL method. The obtained
results indicate the positive impact of health expenditure and negative impact of population growth
both in short and long run. Foreign investment has a negative impact in the short run, but the
financial development and research and development expenditure have positive impact in the short
run; while the rate of foreign investment and trade openness have a positive significant impact in
the long run. Furthermore, the results suggest the relatively good speed of adjustment towards long-
run equilibrium of variables.
Keywords: Economic development, Azerbaijan, ARDL method, production growth
1- Introduction
Nowadays, the concept of development is a very important concept based on which the countries of
world are classified into three categories: developed, developing and underdeveloped countries.
Economic development issues had been introduced in European countries during the seventeenth
and eighteenth centuries. Due to the pressure of industrialization and technological development in
these countries along with dominance of market in weak colonial countries in a short time, the gap
between advanced and backward poles were deepened and two groups of countries were created in
the world: Developed and underdeveloped countries. By the end of World War II and creation of
public order in the world (along with independence of numerous colonial countries), this gap was
highlighted and various nations confronted with the fundamental question of "why are some of the
world population are living in poverty and absolute hunger and others in welfare?" Since then, the
development ideas and theories have been created in the world. Despite the fact that the growth had
been considered as the development, we should now distinguish between economic growth and
development (Salimifar, 2003). In all definitions, the economic growth is as a quantitative
phenomenon of changes in national production and can be positive or negative; and in the case that
there are not any changes, the economic growth will be zero. However, the development concept is
wider than growth and includes the change in production and reallocation of resources and
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workforce. The definition of economic development pays attention to concept of expansion and
improvement of economic status in countries. Economic development is not limited only to growth
and covers the issues related to poverty, justice, urbanization, migration, unemployment, income
distribution and other social indices at wider level (Tavallaei, 2014). Therefore, according to the wide
concept of development and coverage of several issues, it is important to pay attention to it and
investigate the effective concepts which can play essential roles in economic policy of countries, so
that planning for identification of economic growth structure and efforts to increase it is one of the
economic development requirements; and some experts have considered it in line with justice
(Gaskari and Mistry, 2010). Therefore, this study aims at investigating the factors influencing the
economic development of Azerbaijan.
2- Theoretical principles
Development literally means gradual growth to become advanced, more powerful and even larger
(Oxford dictionary, 2001). Economic development refers to economic growth which is along with
fundamental changes in economy and increased production capacities ranging from physical, human
and social capacities. The quantitative growth of production will be achieved in economic
development, but the social institutions will be also changed along with it (Wikipedia). Therefore, the
economic growth is a quantitative concept, while the economic development is a qualitative concept.
Brookfield defines development as follows: Development should be defined based on progress
towards welfare goals such as reduction of poverty, unemployment and inequality. In addition to
improving production and income, the development includes the fundamental changes in
institutional, administrative- social structures, and also public views. I most of the cases, the
development even contains the public habits, customs and beliefs (Daneshvar, 2007). Therefore, the
variables are qualitatively considered in economic development, and thus they express the
qualitative changes of a society which can be manifested in growth. Therefore, the economic
development refers to qualitative changes in economic structure of a society and those fundamental
changes which affect gross domestic product. According to a general definition, the development is a
process under which the cultural beliefs, and social, economic and political institutions are
fundamentally changed in order to be coordinated with new well-known capacities and it promotes
the public welfare process (Azimi, 2003). According to another definition, economic development is a
process which increases the real per capita income of a country over a long period. The important
point is that the economic development should not be reduced to economic growth, but the other
factors such as quality of life, life expectancy, increased productivity, social and economic equality,
reduced poverty, improved attitudes, and advanced factors and techniques of production according to
environmental protection should be taken into account in addition to growth (Meier, 1999).
The first economic ideas have been emerged since the eighteenth century and by fast growth of
industries in the West. The basic schools of economic development are as follows:
Adam Smith's theory (1723-1790): Smith was one of the most optimistic classical economists known
as the "father of economics". Smith and other classical economists (such as Ricardo and Malthus)
considered the "earth", "labor" and "capital" as the factors of production. The concepts such as
invisible hand of "division of labor", "capital accumulation" and "market expansion" form the
skeleton of his theory in economic development.
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Malthus's Theory (1766-1823): Malthus was more famous for his population theory; however, he had
accurate theories about economic issues such as market saturation and economic crises.
Ricardo's theory (1772-1823): He developed the classical school by Smith by adoption of Malthus's
theory. Smith emphasized on "production", while Ricardo focused on "income distribution" topic, and
later neoclassics (his students) concentrated on "efficiency". His two famous theories were "law of
diminishing returns" and "comparative advantage". In law of diminishing returns, he believes that
the economic growth in a capitalist society is achieved thanks to cost-effective food which means low-
wage industrial workers and higher profits for capitalists, increasing the possibility of capital
accumulation in industry, producing more and finally increased total economic revenue. According to
Ricardo, the increased agricultural productivity (compared to industry) is the basic foundation of
economic growth. By the help of "opportunity cost" concept, Ricardo concludes in theory of
comparative advantage that the countries should not (according to previous economists) solely
concentrate on production of goods in which they have absolute advantage (in comparison to other
countries), but they also act based on comparative advantage by considering the replacement cost of
a product with another product.
Classical growth model: The classical economic growth model will arise according to classical
economists' views. From their perspective, the development of capitalist economies is a competition
between technological progress and population growth and it has the technology advance on the
priority for a period, but it will end one day (or face with recession) and thus the economy will be
declining. In short, there is not any real progress in this model. However, the growth models offered
by classical economists promise the stop of economic progress in these countries in the long run when
the per capita income will not be grown any longer.
Karl Marx's theory (1818-1883): Unlike Smith, Malthus and Ricardo, Marx did not consider the
capitalism unchangeable. According to him, the capitalism is as one of the production methods which
is began with primitive commune, and then enters the slavery stage and finally leads to feudal
production in communities. He believes that the capitalism is the fourth stage of current production
methods in the world and will eventually collapse. This collapse will not be due to the recession, but
also for social reasons, and eventually the world will reach a final stage called the communism.
Marx's economic capitalism growth model: According to Marx, each production method (primitive
commune, slavery and feudalism, capitalism, socialism and communism) has two major
characteristics called the "productive forces" and "relations of production". The productive forces
refer to technical structure of production (such as the level and rate of change of technology and tools
of production, and natural resources). According to fundamental point of Marx's view, the capitalists
continue the capital accumulation to earn higher profits, but ultimately, the increase or decrease
benefits has a strong dependence on level of value added, not the rate of population growth or low-
quality agricultural lands.
Schumpeter's theory (1950-1870): According to Joseph Schumpeter, the capitalism machine is able to
produce high rates of economic growth in addition to compensation of its social losses. Mathematical
model of his theory has three difference with classical and Marx models: Introduction of interest rate
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and its importance; separation of different types of investment (particularly in the field of
innovation); and emphasis on centrality of entrepreneurship for economic growth.
Lewis-Fei-Ranis development model (LFR): Arthur Lewis's model (1954) was the first and foremost
development model which implicitly at least focused on rural-urban migration process, and was later
formulated and developed by John Fei and Gustav Ranis (1961). This model was known as the
general development process theory of "labor surplus" in the third world countries during the 1950s
and 1960s. In this model, the economy consists of two sectors: First, traditional sector (current rural
section), which is characterized by very low productivity (even zero) and labor "surplus". Second, the
industrial sector (intra-urban sector) which has high productivity; and the labor is gradually
absorbed to it from rural sector. This model focuses on the process of labor transfer and employment
growth in industrial sector (modern) and is due to the development and growth of its production.
(Motavasseli, 2003). The examples of economic development indices or level of development are as
follows (Salimifar, 2003):
A. Per capita income: The per capita income is obtained from dividing the national income of a
country (GDP) by its population. In different countries, this simple and evaluable index is usually
compared with per capita income of developed countries.
B. Purchasing power parity (PPP): The PPP is used since the per capita income is calculated
according to local prices of countries, and the prices of goods and service are not the same in different
world countries. In this method, the production rate of various goods in any country is multiplied by
global prices of those goods; and their GDP and per capita income are calculated after necessary
adjustments.
C. Stable income index (GNA, SSI): The effort to overcome the deficiencies of per capita income and
paying attention to "sustainable development" rather than "economic development" has led to
measurement of stable income index. In this method, the environmental costs of production and
economic growth are also considered in national accounts (either as compensation or as improved
resources and environment) and then the rate of growth and development is obtained.
D. Combined indices of development: Since the early 1980s, some economists suggested the use of
combined indices rather than relying on a single index for measuring and comparing economic
development between countries. For instance, the weighted combined index introduced by
McGranahan (1973) based on 18 main indices (73 sub-indices) (the Human Development Index was
then introduced).
E. Human Development Index (HDI): This index was introduced by the United Nations in 1991 and
is calculated based on these indices: The real per capita income (based on purchasing power parity
index), life expectancy (at birth) and access to education (which is a function of adult literacy rate
and the average years of going to school) (Salimifar, 2003).
In addition to the above-mentioned cases, the extent of poverty, employment rate, the change in
economic structure, decentralization and increased participation rate, access to healthcare facilities
Factors affecting the economic development of Azerbaijan
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and access to education facilities are among the most important indices of development
measurement (Tavallaei, 2014).
3- Review of research literature
The development and its determinants have been investigated in numerous studies. Obviously, the
review of empirical studies along with theoretical issues helps to identify the appropriate variables
as well as developing the optimal model. Knight, Dillanueva and Loagza (2013) studied the
importance of human resources and public investment in growth of countries using panel data and
cross-country data and time series for 98 developed and developing countries during 1960-1985.
They have concluded that entering the degree of freedom of foreign trade and level of infrastructure
economic costs in growth model estimation equation increases the effect of public investment on
growth process and thus enhances the investment efficiency which is achieved in the light of
commercial regime liberation and change in infrastructures. Furthermore, this study indicates that
the trade restrictions such as increased tariffs on imports of capital and intermediate goods have
negative impact on growth.
James Raymo's study (1995) is another conducted study on the role of human capital in economic
growth in 1995. In this study, he measures the human capital role in GDP or economic growth using
data of 1970-1991. Based on obtained results, the education expenditure spent on education and the
labor's average years of school have had significant positive impact on economic growth of Japan as
two indices of human capital.
Fernandez et al. (2001) studied the model uncertainty in growth regression through Bayesian model
averaging on a sample of 140 countries and rated the determinants of growth in a period of 1992-
1960.
Wang, Hu and Yu (2007) studied the correlation between educational measures and economic growth
in China. Comparing the R&D expenditure efficiency in Hebei Province of with seven other provinces
of China, they sought to find ways to improve the performance of research and education on
economic growth. They measured the effects of research and education on economic growth of China
through data of 532 large and medium-sized enterprises in Hebei Province and based on data
envelopment analysis (DEA).
In a study on the impact of using the higher education graduates on economic growth of Iran,
Almasi, Soheyli & Sepahban (2010) introduced the growth as an endogenous variable which was the
function of investment in human, physical capital, etc. The results of this study indicate that the
impact of human capital on growth variable is more than physical capital.
In a study based on time series of large industrial factories, Dejband (2005) estimated the large-scale
production function and growth model. The obtained results indicate that the research and
educational capital accumulation in all estimated models at the macro level is among the most
important factors of economic growth in Iran. The confirmed human capital, research and physical
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capital in all models indicate the priority of both human capital and research to physical capital in
its models.
In a research entitled "The determinants of economic growth in different countries", Jalalabadi and
Bahrami (2010) studied the impact of variables affecting the economic growth in 7 theories of
economic growth for 79 countries in two groups of total countries and non-developed countries (52
countries) during the period of 1970-2006. Based on obtained results, the factors affecting the
economic growth of different countries can be different. On this basis, various theories of economic
growth do not have the same impact on their economic growth for different groups of countries based
on the impact of alternative variables.
In a research entitle "The factors affecting economic growth of Iran" An approach to Bayesian
approach with definition of uncertainty in growth function", Kafaei and Jozi (2013) determine the
factors affecting the economic growth of Iran. According to results, from total of 18 explanatory
variables, only three variables namely the oil income, human capital and private investment are
important factors affecting the economic growth of Iran.
In a latest study on this field, Ostadi (2016) studies the determinants of economic growth according
to effects of subsidy reform plan and increased energy prices. According to obtained findings, the
value-added of different economic sectors has a significant positive effect on GDP and economic
growth, but the governmental expenditure has a negative and significant correlation with them. The
increased governmental involvement in economy reduces the cost of private investment and growth
by algebraic substitution phenomenon and replacement of public sector with private sector. Based on
results of this study, the prices of energy carriers have significant negative impact on them.
4- Materials and methods
According to the literature and based on conducted studies on this field, the following model is used
to examine factors affecting the economic development in Azerbaijan during 1995-2015 based on
models by Lucas (1988) and Raymo (1995):
Where, the applied variables and type of calculation are as follows:
Rg: Rate of production growth;
OPEN: Trade openness;
FDI: Foreign direct investment;
EXH: Expenditure of health to total expenditure;
RPO: Rate of population growth;
FIN: Ratio of domestic credit granted to private sector compared to GDP;
RD: Research and development expenditure compared to GDP;
ε is the error term and i index indicates the surveyed period. It should be noted that all required
figures are extracted from information published by the World Bank.
When the sample size is small, the use of OLS for estimating the long-run correlation due to non-
considered short-run dynamic interactions between variables will not provide the unbiased estimate
Factors affecting the economic development of Azerbaijan
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(Tashkini, 2005). Given that the studied period covers the years of 1995- 2015, it is suggested
applying a models which considers the short-run dynamics in order to estimate the model coefficients
more accurately because of small number of observations (due to the lack of available figures) for
investigating the factors affecting the economic development. In this regard, ARDL model is selected
and it is estimated by Microfit software.
5- Results and findings
5-1- Evaluation of variable statics
The evaluation of variable statics of time series model is the first step to estimate this model.
Therefore, Augmented Dickey-Fuller Test is used to investigate the statics of time series; and the
summary of test results for each studied variable is presented in the following table and indicates
the statics of all studied variables. Among all variables except for foreign direct investment (FDI),
which has static level, all other variables are static in the first-order difference.
Table 1: Static test of studied variables according to Augmented Dickey-Fuller Test
Variable
name
Dickey-
Fuller
test
MacKinnon critical
values Probability Intercept Process Result
1% 5% 10%
RG -3.42 -3.83 -3.02 -2.65 0.0229 It has It does not
have I (1)
EXED -7.664 -4.12 -3.14 -2.71 0.0001 It has It does not
have I (1)
OPEN -3.06 -2.69 -1.96 -1.69 0.0041 It does
not have
It does not
have I (1)
FDI -3.35 -3.83 -3.02 -2.65 0.02 It has It does not
have I (0)
EXH -5.58 -3.85 -3.04 -2.66 0.0003 It has It does not
have I (1)
RPO -4.44 -3.85 -3.04 -2.66 0.0031 It has It does not
have I (1)
FIN -5.07 -3.88 -3.05 -2.66 0.0010 It has It does not
have I (1)
RD -4.15 -3.92 -3.06 -2.67 0.0064 It has It does not
have I ( 1 )
Source: Research authors
5-2- Results of estimated ARDL model
Here, the target model is estimated through autoregressive distributed lag model (ARDL). Before
investigating the long-run correlation between variables of model, it is necessary to test the long-
term convergence between available variables because the total coefficient of lagged dependent
variable should be smaller than 1 so that the dynamic model of autoregressive distributed lag model
will have convergence towards the long-run equilibrium (∑ ̂ .
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The results of estimating the short-run dynamic equation through Microfit software are shown in the
following table. Given the annual data of this study and since there is a low number of studied data,
Schwarz Bayesian Information Criterion (SBIC) is used to determine the optimal lag, so that the loss
of too much degree of freedom is prevented; hence, the lag number criterion is selected for model
variables. The test for existence or lack of long-run correlation can be done based on these results.
Based on what is shown in table, since the coefficient of dependent variable (RG) is less than 1, the
studied model is close to long-run equilibrium model. Furthermore, the results indicate the
significant impact of all studied variables except for trade openness. Furthermore, the significance of
f-statistic at the level of 99% requires the significance of whole model, and the coefficient of
determination equal to 0.98 refers to high explanatory power of model.
Table 2: Results of estimated dynamic model
Autoregressive Distributed Lag Estimates
ARDL(1,0,1,1,1,1,1) selected based on Schwarz Bayesian Criterion
*******************************************************************************
Dependent variable is RG
16 observations used for estimation from 1998 to 2013
*******************************************************************************
Regressor Coefficient Standard Error T-Ratio[Prob]
RG(-1) -.44722 .21659 -2.0648[.031]
OPEN .055438 .37689 .14709[.892]
FDI -1.0636 .39176 -2.7149[.073]
FDI(-1) 1.1372 .24631 4.6169[.019]
EXH 95.9139 23.2380 4.1275[.026]
EXH(-1) 51.3726 13.9626 3.6793[.035]
RPO -30.5010 6.6748 -4.5696[.020]
RPO(-1) 25.9475 5.6655 4.5799[.020]
FIN .063652 .48995 .12992[.005]
FIN(-1) 1.0040 1.1985 .83770[.464]
RD 154.4107 113.0968 1.3653[.026]
RD(-1) -231.0781 65.0006 -3.5550[.038]
C 171.2515 50.7866 3.3720[.043]
*******************************************************************************
R-Squared .98078 R-Bar-Squared .90390
S.E. of Regression 2.8365 F-stat. F( 12, 3) 12.7579[.030]
Mean of Dependent Variable 11.8406 S.D. of Dependent Variable 9.1501
Residual Sum of Squares 24.1367 Equation Log-likelihood -25.9922
Akaike Info. Criterion -38.9922 Schwarz Bayesian Criterion -44.0140
DW-statistic 3.2467 Durbin's h-statistic -4.9927[.000]
*******************************************************************************
Source: Research authors
The co-integration between variables should be ensured after estimation of ARDL equation. As
mentioned, if the sum of lagged coefficients related to dependent variable is smaller than 1, the
dynamic model will tend towards long-term equilibrium model. The following hypothesis test should
be done to test the long-term co-integration test in autoregressive distributed lag model:
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The required value of t-statistic for doing the above-mentioned test is calculated as follows:
Where, SE is the standard deviation of variable i coefficient.
After calculation of the above-mentioned statistics, we should compare it with critical quantity by
Banerjee, Dolado & Mester (1992). If the t-statistic is greater than critical value, the H0, or the lack
of convergence is rejected and the long-run correlation between variables of model is confirmed.
Therefore, the long-run equilibrium correlation between variables of model can be studied by
rejecting the H0 and this provides the basis for use of error correction model in which the short-term
fluctuations of variables are connected to long-run equilibrium values.
The t-statistic quantity for doing the above-mentioned test is calculated as follows:
Since the absolute value of calculated statistics is higher than critical value by Banerjee, Dolado &
Mester, the null hypothesis based on the long-run correlation in favor of alternative hypothesis (long-
run correlation) is rejected, and there will be a long-run correlation. This result is obtained through
F-statistic of output. Therefore, the long-run correlation is also estimated and its result is presented
in the following table and indicates the positive and significant impact of trade openness, the
positive and significant impact of foreign direct investment, the positive impact of health
expenditure, and negative significant impact of population growth. However, the financial
development and R&D expenditure have not shown any significant effect.
Table 3: Results of long-run estimation of model
Estimated Long Run Coefficients using the ARDL Approach
ARDL(1,0,1,1,1,1,1) selected based on Schwarz Bayesian Criterion
*******************************************************************************
Dependent variable is RG
16 observations used for estimation from 1998 to 2013
*******************************************************************************
Regressor Coefficient Standard Error T-Ratio[Prob]
OPEN .038306 .26117 .14667[.003]
FDI .050850 .22359 .22742[.035]
EXH 101.7722 22.2345 4.5772[.020]
RPO -3.1464 3.6212 -.86889[.049]
FIN .73773 .77220 .95535[.410]
RD -52.9758 50.9685 -1.0394[.375]
C 118.3316 27.6357 4.2818[.023]
*******************************************************************************
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In accordance with any long-run correlation, there is an error correction model (ECM) which
connects the short-term fluctuations of variables to their long-run equilibrium values. The error
correction model is used to combine the short and long-run correction. The existence of cointegration
relationships between a set of economic variables provides the statistical basis for use of error
correction models. Error correction model connects the short-run fluctuations of variables to their
long-run equilibrium values. To adjust the error correlation model, we just need to put the error
terms of cointegration regression for estimation of long-run coefficients with a time lag as an
explanatory variable together with the first order difference of other variables of model, and then
estimate the coefficients of model by Ordinary Least Squares (OLS). The results of estimating the
error correction equilibrium for investigating how the short-run fluctuations of studied variables
lead to long-run equilibrium are presented in the following table. The coefficient related to ECM (-1),
which indicates the process adjustment speed of non-equilibrium, is taken into account in this model
as an important issue. In other words, the ECM coefficient indicates what percentage of target
variables are put in direction of their long-run procedure in any year.
Therefore, all coefficients of error correction model except for financial development and R&D
expenditure are significant with a probability of more than 90%. Error correction coefficient is also
estimated equal to 1.44 and it is statistically significant. The negative coefficient indicates that the
non-equilibrium move towards equilibrium in the long-run. The value of this coefficient indicates
that 84% of non-equilibrium of a period (year) is mitigated (adjusted) in the next period. This figure
indicates that the adjustment towards equilibrium is done with fairly good speed.
Table 4: Results of estimating the error correction model (ECM)
Error Correction Representation for the Selected ARDL Model
ARDL(1,0,1,1,1,1,1) selected based on Schwarz Bayesian Criterion
*******************************************************************************
Dependent variable is dRG
16 observations used for estimation from 1995 to 2015
*******************************************************************************
Regressor Coefficient Standard Error T-Ratio[Prob]
dOPEN .055438 .37689 .14709[.017]
dFDI -1.0636 .39176 -2.7149[.026]
dEXH 95.9139 23.2380 4.1275[.003]
dRPO -30.5010 6.6748 -4.5696[.002]
dFIN .063652 .48995 .12992[.900]
dRD 154.4107 113.0968 1.3653[.209]
dC 171.2515 50.7866 3.3720[.010]
ecm(-1) -0.8472 .21659 -6.6817[.000]
6- Summary and conclusion
In general, according to this section, this research considers the comprehensive variables in order to
study the factors affecting the economic growth and development in Azerbaijan. Therefore, the
following variables are considered for estimating their impact on GDP growth (Gt) during 1995-2015:
The trade openness (OPEN) is the first studied variable. Despite the fact that this variable has not
shown any significant impact in the short run, it has significant positive impact on growth in the
long run. This is consistent with results of research by Samimi et al (2009) and Dani (2007).
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The foreign direct investment (FDI) is the second studied variable. The obtained results indicate the
negative impact of this variable in the short run and its positive impact in the long run. The positive
long-run effect of this variable is consistent with results of research by Alipour and Ghadkachi
(2011), Liang, Qi et al (2005) and Kottaridi and Stengos (2010).
The ratio of health expenditure (EXH) to gross domestic product is the third variable; and the
obtained results indicate a significant positive influence of this variable on economic growth. This
result is consistent with results of research by Raeispour and Pajouyan (2013).
The rate of population growth (RPO) is another variable which is examined in this research for its
impact on growth. The results indicate its significant negative impact on economic growth. This
result is consistent with results of research by Bakhshi et al (2011).
Financial development variable (FIN), which is considered as the ratio of domestic credit granted to
private sector to GDP (DCP), is one of the most important studied variables. Based on the obtained
results, despite the fact that this variable has a positive significant impact in the short run, it does
not have any significant impact in the long-run. The obtained result about the short-run impact of
financial development variable is consistent with research by Salmani and Amiri (2009).
The last studied variable is related to ratio of R&D expenditure on production, and the results
indicate a significant positive correlation in the short-run and its insignificance in the long-run. The
significant and positive result of this variable in the short run is consistent with result of research by
Daghighi-Asli et al (2013).
The results of VECM model estimation indicate that the speed of short-run error equilibrium
towards the long-run equilibrium is equal to 0.84 and it is significant at the level of 5%. This
indicates the fairly good speed of equilibrium towards the long-run equilibrium.
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