




































 
 
AGORA International Journal of Economical Sciences, http://univagora.ro/jour/index.php/aijes 

ISSN 2067-3310, E-ISSN 2067-7669 

Vol. 18, No. 1 (2024), pp. 65-73 

 

65 
 

IMPACT OF INNOVATION ON ECONOMIC GROWTH IN BALKAN 

COUNTRIES 

 

A. HYSAI, K. SULҪAJ 

 

Albina Hysaj¹, Kriselda Sulҫaj² 

¹ Epoka University, Albania 

https://orcid.org/0000-0001-9632-316X, E-mail: albinahysaj@gmail.com  

² Beder University, Albania 

https://orcid.org/0000-0001-8168-2434, E-mail: kriseldasulcaj@gmail.com  

 

Abstract: Innovation plays a crucial role in the daily activities of economic units and 

its impact extends to the macroeconomic level as well. After the last pandemic, firms and even 

nations are aiming to adopt the new reality. They are employing advanced technology to 

develop innovative products and approaches for customers and markets. This study analyzes 

the impact of innovation on economic growth in Balkan Countries by using annual data for the 

period between 2011 and 2022. This study uses the individual pillars of the Global Innovation 

Index as the explanatory variables of GDP Growth rate. Through a panel data analysis, the 

findings of the study suggest that creative output and infrastructure have a positive significant 

effect on the GDP growth rate, while the effect of institutions is negative. The test employed 

failed to prove any impact of other pillars of innovation on economic growth meaning that the 

impact of other pillars is still insignificant. The findings of this study may serve policymakers 

to work on the direction of enhancing the impact of all innovation pillars on the economic 

growth rate.  

Keywords: innovation, GDP growth, sustainable development, innovation pillars 

       

INTRODUCTION 

      With the fast development of informational technology and the involvement of 

artificial intelligence in every activity, the competitiveness among regions, countries, 

industries, firms, and even individuals and professionals has known significant growth. It is 

difficult to achieve growth and development without the involvement of innovation and 

innovative processes (Živanović et al. 2023). Operating in a globally dynamic environment and 

context has shifted the attention of policymakers to the innovation and exploration of new 

opportunities and economic activities. The governments and monetary authorities seek to 

achieve a high economic growth rate by focusing on factors that will serve this aim.  

     All the economic theories emphasize the significance of technological advancement 

and innovation in increased productivity and economic growth. Adam Smith the most 

important representative of classical theory, in his book Wealth of Nations (Smith, 1776), 

defines that the determinants of output are the factors of production such as land, labor, and 

capital. Classical theory highlights the role of technological advancement and innovation as a 

key driver of the increased productivity of land and labor. Schumpeter (1911) is the first to 

emphasize the role of innovation and entrepreneurship in economic growth (Ziemnowicz, 

2013).  

https://orcid.org/0000-0001-9632-316X
mailto:albinahysaj@gmail.com
https://orcid.org/0000-0001-8168-2434
mailto:kriseldasulcaj@gmail.com


 
 

IMPACT OF INNOVATION ON ECONOMIC GROWTH IN BALKAN COUNTRIES 

 

66 
 

Solow (1956) and Swan (1956) shaped the neoclassical economic growth theory 

(Dimand, 2009). Based on their model, economic growth is a function of factors of production 

such as capital, labor, and technology. While acknowledging the limited sources of capital and 

labor, the authors emphasize technological advancement as the primary driver of economic 

growth. The endogenous economic growth theory considers technological change as an 

endogenous factor. (Romer, 1994) highlights that the combination of human capital with 

knowledge brings innovation which contributes to economic growth by higher productivity. 

The purpose of this study is to analyze how innovation has impacted the economic 

growth in the Balkan region the recent years. Figure 1 gives information regarding the GDP 

growth rate of Balkan countries as e proxy for economic growth. As seen in the figure, the 

economic growth of all Balkans except Greece follows the same trend. As an aftermath of the 

financial crisis, the Greek economic growth had a downtrend, and it reached a value of -10.01% 

in 2011. In 2020, because of the Covid-19 pandemic crisis, all countries besides Turkey had 

negative economic growth with the lowest value of -15.3% reached by Montenegro.  

 

Figure 1.  

GDP growth annual % 

 
Source: World Bank Database  

       

 This study utilizes the change in the Global Innovation Index (GII), which is measured 

and published by the World Intellectual Property Organization for 132 nations, as an indicator 

of innovation. Two sub-indexes constitute the Global Innovation Index. The first sub-index, 

Innovation Input, measures elements such as institutions, human capital, research, 

infrastructure, and market sophistication. The second sub-index, Innovation Output, gauges 

knowledge and technology outputs as well as creative outputs. 

 

 

 

 

 

 



 
 

Albina HYSAJ, Kriselda SULҪAJ 

67 
 

Figure 2 

The composition of the Global Innovation Index (GII) 

 
Source: World Intellectual Property Organization 

       

Based on a report published by the World Intellectual Property Organization for 2022, 

Slovenia has been the leading country to embrace innovation in the region with the highest GII 

value for many years. In recent years, starting from 2020, Bulgaria has emerged as the most 

innovative Balkan country, ranking 35th, followed by Turkey and Croatia for 2022. 

 

Figure 3  

Global Innovation Index (GII) Value 

 
Source: World Intellectual Property Organization 

(Cvetanovic et al, 2014; Despotovic et al, 2014) investigate the level of innovation and 

the relationship between innovation and competitiveness for a group of chosen Western 

Balkans and European Union countries. The authors find that EU countries’ level of innovation 

is higher compared to Western Balkan countries. There is no evidence of a relationship between 

innovation and competitiveness in Western Balkan, while there is a strong correlation in EU 

countries. Although macroeconomic factors, monetary and fiscal policies, country competitive 

advantages, and political risks explain economic growth, this study’s focus is the investigation 

of the role of innovation on economic growth. The next section briefly introduces the existing 

literature on the research topic, followed by the methodology, main findings, and conclusions.  



 
 

IMPACT OF INNOVATION ON ECONOMIC GROWTH IN BALKAN COUNTRIES 

 

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LITERATURE REVIEW 

The growing significance of innovation has heightened the curiosity of researchers and 

scholars about its impact on growth and development. In their studies spanning from 1989 to 

2014, Maradana et al. (2017; 2019) investigate the enduring relationship between innovation 

and economic growth in the European Economic Area. They reveal the presence of both 

unidirectional and bidirectional causality relationships between innovation and economic 

growth. The authors observe that in various countries, this relationship is influenced by diverse 

indicators of innovation utilized. Kacprzyk & Doryń (2017) make a comparison analysis 

between the EU's old and new members regarding the role of innovation in economic growth. 

The authors find that growth strategies might be different for different countries, and to 

strengthen the impact of innovation on economic growth, governments should focus on policies 

that will contribute to innovation. 

     Nihal et al. (2023) examine the impact of innovation on economic growth in G8 

countries. They find that innovation positively affects economic growth in those countries, 

which is especially significant in the fields of technology and research and development. 

Sarangi et al. (2022) investigate the causal short-term and unidirectional long-run relationship 

between innovation and economic growth in G20 countries. They find that this relationship is 

significant, even though different variables of innovation impact economic growth differently.  

     Ulku (2004) investigates the role of innovation on GDP per capita from 1981 to 

1997. The empirical analysis suggests a positive relationship between innovation and economic 

growth in both OECD and non-OECD countries. Another study that suggests a positive 

relationship between innovation and economic growth was conducted by (Pece et al., 2015)The 

authors employ multiple regression analysis to explore the relationship between economic 

growth and various innovation variables, including research and development expenses, as well 

as the number of trademarks and patents, across Central and East European countries. 

      Dempere et al. (2023)  investigate the relationship between innovation, economic 

growth, and other macroeconomic variables, using the main pillars of the Global Innovation 

Index as a proxy for innovation. Through a panel data analysis of 120 countries, the authors 

conclude that innovation positively affects the economy and that all pillars of innovation have 

a crucial role in the economy. Besides the impact on the economy, innovation has a significant 

role in recovering the economy from crises and financial distress (Hausman & Johnston, 2014). 

     (Özdener, 2020) analyzes the impact of innovation on economic development in the 

Turkish economy from 2006 to 2017. By analyzing the pillars of the Global Innovation Index 

the authors find a positive impact of innovation on economic development and other 

macroeconomic variables. Cameron (1996) investigates the role of innovation in economic 

growth. The study suggests a spillover of innovation from one country to another by 

emphasizing the importance of each country's effort toward innovation. 

 

METHODOLOGY 

     This study employs panel data analysis to investigate the role of innovation on 

economic growth in Balkan countries from 2011 until 2022. The GDP growth rate serves as the 

dependent variable in this study, which will be explained by the pillars of the Global Innovation 

Index such as Institutions, Human capital and research, Infrastructure, Market sophistication, 

Business sophistication, Knowledge and technology outputs, and Creative outputs. The data 



 
 

Albina HYSAJ, Kriselda SULҪAJ 

69 
 

utilized are sourced from the databases of the World Bank and the World Intellectual Property 

Organization, which also publishes the Global Innovation Index. 

The hypotheses that are assessed are: 

H1. Institutions positively affect economic growth. 

H2. Human capital and research positively affect economic growth. 

H3. Infrastructure positively affects economic growth. 

H4. Market sophistication positively affects economic growth. 

H5. Business sophistication positively affects economic growth. 

H6. Knowledge and technology outputs positively affect economic growth. 

H7. Creative outputs positively affect economic growth. 

     Preliminary tests are conducted to ensure that ordinary least square estimates yield 

optimal and unbiased results. The stationarity of the series is assessed using the Philips Perron 

test. The test indicates that series such as GDP growth rate, human capital and research, 

infrastructure, institutions, knowledge and technology market sophistication and business 

sophistication are stationary at level, while the creative outputs variable is stationary at the first 

difference.  

 

Table 1  

Series stationarity estimation. 

Source: Author | E-views 10 

 

Multicollinearity analysis is utilized to demonstrate the absence of correlation among 

explanatory variables, ensuring unbiased results. 

Table 2 

Correlation Matrix 

Source: Author | E-views 10 

 

As the values are lower than 80%, the correlation matrix indicates that the independent 

variables are not correlated to each other, thus the no correlation assumption is satisfied.  

Variable Philips-Perron Probability Order of cointegration 

GDP Growth rate 101.42 0.000 I(0) 

Business Sophistication 128.53 0.000 I(1) 

Creative Outputs 102.26 0.000 I(1) 

Human Capital and Research 73.07 0.000 I(0) 

Infrastructure 69.48 0.000 I(0) 

Institutions 34.99 0.039 I(0) 

Knowledge and Technology 49.12 0.000 I(0) 

Market Sophistication 36.81 0.025 I(0) 

 

Variables LBS LCO LHC_R LINF LINS LKN_T LMS 

LBS 1       

LCO 0.538 1      

LHC_R 0.454 0.427 1     

LINF 0.089 0.025 0.042 1    

LINS 0.391 0.380 0.259 0.217 1   

LKN_T 0.545 0.472 0.380 0.231 0.256 1  

LMS -0.261 -0.001 -0.138 -0.112 0.098 -0.194 1 

 



 
 

IMPACT OF INNOVATION ON ECONOMIC GROWTH IN BALKAN COUNTRIES 

 

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The Hausman test is utilized to determine the appropriateness of either a fixed effect or 

random effect model for the panel data analysis. Based on the results of this test, a random 

effect model will be used.  

 

Table 3  

Hausman Test 

Source: Author | E-views 10 

 

Zero conditional mean is another important assumption. Based on the results of the test 

it is noticed that the mean value of error residuals equals 3.74E-15. A further step is analyzing 

the correlation between the error term residuals and explanatory variables. As shown in table 4 

the correlation coefficients are remarkably close to zero. Both results indicate that the zero 

conditional mean assumption is satisfied.  

 

Table 4  

Correlation matrix of residuals 

Source: Author | E-views 10 

 

The two last assumptions that should be satisfied are independence of error terms which 

is related to the lack of serial correlation and a constant variance of residuals for all levels of 

independent variables, known as homoskedasticity. 

Table 5  

Heteroskedasticity - Breusch-Pagan Test. 

Source: Author | E-views 10 

 

Based on the results of the heteroskedasticity test, as both the probabilities of the 

dependent variable and the square of dependent variables are zero, the homoskedasticity 

assumption is not satisfied.  

 

 

Hausman test Coefficients 

Chi-Sq. Statistic 7.956012 

Prob.  0.3365 

Degree of freedom 7 

 

Variables RESID01 

LBS -5.093e-14 

LCO -0.0244828 

LHC_R 1.129e-14 

LINF -7.673e-14 

LINS -2.183e-16 

LKN_T -2.899e-14 

LMS 5.428e-14 

 

Depended variable Resid01^2    

Variable Coefficient Std. Error t-Statistic Prob.   

C 5.472601 0.878759 6.227645 0.0000 

GDP -3.979918 0.171216 -23.24496 0.0000 

GDP^2 0.827515 0.019193 43.11569 0.0000 

 



 
 

Albina HYSAJ, Kriselda SULҪAJ 

71 
 

Table 6  

Serial Correlation Durbin-Watson Test. 

Source: Author | E-views 10 

The results of the test indicate that as the probability of AR (1) is higher than 5%, the 

regression is free of serial correlation. As a result, only the homoskedasticity assumption is 

violated thus it is necessary to use a model that adjusts the standard errors of coefficients to 

address the presence of the heteroskedasticity. 

  

THE RESULTS 

According to the Hausman test, the random effect model is deemed suitable for 

analysis. Equation (1) is the equation estimated, while Table 7 shows the regression estimation 

output by using the White Diagonal coefficient covariance method.  

GDP Growth% = 𝛽0+𝛽1𝐿𝐵𝑆𝑖𝑡+𝛽2𝐿𝐶𝑂𝑖𝑡 + 𝛽3𝐿𝐻𝐶_𝑅𝑖𝑡 + 𝛽4𝐿𝐼𝑁𝐹𝑖𝑡 + 𝛽5𝐿𝐼𝑁𝑆𝑖𝑡 + 𝛽6𝐿𝐾𝑁_𝑇𝑖𝑡 + 𝛽7𝐿𝑀𝑆𝑖𝑡 +μ    (1) 

 

Table 7  

Regression estimation output 

Source: Author | E-views 10 

      

The results of the regression estimation output show that only three variables such as 

creative outputs, infrastructure, and institution are significant determinants of GDP growth rate 

in Balkan countries. The impact of creative output and infrastructure is positive, thus the third 

and seventh hypotheses cannot be rejected. Those results are in line with Özdener (2020), and 

Dempere et al. (2023), who suggest a positive impact of innovation in economic growth. The 

impact of institutions is negative so the first hypothesis cannot be accepted. Institutions as a 

pillar include the political, regulatory, and business environment. Because in Balkan countries 

the informal economy and corruption still have a significant presence, innovation may not have 

the desirable impact on economic growth. As the probability value of all other coefficients is 

higher than 5% none of the other hypotheses can be accepted, suggesting that the role of other 

pillars of innovation on economic growth is still insignificant and limited.  

Depended variable Resid01    

Variable Coefficient Std. Error t-Statistic Prob.   

C 0.177068 0.303211 0.583976 0.5605 

AR(1) -0.169178 0.091089 -1.857282 0.0660 

 

Dependent Variable: GDP Growth rate %   

Method: Panel EGLS (Cross-section random effects) 

Total panel (unbalanced) observations: 120 

White diagonal standard errors & covariance (d.f. corrected) 

Variable Coefficient Std. Error t-Statistic Prob.   

BS 5.402 6.967 0.775 0.4397 

D(CO) 13.233 4.689 2.822 0.0056 

HC_R -3.981 3.970 -1.003 0.3182 

INF 12.069 4.420 2.730 0.0074 

INS -19.392 8.127 -2.386 0.0187 

KN_T -2.654 3.416 -0.777 0.4389 

MS 3.066 5.159 0.594 0.5535 

C 14.795 14.588 1.0141 0.3127 

R-squared 0.129 Adjusted R-squared 0.0746 

F-statistic 2.371 Prob(F-statistic) 0.0268 

 



 
 

IMPACT OF INNOVATION ON ECONOMIC GROWTH IN BALKAN COUNTRIES 

 

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CONCLUSIONS 

      This study investigates the impact of innovation on economic growth in Balkan 

countries from 2011 until 2022 using the Global Innovation Index, its sub-indexes, and pillars 

as a proxy for innovation. Panel data analysis and a random effect model are employed in the 

analysis. The findings of the study suggest that creative output and infrastructure have a 

positive significant effect on the GDP growth rate, while the effect of institutions is negative. 

The test employed failed to prove any impact of other pillars of innovation on economic 

growth. Apart from the modest contribution in enriching the existing literature, the findings of 

this study may serve policymakers to work on the direction of enhancing the impact of all 

innovation pillars on the economic growth rate. 

The main limitation of this study is the brief period considering the annual frequency 

of data. Another limitation stands on the fact that the subject of this study is the unidirectional 

relationship between innovation and economic growth, while the bidirectional relationship is 

significant to be studied as well. Including other variables that affect the economic growth rate, 

analyzing the effect of corruption in each country, dividing the EU countries from non-EU 

countries, and making a comparison analysis may be a suggestion for future research.  

 

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