Economic growth and its determinants across CEE countries

Over the last decades various economic approaches have been used to identify the sources of economic growth across individual countries. In our paper we use Growth Accounting approach developed by Solow to analyse the significant determinants of economic growth in ten Central and Eastern European countries over the time period from 2004 to 2012. The data source is Total Economy Database provided by The Conference Board. Total Economy Database is a comprehensive database with annual data covering GDP, population, employment, hours, labour quality, capital services, labour productivity, and total factor productivity for about 123 countries in the world. Total Economy Database was developed by the Groningen Growth and Development Centre (University of Groningen, The Netherlands) in the early 1990s and the database was extended with a module on sources of growth in January 2010. The contribution of labour quantity and quality, Information and Communication Technology capital services, non-Information and Communication Technology capital services and Total Factor Productivity to the growth of Gross Domestic Product is identified. Capital and Total Factor Productivity are found as a main source of economic growth. Moreover, the impact of Foreign Direct Investment inflow, investment on Research and Development, openness of the economy and life expectancy on Gross Domestic Product is identified.


Introduction
To think about the importance of economic growth we begin with assessing the long term performance of the Slovak economy.The real per capita Gross Domestic Product (GDP) in Slovakia grew from 6,300 EUR from 2004 to 13,300 EUR in 2013.This increase in per capita GDP corresponds to an average growth rate of 4.2 percent per year.To appreciate the consequences of apparently small differentials in growth rates we can calculate where Slovakia would have been in 2013, if it had grown since 2004 at 3.2 percent per year, one percentage point below its actual average rate.If Slovakia had begun in 2004 at the real per capita GDP of 6,300 EUR and had then grown at average 3.2 percent per year over the next 9 years, its per capita GDP in 2013 would have been 8,365 EUR, only 1.3 times the value in 2004 and 63 percent of the actual value in 2013 of 13,300 EUR.Then instead of ranking 46th in the world in 2013, Slovakia would have ranked 74th near Romania and Mauritius.Given perception helps us to highlight the importance of economic growth, not only in case of Slovakia, but across the whole world as well.What have a significant impact on the economic growth?Economists use various approaches to identify the elements of the economic growth.Researchers decompose economic growth into growth in labour, capital and productivity referred to as Total Factor Productivity (TFP) or Multifactor productivity (MFP).Determinants of the economic growth and TFP have been widely analysed by many authors.The majority of studies conclude that Foreign Direct Investment (FDI) inflow, economic freedom, Research and Development (R&D) expenditures, openness of the economy and life expectancy are positively and significantly correlated with GDP and TFP respectively.http://dx.doi.org/10.15414/isd2016.s12.07

Literature review
The paper is focused on recent studies in field of growth accounting, where the growth in GDP can be decomposed into growth in Labour, Capital and Total Factor Productivity.Moreover, the literature review is specified on studies, where the contribution of other factors on GDP were analysed, namely FDI, R&D expenditures, patents application, life expectancy, trade openness.
The sources of economic growth in EU countries in period 1981-2003 were decomposed by Musso and Westermann (2005).They found TFP as the most important determinant of economic growth in EU 1980s.More than 50 % or 1.3 percentage points of GDP was explained by TFP, less than 50% or 1.0 percentage points was accounted for by capital while labour had a broadly neutral effect on growth due to the offsetting effects from increases in employment and decreases in average hours worked.For the 1990s the results show a small decline in average real GDP growth, which essentially reflected a decline in the contribution from TFP by around one-third to 0.8 percentage point.By contrast the contribution from capital was broadly unchanged compared with that in the 1980s and labour made a positive contribution of around 0.4 percentage point or almost 20% of real GDP growth.Research also shows that the contribution from labour force growth was 0.5 percentage point in both the 1980s and the 1990s.However, in the 1980s most of this contribution was offsetted by a rise in the unemployment rate and a decline in average hours worked.In the same character, the higher contribution to growth from the labour supply in the 1990s reflected a decrease in the unemployment rate and a slower decline in hours worked.Recent study of Dombi (2013) examined the direct sources of economic growth and development in 10 post-socialist Central and East European countries in the period from 1995 to 2012.Author performed an empirical analysis based on the methods of growth accounting and development accounting.The results of the growth accounting analysis in period from 1996 to 2008 demonstrated that the most important sources of economic growth in ten investigated economies was the accumulation of physical capital and the growth of Total Factor Productivity, while the growth of labour productivity had often a marginal effects only.According to Mühlberger and Körner (2014) the TFP was the main source of GDP growth in Central and Eastern European countries in the period from 1994 to 2011.As reported by authors the annual average output growth in observed period was 3.5 percentage points and more than 2.0 percentage points (57.14 %) was explained by TFP.Physical capital contributed to GDP by 1.3 percentage points (37.14 %) and human capital contributed to GDP by 0.2 percentage points (5.72 %).The contribution of TFP on GDP was significant in research of Arratibel et al. (2007), as well.Authors conducted research in the period 1996-2005 at eight new EU members states (Czech Republic, Estonia, Latvia, Lithuania, Hungary, Poland, Slovenia and Slovakia) and identified that TFP growth made a very significant contribution to GDP growth in all new EU member states, with the exception of Latvia.On the accounting side, given relatively small changes in labour and capital inputs, high GDP growth rates necessitated fast growth in TFP.The economic explanation is that the transition process (involving privatisation, restructuring, higher competition, deregulation in product and labour markets, opening to international trade, FDI inflows, transfer of technologies, etc.) had forced a more efficient use of production inputs and better managerial practices which were captured by TFP.On the other hand, for most of the new EU member countries the contribution of labour to GDP growth was very modest or even negative in 1996-2000.
Determinants of economic growth have been widely analysed by many authors.The majority of researches concluded that FDI inflow, R&D expenditures, patents applications, openness of the economy and life expectancy were positively and significantly correlated with GDP and TFP.
Rapacki and Próchniak (2009) aimed to check whether the European Union (EU) enlargement contributed to economic growth of ten new member states from Central and Eastern Europe, including their real convergence towards the EU-15 development level.Authors econometrically tested the relationships between selected macroeconomic variables linked to the EU enlargement and the rate of economic growth of the CEE countries over the period 1996-2007.The variables comprised the progress of market or structural reforms, economic freedom, foreign aid and the FDI inflow.Their approach was based on neoclassical growth models (Solow, Mankiw) and beta and sigma convergence.Authors' results indicated that the EU enlargement significantly contributed to economic growth of the CEE countries and the econometric test of economic growth determinants unveiled that four variables were related to the EU enlargement: FDI inflow, economic freedom, progress of structural reforms, and aid inflow, were positively and significantly correlated with GDP growth rates in the CEE countries.Keller and Yeaple (2003) studied plants in the U.S.A (1987)(1988)(1989)(1990)(1991)(1992)(1993)(1994)(1995)(1996) and found a strong link between FDI and growth.Approximately 14 per cent of productivity growth over this period can be attributed to FDI spillovers.Furthermore, FDI spillovers seems to be stronger in high-tech compared to other sectors.Popescu (2014) found FDI and export level as an important driver of economic growth.Author´s paper generated insights into the significance of trade and FDI for the economic growth of CEE counties, the influence of FDI on productivity growth, the features of financial intermediation in the CEE region and the effect of financial and capital limitations on FDI.Bloom et al. (2004) investigated the relationship between life expectancy at birth and economic growth.Authors included life expectancy in an aggregate production function in an attempt to establish whether health influenced labour productivity and TFP.They used panel data covering the period 1960 to 1990 for 104 countries and they found that increased life expectancy had a positive effect on growth.A one-year improvement in the population's life expectancy contributed to an output increase of 4 per cent in their research.Miller and Upadhyay (2002), covered 83 countries between 1960 and 1989 and found that trade measured as a percentage of export in GDP was positively associated with TFP growth.They also showed that human capital was a threshold variable as evidenced when their study aimed to investigate how the correlation changed with economic development.For high levels of per capita income trade had a positive significant impact, although its effects were negative for low per capita incomes.

Data and Methods
Data on growth accounting is obtained from Total Economy Database (TED) (TED, 2015a) provided by The Conference Board.TED is a comprehensive database with annual data covering GDP, population, employment, hours, labour quality, capital services, labour productivity, and total factor productivity for about 123 countries in the world.TED was developed by the Groningen Growth and Development Centre (University of Groningen, The Netherlands) in the early 1990s, and starting in the late 1990s, it was produced in partnership with The Conference Board.As of 2007, the database was transferred from the University of Groningen to The Conference Board, which has maintained and extended the database since then.In January 2010, the database was extended with a module on sources of growth, including labour quantity and quality, capital services (non-ICT and ICT), and total factor productivity (TED, 2015b).The following data are used from TED: GDP growth, labour (Labour Quantity and Labour Quality), capital (Non-ICT Capital Services and ICT Capital Services), Total Factor Productivity Growth (TFPG) and the Share of labour compensation in GDP.The data on factors affecting TFP growth is obtained from EUROSTAT database.We examine the impact of determinants as FDI inflow as a percentage of GDP, expenditures on Research and Development per person (RaD), openness of the economy expressed as a percentage of export http://dx.doi.org/10.15414/isd2016.s12.07 on GDP (EX), life expectancy (LE) on GDP growth by regression analysis using statistical program STATA 12.0.The following table represents the descriptive statistics of the data used.As you can see, the data vary across the individual states of CEE region.

Growth Accounting
Following methodology is based on TED methodology for the Growth Accounting approach (TEDc, 2015).As we state, the growth in GDP can be decomposed into growth in labour quality, labour quantity, growth in ICT capita, non-ICT capital and growth in TFP.TFP growth is not measured directly; rather, it is obtained as a residual after accounting for the contributions of all other factors of production to growth in output.Assuming a neo-classical aggregate production function, the output growth, in our case GDP growth, can be decomposed into the contribution of aggregate capital input (K), aggregate labour input (L) and aggregate total factor productivity (A) growth as: where vK and vL are the share of capital compensation and labour compensation in nominal GDP, both averaged over the current and previous years.Under constant returns to scale vK + vL = 1, so that the capital compensation share can be obtained by subtracting labour compensation from nominal value added.ΔlnK is the capital services growth rate and ΔlnL is the labour input growth rate.ΔlnTFP is the growth of total factor productivity.In paper, we present the contribution of labour, split into the contribution of pure employment quantity (LH) and labour quality (LQ), and the contribution of capital services split into ICT and non-ICT capital.Then the equation 1 can be rewritten as: ∆ = ̅ , ∆  + ̅ , ∆  + ̅  ∆ + ̅  ∆ + ∆ (2) Subtracting ΔlnA from the equation 2 we can calculate the contribution of TFP to GDP growth as follows:

Results and Discussion
Following subchapter is based on the TED and deals with the decomposition of GDP growth.
After averaging (2004-2012) the values for the variables which are necessary to calculate the contribution of LQ, LH, ICT, non-ICT capital and TFP to GDP based on TED, we can conclude the following results (Figure 1).The contribution of labour quantity (LH) was insignificant or even negative in cases of Hungary, Latvia, Romania, Slovenia, Estonia and Lithuania.Slightly positive contribution of LH to GDP was seen in the case of Slovak Republic and Bulgaria.The importance of labour quality (LQ) was moderate in case of Hungary, Slovenia and Bulgaria.These findings are in line with the findings of other authors.Dombi (2013) claimed that the contribution of labour in GDP was moderate, insignificant and even negative in CEE region over the period 2008-2012.
Research of Mühlberger and Körner (2014) confirms our findings, as well.Contribution of ICT capital on GDP growth was important in case of Hungary, Bulgaria and Slovakia.In Hungary, the contribution of ICT capital had significant share on GDP of 168 %, while in http://dx.doi.org/10.15414/isd2016.s12.07 Bulgaria and Slovakia the share was 47 % and 34 %, respectively.In other countries in the CEE region the ICT capital contributed to GDP from zero percentage points in cases of Estonia, Lithuania and Latvia to 0.74 percentage points in case of Poland.Analysis revealed that, the contribution of non-ICT capital had the most significant impact on GDP growth in case of Bulgaria, Czech Republic, Estonia, Latvia, Lithuania and Slovenia.It accounted for the most in case of Latvia (119 % of GDP) and in Bulgaria (110 % of GDP).Dombi (2013) confirmed that the growth in capital had significant impact on GDP growth.We found similar results in studies of Arratibel et al. (2007), Iradian (2007) and Musso and Westermann (2005).Beside of contribution of labour quality, labour quantity, ICT capital and non-ICT capital, the contribution of TFP to GDP growth was also analysed.According to our research, the contribution of TFP to GDP had negative impact only in case of Bulgaria (-2.3 percentage points) and Hungary (-0.87 percentage points).TFP was the main source of economic growth in Poland and Romania.In the remaining countries in CEE region the TFP contributed to GDP form 0.17 to 1.40 percentage points.
According to our analysis, we state that the main determinants of economic growth in CEE region are the growth of non-ICT capital followed by ICT capital and TFP.Labour quality had only marginal effect on GDP and labour quantity even negative.The share of non-ICT capital on the GDP growth was in average 59 %, the share of ICT capital was 32 %, the share of TFP was 14 % and the share of labour quality and quantity on GDP growth was in average 11 % and -17%, respectively.The average growth of GDP in CEE region over the observed period from 2004 -2012 based on TED was 2.93 %, while the best performer was Slovakia and the least was Hungary followed by Slovenia.We found that our results were identical, or very similar to other authors' findings.On the other hand, we found a discrepancy between the importance of TFP growth.Musso and Westermann (2005), Arratibel et al. (2007), Ganev (2005), Mühlberger and Körner (2014) stated that TFP had a significant impact on GDP growth, but growth in capital stock had a more significant impact on GDP growth than TFP growth.Furthermore, we analysed the impact and the significance of selected variables on GDP growth.In order of the analysis we took FDI inflow as a percentage of GDP, expenditures on Research and Development per person (RaD), openness of the economy expressed as a percentage of export on GDP (EX), life expectancy (LE) into consideration.Based on regression analysis we can conclude that the determinants of GDP varied across individual states.As Table 2 indicates, the most common determinant of GDP growth across states was the openness of the economy.It can be caused by the fact that the countries in CEE region is mainly export oriented.It can be seen mainly in case of Slovakia and Estonia, where the share of export in GDP exceeds 70 %.The Life Expectancy at 1 year and Research and Development investments had also a significant impact on GDP growth.Foreign Direct Investments had significant impact on GDP only in the case of Hungary.The following table contains the significance level of t statistics.At level α=0.05 it indicates that if t stat is lower than 0.05 the selected variable has significant impact on GDP growth.Due to the clarity, the insignificant values of t stat are omitted.In case of Lithuania, we found all variables insignificant.http://dx.doi.org/10.15414/isd2016.s12.07Our findings are in line with the findings of the other authors mentioned in literature review.We can conclude that the variable with the most significant impact on GDP growth over the observed period was the openness of the economy.

Conclusion
In previous several chapters we aimed to find the significant determinants of economic growth.Based on literature review we can conclude that we can divide the GDP growth into growth in labour, capital and TFP.Furthermore, we state that GDP growth can be decomposed to the contribution of labour quantity and quality, ICT capital services and non-ICT capital services and TFP, as well.Based on TED methodology, we applied the Growth Accounting approach in order to found the determinants of economic growth in CEE region.According to our analysis we stated that the key determinants of economic growth in CEE region was the growth of non-ICT capital followed by ICT capital and TFP.Labour quality had only marginal effect on GDP and labour quantity even negative.The share of non-ICT capital on the GDP growth was in average 59 %, the share of ICT capital was 32 %, the share of TFP was 14 % and the share of labour quality and quantity on GDP growth was in average 11 % and -17%, respectively.The average growth of GDP in CEE region over the observed period from 2004 -2012 based on TED was 2.93 %, while the best performer was Slovakia and the least was Hungary followed by Slovenia.Moreover, we investigated the impact of selected variables on the economic growth represented by the growth in GDP.In order of the analysis we took FDI inflow as a percentage of GDP, expenditures on Research and Development per person, openness of the economy expressed as a percentage of export on GDP and life expectancy at 1 year into consideration.Base on regression analysis we found openness of the economy as a most significant variable with the impact on the GDP growth.

Figure 1 :
Figure 1: Decomposition of the sources of GDP growth

Table 1 : Descriptive statistics of the data
Note: FDI -Foreign Direct Investments inflow, RaDexpenditures on Research and Development, EXexport as a % share in GDP, LElife expectancy at 1 year Source: own processing based on Eurostat data