Financial performance (dis)parity in post-transition Europe

Mošnja-Škare, Lorena Article Financial performance (dis)parity in post-transition Europe Contemporary Economics Provided in Cooperation with: VIZJA University, Warsaw Suggested Citation: Mošnja-Škare, Lorena (2024) : Financial performance (dis)parity in post-transition Europe, Contemporary Economics, ISSN 2300-8814, University of Economics and Human Sciences in Warsaw, Warsaw, Vol. 18, Iss. 1, pp. 1-16, https://doi.org/10.5709/ce.1897-9254.523 This Version is available at: https://hdl.handle.net/10419/297645 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen. 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Decades after the transition processes have spread across Central, Eastern, and South-Eastern Europe (CESEE), the former Soviet Union, and the Baltic, it was interesting to perform the post-transition and non-transition advanced European economies comparison to capture the outcomes of the 'catching-up process' . In this analysis, I tried to reach the results of this ‘catching process’ using the firm-level accounting data, namely, enterprises' annual accounts rather than countries' national accounts. The goal was to evaluate if post-transition countries' enterprises have reached the financial performance of non-transition countries' enterprises across Europe, three decades after the transition processes began. The research captured firm-level financial performance aspects revealing some differentiators, namely, financial report indicators that differed for the enterprises belonging to post-transition countries in comparison with the ones belonging to non-transition countries in Europe. The findings related to the liquidity, solvency, indebtedness, profitability indicators, and labor intensity ratio were derived by logit regression models. The observations for 569 European companies were provided by Orbis Europe for the year 2021 annual accounts. According to the results, enterprises in post-transition countries, characterized by lower total assets and working capital scale, were likely to have lower profit margins, share of employees’ costs in operating turnover, current ratio, and gearing, while higher solvency and liquidity ratio. Mild marginal effects indicated the gap narrowed but with still existing significant disparities, particularly in the field of liquidity. 1. Introduction1. Introduction Decades have passed after early transition processes appeared across Central, Eastern, and SouthEastern Europe (CESEE), the former Soviet Union, and the Baltic with high expectations towards strong market and institutional developments, resulting in higher growth rates of economies in transition. There was numerous research performed upon transition processes that were going on, with screening studies upon the results reached after a decade or two (section 2), but there is scarce literature studying the post-transition results using the comparative approach among post-transition and non-transition European countries’ enterprises financial ratios. Usually, macroeconomic indicators were exploited to analyze the transition economies convergence process with advanced ones, with fewer studies performed at the firm-level, particularly in the field of firms’ annual accounts comparative analysis. While macroeconomic analyses have assessed the transition economies convergence results and provided prognostic models for the long Financial Performance (Dis)parity in Post-transition Europe ABSTRACT M41, G30, P27. KEY WORDS: JEL Classification: financial indicators, annual accounts, financial performance, transition. Juraj Dobrila University of Pula, Croatia Correspondence concerning this article should be addressed to: Lorena Mošnja-Škare, Juraj Dobrila University of Pula, Zagrebačka 30, 52100 Pula, Croatia. E-mail: [email protected] Lorena Mošnja-Škare Primary submission: 14.10.2023 | Final acceptance: 17.11.2023 2 Lorena Mošnja-Škare 10.5709/ce.1897-9254.523DOI: CONTEMPORARY ECONOMICS Vol. 18 Issue 1 1-162024 run, this research aimed to evaluate their catchingup process with developed economies at the firm’s level. The goal was to assess if post-transition countries' enterprises have reached the financial performance of non-transition countries' enterprises across Europe. Considering three decades after the transition processes beginnings passed, lower discrepancies were expected, so the following hypothesis was developed: H1: The financial performance doesn’t differ substantially between European post-transition and non-transition countries’ enterprises three decades after the transition. Just like macroeconomic aggregates derived from national accounts served the convergence analysis, the enterprises' annual accounts served as a relevant source for financial indicators comparisons. So, this research was performed based on annual accounts and financial indicators belonging to randomly sampled enterprises operating in posttransition European countries (CESEE and Baltic countries) in comparison with the ones running their business in non-transition European countries. The comparisons and nonparametric binary logistic regressions were based on 2021 annual accounts indicators. Along with descriptive statistics, logit models were developed over financial indicators of profitability, liquidity, solvency, leverage, turnover, and labor intensity of post-transition and non-transition firms from thirteen European countries, derived from the Orbis Europe financial data for 569 enterprises of various sectors and industries, mostly of small and medium size. The gap between financial reports indicators belonging to enterprises in post-transition vs. nontransition countries, if persisted, was expected to reflect worse financial performance as presented by lower profitability, turnover, liquidity, solvency, and higher leverage and labor intensity. There were significant negative correlations found for profit margin, the share of employees’ costs in operating turnover, current ratio, gearing ratio, working capital, and total assets scale, while positive correlation for liquidity and solvency ratios in the posttransition enterprises group. Although there were clear relations derived from the logit models developed, the financial ratios’ marginal effects were not sharp indicating the financial performance gap has narrowed, except it was still evident in the field of liquidity. The remainder of this paper is organized into five sections. After the introduction, a short literature review is provided in the second section. The third section describes the data source, defines the variables used, and provides descriptive statistics and methods employed. The empirical results are presented and discussed in the fourth section, followed by conclusions, research limitations, and future research steps in the fifth section. 2. Literature Overview2. Literature Overview Did the results meet the expectations, did the transition economies manage to get closer to catch up with developed ones? The questions arising in each phase of the transition process could look for answers in political, legal, social, institutional, macroeconomic, financial, and other spheres. Although the fields were tightly interrelated, I focused on the literature analyzing this topic from a macroeconomic approach as well as based on microeconomic and financial firmlevel approaches. Based on the neoclassical growth model, empirical studies dealt with the problem of convergence, searching how poorer economies caught up with richer economies with convergence analysis findings that „over the long run, poorer countries move around 2% of the remaining distance towards their steady-state growth path per year” (Rassekh et al., as cited in Mihaljek, 2018, p.3). Among the available post-transition period literature, it was mostly related to macroeconomic aggregates, GDP, GDP per capita, capital stock, labor force, gross fixed capital formation, unemployment rates, growth rates, and less to the firm-level variables. Some studies (like Neimke, 2003) used macroeconomic indicators for the financial sector to reach insights into the transition process and progress among CEE (Central and Eastern European) countries in approaching Western financial market standards, to raise investment and growth in such a way. Svejnar (2002) concluded that after more than a decade, „the income gap between transition and advanced economies has widened, ... while countries www.ce.vizja.pl 3 Financial Performance (Dis)parity in Post-transition Europe This work is licensed under a Creative Commons Attribution 4.0 International License. that developed a functioning legal framework and corporate governance have performed better than other countries.“ (p. 3) According to some studies (Gugler et al., 2013), after 20 years, control structure and institutional quality convergence in the West was still largely incomplete. Similarly, another research has explored legal and institutional framework impacts in CEE countries and their developments, considering their importance for attracting foreign direct investments. Vučković et al. (2020) have identified the business environment factors of influence on foreign direct investments in five CEE emerging economies (Bulgaria, Poland, Romania, Serbia, and Slovenia) in the period 20062016, and various impacts of business regulation and institutional factors relevant for foreign investments attraction were found among the analyzed countries. Also, after a quarter of a century of transition processes, Havrylyshin et al. (2016) found that rapid reformers far outperformed gradual reformers, proved by empirical correlation between the reforms’ speed and relevant measures of economic and social results, and that same trends held over 25 years – „early reform leaders still lead, and most of the laggards still lag” (p. 22). Ranjbar et al. (2018) investigated income convergence in 29 transition countries and found that in the 2000s income per capita in most of them was catching up with the USA. Żuk et al. (2018) explored the real convergence in Central, Eastern and South-eastern Europe and their results showed that CESEE economies have narrowed their gaps to the EU average in terms of GDP per capita since 2000 while a few of CESEE countries that have joined the EU have already reached GDP per capita levels close to this average. As noted above, usually, the researchers were looking for evidence of the convergence of per capita incomes, GDP per capita, and so on. Some authors examined the macroeconomic performance and explored the topic of catch-up and convergence in transition countries by calculations and comparisons of technical efficiency change, technical change, and the total factor productivity growth (Deliktas & Balcilar, 2005, p.14). Firm-level studies were focused on inefficiency reduction, technological changes and innovation, factor productivity growth, competitiveness (Brada et al., 1997; Bierut & Kuziemska-Pawlak, 2017; Botrić, 2021; Botrić et al., 2017; Jakšić et al., 2020; Kravtsova, 2007; Krammer, 2015; Piesse & Thirtle, 2000; Rusu & Roman, 2018; Stubelj et al., 2017) and similar outputs considered to capture the results of transition processes. The research on the firm-level total factor productivity in post-transition economies revealed that the speed of catching up of different firms within national economies was correlated with the general economic conditions in each economy. (Botrić et al., 2017). The same study also reminded us that transition economies were rather heterogeneous in catching up with developed economies, some of them demonstrating no improvements in productivity (Bah & Brada, 2009), while the reason for such diversities remained unveiled. This study aimed to enhance existing knowledge by analyzing annual accounts and financial reports indicators from firms in European post-transition countries. The goal was to investigate whether there remained a difference in financial performance compared to enterprises in non-transition European countries. The ratio analysis is used for financial, economic, and scientific purposes, also here as an assessment tool of the performance achievements toward advanced non-transition countries companies. „Ratio analysis is indispensable part of interpretation of results revealed by the financial statement. It provides users with crucial financial information and points out the areas which require investigation.“ (Suthar, 2018, p. 1) Suthar (2018) has provided an overview of ratios and their contribution as proposed, explained or used by various researchers from 1965 onwards, like Horrigan, Patton, Chabotar, Leibowitz, GonzalezBravo, Marginean, and many others. Usually, financial ratios are used in financial statement analysis, performance measurement, decision-making purposes, and several analytic or prognostic model building (like in Kliestik et al.) and here I use them to assess the post-transition vs. non-transition countries enterprises’ comparative results. Financial ratios are the most suitable to become the core component of the fundamental index because 4 Lorena Mošnja-Škare 10.5709/ce.1897-9254.523DOI: CONTEMPORARY ECONOMICS Vol. 18 Issue 1 1-162024 of their ability to depict the various fundamental dimensions of a company (Arnott et al., 2005; Jia & Li, 2015, as cited in Nadar & Wadhwa, 2019). Nadar and Wadhwa (2019, p. 3-8) have given a theoretical review of financial ratios' role and use for various purposes as analyzed by Gibson, Woelfel, Wang and Lee, Teker, Teker, and Güner, Petroska Angelovska and Ackovska, Drew and Dollery, Dulababu, Bansal and Singh, Sueyoshi, Piotroski (F-Score), Hyde, Young, including Du Pont model for financial reports interpretation and benchmarking, then Beaver, Horrigan, Daniel, Altman, Deakin models, Altman Z-Score, that were developed to assess solvency and firm viability problems, Beneish M score and the Montier C score to evaluate earning management, along with many researchers who used them for the share price prediction, capital structure decisions, valuation purposes. In this research, I employed financial ratios for another purpose – to serve as a tool for the assessment of post-transition countries firms' discrepancies with the ones in non-transition countries. Rather than the macroeconomic performance of post-transition economies, this research is focused on the financial performance of their enterprises analyzed by financial ratios, compared to the ones in advanced non-transition economies in Europe, three decades after the beginnings of transition processes. Similar research performed for the period 1998-2004, analyzed the financial effect of the EU enlargement by ten Central and East European countries on the firm's business and financial structure using financial ratios and quantitative analytic techniques to discover if new EU members converged with EU-15 companies' financial statements structure. The research explored productivity, indebtedness, and returns versus the cost of debt to examine the gaps and the results revealed that convergence is „still a long way off“ with only returns versus the cost of debt ratios which „exhibit some approximation“, while productivity and indebtedness ratios showed „scant signs of convergence because of the structural differences in the economic systems of the CEECs, where labor regulation, the situation of the financial system, and tax reform prevent firms from catching up” (Galizzo, 2010, p. 96). 3. Methods3. Methods This section describes the data and methods used to assess the differences in financial performance between the enterprises in selected European posttransition and non-transition countries. Under the term post-transition countries, I included CESEE and Baltic companies that entered the transition processes in the early nineties of the last century, taken as a whole, without intention to perform individual country-specific comparisons that would be outside the extent of this paper. The data empirically analyzed were exported from Orbis Europe data resource, provided by Bureau van Dijk. This database offers relevant, tested, and comparable data enabling cross-border analysis. According to Orbis Internet user guide: The presentation of the information follows a tried and tested approach, recognized and approved by leading accountancy bodies and practitioners in the field. The layout of the data is designed for ease of comprehension and uses terminology widely accepted in the financial world. The emphasis is on both consistency in the treatment of accounts, and accuracy in the recording of data. The overriding aim is to provide information in a form, which can be compared meaningfully between companies from varying countries, and within the same company, between different years. The data entry procedures include rigorous checking of individual records and updates as they are entered, with many of the data fields subject to automatic validation on entry. Information on financial and performance ratios is calculated automatically using standard formulas. (2007, p.16) The set of 569 companies was randomly sampled out of 287.802 active companies of all sizes: large, medium, small, very large; in standardized legal form: public limited companies, private limited companies, sole traders/proprietorships, and partnerships; incorporated in the period 2010.-2020, from Austria, Belgium, Estonia, Finland, Germany, Latvia, Lithuania, Luxembourg, Netherlands, Portugal, Croatia, Slovakia, Slovenia. The data were derived from 2021 annual accounts as the most recent accounts available on the export data 11/01/2023. The financial searches excluded companies with no recent financial data and public authorities/states/governments. www.ce.vizja.pl 5 Financial Performance (Dis)parity in Post-transition Europe This work is licensed under a Creative Commons Attribution 4.0 International License. Firm-level accounting data were used, which included balance sheet and income statement items, as well as the lists of selected financial ratios related to liquidity, solvency, leverage, turnover, profitability, and labor intensity. The number of enterprise employees, total assets, and working capital data were also included. Financial categories and performance ratios based on ORBIS data and formulas were calculated as follows: Current ratio (CURR) = Current assets/Current liabilities Liquidity ratio (LIQR) = (Current assets – Stocks)/ Current liabilities Profit margin (%) (PRMA) = Profit/loss before tax and extr. items/Operating revenue x 100 Solvency ratio – assets based (%) = Shareholders funds / Total assets x 100 Net assets turnover (NAT) = Operating revenue / (Shareholders funds + Non-current liabilities) Labor intensity = Cost of employees/Operating revenue (%) (SCT) Gearing (GEAR) = (Non-current liabilities + Current loans)/ Shareholder funds x 100 Total assets (TOAS) = Fixed assets + Current assets (th.USD) Working capital (WKCA) = (Stocks+Debtors) - Creditors (th.USD). The categories and ratios listed above, together with the number of employees (EMPL) presented explanatory (independent) variables in the further model in section 4. The dependent variable was defined as follows: Non-transition countries' enterprises 0 Post-transition countries enterprises 1 This two-category response variable was the outcome of two nonparametric binary logistic regression models developed in the next section. In the sample, most enterprises were small enterprises, followed by medium-sized, while there were a few large and very large entities, according to Orbis Europe company size classification. The enterprises' size in both groups of post-transition and non-transition European countries companies is presented in Table 1. According to sector classification, most sampled enterprises belonged to the business services sector both in non-transition and post-transition countries enterprises, followed by travel, personal & leisure, then wholesale and retail in post-transition countries enterprises, and by construction, then banking, insurance, and financial services in non-transition countries enterprises. Table 1 Sampled Enterprises by Size in Post-transition and Non-transition European Countries Company Category Large Medium sized Small Very large Non-transition countries enterprises 9 48 260 3 Post-transition countries enterprises 2 20 227 0 Note: Company size classification on Orbis Europe: Very large company - matching at least one of the following: Operating revenue>=100 million EUR; Total assets>=200 million EUR; Employees>=1,000; Listed Large company - matching at least one of the following: Operating revenue>=10 million EUR; Total assets>=20 million EUR; Employees>=150; Not very large company Medium-sized company - matching at least one of the following: Not very large or large company Small company – all other companies not included in another category. Source: Orbis Europe 6 Lorena Mošnja-Škare 10.5709/ce.1897-9254.523DOI: CONTEMPORARY ECONOMICS Vol. 18 Issue 1 1-162024 Table 2 Sampled Enterprises by Sector in Non-transition and Post-transition European Countries Sector Agriculture, Horticulture & Livestock Banking, Insurance & Financial Services Biotechnology and Life Sciences Business Services Chemicals, Petroleum, Rubber & Plastic Computer Software NTC 5 25 1 103 2 12 PTC 7 1 1 67 2 11 Construction Food & Tobacco Manufacturing Industrial, Electric & Electronic Machinery Information Services Media & Broadcasting Metals & Metal Products Miscellaneous Manufacturing NTC 37 2 5 1 2 2 0 PTC 18 3 4 0 2 5 1 Printing & Publishing Property Services Public Administration, Education, Health Social Services Retail Textiles & Clothing Manufacturing Transport Manufacturing Transport, Freight & Storage NTC 1 21 19 17 4 1 6 PTC 2 13 9 21 2 0 17 Travel, Personal & Leisure Utilities Wholesale Wood, Furniture & Paper Manufacturing NTC 24 2 20 3 PTC 33 6 21 3 Note: NTC – non-transition countries enterprises. PTC – post-transition countries enterprises. Source: Orbis Europe Table 3 Sampled Enterprises by Countries Country (Iso Code) AT BE DE EE FI HR LT LU LV NL PT SI SK Nontransition countries enterprises 19 85 11 0 41 0 0 4 0 88 72 0 0 Post-transition countries enterprises 0 0 0 40 0 25 24 0 25 0 0 32 103 Note. Austria (AT), Belgium (BE), Estonia (EE), Finland (FI), Germany (DE), Latvia (LV), Lithuania (LT), Luxembourg (LU), Netherlands (NL), Portugal (PT), Croatia (HR), Slovakia (SK), Slovenia (SI) Source: Orbis Europe www.ce.vizja.pl 7 Financial Performance (Dis)parity in Post-transition Europe This work is licensed under a Creative Commons Attribution 4.0 International License. In the random sample, there were 569 entities from 13 European countries included. Table 4 presents some descriptive statistics for independent (explanatory) variables in the model: current ratio, profit margin, solvency ratio, liquidity ratio, net assets turnover, gearing, natural logarithm of total assets and working capital, as well as the number of employees including the number of observations, mean, standard deviation and median. Significant differences, that is, unequal medians were found for SCT, EMPL, TOAS, and WKCA (MannWhitney, p < 0,001), as well as unequal means for SCT (t-test, p = 0,001), EMPL (t-test, p = 0,004) and TOAS, WKCA (t-test, p <0,001) indicating lower share of cost of employees in operating revenue in post-transition countries enterprises, which disposed with lower assets and working capital in comparison with non-transition countries companies. In addition to descriptive statistics methods used, in the next section, there were two logit regression models developed based on Orbis annual accounts data. There were different methods that could be employed for financial performance topics analysis like discriminant, cluster, principal component, or factor analysis (Curea et al., 2019). For the purposes of financial (dis)parity evaluation under this research, the logistic regression method was selected because of its flexibility and robustness since the financial data from the annual accounts contained outliers as it was noticed by the descriptive statistics overview, while other methods were more sensitive regarding the model assumptions (like multivariate normality required for discriminant analysis). Since the logistic regression served as the classification algorithm, it was convenient to use it with already set-up post-transition and non-transition groups instead of employing clustering methods. Also, the dependent variable in the model was categorical, so logistic regression was more suitable than factor analysis, eventually principal component analysis could be combined with logistic regression in further research with more variables employed. The logistic regression not only could identify the specific financial ratios conTable 4 Descriptive Statistics Count Mean Stdev Median CURR (NTC) 273,00 7,05 12,73 1,97 CURR (PTC) 226,00 7,89 15,27 1,76 PRMA (NTC) 104,00 13,95 31,20 5,21 PRMA (PTC) 228,00 6,91 30,89 3,15 SOLR (NTC) 303,00 48,48 42,10 54,77 SOLR (PTC) 234,00 47,48 45,20 52,97 LIQR (NTC) 272,00 6,60 12,57 1,58 LIQR (PTC) 210,00 7,42 15,20 1,41 NAT (NTC) 98,00 3,42 6,22 1,60 NAT (PTC) 201,00 8,80 60,45 1,62 GEAR (NTC) 163,00 87,65 176,19 10,60 GEAR (PTC) 174,00 60,40 133,08 0,99 SCT (NTC) 320,00 31,56 21,18 27,87 SCT (PTC) 249,00 22,25 19,60 16,79 EMPL (NTC) 135 8,252 15,8 3 EMPL (PTC) 174 4,172 8,637 2 TOAS (NTC) 320 30.238,571 324.391,029 378,247 TOAS (PTC) 247 446,578 1.916,712 69,188 WKCA (NTC) 162 269,501 2.149,05 11,791 WKCA (PTC) 192 50,061 372,195 1,207 Source: Orbis Europe 8 Lorena Mošnja-Škare 10.5709/ce.1897-9254.523DOI: CONTEMPORARY ECONOMICS Vol. 18 Issue 1 1-162024 tributing to the disparity assessment under this set of data but since it was a scalable algorithm, it could be applied to very large datasets to extend this research in the following steps and to compare its outputs with the ones based on other countries companies’ set of accounts or industries they belong to. 4. Results and Discussion4. Results and Discussion This section provides the empirical results of the analysis of the data presented in the previous section. The research question was: Did post-transition countries' enterprises reach the financial performance of non-transition countries' enterprises across Europe, decades after the transition? The goal was to identify if there were remaining differences between financial report indicators belonging to enterprises in posttransition vs. non-transition countries three decades after transition processes have spread over a considerable part of Europe. To reach that goal, as it was previously stated, I used financial reporting indicators, under the firmlevel approach, as they were consistently used in the accounting literature and ordinary data basis. The selected ratios from several financial indicators groups were already calculated upon balance sheets and income statements of sampled companies for the year 2021, available in the Orbis database. The independent variable was a dummy variable, set for enterprises belonging to post-transition countries (1) and non-transition countries (0). The financial report analysis indicators used were: - Current ratio (CURR) - Profit margin (%) (PRMA) - Solvency ratio – assets based (%) (SOLR) - Net assets turnover (NAT) - Liquidity ratio (LIQR) - Cost of employees/operating revenue (%) (SCT) I also included the number of employees (EMPL) and the natural logarithm of total assets (TOAS) in th.USD. Those were the explanatory variables of the logit regression model as followed: (1) In case there were no significant relation or just marginal effects found between the TC and financial indicators, it suggested that the enterprises' performances were comparable regardless of belonging to post-transition or advanced non-transition countries. If the gap persisted, significant marginal effects and a negative correlation with current and liquidity ratio could be expected, indicating weaker coverage of short-term liabilities by short-term assets in post-transitional countries because of higher level of short-term indebtedness that stifled operations. As well, short-term indebtedness was expected to be accompanied by higher gearing levels, since indebtedness was among the general features of transition economies. The macroeconomic environments could greatly influence the companies' behavior to suppress the gearing level. According to The EBRD Transition Report 2015-16, the transition region was overleveraged, and „average debt increases in the region have outpaced those observed elsewhere (European Bank for Reconstruction and Development [EBRD], 2016, p. 16) in the period 2007-2014. On the other hand, in the same report based on Dehesa et al. discussion „Macroeconomic instability, which is reflected in higher average inflation rates, is associated with significantly lower levels of domestic corporate debt.” (EBRD, 2016, p. 20) Considering such macroeconomic flows, the opposite were the expectations regarding solvency ratio with greater assets coverage by shareholder funds than by debts under lower gearing ratio. Regarding the profitability indicators, as previously mentioned, firm-level studies were focused on inefficiency reduction, technological changes and innovation, factor productivity growth and competitiveness, which were finally expected to raise the profitability in post-transitional countries. So, the gap in catching up process regarding inefficiency reduction, factor productivity, innovation was expected to leave profitability levels lower in post-transition countries firms. In that case, I could find lower profit margins in those firms. Kafouros and Aliyev (2016) have explored the influence of institutional reforms and international openness onto firms’ profitability in CEE countries and found that domestic firms’ profitability was positively influenced by institutional reforms and negatively affected by international openness. www.ce.vizja.pl 15 Financial Performance (Dis)parity in Post-transition Europe This work is licensed under a Creative Commons Attribution 4.0 International License. ReferencesReferences Aghion, P., Harmgart, H., & Weisshaar, N. (2010). Fostering growth in CEE countries: a country-tailored approach to growth policy. (European Bank for Reconstruction and Developmen Working Paper No. 118) https://www.ebrd.com/downloads/research/ economics/workingpapers/wp0118.pdf Bierut, B.K., & Kuziemska-Pawlak, K.(2017).Competitiveness and export performance of CEE countries. Eastern European Economics, 55(6),522542. https://doi.org/10.1080/00128775.2017.138 2378 Bah, H.M., & Brada, J.C. (2009). 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