Volume 24 Issue 3 Thematic Issue: The Characteristics and Role of Intangible Capital in Central-Eastern Europe, the Balkans and in the Mediterranean Article 5 September 2022 The Impact of Intangible Capital on the Productivity of Small The Impact of Intangible Capital on the Productivity of Small Firms Firms Č rt Kostevc University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia, crt.kostevc@ef.uni-lj.si Tjaš a Redek University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia Follow this and additional works at: https://www.ebrjournal.net/home Part of the Growth and Development Commons Recommended Citation Recommended Citation Kostevc, Č ., & Redek, T. (2022). The Impact of Intangible Capital on the Productivity of Small Firms. Economic and Business Review, 24(3), 171-186. https://doi.org/10.15458/2335-4216.1305 This Original Article is brought to you for free and open access by Economic and Business Review. It has been accepted for inclusion in Economic and Business Review by an authorized editor of Economic and Business Review. ORIGINAL ARTICLE The Impact of Intangible Capital on the Productivity of Small Firms Crt Kostevc*, Tjasa Redek University of Ljubljana, School of Economics and Business, Ljubljana, Slovenia Abstract Despite the mounting evidence in support of the role of intangible capital on firm performance, some research gaps remain. This paper focuses on the link between intangible capital and firm performance with a particular focus on the effect firm size has on the relationship by studying the population of Slovene enterprises between 2007 and 2020. We findthatwhileintangibleassetsarepositivelyassociatedwithproductivity,thelinkisbynomeanslinear.Furthermore, micro firms appear to benefit most from investing in intangible assets, while the effect is less robust for small and medium-size enterprises (SMEs) and large firms. Amongst different types of intangible assets, the strongest effect on productivitywasfoundforinvestmentinpropertyrightsandgoodwill,whilelong-termdeferreddevelopmentcostshad a weaker effect on firm productivity. Keywords: Intangible capital, Productivity, Firm size JEL classification: O47, L11 Introduction I ntangiblecapitalhaslongbeenrecognizedasthe key to strong economic performance. Over a century ago, Veblen (1908) defined intangible assets as »immaterial items of wealth, immaterial facts owned, valued, and capitalized on an appraisement of the gain to be derived from their possession.« However, measuring the intangible has been a challenge, which contributed to the delayed empir- ical evidence on the role of intangibles for produc- tivity. Literature on the role of intangible assets in economic development and their contribution to economic growth, sectoral dynamics and firm per- formance began emerging in the 1960s and 1970s, is stressing that a notable proportion of productivity growth cannot be completely explained by standard productivity growth elements (capital and labour). Instead the literature suggests that other elements such as education, skills and R&D could explain it (Griliches, 1980, 1981; Kendrick, 1972) could play an important role. The intangible capital literature continued to develop steadily also in the 1980s and 1990s, studying for example the role of advertising, internationalization, market entry, firm valuation, goodwill, market strategy, firm competencies, firm performance and profitability. 1 But the literature gained momentum with the research of Lev (2001) and Nakamura (1999) and primarily the seminal definition of intangible capital by Corrado et al. (2006, 2009) who divided intangible capital into three broader categories, which are: (1) computer- ized information, (2) innovative property, and (3) economic competencies. The literature has since been developing fast, both methodologically, investigating sources of data, measurement ap- proaches and definitions 2 as well as providing evi- dence of the size of the investment into intangibles Received 29 June 2021; accepted 1 March 2022. Available online 15 September 2022 * Corresponding author. E-mail addresses: crt.kostevc@ef.uni-lj.si ( C. Kostevc), tjasa.redek@ef.uni-lj.si (T. Redek). 1 Barrett, 1986; Barwise et al., 1990; Harvey & Lusch, 1997; Hirschey, 1982; Hula, 1989; Kumar, 1987; Lefcbvre et al., 1996; Patterson & Hayenga, 1995. 2 Awano et al., 2010; European Commission, 2014; Globalinto, 2021; Perani & Guerrazzi, 2012; Piekkola, 2011b. https://doi.org/10.15458/2335-4216.1305 2335-4216/© 2022 School of Economics and Business University of Ljubljana. This is an open access article under the CC-BY-NC-ND license (http://creativecommons. org/licenses/by-nc-nd/4.0/). as well as their contribution to growth at national and sectoral 3 as well as firm level. 4 Whileevidenceontheimpactofintangiblecapital on economic performance and productivity is already abundant, there is very scarce evidence on the role of intangible assets and intangible in- vestments in micro, small and medium firms. Data shows that the distribution of intangible in- vestments and assets is heavily right skewed, pri- marily to the benefit of large firms, while the vast majorityoffirmsinvestslittleorevennothing(Kaus etal.,2020).Evidencealsosuggeststhatinsmalland mediumfirms,theinvestmentinintangibleassetsis very often »minor because they tend to consider intan- gible investment as an inefficient cost and concentrate on investments in tangible assets« (Seo & Kim, 2020), although also in smaller firms the intangible assets do contribute to productivity. Nevertheless, the research on the role of intangibles in micro, small and medium firms (hereinafter MSMEs) is still scarce, especially in the literature for the emerging economies. This paper further investigates the nature of intangible assets and investments in micro, small and medium companies in Slovenia with the focus on determining the differences in the intensity of intangible investments by firm size class as well as its contribution to firm productivity, while not focusing on the aggregate intangible assets only but also providing a more detailed insight into the contribution of intangible capital components. Methodologically, the analysis relies on the popu- lation data of Slovenian companies in the period between 2007 and 2020, using their detailed finan- cial statements data. The paper makes several contributions to the literature. First, it adds to the understanding of the importance of intangible investments for produc- tivity growth also in micro firms, which is from managerial and policy perspective especially important in view of the knowledge economy and knowledge-intense services, where micro and small firms are more prevalent. Second, it is to the bestofourknowledgethefirstsuchregionalstudy, focusing on the Central and Eastern Europe (CEE) or South East Europe (SEE) economy. Given the importance of the small business sector in the re- gion, the results again make important implica- tions also for the process of catching up with the most developed in the EU and firms maintaining their competitive positions in the global value chains. Third, it is the first study that investigates both the total intangibles as well as the compo- nents of intangible capital. The analysis also uniquelyreliesonapopulation-widedatasetwhich contributes to the validity and possibility to generalize the results. In continuing, first the theoretical background is provided and research hypotheses developed. This is followed by the explanation of the empirical methodology. The results are discussed in the third section. The paper ends with a discussion and conclusions. 1 Theoretical background 1.1 Defining intangible capital While the contribution of intangible capital to aggregate, sectoral and firm performance has been long acknowledged (Budworth, 1989; Chudnovsky, 1979; Cox, 1977; Eisner, 1978; Kendrick, 1972; Veblen, 1908), the empirical analysis gained mo- mentum primarily with the rise of the knowledge economy (Farrell, 2003; Guthrie et al., 2001) and the seminal works of Nakamura (1999) who argued that spendingonintangiblesshouldbecapitalized,since they generate future value and as such are in fact investments, and Lev (2001) who provides the first economic framework to analyse managerial and investment issues regarding intangible assets and their impact on corporate performance and market values. The literature at the time, despite struggling to provide a unified definition, predominantly focused on the contributions of R&D, brand value and economic competences (Ballot et al., 2001; Bobilloetal.,2006;Johnsonetal.,2002;Leliaertetal., 2003;Lev,2004;Lev&Sougiannis,1996).Despitethe literature usually being focused on a specific component of intangible capital, these elements established themselves as the »core« of intangibles also in the now wide-spread definition of in- tangibles (Corrado et al., 2006). According to Cor- rado et al. (2006), intangible capital comprises: 1) computerized information (computer software, computerized databases), 2) innovative capital (pri- marily research and development (R&D), but also other innovative expenditure), 3) economic compe- tencies (brand equity, firm-specific human capital and organizational structure). 3 Corrado et al., 2016; Fukao et al., 2009; Piekkola, 2011a; Roth & Thum, 2013; Tsakanikas et al., 2020. 4 Bontempi&Mairesse,2015;Chappell&Jaffe,2018;Crassetal.,2015;Drenkovska&Redek,2015;Kausetal.,2020;Prasnikaretal.,2017;Rico&Cabrer- Borras, 2020. 172 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 1.2 Impact of intangibles on firm performance Measurement of intangible capital was the first obstacle in determining the link between firm pro- ductivity and intangible capital. Several options were available to comprise measures of intangible investment, from (1) industry-level data with inputeoutput approach (Corrado, Haltiwanger, et al., 2005; Corrado, Hulten, et al., 2005; Roth, 2010, 2020) to (2) firm-level survey data (Awano et al., 2010;European Commission, 2014;Globalinto, 2021; Perani & Guerrazzi, 2012; Prasnikar, 2010) and (3) measures of intangible capital based on population administrative dataset (Ilmakunnas & Piekkola, 2014; Piekkola, 2011b). Various estimates of intan- gible investments have shown that the actual in- vestment varies significantly between countries, rangingfrom5toeven13%ofGDP(seeforexample (Roth&Thum,2013;Tsakanikasetal.,2020;vanArk et al., 2009), however, the contribution of intangible capital to economic performance, usually measured with productivity, is strong and positive. Initial es- timates showed that intangible capital contributed around a quarter of the total productivity growth in the six investigated EU economies and the US and the UK in the period between 1995 and 2006. For example, in Germany, France, Italy, Spain, DenmarkandAustria,productivitygrewonaverage by 1.32% per year and the contribution of the intangible capital deepening was 0.3 percentage points. In the US, productivity grew on average by 2.96% per year and intangible capital contributed 0.83percentagepoints(vanArketal.,2009).Alsothe estimates of Roth and Thum (2013) show a positive as well as robust relationship between intangibles andlabourproductivitygrowth.Inaddition,authors stress that incorporating intangibles into the empirical analysis helps to explain a large propor- tion of the unexplained variance e the latter de- creases even by 51%. Corrado et al. (2018) investigate the period between 2000 and 2013 and find that during the crisis, the intangible in- vestments were relatively resilient, while tangible investment fell. Intangible investment also bounced back relatively fast. This is consistent with the esti- mates of Roth (2020) who investigated in detail the behaviour of intangible investment in the period between 2000 and 2014. The results first show that the tangible investment was significantly more affected by the 2009 crisis, especially in some countries, e.g. Greece, Spain, Italy, Portugal and Slovenia.Ontheotherhand,intangibleinvestments declined moderately and soon regained growth. In other countries (e.g. Ireland, Austria, Germany, France and Sweden), there was only a moderate decline in 2009, but then growth resumed. The es- timates also confirm that intangibles had a strong and positive contribution to productivity growth. A number of papers at the firm level also confirm the existence of the link between intangible capital and firm productivity. For example, Kaus et al. (2020)find thatfirms that invest more in intangibles are more productive. They particularly stress the contribution of R&D, while software and patent in- vestment are less important. They also identify big differences between industries and firms and stress that the impact of intangibles is more positive with firms with high focus on intangibles. Di Ubaldoand Siedschlag (2021) show using firm-level data from Ireland between 2006 and 2012 that the estimated average elasticity of productivity with respect to investment in knowledge-based capital per employee is 0.3. Nakatani (2019) studies the case of New Zealand and shows that for example the impact of R&D became more pronounced after the crisis in 2009 and also finds that an R&D tax incentive contributes to higher profitability performance. Empiricalanalysis ontheroleofintangiblecapital in emerging markets is still relatively scarce, although for the European economies (new EU members) the data and analyses are indeed done within the broader analysis of the EU economies. Nonetheless, the results show that the impact of intangible investment is positive as well. Several studies were done for Latin America, Brazil, Russia, India, China and South Africa (BRICS), and China. Nadeem et al. (2017) focus on the role of intangible capital for BRICS countries and find that intangible capital is positively related to return on assets and equity as well as components of intangible capital (human, structural and physical capital). Fleisher et al. (2015) similarly show that intangible in- vestments positively impact the performance of both domestically and foreign-owned firms in China, but also show that sectors where domestic firms invested more in intangibles have compara- tively gained competitive advantage. Ivanov and Mayorova (2015) investigate the retail sector in Russia and show that besides investing in in- tangibles, it is also important to manage the intan- gible assets appropriately in order to derive competitive advantages from them. De Castro and Uhlenbruck (2018) stress also the role of privatiza- tion (predominantly the role of foreign owners) in determining the intensity of intangible investment. Vrh (2018, 2019) investigates the link between do- mestic value added and exports performance in Central and Eastern European Countries (CEECs) and finds a positive impact of intangible capital on ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 173 the share of domestic value added. Prasnikar and his team investigated the investments in intangible capital inSlovenia, BiH and Albania and inall three cases identify a link between firm performance and intangible investments (Prasnikar, 2010, Prasnikar etal.,2013;Prasnikar&KnezevicCvelbar,2012),but also highlight the importance of export orientation for learning and strengthening firm's »genetic mate- rial« (Prasnikar et al., 2017). 1.3 Firm size and impact of intangibles Evidence of the impact of intangible capital on firmsdependingontheirsizeiscurrentlystillscarce in the extant literature. For example, Piekkola and Rahko(2019)useadministrativedatatomeasurethe impact of innovation inputs, which are defined by intangible capital components. They stress that the relationship between innovative input and profit- ability is not straightforwarde while high-market- share companies can derive more profit, those with low market shares derive less profit from new in- novations. Kaus et al. (2020) finds that the distribu- tion of intangible investment is very right-skewed, with many firms investing nothing or very little in intangible investments. They add that firms that invest more in intangible capital are also more productive.SeoandKim(2020)showthatintangible capital (human capital, advertising, R&D) is very important also for SMEs that want to be very pro- ductive. They make a very important note on the perceivedlesserimportance ofintangibles,claiming that managers in SMEs often »consider intangible investment as an inefficient cost and concentrate on investments in tangible assets«. However, their re- sults show that all three types of intangible capital (human capital, advertising, R&D) have a positive effect on firm profitability, with the most pro- nounced being the impact of advertising. Based on the above discussion and the relevant literature at large, we take advantage of the data on the population of Slovene enterprises to (i) explore the distribution of intangible assets acrossfirms, (ii) see how investment intensity in intangible assets is related to firm size, and (iii) explore the effect of intangible assets of performance of micro and SME firms. Given the findings of the literature, we hy- pothesize that: H1. The intensity of investments in intangible capital differs by firm size. Namely, given existing evidence, we expect intan- gible capital to be highly concentrated even when compared to fixed assets. Moreover, we expect a considerable proportion of firms to have no intan- gible capital at all. Given the size-threshold for in- vestments in intangible capital, we expect micro, small and medium-sized firms to be less likely to invest in intangible capital. Those micro and SME firms that do invest in intangible assets will expe- rience a positive performance effect. H2. Intangible capital has a positive impact on firm performance, however, the intensity of the contribution will be affected by firm size. H3. Intangible capital components differ in importance of their contribution towards firm performance by firm size. The literature in this field examining the compara- tive importance of intangible investments by firm size is scarce, however, we follow the ideas of Seo and Kim (2020) who argue that managers in SMEs often »consider intangible investment as an ineffi- cient cost and concentrate on investments in tangible assets«. Following the broader discussion on the role of intangibles, we nevertheless believe that some components of intangibles may be more important than other (as shown similarly by Cor- rado et al., 2006). 2 Research design 2.1 Data and methodology The analysis relies on the population data of Slovenian companies in the period between 2007 and 2020 (AJPES, Agencija Republike Slovenije za javnopravne evidence in storitve, 2021a). The data- basecomprisesbalancesheetandincomestatement data for the whole population of the Slovenian limited liability and joint stock companies, which includes depending on the year around 50e60 thousand companies. The balance sheet and finan- cial statements data comprise also data on intan- gible capital as captured by the International accounting standards. To analyse the population of enterprises, several different approaches were used. First, descriptive statistics were prepared. To study the contribution of intangible investment and assets to the produc- tivity offirms, several categories of intangible assets were considered: total intangible assets, property rights and long-term deferred development costs. The total intangible assets, according to the Inter- national accounting standards, incorporates the following: (a) Intellectual property rights, (b) 174 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 Goodwill, (c) Active long-term deferred develop- ment costs and (d) Other intangible assets. 5 The active long-term deferred development costs are often used to incorporate R&D into the assets or capitalize the assets. In the estimations, the total intangibleassets,IPanddeferreddevelopmentcosts will be used to estimate the contribution to pro- ductivity, as these, as will be shown, represent the major parts of intangible assets. To estimate the importance of intangible capital for firm productivity, regression analysis was used. The regressions followed the standard approach. In order to explore the impact that intangible assets have on firm performance, we focus on exploring the correlation between firm productivity and intangible assets. We estimate a relatively parsi- monious production function: lnðsalesÞ it ¼aþb 1 lnðcapitalÞ it þb 2 lnðmaterial costsÞ it þb 3 lnðemployÞ it þb 4 Int cap sh it þb 5 exp it þgIþdT þ3 it ð1Þ where sales it , capital it , material_costs it and employ it are sales revenue, fixed assets and expenditure on ma- terials and services (all in EUR), respectively, while employ it is the average number of full-time em- ployees. exp it istheexportingstatusindicator(which takes on value “1” for firms with positive export sales and “0” for firms with no export sales). Depending on specification, Int_cap_sh 6 captures either the existence of different types of intangible assets at thefirm level with an indicatorvariable for firms with positive (i) assets in long-term property rights, (ii) assets in goodwill, and (iii) assets in long- term deferred development costs or the share of individual components (i)-(iii) in total assets. We alsocontrolfortime(T)andindustry(I)fixedeffects in all specifications. e it is the error term. Given the likely high correlation between components of intangibleassets,weestimate(1)separatelyforeach of the three regressions. While our benchmark es- timates rely on the OLS estimator, we also control for (unmeasurable) time-invariant firm-specific factors by estimating a fixed-effects version of model (1). 2.2 Data In total, the database contains roughly 850 thou- sand observations over the period of 14 years. The average observed company had 7.75 employees, while the median was much lower with only 1 employee. Average sales were at 1.3 million euros per company, with 50% of the companies selling 70 thousand orless.Onaverageovertheentireperiod, the observed value added per employee was 34.5 thousand euros, while median company only had value added of around 23 thousand euros per em- ployees. Table A1 provides further detail about the basic descriptive variables. 3 Results 3.1 Characteristics of intangible investment in Slovenian firms 3.1.1 Size structure of the observed population The analysis focuses on limited liability or joint stock companies (and excludes self-proprietors). These represent around 50% of the total population of Slovenian companies. 7 The observed population of companies comprised predominantly micro companies, which represented between 87 and 90% of the observed population (Fig. 1). Small and me- dium companies with 10e199 employees repre- sented around 10% of the population, while the 300 large companies represented only around 0.5% of the population. On average, the observed micro companies had in 2020 1.6 employees with average company sales of almost 300 thousand euros. Small and medium companies had on average 32.7 em- ployeeswithaverageyearlysalesof5.95millionand the large companies on average had 602 employees and sales of 249 million euros (details provided in Table A1). 3.1.2 Intangible assets by firm size On average, in 2020 around 70% of all companies reported no intangible assets. The shares and their 5 The companies according to the International accounting standards (IFRS, 2021) report these four categories of intangible assets. For an asset to be recognized as an intangible asset by accounting standards, it must be measurable and must bring future benefit. It is acknowledged also that “intangible asset is an identifiable non-monetary asset without physical substance” (IFRS, 2021). All four variables are categories in the financial statements of companiesandrepresentsub-categoriesof “intangibleassets”.Sincethesearetheofficiallyreportedvaluestothetax-auditors,thedatarepresentasource of most reliable data on officially reported intangibles. Intangible categories represent the following accounting categories: (a) Intellectual property rights (AOPT05), (b) Goodwill (AOPT06), (c) Active long-term deferred development costs (AOPT06) and (d) Other intangible assets (AOPT08). Total intangible assets are provided in the balance sheet category AOPT04. 6 The shares are calculated as the share of total or intangible asset component as share/compared to total assets (accounting category AOPT01). 7 While the number of self-proprietors is large (50 of 120 thousand in 2020), their relative economic importance is small. On average, they have 0.7e0.8 employees, but 2/3 have no employees. In 2019, the largest companies, which represent around 0.2% of all companies (including self-proprietors) contributed in total to around 1/3 of total employment and 1/3 of total revenue in the economy. Medium companies contributed the last third. ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 175 absolutenumberhavebeenincreasingsince2006.If in 2007 the share of firms with no intangible capital was55.6%, thesharerose to70.5% by2020.This can be explained by the increasein theshare ofMSMEs in the total number offirms (Fig. 1) and the fact that MSMEs are less likely to invest in intangible assets, inparticularmicrocompanies(Fig.2).Even74.5%of micro firms had no intangible assets in 2020. As companies grow, they also invest into intangiblese as the share of the SMEs with no intangibles is Fig. 1. Number of observed companies by size. Source: AJPES data and own calculations. Fig. 2. Share of firms with no intangible capital by firm size. Source: AJPES data and own calculations. 176 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 »only« 54%. Intangible investment in Slovenia is comparatively most important in large firms. Since 2001, the share of large firms with no reported intangible assets has declined from 10 to 5%. Knowing that there are around 300 large firms, this impliesaround15largecompanieswithnoreported intellectual property rights, goodwill, active long- termdeferreddevelopmentcostsorotherintangible assets. For example, in 2020, there were 5 such companies in manufacturing and 3 in retail (NACE G) and 3 in NACE N, in total 16 such companies. The share of intangible capital in total assets in Slovenia was increasing rapidly between 1994 and 2005. In 1994, the share of intangible capital repre- sented about 3.4% of all firm assets. By 2005 it reached 4.8%. This was a period of fast growth in Slovenia, economic transformation and accession to the EU (2004). Between 2006 and 2007 economic growth as well as investments accelerated, but due to the focus on tangible investment, primarily in- vestments into »core« activities (Griliches, 1980; Griliches & Mairesse, 1995; Kendrick, 1972), the share of intangible assets in total firm assets declined.Theperiodduringandafterthe2009crisis was marked with a general decline in investment rate. The share of investments in GDP declined from even 29.4% in 2008 to around 19% on average (Statisticni urad Republike Slovenije, 2022). While the tangible investments declined significantly, which was particularly evident in Slovenia, the share of intangible investments remained relatively stable (Roth, 2020). The investment cycle in Slovenia, especially in terms of tangible in- vestments, was determined primarily by the in- vestment dynamics in large firms (Prasnikar, 2010, 2012). The granularity seems to be a major factor driving also intangible investments, in addition, the relationship is not as straightforward as in the case of tangible investments, where the investment was significantly more pronounced in large companies. Intangible assets in large firms represented around 5% of assets on average after 2008, and the share was increasing ever since. In small and medium companies and in micro companies, the share of intangible assetswere declining. If in2005 theshare was at around 5%, it declined to only 3.2% by 2020 (Fig.3).Especiallyinmicrocompanies,thedeclineis sharp in the period 2005e2007, which marks the process of strong investment cycle in tangible cap- ital (Bole et al., 2018). In addition, the decline can be perceived by the bias of micro, small and medium companies towards tangible investments, as the intangible is perceived as less efficient (Seo & Kim, 2020). Acloserlookintothestructureofintangibleassets (Fig. 4) reveals that microfirms invested on average the least in all three categories of intangible assets: goodwill,propertyrightsanddeferreddevelopment costs. For example, in terms of development costs, micro companies on average had an about 3 times Fig. 3. The share of intangible capital as percent of fixed assets, 1994e2020. Source: AJPES data and own calculations. ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 177 lower share of development costs as share of assets in comparison to small and medium companies in the entire observed period between 2007 and 2020: 0.21% of all assets in micro companies in compari- son to 0.32% in small and medium and about 0.46% in large companies. Property rights in the observed periodonaveragerepresentedabout0.47%inmicro companies, 0.57% in small and medium and 0.92% in large companies. The difference is most striking in the case of goodwill, which in micro companies represented just 0.076% of assets, 0.2% in small and medium companies and 0.61% in large companies. Fig.3alsorevealsthetrends.Theshareofintangible assets in the case of all three investigated categories wasrelativelystablesince2011formicrocompanies. In the case of small and medium companies, the share of goodwill has been declining slightly, the share of property rights was also declining steadily, while the development costs increased significantly between 2007 and 2011, but then remained at the newhigherlevel.Inthecaseoflargecompanies,the mostnotabletrendisthefastincreaseintheshareof property rights. The differences in the intangible capital by type as share of all assets are highly sta- tistically significant in all cases (p < 0.000), only the significance of the differences in the development costs between small and medium and large com- panies are significant at 0.0032. 3.2 Intangible assets and firm productivity Generally, intangible capital has been shown to positively impact productivity of firms as well as drive productivity growth at industry and national level (Corrado et al., 2019, 2018; Piekkola, 2011a; Tsakanikas et al., 2020). The literature on intangible assets and their contribution to productivity sug- gests also that intangible assets, although often neglectedinMSMEs,alsosignificantlycontribute to firm performance (Rico& Cabrer-Borras, 2020). The distribution of value added by firms depending on intangible capital and type of intangible capital (Fig. 5) shows that in general in 2020 value added per employee was the lowest in companies with no intangible capital (medianvalue for companies with intangible capital statistically significantly higher). Similar is true also if firms have either property Fig. 4. The share of intangible capital as percent of fixed assets by type of intangibles, 2007e2020. Source: AJPES data and own calculations. Fig. 5. Value added per employee in firms with and without intangible capital. Source: AJPES data and own calculations. 178 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 right, or long-term development costs. These are investigated in more detail below. Intangible assets were a characteristic of firms with higher value added also if firm size was controlled for (Fig. 6). The distribution of value added per employee in small and medium com- panies with intangible assets had larger median than in firms with no intangible assets (left panel, Fig. 4,p¼ 0.000). Similar is true also for microfirms (right panel, p ¼ 0.000). The distribution for large firms is not depicted, due to the small number of firms (16) with no intangible assets. Besides value added per employee (i.e. produc- tivity), intangible capital also has a positive corre- lation with employment and relative size of capital (in comparison to industry average) (Figs. 4 and 5). Fig. 7 depicts the distribution of the relative size of firm capital (relative to the respective annual in- dustry average) for (i) firms with no intangible capital, (ii) firms with intangible capital, (iii) firms withanaboveaverageshareofintangiblecapital(in the respective industry) and (iv) firms with at least twice the average share of intangible capital. As expected, the distribution relative capital of firms with intangible capital stochastically dominates that of firms with no intangible capital. On the other hand, firms with an above average share of intan- gible capital appear to be relatively smaller (compared to the average firm with intangible cap- ital), while relative capital of firms with twice the Fig. 6. Value added per employee in firms with and without intangible capital by firm size for micro and small and medium companies*. Note. *Distributions for large companies are not shown, as there are only 16 large companies with no intangibles in 2020. Source: AJPES data and own calculations. Fig. 7. Relative size of capital of firms with and without intangible capital in comparison to industry average in 2020. Source: AJPES data and own calculations. Fig.8.Relativesizeoffirmswithandwithoutintangiblecapitalinterms of employment in comparison to industry average in 2020. Source: AJPES data and own calculations. ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 179 average share of intangible capital only marginally exceedsthat ofallfirmswith intangible capital. This confirms our finding that a critical size of firm cap- ital is key for effective use of intangible capital and that the effect of the share of intangible capital on firm performance is likely not linear. Fig. 8 looks at the relative size of firms with respecttoemploymentbyfocussingonthesamefor cohorts as above. As was the case with the relative size of capital, firms with intangible capital tend to employ more than those without intangible capital. There is a substantial difference in terms of the size of firms with at least twice the average share of intangiblecapitalcomparedtotheaveragefirmwith intangible capital, while firms with above average shares of intangible capital perform slightly worse than firms with intangible capital. Again, it is obvious that the effect of intangible capital on employment is not linear. The association between intangible capital and firm performance indicators (size and productivity) is clearly strong, but is also likely to be non-linear. While firms with intangible capital tend to also be larger and more productive than those without it, the share of intangible capital does not (linearly) predict either size or productivity. A closer look at the correlation between firm performance and availability of intangible capital is needed with a special focus on the effect firm size has on the relationship.Inordertogainfurtherinsightintothe differential effect of firm size on the link between intangible capital and firm performance, we focus on regression analysis next. 3.3 Regression analysis To determine the impact of intangible investment on firm performance, a standard productivity approachwasused,asdescribedbyequation(1).To measure intangible capital and its impact, the components of intangible capital were used: (a) In- tellectual property rights, (b) Goodwill, (c) long- termdeferreddevelopmentcostsand(d)theirtotals (property rights and long term deferred develop- ment costs, property right, goodwill and long term deferred development costs). 8 The estimates presented in Table 1 show that, in addition to the standard production-function de- terminants of firm output (capital, material costs and employment), intangible assets also positively affect firm sales. While the effect of intangible as- sets on sales is generally positive, it is only signifi- cantly different from zero in case of total intangible assetsshare(column5),theshareofpropertyrights (column 1) and the share of property rights and long-term deferred development costs (column 4). Ownership of property rights on intellectual prop- erty in particular appears to be highly correlated with firm productivity, 9 while long-term deferred development costsandgoodwill,while positive,are not significantly correlated with firm productivity. This may be an indication of the fact that goodwill mainly reflects the difference between the market value of thefirm and its book value, which may not have an immediate effect on firm productivity, while long-term deferred development costs may serve as an accounting catch-all category for development projects of longer duration, which, again, may cause a lack of correlation with current productivity. In addition, we find a strong negative correlation betweenthesquared term ofintangible assetshares and firm productivity in all specifications. This in- dicates that the impact of intangible capital on firm productivity displays decreasing marginal produc- tivity after a threshold level of intangible capital has been exceeded. Ifwesplitthesamplebyfirmsizeintomicrofirms (lessthan10employees) andSMEs(between10and 200 employees), we get a clearer picture of the dif- ferential impact of firm size on the respective elas- ticity of intangible assets. As before, due to the very small population of large firms with no intangible assets, we do not show the estimates for the sub- sample of large firms. Micro firms are revealed to have the strongest association between the share of intangible assets and firm productivity. Both prop- erty rights and goodwill are revealed to have a strong positiveeffectonproductivity,with theeffect beingdecidedlynon-linear.Giventherelativeshare of micro firms in the population of Slovene enter- prises,itisclearthatthefullsamplecorrelationsare primarily driven by micro firms. SMEs (columns 6e10) generally exhibit weaker correlations, which areinmostcasesinsignificant.Theonlyexceptionis the long-term deferred development costs which show a weakly significant negative correlation with firm productivity. 8 The category »Other intangible assets« was excluded from the regression analysis, due to concerns with the quality of datae only around 5000 companies in total reported the »other« category, with high volatility. In addition, the »other« category is much less clearly defined and includes for examplealsoemissioncoupons,valuecorrections(AgencijaRepublikeSlovenijezajavnopravneevidenceinstoritve,2021b)andassuchdoesnotrepresent the intangible capital this analysis is interested in. 9 Aftercontrollingfortheimpactofproduction-functiondeterminantsintheregressionoffirmsales,theremainingdeterminantseffectivelyexplainfirm productivity. 180 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 Table 1. Regression results on the contribution of intangible capital to firm performance (fixed-effects estimates). VARIABLES All companies Small and medium companies Micro companies Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) Ln(material costs) it 0.698*** 0.697*** 0.698*** 0.697*** 0.697*** 0.648*** 0.648*** 0.648*** 0.648*** 0.648*** 0.708*** 0.708*** 0.707*** 0.708*** 0.707*** (0.001) (0.001) (0.001) (0.001) (0.001) (0.002) (0.002) (0.002) (0.002) (0.002) (0.001) (0.001) (0.001) (0.001) (0.001) Ln(capital) it 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.017*** 0.016*** 0.016*** 0.017*** 0.016*** 0.016*** (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) (0.001) Ln(employment) it 0.295*** 0.295*** 0.295*** 0.295*** 0.295*** 0.348*** 0.348*** 0.348*** 0.349*** 0.349*** 0.280*** 0.280*** 0.280*** 0.280*** 0.280*** (0.002) (0.002) (0.002) (0.002) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) (0.002) (0.002) (0.002) (0.002) (0.002) Share of property rights it 0.042** 0.014 0.049** (0.019) (0.030) (0.024) (Shareofproperty rights) it 2 0.062** 0.027 0.060** (0.024) (0.041) (0.029) Long-term de- ferred dev. cost share 0.001 0.086* 0.002 (0.039) (0.045) (0.054) (Long-term de- ferred dev. cost share) 2 0.103** 0.001 0.077 (0.048) (0.062) (0.064) Share of goodwill 0.044 0.098 0.283*** (0.061) (0.062) (0.098) (Share of goodwill) 2 0.142* 0.107 0.431*** (0.075) (0.084) (0.113) Share of property rightsandlong- term deferred dev.cost 0.035** 0.033 0.045** (0.018) (0.026) (0.022) (Shareofproperty rightsandlong- term deferred dev.cost) 2 0.078*** 0.001 0.073*** (0.022) (0.035) (0.027) (continued on next page) ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 181 Table 1. (continued) VARIABLES All companies Small and medium companies Micro companies Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it Ln(sales) it (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) (12) (13) (14) (15) Share of property rights, goodwill and long-term deferred dev.cost 0.031* 0.048** 0.053** (0.017) (0.024) (0.022) (Shareofproperty rights, goodwill and long-term deferred dev.cost) 2 0.077*** 0.021 0.088*** (0.021) (0.032) (0.026) Export-status 0.033*** 0.033*** 0.033*** 0.033*** 0.033*** 0.003 0.003 0.003 0.003 0.003 0.040*** 0.040*** 0.040*** 0.040*** 0.040*** (0.002) (0.002) (0.002) (0.002) (0.002) (0.003) (0.003) (0.003) (0.003) (0.003) (0.002) (0.002) (0.002) (0.002) (0.002) Small and me- dium size dummy (micro is base) 0.002 0.002 0.002 0.002 0.002 (0.003) (0.003) (0.003) (0.003) (0.003) Large companies dummy (micro is base) 0.022** 0.022** 0.022** 0.022** 0.022** (0.010) (0.010) (0.010) (0.010) (0.010) Constant 3.495*** 3.495*** 3.495*** 3.496*** 3.496*** 4.147*** 4.145*** 4.146*** 4.145*** 4.147*** 3.446*** 3.445*** 3.446*** 3.445*** 3.446*** (0.258) (0.258) (0.258) (0.258) (0.258) (0.047) (0.047) (0.047) (0.047) (0.047) (0.272) (0.272) (0.272) (0.272) (0.272) Observations 352,319 352,319 352,319 352,319 352,319 80,996 80,996 80,996 80,996 80,996 267,044 267,044 267,044 267,044 267,044 R-squared 0.790 0.790 0.790 0.790 0.790 0.816 0.816 0.816 0.816 0.816 0.752 0.752 0.752 0.752 0.752 Number of enterprises 54,447 54,447 54,447 54,447 54,447 12,858 12,858 12,858 12,858 12,858 48,852 48,852 48,852 48,852 48,852 Industry FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Year FE Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Yes Note. Standard errors in parentheses, ***p < 0.01, **p < 0.05, *p < 0.1. 182 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 The econometric results highlight the importance of intangible assets for micro firms. Comparing these results to the characteristics of intangible in- vestments in micro data highlights an interesting pattern. The share of companies that do invest in intangible assets is the smallest among micro com- panies, since only around 30% of micro companies invest in intangible assets. However, those that do invest have a statistically significant impact on firm performance, which is in fact even stronger than in large firms. Sectoral impacts have been controlled for. In summary, the impact of intangible capital on firm productivity appears to be very heteroge- neous both across firm size, share of intangible capital as well as the amount of capital a firm has 10 . While smaller firms appear to experience a bigger boost to productivity by investing in intangible capital, the effect tends to dissipate somewhat as the share of intangible capital ex- ceeds the threshold value. On the other hand, firms with more capital tend to experience a stronger association between share of intangible capital and productivity. 4 Discussion and conclusion Intangible capital in its many incarnations has long been seen as the key factor in afirm's ability to generate value added, improve its market power and provide long-term profitability. While there is ample empirical evidence in support of the positive long-term impact of intangible capital on firm pro- ductivity and efficiency, the evidence is mainly focused on medium-sized and largefirms andfirms in mature Western markets. This paper aims to fill the empirical gap in the literaturebyfocusingonthehithertounderexplored dataforaformertransitioncountryandfocusonthe effect of firm size on the link between intangible capital andfirm performance. Ourfindings indicate that micro firms with at most nine employees experience the strongest positive association be- tween intangible capital and firm performance, while the effect is less robust for SMEs or large firms. The effect itself is highly nonlinear as its marginal impact tends to weaken after a certain threshold intensity of intangible assets has been passed. Furthermore, not all forms of intangible assets have proven equally effective. Property rights, in particular, and goodwill to a lesser extent have beenshown to have a positivecorrelation with firm performance, while long-term deferred devel- opmentcostshavebeenrevealedtobelesseffective. Our findings lead to some potential policy impli- cations. Firstly, in studied industries, small and capital intensive firms were found to benefit most from investing in intangible assets. Stimulating in- vestment in intangible assets wouldenablefirms on the margin to bridge the financing gap and, by making the investment in intangible assets, provide themselves with long-term growth potential. Sec- ondly, policies stimulating investment in (intellec- tual) property rights in particular would seem to be most beneficial. Investment in long-term deferred developmentcostsarefoundtobetheleasteffective as short-term productivity determinant. Potentially, given a long enough horizon, long-term deferred development costs may impact productivity long term. Lastly, policies stimulating investment in intangibleassetsshouldtakeaccountofthefactthat they display decreasing marginal effectiveness once a threshold level of investment has been exceeded. The research results may also be limited due to the nature of data and not directly comparable to those that follow theCorradoet al.(2006) definition. Intangible assets, as measured by the International accounting standards, incorporate the 4 categories used in this analysis. According to the accounting standards, much of the actual intangible in- vestments would be considered as cost. Conse- quently, inthe future it may be interesting to repeat the estimation using a different, possibly survey dataset. Second, intangible capital interestingly has a pronounced impact in micro companies. A more focused, detailed analysis of micro companies, possibly using a mixed-methods approach, could help understand the results better. Conflict of interest Theauthorsdeclarethereisnoconflictofinterest. Acknowledgement The work was co-funded by (1) H2020 GLOBAL- INTO project, which was supported by the Euro- pean Union's Horizon 2020 The mechanisms to promote smart, sustainable and inclusive growth undergrantagreementNo.822259and(2)Slovenian Research Agency projects J5-6815(B) and P5-128. 10 Regressions results where the sample was split between the top and bottom quartiles of capital distribution indicate that firms with more capital (top quartile) are likely to experience a positive effect of intangible capital on productivity, while firms in the bottom quartile show no significant correlation. These results were omitted from the paper for the sake of brevity and are available from the authors upon request. ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 183 References AgencijaRepublikeSlovenijezajavnopravneevidenceinstoritve. (2021a).AJPES Podatkovna baza,zakljucni racunipodjetij.https:// www.ajpes.si/ AgencijaRepublikeSlovenijezajavnopravneevidenceinstoritve. (2021b). Porocanje organizacij, ki racunovodijo po SRS, Ajpesu za leto 2020. https://revijaiks.si/2021/02/Racunovodstvo/clanek/ 5787034 Awano, G., Franklin, M., Haskel, J., & Kastrinaki, Z. (2010). Measuring investment in intangible assets in the UK: Results from a new survey. Economic and Labour Market Review, 4(7), 66e71. https://doi.org/10.1057/elmr.2010.98 Ballot, G., Fakhfakh, F., & Taymaz, E. (2001). Firms' human cap- ital, R&D and performance: A study on French and Swedish firms. Labour Economics, 8(4), 443e462. https://doi.org/10.1016/ S0927-5371(01)00038-0 Barrett, T. F. (1986). Why Not, Why and how to value intangible marketing assets. European Journal of Marketing, 20(1), 32e50. https://doi.org/10.1108/EUM0000000004627 Barwise,P.,Higson,C.,Likierman,A., &Marsh,P.(1990).Brands as “separable assets”. Business Strategy Review, 1(2), 43e59. https://doi.org/10.1111/j.1467-8616.1990.tb00010.x Bobillo, A. M., Rodriguez Sanz, J. A., & Tejerina Gaite, F. (2006). Innovation investment, competitiveness, and performance in industrial firms. Thunderbird International Business Review, 48(6), 867e890. https://doi.org/10.1002/tie.20126 Bole, V., Oblak, A., Prasnikar, J., & Trobec, D. (2018). Financial frictionsandindebtednessofBalkanfirms:Acomparisonwith Mediterranean and Central European countries. Journal of Policy Modeling, 40(4), 790e809. https://doi.org/10.1016/ j.jpolmod.2018.02.013 Bontempi, M. E., & Mairesse, J. (2015). Intangible capital and productivity at the firm level: A panel data assessment. Eco- nomics of Innovation and New Technology, 24(1e2), 22e51. https://doi.org/10.1080/10438599.2014.897859 Budworth, D. W. (1989). Intangible assets evaluated. Science and Public Policy, 16(6), 372e373. https://doi.org/10.1093/spp/ 16.6.372 Chappell, N., & Jaffe, A. (2018). Intangible investment and firm performance. Review of Industrial Organization, 52(4), 509e559. https://doi.org/10.1007/s11151-018-9629-9 Chudnovsky, D. (1979). Foreign trademarks in developing coun- tries. World Development, 7(7), 663e682. https://doi.org/ 10.1016/0305-750X(79)90080-9 Corrado,C.,Haltiwanger,J.,&Sichel,D.(2005).Measuring Capital intheneweconomy(No.corr05-1).NationalBureauofEconomic Research. https://www.nber.org/books-and-chapters/ measuring-capital-new-economy Corrado, C., Haskel, J., & Jona-Lasinio, C. (2019). Productivity growth, capital reallocation and the financial crisis: Evidence from Europeand the US. Journal of Macroeconomics, 61, Article 103120. https://doi.org/10.1016/j.jmacro.2019.04.006 Corrado, C., Haskel, J., Jona-Lasinio, C., & Iommi, M. (2016). Intangible investment in the EU and US before and since the Great Recession and its contribution to productivity growth (No. 2016/08; EIB Working Papers). European Investment Bank (EIB) https:// ideas.repec.org/p/zbw/eibwps/201608.html Corrado, C., Haskel, J., Jona-Lasinio, C., & Iommi, M. (2018). Intangible investment in the EU and US before and since the Great Recession and its contribution to productivity growth. Journal of Infrastructure, Policy and Development, 2(1), 11e36. https://doi.org/10.24294/jipd.v2i1.205 Corrado, C., Hulten, C., & Sichel, D. (2005). Measuring capital and technology: An expanded framework (pp. 11e46). [NBER Chap- ters]. National Bureau of Economic Research, Inc. https:// econpapers.repec.org/bookchap/nbrnberch/0202.htm Corrado, C., Hulten, C. R., & Sichel, D. (2006). Intangible capital and economic growth (NBER working paper No. 11948). National Bureau of Economic Research, Inc. https://econpapers.repec. org/paper/nbrnberwo/11948.htm Corrado,C.,Hulten,C.,&Sichel,D.(2009).Intangiblecapitaland U.S. economic growth. Review of Income and Wealth, 55(3), 661e685. https://doi.org/10.1111/j.1475-4991.2009.00343.x Cox, J. G. (1977). Planning for technological innovation part I. Investment in technology. Long Range Planning, 10(6), 40e44. https://doi.org/10.1016/0024-6301(77)90006-1 Crass, D., Licht, G., & Peters, B. (2015). Intangible assets and in- vestments at the sector level: Empirical evidence for Germany. SpringerInternationalPublishing.https://doi.org/10.1007/978- 3-319-07533-4_4 De Castro, J. O., & Uhlenbruck, N. (2018). Comparing privatiza- tion characteristics in former communist, developing, and developed countries. In Privatization and entrepreneurship: The managerial challenge in central and eastern Europe. Taylor & Francis. https://doi.org/10.4324/9780203714584-7 Di Ubaldo, M., & Siedschlag, I. (2021). Investment in knowledge- based capital and productivity: Firm-level evidence from a small open economy. Review of Income and Wealth, 67(2), 363e393. https://doi.org/10.1111/roiw.12464 Drenkovska,M.,&Redek,T.(2015).Intangiblecapital,innovation and export-led growth: Empirical comparative study of Slovenia and the Western Balkans. Economic and Business Re- view, 17(1), 25e67. Eisner, R. (1978). Total incomes in the United States, 1959 and 1969.ReviewofIncomeandWealth,24(1),41e70.https://doi.org/ 10.1111/j.1475-4991.1978.tb00031.x EuropeanCommission,B.(2014).Flasheurobarometer369(Investing in intangibles: Economic assets and innovation drivers for growth) (ZA5881). https://doi.org/10.4232/1.11908 Farrell,D.(2003).Therealneweconomy. Harvard Business Review. https://hbr.org/2003/10/the-real-new-economy Fleisher, B. M., McGuire, W. H., Smith, A. N., & Zhou, M. (2015). Knowledgecapital,innovation,andgrowthinChina.Journalof Asian Economics, 39,3 1 e42. https://doi.org/10.1016/ j.asieco.2015.05.002 Fukao, K., Miyagawa, T., Mukai, K., Shinoda, Y., & Tonogi, K. (2009). Intangible investment in Japan: Measurement and contributiontoeconomicgrowth. Review of Income and Wealth, 55(3),717e736.https://doi.org/10.1111/j.1475-4991.2009.00345.x Globalinto. (2021). Large scale pilot survey of intangible investments. GLOBALINTO. https://globalinto.eu/work-packages/large- scale-pilot-survey-of-intangible-investments/ Griliches, Z. (1980). R & D and the productivity slowdown. The American Economic Review, 70(2), 343e348. Griliches, Z. (1981). Market value, R&D, and patents. Economics Letters, 7(2), 183e187. https://doi.org/10.1016/0165-1765(87) 90114-5 Griliches,Z.,&Mairesse,J.(1995).Production Functions: The Search for Identification. NBER Working Papers, No. 5067. National Bureau of Economic Research. https://doi.org/10.3386/w5067 Guthrie, J., Petty, R., & Johanson, U. (2001). Sunrise in the knowl- edgeeconomy:Managing,measuringandreportingintellectual capital. Accounting, Auditing & Accountability Journal, 14(4), 365e384. https://doi.org/10.1108/EUM0000000005869 Harvey, M., & Lusch, R. (1997). Protecting the core competencies of a company: Intangible asset security. European Management Journal, 15(4), 370e380. https://doi.org/10.1016/S0263-2373(97) 00017-0 Hirschey, M. (1982). Advertising and the profitability of leading and following firms. Managerial and Decision Economics, 3(2), 79e84. https://doi.org/10.1002/mde.4090030205 Hula, D.G. (1989).Intangiblecapital,market share andcorporate strategy. Applied Economics, 21(11), 1535e1547. https://doi.org/ 10.1080/758516019 IFRS. (2021). IFRS - IAS 38 intangible assets. https://www.ifrs.org/ issued-standards/list-of-standards/ias-38-intangible-assets/ Ilmakunnas, P., & Piekkola, H. (2014). Intangible investment in people and productivity. Journal of Productivity Analysis, 41(3), 443e456. https://doi.org/10.1007/s11123-013-0348-9 Ivanov, G., & Mayorova, E. (2015). Intangible assets and competitiveadvantageinretail:CasestudyfromRussia. Asian 184 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 Social Science, 11(12), 38e45. https://doi.org/10.5539/ ass.v11n12p38 Johnson, L. D., Neave, E. H., & Pazderka, B. (2002). Knowledge, innovationandsharevalue.InternationalJournalofManagement Reviews, 4(2), 101e134. https://doi.org/10.1111/1468-2370.00080 Kaus, W., Slavtchev, V., & Zimmermann, M. (2020). Intangible capital and productivity: Firm-level evidence from German manufacturing. In IWH discussion papers (No. 1/2020; IWH discussion papers). Halle Institute for Economic Research (IWH). https://ideas.repec.org/p/zbw/iwhdps/12020.html Kendrick, J. W. (1972). The treatment of intangible resources as capital. Review of Income and Wealth, 18(1), 109e125. https:// doi.org/10.1111/j.1475-4991.1972.tb00853.x Kumar, N. (1987). Intangible assets, internalisation and foreign production: Direct investments and licensing in Indian manufacturing. Weltwirtschaftliches Archiv, 123(2), 325e345. https://doi.org/10.1007/BF02706666 Lefcbvre, L. A., Lefcbvre, E., & Harvey, J. (1996). Intangible assets as determinants of advanced manufacturing technology adoption in sme's: Toward an evolutionary model. IEEE TransactionsonEngineeringManagement,43(3),307e322.https:// doi.org/10.1109/17.511841 Leliaert,P.J.C.,Candries,W.,&Tilmans,R.(2003).Identifyingand managing IC: A new classification. Journal of Intellectual Capital, 4(2), 202e214. https://doi.org/10.1108/14691930310472820 Lev, B. (2001). Intangibles: Management, measurement, and reporting. JSTOR: Brookings Institution Press. https://www.jstor.org/ stable/10.7864/j.ctvcj2rf2 Lev, B. (2004). Sharpening the intangibles edge. Harvard Business Review, 82(6), 109e138. Lev,B.,&Sougiannis,T.(1996).Thecapitalization,amortization,and value-relevance of R&D. Journal of Accounting and Economics, 21(1),107e138.https://doi.org/10.1016/0165-4101(95)00410-6 Nadeem, M., Gan, C., & Nguyen, C. (2017). Does intellectual capital efficiency improve firm performance in BRICS econo- mies? A dynamic panel estimation. Measuring Business Excel- lence, 21(1), 65e85. https://doi.org/10.1108/MBE-12-2015-0055 Nakamura, L. (1999). Intangibles: What put the new in the new economy? The Business Review,3e16. Nakatani, R. (2019). Firm performance and corporate finance in New Zealand. Applied Economics Letters, 26(13), 1118e1124. https://doi.org/10.1080/13504851.2018.1539805 Patterson, M. D., & Hayenga, M. L. (1995). Valuing intangible assets: Newark and beyond. Agribusiness, 11(4), 371e381. https://doi.org/10.1002/1520-6297(199507/08)11:4<371::AID- AGR2720110408>3.0.CO;2-W Perani, G., & Guerrazzi, M. (2012). The statistical measurement of intangible assets: Methodological implications of the results of the ISFOL 2011 pilot survey. Mimeo (available upon request from the authors). Piekkola, H. (Ed.). (2011a). Intangible capitale driver of growth in Europe. University of Vaasa. http://www.innodrive.org/ attachments/File/Intangible_Capital_Driver_of_Growth_in_ Europe_Piekkola(ed).pdf Piekkola, H. (2011b). Intangible capital: The key to growth in Europe. Intereconomics, 46(4), 222e228. https://doi.org/10.1007/ s10272-011-0387-2 Piekkola, H., & Rahko, J. (2019). Innovative growth: The role of market power and negative selection. Economics of Innovation and New Technology. https://doi.org/10.1080/10438599.2019. 1655878 Prasnikar, J. (Ed.). (2010). The role of intangible assets in exiting the crisis. Casnik Finance. Prasnikar, J. (2012). Comparing companies' success in dealing with external shocks: The case of the Western Balkans, Mediterranean countries and core European countries. Casnik Finance. Prasnikar, J., & Knezevic Cvelbar, L. (2012). Intangible assets as a potential for growth in Republic of Srpska. Faculty of Economics University of Ljubljana. http://maksi2.ef.uni-lj.si/ zaloznistvoslike/372/SRPSKA_september_cela.pdf Prasnikar, J., Memaj, F., Redek, T., & Voje, D. (2013). The role of corporations in economic development: Albania on its way to internationalisation. Post-Communist Economies, 25(3),392e406. https://doi.org/10.1080/14631377.2013.813143 Prasnikar, J., Redek, T., & Drenkovska, M. (2017). Survival of the fittest: An evolutionary approach to an export-led model of growth. Economic Research-Ekonomska Istrazivanja, 30(1), 184e206. https://doi.org/10.1080/1331677X.2017. 1305796 Rico, P., & Cabrer-Borras, B. (2020). Intangible capital and busi- ness productivity. Economic Research-Ekonomska Istrazivanja, 33(1), 3034e3048. https://doi.org/10.1080/1331677X.2019. 1699139 Roth, F. (2010). Measuring innovationdintangible capital invest- ment in the EU. Intereconomics, 45(5), 9e13. https://doi.org/ 10.1007/s10272-010-0346-3 Roth,F.(2020).Revisiting intangible Capital and labour productivity growth, 2000-2015: Accounting for the Crisis and economic Re- covery in the EU (No. 3; Hamburg Discussion Papers in In- ternational Economics). University of Hamburg, Chair of International Economics. https://ideas.repec.org/p/zbw/ uhhhdp/3.html Roth, F., & Thum, A.-E. (2013). Intangible capital and labor pro- ductivity growth: Panel evidence for the EU from 1998-2005. Review of Income and Wealth, 59(3), 486e508. https://doi.org/ 10.1111/roiw.12009 Seo, H. S., & Kim, Y. (2020). Intangible assets investment and firms' performance: Evidence from small and medium-sized enterprises in Korea. Journal of Business Economics and Man- agement, 21(2), 423e445. https://doi.org/10.3846/ jbem.2020.12022 Statisticni urad Republike Slovenije. (2022). SI-STAT podatkovni portal. http://pxweb.stat.si/pxweb/Database/Ekonomsko/ Ekonomsko.asp Tsakanikas, A., Roth, F., Calio, S., Caloghirou, Y., & Dimas, P. (2020). The contribution of intangible inputs and participation in global value chains to productivity performance: Evidence from the EU-28, 2000-2014 (No. 5; Hamburg Discussion Papers in In- ternational Economics). Hamburg University. vanArk,B.,Hao,J.X.,Corrado,C.,&Hulten,C.(2009).Measuring intangiblecapitaland itscontributiontoeconomicgrowthinEurope (EIB Paper No. 3/2009). European Investment Bank, Eco- nomics Department. http://econpapers.repec.org/paper/ riseibpap/2009_5f003.htm Veblen, T. (1908). On the nature of capital: Investment, intangible assets, and the pecuniary magnate. Quarterly Journal of Economics, 23(1), 104e136. https://doi.org/10.2307/ 1883967 Vrh, N. (2018). What drives the differences in domestic value added in exports between old and new E.U. member states? Economic Research-Ekonomska Istrazivanja, 31(1), 645e663. https://doi.org/10.1080/1331677X.2018.1438910 Vrh, N. (2019). The DNA of the domestic value added (DVA) in exports: Firm-level analysis of DVA in exports. The World Economy, 42(9), 2566e2601. https://doi.org/10.1111/ twec.12800 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186 185 Appendix Table A1. Descriptive statistics for sales, and number of employees for the studied companies by company size. Micro Small and medium Large Sales Employment Number of firms Sales Employment Number of firms Sales Employment Number of firms Mean SD Mean SD Count Mean SD Mean SD Count Mean SD Mean SD Count 2007 282423 1544435 1.72 2.18 42798 5373559 20300000 35.46 34.90 5612 82629458 180000000 611.61 967.34 371 2008 287823 1662963 1.70 2.18 45645 5800472 23800000 35.18 34.90 5998 88550199 207000000 610.82 985.20 354 2009 238587 1291864 1.66 2.15 47686 4993208 18600000 34.86 35.11 5895 85360030 188000000 617.49 999.38 316 2010 249073 1529414 1.59 2.10 49716 5376143 21800000 34.69 34.69 5717 85373909 158000000 611.26 949.19 301 2011 249129 1605428 1.53 2.08 51986 6117703 30000000 34.59 34.40 5512 94409649 219000000 597.38 853.65 300 2012 242748 1661560 1.40 2.06 54070 6500910 39600000 34.73 34.93 5370 96615010 236000000 604.21 834.59 286 2013 234678 1770631 1.39 2.03 55734 6469627 35300000 34.44 34.75 5305 98927396 243000000 607.31 859.78 273 2014 238485 1636268 1.42 2.02 57852 6378389 32600000 33.80 34.07 5465 102000000 248000000 608.87 864.99 273 2015 243094 1463876 1.46 2.04 59296 6360349 35500000 33.57 34.15 5649 104700000 241000000 619.91 862.73 269 2016 264514 2978791 1.52 2.07 59492 6232144 33000000 33.21 33.68 5825 102100000 240000000 611.19 836.75 286 2017 281826 2749487 1.56 2.10 60061 6291159 31200000 33.11 33.34 6106 116200000 301000000 610.66 814.01 303 2018 302747 3353227 1.60 2.13 59976 6406240 30200000 33.00 32.90 6454 118700000 317000000 609.75 800.39 319 2019 318832 4535272 1.63 2.15 60023 6349720 31700000 32.79 32.64 6832 116300000 288000000 611.55 804.90 323 2020 296746 3559891 1.62 2.13 60960 5949038 30400000 32.63 32.67 6854 111400000 249000000 602.97 795.68 311 186 ECONOMIC AND BUSINESS REVIEW 2022;24:171e186