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Internationalization of blue-chip versus mid-cap stock indices: an empirical analysis for France, Germany, and the UK.

Introduction

Investments in domestic stock indices provide investors with international diversification and can prevent them from home-biased investment decisions. To realize these diversification benefits, investors do not need to pick single firms. Instead, selecting broad domestic stock indices already yields a considerable degree of international diversification (e.g., Oehler et al. 2015). This means that investors are able to realize international diversification benefits even without investing in foreign stocks (e.g., Berrill and Kearney 2010). Firm size, on the other hand, has been shown to be positively correlated with the degree of firm-level internationalization (e.g. Horst 1972; Riahi-Belkaoui 1999; Mayer and Ottaviano 2007; Altomonte et al. 2014). More recent studies, however, challenge this finding by detecting smaller firms which sell niche products via low-cost communication channels resulting in export intensities of up to 75% already in the second year after their foundation (so called born globals and international new ventures', e.g. Hennart 2013).

Our contribution to the literature is an answer to the question of whether investments in indices with the highest market capitalization provide a higher degree of international diversification than investments in indices with less market capitalization. Beyond this, we contribute to the literature with an analysis of whether a specific industry focus influences index constituents' level of international diversification. Since extensive literature already documents positive effects of international diversification on portfolio performance, we do not quantify the impact of international diversification on investors' risk-return profile. Instead, we examine whether index characteristics such as market capitalization and industry focus act as indicators for stock indices' level of international diversification.

Our research questions are of particular importance for different investor groups. It is important for retail investors to know whether they need to stick to indices that include firms with the highest market capitalization or whether mid-cap indices provide similar degrees of international diversification. Our findings provide implications for institutional investors, such as pension funds or mutual funds, with respect to both adequately diversified investment opportunities (e.g., investing in an index) and potential benchmarks for their investment decisions (e.g., tracking of indices).

We use a unique, hand-collected dataset which allows us to examine internationalization of blue-chip versus mid-cap indices in France, Germany, and the UK. We choose blue-chip and mid-cap indices as widely used index categories. In addition, the separation between blue-chip and mid-cap firms typically serves as a proxy for firm size. We chose stock indices in France, Germany, and the UK because, behind the U.S. and Japan, these three countries host the highest number of the 100 largest transnational companies (TNCs) worldwide (e.g., Ietto-Gillies 1998). Therefore, the blue-chip indices in these countries should cover a sufficient number of highly internationalized firms whereas we would not necessarily expect mid-cap indices in these countries to reach a similar degree of internationalization. However, domestic economies in European countries require firms to strive for higher export intensities if they want growth due to smaller domestic markets than those in the U.S. and Japan. Supporting this idea, Ietto-Gillies (1998) and Oehler et al. (2015) show that TNCs in Europe show higher degrees of internationalization than TNCs in the U.S. and Japan. Consequently, if mid-cap firms indeed show a lower degree of internationalization than blue-chip firms, the difference between both groups should be most obvious in European countries.

We follow Oehler et al. (2015) and use the following three indicators of internationalization: percentages of employees based inside and outside of the firms' home country, percentages of domestic and foreign sales, and percentages of domestic and foreign corporate tax payments. For France, we include the CAC40 as the blue-chip index and the two indices, CAC Next 20 and CAC Mid 60, which we aggregate to a combined mid-cap index. For Germany, we compare the blue-chip index DAX30 with the MDAX and TecDAX as a combined mid-cap index. For the UK, we form a blue-chip sample consisting of the 30 firms with the highest market values in the FTSE100 and a mid-cap sample including the remaining 70 companies with lower market values.

In the empirical analysis, we first combine the data for the three countries and analyze the overall level of international diversification in blue-chip versus mid-cap stock market indices. Second, we analyze blue-chip versus mid-cap indices separately for France, Germany, and the UK. Third, we examine whether differences in the degree of internationalization between blue-chip and mid-cap firms depend on the firms' industry sectors.

Our results for the combined sample of French, German, and UK indices reveal that, overall, both blue-chip and mid-cap indices exhibit high levels of internationalization. The degree of internationalization, however, appears to be stronger in blue-chip than in mid-cap indices, a finding that is mainly driven by German and UK firms. Details for French indices do not reveal statistically significant differences between blue-chip and mid-cap indices. Furthermore, blue-chip and mid-cap firms in the energy/materials/ utilities and industrials sectors exhibit similar levels of international diversification, which reflect mid-cap firms' high levels of internationalization in these sectors. Consequently, investments in blue-chip indices do not necessarily lead to higher levels of international diversification than investments in mid-cap indices. Internationalization is high in all industry sectors among both blue-chip and mid-cap firms.

Related Literature

Internationalization has mainly been analyzed in the context of international diversification of investment portfolios (e.g., Grubel 1968; Levy and Samat 1970; Solnik 1974; Errunza 1977; Erb et al. 1994; DeSantis and Gerard 1997; Errunza et al. 1999, and Bekaert and Harvey 2000). In recent years, however, the focus has shifted to international financial market integration (e.g., Errunza et al. 1994, Bekaert and Harvey 1995, Longin and Solnik 1995, Stulz and Williamson 2003, Brooks and Del Negro 2004, Bekaert et al. 2005, Goetzmann et al. 2005, Bekaert et al. 2007, Baele and Inghelbrecht 2009, Bekaert et al. 2009, Pukthuanthong and Roll 2009, Phengpis and Swanson 2011, Christoffersen et al. 2012, Chiou and Lee 2013, and Eiling and Gerard 2015). The impact of internationalization at the firm level has been analyzed in the context of multinational companies but hardly with focus on diversification benefits for investors.

Internationalization at the firm level is commonly attributed to an elite group of only a few very big firms ("the happy few," Mayer and Ottaviano 2007, Altomonte et al. 2014). Approaches which associate internationalization with large firms are supported by studies which identity a positive relationship between the level of internationalization and firms' value of equity (e.g. Horst 1972; Riahi-Belkaoui 1999; Mayer and Ottaviano 2007; Altomonte et al. 2014). However, these approaches are challenged by a significant number of smaller firms that are able to generate a considerable proportion of their revenue via foreign sales (Fillis 2001). In addition, firms that sell niche products via low-cost communication channels resulting in export intensities of 25% in the first year and 75% in the second year after their foundation (so called born globals and international new ventures; e.g., Hennart 2013) support the idea that internationalization is not limited to the largest firms (also Curci et al. 2013 and Altomonte et al. 2014).

Instead, firms' degree of internationalization may also depend on the industrial sector. Ietto-Gillies (1998) finds that some industries, including food, beverages, tobacco, and oil and gas extraction and refining, show a higher degree of internationalization because firms need to provide their products and/or locate employees near the customers and/or near the sources of raw materials. Analyzing the phenomenon of bom globals, Hennart (2013) supports the idea that firms' degree of internationalization depends on their industrial sector. He argues that bom globals differ from other firms by selling products or services which do not require adapting the international marketing mix. Instead, they use low-cost communication and delivery channels. Other firms and products or services, however, might be the subject of local regulation. Likewise, some products cannot be communicated and transported via low-cost channels, which impedes internationalization.

Data and Methodology

To measure blue-chip and mid-cap index constituents' level of internationalization, we follow Oehler et al. (2015) and use the following three indicators: percentages of employees based inside and outside of the firms' home country, percentages of domestic and foreign sales, and percentages of domestic and foreign corporate tax payments. Foreign employment (see, e.g., Ietto-Gillies 1998; Hassel et al. 2003) and foreign sales (e.g., Sullivan 1994; Ietto-Gillies 1998; Hassel et al. 2003; Berrill and Kearney 2010) are frequently used in studies that analyze firms' degree of internationalization and in internationalization indices (for an overview of approaches to measure firm-level internationalization e.g., Hitt et al. 1997, Dorrenbacher 2000, and Aggarwal et al. 2011). The data on these criteria and on foreign tax payments are publicly available in the firms' annual reports and, therefore, even retail investors can easily access this information through the firms' websites. Some studies also consider the geographic distribution of total assets (e.g., Dorrenbacher 2000). We, however, do not include geographic distribution of assets for two reasons. First, firms' distribution of assets and sales were traditionally highly positively correlated (e.g., Ietto-Gillies 1998). Second, the geographical distribution of firms' assets is hardly reported in firms' annual reports. Likewise, we do not determine the international composition and background of the top management team (e.g., Sullivan (1994), Ramaswamy et al. 1996, and Sanders and Carpenter 1998) and the internationalization along the value chain proposed by Curci et al. (2013) as data for these measures are typically not included in the annual reports.

We use data published in the annual reports for the year 2012 of firms that are included in the German stock market indices DAX30, MDAX, and TecDAX, the French stock market indices CAC40, CAC Next 20, and CAC Mid 60, and the UK stock market index FTSE100. The annual reports are collected from the firms' websites. In addition, we use share price data and number of outstanding shares extracted from Thomson Reuters Datastream to compute FTSE100 constituents' market values at the end of 2012. As an industry taxonomy, we use the Global Industry Classification Standard (GICS) as developed by MSCI and Standard & Poor's. (1)

By analyzing domestic and foreign values for employees, sales, and corporate taxes, we refer to the intensity dimension of internationalization proposed by Ietto-Gillies (2010). In addition, for employees and sales we differentiate between Europe (including the home country) as the firms' main geographic region and the rest of the world which, when comparing to the results from the first approach, allows us to analyze where the firms' foreign activities are concentrated, either in the main geographic region (Europe) or beyond. We thereby refer to the geographic concentration dimension of internationalization proposed by Ietto-Gillies (2010). (2) Following both approaches also reflects that internationalization data in particular on employees and sales are not presented in a uniform way in the firms' annual reports.

First, we form a combined sample that includes the blue-chip index constituents from France, Germany, and the UK and compare them with the combined sample including all mid-cap index constituents from the three countries. Thereafter, we analyze the country-specific samples separately. This means that we compare our internationalization indicators for constituents of the French CAC40 as the blue-chip index and the two indices CAC Next 20 and CAC Mid 60 which we aggregate to a combined mid-cap index. For Germany, we compare the blue-chip index DAX30 with results for the MDAX and TecDAX as a combined mid-cap index. Since the UK's most popular index is the FTSE100, we form the UK blue-chip sample based on the 30 firms with the highest market values at the end of the year 2012, and we combine the remaining 70 companies with lower market values into the UK mid-cap index.

We analyze the values at the index level, because investing in indices typically represents a low-cost alternative to individual stock picking. Investors who choose to invest in entire indices will not focus on firm-level but on index-level internationalization. This means that when choosing between investments in blue-chip and mid-cap indices as a proxy for the constituents' size, they need to know whether aggregate degrees of internationalization show significant differences between indices. Therefore, we favor a comparison of the degree of internationalization at the index level over potentially more sophisticated regression analyses that would examine the impact of size on internationalization at the firm level. We compute mean and median values, the 20th and 80th percentiles, and standard deviations for domestic and foreign values of our three indicators, employees, sales, and corporate taxes. To identify if potential differences are statistically significant, we employ a parametric approach using t-tests as tests of equality. We additionally employ a non-parametric approach using Wilcoxon tests. Although t-tests are generally quite robust to violations of the underlying assumptions, the non-parametric approach makes fewer assumptions with respect to normal distribution of the variables. Running both tests is therefore intended to ensure the robustness of our results.

Finally, we analyze whether differences between blue-chip and mid-cap indices' degree of internationalization result from industry-specific effects. This means that we analyze the level of internationalization of blue-chip versus mid-cap firms separately for six industries. The industry-specific analysis includes the combined data across the three countries to avoid too small subsamples. Due to small number of firms in some industries, we merge energy, materials, and utilities and form the combined sector EMU, we merge consumer discretionary and consumer staples and form the combined sector consumer, and we merge information technology and telecommunication services to form the sector IT/telecom. Our industry-specific analysis is thus based on six sectors: EMU (energy, materials, and utilities), industrials, consumer, health, financials, and IT/telecom. For each of the six sectors, we provide mean values of our three indicators employees, sales, and corporate taxes and analyze differences between blue-chip and mid-cap indices using parametric t-tests.

Results and Discussion

We analyze blue-chip and mid-cap index constituents' degree of internationalization by comparing the percentages of employees based inside and outside of the firms' home country, percentages of domestic and foreign sales, and percentages of domestic and foreign corporate tax payments as documented in the firms' annual reports.

Results for the Combined Samples

The analysis of the samples that include the combined data for France, Germany, and the UK reveals a consistent picture of higher degrees of internationalization of blue-chip than of mid-cap firms. The level of internationalization, however, is high in both groups with more than 50% of the employees being employed abroad, more than 60% of the sales being generated abroad, and more than 50% of the taxes being paid abroad. Table 1 presents the detailed results for the combined sample of blue-chip index constituents versus the combined sample of mid-cap firms.

In Panel A of Table 1 we report percentages of employees based in the firms' domestic country and in the rest of the world (RoW), percentages of sales generated in the domestic country and in the RoW, and taxes paid in the domestic country and in the RoW. On average, 40.1% of the 56 blue-chip firms' employees work in the firms' domestic country and 59.9% work abroad, whereas the workforce in the 102 mid-cap firms is based to a larger extent in the firms' domestic country with 48.6%. The difference between blue-chip and mid-cap firms is statistically significant at the 10% level (t-test). The median values (39.5 vs. 44.1% in domestic country) support the findings. However we do not find a statistically significant difference when using the Wilcoxon test. The levels of sales abroad even indicate stronger levels of internationalization than the distribution of the workforce. Blue-chip firms exhibit even higher levels of foreign sales with mean (median) values of 74.2 (82.7) than mid-cap firms with foreign sales representing 61.8 (73.7)% of all sales. The differences between blue-chip and mid-cap firms are statistically significant at the one and 5% level when using the t-test and the Wilcoxon test, respectively. In addition, about one fifth of the 65 blue-chip firms and also of the 144 mid-cap firms generate more than 90% of their sales abroad. The proportions of domestic and foreign tax payments reveals the biggest difference between blue-chip and mid-cap firms among our measures, but also the highest dispersion among the firms within the two groups. Blue-chip (mid-cap) firms' mean value of domestic tax payments is 34.0 (49.9)% with a standard deviation of 35.8 (46.4)%. Differences between blue-chip and mid-cap firms are statistically significant at the 10 and 5% level based on the t-test and the Wilcoxon test respectively.

In Panel B of Table 1, we report blue-chip and mid-cap firms' percentages of employees based in Europe and in countries outside of Europe (RoW) as well as percentages of sales in Europe and in the RoW. The results support the findings in Panel A. Mid-cap firms employ less of their workforce and generate less sales outside of Europe than blue-chip firms. While the 70 blue-chip firms exhibit a mean value of employees working outside of Europe of 45.6%, the 104 mid-cap firms' mean value is 34.5%. The median values barely differ from the mean values. Tests of equality show statistically significant differences between blue-chip and mid-cap firms at the 1% level. In addition, blue-chip firms generate a higher proportion of their sales outside of Europe than mid-cap firms. However, only the Wilcoxon test reveals statistically significant differences (10% level).

Overall, this step in our analysis reveals similar or even higher degrees of internationalization in blue-chip indices compared to mid-cap indices. Potential explanations for less internationalization for mid-cap index constituents include high costs of establishing own sales structures abroad. Blue-chip firms are expected to be more able to make the necessary investments than mid-caps. Mid-caps, instead, might indirectly realize sales abroad by using intermediaries that are situated in the same country as the mid-cap firms but they specialize, e.g., in international trade and sell the products abroad. This type of foreign sales, however, neither requires mid-cap firms to employ their own workforce abroad nor are these sales reported as foreign sales in the annual reports.

Results for the Separate Analysis of French, German, and UK Indices

Investments in the French blue-chip index and the French mid-cap index provide similarly high degrees of internationalization. We present the detailed results for these indices in Table 2. In Panel A of Table 2 we report percentages of employees based in France and in the RoW and percentages of sales generated in France and in the RoW for both blue-chip and mid-cap index constituents. Due to insufficient data, we do not report results for domestic and foreign tax payments. The 21 French blue-chip firms, for example, employ 35.3% of their employees in France and 64.6% abroad. Overall, the results reveal that both blue-chip and mid-cap index constituents exhibit a strong degree of internationalization. The mean values indicate that about 65% of the blue-chip firm employees and about 60% of the mid-cap firm employees are based outside of France. The median values barely diverge from the mean values. Even the dispersion as reported using the 20th and 80th percentile is largely similar for blue-chip and midcap firms. The results for sales generated inside and outside of France strongly support the results for employees. Roughly three quarters of French blue-chip and mid-cap firms' sales are generated abroad. For both employees and sales, we do not find any statistically significant difference between the blue-chip and the mid-cap index.

In Panel B of Table 2 we report French firms' employees based in Europe, including France, and in the RoW, and sales generated in Europe and in other countries. Roughly 40% of both blue-chip and mid-cap index constituents' employees are based outside of Europe and about 45% of their sales are generated in non-European countries. These results support the finding of considerable internationalization without statistically significant differences between the blue-chip and the mid-cap index reported in Panel A. From these results, we conclude that an investment in the French mid-cap indices will not lead to less international diversification than an investment in the blue-chip index.

The results for German indices are presented in Table 3. Panel A of Table 3 comprises German and RoW values for the three indicators employees, sales, and tax payments for German firms that are listed in the blue-chip index DAX30 and in the combined mid-cap index covering the MDAX and the TecDAX. The mean percentage of employees in Germany, for example, is 43.1 % for the blue-chip index and 56.4% for the mid-cap index. The median values support these results. The overlap in the dispersion among the constituents of both indices is considerably smaller than in France. Consequently, our tests of equality reveal that the internationalization of the German blue-chip index is significantly larger than the internationalization of the German mid-cap index. With 78 and 59% for the blue-chip and the mid-cap index, respectively, the mean proportion of foreign sales reveals a high degree of internationalization for both indices. The median values are even larger than the mean values. The dispersion among German blue-chip firms is much smaller than the dispersion among the mid-cap firms. For both mean and median values we find statistically larger percentages of foreign sales in blue-chip than in mid-cap firms. German blue-chip index constituents pay a larger proportion of their taxes abroad (56%) than at home (44%), while mid-cap index constituents pay more taxes at home (57%) than abroad (43%). The difference, however, is statistically insignificant which results from the high dispersion among both blue-chip and mid-cap firms. Interestingly, the standard deviation among mid-cap firms is larger than 50% which is most probably a result of tax refunds some mid-cap firms received. For all three indicators, the domestic share is higher for the mid-cap index than for the blue-chip index suggesting a higher degree of internationalization of the latter index.

Panel B which includes German blue-chip and mid-cap index constituents' employees and sales in Europe and beyond (RoW) largely supports the findings from Panel A, even though the differences between the blue-chip and mid-cap index are less statistically significant. Specifically, blue-chip index constituents employ more of their workforce outside of Europe and they generate more sales outside of Europe than midcap index constituents.

Results for UK blue-chip and mid-cap index constituents are presented in Table 4. The domestic and foreign percentages in Panel A reveal a larger degree of internationalization of blue-chip than of mid-cap index constituents, in particular with respect to sales and tax payments. Both groups, however, exhibit strong overall levels of internationalization. Mean values indicate that more than half of the blue-chip firms' workforce (57%) are employed abroad, whereas mid-cap firms employ 50% abroad. In median values, both proportions are about 60%. However, there is no statistically significant difference between blue-chip and mid-cap firms. Interestingly, however, about 20% of the mid-cap firms have almost no employees abroad. The results for UK firms' domestic and foreign sales are very similar to the results for German firms. Specifically, blue-chip index constituents generate more sales abroad than mid-cap index constituents at statistically significant levels both when considering mean and median values. The 80th percentile supports this notion although overall dispersion is relatively large. The results for domestic and foreign tax payments support the finding of a larger degree of internationalization among blue-chip than among mid-cap index constituents. We find noteworthy that, given the median value of 7% of the taxes paid at home, nearly 50% of the UK blue-chip firms in our dataset do not pay taxes in the UK.

The results for employees and sales in Europe and RoW as reported in Panel B are very similar to the findings in Panel A. This means that the employees and sales outside the UK are actually related to countries outside of Europe. The larger proportion of employees outside of Europe for blue-chip than for mid-cap index constituents is statistically significant, which supports the notion of stronger internationalization for blue-chip firms.

Results for Industry Sectors

Finally, we analyze whether the degree of internationalization of blue-chip and mid-cap firms is sector-specific. We combine the data for France, Germany, and the UK and analyze six industries: EMU (energy, materials, and utilities), industrials, consumer, health, financials, and IT/telecom. On average, blue-chip (mid cap) firms in every sector have at least 52 (31)% of employees based abroad, 54 (37)% of foreign sales, and 53 (18)% of foreign tax payments. The detailed results are presented in Table 5.

Panel A of Table 5 comprises domestic (Home) and RoW values as well as the number of firms included per sector (N) for the three indicators employees, sales, and tax payments. The blue-chip firms' percentage of employees in the domestic country ranges from 15.8 (health) to 48.4 (EMU). Among mid-cap firms, the health sector appears to be the most internationalized sector (63.2% of the employees are based in foreign countries) and firms in the financial sector exhibit the lowest degree of internationalization (31.4%). Mid-cap firms' mean percentages of employees in the domestic country exceed the respective blue-chip firms' mean values in five out of six sectors. The difference is statistically significant at the 5% level in the financial sector. Blue-chip firms have higher proportions of foreign sales than mid-cap firms in nearly all sectors. A statistically significant difference (1% level) can only be observed for the consumer sector. Although the blue-chip firms in the health sector exhibit the highest percentage of foreign sales, this result needs to be interpreted with caution due to the very small sample size. Blue-chip financials show the lowest degree of internationalization with a mean percentage of foreign sales of 53.6. Among blue-chip firms, financials pay the highest proportion of their taxes domestically (46.7%), whereas mid-cap firms in the IT/telecom sector pay the highest proportion of taxes domestically (82.5%). Blue-chip firms exhibit a higher proportion of foreign tax payments in four out of six sectors. Statistically significant differences however, are limited to the sectors IT/telecom and consumer (10 and 5% level, respectively).

Results in Panel B of Table 5 support the finding that blue-chip firms are internationalized at a higher degree than mid-cap firms across most sectors. Regarding employees and sales, the consumer and health sectors reveal significant differences between blue-chip and mid-cap firms at least at the 5% level. In both sectors the blue-chip firms' proportion of employees and sales outside of Europe exceed the corresponding amounts of the mid-cap firms. For the six blue-chip firms in the health sector, the difference compared to the mid-cap firms is significant at the 1% level.

In both panels and for all three measures, mid-caps in the financials sector show a low degree of internationalization. This finding is in line with Hennart (2013). As (especially retail) products in the financial sector are subject to domestic legal requirements (e.g., pension or insurance products), financial firms would need to adapt them for internationalization. Therefore, it is not surprising that mid-caps in this sector shun the risk to invest in costly adaptations of their product and marketing mixes, in particular when taking already highly competitive (local) markets for financial products and services into account. In contrast, blue-chip firms in the health sector show very high degrees of internationalization. This finding is in line with Ietto-Gillies (1998) who argues that in industries where firms need to provide their products and/or employees near the customers (as in the health sector), firms show higher degrees of internationalization.

Conclusions

We analyze the question whether blue-chip indices provide a larger degree of internationalization than mid-cap indices. Beyond this, we analyze whether a specific industry focus influences index constituents' level of international diversification. Since extensive literature already documents positive effects of international diversification on portfolio performance, we do not quantify the impact of international diversification on investors' risk-return profile. Instead, we examine whether index characteristics such as market capitalization and industry focus act as indicators for stock indices' level of international diversification. We apply these research questions to a dataset that includes French, German, and UK stock market indices. Our research question is of particular importance for retail investors and institutional investors alike. For retail investors, investing in an index typically represents a low transaction cost alternative to individual stock picking and at the same time delivers a considerable degree of diversification, even without taking international diversification into account. Our findings provide implications for institutional investors with respect to both adequately diversified investment opportunities (e.g., investing in an index) and potential benchmarks for their investment decisions (e.g., tracking of indices).

Our results for the combined sample of French, German, and UK stock market indices show that both blue-chip and mid-cap indices exhibit high degrees of internationalization. Particularly in Germany and in the UK blue-chip index, constituents' degree of internationalization appears to be even higher than internationalization in mid-cap indices. These results support findings of Horst (1972) and Riahi-Belkaoui (1999), Mayer and Ottaviano (2007), and Altomonte et al. (2014) who find that firm size is positively correlated with the degree of firm-level internationalization. Blue-chip firms in the consumer and health sectors appear to be more internationally diversified than mid-cap firms in these sectors. For French firms, we do not find statistically significant differences between blue-chip and mid-cap index constituents primarily due to mid-caps' high degree of internationalization which is comparable to German blue-chips' degree of internationalization. Similarly, we do not find statistically significant differences between blue-chip and mid-cap index constituents for the energy/materials/utilities and industrial sectors. Consequently, investments in blue-chip indices do not necessarily lead to higher levels of international diversification than investments in mid-cap indices. Internationalization is high in all industry sectors among both blue-chip and midcap firms. Mid-cap firms exhibit slightly lower levels of internationalization in only a few of the sectors.

The limitations of our study include inability to analyze the degree of internationalization of all index constituents because some firms do not report information in their annual reports that would allow us to include them in the dataset. Furthermore, indirect foreign sales, this means sales to local intermediaries that sell the products abroad (e.g., Bekes and Murakozy 2012) are not considered. As indirect foreign sales do not require a costly infrastructure abroad, smaller firms potentially have more indirect foreign sales than larger firms. Further research on the role of indirect foreign sales in internationalization is necessary to disentangle this effect and to identify if differences in foreign sales between blue-chip and mid-cap firms disappear when including indirect foreign sales. A further limitation of our study relates to our choice of measures of firms' internationalization. We are aware that various additional measures have been proposed in the literature. However, our approach focused on measures and information that are easily accessible for retail investors. Further research could therefore examine whether other measures provide results that are consistent with our findings. Moreover, we invite further research to expand our analysis to other countries and continents.

Acknowledgements We would like to thank Sergey Barabanov, University of St. Thomas, Minneapolis, Thomas Walker, Concordia University, Montreal, Andreas Hofer, participants of the 2015 Annual Meeting of the Academy of Financial Services, and an anonymous referee for helpful comments and suggestions. We further thank the editor and seminar participants at Bamberg University in Bamberg, Germany and Concordia University in Montreal, Canada. All remaining errors are our own.

Andreas Oehler (1) * Stefan Wendt (2) * Matthias Horn (3)

[mail] Andreas Oehler

andreas.oehler@uni-bamberg.de

(1) Bamberg University, Kaemtenstrasse 7, 96045 Bamberg, Germany

(2) School of Business, Reykjavik University, Menntavegi 1, 101 Reykjavik, Iceland

(3) Department of Finance, Bamberg University, Kaemtenstrasse 7, 96045 Bamberg, Germany

Published online: 8 December 2016

DOI 10.1007/s11293-016-9518-2

(1) See e.g. https://www.msci.com/gics for further information.

(2) Ietto-Gillies (2010) suggests a third dimension: geographic extensity, which reflects the number of countries a firm is active in. We do not use this dimension due to lack of data.

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Table 1 Internationalization of firms, full sample

Panel A

         Employees

         Blue chips    Mid caps      Significance

         Home   RoW    Home   RoW

Mean     40.1   59.9   48.6   51.3   *
20%      17.4   82.6   20.7   79.3
Median   39.5   60.5   44.1   55.2
80%      57.6   42.4   78.3   21.7
Sdv      22.8   22.8   29.1   29.2
N        56     56     102    102

         Sales

         Blue chips    Mid caps      Significance

         Home   RoW    Home   RoW

Mean     25.9   74.2   38.2   61.8   ***
20%      8.2    91.8   10.6   88.8
Median   17.3   82.7   26.3   73.7   **
80%      45.0   55.0   78.0   22.0
Sdv      22.7   22.8   32.6   32.6
N        65     65     144    144

         Taxes

         Blue chips    Mid caps      Significance

         Home   RoW    Home   RoW

Mean     34.0   65.9   49.9   50.2   *
20%      3.5    96.5   12.3   87.7
Median   28.4   71.6   47.7   52.3   **
80%      60.8   39.2   100.0  0
Sdv      35.8   35.7   46.4   46.4
N        41     41     73     73

Panel B
         Employees

         Blue chips      Mid caps        Significance

         Europe   RoW    Europe   RoW

Mean     54.4     45.6   65.4     34.5   ***
20%      36.5     63.5   46.8     53.2
Median   53.2     46.8   67.0     33.0   ***
80%      73.9     26.1   87.9     12.1
Sdv      23.6     23.6   23.2     23.3
N        70       70     104      104

         Sales

         Blue chips      Mid caps        Significance

         Europe   RoW    Europe   RoW

Mean     48.2     51.5   53.4     46.6
20%      28.5     71.5   31.5     68.5
Median   42.0     58.0   52.9     47.2   *
80%      74.2     25.8   72.5     27.5
Sdv      23.2     23.6   25.1     25.1
N        74       74     148      148

We document the level of internationalization of French, German, and
UK blue-chip and mid-cap indices at the end of 2012. In Panel A, we
report internationalization based on percentages of employees in the
domestic country (Home) and in the rest of the world (RoW),
percentages of domestic (Home) and foreign (RoW) sales, and
percentages of taxes paid in the domestic country (Home) and abroad
(RoW). In Panel B, we measure internationalization based on
percentages of employees in Europe and in the RoW and percentages of
sales in Europe and in the RoW. In each panel we report mean and
median values, 20th-and 80th-percentiles, standard deviations (Sdv),
and the numbers of firms included (N). We provide tests of equality
of mean and median values using parametric t-tests and non-parametric
Wilcoxon tests, respectively. The symbols ***, ** and * denote
statistical significance at the one, five and 10% level,
respectively. Source: Annual reports from the companies' corporate
websites and own calculations

Table 2 Internationalization of French firms

Panel A

         Employees                       Sales

         Blue chips      Mid Caps        Blue chips      Mid caps

         France   RoW    France   RoW    France   RoW    France   RoW

Mean     35.3     64.6   40.7     59.0   27.5     72.5   26.3     73.8
20%      15.0     85.0   20.0     79.7   9.3      90.7   8.4      91.6
Median   33.2     66.9   42.3     57.7   23.0     77.0   18.5     81.5
80%      56.5     43.5   60.2     39.8   43.9     56.1   43.8     56.3
Sdv      21.6     21.8   25.5     25.6   20.3     20.3   25.1     25.1
N        21       21     39       39     29       29     37       37

Panel B

         Employees                       Sales

         Blue chips      Mid caps        Blue chips      Mid caps

         Europe   RoW    Europe   RoW    Europe   RoW    Europe   RoW

Mean     57.4     42.5   62.2     37.6   54.3     45.1   54.9     45.2
20%      42.3     57.8   40.7     59.3   35.1     65.0   41.2     58.8
Median   54.6     45.4   59.4     40.6   51.9     48.0   52.5     47.5
80%      75.0     25.0   81.7     15.9   76.4     23.5   67.6     32.4
Sdv      20.2     20.4   23.3     23.3   21.7     22.0   21.5     21.5
N        33       33     48       48     37       37     52       52

We document the level of internationalization of French blue-chip and
mid-cap indices. In Panel A, we report internationalization based on
percentages of employees in France and in the rest of the world
(RoW), percentages of French and foreign (RoW) sales, and percentages
of taxes paid in France and abroad (RoW). In Panel B, we measure
internationalization based on percentages of employees in Europe
including France and in the RoW and percentages of sales in Europe
including France and in the RoW. In each panel we report mean and
median values, 20th-and 80th-percentiles, standard deviations (Sdv),
and the numbers of firms included (N). We provide tests of equality
of mean and median values of blue-chip vs. mid-cap firms using
parametric t-tests and non-parametric Wilcoxon tests, respectively.
However, the tests do not show statistical significant differences.
Source: Annual reports from the companies' corporate websites and own
calculations

Table 3 Internationalization of German firms

Panel A

         Employees

         Blue chips       Mid caps         Significance

         Germany   RoW    Germany   RoW

Mean     43.1      56.9   56.4      43.5   **
20%      29.7      70.3   34.4      65.0
Median   43.8      56.2   50.5      49.0   *
80%      55.5      44.5   82.8      16.7
Sdv      18.4      18.4   27.5      27.6
N        23        23     49        49

         Sales

         Blue chips       Mid caps         Significance

         Germany   RoW    Germany   RoW

Mean     21.8      78.2   41.9      59.4   **
20%      14.1      85.9   14.9      85.1
Median   17.3      82.7   30.1      72.2   **
80%      24.6      75.4   78.5      21.5
Sdv      15.5      15.5   30.7      30.0
N        16        16     63        63

         Taxes

         Blue chips       Mid caps         Significance

         Germany   RoW    Germany   RoW

Mean     43.7      56.3   57.0      43.0
20%      10.0      90.0   26.9      73.1
Median   34.5      65.5   69.4      30.6
80%      89.0      11.0   100.0     0.0
Sdv      38.2      38.2   53.1      53.1
N        17        17     37        37

Panel B

         Employees

         Blue chips      Mid caps        Significance

         Europe   RoW    Europe   RoW

Mean     67.2     32.8   74.7     25.1
20%      51.0     49.0   63.1     36.9
Median   66.8     33.2   73.0     27.0
80%      83.4     16.6   91.0     8.6
Sdv      19.1     19.1   16.1     16.2
N        21       21     41       41

         Sales

         Blue chips      Mid caps        Significance

         Europe   RoW    Europe   RoW

Mean     48.7     51.2   61.3     38.7   *
20%      39.0     60.9   40.6     59.4
Median   43.5     56.5   60.8     38.9   **
80%      54.7     45.3   84.9     16.0
Sdv      16.3     16.3   24.8     24.7
N        14       14     55       55

We document the level of internationalization of German blue-chip and
mid-cap indices. In Panel A, we report internationalization based on
percentages of employees in Germany and in the rest of the world
(RoW), percentages of German and foreign (RoW) sales, and percentages
of taxes paid in Germany and abroad (RoW). In Panel B, we measure
internationalization based on percentages of employees in Europe
including Germany and in the RoW and percentages of sales in Europe
including Germany and in the RoW. In each panel we report mean and
median values, 20th-and 80th-percentiles, standard deviations (Sdv),
and the numbers of firms included (N). We provide tests of equality
of mean and median values of blue-chip vs. mid-cap firms using
parametric t-tests and non-parametric Wilcoxon tests, respectively.
The symbols ** and * denote statistical significance at the five and
10% level, respectively. Source: Annual reports from the companies'
corporate websites and own calculations

Table 4 Internationalization of UK firms

Panel A

         Employees

         Blue chips     Mid caps      Significance

         UK     RoW     UK     RoW

Mean     42.6   57.3    50.2   49.8
20%      14.9   85.1    14.0   86.0
Median   39.4   60.6    38.7   61.3
80%      77.3   22.7    98.2   1.8
Sdv      31.6   31.7    38.6   38.6
N        12     12      17     17

         Sales

         Blue chips     Mid caps      Significance

         UK     RoW     UK     RoW

Mean     26.8   73.4    43.6   56.3   *
20%      5.3    94.7    7.5    92.6
Median   12.5   88.5    31.1   68.9   *
80%      65.4   34.3    92.4   7.6
Sdv      30.4   30.6    37.9   37.9
N        20     20      47     47

         Taxes

         Blue chips     Mid caps      Significance

         UK     RoW     UK     RoW

Mean     24.2   75.5    45.2   54.9   *
20%      -0.3   100.0   3.5    97.0
Median   7.0    93.0    37.5   62.5
80%      53.2   46.8    98.6   1.4
Sdv      36.1   35.9    40.1   40.2
N        16     16      30     30

Panel B

         Employees

         Blue chips      Mid caps        Significance

         Europe   RoW    Europe   RoW

Mean     31.3     68.6   50.8     49.2   **
20%      14.9     84.0   30.3     69.7
Median   30.2     69.8   51.7     48.4   **
80%      45.7     54.3   78.0     22.0
Sdv      19.5     19.6   28.7     28.7
N        16       16     16       16

         Sales

         Blue chips      Mid caps        Significance

         Europe   RoW    Europe   RoW

Mean     38.1     62.1   41.7     58.2
20%      16.7     83.4   19.6     80.4
Median   27.7     72.3   35.8     64.2
80%      61.5     38.5   64.2     35.8
Sdv      26.3     26.6   25.1     25.2
N        23       23     43       43

We document the level of internationalization of UK blue-chip and
mid-cap indices. In Panel A, we report internationalization based on
percentages of employees in the UK and in the rest of the world
(RoW), percentages of domestic and foreign (RoW) sales, and
percentages of taxes paid in the UK and abroad (RoW). In Panel B, we
measure internationalization based on percentages of employees in
Europe including the UK and in the RoW and percentages of sales in
Europe including the UK and in the RoW. In each panel we report mean
and median values, 20th-and 80th-percentiles, standard deviations
(Sdv), and the numbers of firms included (N). We provide tests of
equality of mean and median values of blue-chip vs. mid-cap firms
using parametric t-tests and non-parametric Wilcoxon tests,
respectively. The symbols ** and * denote statistical significance at
the five and 10% level, respectively. Source: Annual reports from the
companies' corporate websites and own calculations

Table 5 Internationalization of blue-chip and mid-cap firms in
industry sectors

Panel A

              Employees

              Blue-chips         Mid-caps

Sector        Home   RoW    N    Home   RoW    N    Sig.

EMU           48.4   51.6   12   37.5   61.8   13
Industrials   43.0   56.9   9    47.5   52.5   24
Consumer      31.7   68.2   13   46.8   53.0   28
Health        15.8   84.1   3    36.8   63.2   12
Financials    48.0   51.7   12   68.6   31.4   12   **
IT/Telec.     34.3   65.7   7    57.9   42.0   13

              Sales

              Blue-chips         Mid-caps

Sector        Home   RoW    N    Home   RoW    N    Sig.

EMU           24.2   75.9   16   23.2   76.9   18
Industrials   23.5   76.5   11   29.3   70.6   38
Consumer      18.9   80.9   20   41.2   58.6   35   ***
Health        7.0    93.0   2    30.4   69.7   12
Financials    46.7   53.6   11   62.5   37.4   15
IT/Telec.     25.7   74.2   5    47.2   52.9   26

              Taxes

              Blue-chips         Mid-caps

Sector        Home   RoW    N    Home   RoW    N    Sig.

EMU           41.4   58.2   10   24.5   75.5   5
Industrials   31.5   68.5   4    21.8   78.3   16
Consumer      25.2   74.8   11   52.3   47.7   20   **
Health        16.3   83.6   4    34.9   65.1   8
Financials    46.7   53.3   8    70.0   30.0   11
IT/Telec.     34.6   65.4   4    82.5   17.5   13   *

Panel B

              Employees

              Blue-chips         Mid-caps

Sector        Eur    RoW    N    Eur    RoW    N    Sig.

EMU           53.8   46.2   20   51.0   48.3   15
Industrials   64.1   35.9   10   69.2   30.8   26
Consumer      48.8   51.1   18   63.2   36.7   27   **
Health        40.7   59.3   6    68.8   31.2   13   ***
Financials    61.6   38.1   11   78.6   21.4   10
IT/Telec.     57.7   42.3   5    65.3   34.5   13

              Sales

              Blue-chips         Mid-caps

Sector        Eur    RoW    N    Eur    RoW    N    Sig.

EMU           44.6   54.3   20   38.8   61.2   25
Industrials   49.3   50.7   10   53.2   46.7   43
Consumer      45.5   54.4   24   59.1   40.8   34   **
Health        33.9   66.1   7    56.2   43.8   13   **
Financials    68.9   31.5   9    67.0   32.9   11
IT/Telec.     58.0   42.0   4    53.1   47.1   22

We document the level of internationalization of French, German, and
UK blue-chip and mid-cap indices segmented by industrial sector. In
Panel A, we report internationalization based on percentages of
employees in the domestic country (Home) and in the rest of the world
(RoW), percentages of domestic (Home) and foreign (RoW) sales, and
percentages of taxes paid in the domestic country (Home) and abroad
(RoW). In Panel B, we measure internationalization based on
percentages of employees in Europe and in the RoW and percentages of
sales in Europe and in the RoW. In each panel we report mean values
and the numbers of firms included (N) per sector. We provide tests of
equality of blue-chip vs. mid-cap firms using parametric t-tests. The
symbols ***, ** and * denote statistical significance at the one,
five and 10 % level, respectively. Source: Annual reports from the
companies' corporate websites, own calculations
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Author:Oehler, Andreas; Wendt, Stefan; Horn, Matthias
Publication:Atlantic Economic Journal
Geographic Code:4EUGE
Date:Dec 1, 2016
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