Appendix 1 Protecting investors index and correlation matrix

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Appendix 1

Protecting investors index and correlation matrix

Table 17 Protecting investors index

The following table presents the grades of the protecting investors index, collected from the website of the World Bank. The protecting investors index consists of the disclosure index, director liability index and the shareholder suits index. The investor protection index is an overall grade of these three indexes. All the countries included in this research are taken into account. The investor protection dummy used in the cross sectional analysis is divided in high and low investor protection. If the investor protection score of the acquirer minus the target is negative, then the investor protection is denoted as low. This means that the target country cannot take advantage of the higher investor protection of their acquirer.

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This tables presents the correlations between all variables used in the cross sectional analysis. These correlation are calculated to control for multicollinearity. If the correlation between two variables is higher than 0.8 then there is multicollinearity between two variables. This tables shows there is no multicollinearity between the variables.

Period Cons. Cons. Investor Economic

EU Private Majority 02-'08 Focus Goods Services Finan. Indus. Protection Freedom Poland U.S. Austria France Germany

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Appendix 2

Results event study

Table 19 Results of the AARs and CAARs for the event window of 21 days (Non-EU sample and EU sample)

The following table presents the AARs and CAARs for bidder shareholders of Non-EU and EU acquisitions for the event window of 21 days. The average abnormal return (AAR) says something about the abnormal return by each event day. The significance of the AARs is calculated by the one sided T-test. Statistical significance of 10%, 5% and 1% is denoted as *, **, ***. The number of events is 92.

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This table below presents the CAARs for bidder shareholders of the EU sample, the Non-EU sample and the total sample. Statistical significance is calculated by using the T-test. Differences between the samples are calculated by the T-test for independent variables. Statistical significant of 10%, 5% and 1% denotes *,** or ***. SD = standard deviation and N = the amount of events

CAAR CAAR CAAR CAAR

21 days 3 days 10 days 10 days

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This figure present the AARs per event day. The green polynomial trend line represents the trend of the AARs for the EU sample during the event window of 21 days. The black line denotes the polynomial trend line for the Non-EU sample. The trend for the EU sample is increasing from the announcement date (=0), while the Non-EU sample is decreasing from the announcement date.

Figure 3: Economic freedom by EU transition country

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Appendix 3

Results univariate analysis

-5,00% -4,00% -3,00% -2,00% -1,00% 0,00% 1,00% 2,00% -10 -8 -6 -4 -2 0 2 4 6 8 10 CA A Rs Event days

Figure 4: Non-EU bidders CAARs by legal status of the target company Public Private -2,00% 0,00% 2,00% 4,00% 6,00% 8,00% 10,00% 12,00% 14,00% -10 -8 -6 -4 -2 0 2 4 6 8 10 CA A Rs Event days

Figure 5: Non-EU bidder CAARs by legal status of the target company

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Figure 6: EU bidders CAARs by type of acquisition

Minority Majority -1,00% -0,50% 0,00% 0,50% 1,00% 1,50% 2,00% 2,50% 3,00% 3,50% 4,00% 4,50% -10 -8 -6 -4 -2 0 2 4 6 8 10 CA A Rs Event days

Figure 7: Non-EU bidder CAARs by type of acquisition

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Figure 8: EU bidder CAARs by time period

Period '97-'02 Period '02-'08 -2,00% -1,00% 0,00% 1,00% 2,00% 3,00% 4,00% 5,00% -10 -8 -6 -4 -2 0 2 4 6 8 10 CA A Rs Event days

Figure 9: Non-EU bidder CAARs by time period

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Figure 10: EU bidder CAARs by corporate strategy

Diversification Focus -0,50% 0,00% 0,50% 1,00% 1,50% 2,00% 2,50% 3,00% 3,50% -10 -8 -6 -4 -2 0 2 4 6 8 10 CA AR s Event days

Figure 11: Non-EU bidder CAARs by corporate strategy

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The following table presents the bidder shareholders CAAR by industry of the acquirer. The results are presented for the European sample, Non-European sample and for the total sample. Furthermore, the differences in the CAARs between the sub samples is calculated by using the T-test for independent variables. Other industries are: Oil and Gas, Basic Materials, Healthcare, Telecommunications, and Technology. Statistical significance of 10%, 5% and 1% is denoted as *,** or ***. N is the number of events.

Event window 21

Consumer Consumer Financials+

Goods Services Utilities Industrials Others

EU sample N= 46 N= 31 N= 38 N= 46 N= 30 CAAR [-10;10] 2,29% 3,11% 0,76% 0,99% -3,14% StDEV 0,76% 1,09% 0,47% 0,58% 1,59% T-test 1,289 1,245 0,476 0,602 -1,274 Non-EU sample N= 19 N= 20 N= 7 N= 21 N= 25 CAAR [-10;10] 2,80% 0,00% 1,59% 9,36% 0,11% StDEV 0,77% 0,71% 0,93% 3,29% 0,69% T-test 1,079 0,000 0,385 3,734 *** 0,026 ALL N=65 N=51 N=45 N=67 N=55 CAAR [-10;10] 2,44% 1,89% 0,99% 3,61% 0,90% StDEV 0,63% 0,65% 0,36% 1,25% 0,40% T-test 1,778 * 0,964 0,682 2,423 ** 0,377 Difference EU and Non-EU -0,51% 3,11% -0,83% -8,37% -3,25% T-test 2,049 ** 6,512 *** 4,262 *** 5,901 *** 4,536 *** -4,00% -3,00% -2,00% -1,00% 0,00% 1,00% 2,00% 3,00% 4,00% -10 -8 -6 -4 -2 0 2 4 6 8 10 CA A Rs Event days

Figure 12: EU bidder CAARs by industry

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Figure 13: Non-EU bidder CAARs by industry

Consumer Goods Consumer Services Financials

Industrials Others

Table 22 Statistical differences between industries for the event window of 3 days

This following table presents the statistical differences between the industries investigated in this research. The statistical differences between the industries is measured by using the T-test between two independent variables. Statistical significance of 10%, 5% and 1% is denoted as *,** or ***.

Event window 3

Difference Difference

Industry EU sample T-test Non-EU sample T-test

Consumer goods - Consumer services 0,39% 0,134 -0,92% 1,358

Consumer goods - Financials 1,76% 1,928 * 0,68% 0,725

Consumer goods - Industrials 0,11% 0,465 -2,09% 1,807 *

Consumer services - Financials 1,37% 1,997 ** 1,60% 0,040

Consumer services - Industrials -0,28% 0,378 -1,17% 0,787

Financials - Industrials -1,65% 1,361 -2,77% 0,515

Consumer goods - Others 3,53% 2,885 *** -0,66% 0,736

Consumer services - Others 3,14% 2,938 *** 0,26% 0,720

Financials - Others 1,77% 1,985 ** -1,34% 0,386

Industrials - Ohters 3,42% 2,344 *** 1,43% 1,383

Table 23 Statistical differences between industries for the event window of 21 days

This following table presents the statistical differences between the industries investigated in this research. The statistical differences between the industries is measured by using the T-test between two independent variables. Statistical significance of 10%, 5% and 1% is denoted as *,** or ***.

Event window 21

Difference Difference

Industry EU sample T-test Non-EU sample T-test

Consumer goods - Consumer services -0,82% -1,919 ** 2,80% 8,328 ***

Consumer goods - Financials 1,53% 5,792 *** 1,21% 3,257 ***

Consumer goods - Industrials 1,30% 3,537 *** -6,56% 4,793 ***

Consumer services - Financials 2,35% 6,016 *** -1,59% 4,901 ***

Consumer services - Industrials 2,12% 4,919 *** -9,36% 6,485 ***

Financials - Industrials -0,23% 3,130 *** -7,77% 6,195 ***

Consumer goods - Others 5,43% 6,198 *** 2,69% 6,971 ***

Consumer services - Others 6,25% 7,234 *** -0,11% 2,140 **

Financials - Others 3,90% 3,923 *** 1,48% 2,901 ***