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Asher Griffith
6 years ago
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14 Number of companies 1,600 1, ,600 1, DACH NORDICS CENTER SOUTH BI CESEE ROW ICT Life Sciences Manufacturing Services Green Technologies

15 % of EIF-backed startups 100 % 75 % 50 % (% of matched startups) 25 % 0 % Nr. of employees Turnover Total assets Profit/Loss before taxes Return on assets Pre-tax profit margin Quick ratio Leverage ratio Available Data (%) Missing Data (%)

17 average median (with 95% C.I.) Number of Employees Nr. of employees Nr. of employees Number of Employees EUR million (2005 prices) Turnover Turnover EUR million (2005 prices) EUR million (2005 prices) Total assets Total assets EUR million (2005 prices) EUR million (2005 prices) Profit/Loss before taxes Profit/Loss before taxes EUR million (2005 prices) Years after first EIF-backed investment (t = 0)

19 Median (with 95% C.I.) Distribution classes Return on assets Return on assets % 5 25% more than 3 to 3-3 to less than -3 Pre-tax profit margin Pre-tax profit margin % 5 25% more than 5 to 5-10 to less than Quick ratio Quick ratio % 5 25% more than to 40 3 to 10 less than Leverage ratio Leverage ratio more than 20 75% 5 to 20 5 to 5 25% less than Years after first EIF-backed investment (t = 0)

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24 Total assets under-performers Employees nr. Turnover Company Valuation Patents nr ,50 Total assets moderate performers Employees nr. Turnover Company Valuation Patents nr ,50 Total assets sale-based growth Employees nr. Turnover Company Valuation Patents nr ,50 Total assets patent-based growth Employees nr. Turnover Company Valuation Patents nr ,50 Compound annual growth rate 5 years after investment (log scale)

26 Startup s macro-region location Startup s macro-industry Deviation from total sample (%) 45% 3 15% -15% -35% under-perfomers CENTER BI DACH NORDICS SOUTH CESEE ICT Life Sciences under-perfomers Services Manufacturing Green- Tech. 45% 3 15% -15% -35% Deviation from total sample (%) moderate performers moderate performers 45% 45% % 15% -15% -15% -35% CENTER BI DACH NORDICS SOUTH CESEE ICT Life Sciences Services Manufacturing Green- Tech. -35% sale-based growth sale-based growth 45% 45% % 15% -15% -15% -35% CENTER BI DACH NORDICS SOUTH CESEE ICT Life Sciences Services Manufacturing Green- Tech. -35% patent-based growth patent-based growth 45% 45% % 15% -15% -15% -35% CENTER BI DACH NORDICS SOUTH CESEE ICT Life Sciences Services Manufacturing Green- Tech. -35%

27 Startup s vintage period Age at (first) investment date Deviation from total sample (%) 45% 3 15% -15% -35% under-perfomers under-perfomers % 3 15% -15% -35% Deviation from total sample (%) moderate performers moderate performers 45% 45% % 15% -15% -15% -35% % sale-based growth sale-based growth 45% 45% % 15% -15% -15% -35% % patent-based growth patent-based growth 45% 45% % 15% -15% -15% -35% %

30 Exit types Initial Public Offering sale-based moderate growers patent-based performers growers underperformers underperformers moderate performers sale-based growers patent-based growers Written-off Trade sale (MOC < 1) Trade sale (MOC 1) Initial Public Offering

34 More patentbased growers 0 More salebased growers No data

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45 Size Performance Number of Employees Nr. of employees Return on assets 5 Percentage EUR million (2005 prices) Turnover Pre-tax profit margin -50 Percentage 20-1, , ,00 EUR million (2005 prices) Total assets Quick ratio Ratio EUR million (2005 prices) Profit/Loss before taxes Leverage ratio Ratio Lower quartile Median Upper quartile Years after first EIF-backed investment (t = 0)

53 median (with 95% C.I.) Return on equity median (with 95% C.I.) Pre-tax return on inv. capital Cashflow to capital expenditure ratio Weighted average cost of capital % -20 5% % Cash to current assets ratio Solvency ratio Years after first EIF-backed investment (t = 0)

55 Average of active variables Bayesian information criterion Average of active variables Calinski-Harabasz pseudo-f Number of clusters Number of clusters 100 Average of active variables Calinski-Harabasz pseudo-f Number of clusters 120

56 % of portfolio start-ups cluster affiliation probability (%) under-performers moderate perf. sale-based growth patent-based growth

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EIF s Impact Assessment (ImA)

EIF s Impact Assessment (ImA) Helmut Kraemer-Eis & Simone Signore EIF Research & Market Analysis EIB Group / Bruegel Workshop, Impact Assessment, 05 April 2017, Brussels EIF In a nutshell OBJECTIVE To