This analysis identified investment needs and obstacles to investment for firms with significant growth potential, including SMEs in the industry sector across EU Member States. These results based on firm level data complement the quantitative analysis of industrial value chains discussed in section 3.1 and have guided the design and development of the qualitative analysis based on interviews, reported in section 3.3. Finally, this analysis provided useful evidence for designing the investment packages discussed in Chapter 7. The main findings are summarised below.
Firms with high-growth potential (expected turnover growth of over 20% per year over 2015-2017) and large investment needs (external financing from €250,000 to over €1 million) to realise their growth ambitions tend to be medium-sized (50-249 employees); middle aged (2-10 years); simultaneous innovators and exporters.
Firms that prefer equity capital over bank loans are more likely to be both high growth-potential firms and firms with large-investment needs. The effect is strongest for firms reporting the highest investment needs (over €1 million).
Firms reporting obstacles to financing (insufficient collateral or guarantee; interest rates or price too high; reduced control over the enterprise; too much paperwork involved; financing not available at all; or other obstacles) are more likely to report investment needs over €1 million.
Smaller firms are more likely to face obstacles to financing than larger firms. Firms in the 5-10 years age category are more likely to report any type of obstacle relative to older firms; in contrast, simultaneous exporters-innovators are less likely to do so, relative to firms which neither export nor innovate.
Overall, the general profile of firms with high-growth potential and high-investment needs described above is similar across various EU groups of countries. The smallest economies and Eastern EU countries tend to report larger shares of high-growth potential firms in comparison to Central and Western EU countries. However, Western EU countries tend to report larger shares of firms with high investment needs while Eastern EU countries tend to report lower shares of these types of firms.
In addition to complementing the quantitative analysis in Task 1.2 and guiding the qualitative analysis in Task 1.4, the results of the firm level analysis are useful for the design of the investment packages to be discussed in Task 2.
Data and measures
This empirical analysis was based on a representative firm level data in EU Member States related to access to finance and innovation activities, the Survey of the Access to Finance of Enterprises (SAFE). The SAFE questionnaire, conducted by the European Central Bank and the European Commission, provides a rich source of information on firms’ financing conditions in the Member States. The survey covers micro, small, medium-sized and large firms and provides evidence on the financing conditions faced by SMEs compared with those of large firms over six month periods over 2009-2015. This analysis was based on the April to September 2015 survey data, the most recent available for the purpose of identifying firms’ investment needs, financing gaps and obstacles to investment.
The analysed sample includes 3,806 firms in the industry sector across EU 28 countries. Firms with significant growth potential are defined as those firms with expected turnover growth of over 20% per year over 2015-2017. The SAFE survey also provides direct information on firms’
Study on investment needs and obstacles along industrial value chains: Final Report
assessment of investment needs (external financing) to realise growth ambitions over the three years ahead.
Empirical approach
The empirical approach is based on econometric analysis that links the high-growth potential firms with their characteristics, investment needs, and obstacles to investment.
The econometric analysis proceeded as follows:
Profiling firms with significant growth potential (the target group) in EU 28 and its distribution across Member States;
Identifying investment needs for the target group and preferred financing mode; and
Profiling firms facing obstacles to investment in the target group.
The profile of high growth-potential firms has been identified by estimating the following probability (probit) model:
ℎ𝑔𝑝
𝑖= 𝛽
0+ 𝛽
1𝑠𝑖𝑧𝑒
𝑖+ 𝛽
2𝑡𝑢𝑟𝑛
𝑖+ 𝛽
3𝑎𝑔𝑒
𝑖+ 𝛽
4𝑔𝑟
𝑖+ 𝛽
5𝑒𝑥𝑝
𝑖+ 𝛽
6𝑖𝑛𝑛
𝑖+ 𝜀
𝑖(1)
where hpg denotes a binary variable taking value 1 if the firm expects turnover growth greater than 20% over the following three years and 0 otherwise; size, turn and age denote categorical variables identifying the number of employees, firms’ turnover and age, respectively; gr denotes a binary variable taking value 1 if the firm is an affiliate or a branch of a business group; exp and inn denote, respectively, binary variables taking value 1 if the firm reports that part of its revenue is obtained from exporting and that it has introduced a product, process, marketing or organisational innovation in the past twelve months. The relevance of exporting and innovation activities has also been tested by introducing a categorical variable indicating the intensity of export turnover4 (exp_int) and a categorical variable identifying whether a firm belongs to one of the following mutually exclusive categories5 (ex_in): neither exporting nor innovation, exporting but no innovation, innovation but no exporting, both exporting and innovation.The profile of firms with high-investment needs
has been identified in two alternative ways:
(1) by analysing the factors associated with the probability of being a high growth-potential firm reporting high investment needs (financing needed larger than €250,000), relative to all other firms in the sample (probit analysis). To this purpose, the following model was estimated:
ℎ𝑔𝑝_ℎ𝑖𝑛
𝑖= 𝛽
0+ 𝛽
1𝑠𝑖𝑧𝑒
𝑖+ 𝛽
2𝑡𝑢𝑟𝑛
𝑖+ 𝛽
3𝑎𝑔𝑒
𝑖+ 𝛽
4𝑔𝑟
𝑖+ 𝛽
5𝑒𝑥_𝑖𝑛
𝑖+ 𝜀
𝑖(2)
where hgp_hin denotes a binary variable taking value 1 if a firm expects turnover growth greater than 20% and reports high investment needs. The explanatory variables in model (2) have the same interpretation as in model (1), except for ex_in, which denotes the four mutually exclusive categories of exporters and innovators described above.(2) by analysing the factors associated with the probability of being in a specific investment need category (ordered probit analysis), focusing separately on the target group of high growth-potential firms and for all firms. For this purpose, the following model was estimated:
4
As an alternative to engagement in exporting (exp).
5
𝑖𝑛𝑣_𝑛
𝑖= 𝛽
0+ 𝛽
1𝑠𝑖𝑧𝑒
𝑖+ 𝛽
2𝑡𝑢𝑟𝑛
𝑖+ 𝛽
3𝑎𝑔𝑒
𝑖+ 𝛽
4𝑔𝑟
𝑖+ 𝛽
5𝑒𝑥_𝑖𝑛
𝑖+ 𝜀
𝑖(3)
where inv_n denotes a categorical variable identifying the amount of financing firms report to need to realize their growth potential.
Further, to better understand the investment needs of firms with high growth potential, the Study analysed the
preferred source of financing for firms with high growth-potential
and firms with high investment-needs. This question is explored adding to the regressors in
models (1)-(3) a categorical indicator representing the reported preferred source of financing among the following alternatives: bank loan, other loans, equity, other financing. The Study examined nextobstacles to financing growth enhancing activities.
It looked at the identified relationship between firms’ obstacles to financing growth and the probability of being a high growth-potential firm and a firm with high investment-needs. To this purpose, a binary variable identifying firms facing obstacles to financing (of any kind) was introduced in the models (1)-(3) discussed above. The results of the estimated augmented models reveal that these firms are less likely to expect high growth and to be firms with high-growth and high-investment needs, relative to firms facing no obstacles to financing. When exploring the association with the probability of being in a particular investment needs category, it appears that obstacles to financing are negatively related to the probability of being a firm in lower investment needs categories, but positively related to the probability of being in the higher investment needs categories.In order to further understand the characteristics of firms reporting obstacles to financing
growth ambitions the following models were estimated:
𝑜𝑏𝑠𝑡
𝑖= 𝛽
0+ 𝛽
1𝑠𝑖𝑧𝑒
𝑖+ 𝛽
2𝑡𝑢𝑟𝑛
𝑖+ 𝛽
3𝑎𝑔𝑒
𝑖+ 𝛽
4𝑔𝑟
𝑖+ 𝛽
5𝑒𝑥_𝑖𝑛
𝑖+ 𝜀
𝑖(4)
where
obst
denotes a binary variable taking value 1 if a firm reports any of the following obstacles:insufficient collateral or guarantee, interest rates or price too high, reduced
control over the enterprise, too much paperwork involved; financing not available at all, or
other, and 0 if the firm reports there are no obstacles to financing growth.
In order to explore in more depth the relevance of the specific obstacles faced by firms to financing their growth, an additional series of models was estimated:
𝑜𝑏𝑠𝑡_𝑠𝑝𝑒𝑐
𝑖= 𝛽
0+ 𝛽
1𝑠𝑖𝑧𝑒
𝑖+ 𝛽
2𝑡𝑢𝑟𝑛
𝑖+ 𝛽
3𝑎𝑔𝑒
𝑖+ 𝛽
4𝑔𝑟
𝑖+ 𝛽
5𝑒𝑥_𝑖𝑛
𝑖+ 𝜀
𝑖(5)
where obst_spec denotes a binary variable taking value 1 if a firm reports a specific obstacle (e.g. insufficient collateral) and 0 if the firm reports there are no obstacles. Model (5) was therefore estimated separately for each type of obstacle.Study on investment needs and obstacles along industrial value chains: Final Report
Firms with High-Growth Potential and their Investment Needs: Quantitative Analysis by Groups of EU Countries
In order to explore whether there is variation within the EU 28 in the profile of firms with high growth potential and large investment needs, models (2) and (3) were estimated separately for groups of countries defined along geographical closeness and economic similarities. The composition of the analysed groups of EU countries are as follows:
Southern EU group: Portugal, Italy, Greece and Spain;
Central EU group: Germany, France, Austria, Belgium, Netherlands and Luxembourg;
Eastern EU group: Croatia, Hungary, Romania, Bulgaria, Poland, Czech Republic, Slovakia, Slovenia;
Nordic and Baltic EU group: Sweden, Finland, Denmark, Estonia, Latvia, Lithuania;
UK and Ireland EU group.
Overall, the general pattern in regard to the profile of high growth-potential and high investment-needs firms described above is similar across the various groups of EU countries. Due to the smaller size of the analysed firms’ samples, some estimates are no longer statistically significant. However, the sign of the most estimated coefficients does not change.