What Happened After the EIB Loan?

The EIB impact assessment asks a harder question than whether venture debt is available: what changed after a selected company received it? This chapter examines the comparison with similar venture-capital-backed firms that did not receive identified venture debt. The goal is to read the results correctly—strong evidence of relative growth and additional financing, but not a blanket guarantee of employment, innovation, or long-run success.

A comparison designed to approximate a missing timeline

The ideal experiment would take the same company, give it an EIB venture loan in one version of reality, withhold the loan in another, and compare the outcomes. Only the first version can be observed. The EIB report therefore constructs a control group intended to approximate what the beneficiaries might have done without the loan.

The choice of controls is important. Comparing EIB borrowers with all European firms would mix together differences in innovation, age, growth ambition, and access to investors. Venture capital is a prerequisite for EIB venture debt, and VC-backed companies are already more similar to the beneficiaries in stage and innovation profile than the average firm. The report starts with about 12,000 firms that received venture capital but no identified venture debt. About 4,000 EU firms in that pool have the financial and employment information needed for the analysis.

From that pool, the researchers select firms similar to EIB beneficiaries on age and pre-treatment characteristics: number of employees, total assets, fixed assets, and long-term debt. They use propensity-score matching, a method that estimates how likely a firm is to receive the EIB instrument based on those characteristics and then chooses comparable controls. The age restriction focuses on firms founded between 2005 and 2018. The purpose is not to claim that matched firms are identical. It is to reduce observable differences before asking whether their trajectories diverge after the loan.

The comparison follows a difference-in-differences design. It measures the difference between beneficiary and control firms before treatment, then asks whether that difference changes after the EIB loan is signed. Firm fixed effects remove persistent differences such as a company’s location, sector, or underlying ability, to the extent those characteristics remain stable. Time fixed effects remove shocks shared across firms, such as broad financing conditions or economic growth. The estimated treatment effect comes from the additional post-signature change for the beneficiaries relative to the controls.

The logic is:

flowchart LR Pool["VC-backed candidate firms"] --> Match["Match on age, employees, assets, fixed assets, and long-term debt"] Match --> Groups["EIB beneficiaries and controls without identified venture debt"] Groups --> Pre["Check pre-treatment trends"] Pre --> Sign["EIB loan signature"] Sign --> Outcomes["Compare post-treatment outcomes"] Outcomes --> Assets["Total assets"] Outcomes --> Debt["Additional long-term debt"] Outcomes --> Value["Value added"]

The pre-treatment trend check is the hinge. If beneficiaries were already growing faster before the loan, then a later advantage could reflect selection rather than venture debt.