Government venture capital and exit performance in European AI start ups

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School of Business | Bachelor's thesis
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Date

2025

Department

rahoitus

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Mcode

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raho

Language

en

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25 + 12

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Abstract

This thesis examines whether government-backed venture capital (GVC) and independent venture capital (IVC) investors differ in their ability to lead portfolio companies to successful exits in the European artificial intelligence (AI) industry. The sample consists of 948 first-round investments made in AI firms across the EU27 between 2011 and 2020. Investor type is determined based on the lead investor in the initial financing round. Firm-level investment and exit data are obtained from Refinitiv Workspace, and portfolio companies are classified as successful or unsuccessful depending on whether an IPO or merger and acquisition (M&A) exit is observed after allowing for a minimum four-year exit window through the end of 2024. Exit performance is evaluated with logistic regression models, where success is measured as a binary outcome, and Cox proportional hazard models are additionally employed to account for exit timing and right-censoring. Across all specifications, investment size emerges as the only statistically significant and robust predictor of exit success. The results do not support the conventional GVC underperformance hypothesis, although the estimated effects remain statistically insignificant.

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Thesis advisor

Kokkonen, Joni

Keywords

venture capital, Europe, independent venture capital, government-backed venture capital, exit performance, AI industry

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https://urn.fi/URN:NBN:fi:aalto-202602152516

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[kand] Kauppakorkeakoulu / BIZ (Open Access)