• We started with the initial filter that we applied to all PitchBook deals:
  • First Financing Deal Type (Seed Round OR Accelerator/Incubator)
  • First Financing Date (01.01.14 - 31.12.23)
  • First Financing Size (≤$500K)
  • Last Financing Deal Type (Fail (Bankruptcy: Admin/Reorg, Bankruptcy: Liquidation, Out of Business) OR Exit (Buyout/LBO, IPO, Merger/Acquisition, Reverse Merger, Secondary Transaction - Private, Secondary Transaction - Open Market))
• Next, we selected the deals that had the valuation data for the first and last financing if they resulted in an Exit event (3452 deals)
• After that, we added the missing values (like the Year Founded), calculated the difference between the foundation year and first financing date, and excluded those, which were greater than 2 years (2772 deals)
• Next, we manually identified the first investor(s) in each deal, left the startups, for which it was possible to perform (2293 deals), and cleaned the data from the faulty cases (2290 deals)
• For the resulting sample of deals, we manually checked each investor and identified its type. We excluded the cases, which were funded by corporates or were developed as spinoffs since these categories do not lie within the scope of this study (2246 deals)

Two additional data manipulations have to be explained:

• In some deals, several investors participated according to public data. These deals were duplicated to account for each investor, and the series amount was equally divided between all investors ignoring the possible variability in shares
• Several deals coming from VSs were assigned to other groups since, according to the public data, in these deals VSs behaved either like an accelerator or a VC fund