A large and growing literature demonstrates the impact of early stage investments on start-up success, and the factors that affect the terms of financing. But, what factors drive the investment process of early-stage investors, that is, how do they choose which start-up to fund?
The ideal setting to establish causality would compare an investor's reaction to two identical firms that differ only in the characteristic of interest. Such a setting is not feasible using observational data, but here we approximate it with a randomized field experiment using the correspondence testing methodology pioneered in labour economics. The experiment takes place on Seedrs, a European online equity investment platform that matches start-ups and angel investors. We observe these start-up companies at the stage at which they approach investors to raise capital through Seedrs.
Seedrs present "campaigns" to investors on their web site featuring start-ups that are raising capital. On the primary window for each campaign, and on the top banner, the web site contains information on how much money the firm aims to raise, equity offered, current valuation, how much it has raised to date, and number of days of the campaign remaining. In addition, Seedrs provides several additional pieces of information below the top banner: the founding team, lead investors and amounts, company legal information, and the idea. Investors may choose to remain anonymous, or they may show their name and provide investment experience. Through clickable tabs further pages provide information about the start-up team (position, time commitment and ownership share), the market, updates, Q&A and all investors.
In the experiment, we randomly choose which of the categories of information which is first presented to a potential investor, and exploit the variation across angels' reaction within each start-up. We randomly display on the first page an investor with a leading amount as lead investor (or not), and either as anonymous or with their name displayed, to determine whether their identity matters, both for entrepreneurs and for unrelated investors. We infer which factors drive investors' decisions by measuring each investor's interest in the company by the "click-through" on any of the tabs to subsequent information. On the subsequent investor page all the above information is displayed for all subjects, but on this investor page we still randomly either permanently hide or display the investment pedigree of the investor to determine if this is an important feature for follow-on investments. We also record whether the order of information, and whether knowing the investment pedigree, matters for subsequent investments.