Annamaria Conti

Abstract

We document and quantify the importance of information frictions in the market for startup acquisitions. Examining a sample of 5,727 Israeli venture-backed startups, we implement machine learning algorithms to generate dyads of technologically similar companies. Difference-in-differences and instrumental variable models show that the acquisition of a startup by a foreign company increases the chances that its technologically-related pair is also acquired by a foreign company by approximately 42%. This effect is largest for acquisitions that are prominent in the news. Consistent with information frictions being more severe for distant acquirers, acquisitions of Israeli startups by foreign companies minimally affect the pairs’ likelihood of being acquired domestically. Moreover, we show that foreign companies are insensitive to acquisitions of Israeli startups by domestic incumbents, suggesting that the information value of an acquisition is greatest when the acquirer is foreign. An in-depth analysis of venture capitalist reactions and startup sales prices confirms that, following an initial acquisition, the foreign demand for Israeli startups increases, although the supply of startups available for an acquisition seems to rise as well.