How do accelerators impact the performance of high-technology ventures?

Accelerators aim to help nascent companies reach successful outcomes by providing capital, enabling industry connections, and increasing exposure to investors. Critically, however, accelerators also provide informative signals to founders about the probability of success. Founders use this information to decide whether to continue or shut down. To better understand these issues, I provide a model of accelerator participation and performance and then test empirical predictions from the model using a novel data set of approximately 900 accelerator companies across 13 accelerators and 900 matched nonaccelerator companies. I find that, through accelerator feedback effects, accelerator companies close down earlier and more often, raise less money conditional on closing, and appear to be more efficient investments compared with non-accelerator companies. Additional analysis using a separate sample of rejected accelerator applicants further supports these findings. These results suggest that accelerators help resolve uncertainty around company quality sooner, allowing founders to make funding and exit decisions accordingly.