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Adjusting the rate of R&D spending is costly if the probability of converting new hires into productive R&D workers ("onboarding") is decreasing in the number of hires ("congestion"). We show that such congestion induces R&D-producing firms to hire slowly in response to good shocks, and hoard workers in response to bad shocks, providing a microfoundation for the convex adjustment costs widely used to capture the delayed, hump-shaped response of R&D spending to shocks. Using novel, high-frequency productivity data on individual software developers collected from GitHub, we document quantitative evidence suggesting that congestion is an economically-significant feature of R&D investment production.
