The Formation of Production Networks: How Supply Chains Arise from Simple Learning with Minimal Information (2504.16010v1)

Abstract: We develop a model where firms determine the price at which they sell their differentiable goods, the volume that they produce, and the inputs (types and amounts) that they purchase from other firms. A steady-state production network emerges endogenously without resorting to assumptions such as equilibrium or perfect knowledge about production technologies. Through a simple version of reinforcement learning, firms with heterogeneous technologies cope with uncertainty and maximize profits. Due to this learning process, firms can adapt to shocks such as demand shifts, suppliers/clients closure, productivity changes, and production technology modifications; effectively reshaping the production network. To demonstrate the potential of this model, we analyze the upstream and downstream impact of demand and productivity shocks.