A Dynamic Model of Input–Output Networks.

This article develops a dynamic model of input–output networks incorporating adjustment costs for changing inputs, providing a closed-form solution that characterizes the gradual recovery from temporary sectoral productivity shocks and their welfare implications. It demonstrates that temporary shocks to upstream sectors—those whose outputs pass through long supply chains—have disproportionately large and persistent welfare impacts compared to what static Domar weights predict. Empirical analysis of the 2022 U.S. input–output network reveals that the welfare impact of temporary shocks can be effectively captured by a low-dimensional, three-factor spectral structure, highlighting a hierarchical and asymmetric network where upstream sectors play a critical role in shock propagation and recovery. Extensions of the model accommodate heterogeneous adjustment costs, gradual contraction and expansion of inputs, and continuous TFP recovery, with findings showing that network structure, rather than adjustment cost heterogeneity, primarily drives the variation in welfare impacts.