Planning Against Disasters in Dynamic Production Networks

Vasco M. Carvalho, Matias Covarrubias and Galo Nuño Barrau

No 12796, CESifo Working Paper Series from CESifo

Abstract: In dynamic multisector economies, the planner’s optimal capital allocation can serve to minimize the aggregate impact of shocks cascading through nonlinear production networks. We show analytically in a simplified model that, under complementarity and if risk aversion is not too low, (i) optimal capital allocation under uncertainty involves deliberately over-investing, relative to the deterministic optimum, in upstream sectors in order to mitigate severe economic downturns; (ii) this strategy can reduce the average level of consumption and give rise to a high welfare cost of business cycles. Deploying novel deep-learning techniques in a general environment, we show quantitatively that: (iii) the ergodic distribution of the simulated nonlinear economy features higher mean capital levels in key upstream sectors, lower mean levels of macroeconomic aggregates, realistic aggregate volatility, and a welfare cost of business cycles two orders of magnitude larger than in standard one-sector models.

Keywords: deep learning; production network; nonlinear propagation (search for similar items in EconPapers)
JEL-codes: C63 C67 E32 (search for similar items in EconPapers)
Date: 2026
New Economics Papers: this item is included in nep-dge
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