Planning Against Disasters in Dynamic Production Networks

Vasco M. Carvalho, Matias Covarrubias and Galo Nuñoc

Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge

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 Networks; Nonlinearities (search for similar items in EconPapers)
JEL-codes: C63 C67 E22 E32 (search for similar items in EconPapers)
Date: 2026-07-06
References: Add references at CitEc
Citations:

Downloads: (external link)
https://www.econ.cam.ac.uk/sites/default/files/pub ... pe-pdfs/cwpe2650.pdf

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:cam:camdae:2650

Access Statistics for this paper

More papers in Cambridge Working Papers in Economics from Faculty of Economics, University of Cambridge
Bibliographic data for series maintained by Jake Dyer ().