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 that (i) optimal capital allocation under uncertainty involves deliberately over-investing in upstream sectors in order to mitigate severe economic downturns; (ii) this efficient strategy reduces the average level of consumption and gives 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 one order of magnitude larger than in standard linear models.

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