Seminario Navigating Supply Shocks: Sector Resilience and Production Prices through Stochastic Input-Output Modeling

Abstract

This study develops a novel multivariate stochastic framework for assessing systemic risks, such as climate and nature-related shocks, within production or financial networks. By embedding a linear stochastic fluid network, interpretable as a generalized vector Ornstein-Uhlenbeck process, into the {production network} of interdependent industries, the model captures how physical shocks (e.g., extreme climate events or geopolitical disruptions) propagate through input-output (IO) linkages and affect sectoral price dynamics. The framework extends traditional IO models with advanced stochastic and dynamic features, enabling a quantification of both direct and indirect transmission channels of supply-cost shocks to production prices.
Contributing to the literature on stochastic IO and Markovian networks, the model introduces the concept of divisible shocks, allowing for finer-grained simulation of adaptation responses and resilience across sectors. Empirical calibration leverages real-world economic data, including IO tables and historical industrial price indices. Sensitivity analyses are conducted using distributional risk measures, offering new tools for climate stress testing and medium to long-term risk assessment.
Our findings support the optimal design of supply risk management strategies, including policy interventions and decentralized adaptation incentives for systemic stability under environmental stress.

In collaborazione con:

Giovanni Amici, Department of Industrial and Systems Engineering, North Carolina State University gamici@ncsu.edu

Anna Maria Gambaro, Dipartimento di Studi per l'Economia e l'Impresa, Università del Piemonte Orientale annamaria.gambaro@uniupo.it

Daniele Marazzina Department of Mathematics, Politecnico di Milano. daniele.marazzina@polimi.it