# Structural propagation in a production network with restoring substitution elasticities

## TL;DR

This paper models an economy-wide production network using cascading functions and hierarchical clustering to analyze how productivity shocks propagate through the network structure.

## Contribution

It introduces a novel modeling approach that captures intra-sectoral processes and restores elasticities, accurately replicating observed price and input share data over time.

## Key findings

- The model replicates multi-sectoral price and share data accurately.
- Hierarchical clustering reveals how productivity shocks propagate.
- The approach links network structure to economic dynamics.

## Abstract

We model an economy-wide production network by cascading binary compounding functions, based on the sequential processing nature of the production activities. As we observe a hierarchy among the intermediate processes spanning the empirical input--output transactions, we utilize a stylized sequence of processes for modeling the intra-sectoral production activities. Under the productivity growth that we measure jointly with the state-restoring elasticity parameters for each sectoral activity, the network of production completely replicates the records of multi-sectoral general equilibrium prices and shares for all factor inputs observed in two temporally distant states. Thereupon, we study propagation of a small exogenous productivity shock onto the structure of production networks by way of hierarchical clustering.