Productivity propagation with networks transformation

TL;DR

This paper models sectoral production as a hierarchical network process, analyzing how productivity shocks propagate through the economy and how network transformations influence macroeconomic fluctuations and social benefits.

Contribution

It introduces a novel hierarchical network model of production with self-similar structures and measures substitution elasticities and productivity growth to analyze shock propagation.

Findings

Sectoral productivity shocks propagate through the network affecting macroeconomic fluctuations.

Network transformations significantly influence the transmission of productivity increments.

The model demonstrates how sectoral productivity improvements can lead to social benefits.

Abstract

We model sectoral production by cascading binary compounding processes. The sequence of processes is discovered in a self-similar hierarchical structure stylized in the economy-wide networks of production. Nested substitution elasticities and Hicks-neutral productivity growth are measured such that the general equilibrium feedbacks between all sectoral unit cost functions replicate the transformation of networks observed as a set of two temporally distant input-output coefficient matrices. We examine this system of unit cost functions to determine how idiosyncratic sectoral productivity shocks propagate into aggregate macroeconomic fluctuations in light of potential network transformation. Additionally, we study how sectoral productivity increments propagate into the dynamic general equilibrium, thereby allowing network transformation and ultimately producing social benefits.