Industry Aware Firm Level Network Reconstruction

TL;DR

This paper enhances firm-level network reconstruction by integrating sectoral input-output data, significantly improving the accuracy of the reconstructed production networks compared to standard methods.

Contribution

It introduces a novel reconstruction approach that incorporates input-output sectoral flows into the maximum entropy framework, improving network accuracy.

Findings

Input-output constraints greatly improve network reconstruction accuracy.

The augmented method nearly perfectly fits input-output data.

All methods struggle to reproduce other structural features.

Abstract

A number of recent contributions have put forward the topological structure of production networks as a key determinant of macro-economic dynamics. However, firm-to-firm production networks data is generally not available. Against this background, reconstruction method based on firms' size have been developed. This paper enriches this set of reconstruction methods by integrating input-output sectoral flows in the reconstruction process. We derive analytical expressions for the maximum entropy solutions to the firm network reconstruction problem with sectoral input-output constraints, first for binary networks and then for weight reconstruction. We perform a numerical analysis comparing standard and input-output based reconstruction methods using Hungarian production network data. Our results show that adding input-output constraints substantially reduces deviations from the input-output structure compared with standard methods. Our augmented method provides an almost perfect fit to input-output data, though all methods have difficulties reproducing other structural characteristics.