Facts of US Firm Scale and Growth 1970-2019: An Illustrated Guide

TL;DR

This paper provides a comprehensive analysis of US public firms from 1970 to 2019, revealing key distributional patterns and scale effects in firm data, with implications for understanding firm dynamics and heterogeneity.

Contribution

It introduces detailed stylized facts about firm scale, growth, and income, emphasizing the role of the Difference-of-Log-Normals distribution and scale-dependent heteroskedasticity.

Findings

DLN distribution describes firm data well

Small firms differ systematically from large firms

Scale effects influence firm heteroskedasticity

Abstract

This work analyzes data on all public US firms in the 50 year period 1970-2019, and presents 18 stylized facts of their scale, income, growth, return, investment, and dynamism. Special attention is given to (i) identifying distributional forms; and (ii) scale effects -- systematic difference between firms based on their scale of operations. Notable findings are that the Difference-of-Log-Normals (DLN) distribution has a central role in describing firm data, scale-dependent heteroskedasticity is rampant, and small firms are systematically different from large firms.