Persistence in firm growth: Inference from conditional quantile transition matrices - Giulio Bottazzi; Taewon Kang; Federico Tamagni (Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM), 2022)
We propose a new methodology to assess the degree of persistence in firm growth, based on Conditional Quantile Transition Probability Matrices (CQTPMs) and well-known indexes of intra-distributional mobility. Improving upon previous studies, the method allows for exact statistical inference about TPMs properties, at the same time controlling for spurious sources of persistence due to confounding factors such as firm size, and sector-, country- and time-effects. We apply our methodology to study manufacturing firms in the UK and four major European economies over the period 2010-2017. The findings reveal that, despite we reject the null of fully independent firm growth process, growth patterns display considerable turbulence and large bouncing effects. We also document that productivity, openness to trade, and business dynamism are the primary sources of firm growth persistence across sectors. Our approach is flexible and suitable to wide applicability in firm empirics, beyond firm growth studies, as a tool to examine persistence in other dimensions of firm performance.
Keywords: C14; D22; L25; 330; Firm growth persistence; Transition probability matrices; Mobility indexes; Non-parametric statistics