Arbeitspapier

Persistence in firm growth: Inference from conditional quantile transition matrices

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.

Sprache
Englisch

Erschienen in
Series: LEM Working Paper Series ; No. 2022/27

Klassifikation
Wirtschaft
Semiparametric and Nonparametric Methods: General
Firm Behavior: Empirical Analysis
Firm Performance: Size, Diversification, and Scope
Thema
Firm growth persistence
Transition probability matrices
Mobility indexes
Non-parametric statistics

Ereignis
Geistige Schöpfung
(wer)
Bottazzi, Giulio
Kang, Taewon
Tamagni, Federico
Ereignis
Veröffentlichung
(wer)
Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM)
(wo)
Pisa
(wann)
2022

Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Arbeitspapier

Beteiligte

  • Bottazzi, Giulio
  • Kang, Taewon
  • Tamagni, Federico
  • Scuola Superiore Sant'Anna, Laboratory of Economics and Management (LEM)

Entstanden

  • 2022

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