Quantifying heterogeneity in the relationship between R&D intensity and growth at innovative Japanese firms: A quantile regression approach

Galina Besstremyannaya, Richard Dasher () and Sergei Golovan ()
Additional contact information
Richard Dasher: Stanford University, Stanford, US
Sergei Golovan: New Economic School, Moscow

Applied Econometrics, 2022, vol. 67, 27-45

Abstract: This paper focuses on innovative manufacturing firms in Japan in 2009–2020 and evaluates differences in the relationship between R&D intensity and firm growth. We use a longitudinal version of the conditional quantile regression model to estimate the augmented Gibrat’s law equation for each of four innovative industries: chemicals and allied products; electronic and other electrical equipment; industrial and commercial machinery and computer equipment; and transportation equipment. The analysis reveals statistical differences in estimated coefficients for R&D intensity across low, median and high-growth firms within each industry and across pairs of industries. The results imply the presence of different patterns of R&D effectiveness which are discussed in the light of R&D management drawing on the experience of Sony and other fast-growing Japanese electronics firms. We also discover heterogeneity in the impact on growth of the age and size of firms.

Keywords: quantile regression; panel data; firm growth; innovation; R&D intensity. (search for similar items in EconPapers)
JEL-codes: C21 C22 D22 D24 O32 O47 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://pe.cemi.rssi.ru/pe_2022_67_027-045.pdf Full text (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ris:apltrx:0451

Access Statistics for this article

Applied Econometrics is currently edited by Anatoly Peresetsky

More articles in Applied Econometrics from Russian Presidential Academy of National Economy and Public Administration (RANEPA)
Bibliographic data for series maintained by Anatoly Peresetsky ().