Empirical research on the different innovation engine between China and US manufacturing using an improved method
Yu Li,
Peipei Mao and
Yanming Zhang
Applied Economics, 2016, vol. 48, issue 6, 471-482
Abstract:
Most studies arrive at controversial conclusions about the relationship between firm size and technological innovation. Industrial differences and subjective model design are generally considered the primary cause. In static comparisons across industries, dynamic industrial changes are ignored, but this might lead to differing results when attempting to identify the driving forces of evolutionary change in an industrial environment. This study applies nonparametric regression methods with an expansive industry grouping to overcome the industry-difference interference and empirical model error, typifying traditional studies. First, a comparative analysis of the forces driving US and Chinese manufacturing is performed. Results indicate that US and Chinese manufacturing are in different industrial growth stages. Chinese manufacturing takes the traditional elements and R&D input as its main driving factors, which require objectively, expansive scale of enterprise, therefore showing characteristic Schumpeterian innovation. US manufacturing is driven by both R&D and non-R&D inputs; so it can maintain continuous innovation through cooperative networks under conditions of constant or contracting firm size.
Date: 2016
References: View complete reference list from CitEc
Citations: View citations in EconPapers (3)
Downloads: (external link)
http://hdl.handle.net/10.1080/00036846.2015.1083083 (text/html)
Access to full text is restricted to subscribers.
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:taf:applec:v:48:y:2016:i:6:p:471-482
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/RAEC20
DOI: 10.1080/00036846.2015.1083083
Access Statistics for this article
Applied Economics is currently edited by Anita Phillips
More articles in Applied Economics from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().