Clustering effects on firm exporting with productivity‐enhancing R&D in China

• Author: Anthony Howell
• Date: 01 November 2019
• Published date: 01 November 2019
• DOI: http://doi.org/10.1111/twec.12834

3168

|

wileyonlinelibrary.com/journal/twec World Econ. 2019;42:3168–3187.

© 2019 John Wiley & Sons Ltd

Received: 2 October 2017

|

Revised: 10 April 2019

|

Accepted: 2 June 2019

DOI: 10.1111/twec.12834

ORIGINAL ARTICLE

Clustering effects on firm exporting with

productivity‐enhancing R&D in China

AnthonyHowell

School of Public Affairs,Arizona State University, Phoenix, Arizona

Funding information

This project received funding support from the Natural Science Foundation of China No. 71603009.

KEYWORDS

China, exporting, productivity, R&D, regional clusters

1

|

INTRODUCTION

China emerged as the world's number one exporter in 2009, increasing its share of global manufac-

turing exports to 13%, up from just 2% in 1990. It is no secret that China's export‐led growth strategy

led in large part to its unprecedented growth miracle of nearly double‐digit growth for a quarter of a

century. Following the aftermath of the financial crisis, however, China began to shift away from its

traditional export‐led growth strategy towards an innovation‐led, service‐based economy. Despite this

shift, maintaining international competitiveness in manufacturing is an important driver of aggregate

country growth and remains an important goal for Chinese officials.

A variety of challenges threaten to undermine China's competitiveness on the international market,

however. One well‐known challenge is the lack of financial development across China, which makes it

difficult for firms to overcome the high initial sunk costs of entering and remaining in foreign markets

(Long & Zhang, 2011). A more recent challenge is the rapid increase in China's labour costs, driven in

part, by large and substantial increases in the minimum wage, which has been shown to have a small

but negative effect on the exporting performance of Chinese firms (Gan, Hernandez, & Ma, 2016).

In the light of these challenges, and others, policymakers and academics alike are turning in earnest

to the potential role that clustering can have on helping to promote China's regional and international

competitiveness. In recent years, China has spent billions of dollars on cluster‐based policies to build

new industrial zones. The unveiling of the ‘new urbanization plan’ (2014–20), for instance, demon-

strates the Chinese government's commitment to re‐orient the spatial economy by building a massive

network of clusters unprecedented in scale spread out across coastal and central parts of China.

A timely and critical concern that naturally arises is to what extent regional clustering can help

Chinese firms to achieve and maintain international competitiveness. In theory, the ability to contain

|

3169

HOWELL

competitive advantages in a global economy lies, somewhat paradoxically, in location‐specific ad-

vantages that distant rivals cannot match (Porter, 1990). In particular, the firm may benefit from the

knowledge produced by other local firms that arise from agglomeration economies, and it is well‐

known that such knowledge spillovers tend to be highly geographically concentrated due to the ‘tacit’

nature of knowledge (Audretsch & Feldman, 1996).

The benefits of local clusters may therefore help to reduce firms' financial and technological lim-

itations of attempting to produce new knowledge solely based on in‐house innovation, which, in turn,

can affect exporting performance (Greenaway & Kneller, 2007), as well as overall economic perfor-

mance (Krugman, 1991). Existing studies of China tend to confirm theoretical expectations by show-

ing that regional clustering improves the exporting performance of Chinese firms (Long & Zhang,

2011); however, these studies typically do not take into account differences in firms' productivity. This

omission is most likely due to the notorious difficulties in controlling for differences in productivity

when estimating the effects of clustering on firms' exporting performance due to the bi‐causal rela-

tionship between productivity and exporting.

In a relevant and recent strand of the trade literature, several studies do attempt to endogenize firm‐

level productivity by allowing for the possibility that firms can influence their own efficiency level via

investments in innovation (Bustos, 2011; Yeaple, 2005). Aw, Roberts, and Xu (2011) develop a struc-

tural framework to simultaneously estimate the linkages between R&D, exporting and productivity

(REP), and find that R&D and exporting jointly increase productivity. Related studies offer additional

empirical evidence for the complementarity between productivity‐enhancing investment activities and

exporting (Harris & Li, 2008; Lileeva & Trefler, 2010).

Paramount to the purposes of this paper, however, the existing REP studies tend to focus exclu-

sively on firms' in‐house innovation investments. This exclusive focus on knowledge accumulation

internal to the firm ignores the potential role of regional clusters and the presence of location‐binding

specific resources generated external to the firm. That is, none of the REP studies, at least to the au-

thor's knowledge, take into account firms' attempts to improve its productivity by simultaneously in-

vesting in in‐house R&D activities and searching the local environment for external knowledge inputs.

Drawing from the above discussion, this paper explores the potential role of cluster benefits or

externalities within a REP structural framework applied to the Chinese context. The REP structural

approach relies on a set of recursive equations linking firms' R&D, exports and productivity using

a structural equation model approach that is capable of controlling for most of the identification

problems, including endogeneity and the discrete nature of some of the variables. In this case, the

definition of regional clustering draws on the definition in Porter (2000), which emphasises inter-

connectedness of clustered firms. Specifically, I calculate a measure of product relatedness defined

at the municipal level and incorporate the relatedness proxy into each stage of the REP framework

to capture externalities arising from spillovers expected to take place between related industries (and

their participating firms).

This paper contributes to the empirical trade and agglomeration literature by studying how re-

gional clustering influences firms' international competitiveness after, respectively, controlling for

differences in productivity and efforts to expand internal capabilities via innovation investments in

R&D. Moreover, as in the existing REP studies, the structural framework also lends itself to testing

multiple key hypotheses in the empirical trade literature: (a) exporting by innovating; (b) innovating

by exporting; (c) self‐selection into exporting; and (d) learning by exporting.

The outline of the paper is as follows. The subsequent section introduces the relevant literature.

Section 3 introduces the data and variable development. Section 4 describes the econometric frame-

work. Section 5 presents the main results and checks for robustness. Section 6 concludes.