Industrial development in Malaysia and Singapore: Empirical analysis with multiple‐cone Heckscher–Ohlin Model

• Author: Yasuhiro Doi,Kensuke Suzuki
• DOI: http://doi.org/10.1111/rode.12595
• Published date: 01 August 2019
• Date: 01 August 2019

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wileyonlinelibrary.com/journal/rode Rev Dev Econ. 2019;23:1414–1431.

© 2019 John Wiley & Sons Ltd

DOI: 10.1111/rode.12595

REGULAR ARTICLE

Industrial development in Malaysia and Singapore:

Empirical analysis with multiple‐cone Heckscher–

Ohlin Model

KensukeSuzuki1

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YasuhiroDoi2

1Department of Economics,Pennsylvania

State University

2Graduate School of Economics,Nagoya

University

Correspondence

Kensuke Suzuki, 303 Kern Graduate

Building, University Park, PA 16802, USA.

Email: kxs974@psu.edu

Funding information

Japan Society for the Promotion of Science,

Grant/Award Number: JP15J01682 and

JP16K03620

Abstract

This paper employs the multiple‐cone Heckscher–Ohlin

model to analyze industrial development in Malaysia and

Singapore. In particular, we focus on industrial upgrading

along with capital accumulation as a key determinant for the

cross‐country difference in production technology and in-

come. By pooling two countries’ data on factor endowment

and sectoral output in manufacturing from 1990 to 2008, we

estimate the common industrial development paths of the

two‐cone Heckscher–Ohlin model, the Rybczynski linear

relationship between capital–labor ratio and sectoral out-

put per capita. Our results demonstrate that, after control-

ling for quality of workers (by educational attainment), the

two countries resided in different cones during our sample

period, implying that Singapore succeeded in accumulating

capital steadily with the support of foreign investment and

upgrading its industry mix to make it more capital‐intensive.

The separation of cones is also consistent with the observed

gap in gross domestic product per capita between the two

countries. Furthermore, we implement a factor‐augmenting

productivity test to see the gaps in efficiency of capital and

human‐capital‐augmented labor and confirm no significant

difference between the two countries.

KEYWORDS

Industrial development, Multiple‐cone Heckscher‐Ohlin model

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INTRODUCTION

What makes one country more developed and another country less developed? Cross‐country differ-

ences in production technology and income are an important topic in the literature of development

economics and international trade. This paper focuses on industrial upgrading along with capital ac-

cumulation as a key determinant for a country’s economic development. In doing so, we propose to

employ the multiple‐cone version of the Heckscher–Ohlin (HO) model to investigate the industrial

development of a set of countries which have an intimate economic relationship. One of the striking

features of the multiple‐cone HO model is that a country specializes in the set of industries which best

fit its relative factor endowment. This allows for countries to have different sets of goods produced

and factor prices depending on the countries’ capital–labor ratio. In the dynamic context, the multi-

ple‐cone equilibrium can describe the industrial upgrading process: the set of industries a country

specializes in becomes more capital‐intensive as capital accumulates. In other words, there exists a

series of industries which appear, prosper, decline, and finally disappear in succession. We refer to

the industrial upgrading process as the industrial development paths à la Kiyota (2014). In this frame-

work, whether a country can accumulate capital relative to labor and upgrade its industry mix is the

key determinant of cross‐country differences in industrial development.

With this emphasis, this paper analyzes the industrial development of Singapore and Malaysia.

In particular, we assume that the two countries have primitives of the multiple‐cone HO model (pro-

duction functions and commodities prices determined in the world market) in common so that they

follow a set of industrial development paths. There are several facts motivating the analysis of the two

countries’ economic development through the lens of the HO framework. First of all, the two coun-

tries were a single country, the Federation of Malaya, until 1965. Despite the same departure point,

the two countries have revealed distinct patterns of economic development in the past several decades.

In 2008, gross domestic product per capita in Malaysia (US$35,600) was 44% of that in Singapore

($81,508). One of the underlying reasons for this gap is the two countries’ different economic policies

for foreign investment. Because of its small market size and scarcity of major productive resources,

Singapore has been aiming since the 1960s to foster industries with high productivity by attracting

investment from overseas. In Malaysia, conversely, a low‐cost export‐oriented industrial strategy

paid rich dividends until the late 1980s. Keen competition from low‐cost producers in neighboring

countries motivated the Malaysian government to shift from its primary industrial strategy. However,

action by the Malaysian government to attract foreign investment has not been as effective as it has

been in Singapore. The steady capital accumulation supported by foreign investment in Singapore

may account for the faster economic growth, behind which there is an industrial upgrading process.

The other important observation is the economic interdependence between these two trade part-

ners, promoted in the 1990s by the Association of Southeast Asian Nations free trade agreement (the

ASEAN Free Trade Area). Their membership of the ASEAN Free Trade Area favors the HO frame-

work, which assumes frictionless trade among countries.

By pooling the data on factor endowments and sectoral output of the two countries from 1990 to

2008, we estimate a single set of industrial development paths for the two‐factor (capital and labor),

three‐good HO model featuring the two cones of diversification. We set the number of cones to two,

given that previous studies (Kiyota, 2011, 2014; Schott, 2003) have found empirical evidence of

JEL CLASSIFICATION

F11; F14; F43; C33