Strategy for Cluster-Based Industrial Development in Developing
Countries
Keijiro Otsuka
October, 2020
Discussion Paper No.2019

GRADUATE SCHOOL OF ECONOMICS
KOBE UNIVERSITYROKKO, KOBE, JAPANStrategy for Cluster-Based Industrial
Development in Developing Countries
Keijiro Otsuka
Kobe University and JETRO-Institute of Developing Economies(Presidential Address for the Japanese Association for Development Economics,
November 14, 2020)

Draft: October 29, 2020

Abstract
Discussions on industrial policy are back on the scene primarily because of the failureof the Washington Consensus as a development strategy. Having emerged is a newconsensus that the industrial policy should address market failures while pursuing
comparative advantage. However, it is unclear where markets fail, how market failures
can be corrected, and whether governments can identify them. In the literature, credit
provision, management training, and information externalities arising from industrial
clusters and foreign direct investment are discussed separately as means to promoteindustrial development. This study proposes a strategy for cluster-based industrial
development based on a comprehensive review of the relevant literature.

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Introduction
Renewed interest in industrial policy has been emerging because of the failure of the
Washington Consensus, which advocates liberalization and privatization of thedeveloping economy, as a development strategy. The new consensus is that industrial
policy ought to address market failures and target the development of industries thathave a comparative advantage (e.g., Rodrik 2004; Lin 2012; Nathan and Overman
2013; Stiglitz et al. 2013; Calcagno et al. 2015; Noman and Stiglitz 2017; Higuchi and
Shimada 2019; Aiginger and Rodrik 2020; Asian Development Bank 2020; FernándexArias, Hausmann, and Panizza 2020). Surprisingly, it took more than a few decades
to arrive at this new consensus because it is nothing more than the firmly establishedthrust of microeconomics.

The real questions are where markets fail and in what industries the comparativeadvantage resides. The related question is whether the government possesses theability to identify market failures and promising industries. Rodrik (2004, p. 3) argues
that “the task of industrial policy is as much about eliciting information on significant
externalities and their remedies from the private sector as it is implementing
appropriate policies.” This is what the South Korean government did to promoteindustrial development, according to Pack and Westphal (1986). On the other hand,
Fernándex-Arias, Hausmann, and Panizza (2020) contend that market failures are socomplex that policymakers do not know where markets fail. They advocate theestablishment of national development banks staffed with experts of economics
capable of designing effective development policies while paying attention to positive
externalities.

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My view is that it is the role of development economists to identify market failures andprovide appropriate policy recommendations for industrial development,1 possibly incollaboration with the private sector. In fact, there is voluminous literature indevelopment economics concerned with failures of credit markets as well as markets
providing management skills and positive externalities arising from the formation ofindustrial clusters and foreign direct investment. For instance, a large number ofexperimental studies examined the impact of credit on the performance of
microenterprises (e.g., Banerjee et al. 2017; Fiala 2018), and many experimental
studies have evaluated the impact of management training of entrepreneurs on theperformance of their enterprises (e.g., McKenzie and Woodruff 2014; McKenzie 2020).
Information externalities, particularly those arising from clustered enterprises, global
buyers, and subsidiaries of foreign multinational companies (MNCs), have also been
extensively analyzed (e.g., Sonobe and Otsuka 2006, 2011, 2014; Murakami andOtsuka 2020). In other words, development economists have already been analyzing
market failures in developing economies.

The problem is that these strands of economic analyses have been carried out
independently and separately. Thus, we do not know whether credit and management
skills are complementary and which policy should be implemented first, subsidized
credit or management training.2 Furthermore, although it is well-known that innovation
is an engine of economic development,3 these studies, in general, do not pay attention

1 In this article, I do not cover “industrial clusters for agro-processing,” because there are additional issues related

to the development of agriculture. See Otsuka and Ali (2020) for a discussion on the development of agrobased clusters.
2 Giné and Mansuri (2020), however, attempted to analyze this issue without notable success.
3 Innovation here does not necessarily refer to big change leading to constructive destruction as envisaged by

Schumpeter (1934). It is defined to be new change leading to improvement of production efficiency.

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to relationships between innovation and credit or management skills. While learningfrom abroad is known to be a significant source of innovations in the process of
miraculous development of East Asian countries (e.g., Pack and Westphal 1986;
Amsden 1989; Wade 1990a, 1990b; Hobday 1995; Sonobe and Otsuka 2006), suchaspect of innovation has seldom been taken into consideration in the recent
development economics literature.

This article attempts to propose an effective strategy for cluster-based industrial
development based on a comprehensive literature review. I use the term strategy
rather than policy because I would like to propose industry-specific policies targeting
particular industries, rather than a comprehensive package of industrial policies
encompassing not only industry-specific policies but also macro policies and functional
policies affecting many industries.4 I emphasize cluster-based industrialization rather
than industrialization because industrial clusters’ development ought to play a central
role in industrialization in developing countries for a number of reasons that will be
discussed in this article. I do not deny, however, the importance of all-encompassing
industrial policies. I focus on narrowly defined targeted policies primarily because richand useful empirical evidence is available for formulating such policies. Specifically, I
would like to support the development of existing industrial clusters in developing
countries by investing in entrepreneurs’ managerial human capital and promoting
subcontracting and other contractual relationships between foreign and local
enterprises.

4 Stiglitz et al. (2013) and Noman and Stiglitz (2017) argue that industrial policy refers to public policy measures

aimed at influencing the sectoral allocation and accumulation of resources and choice of technologies.

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The structure of this article is as follows. While Section 2 discusses the nature ofmarket failures in industrial clusters, Section 3 explores how to identify promisingindustries with comparative advantage. Section 4 reviews the literature on the impactsof credit provision, including microcredit and management training on enterprise
performance. Section 5 considers the role of foreign direct investment in thedevelopment of local industries. Finally, I would like to conclude the paper by offering
several strategies that are expected to be conducive to industrial development indeveloping countries.

Market Failures and Industrial Clusters
More often than not, manufacturing industries are clustered both historically andcurrently in developed and developing countries. Hashino and Otsuka (2016) reportthat many industries are clustered in modern Japan, postwar Europe, and many
contemporary developing countries. While Long and Zhang (2011) argue thatindustrial development in China is cluster-based, particularly in Zhejiang province
where rapid industrialization was led by small- and medium-sized private enterprises(SMEs), Hobday (1995) points out that a major characteristic of manufacturingindustries in Taipei, China is the overwhelming dominance of industrial clusters
consisting of SMEs. Industrial clusters are also ubiquitous even in sub-Saharan Africa
in such industries as apparel, footwear, metal products, and furniture (e.g., Sonobe
and Otsuka 2011, 2014). These industries are common and typically run bymicroenterprises in low-income economies (Tybout 2000).

Sonobe and Otsuka (2006, p. 4) define “an industrial cluster as the geographicalconcentration or localization of enterprises producing similar or closely-related

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products in a small area,” which is a fairly representative definition of industrial cluster.
On the other hand, Porter (1990) defines a cluster as the geographic concentration ofinterconnected companies, specialized suppliers, firms in related industries, andassociated institutions (e.g., universities, standards agencies, and trade associations).
A significant difference between the two definitions is the inclusion of the associatedinstitutions in the latter. Such institutions emerge in the process of the successful
development of industrial clusters (Hashino and Otsuka 2016). Hence, Porter’s
definition is generally applicable for successfully developed, mature industrial clusters
in developed countries. Such institutions, however, should not be included in thedefinition when we analyze industrial clusters in developing countries where they
seldom exist.

Manufacturing enterprises tend to be clustered because of the agglomeration of
economies. According to Marshall (1920), there are three advantages of industrial
clusters: (1) the specialization and division of labor among enterprises, (2) the
development of skilled labor markets, and (3) information or knowledge spillovers
among clustered enterprises. 5 Such agglomeration economies arise from lowtransaction costs due to the geographical proximity of enterprises. In other words, theindustrial cluster is an artificially-created institution to reduce transaction costs so as
to mitigate market failures, particularly in markets of intermediary inputs and labor.
Such markets improve resource allocation and guide appropriate technology choice
and development by providing appropriate price signals.

5 Recently Greenstone, Hornbeck, and Moretti (2010) describe agglomeration economies differently but its

essence is no different from Marshall’s.

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Information spillover, which is basically imitation through visual observation, reverse
engineering, spin-offs of workers, and poaching of skilled engineers and managers
from other enterprises, is also very important in industrial clusters. According to
Audretsch and Feldman (1996), knowledge-intensive industries tend to be clusteredin the United States (US). However, in developing countries, labor-intensive industries
are also clustered (e.g., Sonobe and Otsuka 2006, 2011, 2014). Sonobe and Otsuka
also point out, based on roughly 20 case studies conducted in Asia and Africa, that theformation of an industrial cluster is led, without exception, by spin-offs of workers whoestablish new enterprises producing the same products as those produced by theirformer employers, using the same technologies, and selling them in the same market.
This is prima facie evidence that information spillovers are prevalent in industrial
clusters. Greenstone, Hornbeck, and Moretti (2010) observed substantial increases intotal factor productivity among incumbent plants following the opening of large plants,
particularly in areas in the US where similar technologies are adopted.

Given innovative ideas, knowledge spillovers enhance the production efficiency ofboth existing and those that have just entered a cluster. Simply put, firms’ productivity
in an industrial cluster is a function of the density of economic activity (Kline and Moretti
2014a). Knowledge spillovers, however, reduce incentives to innovate by creating the
gap between private and social benefits. Bloom, Reenen, and Williams (2019, p.166)
rightly point out that “knowledge spillovers are the central market failure.” If this is thecase, as it certainly is, the industrial cluster reduces failures in a few markets but
creates failure in the knowledge market. This is why collective action is needed tointernalize the externality associated with information spillovers. In fact, tradeassociations, particularly in successfully growing clusters, play a critical role in7

introducing new ideas from other areas, providing training to member enterprises todisseminate them, and enforcing quality standards to maintain a cluster’s reputation
as a producer of decent products. 6 If trade associations do not work or work only
nominally, policy interventions to support the generation and dissemination of
innovations can be justified. In the case of Japan in the early twentieth-th century, thegovernment advised local trade associations, which were spontaneously establishedprimarily in industrial clusters, to set up training schools and experimental and testingstations, and responded to the request for assistance by sending officials andengineers (Sugihara 1994). In Silicon Valley, fierce competition for innovation led tocooperation and the sharing of knowledge among competing firms for collective
benefits (Boldrin and Levine 2008).

Indeed, economic geographers argue that the presence of agglomeration economies
can justify the implementation of place-based policies (Glaeser and Gottlieb 2008).
While place-based policies are likely to be welfare-enhancing for the target
community, they may be welfare-reducing for the nation as a whole because of theeconomic losses associated with the geographical diversion of economic activities
and resources (Kline and Moretti 2014a).7 However, this is unlikely to be the case forsupporting a particular industrial cluster in developing countries because competing
industrial clusters, from which laborers may move, are either absent or limited inthese countries. Thus, this study advocates policy support for developing industrial

6 See, for example, Nadvi (1999) for the case of a surgical instrument cluster in Pakistan, Schmitz and Musyck(1994) for the case of several industrial clusters in post-war Europe, Ruan and Zhang (2016) for the case of anumber of industrial clusters in Zhejiang Province in China, and Hashino (2016) for the case of silk-weaving
clusters in modern Japan.
7 There are empirical studies which confirm the positive effects of place-based policies in the US (e.g., Busso,

Gregory, and Kline 2013; Kline and Moretti 2014b).

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clusters by generating or importing useful new technologies and management
practices and providing management and technology training, which amounts tocorrecting the failure of “knowledge markets.”8Comparative Advantage, Target Industries,
and Technological Change
While it is not easy to identify market failures, it is more challenging to identify
industries with a comparative advantage because it depends on factor endowments
and a country’s technologies vis-à-vis that of many other countries. Therefore, it is aformidable task to identify a particular industry’s comparative advantage in a particularcountry. Emphasizing the importance of following the changing comparativeadvantage for developing economies to succeed in industrialization, Lin (2012) argues
that developing countries should target mature industries in countries with a similar
factor endowment that is not too far advanced compared with their own level of percapita income. According to Komiya (1988), the desired industries targeted by theJapanese government were those that had already been pursued by countries moreadvanced than Japan. Wade (1990b) suggests that following Japan’s experience, theIndustrial Development Bureau and its predecessor Industrial Development
Commission in Taipei, China in the 1960s assisted in establishing and developing
promising industries (i.e., plastics, rayon, cement, and fertilizer) and later supported
the electronics industry. Lin’s argument, therefore, would be consistent with industrial
policies in Japan and Taipei, China.

8 Support for industrial clusters is unpopular in developed countries, because declining clusters are often

supported without success (e.g., Martin, Mayer, and Mayneris 2011; Beason and Weinstein 1996).

9Rodrik (2004) argues that the government may not know what they do not know. Thus,
he argues that the right model of industrial policy is to facilitate strategic collaboration
between the private sector and the government to uncover where the most significant
obstacles to restructuring lie and what types of interventions are most likely to remove
them. Consistent with this argument, the South Korean government closely consulted
with the private sector in designing its industrial policy (e.g., Pack and Westphal 1986).
Suspecting governments’ inability to identify market failures and industries with thecomparative advantage, Fernándex-Arias, Hausmann, and Panizza (2020) advocate
the establishment of national development banks capable of carrying out industrial
policy effectively. According to them, a national development bank, whose staff include
professional analysts of the economy, has the advantage in identifying promising firms
and industries through loan screening and lending activities. I agree with them thatprofessional staff with proper knowledge of economics must design and implement aneffective industrial development policy.

It seems that Rodrik (2004) and Lin (2012), as well as Stiglitz et al. (2013), implicitly
assume that there are few industries in developing countries, particularly in subSaharan Africa. This is, however, not true. There are a large number of garment,
leather shoe, metalworking, fish canning, furniture, and food processing clusters in
sub-Saharan Africa (McCormick 1999; Akoten and Otsuka 2007; Galvez-Nogales
2010; Sonobe and Otsuka 2011, 2014; Mano et al. 2012, 2014; Higuchi, Mhede, andSonobe 2019). These industries are labor intensive and, hence, consistent with factor
endowments of low-income economies.

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Table 1 summarizes the basic characteristics of 17 industrial clusters in Asia and Africa
studied by Sonobe and Otsuka (2006, 2011, 2014). Some of the clusters are huge;
there are an estimated 900 small leather shoe enterprises with an average
employment of 10 workers in Addis Ababa in Ethiopia and 1,000 small metalworking
enterprises in Kumasi in Ghana. The founders of these clusters were mostly smallfamily enterprises, including former farmers and tailors. Gradually the clusters havebeen formed spontaneously by private enterprises without any or much government
support. This clearly supports the view that these clustered industries have acomparative advantage. Therefore, we strongly argue that the government should
target existing industrial clusters for development. Porter (2000) also argues that the
government should reinforce and build on established and emerging clusters rather
than attempt to create entirely new ones because new industries and new clusters
emerge from established ones as economies develop. This view is consistent withHidalgo et al.’s (2007) observation that new products gradually evolve from existingones rather than emerge from scratch.

Comparative advantage is strengthened and transformed with technological change
and changes in factor endowments over time. There is a broad agreement amongdevelopment economists that learning advanced technology and management fromabroad is critical to the catch-up growth of low-income economies (e.g., Mazzoleni and
Nelson 2006). Indeed, this view is supported by the development of Japan, South
Korea, and Taipei, China. The story of technological change based on learning fromabroad in the long-term process of economic development since the late 19th century
in Japan is well-known. The Japanese government sent hundreds of Japanese, manyof whom were recruited from local trade associations, to Europe and the US to learn

11western technology (Sugihara 1994). Japan also invited a large number of foreign
advisers and consultants (Odagiri and Goto 1996). Hobday (1995) argues that
although industrial structures are quite different between South Korea, which isdominated by large conglomerates or chaebol, and Taipei, China which relies on
SMEs, there are similarities in mechanisms for acquiring new foreign technology.
Hobday (1995) and Wade (1990a, 1990b) observed that local and foreign traders were
important technology conduits, as were the subsidiaries of MNCs, through theirsubcontracting arrangements, including training of local engineers and technicians.
Levy (1991) observed that Japanese traders supported the development of the
footwear industries in both Taipei, China and South Korea, and both countries sent
vast numbers of workers abroad for training (Amsden 1989; Wade 1990b). Amsden(1989) also points out that the star of technology transfer to South Korea was the shortterm independent consultants from Japan.9

Another common strategy for industrial development in Taipei, China and South Korea
is the institutionalization of technology imports. In Taipei, China the Electronics
Research and Service Organization, under the guidance of the Industrial Technology
Research Institute, for example, was given the responsibility of guiding thedevelopment of core technologies and new products and for training microelectronicengineers, some of whom moved to private industry and established spin-off
companies (Wade 1990a, 1990b). Wade (2015) argues that the Industrial
Development Bureau plays an extension role in Taipei, China similar to an agriculturalextension service. In other words, the introduction, assimilation, and diffusion of new

9 According to my ongoing research, a large number of Japanese private consultants contribute to theimprovement of technologies and management of local companies in the motorcycle and automobile
industries in Thailand as well as in India.

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foreign technologies were assisted by public organizations in Taipei, China. Similarly,
the South Korean government set up the Electronics and Telecommunications
Research Institute, which helped major conglomerates enter the telecommunicationsindustry, and the Korean Institute of Science and Technology to absorb and adapt
foreign technologies and to promote R&D in private firms (Amsden 1989; Hobday1995). Although it is not easy to quantify the impact of such government technology
policies on the development of industries in Taipei, China and South Korea, there isno question that governments of these two countries made serious efforts to nurture
promising industries with dynamically-growing comparative advantage by facilitating
learning technology from abroad.

To the best of my knowledge, the most spectacular example of the successful
development of industrial clusters based on learning from abroad is the case of thegarment industry in Bangladesh (Mottaleb and Sonobe 2011). When the Daewoo
company of South Korea planned to initiate garment production through a technology
agreement with a Bangladeshi company in 1979, there was no garment factory in the
country. Thus, Daewoo invited 130 newly-recruited employees to Korea for ninemonths of training on garment production, quality control, marketing, and so on.
Knowledge acquired by training was not company-specific but general for the garment
industry. After returning to Bangladesh, all of the trained workers quit in a few years,
either to initiate their own garment companies or to launch trading companies to assist
the procurement of materials and export of final products for new garment companies.
Approximately 4,000 garment enterprises with an average employment of 700 workers
operated in 2010, and they accounted for more than 80% of exports from this country.
The garment industry in Bangladesh would not have developed so dramatically without

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intensive learning of useful knowledge from South Korea. Another lesson we must
learn from the Bangladeshi experience is that the social benefit of training exceeds theprivate benefit because of the information spillovers brought about by the trained
workers who quit. Thus, no other foreign enterprises have followed the policy ofintensive training of employees abroad adopted by Daewoo, even though it resulted
in the dramatic development of Bangladesh’s garment industry.

To sum up, it makes sense to support the development of existing industrial clusters,
which are deemed consistent with the country’s comparative advantage, by enablingor facilitating the learning of new useful knowledge from abroad.

Impacts of Microfinance and Management Training
It is widely believed that credit markets do not function well because of the asymmetric
information, adverse selection, and moral hazard, coupled with the lack of collateral ofborrowers and high default costs associated with risky small businesses. Management
skills in developing countries are inadequate partly because their value tends to beunderestimated and partly because management training, such as an MBA program,is not practical. Access to credit and management skills, therefore, are widely
considered critical factors affecting manufacturing enterprises’ performance. To
assess the importance of credit and management skills in enterprise performance,
many randomized controlled trials (RCTs) have been conducted primarily for
microenterprises in developing countries. This section attempts to review briefly the
results of recent studies on the impacts of microfinance and management training to
draw implications for a strategy for cluster-based industrial development. Note,however, that only a small number of studies are concerned with management training

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in industrial clusters.10

Assessment of microfinance and credit provision
Reviewing the experimental studies of microfinance, Banerjee, Karlan, and Zinman(2015) argue that microcredit has modestly positive but not transformative effects on
business activities. Similarly, Banerjee et al. (2017) conclude that microcredit provision
has a modest impact on business activities, but there is very little evidence ofincreased consumption. These findings indicate that microfinance clients do not seemto be severely constrained by the lack of credit. In contrast, however, de Mel,McKenzie, and Woodruff (2008) and Fafchamps et al. (2014) found that the provisionof grants, particularly in-kind grants, to microenterprises had significant and large
impacts on the rate of return; 60% per year in Sri Lanka and 15% per month in Ghana.
These studies also found that grants had no or little effects on female-owned
businesses, particularly female-managed subsistence enterprises. Later Fiala (2018)
found that in Uganda, microcredit has no effects on business and household income
because of particularly weak effects among women.

The provision of credit does not have significant effects on women’s business activities
because they may not be major decision-makers or the most capable in managing
microenterprises, or their behaviors may be constrained by culture and tradition. Morerecently, Banerjee et al. (2019) discovered that although the provision of microcredit
to women had no effect on their microenterprise’s performance on average, it has

10 Ruan and Zhang (2009) demonstrate in the context of China that because of the fine division of labor among

enterprises in industrial clusters, each firm specializes in a narrow range of production processes, whichsaves working capital and initial fixed capital investment. Akoten, Sawada, and Otsuka (2006) find that accessto formal credit is not a decisive factor affecting the performance of microenterprises in the garment cluster in
Kenya, because of the development of informal credit markets within a cluster.

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positive and persistent effects on women already running a business, who must haveaccumulated business skills through experience. They conclude that heterogeneity inentrepreneurial ability is an essential factor affecting microcredit’s impact on businessactivities. Such a conclusion is consistent with the findings of Gindling and Newhouse(2014) that only a small portion of self-employed business people have the potential
to be successful. Thus, if possible, interventions, such as microcredit, should target
the minority of those who are self-employed but with high growth potential.

It appears that the provision of credit alone may not be sufficient to significantly
improve the performance of microenterprises unless entrepreneurs have the ability to
manage their businesses efficiently. We now turn to the role of managerial ability,
which has received considerable attention in the literature, particularly since the highly
stimulating paper by Bruhn, Karlan, and Schoar (2010).

Assessment of management training
The importance of management in enterprise performance was strongly suggested by
Bertland and Schoar (2003), who found that differences in management practices are
systematically related to differences in enterprise performance; by Bloom and van
Reenen (2010), who found that one crucial explanation for the large difference inproductivity between firms and countries is the variation in management practices; andby Bandiera et al. (2018) who found that the work hours of chief executive officers area critical determinant of enterprise performance. In addition, a review of studies on
small enterprises in several developing countries by McKenzie and Woodruff (2017)
found that variation in business practices explain much of the variation in sales, profit,
and total factor productivity. A pathbreaking study in this area is Giorcelli (2019), whofound that small-scale Italian manufacturers employing about 50 workers who were16

invited to the US to take management training under the Marshall Plan significantly
improved enterprise performance even 15 years after the program.11 Furthermore, hefound that management and new machines were complementary and that thoseenterprises which received only new machines without taking management training
improved their enterprise performance but only temporarily. He concludes that credit
access or access to new machines mattered only after enterprises improved their
management skills.

There is significant evidence based on the RCT that management training improves
not only the management practices (e.g., quality of products, inventory management,
sales, return on assets, and profit) but also the performance of small to medium
enterprises, in the cotton weaving plants in India (Bloom et al. 2013) and the
manufacturing, commerce, and service enterprises in Mexico (Bruhn, Karlan, andSchoar 2018). Furthermore, in conducting a resurvey of the same plants, Bloom et al.
(2020) found that the intervention generated persistent or long-term impacts on treatedplants in India. Bruhn, Karlan, and Schoar (2018) also found long-term impacts ofmanagement training on employment generation.

Results of management training for microenterprises with a few or no paid employees
seem puzzling. According to the survey of 13 RCT-based studies by McKenzie andWoodruff (2014), most studies found significant impacts of management training on
adopting improved management practices but did not find statistically significant
impacts on firm profitability. Another survey by McKenzie and Woodruff (2017), which

11 He used, as a control, a group of Italian entrepreneurs who were initially invited but their invitations were latercancelled due to a budget cut caused by the outbreak of the Korean War.

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includes non-RCT studies, basically supports their earlier findings. They also point out
that impacts on firm performance are small because the training programs achievechanges in management practices that are not large enough to translate into higher
enterprise performance. According to them, possible causes for such results may be(1) small sample size, (2) assessment of very short-run impacts, (3) large
heterogeneity of sample enterprises, (4) short training courses, and (5) focus on
microenterprises. These points are sensible, and I would like to add that because thesample enterprises in the existing studies belong to a variety of industries with different
requirements for efficient management and because the management of
microenterprises is not complex compared with SMEs with sizable numbers of
employed workers, it would be difficult to detect statistical differences in enterprise
performance between treated and controlled enterprises.

More recent RCT-based studies of management training by Karlan, Knight, and Udry
(2015) in Ghana; Lafortune, Riutort, and Tessada (2018) in Chile; Brooks, Donovan,
and Johnson (2018) in Kenya; Iacovone, Maloney, and McKenzie (2019) in Colombia;
and Giné and Mansuri (2020) in Pakistan tend to make similar findings,12 even thoughseveral new findings are made such as the effectiveness of the use of mentors andex-students and group training.

The lack of significant management training effects on enterprise performance may beinterpreted as showing that traditional management training does not work or does nothave large effects. However, McKenzie (2020) attributes this to low powers of

12 Sample enterprises of Iacovone, Maloney, and McKenzie (2019) are medium with the average employment of

58 workers, whereas those of the others are microenterprises. It must also be noted that Giné and Mansuri(2020) find significant impacts of management training on business income and household expenditures formale businessmen.

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statistical analyses; his meta-analysis demonstrates small but significant effects ofmanagement training on enterprise performance.

In my view, a major defect of management training studies is the lack of analysis of
information spillovers. The majority of sample enterprises are engaged in different
businesses, so that information spillover, if any, may not be substantial. Then, how can
we justify the provision of management training by the public sector from the social
point of view? Many entrepreneurs indeed underinvest in learning about improved
management practices because they are not aware of the real value of management
training (Bloom and van Reenen 2010; Bloom et al. 2013; Suzuki, Vu, and Sonobe
2014; Shimada and Sonobe 2018; Iacovone, Maloney, and McKenzie 2019). If so, thebest policy is to disseminate the right information but not offering subsidized
management training programs. Another shortcoming is the exclusive focus on
management without considering how improved management can facilitate
technological innovation. I believe that management training should be combined withtechnical training.

A few studies applied RCT to the management training of small enterprises, with an
employment size of 5–25 workers, in industrial clusters. These are in the metalworking
cluster in Ghana (Mano et al. 2012); garment and steel bar clusters in Vietnam(Higuchi, Nam, and Sonobe 2015); and garment cluster in Tanzania (Higuchi, Mhede,
and Sonobe 2019). The training programs commonly employ standardized methodsof business development training, such as the International Labour Organization’sStart/Improve Your Business program covering the areas of marketing, costing,record-keeping, and financial planning. Moreover, these training programs have also

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included quality control and production management called Kaizen or continuous
improvement, which used to be viewed as Japanese-style management but is now
considered a world standard. Kaizen is inexpensive and makes use of a commonsense approach focusing on waste reduction, including the elimination of inventory,
equalized work burdens of all workers in the same production line, quality
management, routinized machine maintenance, and maintenance of clean anduncluttered workspaces. 13 Kaizen experts are generally industrial engineers who
provide managerial knowledge and technological advice for the layout of productionlines, division of labor among shop-floor workers, and inventory management.
Although reliable statistics are unavailable, it is no exaggeration to argue that manylarge manufacturing enterprises in developing countries employ Kaizen (Kaplinsky
1994; Otsuka, Jin, and Sonobe 2018). Since information spillovers are prevalent within
an industrial cluster, the RCT studies would have suffered from information spillovers
from trainees to non-trainees, which dilutes the measured impacts of management
training. Yet, it is remarkable that some of these RCT studies find significant effects ofmanagement training on enterprise performance, even in the medium-run of a few
years after the training programs as Kaizen is designed to facilitate a continuous
improvement of management efficiency.14

If management training is used as an instrument to develop manufacturing industries,
it should be implemented in industrial clusters. A major challenge for empiricalresearchers is how to assess the impact of information spillovers from trainees to non-

13 Suzuki, Vu, and Sonobe (2014) and Shimada and Sonobe (2018) found that after Kaizen management

training, trainees became more willing to pay significantly larger amounts for training fees.
14 By applying the propensity score matching method, Mano et al. (2014) found significant effects of management

training, including Kaizen, on enterprise profit in the metalworking cluster in Nairobi.

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trainees within a cluster, rather than ignoring research on the impact of management
training in industrial clusters.

Role of Foreign Direct Investment
There have been many econometric studies on the impact of foreign direct investment
on the productivity of local firms (see Murakami and Otsuka [2020] for the most recent
literature review). Typically, total factor productivity of a local firm is regressed on (1)the presence of foreign firms in the same industry (e.g., measured by the share of
production) to determine the effect of horizontal linkage; (2) the extent of connection
with foreign firms in the upstream industries, also known as forward linkage; and (3)the extent of connection with foreign firms in the downstream industries, which isrelated to the effect of backward linkage. Roughly speaking, the horizontal linkage
effect is negative due to the loss of local firms’ market share, the forward linkage effectis small or negligible, and the backward linkage effect is positive and significant. Since
Javorcik’s (2004) pathbreaking study, many studies have found positive and significant
backward linkage effects. While the linkage effects may be closely related to theinformation spillovers, it may not necessarily be so because other channels affect theflow of useful information. In fact, one may wonder how the technology of downstream
foreign firms or their subsidiaries spills over to upstream local firms despite thedifference in products and technologies.

According to Table 1, the average size of enterprises in terms of the average numberof workers per enterprise is much larger in industrial clusters where foreign
enterprises, be it subsidiaries or joint ventures, operate. This includes the case of thegarment industry in Bangladesh. In contrast, the size of enterprises is generally

21

smaller in clusters where foreign enterprises do not operate. These observations
suggest that technology might have been transferred from foreign to local enterprises
in industrial clusters because of the ease of information spillovers.

As Hobday (1995) points out in the context of East Asia and from what I personallyobserved in Thailand, India, and South Africa, foreign subsidiaries, which are often
engaged in assembly, provide blueprints, technical advice, and training of engineers
to subcontracted local firms. Since the procurement of cheap and decent quality parts
and intermediary products is critically important for foreign subsidiaries, they haveclear incentives to transfer useful skills and know-how to the subcontracted local firms.
This is, however, not information spillovers but the market transaction of information.
Such technology transfer, however, is bound to fall short of the social optimum
because parts-supplying local firms do not work exclusively for the subcontractor andmay use acquired technology for purposes other than the delivery of parts andintermediate products to the subcontractors.

Technology may be transferred to local firms not only by foreign subsidiaries throughsubcontracting but also by global buyers (mostly large supermarkets in developed
countries) and foreign traders, and foreign manufacturers offering original equipment
manufacturer (OEM) contracts to local firms in which the former provide blueprints andtechnological advice to the latter to produce products of their brand, and own-design
manufacturing (ODM) in which local firms are also engaged in designing for the
products of foreign manufacturers. As was argued by Gereffi, Humphrey, and Sturgeon(2005), among others, global buyers may play a critical role in technology transfer in
the apparel and other light industries.

22Regardless of whether information spillovers or training and other conscious efforts totransfer technology are important, it is obvious that local firms’ absorptive capacity is
the key to transferring advanced technological and management information. The
point here is that so far as information spills over from foreign to local enterprises orfrom subcontracted local enterprises to others, the “information market” is bound to
fail. Thus, it must be the role of governments to invest in the transfer of valuable
information to entrepreneurs, managers, and industrial engineers through training inorder for local firms to receive greater benefits from foreign firms, traders, and buyers.

Strategy for Industrial Development
The efficiency of the economy improves primarily with (1) improved resource
allocation, (2) technological change, and (3) improvement of management skills or
accumulation of managerial human capital. I argued in this article that industrial
clusters contribute to improved resource allocation by reducing transaction costs andthereby facilitating market transactions. I also argued that because of information
spillovers, investments in new technology and managerial human capital tend to be
insufficient unless trade associations organize collective action to internalize theexternality or the government provides appropriate support for such critical investment
activities. By way of summary and conclusion, I would like to specify four essential
elements of an effective strategy for cluster-based industrial development in thefollowing subsections.

Promote the development of existing industrial clusters
Industrial clusters consisting of microenterprises and SMEs are ubiquitous even in
non-industrialized, low-income economies. They have been formed spontaneously

23without government support in order to reduce market failures by reducing transaction
costs. Such clustered industries must have the comparative advantage. Thus, I would
like to recommend to support the development of such industrial clusters. Many ofthem, however, are stagnant. As Porter (1990, 2000) points out and Sonobe andOtsuka (2006, 2011, 2014) observe, such industrial clusters, or at least some of them,
have the potential to evolve and develop to become dynamically-growing clusters.
Page (2012) agrees with this recommendation.

Invest in the human capital of entrepreneurs for innovations
Since entrepreneurs’ managerial human capital is a major missing factor that
constrains the growth and productivity of micro and small enterprises, I recommend
investing in their managerial human capital by offering management training.
Management training is essential not only for enhancing human capital but also forscreening promising and non-promising entrepreneurs because the difference ininnate management ability between them becomes apparent after the training (Otsuka
2018). Since only a small fraction of small enterprises have the potential to be
successful, as discussed by Gindling and Newhouse (2014), this screening function ishighly important. Nevertheless, management training is only one aspect of learningfrom abroad. For successful innovation, training to learn advanced technologies fromabroad is also essential. Thus, I recommend combining management and technology
for local entrepreneurs to stimulate innovations or enhance their absorptive capacity.

So far as access to credit is indispensable for innovations, support for credit provision
to promising entrepreneurs can be justified after the management and technology
training. A possible alternative is introducing Kaizen, as it intends to promote low-costor cost-saving management without requiring substantive additional investments. The
24

establishment of industrial zones for promising entrepreneurs will also be useful once
identified by the training.15

Strengthen contractual relationships with foreign enterprises
As the East Asian experience amply illustrates, there are many channels throughwhich enterprises in developing countries can learn advanced technologies andmanagement methods from abroad. They include foreign traders and global buyers,
who provide blueprints and basic technology to local enterprises; foreign
manufacturers which order OEM and ODM; and subsidiaries of MNCs, which provide
training to subcontracted local part-supplying firms. Local enterprises employing
foreign advisers who used to work for foreign companies seem to be another effective
way of learning from abroad.

Attracting the attention of foreign traders, buyers, manufacturers, and MNCs to local
production in developing countries is not an easy task. The establishment of industrial
zones with appropriate infrastructure and the promulgation and enforcement of therules of fair transactions are necessary. Also, the availability of trained managers,
engineers, and workers, and the services of supporting industries, which provide parts
and intermediary products and repair services, are indispensable. To nurture suchlabor force and industries, the upgrading of existing industrial clusters by investing incompetent entrepreneurs’ human capital seems to be a prerequisite.

Role of government
The role of government is to stimulate innovations by correcting market failures arising

15 The establishment of special economic zones (SEZs) is not successful in Africa (Farole 2011), presumably

because of the failure to nurture entrepreneurs willing to locate their factories in SEZs.

25

from information spillovers. More specifically, the government should support thedevelopment of existing industrial clusters by investing in managerial andtechnological training for entrepreneurs, establishing industrial zones, supporting
credit provision, and enforcing rules of transactions. It is also appropriate for thegovernment to support trade associations’ activities while clearly recognizing a
critically important role played by these associations in internalizing the benefit of
information spillovers. These are precisely the policies consistent with the newconsensus of industrial policy, which mandates the government to correct market
failures and assist industries with comparative advantage.

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Table 1. Location, product, origin, number of enterprises, average number of workers, and presence of foreign enterprises
in selected industrial clusters in Asia and Africa

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17

Location

Main ProductOriginNo. ofEnterprisesa

Average
Number ofWorkersa, b

Presence ofForeignEnterprises

Taichung, Taipei, China

Machine tools

Small enterprises

100

17

No

Zhili, China

Baby clothes

Farm households

2,000

15

No

Wenzhou, China

Electric fittings

Farm households

120

339

No

Bac Ninh, Vietnam

Rolled steel bars

Farm households

133

25

No

Sargodha, Pakistan

Electric fittings

Small enterprises

1,200

11

No

Addis Ababa, Ethiopia

Garments

Tailors

700

10

No

Nairobi, Kenya

Garments

Tailors

640

13

No

Kumasi, Ghana

Metalwork

Small car repairers

1,000

5

No

Hatay, Vietnam

Garments

Cooperatives

160

20

No

Addis Ababa, Ethiopia

Leather shoes

Migrant artisans

900

10

No

Nairobi, Kenya

Metalwork

Spin-offs from FDI

150

8

No

Dar es Salaam, Tanzania

Garments

UNIDO training

700

5

No

Addis Ababa, Ethiopia

Metalwork

Migrant artisans

130

70

No

Suzhou, China

Printed circuit board

SOEs

n.d.c

28

No

c

146

Yes

Kunshan, China

Printed circuit board

SOEs

n.d.

Shinjhu, Taipei, China

Printed circuit board

Foreign enterprises

60

1,100

Yes

Dhaka, Bangladesh

Garments

Foreign enterprises

4,100

1,231

Yes

Source: Sonobe, Higuchi, and Otsuka (2012) and Sonobe and Otsuka (2015)
Notes: a Data refer to the period between 2000 and 2010.
b Average number of workers of sample enterprises.
c Data is not available.

34