An Inquiry into the Rapid Growth of the Garment Industry in Bangladesh [PDF]

National Graduate Institute for Policy Studies Global Center of Excellence Economics Working Paper No. 21 August 2009

An Inquiry into the Rapid Growth of the Garment Industry in Bangladesh Khondoker Abdul Mottaleb National Graduate Institute for Policy Studies, Tokyo and Tetsushi Sonobe Foundation for Advanced Studies on International Development, and National Graduate Institute for Policy Studies, Tokyo

Abstract The export-oriented garment industry in Bangladesh has grown rapidly for the last three decades and now ranks among the largest garment exporters in the world.

While its

early success is attributed to the initial technology transfer from South Korea, such a one-time infusion of knowledge alone is insufficient to explain the sustained growth for three decades.

This paper uses primary data collected from knitwear manufacturers

and garment traders to explore the process of the continuous learning of advanced skills and know-how.

It finds, among other things, that the high profitability of garment

manufacturing due to the initial infusion of specific human capital attracted a number of highly educated entrepreneurs to the industry, that the division of labor between manufacturers and traders has facilitated the expansion of the industry, and that enterprise growth has lasted long because of the continuous learning from abroad by the highly educated entrepreneurs.

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1. Introduction The phenomenal growth of the garment industry in Bangladesh is widely known, due in no small part to the popular book by Easterly (2002) and an earlier paper by Rhee (1990).

The industry now ranks among the largest garment exporters in the world.

It

accounts for 75 percent of the country’s export earnings and 25 percent of GDP and provides ample job opportunities for females. scratch three decades ago.

The garment industry started from

Since its exports were negligible in those days, the country

was not subject to export restrictions under the Multi-Fiber Arrangement (MFA), which attracted the attention of Daewoo Corporation of South Korea, one of the rising garment manufacturers suffering severely from the quota system.

The company planned to

develop a production base in Bangladesh and teamed up with an indigenous new enterprise called Desh Ltd. in 1979. Desh sent 130 new employees to Daewoo’s factory in South Korea, where they participated in an eight-month intensive training course covering diverse topics from sewing skills to factory management and international marketing.

By two years after the training, however, almost all the

trainees had left Desh to start their own garment businesses (Rhee, 1990).

Easterly

(2002, pp.147-148) comments: “This explosion of garment companies started by ex-Desh workers brought Bangladesh its $2 billion in garment sales” in the late 1990s. By 2007/08, the industry was earning more than $10 billion. Like the Bangladesh of three decades ago, countries in Sub-Saharan Africa are now given favorable treatments to their garment industries, such as duty-free, quota-free access to the US market provided by the African Growth and Opportunity Act (AGOA). What can be done for the garment producers in Africa to allow them to take full advantage of such a helpful situation?

Existing studies of the Bangladeshi garment

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industry agree with Easterly (2002) and Rhee (1990) that a central role in the industry’s development was played by technology transfers from abroad (e.g., Quddus and Rashid, 2000; Hoq, 2004; Khan, 2004; Mlachila and Yang, 2004; Rahman, 2004; Siddiqi, 2005). This paper uses primary data of garment manufacturers and traders in Bangladesh to investigate further the role and mechanism of technology transfers.

While Rhee

(1990) describes vividly the technology transfers that occurred in the early stage of the industry’s development, his study does not cover the recent period.

From the

description provided by Easterly (2002), one may have an impression that the proliferation of manufacturers was the major way in which the industry has grown.

In

the proliferation process, the Desh-Daewoo trainees established their factories and taught their workers, who later started their own factories and disseminated the knowledge originally from Korea.

While this is true, it is not the whole story.

Many

of the original Desh-Daewoo trainees did not become garment manufacturers but instead became garment traders, who act as intermediaries between manufacturers and foreign buyers.

The subsequent proliferation of local garment traders suggests that

their activities have been useful for the development of the industry. A question arises as to what roles local traders play in industrial development in developing countries. The economics literature, however, is silent about this question.1

In an attempt to

examine what role local traders play, we collected data of traders as well as manufacturers. The export-oriented garment industry in Bangladesh today is large not just in 1

The roles of agricultural traders in counteracting the imperfections of market institutions are extensively discussed by Fafchamps (2004) and Hayami and Kawagoe (1993). Gereffi (1995), Schmitz and Knorringa (2000), and Bazan and Navas-Aleman (2004) among others investigate how global buyers organize international trade networks and how learning takes place in the network. To our knowledge, however, there are few studies of local traders in industries in developing countries.

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terms of the number of manufacturers (over 4000), but also because these enterprises are large in size.

During the last three decades, the export-oriented garment industry

in other countries, such as the Philippines, has experienced prosperity and then a sharp decline.

This fact suggests that there is an interesting story not just about the

beginning of the industry but also about the subsequent process of enterprise growth. According to Gereffi (1999), Schmitz and Knorringa (2000), and Bazan and Navas-Aleman (2004), opportunities for continuous learning are built in to operation within the global commodity chain, and it is up to local suppliers, such as garment manufacturers in Bangladesh and the Philippines, whether they learn advanced skills and know-how.

What are the determinants of enterprises’ continuous learning from

abroad and own experiences?

One answer is the profitability from learning, which

will in turn depend on labor costs and other conditions. In search of the fundamental determinants of the profitability, we attempt to identify the entrepreneur’s background attributes that affect the enterprise performance. Since information on entrepreneurs is unavailable from secondary data, we conducted personal interviews with them. It was, however, difficult to meet with entrepreneurs, especially with traders, because they always move from place to place. It is no wonder that empirical studies of traders are scarce.

Our data indicate that

traders provide manufacturers with services by using specific skills that newly established manufacturers tend to lack, and that manufacturers reduce their dependence on traders as they learn such skills. These findings suggest that the division of labor between traders and manufacturers has facilitated the reproduction of manufacturers and the formation of a cluster.

Our data also indicate that not just enterprise size but

enterprise growth depends much on the general human capital of the entrepreneur. We

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conjecture that highly educated entrepreneurs have been attracted to this industry by the high profitability which was boosted initially by the Desh-Daewoo infusion of Korean skills and know-how. The rest of the paper is organized as follows.

Section 2 reviews the historical

development of the garment industry in Bangladesh.

Section 3 advances three testable

hypotheses.

After the descriptive analysis is presented in Section 4, regressions

analyses are carried out in Section 5.

Section 6 summarizes the findings and discusses

the implications.

2. Brief History In the 1970s, Bangladesh was dominated by the socialistic ideology.

The government

controlled foreign trade nearly completely and regulated private investments.

When

Desh Garment made its debut on the world market in 1980, the government hardly recognized the potential of the garment industry.

In 1982, however, the government

began to provide various incentives to the garment industry, such as the duty free import of machinery, bonded warehouse facilities, and cash incentives, and donated land to garment producers in Narayanganj and Gazipur.2

Furthermore, the government sent

missions to the US government to lobby for duty free access to the US market. government also helped organize trade fairs at home and abroad.

The

Thus, it is clear that

the government has played a role in the development of the garment industry in Bangladesh (e.g., Siddiqi, 2005; Quddus and Rashid, 2000). Textile and garment companies in South Korea and other newly industrialized 2

Large garment clusters have emerged in Gazipur and Narayanganj on the land donated by the government. Very recently, the government has donated another 300 acres of land exclusively to develop a garment village in Munshiganj, a suburb of Dhaka, where at least 390 production units will be accommodated.

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countries (NIEs) in East Asia continued to invest in their factories in export processing zones in Dhaka, the capital city, and Chittagong, the largest port city, in Bangladesh. Like the Desh-Daewoo training, these foreign ventures sent Bangladeshi workers to their home countries for intensive training, and some time after returning to Bangladesh, many of these trainees moved to other factories or started their own factories or trading houses. As a result of its rapid growth, this industry was brought under the MFA quota system in 1986. The system is said to have favored Bangladeshi producers because it protected them from foreign competition and because a more generous export quota was given to Bangladesh than to India and Sri Lanka (e.g., Mlachila and Yang, 2004; Siddiqi, 2005; Saxena and Wiebe, 2005).

Another important event in 1986 was that the Export

Promotion Bureau of Bangladesh and the United Nations Development Programme (UNDP) sent several Bangladeshi knitwear producers to Italy, Germany and Poland, which helped the producers understand the latest production techniques and export market conditions, according to Hoq (2004). From the late 1980s through the 1990s, the center of gravity of the industry shifted from foreign ventures to indigenous producers and traders, who increased exports to large retailers and branded marketers in Europe and North America.

These

customers make new designs at their headquarters and sell the products under their own brands through their own distribution channels. However, production is subcontracted to suppliers in developing countries.

The case studies of global value chains covering

Asia and Latin America find that working to the specifications set by global buyers has helped local suppliers improve production efficiency and product lines, and that some local suppliers have been able to obtain more advanced know-how, such as designing,

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marketing, and branding (e.g., Gereffi, 1999; Tewari, 1999; Schmitz and Knorringa, 2000; Bazan and Navas-Aleman, 2004).

The same seems to hold true in the case of

the suppliers in Bangladesh. In 1994, the international community decided to abolish MFA gradually.

The

phased abolition of the quota system began in 1995 and was completed in 2005. Because the quota elimination allows global buyers to import as many garments from their favorite suppliers as they like, the phase-out of the quota has increased competitive pressure on suppliers. The Bangladeshi garment industry has been a winner.

From

1983 to 2008, as shown in Table 1, the number of garment producers, their employment and export value, and the share of garment export in the country’s total export earnings continued to increase. In 2007/08, the industry earned more than 10.7 billion US dollars from exports, comprised over 4700 factories, employed two and a half million workers, and accounted for more than 76 percent of the country’s total export earnings. Although not shown in the table, garment traders who help to intermediate between local producers and global buyers have also increased in number.

Although

garment traders have no legal obligation to register with the Bangladesh Garment Manufacturers and Exporters Association (BGMEA), 846 traders are registered with BGMEA today.

The location of the garment manufacturers and traders is concentrated

in the greater Dhaka area and the greater Chittagong area. approximately three times as many manufacturers as Chittagong.

The Dhaka area has While Dhaka-based

manufacturers are sprawling out to the suburbs, almost all the traders have their offices in the urban center because foreign buyers hesitate to visit their suppliers located in the suburbs.

One can start a garment trading house with a much smaller initial investment

than for a garment factory.

A number of garment businessmen started their careers as

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traders and later branched out into garment manufacturing. One of the impacts of the phase-out of the quota on the Bangladeshi garment industry is the rise of the knitwear sector and the comparative decline in the woven garment sector.

The emphasis on quick delivery due to the intensified competition has

put the producers of woven garments, such as shirts and pajama sets, at a disadvantage compared to producers of knitwear, such as polo shirts and sweaters. This is because the woven garment producers depend heavily on imported woven textile, which is prone to delays in delivery, whereas the knitwear producers have an abundant and quick supply of domestically produced yarn and fabrics (Siddiqi, 2005). Moreover, knitwear producers in Bangladesh have managed to find higher value-added markets for sweaters and cardigans.

As a result, the knitwear sector has grown much faster than the woven

garment sector since 1995 in terms of both the number of manufacturers and export earnings per manufacturer, as shown in Table 2.

In 2007/08, the knitwear sector

earned more export revenue than the woven garment sector for the first time. Global value chains are influenced by not only market demands and trade agreements.

Global buyers fear that trade unions, NGOs, human rights groups and

consumers’ associations in developed countries may accuse them of encouraging their suppliers in developing countries to run sweatshops and use child labor. To avoid such accusations, they have set parameters on standard rules and regulations regarding product quality, safety, labor standards, working environment, and child labor issues, and push local suppliers to follow these standard parameters, which are known as the codes of conduct (Humphrey and Schmitz, 2004).

In Bangladesh, the garment

industry has undertaken large investments in equipment and working conditions in order to comply with these codes of conduct (e.g., Rahman, 2005).

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Still, wages are low in Bangladesh.

As Figure 1 shows, the real wage index,

which was 100 in 1969/70, remained largely the same in the early 1980s.

This

suggests that real wages remained more or less constant for more than a decade. It rose slowly in the next 15 years to 140, and more rapidly in the early 2000s. According to the Japan External Trade Organization’s (JETRO 2009) compilation of investment cost information, an ordinary factory worker in Dhaka is paid less than half the wage for her counterpart in the Philippines. The labor cost difference may partly explain why the garment industry in Bangladesh has been rising in contrast to that in the Philippines, which has been declining.

However, garment exports have been growing

as rapidly in Turkey as in Bangladesh, and wages are much higher in Turkey than in the Philippines. The garment industry in Turkey focuses on a market segment for more fashionable garments than Bangladesh and is said to have an advantage of being geographically closer to Europe.

In any case, it is clear that labor cost is not the only

determinant of the development of the garment industry.

3. Hypotheses We agree completely with many other authors that the Desh-Daewoo training kick-started the garment industry in Bangladesh. The thorough training formed a mass of specific human capital with high skills not only in production techniques but also in factory management, international procurement, and international marketing (Rhee 1990).

For those with high levels of general human capital and abundant financial

capital, the massive infusion of specific human capital meant that their production functions shifted upward substantially. According to our interview with one of the 130 Desh-Daewoo trainees, highly educated people and wealthy families in Bangladesh

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were not at all interested in the garment business and any kind of manufacturing. However, looking at Desh’s good start in exporting, some of them changed their mind and decided to supply their resources to the garment industry; that is, financial capital and high levels of general human capital. Among those who had received good training, some had sufficient financial capital to establish their own garment factories, and others became garment traders or worked for other manufacturers as managers.3 Probably, traders would work with those manufacturers who started garment manufacturing without sufficient specific human capital.

Traders’ services would be primarily related to but not limited to marketing.

Traders who received better training would provide a variety of more valuable services to client manufacturers.

With the help of traders, a large number of manufacturers can

start production and export without wasting time on trial and error, which would otherwise be needed to find their way into foreign markets.

The collaboration with

traders will also reduce the risk of manufacturers’ bankruptcy.

As manufacturers

acquire specific human capital, they would reduce their dependence on traders and increase direct transactions with foreign buyers.4

Traders will divert their resources

away from such graduating manufacturers to newly established manufacturers. As Sonobe and Otsuka (2006) argue based on case studies in East Asia, the division of labor between manufacturers and traders facilitates the expansion of an industry. Easterly (2002, Ch. 8) refers to Romer’s (1986) model of endogenous economic growth to explain the two special attributes of knowledge as a good: one is that

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Those who received formal training abroad were highly educated because only those who were fluent in English were given training opportunities. 4 Sonobe, Hu, and Otsuka (2002) report that garment manufacturers in Zhejiang province in China depended on local traders initially and then increased direct transactions with retailers in remote large cities.

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knowledge leaks, and the other is that the same knowledge can be used repeatedly without causing rivalry. He uses the anecdote of the Bangladesh garment industry to illustrate how the non-rivalry and spillovers of knowledge as a production input lead to external increasing returns.

In our view, transactions between traders and

manufacturers are an important channel of knowledge spillovers, and external increasing returns arising from knowledge spillovers are strong where traders and manufacturers are agglomerated, because their proximity to each other in an agglomeration reduces transaction costs, thereby encouraging transactions as the theoretical model developed by Becker and Murphy (1992) predicts. Probably, the traders’ provision of services to manufacturers eases the entry of new manufacturers, leading to the expansion of agglomeration, which in turn facilitates the division of labor between traders and manufacturers. Our argument concerning enterprise growth begins with a general observation that a growing enterprise has increasingly complex flows of cash, credit, and debit, an increasing number of workers, and an increasing number of transacting partners.

Thus,

growth requires good management, which in turn requires management skills. Moreover, the global garment chains keep pressure on local suppliers to shorten delivery time, improve quality, and reduce unit costs (Gereffi, 1999; Schmitz and Knorringa, 2000).

Thus, enterprise growth will depend on the pace at which the

enterprise learns advanced skills and know-how.

When the enterprise is small, the

entrepreneur himself can devote much time to learning.

As the enterprise grows

further, however, he needs to hire managers and experts and delegate authority to managers because his time and capacity are limited (Aghion and Tirole, 1997; Hart and Moore, 2005).

As a result, the enterprise’s organizational learning no longer depends

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on the entrepreneur’s learning ability but on his selection of managers and experts as well as the quality of his guidance to them.

We conjecture that the entrepreneur’s

ability to make good decisions related to organizational learning as well as his learning ability depends on his general human capital. To substantiate these arguments, we will analyze some portion of the arguments with data. The first concerns the provision of services by traders to manufacturers as follows:

Hypothesis 1: Traders with good training and rich experience in the business provide manufacturers with higher-valued services and earn greater revenues, whereas manufacturers with high education and rich experience depend less on traders’ services.

We have argued that the growth of an enterprise depends on its organizational learning because not just the scale but the complexity of activities increases as the enterprise grows. We have also argued that organizational learning depends on the general human capital of the entrepreneur.

Since the activities of trading houses are much smaller in

scale and less diverse, it follows that the growth effect of the entrepreneur’s general human capital is expected to be weaker for the trader than the manufacturer.

If our

argument is correct, however, it also follows that the trader’s general human capital assumes importance when his business branches out into manufacturing. We thus formulate a hypothesis as follows:

Hypothesis 2: The trader’s education level has only a weak effect on the growth of

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his trading business but a positive and significant effect on his entry into manufacturing.

We have argued that the manufacturer’s education level is likely to have a positive effect on enterprise growth. this apply to formal training?

From formal education, one learns how to learn.

Does

To the extent that formal training concentrates on the

acquisition of specific skills and know-how, there is no convincing reason to expect that it has a lasting growth effect, and thus it seems reasonable to formulate the following hypothesis:

Hypothesis 3: The manufacturer’s education level has positive effects on the size and growth of his enterprise, but his prior formal training has only a level effect.

4. Data In August and December 2005, we conducted preliminary surveys of producers, traders, and consultants for four weeks in total. After visiting both knitwear factories and woven garment factories of various sizes, we decided to study the development of the knitwear sector and the trading sector, because the knitwear sector has been growing faster than the woven garment sector in recent years and because the roles of traders in industrial development remain an enigma. Our sample was selected randomly from the member lists of three associations: BGMEA, the Bangladesh Knitwear Manufacturers and Exporters Association (BKMEA), and the Bangladesh Garments Buyers Association (BGBA).

After establishing rapport with some leaders of these

associations, we were able to request introductions to the entrepreneurs whom we

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selected randomly.

For three months, from late December 2005 to early March 2006,

we visited 40 traders and 100 knitwear producers in the greater Dhaka area,5 and we were able to interview the entrepreneur at each enterprise except for eight factories. Our sample consists of 40 traders and 92 knitwear manufacturers.

They

provided us with recall information on the number of workers, production and costs, export revenues in 1998, 2000, 2002, 2004, and 2005, as well as information on their educational and occupational backgrounds. For simplicity, we refer to the knitwear manufacturers in the sample as manufacturers. represent woven garment manufacturers.

Note, however, that they do not

By contrast, the traders in the sample

represent the whole population of traders, because they were selected randomly regardless of their specialization. The sample traders deal in both woven garments and knitwear. Of the 92 sample manufacturers, 37 produce sweaters and cardigans, while the remaining 55 do not produce these items but polo shirts and T-shirts instead. The sample entrepreneurs’ background attributes are summarized in Table 3. Both the traders and manufacturers went to school for 15 years on average, and about 60 percent of them went to school for 16 years or more.6

These numbers are very high,

compared with the education levels of entrepreneurs in garment and other light manufacturing industries in East Asia reported by Sonobe and Otsuka (2006), Vietnam by Nam et al. (2009a, b), and Africa by Sonobe et al. (2009a, b).

The high education

level of entrepreneurs is characteristic of the Bangladeshi garment sector.

Note,

however, that highly educated people became interested in garment business only after

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The Greater Dhaka area consists of Dhaka and the neighboring two districts, i.e., Narayanganj and Gazipur. Narayanganj used to be the center of the production of hosiery, but it has many T-shirt factories now. Gazipur is a newly developed cluster of garment factories, especially those producing sweaters. 6 In Bangladesh, it takes 16 years for a student to receive a specialized degree.

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the Desh-Daewoo technology transfer, as mentioned in the previous section. In our view, high education is characteristic of this industry, simply because comparably sizable technology transfers, which shift production functions substantially upward and attract the highly educated to manufacturing, rarely take place. By “years in prior experience in garment trading,” which appears in the middle of Table 3, we mean the number of years the entrepreneur has engaged in the garment trading business, as a worker, manager, or unpaid family worker, prior to the establishment of his own business.

Similarly, “prior experience in garment

production” is the number of years the entrepreneur has worked at a garment factory before he started his own trading house or factory, and “prior experience in other sectors” is the number of years the entrepreneur has worked in a non-garment sector. The second row from the bottom of Table 3 shows the percentage of entrepreneurs who received formal training in garment businesses in Korea and other foreign countries.

Three traders and two manufacturers in the sample received

intensive training in South Korea and Singapore. Desh-Daewoo trainees.

Among them is one of the 130

UNDP provided support for the training of three sample

manufacturers in Europe.

Similarly, the Association for Overseas Technical

Scholarship (AOTS) of Japan supported the training of a sample trader in Japan. Three other sample traders and one sample manufacturer received intensive training in China, Taiwan, and Sri Lanka at their own expense.

We regard these entrepreneurs as

the recipients of good prior training and distinguish them from the other sample entrepreneurs in the analysis below. The education levels of these entrepreneurs with good prior training tend to be higher than the sample average.

Among the six such

manufacturers, the lowest education level is 16 years of schooling, and the mean is 17.3

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years. Tables 4 and 5 present data on the size and activities of the trading and manufacturing enterprises, respectively.

Since new entrants tend to be smaller in size

than incumbent enterprises, it is difficult to see how rapidly enterprises grow if enterprises of very different ages are mixed.

This is why these tables divide the

sample enterprises into three cohorts: those established in 1994 or earlier, between 1995 and 1999, and between 2000 and 2005.

These tables clearly indicate that the growth of

trading enterprises in employment and sales revenues (or export earnings) is slower than the growth of manufacturing enterprises in employment and value added, and that the former becomes even slower as trading enterprises mature whereas fast growth is sustained in the manufacturing case. As indicated in the second row of Table 4, there are five foreign ventures in our trader sample.

They are foreign ventures in the sense that their headquarter offices are

located in foreign countries, even though the heads of their Bangladesh offices are Bangladeshi except for one, who is Italian.

None of the sample manufacturing

enterprises are foreign ventures. With the small number of foreign ventures in our sample, the impacts of foreign direct investment, if any, are impossible to analyze with our data. In the garment industry in Bangladesh, a long-run tendency is that foreign enterprises have been replaced by indigenous enterprises as service providers, manufacturers, and material suppliers (e.g., Siddiqi, 2005; Quddus and Rashid, 2000; Yamagata, 2006).

The proportion of trading houses that hire foreign experts in

marketing is high among relatively long-established trading houses and low among newly established trading houses, which may be another indication of the long-run tendency of decreasing dependence on foreign human capital.

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We will return to this

point in the next section. To test Hypothesis 1, we need a measure of high-valued services provided by traders. All traders provide services related to the procurement of materials from abroad and the marketing and shipment of product to abroad.

It is practically

impossible, however, to measure the quality or the value of such service.

Instead we

will take advantage of the fact that a limited number of traders provide services related to manufacturing.

An example is to make counter samples on behalf of a manufacturer,

following the sample or specifications set by its buyer abroad.

By inspecting counter

samples submitted by local suppliers, the global buyer decides with whom to place the order.

Traders provide sample making services because some manufacturers are too

busy and some lack the skills necessary to make a satisfactory counter sample.

As

shown in Table 4, the majority of traders have equipment and staff for sample making. Another example is design re-engineering. While designs are sent by global buyers to local suppliers, some designs require modifications in order to become more attractive to consumers or easier to produce in large quantities. allow their local suppliers to re-engineer designs.

Some global buyers

When a manufacturer is allowed to

re-engineer a design but cannot do so satisfactorily, he may ask a capable trader for help. Table 4 shows the mean of the percentage of designs that a trader re-engineered in the specified year.

Design re-engineering is regarded as a higher-valued service than

sample making, according to the result of our interviews with traders and manufacturers. In the next section, we will use this percentage or fraction of designs re-engineered and a dummy variable indicating whether the trader has the capacity to make counter samples as proxies for the provision of high-value services. Table 4 ends with the data on the entry of the traders into manufacturing, which

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we use to test Hypothesis 2. If the three cohorts are mixed, slightly more than half of the traders were engaged in garment manufacturing in 2005. According to our interviews with traders who owned factories, their products are exported through their own trading houses.

Thus, if a trader starts operating a garment factory, his export sales revenue

increases. The trading houses which were established between 1995 and 1999 had a high average of sales revenues in 2005 because as many as 68.7 percent of them had started manufacturing. Turning to the manufacturing enterprises, Table 5 shows the percentage of their direct export sales revenues.

This percentage is equal to 100 minus the percentage of

their sales revenues coming from or through traders.

The percentage of direct export

by the relatively long-established enterprises increased over time and is higher than that of the direct export by the newly established enterprises. These observations lend strong support to our argument that the manufacturers reduce their dependence on traders as they learn skills and know-how that they did not have when they started production. Table 5 also shows the percentage of manufacturers with an international certificate.

Global buyers that specialize in high-quality segments of the world

garment market tend to prefer dealing directly with local manufacturers, rather than through traders.

Probably, this is because direct transactions allow tight control of

local manufacturers in terms of product quality, delivery time, and the codes of conduct. For local manufacturers, direct transactions with these demanding buyers involve large investments in equipment, buildings, and training workers but are profitable since only a limited number of local manufacturers in the world can satisfy these buyers’ needs. To attract the attention of these buyers, a number of manufacturers in Bangladesh have

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obtained certificates from international auditing bodies, such as International Organization for Standardization (ISO).

This is why the data on the percentage of

manufacturers with such certificates show a similar tendency as the data on the percentage of direct exporting sales revenues. Direct transactions with global buyers, especially those with quality-conscious buyers, require the use of expensive machines and tight quality control, which in turn require the input of engineering expertise.

Our respondents informed us that human

resources with such expertise have become scarce in the industry and that garment manufacturers have increased the employment of foreign experts mainly from Sri Lanka and India. The data shown in Table 5 are consistent with this information.

5. Regression Analyses Tables 6 to 8 present the results of the reduced-form regressions. Table 6 and the first column of Table 7 concern Hypothesis 1 on the symbiotic relationship between traders and manufacturers.

The rest of Table 7 is about Hypothesis 2 on the effects of traders’

education levels on the growth of their businesses and their entry into manufacturing. Table 8 concerns Hypothesis 3 on the determinants of the size, productivity, and growth of manufacturing enterprises. Column (1) of Table 6 presents an estimate of the function explaining the fraction of designs re-engineered as a proxy for the provision of high-valued services by the trader.

The major determinants of this variable are the trader’s formal training in a

foreign country, the number of years of operation as an indicator of organizational experience as a trading house, the dummy variable indicating whether the trading house is a foreign venture, and the entrepreneur’s experience of working at a foreign venture

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prior to the establishment of his trading house.

Column (2) reports the estimated

probit model for the determination of whether to provide sample making services. estimates in columns (1) and (2) are qualitatively similar, with two exceptions.

The

One is

that the foreign venture dummy has a much stronger effect on design re-engineering than on sample making.

Another is that the entrepreneur’s experience of working at a

foreign venture has a positive effect on design re-engineering and a negative effect on sample making.

Column (3) presents the OLS estimates of the function explaining the

sales revenue of the trading house.

Note that the effects of the regressors on sales

revenues are qualitatively similar to those on design re-engineering and sample making. These results indicate that the trading houses with the skills of design re-engineering and sample making earn high sales revenues, lending support to the first half of Hypothesis 1. The regression results shown in column (4) indicate that the trading house is more likely to employ foreign experts if the entrepreneur is not highly educated, did not receive prior training in the garment business, had prior experience of working at a garment factory or a garment trading house, and the trading house is long established and foreign owned.

The negative and significant effects of the education variable and

the prior formal training variable suggest that foreign experts are not useful for the traders with high education, high skills and know-how specific to the garment industry. The positive and significant effects of the prior experience in garment production and marketing on the employment of foreign experts, together with the insignificant effects of these variables on sales revenues, suggest that such experience as a worker are poor substitutes for formal training in a foreign country.

The coefficients on the four

year-dummy variables are negative, and those for the most recent two years are

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significant in column (4).

These results indicate that the employment of foreign

experts has been decreasing over time, probably reflecting the increasing presence of the Bangladeshi garment industry in the world garment market as well as the increasing skills of the indigenous garment traders.

According to column (4), however, the

long-established trading houses tend to employ foreign experts, and according to columns (1) to (3), they tend to perform well, relative to the newly established trading houses.

These results suggest that the employment of foreign experts has been an

important channel of technology transfer. Table 7 reports the regression results concerning manufacturers’ direct exporting, traders’ growth in revenues, and traders’ entry into manufacturing.

Column (1)

presents the estimated tobit model in which the dependent variable is the fraction of the manufacturer’s sales revenue from direct exporting. This direct export ratio is one minus the rate of dependence on traders.

In this column, the years of schooling of the

entrepreneur, the years of operation, and the sweater production dummy have positive and significant effects.

These results support the second half of Hypothesis 1. A

question arises as to what the number of schooling years represents.

It may represent

the general human capital of the entrepreneur, or the wealth of his family or parents, or both.

Manufacturers need much greater investments to start businesses than traders.

Thus, we should be careful when we discuss the effects of the education and prior experience of manufacturers on their business results. We will return to this point later. Columns (2) and (3) of Table 7 present the results of the growth regressions for traders, which include a lagged dependent variable on the right-hand side.

In column

(2), the dependent variable is the logarithm of the sales revenue in 2005, and the

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corresponding variable on the right-hand side is the logarithm of the sales revenue in 2000.

This is a cross section regression with a small sample size of 33 trading houses.7

In column (3), the four periods (i.e., 1998-2000, 2000-2002, 2002-2004, and 2004-2005) are pooled to increase the sample size.

In neither column does the

education variable have a significant growth effect, which is consistent with the first half of Hypothesis 2. The results of these regressions indicate that the trading houses with older entrepreneurs have grown in size more slowly than those with younger entrepreneurs, and that the foreign trading houses have grown in size more rapidly than the indigenous trading houses. Column (4) presents the estimated probit model for the trader’s entry into garment manufacturing.

The foreign trading house dummy has a negative and significant effect

on the entry into manufacturing, suggesting that the foreign trading houses are not interested in manufacturing.

An indigenous trader is more likely to own a factory if he

is highly educated, received formal training abroad, has prior experience in garment production or trading, and has no experience of working at foreign ventures and if his trading house was established long ago. To finance entry into manufacturing, the trader has to earn large profits every year and accumulate sufficient financial assets, which may be reflected in the positive and significant effects of the prior formal training dummy and the years of operation. The positive and significant effect of the education variable is consistent with the second half of Hypothesis 2.

This effect may be a

reflection of the financial requirement for the entry into manufacturing. It may also be a reflection of the requirement of the sufficient learning ability of the entrepreneur for 7

While there are 40 traders in our sample, the data on the sales revenue in 2000 are available from only 33 traders. An even smaller sample offers data on sales revenue in 1998. The period from 2000 to 2005 is the longest period for which we can run a growth regression.

21

the operation of a manufacturing enterprise. Table 8 presents the regression results for manufacturers’ enterprise size and growth as well as attempts to strengthen their competitiveness.

The entrepreneur’s

education level, his prior experience in garment production, garment marketing, and other sectors, the enterprise’s years of operation, and the sweater production dummy have positive and significant effects commonly on the three dependent variables. entrepreneur’s age has negative effects on the three dependent variables. also dissimilarities, however.

The

There are

For example, the prior formal training dummy has no

significant effect on value added, a negative and significant effect on employment, and a positive and significant effect on the likelihood that the enterprise has received a certificate from an international standards organization.

These results suggest that the

enterprise tends to have higher labor productivity and transact with more quality conscious buyers if its entrepreneur had good prior training. The coefficients of the year dummies in columns (2) and (3) indicate that the employment and the proportion of manufacturing enterprises with international certificates have increased in recent years, even after controlling for the strong effects of the years of operation.

In column (1), the effects of the first three year dummy

variables on value added are negative, but the effect of the year 2005 dummy and that of the year 2000 dummy are positive and marginally significant.

Thus, there was a

tendency among the manufacturing enterprises for both employment and value added to increase.

Note that the expansion of enterprise size was not accompanied by

improvement in labor productivity. Presumably, the size expansion was a response to the recent tendency among the global buyers to focus on local suppliers with large production capacity.

22

Column (4) shows the estimated probit model for the employment of foreign experts.

According to our interviews with manufacturers, they employ Indian and Sri

Lankan experts because these experts have skills useful for meeting the needs of quality conscious global buyers.

Thus, there is small wonder that columns (3) and (4) share

similar patterns of signs of coefficients.

Column (5) presents the result of a growth

regression in which the dependent variable is the logarithm of value added in 2005 and one of the regressors is that in 2000.

It shows that the entrepreneur’s education level

has a highly significant effect on growth in value added, whereas his prior formal training does not, which lends support to Hypothesis 3. In the sample of manufacturers, there is no entrepreneur who used to work as a garment factory worker, and those entrepreneurs with prior experience in garment production used to work as managers or work at factories owned by their family members or relatives. Thus, if the years of prior experience in garment production takes a positive value, it is likely that the entrepreneur is from a wealthy family.8 Similarly, if the years of prior experience in other sectors take a positive value, it is likely that the entrepreneur or his family own a business other than garment manufacturing.

Thus, the positive effects of these variables on the growth in value

added are attributed largely to the ability of the entrepreneur to finance enterprise growth. These considerations may cast doubt on our interpretation of the positive effect of the entrepreneur’s education level on enterprise growth. Does it reflect the effect of the general human capital useful for enterprise growth? 8

Or should it be solely

In the case of traders, this variable and the variable called the years of prior experience in garment marketing are unlikely to represent the wealth of the entrepreneur’s family since the traders with prior experience in garment production or marketing are mostly ex-workers of garment factories or garment trading houses.

23

attributed to the association between the education level of the entrepreneur and his family’s wealth?

To cast a light on this issue, we estimated a function explaining the

employment size in the first year of the enterprise’s operation.

If entrepreneurs from

wealthy families tended to build large factories, and if the education variable represents the wealth of the entrepreneur’s family rather than his general human capital, this variable is expected to have a positive effect on the initial employment size. estimation result is reported in column (6) of Table 7. variable is positive but insignificant.

The

The effect of the education

This is a result favorable to our argument in

Section 3 that the entrepreneur’s general human capital has a growth effect.

The years

of prior experience in garment production and marketing have positive and significant effects on the initial employment size, which is consistent with the assumption that entrepreneurs from wealthier families tended to build large factories.

The negative and

significant effect of the years of operation indicates that the initial employment size was smaller in the remote past than in recent years.

This result is consistent with the

tendency for enterprise size to increase.

6. Conclusions This paper has examined the successful development process of the Bangladesh garment industry and explored the key to its success by using primary data on garment manufacturers, trading houses, and the entrepreneurs operating these enterprises.

The

results of our regression analyses indicate that the high education of the garment manufacturer has had a positive effect on enterprise growth.

Presumably, this is

because manufacturers have to upgrade their skills and know-how continuously in order to survive the intense competition in the world garment market and because the high

24

levels of the general human capital of the entrepreneur are needed to manage an increasing number of managers and experts.

The high education level of the

entrepreneurs is likely to be a major reason why the garment industry in Bangladesh has continued to grow for the last three decades. The regression results also indicate that the formal training that the garment entrepreneur has received in a foreign country has not had a significant effect on enterprise growth.

The entrepreneur’s experience of working at a garment enterprise

also has not had a growth effect.

However, the formal training and on-the-job training

have had significant effects on enterprise size or productivity or both even many years after.

Those garment workers who had acquired skills and know-how but could not

afford to start factories started trading houses and helped those new manufacturers without marketing skills.

It has also turned out that foreign owned trading houses

perform better than indigenous trading houses, which suggests that there still exist skills and know-how to be learned from foreign countries. Thus, technology transfer seems to be a long-lasting process, and its effect also seems long-lasting.

These findings of

this paper strongly support the proposition that sizable technology transfers, which include marketing, procurement, and management as well as production technologies, are critically important for the promotion of industrial development in developing countries.

25

References Aghion, Philippe, and Tirole, Jean. 1997. “Formal and Real Authority in Organization.” Journal of Political Economy 105, 1-29. Bangladesh Bureau of Statistics (BBS). Statistical Yearbook of Bangladesh. Various Issues. Dhaka: Bangladesh Bureau of Statistics. Bangladesh Export Promotion Bureau. 2005. Export from Bangladesh 1972-73 to 2004-2005. Dhaka: Export Promotion Bureau. Bangladesh Garment Manufacturers and Exporters Association (BGMEA). BGMEA Members Directory. Various years. Dhaka. Bangladesh Garment Manufacturers and Exporters Association (BGMEA). 2008. Online: http://bgmea.com.bd/images/member (accessed July 15, 2009). Bangladesh Knitwear Manufacturers & Exporters Association (BKMEA). 2005. BKMEA Members Directory 2005. Dhaka. Bangladesh Knitwear Manufacturers & Exporters Association (BKMEA). Online: http://www.bkmea.com/facts_figures.php (accessed July 09, 2009).

Bazan, L. and Navas-Aleman, Lizbeth. 2004. “The Underground Revolution in the Sinos Valley: A Comparison of Upgrading in Global and National Value Chains.” In Local Enterprises in the Global Economy: Issues of Governance and Upgrading, ed. Hubert Schmitz.

Cheltenham: Edward Elgar..

Becker, Gary S. and Murphy, Kevin M. 1992. “The Division of Labor, Coordinating Costs, and Knowledge.” Quarterly Journal of Economics 107 (4), 1137-60. Easterly, William. 2002. The Elusive Quest for Growth: Economists' Adventures and Misadventures in the Tropics. Massachusetts: The MIT Press. Fafchamps, Marcel. 2004. Market Institutions in Sub-Saharan Africa: Theory and

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Evidence. Cambridge MA: The MIT Press. Gereffi, Gary. 1999. “International Trade and Industrial Upgrading in the Apparel Commodity Chain.” Journal of International Economics 48 (1), 37-70. Hart, Oliver, and Moore, John. 2005. “On the Design of Hierarchies: Coordination versus Specialization.” Journal of Political Economy 113, 675-702. Hayami, Yujiro, and Kawagoe, Toshihiko. 1993. The Agrarian Origins of Commerce and Industry: A Study of Peasant Marketing in Indonesia, London: Macmillan. Hoq, Monzurul. 2004. “Knitwear Industry in Bangladesh: An Untold Story.” Explore the Galore of Bangladesh Knitwear 1st Bangladesh Knitwear Exhibition. Dhaka: BKMEA. Humphrey, John, and Schmitz, Hubert. 2005. “Governance in Global Value Chains.” In Local Enterprises in the Global Economy: Issues of Governance and Upgrading, ed. Hubert Schmitz. Cheltenham: Edward Elgar. Japan External Trade Organization (JETRO). 2009.

“Kakkoku Chiiki Betsu Joho

(Information by Country/Region).” In Japanese. Online: http://www.jetro.go.jp/world/search/compare/ (accessed August 10, 2009) Khan, Sharifa. 2004. “Textile and Clothing Sector in Bangladesh: Post MFA Challenges and Action Plan.” Dhaka: Ministry of Commerce, WTO Cell. Mlachila, Montfort, and Yang, Yongzheng. 2004. The End of Textiles Quotas: A Case Study of the Impact on Bangladesh. IMF Working Paper, No. WP/04/108. Nam, Vu Hoang, Sonobe, Tetsushi, and Otsuka, Keijiro. 2009a. “An Inquiry into the Development Process of Village Industry: The Case of a Knitwear Cluster in Northern Vietnam.” Journal of Development Studies, forthcoming. Nam, Vu Hoang, Sonobe, Tetsushi, and Otsuka, Keijiro. 2009b. “An Inquiry into the

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Transformation Process of Village-based Industrial Clusters: The Case of an Iron and Steel Cluster in Northern Vietnam.” Journal of Comparative Economics, forthcoming. Quddus, Munir and Rashid, Salim. 2000. Entrepreneurs and Economic Development: The Remarkable Story of Garment Exports from Bangladesh. Dhaka: The University Press Limited. Rahman, Mustafizur. 2004. Surviving in a Quota Free World, Will Bangladesh make it? Report No. 72.

Centre for Policy Dialogue, Dhaka.

Rahman, Mustafizur. 2005. “Bangladesh After MFA Phase Out.” South Asian Journal 8 (April-June) http://www.southasianmedia.net/Magazine/journal/8_phases_out.htm (accessed on August 3, 2007). Rhee, Yung Whee. 1990. “The Catalyst Model of Development: Lessons form Bangladesh’s Success with Garment Exports.” World Development 18 (2), 333-316. Romer, Paul M. 1986. “Are Nonconvexities Important for Understanding Growth?” American Economic Review Papers and Proceedings 80 (2), 97-103. Rushidan Islam Rahman. 2009. “An Analysis of Real Wage in Bangladesh and Its Implications for Underemployment and Poverty.”

Bangladesh Institute of

Development Studies. Online: http://www.peri.umass.edu/fileadmin/pdf/ conference_papers/khan/Rahman_Bangladesh.doc (accessed on July 25, 2009). Saxena, Sanchita B. and Wiebe, Frank. 2005. The Phase-out of the Multi-fiber Agreement: Policy Options and Opportunities for Asia. San Francisco: The Asia Foundation. Schmitz, Hubert and Knorringa, Peter. 2000. “Learning from Global Buyers”. The

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Journal of Development Studies 37 (2), 177-205. Siddiqi, Hafiz G. A. 2005. The Readymade Garment Industry of Bangladesh. Dhaka: The University Press. Sonobe, Tetsushi, Akoten, John, and Otsuka, Keijiro. 2009a. “An Exploration into the Successful Development of the Leather-Shoe Industry in Ethiopia.” Review of Development Economics, forthcoming . Sonobe, Tetsushi, Akoten, John, and Otsuka, Keijiro. 2009b. “Growth Process of Informal Enterprises in Sub-Saharan Africa: A Case Study of a Jua Kali Cluster in Nairobi.” Small Business Economics, forthcoming. Sonobe, Tetsushi, Hu, Dinghuan., and Otsuka, Keijiro. 2002. “Process of Cluster Formation in China: A Case Study of a Garment Town.” Journal of Development Studies 39 (1), 118-139. Sonobe, Tetsushi, and Otsuka, Keijiro. 2006. Cluster Based Industrial Development: An East Asian Model. Basingstoke: Palgrave Macmillan. Tewari, M. 1999. “Successful Adjustment in Indian Industry: The Case of Ludhiana’s Woolen Knitwear Cluster.” World Development 27 (9), 1651-72. World Trade Organization. 2008. International Trade Statistics 2008. http://www.wto.org/english/res_e/statis_e/its2008_e/section2_e/ii69.xls (accessed July 15, 2009). Yamagata, Tatsufumi (2006). “Two Dynamic LDCs: Cambodia and Bangladesh as Garment Exporters.” EIC Economic Review (Economic Institute of Cambodia) 3 (3), 81-136..

Table 1: Growth of the Garment Industry in Bangladesh

29

Fiscal year a

Number of Garment Factories

Employment (million workers)

Export value (billion USD)

% of garments in the country’s export earnings

1983/84

134

0.04

0.03

3.9

1987/88

685

0.28

0.43

35.2

1991/92

1163

0.58

1.18

59.3

1995/96

2353

1.29

2.55

65.6

1999/00

3200

1.6

4.35

75.6

2004/05

4107

2.1

5.17

74.2

2007/08

4740

2.5

10.7

75.8

a. Note: In Bangladesh, a fiscal year starts in July and ends in June. Sources: Bangladesh Export Promotion Bureau (2005) and Bangladesh Garment Manufacturers and Exporters Association (BGMEA), RMG Export Statistics, http://bgmea.com.bd/index.php?option=com_ content&task=view&id=56&Itemid=175 (Accessed July 24, 2009).

30

Table 2: The Number of Manufacturers and Export Value by Sector, 1995-2008

Year

Woven garment sector Knitwear sector No. of No. of Export value Export value manufacturers (million USD) manufacturers (million USD) Total Per Total Per manufacturer manufacturer

1995/96

1646

1835

1.11

350

393

1.12

2000/01

2318

3364

1.45

1044

1496

1.43

2002/03

1997

3258

1.63

1229

1654

1.35

2004/05

1928

3220

1.67

1523

2536

1.66

2007/08

4076

5167

1.27

1500

5533

3.69

Sources: BGMEA (various years), Export Promotion Bureau (2005), and BKMEA (2005): Online: http://www.bkmea.com/facts_figures.php (accessed July 09, 2009).

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Table 3: Means of Entrepreneurs’ Background Attributes Data Traders

Manufacturers

40

92

Age (in 2005)

43.0

44.7

Years of schooling

15.2

15.0

Percentage of entrepreneurs with 16 years or more education

60.0

58.7

Years of prior experience in garment trading before starting the current business

4.0

3.8

2.1

3.6

8.9

n.a.

Years of prior experience in other sectors before starting the current business

n.a.

2.0

Percentage of entrepreneurs who received formal training in garment business abroad

17.5

6.5

Years of operation of the current business

9.8

6.8

Number of sample entrepreneurs

Years of prior experience in garment production before starting the current business Years of prior experience in working at a foreign venture before starting the current business

“n.a.” indicates that data are not available. Few sample traders had worked in other sectors and few sample manufacturers had worked at foreign ventures.

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Table 4: Means of the Trading Enterprise Data by Period of Entry Period of Entry By 1994 1995-99 2000 and onwards No. of Traders 16 16 8 No. foreign trading houses 1 3 1 Number of workers 1998 16.0 2002 22.6 17.0 2005 27.6 20.2 20.2 Export earnings (million USD) 1998 4.3 2002 4.4 3.4 2005 4.6 6.0 3.4 % traders hiring foreign experts 1998 31.3 2002 37.5 18.8 2005 43.8 18.8 12.5 Percentage of traders making samples 1998 68.7 2002 81.3 62.5 2005 81.3 87.5 37.5 Percentage of designs re-engineered 1998 8.8 2002 11.3 33.8 2005 24.4 41.3 12.5 Percentage of traders who own a garment factory 1998 31.3 2002 50.0 37.5 2005 50.0 68.7 37.5

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Table 5: Means of the Manufacturing Enterprise Data by Period of Entry

No. of Producers % producing sweater Number of workers 1998 2002 2005 Value added (million USD) 1998 2002 2005 Percentage of sales revenue from direct exporting 1998 2002 2005 Percentage of manufacturers with an international certificate 1998 2002 2005 Percentage of manufacturers hiring foreign experts 1998 2002 2005 Percentage of manufacturers with a composite factory 1998 2002 2005

By 1994

Period of Entry 1995-99

25 32.0

34 20.8

2000 and onwards 43 55.8

734.0 1287.0 1662.4

677.6 1306.3

939.7

3.1 4.6 6.3

3.0 3.6

3.1

48.1 58.0 65.8

32.9 45.6

40.4

12.5 64.0 76.0

45.8 66.7

34.9

4.2 20.0 32.0

8.3 12.5

18.6

25.0 28.0 40.0

4.2 16.7

13.9

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Table 6: Estimated Functions Explaining Behavior and Performance of Traders (1) (2) (3) (4) Fraction of Sample ln(Export Foreign Designs remaking revenue) expert engineered dummy employment Tobit Probit OLS Probit Years of schooling 0.05 -0.02 -0.001 -0.37*** (0.59) (-0.68) (-0.01) (-3.17) Prior formal training dummy 1.58*** 0.59*** 0.83*** -0.87** (3.68) (4.60) (4.60) (-2.22) Age -0.043* -0.02 -0.04** 0.04 (-1.71) (-1.49) (-2.11) (1.30) Years of prior experience in 0.03 0.015 0.03 0.12*** garment marketing (0.78) (0.83) (1.32) (3.28) Years of prior experience in -0.07* -0.01 0.02 0.083* garment production (-1.91) (-0.57) (1.07) (1.85) Years of operation 0.13*** 0.04*** 0.15*** 0.09*** (4.76) (3.11) (6.28) (4.04) Foreign trading house 0.60 1.67*** 1.01*** 2.58*** dummy (1.49) (8.58) (5.19) (5.21) Foreign venture experience -0.65** 0.41*** 0.19 0.009 dummy (-2.48) (3.89) (1.01) (0.04) Year 2000 dummy -0.03 -0.013 0.05 -0.35 (-0.22) (-0.04) (0.18) (-0.81) Year 2002 dummy -0.02 -0.18 -0.01 -0.51 (-0.14) (-0.49) (-0.03) (-1.22) Year 2004 dummy 0.04 -0.20 0.08 -0.82* (0.28) (-0.50) (0.26) (-1.92) Year 2005 dummy 0.14 0.07 0.15 -0.84** (0.95) (0.18) (0.45) (-1.97) Constant 0.52 0.19 14.6*** 2.29 (0.32) (0.29) (12.29) (1.60) 176 176 176 176 N Left censored 107 Right censored 19 0.38 R2 Numbers in the parentheses are the t- or z- statistics based on heteroskedasticity-robust standard errors. ***, **, * indicate the 1, 5, and 10 percent significance levels, respectively.

35

Table 7: Estimated Functions Explaining Manufacturers’ Direct Exporting and Traders’ Sales Revenue, Growth, and Entry into Manufacturing (1) (2) (3) (4) Manufacturer’s Trader’s Trader’s Trader’s own direct ln(revenue) ln(revenue) factory exporting dummy Tobit OLS OLS Probit Years of schooling 0.16*** 0.043 -0.006 0.21** (5.90) (0.34) (-0.22) (2.15) Prior formal training 0.17 0.39 0.05 0.68** dummy (0.92) (0.95) (0.52) (2.06) Age 0.01 -0.04 -0.02*** -0.02 (0.86) (-1.34) (-2.92) (-0.86) Years of prior experience -0.001 -0.006 0.008 0.07** in garment production (-0.13) (-0.10) (0.54) (2.03) 0.0097 -0.01 0.001 0.09*** Years of prior experience (1.31) (-0.15) (0.12) (2.63) in garment marketing -0.009 Years of prior experience (-1.09) in other sectors Foreign trading house 0.22 0.053 -0.61** dummy (0.54) (0.54) (-2.30) Foreign venture 0.67* 0.33*** -0.61** experience dummy (1.89) (3.16) (-2.30) Years of Operation 0.06*** 0.002 0.004 0.07*** (6.50) (0.05) (0.36) (2.58) Sweater dummy 0.67*** (6.81) Year 2000 dummy -0.15 0.04 (-0.94) (0.12) Year 2002 dummy -0.14 0.012 0.19 (-0.91) (1.20) (0.54) Year 2004 dummy -0.13 0.143 0.28 (-0.88) (1.19) (0.78) Year 2005 dummy -0.12 0.065 0.67* (-0.81) (0.58) (1.78) Lagged dependent 0.48*** 0.76*** variable (3.64) (14.04) Constant -2.45*** 8.91*** 4.60*** -3.73** (-5.32) (3.82) (4.44) (-2.42) 341 33 136 176 N Left censored 83 Right censored 114 0.56 0.87 R2 Numbers in the parentheses are the t- or z- statistics based on heteroskedasticity-robust standard errors. ***, **, * indicate the 1, 5, and 10 percent significance levels, respectively.

36

Table 8.

Estimated Functions Explaining the Size and Growth of Manufacturing Enterprises. (1) ln(value added)

Years of schooling Prior formal training dummy Age Years of prior experience in garment production Years of prior experience in garment marketing Years of prior experience in other sectors Years of Operation Sweater dummy Year 2000 dummy Year 2002 dummy Year 2004 dummy Year 2005 dummy

(3) Int’l certificate

OLS 0.15*** (3.34) 0.01 (0.04) -0.01 (-1.05) 0.07*** (5.77) 0.03*** (3.80)

(2) ln(current number of workers) OLS 0.08*** (4.41) -0.31** (-2.55) -0.02*** (-2.87) 0.05*** (6.60) 0.02*** (3.58)

0.034*** (3.48)

0.04*** (6.29)

0.04** (2.42)

-0.013 (-0.50)

0.03* (1.84)

0.01 (1.07)

0.10*** (8.27) 0.76*** (5.44) -0.22 (-0.84) -0.17 (-0.70) -0.03 (-0.16) 0.25 (1.20)

0.09*** (11.38) 1.21*** (15.80) 0.10 (0.69) 0.24* (1.78) 0.36*** (2.71) 0.51*** (3.80)

0.09*** (3.58) 0.54*** (2.96) 0.79* (1.81) 1.80*** (4.25) 2.01*** (4.86) 2.01*** (4.92)

0.052** (2.30) 0.95*** (3.74) 0.08 (0.19) 0.38 (0.91) 0.41 (1.04) 0.70* (1.82)

0.04 (1.36) 0.57** (2.59)

-0.06** (-2.43) 0.79*** (4.24)

ln (value added in 2000)

Probit 0.35*** (6.40) 1.25*** (3.32) -0.03*** (-2.62) 0.03* (1.88) 0.03** (2.55)

(4) (5) Foreign ln(value expert em- added in ployment 2005) Probit OLS 0.09 0.19*** (1.25) (3.75) 1.01*** -0.53 (2.85) (-1.15) 0.002 -0.01 (0.14) (-1.04) 0.03* 0.04** (1.85) (2.04) 0.023 0.01 (1.50) (0.64)

(6) ln(initial number of workers) OLS 0.02 (0.38) 0.03 (0.09) 0.01 (0.88) 0.04** (2.08) 0.034** (2.00)

0.49*** (5.63) Constant 11.28*** 4.19*** -6.95*** -4.12*** 11.82*** 4.47*** (14.61) (12.79) (-6.92) (-3.36) (13.72) (6.78) 341 341 341 341 53 92 N 0.31 0.59 0.69 0.37 R2 Numbers in the parentheses are the t- or z-statistics based on heteroskedasticity-robust standard errors. ***, **, * indicate the 1, 5, and 10 percent significance levels, respectively.

37

Figure 1: Real Manufacturing Wage in Bangladesh, 1983/84 to 2005/06 (1969/70 = 100)

200 180 160 140 120 100 80 60 40 20 0 1983/84 1987/88 1991/92 1995/96 1999/00 2005/06

Sources: Statistical Yearbook of Bangladesh (various issues) and Rushidan Islam Rahman (2009) “An Analysis of Real Wage in Bangladesh and Its Implications for Underemployment and Poverty” Online: http://www.peri.umass.edu/fileadmin/pdf/ conference_papers/khan/Rahman_Bangladesh.doc (accessed on July 25, 2009).

38