Honesty, Diligence, and Skill
Risk Sharing and Specializationin the Kiryu Silk Weaving Cluster, Japan*
ISS Discussion Paper Series
F–166
December 2013This version: July 2016
Masaki Nakabayashi†
Institute of Social Science
The University of Tokyo

Abstract
Many economies have seen growth in industrial clusters during their industrialization,and the relational contracts between manufacturers and subcontractors are often the organizational basis of clusters. We predict that, if manufacturers form relational contracts
with subcontractors and if manufacturers closely collude when trading with subcontractors, then premium subcontractors suffer more from market volatility than ordinary subcontractors and hence it is optimal for manufacturers to shield premium subcontractors
against the risk. We then study Kiryu, a kimono weaving cluster that expanded from thelate nineteenth century with the development of new synthetic dyeing techniques. We
show that premium subcontracting weavers were allowed long-term relational contracts
and specialization, which shielded already honest weavers against market volatility andinduced them to be diligent and to acquire skills.
Key words: industrial clusters; relational contracts; putting-out system; risk sharing;textile industry; Japan.
JEL: O12; O14; L14.

* This research has been funded by a JSPS Grant-in-Aid (22243022).
†

The author appreciates helpful the comments from the participants of the Canadian Development Economics
Study Group Sessions of the Annual Conference of the Canadian Economic Association 2014. Corresponding
address: Institute of Social Science, The University of Tokyo, Hongo 7–3–1, Tokyo 103–0033, Japan. E-mail:mn@iss.u-tokyo.ac.jp

Introduction
There is a developing awareness that in addition to large-scaled factories, clusters of small
manufacturers can be a driving force of industrialization, as has been increasingly observed indeveloped or emerging economies.1
While technological economies of agglomeration, as defined by Marshal (1920), are widely
observed,2 it is known that organizational efficiency affects clusters’ overall performance.
Furthermore, the path-dependent effects of organizational efficiency sometimes dominate thetechnological economy of agglomeration when clusters were formed, as discussed by Rosenthal and Strange (2003) and Buenstorf and Klepper (2009). In particular, social interactions
and networks have a significant impact on efficiency within industrial clusters in developed
economies,3 as well as in emerging economies.4 This study also addresses the implicationsof social interactions (or relational contracts) within industrial clusters, focusing on the risk
attitudes of small subcontractors organized by manufacturers.
To this end, this study deals with nineteenth-century Japan, when the economy grew froma vibrant emerging economy to become an industrial giant. Japan became the world’s largest
exporter of raw silk in the 1900s, and of cotton goods in the 1930s. Thus, the silk-reelingand cotton spinning industries, based on the factory system, were the driving force behind thecountry’s industrialization. At the same time, growth in the mass demand for high-quality
cloth during the period of industrialization and urbanization resulted in the emergence of
weaving clusters, rather than large factories. Thus, weaving clusters became another engine
1

For Western countries, see Piore and Sable (1984), Sable and Zeitlin (1997), and Becchetti and Rossi(2000)); for Japan, see (Hashino and Otsuka (2013a, 2013b); for Taiwan, see Sonobe and Otsuka (2006); forIndonesia, see Weijland (1999) and Sandee and Rietveld (2001); for China, see Ruan and Zhang (2009) andLong and Zhang (2012); for Vietnam, see Nam, Sonobe and Otsuka (2010) and Kimura (2011); for India, see
Chari (2000); and for Ethiopia, see Sonobe, Akoten and Otsuka (2009), Zhang, Moorman and Ayele (2011), Ali
and Peerlings (2011), and Gebreeyesus and Mohnen (2013).
2
See Morrison and Siegel (1999) and Ellison, Glaeser and Kerr (2010)
3
See Guiso and Schivardi (2007), Yamamura (2009), and Rosenthal and Strange (2012).
4
See Weijland (1999), Sandee and Rietveld (2001), Miguel, Gertler and Levine (2005), and Gebreeyesus andMohnen (2013).

1

of growth by meeting this urban consumer demand.
The growth in urban consumption created a new demand for a greater variety of highquality, but not expensive kimono brocades. This demand was met by weaving clusters, which
introduced synthetic dyes and systematic patterns from the West, while keeping to their flexible putting-out system. This study centers on a representative kimono weaving cluster, namely
the Kiryu region of the Gunma prefecture, near Tokyo,which was the largest consumer of thesegoods. In Kiryu, kimono manufacturers expanded their network of subcontracting weavers
rather than employing them in their own factories.
The kimono manufacturers’ choice to subcontract weavers is not a technological puzzle.
It is likely that the technologically optimal size of the high-mix, low-volume production of
final goods, such as fabrics, was smaller than that of uniform intermediate goods, such as
silk or cotton yarns. However, this does not necessarily mean that technologically efficient,
decentralized organizations always outperform centralized organizations under asymmetric
information. Imperfect information about weaver agents’ actions after concluding puttingout contracts might result in a moral hazard of weavers, as emphasized by Landes (1986).
In addition, risk sharing might matter, as argued in this study. For a cluster of putting-out
contracts to work, specific organizational devices are intrinsically indispensable.
The rise and fall of the Kiryu cluster as technology evolved over the longer term is described well by Hashino (2005) and Hashino and Otsuka (2013a). This study analyzes theorganizational characteristics of the Kiryu cluster at its peak, between the 1890s and the 1900s.
The rest of the paper is organized as follows. Section 1 briefly describes the developmentof the Kiryu silk weaving cluster.
Section 2 introduces a simple model to capture the organizational structure of the cluster,which we test empirically. Our benchmark is standard infinitely repeated game settings, suchas Greif (1983). However, we also add the risk attitudes of weaver agents, which generate
different implications to those from the standard settings. Typical trigger strategies or rela-2

tional contracts in infinitely repeated game settings can be self-enforcing precisely because
both players have something to be lost if they deviate—quasi-rent. Such rent could be earnedin our case when manufacturers and subcontractors produced premium kimono piece goods.
However, subcontractors who produced ordinary pieces using arms-length transactions in acompetitive market had nothing to lose, in either a boom or a downturn. Thus, it follows that
subcontracting weavers who produced premium products were vulnerable to market volatility
because they then had something to lose and, hence, suffered more. Our model captures thisfeature. An insight from our model is that subcontracting weavers of premium products suffer more when collusion among manufacturers performs well. Related to this point, anothernoteworthy prediction is that greater collusion among manufacturers could curb the subcontracting fee for honest premium weaving, but only if the order volatility is constrained beneatha certain threshold. Standard settings emphasize the possible punishment of dishonest agents.
Instead, our model finds that premium subcontractors should be guaranteed stable trades.
Section 3 empirically documents whether our prediction holds by examining contemporary material from the early 1900s, on which manufacturers shared information about theirsubcontracting weavers. Manufacturers tried sharing information, not about cheating subcontractors, but about excellent subcontractors. If the intention of information sharing was to punish cheaters, this is counter intuitive. However, if manufacturers wanted to limit their orders
to excellent subcontractors when demand shrank and, thus, reduce the compensation of risk
paid to honest premium subcontractors who suffered more from demand volatility, then this isconsistent with our theoretical prediction. Evidence also shows that long-term repeated transactions affected diligence, not honesty, and that specialization led to acquiring more skills.
On the equilibrium path, whether to be honest was not an issue, because any cheaters had
already been excluded. After excluding cheating weavers, an urgent issue was to diminish
the volatility burden on their premium weavers, typically by continuing transactions, because
when collusion among manufacturers worked well, honest premium weavers suffered more3

from the order volatility. Responding to this shield against market volatility, subcontracting
weavers showed diligence and commitment to such relational contracts, as our model predicts.
While specialization in a specific product is a less costly way for subcontracting weavers toacquire better skills, it potentially meant greater exposure to the risk of market volatility. Thus,
subcontracting weavers were only motivated to specialize in a specific product if they wereshielded from this volatility.

1

Formation of an industrial cluster

1.1

Silk weaving industry of Kiryu

Since the mid-1880s, the factory system rapidly diffused among the silk-reeling, cotton spinning, cotton weaving, and, in some regions, silk weaving industries. However, in Kiryu, thesilk weaving industry was not dominated by the factory system during this period, but mostmany manufacturers chose to keep the putting-out system. This maintenance of the traditionalorganization did not imply stagnancy in the silk fabric industry in Kiryu. Rather, production
grew in line with the domestic demand from Tokyo. Region-level data reveal that both thetraditional weaving and traditional hand silk-reeling industries grew. The putting-out system,
which organized hand-loom weavers, continued to dominate. In contrast to Kiryu, in the cityof Fukui, in the Fukui prefecture, silk weaving factories with power-looms prevailed, using
machine-reeled raw silk, or filature. Fukui mainly produced cheap habutae, a non-dyed silk
fabric with a plain weave, which was exported to the United States. Power-looms were easily
used to weave plain, white silk fabrics.5
The silk fabric industry emerged in the mid-eighteenth century in Kiryu Town, in thestate of Kozuke, as well as neighboring areas. The industry then developed remarkably after
the early nineteenth century, mainly stimulated by demand from the Shogunate capital, Edo,5

See Hashino and Otsuka (2013b).

4

which was later renamed Tokyo after the Meiji Restoration.6 Kozuke was also renamed theGunma prefecture.
Raw silk was Japan’s most important export after Japan joined international free trade in1859. Prior to the early 1880s, most of the exported raw silk was hand-reeled and produced bypeasant agriculture in Northern Kanto, Chubu, and Southern Tohoku. Subsequent to the mid1880s, exports to the United States were dominated by filature, a product from the modernsilk-reeling industry, centered in the Nagano prefecture. This trend accelerated from the late
1880s onwards, when railway trunk lines built in East Japan greatly facilitated the supply of
cocoons (i.e., the raw material) from farmers to the silk-reeling factories.7 After this period,
the only areas in which traditional hand-reeling dominated were Kiryu, Maebashi, Ashikaga,
and Isezaki (see Figure 1), the cluster where the traditional silk fabric industry still grew.
INSERT Figure 1 HERE
In weaving clusters, given the conditions at the time, the cnoice of production organization
was between the putting-out system and the factory system.8 In the Kiryu weaving industry,
the factory system, equipped with hand-looms, had been chosen to weave luxury fabrics,9while the putting-out system was used for most other fabrics. This only changed when factories equipped with power-looms became dominant for most kinds of fabrics in the 1910s,
and later.10 Instead of being replaced, the putting-out system developed and dispersed within
Kiryu, especially from the 1880s to the 1900s, when the main products of Kiryu were yarndyed silk fabrics. “Yarn-dyeing” means material yarn is dyed before weaving. For luxury
piece-dyed fabrics that were dyed after weaving, the weaving was conducted inside the man6

See Kiryu Orimonoshi Hensankai (Editorial Committee of the History of Kiryu Weaving), ed (1935).
See Nakabayashi (2006, 2015).
8
See Hashino (2005) and Okazaki and Nakabayashi (2007).
9
See Kimura (1959a), pp. 385–399 and Kimura (1960), p. 137. In Ashikaga, luxury fabrics and exported
habutae (plain, white fabric) were also woven using the factory system and hand-looms. See Wasedadaigaku
Keizaishigakkai (Society for Economic History, Waseda University), ed (1960), pp. 208–300, Kosho (1963,1972) and Kawamura (1987, 1995).
10
See Tsujimoto (1978), p. 48, Kameda (1989), pp. 561–565 and Hashino (2005), p.19.
7

5

ufacturers’ workshops. In the production of yarn-dyed fabrics, adopting synthetic dyes andsystematic patterning made it possible to modularize dyeing, arranging warps, cleaning yarn,
throwing, re-reeling, other preparation processes and the weaving process. Because these processes needed special skills, the craftsmen who specialized in each process were organized as
subcontractors by the manufacturers.11
With the move from the production of traditional piece-dyed fabrics to the production of
yarn-dyed silk fabrics, the throwing, finishing, designing, and weaving processes came to be
put out. Manufacturers decreased production in their workshops and established subcontracting relations with independent artisans.

1.2

Diversified demand in the market

Products ranged from the traditional luxury piece-dyed fabrics, which included ryumon (patterned fine gauze), sa aya (gauze), and chirimen (crepe), to the yarn-dyed fabrics that developed after the mid-nineteenth century, and fabrics that were a mixed weave of silk and cotton.
The luxury piece-dyed fabrics were woven from hiraito (flatly thrown silk yarn), which was
produced in Omama Town, Yamada County, while the yarn-dyed fabrics and the mixed fabrics
were woven from ordinary hand-reeled raw silk and cotton yarn. Some weavers also copied
specialties from other weaving districts, such as Nishijin in the Kyoto prefecture, Yonezawa in
the Yamagata prefecture, Chichibu in the Saitama prefecture, and Hachioji in the Kanagawa
prefecture. This broad list of products indicates that Kiryu manufacturers made an effort todiversify their product.12
INSERT Table 1 HERE
Until the 1900s, the production of yarn-dyed fabrics such as kaiki (lustrine), shusu (satin),shuchin (satin), and habutae (plainly woven) increased to become a large portion of total
11
12

See Kimura (1959a, 1959b, 1961) and Kawamura (1983, 1991).
See Nakabayashi (2007), pp. 133–137.

6

production (see Table 1).13 Note that the components and the region’s total output changed
every year, which indicates that the cluster faced a highly volatile and, in that sense, risky
market. The demand for silk fabrics was highly responsive to business cycles and, naturally, tofashion trends. Luxury piece-dyed fabrics, such as ro (fine gauze, leno), were mainly shipped
to Kyoto, while the yarn-dyed fabrics, such as shusu (satin) and shuchin (satin), were destinedfor the larger cities, such as Tokyo and Osaka. The yarn-dyed products contained fabric lowerpriced than the piece-dyed fabrics, but the “high-quality” shusu (satin) destined for Tokyo
suggests that the demand for yarn-dyed fabrics in the larger cities ranged from the low end tothe high end.14
In general, in larger cities, especially in the Tokyo metropolitan area, mass consumers
came to demand higher quality and more diversified fabrics from the 1890s onwards. This
accompanied an increasing level of industrialization and urbanization. Thus, the more diversified fashions, composed of various materials, textures (combinations of warp and weft), anddyes, came to be supplied by weaving districts.15 Kiryu was an example of the response to
the change in demand in Tokyo and Osaka, producing more yarn-dyed fabrics such as shusu(satin).
For a greater variety of products, power-looms were still irrelevant until the 1910s, because they were difficult to apply to weaving yarn-dyed fabrics, such as patterned cloths,
striped cloths, and broad sashes, which were primary products of Kiryu.16 Instead, synthetic
dyeing, rather than the power-loom, was critical to realizing the greater variety of fabrics in
13

For a detailed description of the 1900s and for production statistics that cover a longer period, see
Nakabayashi (2007), pp. 133, 138–139, 142.
14
Of the total sales in Kiryu in 1886, 55 percent went to Tokyo, 17 percent to Osaka, 12 percent to Kyoto, and4 percent to Nagoya in the Aichi prefecture (Kiryu Orimonoshi Hensankai (Editorial Committee of the Historyof Kiryu Weaving), ed (1938), pp. 553–554). In about 1900, the “biggest of the domestic destinations ... is the
Kyoto-Osaka area, followed by Tokyo. Of the total domestic sales, 70 percent goes to the Kyoto-Osaka area andNagoya, and 30 percent goes to Tokyo, ..., the many obi ji (fabrics for broad sashes for kimonos), han eri ji (fordecorative collars) and shusu (satin) are destined for Osaka, with mainly ro and chirimen going to Kyoto, andshusu, shuchin (satin), and other high-quality fabrics going to Tokyo” (Kawamoto, Miura and Ando (1901), p.
222).
15
See Tamura (2004), pp. 177–210.
16
See Minami and Makino (1983).

7the traditional weaving industry.17 If the technologies for the greater variety of products generated more profit than those for the mass-production of intermediate goods, such as plain,
white fabrics, producers naturally chose the former option. Furthermore, the inapplicability of
power-looms implied that sunk costs of weavers were accordingly lighter. If lower sunk costs
relative to the thickness of the market are accompanied by a less vertically integrated production organization, as discussed by Langlois (2003), the dominance of hand-looms, along withthe growth in mass demand in Tokyo, might have favored the horizontal network of putting-out
contracts.
As an example supporting our inference, we take the number of articles related to techniques and technologies of the fabric industry published in Kiryu no Kogyo (Manufacturingof Kiryu), issued by Kiryusha, an industrial body established by weaving and dyeing manufacturers in 1898. During the period 1900–1903, articles related to designs, including dyeing,
patterning, and texture, were predominant.18 Dyeing technique such as alizarin and anilin wererelated to colors, patterning meant a combination of patterns and colors, and texture was related to the combination of warp and weft that resulted in different looks for the cloth surface.
In the early 1900s, manufacturers in Kiryu were more interested in techniques and technologies that could be applied to extend a variety of fabrics rather than those for mass-producing
plain fabrics. Moreover, the Commercial and Industrial Association of Kiryu (Kiryu Sho Ko
Dogyo Kumiai) wanted to have an institute of research and education especially dedicated todyeing, and so established the Textile School of Kiryu Town (Kiryu Cho Ritsu Kiryu Orimono Gakko), a school for apprentices. This school was later extended, becoming a formal
secondary school, and was renamed the Kiryu Textile School of the Prefecture of Gunma(Gunma Ken Kiryu Orimono Gakko) in 1900. The Textile School surveyed designing anddyeing methods in Western countries and systematically taught them to apprentices. It also
17
18

See Tamura (2004), pp. 133–175.
See Nakabayashi (2007), pp.142–143.

8

affiliated a Special Program (Bekka) for craftsmen for dyeing and weaving.19
Thus, manufacturers collectively introduced the knowledge of synthetic dyeing and systematic patterning from the West, which was essential to realize the new standard of variety
from the West, and openly shared the critical knowledge by establishing a technical school, as
discussed by Hashino and Kurosawa (2013). This externality is thought to have prompted thevertical separation of production and the modularization through the network of putting-out
contracts, as described in Langlois and Garzarelli (2008). Furthermore, the strong technology
externality may have decreased individual manufacturers’ incentives to invest in technologies
and techniques, as discussed by Duranton (2000). A joint investment in a technical school
could have been a way to avoid such a trap, while deepening the vertical separation.
Both the synthetic dyeing and systematic patterning techniques enabled the modularization of the preparation processes, such as the dyeing process, and the weaving process. Greater
diversity of products became less costly and created a greater demand. The change was swift.
While most weaving manufacturers dyed their products in their workshops in 1900, by 1904,
subcontracting dyers were predominant.20 The rapidly expanding subcontracting of the dyeing process was part of an extension of the putting-out system that affected both dyers andweavers.

1.3

Development of the putting-out system

In Yamada County, which included the Kiryu Town, the number of power-looms actually
decreased from the 1900s to the early 1910s, a stark contrast to the overall trend in the Gunma
19

See Nakabayashi (2007), p. 144.
In 1900: “Dyeing is conducted by the special method of each weaving manufacturer so that there is no
independent dyer” (Kawamoto et al. (1901), p. 228). In 1904: Putting-out [of dyeing] had not previously been
conducted in Kiryu, but during this time the weaving industry became much more complicated. As a result,each weaving manufacturer could not afford to worry about dyeing, and improvements in dyeing have become
necessary. Therefore, independent specialized dyers emerged” (The Prefecture of Gunma, Third Department(1909), p. 88). There were seven independent dyers, four of whom owned boilers for heating (The Prefecture ofGunma, Third Department (1909), pp. 88–89.
20

9prefecture (see Table 2 and Table 3).21 Another impressive feature of Yamada County is thatthe number of putting-out manufacturers dropped by half from 1905 to 1912, while the numberof subcontracting weavers increased during the same period. The result was that the numberof subcontracting weavers per putting-out manufacturer tripled (see Table 2 and Table 4). In
some subcontracting weavers’ households, more than one family members, were engaged in
the business. Hence, the number of subcontracting hand-looms and operatives was greaterthan that of households, as shown in Table 3.
This expansion of the putting-out system occurred at the same time as the increase in the
production of diversified yarn-dyed fabrics for the mass consumption in the large cities. Thus,
the expanding putting-out sector was a new phenomenon in the early twentieth century, being
stimulated by mass consumption, and became feasible because of the technological progressof synthetic dyeing, which enabled a greater variety of design.
INSERT Table 2, Table 3 AND Table 4 HERE
The weaving manufacturers (motobataya) purchased the yarn material, then either subcontracted with independent producers to weave the yarn or weaved it themselves in their own
workshops. When subcontracting, a manufacturer first ordered patterns, followed by throwing, dyeing, warp setting, weaving, and the cleaning of products before shipment (see Figure2). Spatially, manufacturers were concentrated in Kiryu Town, while craftsmen/women werein Kiryu and in the surrounding areas.22
INSERT Figure 2 HERE
21
In the Gunma prefecture, the number of factories equipped with power-looms steadily increased throughthe 1900s to the early 1910s. See Nakabayashi (2003a), pp.39–41, Tables 1–9 (a) and 1–10 (a).
22
“Subcontractors include those who design (and make patterns), prepare looms, weave, throw, and so on. Of
these, subcontracting weavers and throwsters prospered, and in most small streets in Kiryu, you could hear thesounds of shuttles. In addition, in Nanbu Shinjuku of Kiryu, there are a great many throwing houses equippedwith water wheels along a ditch. Furthermore, every house with a thatched roof in the neighboring villages has aloom so that weaving was conduced” (Kawamoto et al. (1901), p. 225).

10

In 1900, the subcontracting weavers usually wove on looms that they owned, using reeds
and heddles they leased from the manufacturers to which they were subcontracted. These
subcontracting weavers worked mainly on yarn-dyed fabrics, such as shusu (satin) and kaiki(lustrine).23

2

The model

2.1

Advantages and disadvantages of the putting-out system

The advantages of the putting-out system were largely strategic. A survey report by the prefectural government of Gunma summarized the advantages and disadvantages of the putting-out
system, where subcontractors conducted production processes, as opposed to the factory system, where employed workers did the same:24
Document 1...advantages of having subcontracting weavers are that it
1. can flexibly increase or decrease [manufacturers’ own] business dependingon market circumstances and manufacturers’ conditions [compared with thefactory system].
2. can save on the costs and effort of maintaining looms, facilities, and factories
which would be necessary under the factory system.
3. can make it unnecessary to retain slack female workers when sales fall or
profits are not earned.
23“Most subcontracted weaving is that of shusu, while kobai kaiki and mon habutae (plainly patterned) arealso subcontracted. ..., generally, the weaving of fabrics that do not need power-looms is subcontracted, with
only the reeds and heddles being leased to subcontractors, making them to weave using their own looms... Sometimes looms are also leased. As is usually seen in other textile regions, prepared warp with weft is consigned”(Kawamoto et al. (1901), p. 225).
24
See The Prefecture of Gunma, Department of Interior (1904), pp. 61–62.

114. can save the recruitment costs, wages, and other expenses to employ female
workers and can produce large lots cheaply.
5. makes it unnecessary to specifically train female workers when changing the
production of fabric items.
The disadvantages include
1. harmful effects such as that subcontractors embezzling or collateralizing material yarns.
2. deteriorating quality of fabrics.
3. hardly standardized fabrics.
4. a failure to meet delivery times.
5. little monitoring the production process.
For high-mix, low-volume production, the optimal size of production in each process could
be small. Furthermore, in order to set or respond in a timely way to fashion trends, modularized and interchangeable processes, either yarn-dyeing or weaving, might be helpful. In thiscase, the putting-out system yield a technically efficient organization. The aforementioned
advantages are mostly still true for many modern industries.
However, once we consider producing the premium specialty of the Kiryu cluster and thephysical and human capital investment required to do so, the advantages are no longer necessarily consistent. For example, the first and the third advantages indicate that a manufacturer
did not provide job security for subcontracting weavers, which would have been provided to
employed weavers under the factory system. Then, the second and fifth advantages mention
that subcontractors themselves were expected to invest sufficiently in physical and humancapital. At the same time, the disadvantages suggest that manufacturers did recognize embezzlement and the laziness of some subcontractors under weaker monitoring, but still hired them.
12

The numbers of manufacturers and subcontracting weavers in Table 3 suggest that the market was extremely competitive for subcontractors. Thus, a straightforward inference would
be that some weavers who tended to cheat were often changed by manufacturers, such thatthe weavers did not earn quasi-rent in the competitive market. However, some weavers wereallowed to earn quasi-rent in the form of a higher subcontracting fee, which they could invest
in physical and human capital. To provide a rigorous understanding of this arrangement, webuild a simple model in the following section.

2.2

A model with risk-averse agents

Let wh denote the subcontracting fee for a premium fabric, ch the cost of a premium weave, wl
the subcontracting fee for an ordinary fabric, cl the cost of ordinary weaving, and q the probability of a contract in this period if the weaver had not cheated in the past. Here, by “cheat,” wemean that a weaver receives a fee for premium weaving, but weaves ordinary fabric instead,earning wh − cl . In addition,  ∼ N (0, σ 2 ) denotes a symmetric shock in the current period,
such as an unexpected cancellation or booking resulting from a demand shock. Note thatdemand shocks to the Kiryu cluster were considerable (see Table 1). In addition, d denotes
the discount factor. We assume that manufacturers are risk-neutral, but that subcontracting
weavers have a constant absolute risk-averse utility function, u(w − c) = − exp{−r(w − c)},where r denotes the absolute risk-averse coefficient. Then, letting CE and V denote the certainty equivalent and the discounted present value of future revenue, respectively, we haveu(CE) = − exp{−r(CE)} = E[u(V )] = E[− exp{−rV }]. Considering the competitivemarket condition for subcontracting weavers (4,000 weavers against 100 manufacturers in thelate 1900s; see Table 3), we further assume a zero quasi-rent condition for honest, ordinary
weaving, such that wl − cl = 0.
The structure of the game is as follows. In each period, weaver agents choose between
premium weaving, with a cost of ch , and ordinary weaving, with a cost of cl . If a weaver has
13always chosen premium weaving in the past, she/he is known as a premium weaver among
manufacturers, with a probability of q > 1/2. The subcontracting fee is determined at the
beginning of each period and paid as stipulated in the contract.
Then, we consider the following strategy.
• Manufacturers:
1. First period: Manufacturers offer the premium fee wh .
2. Second period and later:– If a manufacturer knows that a weaver has always chosen premium weavingin the past, then the manufacturer offers the premium fee, wh , to the weaver
in this period.
– If a manufacturer knows that a weaver cheated (chose ordinary weaving, earning wh − cl ) in the past on at least one occasion, the manufacturer offers theordinary fee, wl , to the weaver in this and future periods.
• Weavers:
1. First period: Weavers choose premium weaving.
2. Second period and later:– If a weaver is offered the ordinary fee, wl , she/he weaves an ordinary product.
– If a weaver is offered the premium fee, wh , the weaver chooses between premium weaving (honest) and ordinary weaving (cheat), such that his/her payoff
is maximized.
Then, the discounted present value of a weaver’s revenue stream from premium weaving,Vp , isVp = (1 + )(wh − ch ) + d [qVp + (1 − q)(wl − cl )] ,14

which is rearranged toVp =(1 + )(wh − ch ),1 − dqand hence
E[Vp ] =w h − ch(wh − ch )2 σ 2, Var[Vp ] =.
1 − dq(1 − dq)2

The discounted value of cheating, Vc (i.e., choosing ordinary weaving, but receiving a feefor premium weaving, wh ) in this period is

Vc = (1 + )(wh − cl ) + d [q(wl − cl ) + (1 − q)Vc ] ,which is rearranged toVc =(1 + )(wh − cl ),1 − d(1 − q)and, hence,
E[Vc ] =w h − cl(wh − cl )2 σ 2.
, Var[Vc ] =1 − d(1 − q)
[1 − d(1 − q)]2

Furthermore, the certainty equivalents of premium weaving, CEp , and cheating, CEc , aregiven as follows:

CEp = E[Vp ] − r

Var[Vp ]wh − ch r(wh − ch )2 σ 2=−
2
1 − dq2(1 − dq)2

and
CEc =

wh − clr(wh − cl )2 σ 2−.
1 − d(1 − q) 2 [1 − d(1 − q)]2

Then, the incentive constraint for honest premium weaving is
CEp ≥ CEc ⇔(1)wh − ch r(wh − ch )2 σ 2
w h − clr(wh − cl )2 σ 2−≥−.
1 − dq2(1 − dq)2
1 − d(1 − q) 2 [1 − d(1 − q)]2

15

2.3

Theoretical prediction

Let us assume that reservation value is 0, and, hence, individual rationality constraint is satisfied. Then we have the following lemma.
Lemma 1. Suppose that agent weavers are risk-neutral (r = 0). Then, the optimal fee forpremium weaving, wh∗ is decreasing in the degree of collusion between manufacturers, q , andin the discount factor, d.
Proof See Appendix I.

This is a reproduction of the conventional folk theorem, as in Greif (1983). If agents arerisk-neutral, more tightly collective punishment by manufacturers (greater q) simply decreases
the incentive to cheat, makes premium weaving a more stable equilibrium outcome, and lowers
the optimal fee, wh∗ , for premium weaving.
Next, we allow agent weavers to be risk-averse, r > 0, and assume that the difference incosts between premium and ordinary weaving is not negligible, such thatd(2q − 1)< ch − cl .
rσ 2Then, the incentive constraint equation (1) is rewritten as follows:(2)[[1 − (1 − q)d]ch + (1 − dq)cl ] rσ 2 + 2 [1 − d + (1 − q)qd2 ](2 − d)rσ 2[1 − (1 − q)d]ch − (1 − dq)cl≤wh ≤.
(2q − 1)dFirst, we show that premium weavers suffer more from risk when manufacturers better

cooperate with each other.
Lemma 2. There exists a collusion level q such that honest premium weavers suffer more fromorder volatility than cheating weavers do, only if q > q.
16

Proof See Appendix I.

A greater degree of collusion among manufacturers increased the urgency of stabilizingorders for honest premium weavers, for instance in an economic downturn or a change infashion trend. Otherwise, the risk compensation to be paid to premium weavers increases
asymmetrically in the order volatility σ 2 . In practice, it would be possible to share information
about premium weavers and to favorably allocate orders to them.
From equation (2), we have the following proposition.
Proposition 1. There exists a certain level of risk σ̄ 2 such that only if σ 2 < σ̄ 2 , the optimal fee
for premium weaving, wh∗ , is decreasing in the degree of collusion between manufacturers, q;
and otherwise it is increasing in q.
Proof See Appendix I.

A tighter collusion means the honest premium weavers suffer more from order volatility
σ 2 than cheating weavers do and wh is decreasing in the degree of manufacturers’ collusion q
only if σ 2 < σ̄ 2 ,A relational contract with earning quasi-rent is a kind of island in a competitive market.
This island could provide a strong incentive for premium weaving by potentially throwing
cheaters out to the competitive market, where quasi-rent could never be earned. At the sametime, because of this asymmetric payoff between being inside and outside the quasi-rent island, risk also asymmetrically affects premium weaving. In the conventional folk theorem
captured by Lemma 1, assuming the risk-neutrality of agents, tighter manufacturers’ collusion (greater q) always serves as a threat to potential cheaters. In other words, a long-term relationship between a manufacturer and a weaver would result solely in honesty by the weaver.
Meanwhile, Proposition 1 indicates that manufacturers must contain the risk associated withpremium weaving within a reasonable range. Only then a tighter collusion between manu17

facturers would make premium weavers more diligent, which in turn implies that premium
weavers would accept a lower equilibrium fee wh∗ while letting cheating weavers keep doing
ordinary weaving in the competitive market, where they cannot earn rent.

3

Empirical results and descriptive evidence

3.1

Data

As in other cases, there is little quantitative information on the honesty, diligence, and skillof small subcontractors. Fortunately, in the case of Kiryu, the association of silk fabric manufacturers, Kiryusha, issued a monthly periodical, Kiryu no Kogyo (Manufacturing of Kiryu),
later renamed to Orimono Kogyo (Weaving Industry) in 1903, in which issues in 1903 published introductions of subcontractors by manufacturers. Of the issues 53 to 63 in 1903, issues
53–58 and 61–63 are available to us. The introductions describe how diligent, honest, andskilled a particular subcontractor was, how many years the szubcontractor had traded withthe manufacturer, and whether the subcontractor had any specialty products. These introductions are highly qualitative, but we transformed them into quantitative values using themeasures described in Appendix II.25 Out out introduced features of weavers, “diligence” isnot a straightforward expression. However, provided that these introductions are expressedby profit-maximizing manufacturers, we can infer that a positive expression indicates a feature that contributes to profit. Here we interpret “diligence” as tendency to achieve the same
performance by being paid a lower fee.
From these introductions, we have data on 32 manufacturers and 189 subcontractors.
Three of the 189 subcontractors had long-term relationships with two manufacturers. Fourof the 189 subcontractors were throwsters, and the others were weavers. While the sample
size is quite small, given the total number of subcontracting weavers in the period, roughly25

For a summarized description of introductions in the documents, see Nakabayashi (2007), pp. 151–159.

18

4,000 (see Table 2), this is all we can know at this moment.

3.2

Diligence, honesty, and specialization

Table 5 regresses the degree of honesty (H, column 5–1), degree of diligence (D, column
5–2), and degree of skill (S, columns 5–3 and 5–4) on the male dummy variable (dm ), thedummy variable indicating whether both are Kiryu residents (dkk ), which takes the value 1
if both the manufacturer and subcontractor dwell in the Town of Kiryu as the administrative
district, the core of the Kiryu cluster, rather than in suburban areas and, hence, captures geographical closeness;26 the number of years of relational transactions (Y ); and the specialty
dummy variable (ds ), which takes the value 1 if a subcontractor has a specialty, such as shusu(satin) or kaiki (lustrine).
INSERT Table 5 HERE
The regression of honesty (H) in column (5–1) shows that years of relational transactions
do not affect it, and that geographical closeness (dkk ) has a significantly negative effect. The
former effect shows that on the equilibrium path, dishonest weavers, if any, had already been
excluded from the network of relational contracts, such that difference in existing relational
contracts did not affect the degree of honesty of existing relational subcontracts. The latter
effect indicates that geographical closeness on its own did not contribute to honest trades in
the Town of Kiryu. There, subcontractors intended to cheat, and manufacturers intended tobeat prices down in the competitive market. By doing so, neither party earned quasi-rent.
The regression of diligence (D) in column (5–2) shows that years of relational transactions contributed to an increase in diligence. The more stable transactions were, the morediligently subcontractors seemed to work. Job security intensified diligence. This result is
consistent with our theoretical predictions, Lemma 2 and Prediction 1, interpreting “diligence” as propensity to deliver a high performance with being paid a lower wage.
26

Note that most manufacturers were located in the Town of Kiryu.

19

The regression of skill (S) in column (5–3) shows that specialization in a specific product, as captured by the specialty dummy variable (ds ), contributed to skill acquisition. It wasessential to the skill acquisition of subcontracting weavers that manufacturers allowed themto specialize in a product or that they stabilized the order volume of a product to premium
subcontractors, which somehow shielded premium weavers from the volatile market (see Table 1). This is consistent with our theoretical prediction Lemma 2 that premium weavers are
more vulnerable to market volatility if manufacturers collude closely.
In summary, neither the duration of relational transactions nor geographical closeness promoted honest trades on the equilibrium path. This result does not mean that repeated transactions were not helpful in maintaining the honesty of subcontractors. In Kiryu, an establishedcluster, the prevention of cheating by the repetition of trades was already the outcome of adominant strategy because of the rent earned between premium manufacturers and subcontractors. This is why a regression model, which needs a variance from some off-the-equilibriumpath behaviors for identification, cannot find a significantly positive effect of the duration of a
relational contact or geographical closeness on the degree of honesty (H). Subcontractors who
were inclined to cheat and manufacturers who beat prices down traded fairly in the competitivemarket, outside of the relational trades earning quasi-rent.
On-the-equilibrium path, honest trades worked through a different channel. The regressionof skill (S) in column (5–4) clearly shows that the degree of honesty (H) and specialization(ds ) significantly contributed to skill acquisition. Honest weavers devoted themselves to skill
acquisition, rather than fearing punishment in the coming periods.
Although relation between honesty and skill acquisition is not addressed in our modeland hence we cannot give a strong reasoning, the multi-task principal agent model setting by
Holmstrom and Milgrom (1991) provides us with an insight. Effort for skill acquisition ishardly observed in a short-term contract. Thus, if stable contract and fee are guaranteed andrisk is reasonably contained, honest and proud agents would invest in the hardly observable20

activity, skill acquisition.

3.3

Smaller risk by better match?

Although dishonest behaviors were not very rare among subcontractors introduced in Kiryu
no Kogyo (Manufacturing of Kiryu),27 the greater part of the introduction was a descriptionof diligent or skilled subcontractors. The primary purpose of introducing subcontractors in
Kiryu no Kogyo does not seem to have been revealing information about cheating subcontractors and/or their punishment. The association of manufacturers in Kiryu did not exclude
multi-relational contracts between a subcontractor and manufacturers. The standard format
of a subcontracting contract, as designated by the Kiryu Weaving Association, stipulated thefollowing:28
Document 2
Clause 3
1. The consigner [manufacturer, by the quoter] promises following items.
· · · snip· · ·2. The consigner should report to the subcontractor when the consigning
party suspends the consignment of materials and cancels this contract
because of one’s own convenience.
· · · snip· · ·Clause 4
1. The subcontractor should honestly conduct the subcontracted process
beyond doubt and has the following obligations.
· · · snip· · ·27
28

See Matsumura (2002) and Nakabayashi (2007).
The Prefecture of Gunma, Department of Interior (1904), pp. 65–66.

21

2. The subcontractor should report to as soon as possible should he/she
decline the subcontract and cancel the contract.
· · · snip· · ·Furthermore, as the decreasing number of manufacturers in Table 4 shows, the market
was competitive for manufacturers as well. Hence, even if manufacturers wanted to enclose
skilled and diligent weavers, it was unlikely successful. Now that enclosure was impossible
anyway, it would be better to share information about skilled or promising subcontractors andto provide them with better match and job security. This, in turn, would encourage alreadyhonest weavers to work diligently and to acquire the necessary skills by specialization, as
predicted by Proposition 1 and Lemma 2, and as shown in columns (5–2), (5–3), and (5–4)
in Table 5. Furthermore, this would make the premium fee lower than would otherwise havebeen the case.

Concluding remarks
Our findings are not necessarily similar to standard repeated game settings. However, in successful relational trades in the real world, cheating is a dominated strategy and, hence, should
never explicitly emerge on the equilibrium path. Instead, it is recognized that it is critical totake care of risk-averse premium subcontractors. For instance, Toyota, the automobile manufacturer, holds rigorously stable long-term relationships with premium subcontractors only.
These subcontracting firms are already loyal and are referred to as “first tier,” and Toyota
does not necessarily care about potential cheaters. By holding stable long-term relationships
with “first-tier” subcontractors, Toyota does care about optimal risk absorption for “first-tier”
subcontractors.29
In real modern economies, outside of relational contracts earning quasi-rent, competitive
29

See Asanuma and Kikutani (1992).

22

markets dominate. Keeping marginal subcontractors from cheating is not essential to the profitability of the nexus of subcontractors, given the competitive markets. Cheaters might bereplaced immediately, or may be utilized by receiving a discounted fee in such a competitivemarket. This so-called globally optimal procurement by multinational companies is composed of the long-term relationships with premium subcontractors and the competitive purchases from others who may be operating anywhere in the world. The reliance on such global
procurement tends to be greater for more efficient multinationals.30 In such a real context, infinitely repeated transactions can increase the utility of trustable premium agents, rather thanpunishing cheaters. The Kiryu weaving cluster, which emerged in the late nineteenth century,
provides an early example of modern clusters as we now see in daily life.

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Appendix I
Proof of Lemma 1
Proof. The incentive constraint is as follows:
CEp |r=0 ≥ CEc |r=0
(AP1)

w h − chw h − cl≥1 − dq
1 − d(1 − q)
[1 − d(1 − q)] ch − (1 − dq)cl⇔wh ≥.
(2q − 1)d⇔31

Hence, the optimal contract, which is the least wh that satisfies (AP1), is
wh∗ =

(AP2)

[1 − d(1 − q)] ch − (1 − dq)cl,(2h − 1)d∂wh∗
(2 − d)(ch − cl )
=−
< 0,
∂q
(2q − 1)2 d

(AP3)

and
∂wh∗
ch − cl=−< 0,∂d(2q − 1)d2

(AP4)

where (AP4) holds under the assumption q > 1/2. (AP3) and (AP4) prove the lemma.

Proof of Lemma 2
Proof. The magnitude of risk associated with honest premium weaving Rh and that for cheating Rc is as follows:

(AP7)

Rh ≡

r(wh − ch )2 σ 2r(wh − cl )2 σ 2>≡ Rc
2(1 − dq)22 [1 − d(1 − q)]2

if

(AP8)

q>

ch − cl + (wh − ch )d≡ q.
(2wh − ch − cl )dProof of Proposition 1.

32

Proof. From equation (2), we have the optimal fee for premium weaving,

(AP5)

wh∗ =

[[1 − (1 − q)d]ch + (1 − dq)cl ] rσ 2 + 2 [1 − d + (1 − q)qd2 ],(2 − d)rσ 2

and

(AP6)

∂wh∗
(dch − dcl )rσ 2 + 2(d2 − 2qd2 )=≤0∂q(2 − d)rσ 22(2q − 1)d≡ σ̄ 2 .
⇔σ 2 ≤(ch − cl )r33

Appendix II Definitions of variables.
Variable
Definition
male dummydm=1 if the subcontractor is malevariabledummy variable of=1 if the manufacturer and the subcontractor reside in Kiryu Town, Yamada County, Gunmad kk both residents inprefecture
Kiryu
3 "very honest"; "extremely honest"; "loyal through thick and thin"; "very sincere."
2 "honest"; "loyal"; "behaviors are good"; "sincere";"behaviors are fairly good"; "neither good nor bad"; "behaviors are ordinary"; "ordinary"; no1
H Degree of honesty
description.
"a leader of fraud"; "embezzles weft"; "collateralizes weft"; "woven products sometime disappear";0 "pounds (of woven products) are unexpectedly light"; "not so good"; "pounds (of woven products)
are unexpectedly light in good times.""the most steady"; "is earnestly devoted to job"; "is devoted to job"; "faithful to job"; "faithfully";"is devoted to job through thick and thin"; "work diligently"; "conscientious through thick and3thin"; "really conscientious"; "very conscientious"; "is patiently and conscientiously devoted tojob."
D Degree of diligence"conscientious"; "works well and satisfies the manufacturer"; "conscientiously and diligently
2work"; "diligently work"; "is devoted to job"; "never tired of job."
1 "relatively diligent."
0 "neither good nor bad"; no description.
"products for competitive exhibition are ordered to"; "products are the best"; "products are
extremely fine"; "recent products for competitive exhibition are woven by"; "products are
3 especially fine"; "technique is very good"; "products are extremely good"; "the first subcontractor";"skill is very good"; "if the best products are necessary, they are ordered to"; "products are verygood"; "distinguished subcontractor"; "earnestly good".
S Level of skill"large amount and good quality"; "good quality"; "products are good"; "products are fine"; "good2"products"; "fine products"; "technique is fine"; "technique is good," "skill is good"; "skill is fine.""technique is fairly good"; "fairly good products"; "technique is fairly good"; "not the most skilled";
1"promising."

MedianMeanStandard deviation

1.00000.80210.39950.00000.47400.50061.00001.2656

0.61162.00001.66151.22152.00001.5156

1.17110 "ordinary technique"; no description.
Years of relational Described years or 1 if not mentioned. Maximum: 30, minimum: 1, mean: 7.5391, median: 5.0000,
Y5.00007.53917.3863standard deviation: 7.3863, skewness: 1.4224.
transactions
Specialty dummyds=1 if specialty product is mentioned and 0 otherwise.
0.00000.44270.4980variable
Source : Kiryu no Kogyo (Manufacturing of Kiryu) , no. 5358, Orimono Kogyo (Weaving Industry) , whose title was changed from Kiryu no Kogyo, no. 6163, 1903.

Table 1 Production of silk fabric in Kiryu Town, Yamada County, the Gunma prefecture: Decomposed to kinds of fabrics.
Year

Woven of Omama
HiraitoRo(Gauze)a

Othersm2

m2

Habutae(Plain)Kaiki(Lustrine)

Chirimen(Crepe)HakamaJi

Ito Ori

Fushi
Ito Ori

Shike
Ginu

m2

m2

m2

m2

m2

Rinzu
Shusu
(Figured(Satin)Satin)

Others

Total

b
m2

1,000
Yards

m2

1,000
Yards

m2

m2

m2

1,000
Yards

m2

1,000
Yards

1892
8,522
832
825,262
20,48038,451
0
5,632
0
0
0
0
63,565
962,744
1893
60,1785,133 2,059,648
24,55023,045
2,196
11,159
476
8,207
0
0
28,7512,223,345
1894 114,278
8,463
963,776
321,608
16,745
6,920
15,634676 182,477
5,635
0
42,545
1,678,756
1895 336,586 15,250
223,598
244,283
49,421
9,935
22,4671,533
46,8865,412
035,607990,979
1896 165,453
3,994
162,458
217,958
36,736
14,46475,520 12,800
31,13055,296
050,373826,1811897 133,862
3,968
178,790
233,728
40,858
8,192
72,960 16,640
29,44059,392070,272
848,1021898 127,027
3,750
187,149
312,576
36,014
3,072
90,880 16,128
34,5600
0 147,866
959,022
1899 122,138
0
1,395
3,532
36,014
6,016 132,454 15,040 143,759
28,288082,644240
566,354 5,166
1900 107,671
0
3,741
3,384
33,516
5,345
66,017 10,752
01,843 1,597 426,368
0653,110 7,125
1901 238,520
0808,115
83,38931,526
12,92872,371 13,312
02,125 6,400 209,818
1,478,505
1902 210,755
0595,251
91,13623,281
4,124
51,149 14,715
0
4,198 3,750 260,838
1,259,197
Source : Gunma Ken Tokei Sho (Statistics of the Prefecture of Gunma) , the prefecture of Gunma.
Notes : Hiraito is a flat-thrown silk thread. "Others" of "woven of omama hiraito " contain sha (gauze), ryumon , kame aya ori (patterned with hexagons), and kame mon ori (patternedwith hexagons). Handkerchiefs are not included in this table.

Table 2 Production organization of the silk fabric industry in Yamada County, the prefecture of Gunma.
Year
Total Number of
Number of operatives
Number of
Number of
Supporting operatives
Weaving operatives
subcontracting
looms
independent
weaving houses weaving houses
Male
FemaleMale
FemalePower Hand
1901
724
3,796 4,520
455 6,558
1,050
7,258
1902
714
3,691 4,405
168 6,307
1,026
7,132
1903
704
4,331 5,035
181 6,429
2,070
10,984
810
1,227
1904
468
2,751 3,219
167 5,629
903
1,946
1,884
7,928
Source : Gunma Ken Tokeisho (Statistics of the Prefecture of Gunma) , the prefecture of Gunma.
Notes : The difference in number of subcontracting weavers from that of Figure 2 in 1904 is presumed to come fromwhether counted at the beginning of 1904 (Figure 2) or at the end of 1903 (this table).

Table 3 Choice of the factory system in Yamada County, the Gunma prefecture.
Year Factory industry
Cottage industry
NumberNumberNumberNumberNumberNumberof factories of loomsof operatives of cottages of loomsof operatives
Power Hand Male Female
Power Hand Male Female
1905
39
152
438
58
648
302
0
898
37 1,078
1906
35
152
388
70
897
394
0 1,245
91 1,297
1907
33
173
418
59
876
418
0 1,367
95 1,447
1908
32
330
432
60
872
390
0 1,298
81 1,382
1909
41
356
503
54 1,005
423
5 1,369
64 1,463
1910
73
420
625
63 1,195385
0 1,291
60 1,384
1911
66
163
569
46
754
375
12 1,399
51 1,377
1912
59
204
555
33
816
377
12 1,357
35 1,341
Source : Gunma Ken Tokeisho (Statistics of the Prefecture of Gunma) , the prefecture of Gunma.

Table 4 Putting-out manufacturers and subcontractors in Yamada County, the Gunma prefecture.
Year Manufacturers putting-out weaving
Subcontracting weavers' households
NumberNumberNumberNumberNumberNumber of
manufacturersof looms
of operatives of weavers of loomsof operatives
Power Hand Male Female
Power Hand Male Female
1905
199
0
417
13
529
3,540
0 4,20265 4,630
1906
109
0
293
26
382
3,663
0 4,161
217 5,002
1907
139
0
388
37
468
4,034
0 5,650
263 5,562
1908
124
0
343
40
418
4,070
0 5,594
301 5,473
1909
97
0
280
24
446
4,155
0 5,439
293 5,433
1910
104
0
322
32
405
4,560
0 5,950
324 5,892
1911
70
0
0
0
0
4,713
0 6,176279 6,029
1912
99
0
76
21
76
5,337
0 7,347287 7,144
Source : Gunma Ken Tokeisho (Statistics of the Prefecture of Gunma) , the prefecture of Gunma.

Table 5 Honesty, diligence and skill of subcontractors in the Kiryu region, 1903.
53
54
51
52
Dependent variable
H (honesty)
D (diligence)
S (skill)
S (skill)
Ordered probit
Ordered probit
Ordered probit
Ordered probit
Estimation method
192
192
192
192
Number of samples
Independent variables
z -statisticz -statisticz -statisticz -statisticd m (male dummy)-0.3161 -1.4384-0.2677 -1.2530-0.1703 -0.8160
d kk (both in Kiryu dummy) -0.5177 -2.8444 *** 0.0772
0.4595-0.0995 -0.6042
0.01351.13420.02522.2838 **0.0064
0.5877Y (yeas of relation)d s (specialty dummy)
0.21351.21760.13130.7906
0.63813.8709 *** 0.5928
3.6208 ***0.38762.8445 ***H (honesty)
0.09691.4597D (diligence)2
0.04880.03610.01850.0326
Pseudo R-161.8096-218.6757-246.7317-242.6141
Log likelihood******
12.1275
8.2342
16.6326
24.8679 ***LR statistic
Source : Kiryu no Kogyo (Manufacturing of Kiryu) , no. 5358, Orimono Kogyo (Weaving Industry) , whose title waschanged from Kiryu no Kogyo , no. 6163, Kiryu: Kiryusha, 1903. ***, **, and * respectively denote significance of 1, 5,
10 percentage levels.

Figure 1 Kiryu silk weaving cluster.

Source: Produced by the author from copyright free sources created by Satoshi Ishida (url: http://www.tt.rim.or.jp/~ishato/tiri/huken/huken.htm: Last
visited on January 23, 2016).

Figure 2 Number of subcontractors in the Kiryu silk fabric cluster, 1904.

<1>

Weaver4,650

Cleaner
14

Pattern Maker
13

<5>
<6>

Manufacturers
199
shipping

<2>
<3>
<4>

Thrower
218
Dyer
17
Warp Setter
65

Source : Sucontractors: The prefecture of Gunma, Third Department(1909), pp. 217218. Manufacturers: The number in 1905 in Table 3.