The Evolution of an Industrial Cluster in China
C H L R W O R K I N G P A P E R S E R I E S 中国人力资本与劳动经济研究中心工作论文系列
The Evolution of an Industrial Cluster in China
Belton Fleisher
Dinghuan Hu
William McGuire
Xiaobo Zhang
Working Paper 12
December 2009
CHINA CENTER FOR HUMAN CAPITAL AND LABOR MARKET RESEARCH CENTRAL UNIVERSITY OF FINANCE AND ECONOMICS
中央财经大学中国人力资本与劳动经济研究中心
39 Xueyuan South Road, Haidian District, Beijing, China 100081
Web: https://www.docsj.com/doc/168924970.html,
Phone & Fax: 86-010-********
? 2009 by Belton Fleisher,Dinghuan Hu, William McGuire and Xiaobo Zhang. All rights
The Evolution of an Industrial Cluster in China1
November 24, 2008
Belton Fleisher
Department of Economics
Ohio State University
Columbus, OH 43210
&
China Center for Human Capital and Labor Market Research
Central University of Finance and Economics
Beijing, China
&
IZA
Email: fleisher@https://www.docsj.com/doc/168924970.html,
Dinghuan Hu
China Academy of Agricultural Sciences
China
Email: dinghuanhu@https://www.docsj.com/doc/168924970.html,
William McGuire
Department of Agricultural, Environmental, and Development Economics
Ohio State University
Columbus, OH 43210
Email: william.h.mcguire@https://www.docsj.com/doc/168924970.html,
Xiaobo Zhang
International Food Policy Research Institute (IFPRI)
Washington, DC
&
Zhejiang University
Email: x.zhang@https://www.docsj.com/doc/168924970.html,
Prelminary. Please do not cite without author permission.
1 The authors are grateful for the opportunity to present earlier drafts of this paper at the conference, Microeconomics of Growth, St Edmund’s Hall, University of Oxford; the Student/Faculty Seminar of the Center for Human Capital and Labor Market Research, Central University of Finance and Economics, and the Center for Chinese Agricultural Policy, Chinese Academy of Sciences, Institute of Geographical Sciences and Natural Resources Research. We particularly acknowledge the valuable suggestions of John Knight and Jikun Huang. Also we would like to thank Keijiro Otsuka and Tetsushi Sonobe for sharing the first-round survey questionnaire and data with us. Financial support for the surveys was provided by the International Food Policy Research Institute, Ohio State University Department of Economics and by the Ohio State University of Agricultural, Environmental, and Development Economics.
The Evolution of an Industrial Cluster in China
Abstract
We use two rounds of surveys, in 2000 and 2008, in the Zhili Township children’s garment cluster in Zhejiang Province to examine in depth its evolution. Firm size has grown on average in terms of output and employment, and increasing divergence in firm sizes has been associated with a significant increase in specialization and outsourcing among firms in the cluster. Although initial investments have more than tripled, they remain low enough so that formal bank loans remain an insignificant source of finance. Accompanying lower entry barriers, there have been an increasing number of firms in the cluster, which have driven down profit and bid up wages, particularly since the year 2000. Facing severe competition, more firms have begun to upgrade their product quality. By the year 2007, nearly half of the sampled had established registered trademarks and nearly 20 percent had become ISO certified. Declining profit ratios to initial investment and stagnant TFP imply that the future of this industry is likely to rest on using more advanced technology and higher ratios of capital to labor, which imply increases in firm size and initial investment. Thus traditional sources of finance that do not require honest, efficient, and transparent courts are likely to fade as the need for improved legal and financial institutions become critical factor influencing China’s growth prospects.
JEL Codes: L22, O14, P23
1. Introduction
China’s rapid rural industrialization seems to defy the conventional wisdom that high transactions costs imply vertical integration. Its rapid industrialization has been accompanied by the emergence of numerous “specialty cities” of a particular kind. Thousands of firms, large and small, many specialized in a finely defined production step, are agglomerated in a densely populated region, where some particular manufactured consumer good is churned out in millions (if not billions) annually. Many formerly rural towns in the coastal areas have become so specialized, boasting themselves as the world’s Socks City, Sweater City, Kid’s Clothing City, Footwear Capital, and so on. While these rapidly growing rural industries have been a major engine of China’s unprecedented economic growth in the last two decades, their role in the development and growth process can be easily oversimplified. Moreover there are warning signs that these industries’ role as a source of growth is reaching its limits. Competitive pressures at the global level, product market level, and on the labor market side are limiting output prices. At the same time, as China’s growing prosperity is reflected in real wage increases, manufacturing costs are rising because productivity rises do not keep pace with rising labor costs. Despite numerous popular media reports on these phenomena (for example Deering, 2008; Lee, 2008), few studies have rigorously investigated the mechanisms behind the emergence and evolution of these clusters.
The cluster-based rural industrialization described above not only plays a significant role in China’s industrial growth but has also been important in the early stages of industrialization in other East Asian countries and many European countries (Hayami, 1998; World Bank, 2008). Many clusters are initially formed as agglomerations of small and mediums-sized enterprises (SMEs) (Schmitz 1995; Schmitz and Nadvi, 1999). Because most SMEs are generally labor intensive, the cluster-based rural industrialization model is conducive to generating nonfarm employment and fits well the comparative advantage of many developing countries, which are often marked with low capital-labor ratios and high population density (Hayami, 1998). Therefore, it is important to study the mechanism of cluster formation in developing countries.
Most studies on the formation and evolution of clusters in developing countries are based on retrospective surveys and very few have tracked firm performance over a long period of time (Sonobe and Otsuka, 2006). In this paper, we make use of two rounds of surveys, in 2000 and 2008, in the Zhili Township children’s garment cluster in Zhejiang Province to examine the evolution of market structure and productivity in depth.2 Three decades ago, most people in this rural town were paddy farmers. Nowadays Zhili township embodies one of the largest children garment production centers in China and the world. In the year 2006, a trade report stated that there were over 5000 children’s garment manufacturers in Zhili Township (Wu, Yue, and Sim, 2007). In this cluster, the production of garments has been divided into very fine phases. Many of the production tasks are undertaken by family workshops. Recently, because of high labor and land costs, some enterprises have begun to subcontract production to firms in neighboring Anhui and Jiangxi Provinces. An in-depth cast study on the evolution of this rural industrial cluster can help shed light on an important source of China’s rapid industrialization and productivity growth over the past several decades as well as on its limitations.
We find that in the initial stage of cluster formation, because of lower capital and technology barriers to entry, competition in the product market was severe and formal education was not an important characteristic of owners/managers. China’s initial industrialization path since economic reform in the late 1970s has been labor-intensive (Lin, Cai, and Li, 2003). Recently, shortage of skilled laborers has become an increasingly frequent issue. In the later years covered in our surveys, we observe a drop in profit, which is driven not only by competition in the product market but also by rising labor costs. This pressure has induced firms to invest more in design, branding, ISO certification, and quality control so as to climb the value chain. An offsetting cost trend has been a tendency toward production specialization and outsourcing. We also find that TFP growth has been rather stagnant in the cluster over the past two decades. This suggests that reallocation of labor from the low-productivity agricultural sector to the more productive industrial sector has been a key driving force behind China’s rapid industrialization, rather than TFP growth within labor-intensive sectors.
2See Sonobe, Hu and Otsuka (2002) for a description of the first round survey.
In the next section we describe basic features of the Zhili children’s garment cluster; in section 3 we outline major aspects of the evolution of the Zhili cluster since 1990; section 4 draws conclusions and implications for China’s economic growth and development.
2. A Brief History of Zhili Cluster
Zhili Township is located in northern Zhejiang Province, close to Taihu Lake, between Hangzhou and Shanghai. Historically, Zhili was an important silk and weaving production center. The name of Zhili stands for “weaving town” in Chinese. Population density has been very high in Zhili for hundreds of years. In the planned economic era, because of rather limited land, agricultural income was far from sufficient. As a result, many farmers produced pillow covers and bedding at home to generate side income, even though this activity was illegal at the time and was called the “tail of capitalism”. Although the local government tried in many ways to oppress these private industrial activities, Zhili’s reputation as a bedding production center spread widely. After the central government adopted reform policies in the late 1970s, the local government reversed its opposition to private entrepreneurial activities. In the early 1980s, the local township government set up a bedding-product marketplace.
By the mid-1980s, the market for bedding products became saturated. Some Zhili merchants who were specialized in selling bedding products all over China conveyed back the market information that children’s garments were in short supply. This information stimulated a few farmers to start producing children’s clothes at home. Some family members were responsible for making clothes while others carried the clothes to various cities to sell them. Neighbors observed the success of the beginners and began to imitate them by producing children’s garments in their homes, and by the late 1980s, more than ten villages in Zhili Township were specialized in children’s garment production. The growing market facilitated the emergence of specialized merchants who purchased children’s clothes produced in Zhili and sold them in rented counters in department stores all over China. Meanwhile, several wholesale marketplaces of children’s garment were set up in the Zhili town center. This division of labor accompanying the growth of the industry immediately reminds one of the insights of George J. Stigler (1951).
Since the 1990s, specialization has spread to the production process itself. Many farmers moved their production to the Zhili town center. They either bought or rented a three-story house combining the function of living, dining and working. The first floor usually was a store, while production was concentrated in the second floor. Workers slept in the third floor. Although the rent was much higher in the Zhili town center than in nearby villages, these costs were more than offset by agglomeration benefits, including those arising from better market information and reduced marketing costs and access to a centralized labor market. Another benefit arising from centralization of production arose from a signal of quality and reliability. Having a storefront house sent a strong signal of credibility and quality to merchants who came from outside the local market area. By 1999, there were already about 1800 such “three-in-one” workshops. These stores mainly sold their own products, which were regarded being higher quality than those produced in dispersed farmers’ houses in nearby villages.
The success of Zhili’s business model attracted more merchants to order children’s garments in either the wholesale markets or storefronts of the workshops. In 1999, the wholesale markets sold 75 million units with sales of 1.4 billion yuan. In 2000, to meet the rapidly increasing demand, the township government built the eighth wholesale marketplace. The products from nearby villages, which were generally of lower quality than those produced in the storefronts, were primarily sold in these wholesale markets. Fierce competition led to lower prices and profit margins in the whole markets, and many producers responded by relocating to the town center. Of course, the increasing demand for the preferred locations drove up housing prices, which approximately doubled between 1995 and 2000. Thus entry-level capital requirements were rising apace.
In addition to the rapid development of wholesale markets, related businesses, such as button and zipper production workshops, computer design studios, machinery sales and repairing stores, packaging and logistical services, also emerged. The town center was expanded from a narrow, 0.5 kilometer street to an area of four square kilometers, including two three-star hotels, over three dozen small hotels, and hundreds of restaurants. By 2005, Zhili had over 6000 enterprises engaged in children’s garment
production, employing over 200,000 workers and accounting for one-third of the national market.
However, since 2005, the cluster has faced many new challenges. Employers report that there is a labor “shortage,” with skilled workers in increasingly short supply. Moreover, on September 14 and October 19 in 2006, two fatal fire accidents resulted in the deaths of 14 an 8 people, respectively. These disasters received wide media attention and promoted local governments to take various safety measures, in particular, all the three-in-one workshops, where workers live, dine and work in the same place, must install fire exits, and there are other tougher safety standards. 3 These new standards obviously have raised costs to many workshops which were already struggling with rising labor costs. Local enterprises have adapted in different ways. Some have installed more capital-intensive production lines, reducing labor requirements and at the same time upgrading production quality. Other enterprises have been outsourcing production to lower wage regions in neighboring Anhui and Jiangxi Provinces.
The local government also helped firms to adjust to the changing environment and to improve their ability to compete in domestic and international markets. Perhaps most important, a new quality inspection center was established to randomly check the quality of local products. Second, preferential treatments were given to firms that established respected brand names, including access to land at reduced prices.
3. Basic Features of the Industry
This section reports the basic features of the cluster based on two rounds of primary surveys in 2000 and 2008. Table 1 reports basic sample statistics for these firms in the Zhili children’s garment cluster. 4 The top half of the table reports summary statistics for firms surveyed in 2008 and the bottom half for firms surveyed in 2000. One of the most striking statistics in both surveys is the rapid turnover of firms. Of the 121 firms sampled in 1999, only 31, approximately 25%, existed in 1990. Of the 135 firms
sampled in 2008, only 35, again approximately 25% existed in 2000. Mean output value
3 See https://www.docsj.com/doc/168924970.html,/20060914/n245347537.shtml and
https://www.docsj.com/doc/168924970.html,/eastday/node81741/node81763/node167187/u1a2391492.html.
4 Evidently many small workshops were closed. In our effort to link the 2000 and 2008 surveys we have tried to locate firms included in the 2000 survey and have been informed that many were in small shops that have been torn down and replaced with newer house/workshop structures.
of the surviving firms increased significantly. By the year 2007, the average firm produced about 75 per cent more than those in the sample in 2000. In the 1990s, this pattern is also evident, although less pronounced, with mean output increasing about 46 per cent over the sample period.
The data indicate that these are small enterprises, but they also exhibit large variation in size and performance. The median number of employees was as few as 8 in 1990 and is only 26 in the last year of the 2000 sample. In the last year covered in the 2000 survey, the ratio of the mean number of employees in the top quartile of firms to the mean in the lowest quartile was 4.0; in the last year covered in the 2008 survey, the comparable ratio is nearly 11. The dispersion of output value is even larger, equal to nearly 30 in the last year of the 2000 survey and nearly 33 in 2007, the last full year covered in the 2008 survey.
A major feature of these clustered enterprises is low entry barriers in terms of initial investment. Firms starting up in the 1980s report median initial investment of approximately 7,700 yuan in the 2000 survey and 36,200 yuan in the 2000 survey(in real terms with 1990 as the base year). Firms reported in 2000 survey starting in the 1990s reported a median startup investment of 16,000 yuan, while those in the 2008 survey reported 75,000 yuan. Among the firms in the 2000 survey, virtually all initial financing was from the initial principal or his family. Among the firms surveyed in 2008, the proportion of initial investments obtained from formal bank loans has been small. However, the mean proportion of initial investment obtained by means of formal bank loans grew from negligible amount for firms that started operations prior to 1990 almost 13% in 2007. The findings are consistent with early studies (Huang, Zhang and Zhu, 2008; Ruan and Zhang, 2009) on two other rural industrial clusters in Zhejiang Province, namely that lower entry barriers due to clustering enable more firms to participate in the nonfarm production process.
Table 3 and figure 1 summarize features of wages and profits. Firms in both samples show a sharply increase trend of the proportion of wages in value added in both surveys, but the causes are quite different. Profit as a share of valued added declined by roughly half among firms in the 2000 sample and by about 15% in the 2008 sample. In the 2000 sample, wages were roughly steady while product-market competition evidently
forced output prices to decline nearly 60 percent in real terms. The trends in the period covered by the 2008 survey are in sharp contrast, with output prices roughly constant (declining by about 4 per cent in real terms) and mean wages increasing by nearly 40 percent. The pressure on profits had important implications for the evolution of production methods and product quality, as we discuss below.
4. Evolution of the Industry
We discuss several measures of changes in industry structure and the complexity of manufacturing.
Specialization in production and outsourcing.
There is no information on outsourcing in the 2000 survey. Figure 2 shows the proportion of firms outsourcing in the 2008 survey, and the trend is sharply upward. Between 2000 and 2006, the proportion of firms in the full sample who report outsourcing some production rises from about 2.5 percent to about 12.5%, and the proportion of firms outsourcing among the 16 firms entering the sample in 2007 is about 18%. We notice that the ratio of mean output value of firms in the top quartile of mean production to those in the bottom quartile increased from approximately 24 to 30 between 2006 and 2007.
Branding and quality
As discussed above, one of the most important issues facing this industry has been increasing competition creating increased pressure on profits and a tendency for firms to cut costs resulting in a self-defeating “race to the bottom” in terms of product quality and with negative implications for product and employee safety. In the 2008 sample, inflation-corrected profits were only 19% higher in 2008 than in 2000 despite a near tripling of real output. Real profits were actually lower in 2008 than in 2005. As discussed in section 2, industry leaders understand the negative implications of this trend for quality standards and have promoted quality certification and development of brand names in order to create credible indicators of product quality and integrity. Branding and quality certification require investments of entrepreneurs’ time and financial costs. They are a signal to the market that firm stands to lose its investment if its products fall short of promised quality. Moreover, they provide a barrier to effective competition from firms cutting costs but lowering quality. Figures 3 through 6 show the proportion of firms
in the 2008 sample that have obtained and that have applied for trademarks and certification from the International Office of Standardization (ISO). The proportion of firms in the survey with trademarks grew from 10% in 2000 to about 38% in 2005 and to 40% by 2007. There were no firms with ISO certification in 2000, although 10% of firms had applied. Nearly 45% of firms had achieved ISO certified status by 2006. It is noteworthy that among firms appearing in the sample in 2007, less than 10% had registered trademarks and a similar number had applied; a similar gap appears for firms with and applying for ISO certification. We take this as further evidence of increasing specialization in production, with firms that exist mainly as suppliers of semifinished products to firms farther down the production chain not depending on trademarks or ISO certification to establish their bona fides to their customers.
Figure 7 shows mean investment in design over the sample period. The average investment (including firms that reported spending nothing on product design) jumped about 5-fold in real terms between 2000 and 2005 and another 40 percent between 2005 and 2007.
Performance
We discuss three measures of firm performance, total factor productivity (TFP) and profit per unit of invested capital. TFP is obtained by subtracting the weighted sum of the logarithms of labor and total invested capital inputs from the logarithm of value added, where the weights are the share of wages in value added and its complement. Trends in TFP are depicted in figures 7A through 7D. There is no evidence of increasing TFP within or across the samples.TFP rose throughout the period covered in the 2000 sample but remained roughly constant throughout the 2008 sample, rising somewhat between 2006 and 2007 for firms that were in the sample from 2000 through 2008. While at first this failure of TFP to rise may be surprising, on reflection it is consistent with China’s outstanding economic growth having its source in movement out of agriculture and from traditional to more technologically advanced industries (Zhang and Tan, 2007). Because the labor productivity in the non-farm sector is higher than the agricultural sector, even if TFP in the non-farm sector maintains constant, a simple
reallocation of labor from the agricultural sector will lead to overall economic growth.5 The implications for China’s future growth prospects are serious and worth investigating in depth.
Figure 9 shows average product per unit of labor from the 2000 survey; figure 10 shows average labor productivity for firms in the 2008 survey; figure 11 also depicts average labor productivity for the 2008 firms, but instead of output, we use real revenue as the measure of “product”. While the trends in these charts are not identical, it is clear that average labor productivity did not have a distinct upward trend in either time period. Figures 12 and 13 show the trend of profit as a proportion of invested capital in the 2008 sample. In figure 12, we assume a 10 per cent annual depreciation rate for capital, and in figure 13, we assume no depreciation. In both formulations, profit is calculated as reported sales valued in current prices minus all reported costs, deflated by the GDP deflator; invested capital is deflated as described in the discussion of table 2. The profit ratios are indexed to the year 2000 = 100. Figures 12 and 13 differ in one other respect; in figure 13, we have deleted all observations with suspicious zero values for profit in the year 2000. In figure 12 we have not done this. In both figures, we see a clearly declining trend of the profit ratio after 2005. Figure 12 would also exhibit a declining profit ratio between 2000 and 2005 as does figure 13, if the suspicious observations were deleted.
The calculation of profit is problematic for two reasons in addition to normal recall and record keeping problems associated with these small firms: (i) Although we have data for initial investment in all firms, for firms established prior to 2000, we lack data on investment in years between the date of founding and the 2000; (ii) “profit” includes the remuneration of owner/managers, and we have not yet attempted to subtract this item from the residual remaining after other costs are deducted from revenue. For the entire sample, profit/invested capital rises between 2000 and 2005, despite the rise in the median share of wages in value added between these years. The profit ratio declines abruptly between 2005 and 2006, but rebounds somewhat in 2007. It is striking, though, that for firms entering the sample in 2007, the profit ratio is much lower than for any other observation in the chart. We note three possible causes of the low profit rate for
5 According to the simulation by Zhang and Tan (2007), reallocating even 1 percent of the agricultural labor force could increase national GDP by 0.9 percent.
these firms: (i) we have better estimates of their investment because of the shorter period of time covered by the data; (ii) rising wages have cut into the profit rate of new firms more severely than into the profit rate for older firms, perhaps due to sluggish wage adjustments among the currently employed; (iii) as noted in the introduction, in recent years, safety requirements have raised costs, and these requirements for safe workplaces may impinge more severely on new firms.
Figure 14 relates TFP the profit ratio to the human capital of the firms’ founders. In almost all cases, the firm’s founder was also the general manager of the firm at the time of sampling. We divide schooling level into three categories, less than 8 years, 8-11 years, and 12 years and above. We observe two very interesting patterns: (i) The profit rate declines throughout the sample period on average; (ii) the relative standing of firms whose founders have less than 8 years of schooling has dropped substantially. Enterprises whose founder has 12 years of schooling or more actually show a much higher profit rate in 2007 than in 2000, in sharp contrast to firms whose founders fall into the two lower schooling categories. A simple regression of the of the profit ratio for firms with founders in the highest schooling group divided by the profit ratio for firms in the lowest schooling group yields a highly significant slope coefficient of 0.11 per year over the period 2000 through 2007. Moreover, while the founders of a third of the firms in 2000 were in the lowest schooling category, only 11 percent of the founders in the year 2000 were in the highest schooling category, they constituted 19 percent of the founders in the year 2007. This pattern suggests the possibility that schooling was becoming more important to firm profitability as the industry expanded and competitive pressures increased. The exact channel through which schooling operates is difficult to document in our data. Figure 15, for example, indicates no relationship between firm profitability and lagged investment in design.
5. Summary
The average firm in Zhili in 2007, the last year included in the 2008 sample, is 75 per cent larger in terms of output than the average firm in 2000 and more than 7 times larger than in 1990, the first year of the 2000 survey. At the same time, the dispersion of output among firms as grown immensely as has the dispersion of average employment.
One indicator of rising dispersion of firm size can be seen by comparing median employment, which grew from 20 workers per firm in 2000, first year of the 2008 survey, to 26, an increase of 30 percent, while the ratio of mean employment of the top quartile of employers to the bottom quartile grew to nearly 11 from 7. The far greater increase in output dispersion than employment dispersion implies a substantial growth in the dispersion of average labor productivity. The divergence in firm size is associated with a significant increase in specialization among firms, indicated by the proportion of firms that outsource some of their production, which grew from about 2 percent of all firms in 2000 to approximately 20 percent of all firms in 2007.
Although startup costs have risen significantly with median initial investment among firms founded after the year 2000 about twice as large in real terms as among those founded before 1990, many entrepreneurs can still afford to enter the business using their own savings. Formal bank financing still accounts for only a small fraction of initial investment. The rather low initial investment threshold has facilitated business entries and therefore intensified competitions in the cluster. With more people participating in the clustering production, the demand for labor has increased. Moreover, rising incomes have provided more resources for business investment. Not surprisingly, profit margins declined as prices fell (during the years covered by the first survey) and wage costs shot up (during years covered by the second survey).
Avoiding a race to to the bottom in terms of declining profit margins and declining quality (Sonobe and Otsuka, 2006) and employee safety is a major structural problem facing this highly fragmented industry. The township government has imposed safety regulations in response to some major industrial accidents, and the firms themselves have taken steps to signal their commitment to product quality by investing in trademarks and ISO certification. By the year 2007, nearly half of the firms in Zhili had established registered trademarks and nearly 20 percent had become ISO certified. Firms whose main function is to serve as subcontractors for enterprises producing finished products for the wholesale and retail markets are monitored by their outsourcing partners, and the payoff to establishing a trademark is reduced. This characteristic may account for the very low proportion of registered trademarks and absence of trademark applications among firms entering the data in 2007.
We have used two measures of firm performance: total factor productivity and profit per unit of invested capital. While there has not been any significant change in TFP over time, the ratio of profit to invested capital is substantially lower in 2007 than in 2007, with firms entering the sample in 2007 showing the lowest ratio. We conjecture that the low profit ratio is attributable to some combination of rising wage costs, a more accurate measure of total investment, and to the stricter imposition of safety regulations. When firms are grouped according to the schooling of the founder, the relative profit ratio of firms whose founder has schooling of 12 years or more has increased over time and is highest in the year 2007. This observation is consistent with previous studies in China and Japan (Sonobe, Hu and Otsuka, 2002; Yamamura, Sonobe and Otsuka, 2003). In the early stage of clustering formation, formal education does not assume a major role. However, as a cluster develops, years of schooling become positively associated with innovative managerial and production technology.
Our overview of the evolution of firms in the Zhili children’s garment cluster highlights critical features of one of the most important drivers of China’s spectacular growth during the reform period and also highlights some significant limitations. Initial capital requirements to enter this basic industry have been small. Clustering within established communities where long-time relationships among family and neighbors prevail offers an institutional substitute for court enforcement of contractual relationships among borrowers and lenders and between outsourcing firms and their subcontractors. Local government has served a facilitating role in the innovation of institutional arrangements to prevent a destructive “race to the bottom” in terms of product quality and employee safety. The employment opportunities provided to workers with negligible productive opportunities in farming jn Zhili and similar locations have been a major contributor to rising aggregate TFP.
On the negative side, TFP within this cluster is stagnant. The cluster’s contribution to future TFP growth rests in its capacity to continue drawing labor from low productivity agricultural employment, and rising wage pressures imply that this capacity is diminishing if not almost gone in this region of China. Growth will require increasingly capital intensive production methods and perhaps shifting to more technology intensive products. Both channels imply larger initial capital requirements,
and this change is likely to exert considerable pressure on SME financial channels. Borrowing outside the community, from banks and other formal lenders, will require not only an upgrade of contractual formalities but also of courts’ ability and willingness to enforce loan contracts and other contractual arrangements fairly and transparently. Hopefully, local and regional governments will respond to this need positively as they have to the need for quality and reputational certification. Such responses to existing institutional inadequacies can provide a critical stepping stone on the path to assure China’s continuing growth and show the way to other developing nations.
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Table 2 Initial Investment Year Founded Number
of Firms Initial Investment (10,000) Proportion of Initial Investment
from a Bank(%)
2008 Survey Mean Median
1982-1990 8 4.07 3.620.00
1991-1995 1014.79 3.40 3.3
1996-2000 41 5.94 4.01 1.7
2001-2007 7525.067.5 4.1
2000 Survey
1980-1990 35 1.110.77No funding from
formal lenders or
government 1991-1995 47 1.33 1.021996-1999 39 2.45 1.60
Note: Initial investment deflated by price index for investment in fixed
capital, Zhejiang 1990 = 1.00. See Fleisher, Li, Zhao (2008). Deflator values are
1982-90, .689; 1991-95, 1.47; 1996-2000, 1.87; 2001-2008, 2.0; 1980-90, .65;
1996-99, 1.87