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Improving the Investment Climate in China
David Dollar, Mary Hallward-Driemeier, Anqing Shi, Scott Wallsten, Shuilin Wang, and Lixin Colin Xu
March 2003
This report is based on an investment climate survey conducted in 2002 in five Chinese cities (Beijing, Chengdu, Guangzhou, Shanghai, and Tianjin). We gratefully acknowledge financial support from the United Kingdom’s Department for International Development (DFID). A grant from DFID supported the collaboration of the Enterprise Survey Organization in this survey and fellowships for two ESO staff, Mr. Yang Yumin and Ms. Li Hui, to visit Washington, DC, for analysis and preparation of this report. This project is part of a larger effort in the World Bank Group to help countries assess their investment climates and to identify reforms that will lead to higher productivity, more efficient investment, and ultimately more job creation and growth.
2
Table of Contents Chapter 1. Investment Climate Matters
1.1 What do we mean by “investment climate” 1.2 …and why does it matter
Chapter 2. China’s Investment Climate in International Perspective 2.1 International Integration 2.2 Infrastructure 2.3 Regulatory burden, governance, and corruption 2.4 Entry and Exit 2.5 Human Resources, Skills, and Technology Endowment 2.6 Access to Finance 2.7 Conclusion
Chapter 3. Measuring the Investment Climate and its Consequences in China 3.1 Introduction 3.2 Regional Variation In Investment Climate
3.2.1 International Integration 3.2.2 Private Sector Development 3.2.3 Domestic Entry and Exit Barrier 3.2.4 Labor Flexibility 3.2.5 Skills and Technology 3.2.6 Financial Services 3.2.7 Government Effectiveness 3.2.8 A brief Summary: A Score Card for the Cities
3.3 Impact of the Investment Climate 3.3.1 Methodology 3.3.2 Investment Rates 3.3.3 Sales Rates 3.3.4 Productivity
3.4 Policy Implications
3
ANNEXES
1. Technical appendix 2. References
4
Macro environment1995 2000/1 1995 2000/1 1995 2000/1
GNI per capita (US$, PPP) 2650 3940 1860 2390 6180 6330Population, mid year (millions) 1205 1261 929 1016 59 61GDP growth (1991-95 and 1996-2000,avg %) 12.1 8.2 5.2 6.1 8.7 0.4Openness (Imports+Exports/GDP) 45.7 47.1 25.7 28.2 90.2 124.5Private Investment (% GDP) 15.8 16.7 16.9 16.6 32.1 13.6Public Investment (% GDP) 18.9 19.2 7.7 7.1 8.8 6.5FDI inflows (net, % GDP) 5.1 3.9 0.6 0.5 1.2 5.1
Micro environment Inputs
Labor force education (avg yrs educ, manufact.) 10 10 11Excess labor force, % -- 17.3 --Suppliers availability (used for main input), median 20 4 --Stock of inventories of inputs (days of production) -- 28 --R&D (% sales) 2 -- 5.6
GovernanceControl of corruption2 -0.29 -0.31 -0.17Rule of law2 -0.20 0.23 0.44Political Stability2 0.40 -0.05 0.21Number of visits by gvnt officials, avg per year -- 10.5 --% of senior manager time with gvnt officials 9.2 16.0 --
InfrastructureShare of firms with own generator,% 30 69 --Excess cost of private electricity, % of public -- 24 --Days to clear imports, longest in last year3 12 21 24Cost of shipping4, % 5.4 8.5 6.7Telephone lines in largest city (per 1000 people) 294 131 371Personal computers (per 1,000 people) 12 3 23Paved roads, % of total 88 56 97
Finance
Cost of capital (lending interest rate, %) 5.85 12.29 7.83Share of credit from financial institutions, % 25 36 47 Credit to private sector (stock, % GDP) 125 25 109
Entry/Exit and Operation Cost of labor5 0.23 0.21 0.30Import duty on capital equipment6 -- 10 24Median number of days to start a business 30 90 30Number of permits to start business 6 10 3Bankruptcy rate, % of total firms -- 0.04 0.14Uncertainty of expectations in sales7, % -- 14 --
Source: WDI, ICU firm surveys1/ or most recent available year
2 Scale of -2.5 to 2.5. Higher values correspond to better outcomes
3 Average for Thailand
4 Transport cost as share of value of export to US, textiles, 1998.
5 Ratio of average wage to average value added, median value
6 On all imports for Thailand
7 % variation of avg expectations
India
Investment Climate at a glanceChina, India, and Thailand
China Thailand GNI per cap, PPP $
1000
3000
5000
7000
1995 1996 1997 1998 1999 2000
India Thailand China
Credit to Priv. Sector (% gdp)
0
60
120
180
1995 1996 1997 1998 1999 2000
India Thailand China
PC per 1,000 people
0
5
10
15
20
25
1995 1996 1997 1998 1999
India Thailand China
5
Chapter 1. Investment Climate Matters
During the last decade, major developing countries including China have begun to
integrate much more with the global economy. The countries that are aggressively
integrating have grown significantly faster than those that are not. In the 1990s, the more
rapidly globalizing developing countries (measured in terms of increased trade
participation) grew at 5.0 percent per capita, while the rest of the developing world
posted negative growth of 1.1 percent.1 Among the more aggressive globalizers were
Brazil, China, Mexico, Philippines, Thailand, and India.
That globalizing developing countries are doing well on average is good news. But
these averages disguise considerable variation in performance within this group. China
has done spectacularly well, and is the unchallenged leader of the pack. The country has
doubled its ratio of trade to GDP over the past two decades (to 41 percent of GDP in
1999), and has had per capita GDP growth of nearly 8 percent during 1990-99. Malaysia
was another winner: in spite of the temporary income compression due to the Asian
crisis, it could still enjoy per capita GDP growth of 3.8 percent during the 1990s. Again,
despite the crisis, Thailand’s per capita GDP growth in the 1990s averaged 3.8 percent.
However, the per capita GDP growth of another relatively aggressive globalizer, Brazil,
has only been around 1 percent for 1990-99; and growth in the Philippines was only 0.4
percent. India, with per capita GDP growth of 3.3 percent during 1990-99 is in the middle
of the pack (figure 1.1).
1 During the same period, the rich countries grew at about 2 percent per capita.
6
The implication of these variations is striking. Such differences in growth rates
sustained for one or two decades make a huge difference in living standards and the
extent of poverty. While China and India had comparable levels of GDP per capita
(measured at purchasing power parity) in 1990 (approximately $1400), over the
following decade India’s per capita income nearly doubled, while China’s nearly tripled.
Thus, today, China’s per capita income is about 50 percent higher than that of India.
Together with its faster growth, China has also had significantly faster poverty reduction
(figure 1.2).
Figure 1.1 Per capita GDP growth rates in globalizing developing countries
(average 1990-99)
0
2
4
6
8
China Malaysia India Thailand Mexico Brazil Philippines
7
Figure 1.2 Poverty reduction in India and China is closely related to the growth rate
* India poverty reduction figure is for 1993-99
Percent per annum (1992-98)
8.4
China
9.9
India
4.4
5.4*
0
2
4
6
8
GDP per capita
growth ratePoverty
reduction
10
The purpose of our paper is to examine some of the reasons for such performance
variations across countries. We argue that openness to foreign trade and investment is an
important, but not sufficient, condition for sustained GDP growth. For China and other
developing countries to do well, good macro and trade policies need to be complemented
with a host of other institutional factors and policies that can be classified under the broad
heading ‘investment climate’.
In the next section we define in more detail what we mean by investment
climate. Section 2 then briefly reviews some of the macro evidence that shows the
importance of investment climate for sustained growth and poverty reduction. While
illuminating about the importance of the investment climate, the macro literature does not
really provide much specific guidance about what aspects of the investment climate are
important and what specific reforms are needed in particular countries. For this reason
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we go down to a more micro level in chapters 2 and 3. Chapter two looks at China in
international perspective. The source of information includes surveys conducted by the
World Bank with the Enterprise Survey Organization of China’s National Statistical
Bureau, comparable surveys conducted in other countries, and various cross-country
databases. In general, China compares favorably in areas such as macro and political
stability, integration into the world market, and infrastructure. Abundance of cheap labor
associated with rural-urban migration has been and continues to be a comparative
advantage of China. Not everything is rosy, however. The financial sector is not
operating efficiently—the vast majority of credit has been provided to state-owned
enterprises, which often cannot service their debts, and small- and medium enterprises
have to rely mainly on retained earning and personal wealth (or parent company
financing) to finance their investment. Moreover, China also lags its more developed East
Asian neighbors in terms of education level and infrastructure. Another important caveat
is that our survey covers five major cities – Beijing, Tianjin, Shanghai, Guangzhou, and
Chengdu. So, the results should be interpreted as showing something about the
investment climate in these cities. There remains an important question about the
investment climate in smaller cities and in more interior locations, which we plan to take
up in future surveys and analysis.
Chapter three compares the investment climate in the five cities (Beijing, Tianjin,
Shanghai, Guangzhou, and Chengdu), using the ESO-WB survey of 1500 firms. The
main findings are the following: First, investment climate shows large variations across
the five cities. In particular, Shanghai is characterized by the best international
integration, financial services, good entry and exit conditions and labor market flexibility,
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but has the lowest level of domestic private sector participation. Guangzhou is the best in
labor market flexibility, entry and exit fluidity, government efficiency, and private sector
participation; good in international integration and financial services; but relatively low
in skills and technology. Beijing is largely in the middle of the pack, with no especially
strong advantage or disadvantage. Tianjin is good in private sector participation, in the
middle of the pack in terms of entry and exit fluidity and labor market flexibility, poor in
international integration and government efficiency, and worst in skills and technology
and financial services. Chengdu, the only inland city we have surveyed, lags the farthest
in almost everything, with the following exceptions: a good level of private sector
participation, with reasonable skills and especially technology.
Second, the growth potential from improving the investment climate could be
quite large. For instance, we consider what gain Chengdu would get from attaining the
level of investment climate indicators that we observe in the better cities of Guangzhou or
Shanghai. We estimate that in this scenario firm productivity could be increased by
about 30 percent and that the investment rate of the typical firm would increase from the
14 percent that we actually observe in the Chengdu sample to about 19 percent. The
specific point estimates inevitably have some uncertainty around them, but the general
point is that firm productivity, investment, and growth are related to aspects of the
investment climate and that addressing weaknesses identified in this analysis should lead
to substantially better firm performance. Third, within the categories of investment
climate we have found the extent of international integration and the extent of
development of the private sector to be especially important. Other issues such as entry
10
and exit barriers, labor market flexibility, and financial services are important as well.
Each city has specific areas that could be improved.
A. What do we mean by “investment climate”?
The quantity and quality of investment flowing into China or any specific region
depend upon the returns that investors expect and the uncertainties around those returns.
These expectations can be usefully categorized as the following broad yet interrelated
components:
• First, there are a set of macro or country-level issues concerning economic and
political stability and national policy towards foreign trade and investment. By these,
we generally refer to macroeconomic, fiscal, monetary, and exchange rate policies as
well as political stability. As far as these macro indicators go, China performs quite
well, as will be documented in chapter two.
• Second, there is the issue of efficacy of a country’s regulatory framework. As far as
firms are concerned, these relate to the issues of entry and exit, labor relations and
flexibility in labor use, efficiency and transparency of financing and taxation, and
efficiency of regulations concerning the environment, safety, health, and other
legitimate public interests. The question is not whether to regulate or not, but whether
such regulations are designed in incentive compatible ways, avoid adverse selection
and moral hazard, serve the public interest, are implemented expeditiously without
harassment and corruption, and facilitate efficient outcomes. While such variables are
hard to measure, our surveys clearly suggest that regulatory efficacy varies widely
across countries and, as far as China is concerned, across provinces.
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• Third, and no less important, is the quality and quantity of available physical and
financial infrastructure, such as power, transport, telecommunications, and banking
and finance; and given the imperfect mobility of skilled workers and the clustering of
technology, the endowment of skills and technology. When one surveys entrepreneurs
about their problems and bottlenecks, they will often cite infrastructure issues such as
power reliability, transport time and cost, and access and efficiency of finance, along
with the lack of skilled workers and the difficulty of access to advanced technologies
as key determinants of competitiveness and profitability.
China’s success in the 1990s suggests that it has many positive features in its
investment climate, and one objective of our study is to understand what has contributed
to China’s success – which can provide useful lessons to other developing countries. The
evidence also shows that there is still room for significant improvement in the investment
climate. To be sure, China has been excellent in the first dimension of the investment
climate (i.e., macro environment), as characterized by political and macro policy stability.
However, some recent changes in the structure of the Chinese economy require further
structural reforms. The WTO accession, for instance, requires China to shift from a
discretion-based governance system to a rule-based one, which requires the reduction of
the role of the government in how firms operate. Financing also should be less favorable
to one particular type of ownership. Another challenge has been the migration of rural
residents to cities, and the pressure of job creation due to both migration and Xia-Gang
workers (i.e., laid-off workers from SOEs). This challenge also imposes demand for
regulatory reforms to reduce entry barriers for new, and small- and medium-sized
enterprises, which have been shown to be the most important force behind job creation;
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and it also pushes for reforms in financial institutions in order to allow SMEs more ready
access for credit. This paper hopes to shed light on what would be some fruitful areas for
further reforms.
Two caveats are in order at this stage. First, we are not interested in the quantity
of investment per se. Indeed, recent work on economic growth [Easterly 1999] has shown
that there is surprisingly little relationship between the quantity of investment and the rate
of economic growth. In many instances, this is due to a distorted and dysfunctional
institutional and policy milieu — where neither public nor private investments produce
the benefits that they should. Our focus, therefore, is not on the quantity of investment,
but on the overall institutional and policy environment — the ‘investment climate’ —
that determines whether or not investments pay off in terms of greater competitiveness of
firms and sustained growth.
Second, while we recognize that social infrastructure is no less important than its
physical and financial counterparts, we have chosen to exclude from our definition of the
investment climate such issues as the provision of basic education and health services. It
is a deliberate choice. The reforms needed to improve social services are quite different
from the issues of infrastructure and regulation of industry on which we concentrate.
B… and why does it matter
Spurred by the endogenous growth theories of Romer (1986) and Lucas (1986), there is
now a vast empirical literature that investigates the determinants of growth. Some of the
empirical results are fairly robust and provide macro evidence about the importance of
13
the investment climate. Fischer (1993), for example, found that high inflation is bad for
growth. This commonsense result is hard to dispute. To an extent, inflation reflects
exogenous shocks that are beyond the government’s control. But truly high inflation
typically reflects serious monetary mismanagement. There is also a clear negative
relationship between government consumption and growth, which was first noted by
Easterly and Rebelo (1993). No doubt, some government expenditures are socially
productive, but developing countries with very high government spending usually have
inefficient bureaucracies and high levels of corruption.
A number of studies, most recently Frankel and Romer (1999) and Dollar and Kraay
(2001), find that openness to trade and direct foreign investment accelerates growth.
These findings are in the spirit of the new growth models, and emphasize the importance
of market size for creating a finer division of labor and stronger incentives to innovate. In
addition to macro and trade policies, financial development is also a catalyst for growth
[Levine, Loayza and Beck (2000)]. All else being controlled for, countries that have more
developed stock markets and/or deeper banking systems tend to grow faster.
Investment climate measures such as the strength of property rights, rule of law, and
level of corruption are also well correlated with growth [Kaufmann, Kraay, and Zoido-
Lobatón (1999); Knack and Keefer (1995)]. These studies typically use data generated
from surveys of private businesses, and reflect the extent to which investors and/or firms
perceive problems with harassment, corruption, and inefficient regulation. A problem of
these measures, however, is that they are often based on a small sample of very large
entrepreneurs and hence do not provide a robust assessment of how rule of law and
14
corruption are experienced by small and medium enterprises, which form the backbone of
the economy.
Thus, the empirical cross-country literature provides evidence that growth and
poverty reduction are promoted by a good investment climate — an appropriate policy
package of private property rights, sound rule of law, macroeconomic stability,
government spending that is not excessive and well focused on public goods, and
openness to foreign trade and investment. However, most of the macro-indicators of
policy and investment climate used in these studies are quite crude, and are of little help
to countries in identifying what specifically needs to be done to create a better climate.
For instance, the existing cross-country macroeconomic measures are quite similar for
China and India (e.g. rankings on rule of law, corruption, or overall infrastructure quality
from different international sources) (ICU, World Bank, 2002). Both countries ‘fit’ the
empirical growth studies in that both have done relatively well. India has grown at about
twice the rate of the OECD countries in the 1990s. Yet, China has grown much faster and
had much greater poverty reduction. Macro-indices fail to explain such differences. Thus,
while the macro evidence is useful as background and motivation for the rest of our work,
it suggests the need to delve at a much more micro level, and to survey large numbers of
producers, including SMEs, to understand the rich differential relationship between
investment climate and growth.
15
Chapter 2: China’s Investment Climate in International Perspective
China’s solid macroeconomic performance over the past decade is
unquestionable. Moreover, this growth remained relatively stable even during the East
Asia crisis, when other countries in the region saw large GDP decreases (figure 2.1).
Figure 2.1 Growth remains strong through the East Asian crisis
-15
-10
-5
0
5
10
15
1994 1995 1996 1997 1998 1999 2000 2001
Percent GDP growth
ChinaKorea, Rep.
MalaysiaIndonesia
Thailand
Philippines
Other macroeconomic indicators are also consistent with this long-running
economic growth. Low inflation, for example, tends to be an important factor in
sustainable economic growth, though moderate inflation may not be harmful (Barro,
1997).2 Inflation in China was relatively low through the 1990s. Moreover, it remained
2 Spurred by the endogenous growth theories of Romer (1986) and Lucas (1986), there is now a vast empirical literature that investigates the relationship between inflation and growth. Fischer (1993), for example, found that high inflation is bad for growth. This commonsense result is hard to dispute. To an extent, inflation reflects exogenous shocks beyond the government’s control. But truly high inflation, however, typically reflects serious monetary mismanagement.
16
low during the East Asian crisis, unlike other Asian countries which saw higher inflation
(figure 2.2).3
Figure 2.2 Low inflation, even during the East Asian crisis
0
20
40
60
China India S. Korea Malaysia Indonesia Thailand Philippines
CPI percent change
Average1990-2000
1998
Strong macroeconomic performance, however, masks the underlying components
of the investment climate, described in chapter 1, that affect (and are affected by) the
macroeconomy. While chapter 3 will explore the microeconomic foundations of China’s
investment climate, this chapter will compare China’s aggregate performance in certain
investment climate measures to the rest of the world. Broadly speaking, these factors
include international integration, governance, infrastructure, entry and exit of businesses,
human resources, and finance. While macroeconomic indicators present only good news,
as we will see the investment climate analysis reveals both strengths and serious
weaknesses.
3 Some debate these inflation figures, suggesting that enterprises have systematically understated inflation (Young, 2000).
17
1. International Integration
The strong macroeconomic environment has brought—and has been encouraged
by—China’s increased integration in the world economy. Indeed, China’s entry into the
WTO is a major signal of China’s international outlook. The important role that trade
plays in promoting productive investment and growth has long been recognized. Using
different measures of “openness” to trade, including both its relative size (as measured by
import and export shares) and degree of distortion (as measured by average tariff rates
and dispersion), research strongly suggests that greater openness is associated with higher
growth in both industrialized and developing nations. Sachs and Warner (1995) find that
openness is a highly significant determinant of growth, and combined with property
rights may even represent sufficient conditions for growth in poor economies. Kang and
Sawada (2000) find a similar effect of openness on growth, arguing that combined with
financial development it increases growth rates in developing economies by decreasing
the cost of human capital investment.4
Foreign direct investment (FDI) and trade are good indicators of this integration.5
Net FDI increased dramatically in the last decade, from $2.7 billion in 1990 to $37 billion
in 2000. This growth is impressive, and as a share of GDP, net FDI into China is higher
than many other Asian countries, though not as high as some in Latin America (figure
4 Rodriguez and Rodrik (1999) argue that some indicators of openness are highly correlated with other indicators of economic performance, including macroeconomic policy, or that they imperfectly reflect a country’s trade policy regime. The high correlation of components of the Sachs and Warner index with policy and institutional variables yields an upward bias in the estimation of trade restriction effects, while tariff and non-tariff barriers, the two variables that directly measure trade openness, have little explanatory power when considered separately in cross-country regression studies. 5 A number of studies, most recently Frankel and Romer (1999) and Dollar and Kraay (2002), find that openness to trade and direct foreign investment accelerates growth. These findings are in the spirit of the new growth models, and emphasize the importance of market size for creating a finer division of labor and stronger incentives to innovate.
18
2.3). FDI as a share of GDP has come down somewhat in the second half of the 1990s
(figure 2.4), but in absolute terms China is still the largest recipient in the developing
world.
In regards to trade, meanwhile, China has reduced tariff rates to about one-third of
what they were two decades ago: from 49.5 percent in 1982 to 16.8 percent by 1998
(World Bank 2002). Partly as a result, trade increased from 15 percent of GDP in 1980
to nearly 50 percent of (a much larger) GDP by 2000. Imports increased from about $US
36 billion in 1980 to $US 192 billion in 2000 (in constant 1995 US dollars). Likewise,
exports increased from $US 27 billion in 1980 to $US 239 billion in 2000.
Figure 2.3 FDI as a share of GDP, 2000
-2
0
2
4
6
China India S. Korea Malaysia
Indonesia
Thailand Philippines Brazil Argentina
19
Figure 2.4 FDI as a share of GDP in China is high, but declining
0
2
4
6
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
2. Infrastructure
One component of the investment climate is a country’s infrastructure.
Businesses in countries with poor infrastructure must spend more effort to, for example,
acquire information, receive inputs, and get their products to market. The costs of poor
infrastructure can easily undermine any cost-competitiveness that a business would
otherwise have, at best making it more costly for a given firm to operate and at worst
deterring entry in the first place by making it uneconomic. Infrastructure in China
appears to do relatively well compared to other developing countries.
Two separate surveys suggest that businesses do not perceive infrastructure to be
a tremendous obstacle. Figure 2.5 reports the share of firms in the World Business
Environment Survey reporting that infrastructure posed “no obstacle” for “the operation
and growth of [their] business.” Approximately 42 percent of Chinese firms responded
that infrastructure posed no obstacle, much better than Brazil or India, but about average
20
for East and South Asia. Figure 2.6, meanwhile, reports the average responses of
business executives surveyed in the World Economic Forum’s Global Competitiveness
Report (GCR), which asks respondents to rate “the overall infrastructure quality of their
country” on a scale of 1 to 7, with one being the worst ranking and seven the best.6
While China ranks slightly ahead of India, it falls below Brazil, Malaysia, and Thailand.
Figure 2.5 Share of firms reporting that infrastructure was “no obstacle” to doing business
Source: World Business Environment Survey
0
20
40
60
Thailand India Brazil East Asia China South Asia Malaysia OECD
6 There are serious problems with simply averaging responses. For example, it assumes that a response of “2,” for example, means the same thing for each respondent, a notion that research on surveys contradicts (see, for example (Recanatini, et al., 2000). At least one study has criticized the Global Competitiveness Report on the grounds that it is methodologically flawed and theoretically weak (Lall, 2001).
21
Figure 2.6 Overall quality of infrastructure, average response
(1=poorly developed and inefficient, 7= among the best in the world)
0
2
4
6
India China Brazil Thailand Malaysia OECDSource: World Economic Forum, 2002
These two figures are illustrative, but also show the limitations of such surveys:
for example, the GCR suggests that infrastructure, overall, is better in Brazil than in
China, while the WBES suggests that fewer firms in China believe that infrastructure is
an obstacle to their doing business. Several factors could be driving this seemingly
anomalous result. First, neither survey is random or representative, making it difficult to
compare one country to another. Second, firms surveyed in Brazil could be more
technologically advanced than those in China, meaning that Brazilian firms might
demand higher quality infrastructure. If so, infrastructure quality in Brazil could be
higher than in China, but still pose a relatively greater obstacles to firms there. Because
of the imprecision inherent in such surveys, it is worth exploring more factual indicators.
Below we compare data on shipping costs and ports, telecommunications development,
and power provision.
22
Shipping and ports
China is relatively well integrated into the world market through efficient
shipping and relatively well functioning ports. Data from U.S. customs concerning all of
the containerized shipments into U.S. ports allow for a comparison of the shipping costs
for a particular product such as textiles from different ports around the world. China has
a large shipping cost advantage over India and significant cost advantages over Thailand,
Indonesia, and Brazil (figure 2.7).
Figure 2.7 Shipping cost advantages
-10%
0%
10%
20%
30%
40%
50%
Thailand Indonesia China S. Korea Brazil
Cost advantage compared to IndiaE. CoastW. CoastUSA
Textiles
This reflects the large volume of exports from China as well as relatively efficiency of its
ports. On the related issue of bottlenecks in customs clearance, China is good compared
to India and a bit behind Asian neighbors such as Korea and Thailand. In large samples
of manufacturing firms the average clearance time for imported inputs was 8 days in
China, compared to 11 for India, and 7 for Korea and Thailand. In more recent surveys
we have been asking firms their worst customs experience in the past six months, which
23
highlights whether firms operate in an uncertain environment. In the Indian sample the
typical firms worst experience was a three-week delay, compared to only 9 days in
Shanghai (figure 2.8).
6.7
21.0
9.210.6
0
10
20
India Shanghai
Last timeLongest
0
4
8
1210.6
7.0 7.0
India Korea Thailand
7.8
China
Figure 2.8 Days to clear imported inputs through customs
c
The reasonably good port and customs facilities help Chinese firms connect effectively
to the world market.
Telecommunications
Telecommunications is an increasingly important component of a nation’s
infrastructure. There has been a steady increase in the number of telephones per capita in
China, from less than one telephone line per hundred people in 1990 to nearly 14 by
2001, though the telephone penetration rate is still lower than many other developing
countries. Among seven Asian countries, China has fewer telephone lines per capita than
24
South Korea and Malaysia, but more than India, Thailand, Indonesia, and the Philippines
(figure 2.9).
Figure 2.9 Telephones per hundred people
0
10
20
30
40
50
1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000
Korea
Malaysia
Brazil
China
Thailand
India
Source: International Telecommunications Union
The number of telephone mainlines is only a part of the telecommunications
infrastructure. Much telecommunications growth in developing countries now comes
from mobile telephone providers, and China is no exception. By 2001 China had more
mobile telephone subscribers than any country in the world. Of course, China is also the
most populous country in the world, and mobile penetration has exploded throughout the
world, so the number of mobile phones per capita paints a slightly different picture. By
2001 China boasted just over 11 mobile subscribers per hundred people—better than
India or Indonesia, but trailing far behind Korea, Malaysia, and the Philippines (figure
2.10).
25
Figure 2.10 Mobile phone users per hundred people, 2001
0
20
40
60
China
India Indonesia
S. Korea
Malaysia
Philippines
Source: International Telecommunications Union
Power
Access to reliable power at a reasonable cost is a prime concern for most
manufacturing firms. Figure 2.11 shows electricity generation capacity in China and
selected countries. While generation has clearly been growing, generation capacity has
only just managed to stay above population growth. Moreover, China lags several
countries in this measure. Thailand, Brazil, and Malaysia all have more generation
capacity per capita than does China, though the Philippines and two states in India for
which there are data lag behind. China has a number of big projects in the pipeline that
will boost generating capacity substantially.
26
Figure 2.11 Electrical generation capacityMW/thousand people)
1990 1991 1992 1993 1994 1995 1996 1997 1998 19990
0.2
0.4
0.6
0.8
1Korea
Malaysia
Orissa (India)
BrazilThailand
ChinaPhilippines
Punjab (India)
Source: US Energy Information Agency
Generation capacity, of course, is only part of the story. Reliable power means
electricity delivered with few interruptions. Low prices for electricity from the grid are
not helpful to firms if electricity is frequently unavailable. Our surveys of firms contain
some illuminating information. For example, 30 percent of firms in China have backup
generators compared to 69 percent in India, where electricity is less reliable. Chinese
firms report, on average, losing about 2 percent of their output as a result of power
problems, compared to 6 percent in Pakistan.
Regulatory burden, governance, and corruption
A country’s general governance structure and business-government interactions
are an important component of the investment climate. Broadly speaking, these include
the burden firms face in complying with regulations, the quality of the services provided
by these regulations and the extent to which corruption is associated with the
procurement of such services. Five composite indicators from Kaufman, Kraay, and
27
Zoido-Lobaton (1999; 2002) capture the dimensions of interest.7 These categories
include:
• Government effectiveness measures bureaucratic delays, competence of officials,
the quality of public service delivery and the independence of the civil service
from political pressures. This grouping of indicators covers the elements needed
for the government to design and implement good policies.
• Regulatory burden includes the number of regulations within a market, the
number of markets that are regulated, competition policy measures, and price
controls. This captures more of the outcomes of the policies and provides a sense
of how market friendly the business environment is.
• Rule of law captures the extent of crime, property rights, tax evasion and the legal
system’s effectiveness. It indicates the enforceability of contracts and the
predictability of rules.
• Corruption measures include the frequency and size of irregular payments.
7 These governance indices are the compilations of up to 60 sub-indices from various sources. Some qualifications should be noted when using these subjective measures to compare competitive environments. They revolve around the issue of the yardstick used in judging a country’s performance. First, the point of reference itself can vary across country. In one study, Korean entrepreneurs rankings of problems were consistently higher than those of Indonesia. Few would believe the business environment in Indonesia to be superior to that of Korea. Rather, a more plausible explanation is that the Korean entrepreneurs had relatively high expectations of services their government should provide and shortfalls were readily registered. In contrast, if there are few expectations that a service will be performed, its failure is not seen as particularly problematic. Controlling for differences in country mean responses offers at least a partial solution. Another shortcoming of these measures is that they register very little change over time, and do not necessarily reflect that substantial improvements have been made in the substantive area over time. Again, this may be due to changes in the subjective yardstick against which they are being measured. For example, as the judicial system is reformed, expectations will rise as to what role the courts should play. Failure to meet expectations could lead to low rankings, even as the system improves These subjective rankings are more useful for making comparisons within a single country than for attaching great significance to the international ranking. Thus, one can look among Indian entrepreneurs to see the relative rankings of problems, for example infrastructure versus corruption, rather than looking at perceptions of corruption between India and its neighbors. Unfortunately these indictors are rarely used in this fashion.
28
• Political instability and violence measures the incidence of coups, assassinations,
riots, armed conflicts and provides a measure of the likelihood of a violent
overthrow of a governing party.
The individual measures of governance are plotted on ‘governance
pentagons’ for China and selected countries (figure 2.12).
The outer web indicates the best performance, and the inner web the
median measure for the 174 countries for which measures were available.
Thus, the larger the country’s web, the better its governance is measured
to be. China scores very high on political stability, near the median for
government effectiveness, regulations, and rule of law, but below the
median for corruption.
IndiaPolitical stability
Government effectiveness
RegulationsRule of law
Corruption
ChinaPolitical stability
RegulationsRule of law
Corruption
BrazilPolitical stability
RegulationsRule of Law
Corruption
ThailandPolitical stability
RegulationsRule of Law
Corruption IndonesiaPolitical stability
RegulationsRule of Law
Corruption
Government effectiveness
Government effectiveness
Government effectiveness
Government effectiveness
Figure 2.12 Governance ‘pentagons’
Source: Kaufman, Kraay and Zoido-Laboton, 1999
29
Some additional measures support the information presented in the pentagons.
There is both good, bad, and conflicting news on the regulatory burden facing firms in
China. The World Business Environment Survey, for example, found that managers in
China spend about nine percent of their time dealing with public officials, far less than in
India, and about the same as in transition European countries, Latin America, and even
OECD countries (figure 2.13).
The Global Competitiveness Report, on the other hand, ranked China significantly worse
than the median on the same measure, and far worse than India. In terms of corruption,
the Global Competitiveness Report ranked China among the worst in terms of business
costs of corruption, worse even than, for example, Thailand and India. Likewise, China
was worse than the median country on the frequency of “irregular” payments by firms,
though in this case Thailand and India scored even more poorly (figure 2.14).
Figure 2.13Management time spent dealing with public officials on
regulations, administrationPercent of management time
0
5
10
15
20
IndiaChina Transitional Europe
LAC OECD
Source: World Business Environment Survey (WBES) ©2000 The World Bank Group
30
Figure 2.14 Corruption measuresRanking out of 75 countries surveyed in the Global Competitiveness Report, 2001
0 15 30 45 60 75
Frequency of irregular payments
Time senior management spends with government agencies/regulators
Business costs of corruption
Strongest
ChinaIndia
Weakest
Entry and Exit
Free entry and exit of firms is important to a healthy economy. Barriers to entry
and exit block new, more productive and innovative firms from emerging. A growing
body of literature documents the difficulty entrepreneurs face in establishing firms in
developing countries (e.g., Djankov, et al., 2002; Emery, et al., 2000; Friedman, et al.,
2000). Djankov, et al. (2002) compiled data on entry regulations in 85 countries, and
discovered enormous variation in the number of procedures required to start firms across
countries, ranging from a low of two in Canada, to as many as 21 in the Dominican
Republic (with Bolivia and Russia a close second at 20). Likewise, the time required to
establish a firm ranged from two to 152 business days. These procedures can be
extremely costly to the economy—the cost of official procedures (that is, not including
bribes) for setting up a new business was 266 percent of per capita income in Bolivia.
They find that stricter regulation of entry is correlated with more corruption and a larger
informal economy.
31
Figure 2.15 Number of procedures and days to complete them to start a new business
Source: Djankov 2000
0
4
8
12
16
China Malaysia Thailand India S. Korea Philippines 85 country average
0
20
40
60
80
100
Days
Days to complete
Number of proceduresNumber of procedures
Using Djankov’s measure of business entry, China required 12 procedures to start
a firm, more than the sample average of 10, and far more time was required to complete
them at 92 days, versus a sample average of 47 days. These estimates suggest that it
takes more time to start a business in China than in, for example, India, Thailand, or
Malaysia (figure 2.15). These data, however, are somewhat contradicted by survey
responses in the Global Competitiveness Report (figure 2.16). This measure places
China at worse than the median in terms of the number of permits to start a business—
which they estimate at six—but also suggests that the median number of days to start a
business is only 30. In this case China does better than the median, and much better than
India, which is near the bottom. Another way to determine the difficulty of entry and exit
is to examine outcomes that are associated with these factors. In particular, entry and exit
are crucial to a competitive economy, and one of the most telling indicators of whether
32
markets are competitive in a country is the productivity dispersion of firms within an
industry.
In a competitive market, with reasonably free entry and exit, dispersion should be
low as unproductive firms either improve or leave the market. Higher dispersion
indicates that less efficient producers are not being forced to improve their productivity
or exit the market. Firm-level studies in a number of countries bear this out.8 Subsidies
or strict regulations that impede entry or exit can ultimately bolster high cost producers.
When such firms remain in the market, more productive firms may not have adequate
incentives or the ability to increase productivity or to grow. However, as competition
increases, firms face greater incentives to innovate and greater penalties for failure to do
so.
Figure 2.16 Entry and exit
China
0 15 30 45 60 75
Hiring and firing of workers
Administrative burden for startups
Median number of days to start a firm
Number of permits to start a firm(6 permits)(10 permits)
(30 days)(90 days)
Strongest Weakest
India
Ranking out of 75 countries surveyed in the Global Competitiveness Report, 2001
Loss of protection and greater competition from foreign firms can drive
inefficient domestic producers to better exploit scale economies, eliminate waste, reduce
managerial slack, adopt better technologies, or shut down. As a result, productivity
dispersion should shrink as productivity levels rise in the face of greater competition.
8 See Hallward-Driemeier (2001) for a longer discussion; Levinsohn (1993), Haddad and Harrison (1994).
33
Productivity dispersion—a measure of inefficiency—tends to be associated with
barriers to competition, such as administrative barriers to start a business or trade barriers
to competition for India, China, Philippines, Thailand, Malaysia and Korea (figure 2.17).
Figure 2.17 Dispersion of value added by workerRatio of 75th percentile to 25th
0
2
4
6
8
Garments Electronics
India
PhilippinesThailandMalaysiaKorea
China
In Chinese garments and electronics, the higher performers have value added per worker
that is 5 times that of lower performers. In electronics, productivity dispersion is lower in
four East Asian countries where the World Bank has conducted similar surveys, while in
garments only India performs worse than China on this measure. In Malaysia and
Thailand the ratios are just below 3, and in Korea not much more than 2. Thus, more
competitive countries in the group (as proxied by weeks to start a business and average
tariff rates) have lower levels of productivity dispersion than do the less competitive
countries.
34
Human Resources, Skills, and Technology Endowment
The availability of inputs is a crucial component of the investment climate. In
terms of human resources, this does not mean simply an abundant labor force—which
China certainly possesses—but also skill levels and technological know-how. In this
section we explore how educated the Chinese labor force is compared to other countries
at the most basic level and in terms of higher education. We also explore measures of
technological know-how and endowments in the country.
Close to 16 percent of the Chinese population is illiterate. This is considerably
better than India, and only slightly worse than Malaysia and Indonesia, but is much worse
than the Philippines, Thailand, or South Korea (figure 2.18).
Figure 2.18 Illiteracy and school enrollment, 1999-2000
*Philippines data is for 1998-1999 ** No data for India and IndonesiaSource: UNESCO, through SIMA
0
20
40
60
80
100
Illiteracy rate Secondary enrollment Tertiary enrollment**
ChinaIndiaIndonesiaKorea, Rep.MalaysiaPhilippines*Thailand
Similarly, nearly 63 percent of the relevant population in China is enrolled in secondary
school, better than the 50 percent in India, but below the other countries in the sample.
35
Even worse, China’s tertiary enrollment rate is only 7.5 percent, which is extremely low
compared to other Asian countries.
Nonetheless, these relatively low figures still represent improvements over time.
China’s educational infrastructure, especially with respect to science and technology, has
developed mostly since the 1978 reforms. Since then China has rapidly built higher
educational institutions and sent tens of thousands of students to study abroad.
Postgraduate enrollment in Chinese institutions has increased from nearly nothing prior
to 1978 to more than 300,000 by the year 2000. Some recent research has begun to
account for this vast increase in human capital, finding that it has contributed
significantly to growth and welfare (Wang and Yao, 2001).
An ongoing concern in China, however, is the large number of students who leave
to study abroad and then do not return. In response to this concern in 1992 the
government began to send delegations abroad to entice Chinese degree holders to return
(Guo, 2000). While it is true that increasing numbers of students leave to study abroad, it
is also true that an increasing number of students are returning to China once they have
their degree (see figure 2.19).
36
Figure 2.19 Chinese students abroad
0
10,000
20,000
30,000
40,000
1952 1980 1990 1995 2000
Number students studying abroad
Number students returned
Source: Chinese Statistical Yearbook
Data compiled by the U.S. National Science Foundation (NSF) sheds additional light on
this phenomenon. The NSF collects information on, among other things, students from
outside the US who received science and engineering PhDs from US institutions. The
data includes numbers of students and those with “firm plans to stay,” where firm plans
means the students have job offers in the United States.
37
Figure 2.20 Number of science and engineering PhDs received in the US, by citizenship
0
1,000
2,000
3,000
1990 1991 1992 1993 1994 1995 1996 1997
China
Taiwan,China
Korea
India
Brazil
Source: US National Science Foundation
Figure 2.20 shows the number of students from China and other countries that
received science and engineering PhDs in the United States in the 1990s. The figure
shows a steadily increasing trend for China (except in 1997), which has far better
representation than any other country, while the number of students from other countries
remained fairly flat. The share of students from China that plan to stay in the US is
exceeded only by students from India (figure 2.21). Moreover, the share of students with
plans to stay remained relatively stable until 1995, when it began to increase. Whether
this trend continued with the contraction of the US high-tech economy is unclear.
38
Figure 2.21 Share of science and engineering PhDs with firm plans to stay in U.S.
0
20
40
60
1990 1991 1992 1993 1994 1995 1996 1997
India
China
Korea
Brazil
Taiwan,China
Some see the increasing numbers of students abroad and large share of students
staying in the US as evidence of brain drain. On the other hand, ever increasing numbers
of students are returning to China after studying abroad, suggesting more of a brain
circulation. There is likely some truth to both sides. New research, however, is
beginning to document gains to developing countries that emerge over a long period of
time when large numbers of students at first remain abroad but then gradually return.
Saxenian (1999; 2000) found that large numbers of people from India and Taiwan
province came to the US as students and remained to work in Silicon Valley, learning US
high-tech business and management models. Eventually, many of them began to return
home, bringing those skills and education with them. Those re-patriats are largely
responsible for new high-tech firms and success of new technology areas. Moreover,
there is increasing evidence of a similar phenomenon beginning to take place in China.
39
R&D and Technology
Xioajuan (1997) notes three major changes in Chinese science and technology
policy since 1978:
• The government no longer controls all science and technology projects.
• Science and technology no longer takes place only in free-standing research
institutes—enterprises and other non-governmental organizations conduct
research.
• Research results can be transferred to markets as commodities.
Some of these changes can be seen in aggregate statistics.
Figure 2.22 Research and development expenditures in China
0
10,000
20,000
30,000
40,000
1991 1992 1993 1994 1995 1996 1997 1998 19990
0.2
0.4
0.6
0.8
Total R&D expenditure (left axis)
As percent of GDP(right axis)
PPP $
Figure 2.22 shows the change in R&D spending in the Chinese economy over the last
decade. Even with the dramatic growth in China’s GDP, the share of R&D in the
economy is growing.
40
Figure 2.23 Research and development as share of GDP, latest year available
0
1
2
3
China India Brazil Korea Malaysia Thailand
1997 1994 1996
1996
19961996
Though this bodes well, figure 2.23 shows that China spends only about as much on
R&D as a share of GDP as does India and Brazil, more than countries like Malaysia and
Thailand, but far less than more developed countries like Korea.
Access to Finance
Economic theory holds that businesses will invest in projects where the expected
benefits exceed the costs of the investment. This efficient investment can happen,
however, only when businesses do not face credit constraints unrelated to their own
performance. Such credit constraints are less likely to occur in countries with better-
developed financial systems. Indeed, a great deal of research has demonstrated the
importance of well-functioning financial systems to growth (World Bank, 2001). In
general, countries with deep financial systems (banks, stock, and bond markets) tend to
grow faster than countries with more shallow systems. A properly-functioning financial
41
system contributes to growth by allocating financing to high-productivity investments,
which will be more effective than simply increasing overall investment.
Chinese firms have much less access to formal finance than do firms in any other
Asian country surveyed thus far. Approximately 29 percent of working capital for large
Chinese firms comes from bank loans, less than firms in Indonesia, Malaysia, the
Philippines, Thailand, or Korea (figure 2.24).
Figure 2.24 Access to capital, large firms(Share of working capital from various sources)
0%
20%
40%
60%
Retained earnings Bank loans Other (family, informal markets)
ChinaKorea
Thailand
The situation appears even worse for small and medium-size firms (SMEs) (figure 2.25).
On average, only 12 percent of SME’s working capital comes from bank loans. By
comparison, 21 percent of SME’s capital in Malaysia comes from loans, 24 percent in
Indonesia, 28 percent in the Philippines, and 26 percent in Thailand and Korea. The lack
of formal finance among small firms becomes starkly worse as firm size decreases (figure
2.26).
42
Firms with at least 100 employees finance 27 percent of their capital through bank loans,
compared to 39 percent in India. Firms with between 20 and 100 employees finance 13
percent of their capital through bank loans, compared to 38 percent in India. Firms with
fewer than 20 employees finance only 2.3 percent of their capital, on average, through
bank loans, compared to 29 percent in India.
Figure 2.25 Access to capital, SMEs(Share of working capital from various sources)
0%
20%
40%
60%
Retained earnings Bank loans Other (family, informal markets)
ChinaKorea
Thailand
One would expect that, on average, less capital would come from formal sources of
finance in smaller firms. Smaller firms tend to be younger and have a more uncertain
future, making formal financiers more hesitant to lend to them and making loans more
costly to the firm to incorporate this risk premium. On the other hand, the share of
capital financed through loans in China is lower than other countries even among large
firms, and the gap between China and other Asian countries increases as firm size
decreases. These figures strongly suggest that firms may be facing credit constraints
completely unrelated to a firm’s expected probability of being successful in the market.
43
The consequences of real credit constraints could be severe. Large firms
may have difficulty expanding or upgrading. Entrepreneurs may be unable to enter the
market at all. Such a deterrent to entry could be especially costly to the economy as
entrepreneurship—individuals taking risks to bring innovative products and services to
the market—is a key component of economic growth (McMillan and Woodruff, 2002).
Gaining access to the financial credit entrepreneurs need to launch new ideas and
businesses is an issue all over the world. But the formal financial sector should not make
the problem worse by denying access to firms by virtue of their size alone.
Conclusion
Aggregated macroeconomic indicators, while useful, mask underlying issues
facing the economy, making it difficult for policymakers to see the economy’s particular
strengths and weaknesses. Such knowledge can help devise policies targeted at
Fig.2.26 Sources of finance
India
Retained earnings
Parent Bank loan
Equity Other(largely
other loans)
<20 20-100 100 plus
China
Retained earnings
Parent Bank loan
Equity Other (largely other loans)
0
20
40
60Percent
0
20
40
60Percent
44
mitigating specific problems. This chapter explored factors that comprise China’s
investment climate, namely international integration, infrastructure, governance, entry
and exit, human resources and skills, and access to finance.
Overall, international integration increased significantly in the past decade,
culminating, of course, with China’s entry into the WTO. On this measure China
compares well to other Asian countries. Infrastructure, too, compares well to other
countries and seems to be improving rapidly. Most elements of governance compare
favorably to other countries. Human resources and skills are, despite high illiteracy rates
and low tertiary school enrollment, largely comparable to several other Asian countries
and appear to be improving.
Not all investment climate measures were positive, however. Different measures
of entry and exit were mixed, though they seemed to put China somewhat below the
median of developing countries. Moreover, the high productivity dispersion in our firm
survey suggests that entry and exit are less common than elsewhere. The clearest
problem was access to finance, which was worse than every other country in the sample.
Moreover, the gap between China and other Asian countries increased as firm size
decreased.
While this analysis takes us beneath the macroeconomic level, it still requires
aggregating lots of information into single (or just a few) indicators. Microeconomic
analysis at the business level can shed further light on these issues. We take up that
matter in the next chapter.
45
Chapter 3
Measuring the Investment Climate and its Consequences in China
3.1. Introduction.
In international comparison, China’s investment climate is reasonably strong,
with impressive improvements having been realized in the last fifteen years. Within
China, however, the investment climate is not uniform; national indicators can mask
important variations across regions. This chapter addresses the differences in the
investment climate within China, focusing on the variation across five regions. The aim
is two-fold. First, new quantitative measures of the investment climate are presented,
allowing for objective comparisons across the regions. Second, these measures are then
linked to firm performance to illustrate how improvements in different dimensions of the
investment climate can spur additional investment, sales growth and productivity. The
counterfactual analysis indicates that investment rates could be increased by up to one
quarter, sales growth could be increased by up to one half and productivity by up to one
third if the weakest cities had the investment climate indicators of the leading city.
Variation across regions in China is quite considerable, with eastern and coastal
areas generally having developed more quickly and attracted more investors than the
mid- and Western areas. There are two broad sources of factors that help explain this
phenomenon. The first is differences in natural endowments, such as access to ports and
labor endowments. The second source is the particular nature of how the Chinese
economy and policy making has been decentralized. For years, regional governments
46
have been given different degrees of discretion in setting economic policy. Thus, some
experimental provinces and cities were given greater freedom to choose more liberal
policies to attract foreign capital. Furthermore, the central and regional tax arrangements
were negotiated province by province, giving regional governments different incentives
for economic performance (Gordon and Li, 2002). These differences have also given rise
to strong regional protectionism (Poncet, 2002), as carefully documented by the State
Planning Commission (2000). Together, the differences in initial endowments, regional
discretion in policy making, tax arrangements, as well as leadership turnover patterns
have led to strong regional variations in the investment climate. This chapter seeks to use
this regional variation to understand the relative importance of different dimensions of
the investment climate and to explore the potential gains that could be realized by
improvements in investment climate indicators.9
Instead of a one-dimensional indicator of “goodness of investment climate”, we
shall offer a series of measures on the different aspects of investment climate. This
approach highlights not only the complex nature of how the investment climate affects
firms, but also emphasizes that a region can excel in some areas, while lagging in others.
To facilitate discussion, the broad array of indicators is grouped into seven categories.
The final selection of the indicators presented here is based on our empirical investigation
of the most important determinants of firm-level performance and by findings of other
researchers in the literature. In particular, we shall focus on the following areas:
integration into international markets, the pace of private sector participation, entry and
9 In this study the five regions included are among some of the stronger performers so that the differences would be even starker should less industrialized or integrated regions be included in the comparison.
47
exit barrier for firms, financial services, government efficiency, labor market flexibility,
and human capital and technology.
The measurements of the investment climate are based on a new survey of
Chinese firms. With the collaboration of the Enterprise Survey Organization (ESO) of
Chinese National Bureau of Statistics, the World Bank surveyed 1500 firms in 2001 and
2002 in five cities: Beijing, Tianjin, Shanghai, Guangzhou, and Chengdu. The survey
asks in-depth objective questions related to firm performance, production, labor,
governance, financing and technology. Rather than asking subjective questions on how
much of a problem something is perceived to be, objective quantitative data is collected.
Thus, instead of asking if red tape is an obstacle, managers are asked the amount of time
they spend with officials to meet regulation requirements. Or, rather than asking if labor
laws are restrictive, information is gathered on the share of temporary workers and the
extent to which firms have excess workers. (For more details, see the data appendix.)
This rich database provides information over three years, with large variations both in
performance over time and the investment climate across firms and regions.
After presenting the regional variations in the investment climate, the goal of the
second half of the paper is to answer the following questions: Do investment climate
indicators affect firm-level performance? If so, how important are they? How much can
we expect the cities to gain from improving their investment climate? To answer the first
question, we conduct empirical analysis relating firm-level performance (both technical
efficiency and dynamic aspects such as sales growth and investment rate) to indicators of
investment climate. To answer the second and third questions, we conduct some counter-
factual exercises, allowing cities to achieve the investment climate levels of better
48
performing cities and asking how much the typical firm in the city would gain in terms of
investment, sales growth or productivity. These exercises should be treated with some
caution; for some cities, the hypothetical improvements are substantial. The exact
predictions of the extent of benefits are less significant than the general magnitude of
potential gains and the priorities given to the different dimensions of the investment
climate.
3.2. Regional Variations in Investment Climate
The survey has a rich set of measures that could be included in this analysis. We
have restricted the presentation to those measures that were the most significant
determinants of firm performance. In our discussion of investment climate we have
usefully classified a larger list of indicators into the following categories:
1. international integration;
2. pace of private sector participation;
3. domestic entry and exit barriers for firms;
4. labor market flexibility;
5. skills and technology endowment
6. the working of financial markets;
7. government effectiveness of regulation (include physical infra);
We shall discuss how we go about measuring each category, and how the five cities differ
in these aspects.
49
1. International Integration
As noted in the earlier chapters, there is general consensus that greater openness
to international markets facilitates growth. This is true not just in the macroeconomic
level but is confirmed with micro-evidence. Many firm-level studies have found that
firms with foreign partners, firms that participate in international markets and those
facing greater import competition are more productive – particularly in developing
countries.10 Foreign entry encourages technological and managerial know-how transfers
and helps integrate the domestic market with the international market. A higher
proportion of market share accounted for by imports also puts greater pressure on
domestic competitors to improve their productivity and expands the range of available
inputs for use in domestic production. Thus a friendly investment climate would
encourage foreign entry and openness to foreign made goods.
Three measures are used here to capture the extent of international integration.
The first measures the extent of foreign ownership. It is the share of total ownership
accounted for by foreigners and is a clear indicator of the presence of foreign capital.
However, it has long been recognized that the potential for spillovers is often greater if
foreigners partner with local firms rather than enter with a wholly owned subsidiary. The
second indicator is thus the share of firms in each city that report having a foreign
partner. This partnership does often take the form of a joint venture, but this measure has
the advantage of including other types of significant collaborations beyond ownership,
including joint research and development, training and marketing.
10 For a more detailed discussions, see: Roberts and Tybout, 1996, Clerides, Lach and Tybout, 1998, Hallward-Driemeier, Iarossi, and Sokoloff, 2002, Pavcnik, 2000.
50
The inter-city comparison on international integration is featured in figure 3.1.
Figure 3.1 Difference in international integration
0
0.1
0.2
0.3
0.4Share of foreign ownershipShare of firms with foreign partShare of import in the product market
Beijing Chengdu Guangzhou Shanghai Tianjin
The front runners on international integration are Shanghai and Guangzhou. In
Shanghai, almost 40 percent of firms have foreign partners and foreign ownership
accounts for almost a third of the value of surveyed firms in that city. Guangzhou has
roughly 28 percent of firms having foreign partners, although overall foreign ownership
is higher, at 35 percent. Beijing and Tianjin are in the middle of the pack. Chengdu, the
only inland city in our sample, not surprisingly, is the laggard, with only 10 percent of
firms having foreign partners and an even lower share of foreign ownership.
The third indicator from the CICS is the market share of the main product of the
surveyed firm accounted for by imports. The higher the import share, the greater is the
exposure to international competition. Based on this measure, Guangzhou and Shanghai
have greater exposure to international competition, with the market shares accounted for
51
by imports being 11.7 and 8.8 percent, respectively. Chengdu and Tianjin have lower
openness scores, with their shares being 5.9 percent and 7.4 percent.
2. Private sector participation
In conjunction with increased competition from international sources, China has
allowed greater private sector participation domestically. As private ownership has
increased in China, growth and productivity have accelerated. Without a soft budget
constraint or guaranteed sales, private firms face greater incentives to innovate and to
respond to market signals. In the CICS sample, the private firms have significantly
higher productivity levels and investment rates than the state-owned ones. Competition
among privately owned firms is also more likely to be on a level playing field, with
resources flowing to the most productive users. SOEs can continue to operate despite
their lower efficiency due to preferential access to finance and the possibilities of bailouts
– thereby taking up resources and distorting competition among firms. Cities with strong
private participation are likely to be more dynamic and to bolster the investment climate.
In measuring the extent of private sector participation, the CICS differentiates
between three types of private owners: managerial ownership, private individual
ownership, and foreign ownership. Figure 3.2 would focus on all three types of private
ownership.
52
Share of non-managerial private
0
0.2
0.4
0.6Share of managerial ownership
Share of foreign ownershipThree types combined
Beijing Chengdu Guangzhou Shanghai Tianjin
Figure 3.2 Difference in private ownership
The foreign ownership share is repeated from the previous figure, to illustrate the
importance of the role foreigners have played in increasing the private participation in
these cities and to highlight the complementary nature of this and previous categories of
the investment climate. Including all three types of private ownership also allows for a
test if there are significant differences between them – or whether the real difference is
between private ownership and government ownership.
Figure 3.2 depicts the distribution of private ownership among the cities. To
facilitate interpretation, the last bar sums up the total share of private ownership.
Guangzhou is the front runner in terms of private sector participation, followed by
Tianjin and Chengdu. Shanghai is the laggard. The distribution among the alternative
types of private sector participation differs, however. Chengdu is characterized by the
largest managerial ownership and non-managerial private ownership, but the lowest share
of foreign ownership. In fact, the deficit in foreign ownership for firms in Chengdu is so
53
large as to completely offset the surplus in the other two types of private ownership. The
case of Chengdu highlights the potential problems faced by inland firms: the difficulty to
attract foreign participation. Shanghai is characterized by a reasonable level of foreign
ownership (ranked just behind Guangzhou) but a lackluster pace in domestic private
ownership.
3. Domestic entry and exit barrier
Both policy makers and economic researchers have noted the strong domestic
barriers to entry and exit in China. The State Development Planning Commission, for
instance, has organized an ad hoc team to study this issue, and published a book on this
topic in 2000 (SPC, 2000). The World Bank country team has also called for further
study on regional protectionism. Here we thus try to measure the entry and exit barriers
in the five cities from a number of perspectives.
The first measure of regional entry and exit barriers is a measure of border effects
constructed recently by Poncet (Poncet, 2002). She directly analyzes trade in goods to
obtain estimates of “border effects”—how much provincial borders deter trade.
Comparing trade across borders with trade within borders -- taking into account factors
like transport costs and geographical barriers – she calculates what would be the
necessary tariff rate to produce the same pattern of trade if all the markets were perfectly
integrated. (Gilley, 2001). The imputed tariff level is the “border effects”. Thus, the
higher the border effect, the greater the trade barrier erected by a province. For the year
1997, the most recent year for which the data is available, this measure (called “regional
protection” in figure 3.2) was highest for Chengdu, followed by Beijing, Tianjin and
54
Shanghai.11 The least protectionist was Guangzhou, at less than half the level of
Chengdu.
Three other measures of entry and exit barrier come from the CICS. First, CICS
inquires about the market share claimed by the main product of the surveyed firm. This
is not a perfect measure of market competition because, on one hand, a higher figure
could mean a higher entry barrier, and on the other hand, it could imply more efficient
firms in that location. Figure 3.3 suggests that Guangzhou firms have the lowest market
share, at 7.9 percent, followed by Chengdu at 11.1 percent. The firms claimed the
highest market share in Beijing (16.7 percent) and Shanghai (16.5 percent).
Figure 3.3 Difference in entry and exit barriers
Beijing Chengdu Guangzhou Shanghai Tianjin
Regional protectionMarket shareExcess capacityShare of subcontracting
0
0.1
0.2
A second measure is based on the share of costs used to hire subcontracting firms. The
more flexible the market, the less need there is for firms to keep all their activities in- 11 We assume the level of protection is the same within a province.
55
house. The availability of sub-contractors indicates a greater ease of entry for firms, a
greater specialization of production and would be expected to be an attractive feature of a
location. Shanghai leads on this measure, following by Beijing. Chengdu has a
significantly lower share of subcontracting services.
Finally, a nice measure of exit barriers is provided by the excess capacity of the
firm reported in the CICS. Firms often continue to operate with a certain amount of
excess capacity given adjustment costs associated with investment and the hiring and
firing of workers. However, larger shares of excess capacity indicate that the barriers to
exit can be substantial. Chengdu and Beijng top this measure of exit barriers, with their
ratios being 22.1 and 20.5 percent, respectively. Guangzhou and Shanghai are again
better, at 16.9 and 17.2 percent, respectively. Thus the overall impression is that
Guangzhou and Shanghai have lower entry and exit barrier, and Chengdu has the higher
barriers, with Beijing and Tianjin in between.
4. Labor Flexibility
Besides product markets, an important ingredient for a healthy investment climate
is the functioning of labor market. A healthy labor market is characterized by flexibility,
including low exit barriers. While these variables could have been incorporated into the
general category on entry and exit barriers, the particular importance of such features in
the labor market warranted its own category. Exit barriers shows up in forms such as
specific requirement not to fire workers, government interference in shedding redundant
workers, rules or regulations that restrict hiring seasonal and contract workers, or
requirements on firms to provide insurance, medical care and pensions. The CICS data
56
provide two measures of exit barriers for labor. The first is the share of workers or staff
that is non-permanent. Since it is much easier to shed temporary or seasonal workers, a
higher share of non-permanent staff represents a lower exit barrier.12 In addition, firms
were asked directly whether they were overstaffed – i.e. what share of their workforce
would they consider redundant if there were no penalties associated with laying-off
workers. Thus, more flexible labor markets would be characterized by higher non-
permanent labor ratios and lower overstaffing-ratios.
Figure 3.4 shows clearly that Guangzhou leads other cities in terms of reducing
exit barrier in the labor market. Firms in Guangzhou on average only have 6 percent of
redundant workers, yet almost 21 percent of non-permanent workers. Shanghai likely
ranks the second. Its share of non-permanent workers is 14 percent, slightly lower than
that of Tianjin (14.7 percent), but its overstaffing ratio is only 7.5 percent, more than 10
percentage points lower than the other three cities. Chengdu is the laggard, with 12
percent of workers being non-permanent, yet a overstaffing ratio of 20 percent. Beijing
and Tianjin are once again in the middle of the pack.
12 It is true that in some instances the reliance on a large temporary staff is an indication of high exit barriers (i.e. firms hire temporary workers as a way to get around the burdens imposed by regulations). However, we argue that given the nature of China’s migratory labor and residency requirements, allowing the hiring of temporary workers is actually a sign of greater flexibility and a loosening of labor requirements.
57
Figure 3.4 Differences in labor flexibilityOver-staffing ratioNon-permanent labor
0
0.1
0.2
Beijing Chengdu Guangzhou Shanghai Tianjin
5. Skills and technology
Investors are likely to be pulled to locations with abundant skilled workers and
advanced technology. To gauge the skill and technology position of each city, we use
CICS information to construct three indicators. The first is the share of workers with
formal training. Training enhances workers’ skills and productivity. The second is an
index of worker quality, which increases with the shares and schooling levels of technical
personnel and of managerial and sales personnel. We focus on the technical and
managerial (and sales) personnel because they are likely more skilled than the other types
of employees (such as production workers and auxiliary workers). A final measure is an
index of R&D intensity, which increases in R&D expenditure per worker, the ratio of
R&D staff (in all the staff), and an indicator of the extent of reliance of outsider R&D
services.
58
Figure 3.5 suggests that no city is an unambiguous leader in all departments.
Indeed, Shanghai, Beijing and Chengdu appear to be significantly stronger in terms of
skills and technology endowment. Firms in the Shanghai sample have 57 percent of their
workers trained (ranking behind Guangzhou), rank the highest in staff quality, and second
highest in R&D intensity. Firms in Chengdu have roughly half of their workers trained,
ranks the third in staff quality, but the highest in R&D intensity. Firms in Beijing have
48 percent of their workers trained (ranking the fourth), the second best ranking in staff
quality, and the third best ranking in R&D intensity. In contrast, although Guangzhou
has the highest ratio of trained staff, it ranks lowest in staff quality and R&D intensity.
This may reflect the high ratio of migrants in Guangzhou’s workers, and the low-tech
nature of firms in Guangzhou. Tianjin features the lowest ratio of trained staff, the
lowest intensity of R&D, and the second lowest quality of staff.
0
0.2
0.4
0.6
0.8Share of workers trainedIndex of quality of staffR&D intensity index
Beijing Chengdu Guangzhou Shanghai Tianjin
Figure 3.5 Difference in skills and technology
59
6. Financial services
A healthy financial service industry is vital for firms. It frees firms from financial
constraints, allowing firms short of internal funds to expand beyond their own capacity.
In the CICS data we have a number of indicators about the ability to obtain financial
services including funding. For a parsimonious specification of how financial services
differ among regions we constructed a index of availability of financial services. The
index increases in the availability of external financing such as the availability of foreign
loans, bank financing, parent company financing and the availability and amount of trade
credit. The index decreases with the extent that the firm has to rely on own retained
earning or own family financing.(See appendix 1 for more information on the
construction of this index). Figure 3.6 shows that Shanghai is clearly the leader in
availability of financing. Guangzhou is second. Beijing and Chengdu are in the middle,
while Tianjin lags behind.
0
1
2
Beijing Chengdu Guangzhou Shanghai Tianjin
Figure 3.6 Differences in financing availability
60
7. Government effectiveness
Over the last decade, economists have increasingly paid attention to the role that
the state plays for a healthy economy. Indeed, an economy is expected to work much
better when the state sets up a level playing field, when bureaucrats are more interested in
enforcing efficient rules rather than maximizing bureaucratic budgets, when the
government provides sufficient resources to set up an environment characterized by an
adequate supply of public goods (i.e., public safety, infrastructure) (Shleifer and Vishny,
1999).
To measure the effectiveness with which the government provides public goods
and plays the role of “helping hand” rather than “grabbing hand”, we construct three
measures. The first is a measure of informal payment, constructed as the share of sales
spent on gift or bribes to government and regulatory agencies (or called “informal
payment”). The second measure captures the costs to the firm in terms of the share of
time that senior managers spend receiving government officials. This reflects the
cumbersome nature of meeting extensive regulatory requirements, can be a further
indication of corruption and represents an important opportunity cost on the part of
CEOs. The third measure is the share of shipments lost due to theft, breakage or spoilage.
Since pubic safety and ports are largely the business of the government. The losses
occurred should reflect the lack of efficiency associated with government services and
poor infrastructure.
Figure 3.7 suggests that the relative ranking for the three indicators differs a lot
among the cities. For instance, cities with relatively lower informal payments to
government regulators are Shanghai, Guangzhou and Beijing. Yet if you look at
61
managerial share of time on regulation requirements, the lowest are Chengdu,
Guangzhou, and Shanghai. When examining the share of shipment loss due to theft and
other factors, the ranking differs again from the other two. Various aspects of
government efficiency thus do not necessarily agree with one another. Not surprisingly,
we shall later find that for these five cities inter-city performance differences do not
strongly hinge on measures of government efficiency.
0
0.05
0.1
0.15
Figure 3.7 Difference in government effectiveness
Beijing Chengdu Guangzhou Shanghai Tianjin
Payment to regulators as percent of sales x 100Share of managerial time on regulationsShare of loss due to theft x 10
A brief summary: A score card for the cities
Table 3.1 present a summary table about the key ingredients of investment
climates. It is apparent that Guangzhou and Shanghai are clear leaders in investment
climate, while Chengdu and Tianjin lags the farthest. Beijing is in the middle of the
pack. We next investigate whether the relative rankings in terms of investment climate
carry through to economic performance, what are the key investment climate ingredients,
62
and what are the expected gains for each city if it achieves high standards in investment
climate.
Table 3.1 Cities vying for the best investment climate: a report card
Shanghai TianjinGuangzhouSecond
Best
Best
Second
Tied at the middle, but with worst staff quality
Best
Low in informal payment & regulatory burden, high in shipment loss.
International integration
Fourth
Domestic entry and exit barrier
Third
Labor flexibility Tied at third
Financial services
Worst
Skills and technology
Worst: worst in both training and R&D intensity
Private sector participation
Tied at second: a high share of foreign ownership
Government efficiency
Second
Second
Best
Best
Worst
Low shipment loss & informal payment, middle in regulatory burden
Relatively high informal payment; middle in regulatory burden and shipment loss
ChengduWorst
Worst
Worst
Fourth
Tied at the middle
Tied at second: a high share of outside private ownerships
High informal payment; middle in shipment losses, low regulatory burden
Beijing Third
Fourth
Tied at third
Third
Tied at the middle: good staff quality, but little training of staff
Third
middle in informal payment, but bureaucratic, with significant shipment losses
3.3. Impact of the Investment Climate
To investigate whether the various ingredients of investment climate really
matter, we investigate how they affect some common measures of economic
performance. In particular, we focus on three variables: sales growth, investment rates,
and productivity. The first is the annual growth rate of sales. The investment rate is
measured as new investment over the original value of fixed assets. Productivity is
measured as the relative efficiency in generating value added holding constant the
63
amount of labor (as measured by the number of employees) and capital stock (see the
technical appendix for the details of estimating total factor productivity, abbreviated as
productivity). Sales growth and investment rate measure the dynamism of the firms, the
pace at which their businesses are expanding, and productivity measures the relative
efficiency of firms in generating value.
The key questions that this section aims to answer are: Does the investment
climate matter? If so, what are some of the key ingredients? What magnitudes of gains
are expected with a significant improvement in investment climate? What are some of
the key areas that each city can work on to expect important gains in performance?
In what follows, we shall first briefly introduce the background of our
methodology. Then we conduct counterfactual exercises to see how firms in each city
would perform if they could operate in a better environment.
Methodology
Our exercises are based on the empirical investigation of how the three
performance measures (i.e., sales growth, investment rate, and productivity) are affected
by the investment climate, holding constant some basic characteristics such as macro
shocks, industry affiliations, firm size (including both the number of employees and
initial revenue). The set of investment climate indicators presented here reflect those
elements that: (1) the government can do something about, (2) are widely viewed as
important, and (3) have important explanatory power.
64
The statistical relationship between the performance measures and investment
climate are reported in the technical appendix. The main findings can be summarized
succinctly as follows:
1. Overall, international integration affects performance significantly. Firms with a
foreign partner or that have foreign ownership have significantly higher growth
rates and productivity levels. However, somewhat surprisingly, the effect on
investment rates is less. This may be due to foreign owned firms generally being
newer (the average age of a foreign owned firm is 5 years versus 15 years for
those without foreign ownership) so that they are already operating with more up
to date equipment.
2. The development of the private sector also improves firm performance. Including
all three types of private ownership allows for a test of whether there is a
difference in the type of private ownership for firm performance. While
managerial owned and foreign owned have the strongest association with better
performance, the differences between any one of the private ownership measures
and SOEs dwarves the differences between the three ownership types. This
finding echoes another that is based on an entirely different data set of Chinese
firms (Xu, Zhu, and Lin, 2002).
3. The reduction of entry and exit barriers explains a significant part of all three firm
performance measures, although the importance of the specific sub-indicators
varies across them. For instance, firms in provinces with higher protectionism
have lower investment rate and productivity. Firms with higher excess capacity
had lower sales growth rate and productivity. Firms with higher market share also
65
have better performance when being judged by all three measures, supporting the
idea that market share is not a proxy for entry barriers but rather greater
efficiency. Finally, a higher share of sub-contracting contributes to higher sales
growth, investment, and productivity.
4. Labor market flexibility can have important consequences, particularly for
productivity. The percent of non-permanent (or flexibly-deployed) workers is
positively associated with all three performance measures, while the percent of
overmanning is negatively correlated with productivity.
5. Skills and technology availability contribute in positive ways. The training of
employees is associated with better performance based on all three measures; so is
a higher quality of employees. Research and development intensity improves
firms’ investment rate and productivity.
6. The availability of financial services has an impact. When firms have better
access to financial services, their sales growth rates and productivity are both
higher. This finding is consistent with cross-country evidence that financial
development is associated with a significantly higher growth rate of GDP (King
and Levine, 1993).
7. There is also some evidence that governance affects performance. Firms in a city
characterized by a higher level of informal payments had lower sales growth and
productivity. Moreover, managerial time spent dealing with regulatory officials
have a negative effect on sales growth.
66
A number of caveats should be kept in mind in interpreting these findings. First,
these relationships indicate correlation, not causation. For a number of measures there is
potential endogeneity problems (e.g. productive firms could have better access to finance
and not just that better access to finance boosts productivity) that can bias coefficients
upward. On the other hand, there is likely collinearity between a number of the different
investment climate indicators that could reduce the significance of some variables. Also,
the cities included in the study are all relatively strong performers within China. A
number of potential bottlenecks in other regions may not appear as constraining in this
study. Overall, that the results are robust across the different performance measures
bolsters confidence in the findings. The direction and general magnitude of the findings
are informative, but too much emphasis should not be placed on the exact coefficients.
What remains to be seen are what the key determinants of inter-regional
variations in firm performance are, and what is the potential gain that a city can expect
from improving its investment climate. To these ends, we conduct a counterfactual
analysis. First, we identify a leading city for each performance measure. For sales
growth and investment, Guangzhou is the leading city, while for productivity, Shanghai
is the leading city. The leading city is taken as the benchmark and compared to each of
the other remaining cities. The exercise is to see how the comparator’s performance
would change if its investment climate indicators were at the levels of those of the
leading city. We can then infer the contribution of each category of investment climate to
the performance differential between the two cities.
It should be noted that the leading city on performance does not necessarily have
the leading investment climate indicators in all categories – so for some dimensions in
67
some cities the counterfactual could actually detract from performance. The
counterfactual aims to be realistic; that the level of reform that is hypothesized is within
the reach of the cities being studied. It allows for each category of investment climate
indicators to be improved individually – as well as indicating the overall impact if all
indicators were changed simultaneously. This latter exercise is clearly more of an upper-
bound estimate, but remains within plausible bounds.13
Investment Rate
Guangzhou is the leading city in terms of investment, with a rate of 19.4 percent.
The counterfactual compares other cities with Guangzhou, reporting how their
investment rates would change if each category of investment climate indicators were
changed to the level enjoyed in Guangzhou. Figure 3.8 presents the average level of
actual investment rates. They are 15.9 percent for Beijing, 15.6 percent for Shanghai,
14.2 percent for Chengdu, and 13.6 percent for Tianjin. The second bar then reports the
potential investment rates each city could experience if all its investment climate
indicators were at the same level as Guanzhou’s. Thus Tianjin and Chengdu, the cities
with the lowest investment rates would experience the greatest improvements to the
investment climates and would reap the greatest increase in investment. Under this
counterfactual, Beijing would marginally have the highest overall potential rate of
investment.
13 To the extent that this is the local maximum among only the five cities, there could be even greater potential to improve for our sample cities.
68
Figure 3.8 Investment rate: actual versus realistic potential
0
0.05
0.1
0.15
0.2Investment ratePotential investment rate
Beijing Chengdu Guangzhou Tianjin
Figure 3.9 looks at the contribution made by each category of investment climate
indicators individually. Overall, lowering entry and exit barriers, greater international
integration and better skills and technology are the most important sources for reform to
boost investment rates. However, there are clear differences across cities.
For Beijing, the overall increase in investment would be about 3.4 percentage
points. Entry and Exit plus labor market flexibility are the two most important sources of
gain. These are followed by skills and technology plus international integration. The
effects of greater private participation’s contribution is marginal. For Chengdu, the total
contributions are larger, an increase in investment rate by 3.9 percentage points.
Improvements in entry and exit barriers alone would increase investment by almost 3
percent. Greater integration and labor flexibility would together increase investment a
further 2 percent. One striking feature is that changing private sector participation would
actually lower investment rates. Referring back to figure 3.1 explains why. While
69
Chengdu overall ranks in the middle with regard to private participation, its composition
is heavily skewed away from foreign private ownership (the category that enters in
international integration.) Thus, relative to Guangzhou its non-managerial and
managerial domestic private participation is higher – lowering the levels to those of
Guangzhou would hurt Chengdu.
Figure 3.9 Investment rate gains with Guangzhou’s IC
Beijing Chengdu Shanghai Tianjin
International integrationEntry and exitLabor market flexibilityFinanceSkills and technologyPrivate sector participation
-0.02
0
0.02
0.04
The improvement in Shanghai’s investment rate is relatively small (2.5
percentage points). This is largely due to Shanghai’s investment climate indicators not
differing too substantially from the benchmark of Guangzhou. On those dimensions
where Shanghai is stronger, the change due to the counterfactual actually serves to reduce
the measured potential investment rate. Four areas where improvement would assist
Shanghai are greater private sector participation, international integration, labor market
flexibility, and lower entry and exit barriers.
70
Tianjin has the lowest investment rate among the five cities and sees the largest
improvement (4.1 percentage points) coming from all indicator categories. The dominant
source of improvement comes from better skills and technology. Lower entry and exit
barriers, including those in the labor market, are also important.
Sales Growth
The four other cities trail Guangzhou significantly in sales growth rate. The
average sales growth rates, from the highest to the lowest, are 30 percent for Guangzhou,
22 percent for Beijing, 21.8 percent for Shanghai, 20.3 percent for Chengdu, and 18
percent for Tianjin (see figure 3.10).
Figure 3.10 Sales growth: actual versus realistic potential
0
0.1
0.2
0.3Sales growthPotential sales growth
Beijing Chengdu Guangzhou Tianjin
The counterfactual exercise would raise sales growth the most in Chengdu, an
increase of 10.7 percentage points. Beijing and Tiajin would realize increased growth of
around 8 percentage points, while Shanghai would only gain about 2 percentage points.
71
The difference is not so much due to Shanghai having that much higher a sales growth
rate (it doesn’t), but that the improvements in the investment climate proposed in the
counterfactual are not that large.
Figure 3.11 Sales growth gain with Guangzhou’s IC
-0.05
0
0.05
0.1International integrationEntry and exitLabor market flexibilityFinanceSkills and technologyPrivate sector participation
Beijing Chengdu Shanghai Tianjin
As illustrated in figure 3.11, the lagging of Beijing behind Guangzhou in sales
growth can largely be explained by the lower degree of international integration,
followed by labor market flexibility, skills and technology, and entry and exit barrier.
Using the assumptions of the counterfactual, growth could be increased by as much as 8
percentage points.. As with Beijing, greater international integration is also the largest
source of increased sales growth for Chengdu. However, in this case the expected benefit
is 7 percent points of growth rather than 2.5 points for Beijing as the gap in integration
measures is considerably larger for Chengdu than for Beijing. Entry and exit barriers are
the next most important factor for Chengdu’s growth performance. As with the
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investment counterfactual, Chengdu has a negative contribution from changing its private
sector participation.
For Shanghai, there is only a very little gained in terms of increased growth. This
is largely due to the relative strength of Shanghai’s own investment climate indicators;
changing the indicators to the levels realized by Guangzhou does introduce some
improvements, but in other areas it weakens Shanghai’s position. Thus, greater private
participation, international integration, and labor flexibility would increase growth, but it
is almost offset by the greater entry barriers and reduced access to finance. Under the
assumptions of the analysis, if only those categories that improved were included,
Shanghai could realize higher growth on the order of 4 to 5 percent.
For Tianjin the most important source of improvement in sales growth is skills
and technology, followed by integration, finance and labor flexibility. Private
participation has virtually no effect.
73
Productivity
Figure 3.12 Productivity: actual versus realistic potential
ProductivityPotential productivity
Beijing Chengdu Guangzhou Tianjin-0.4
-0.2
0
0.2
0.4
For productivity, the leading city used in the counterfactual is now Shanghai. Its
performance on this dimension is particularly impressive; the productivity gap appears to
be quite large. The average productivity of Shanghai exceeds those of Beijing, Chengdu,
and Tianjin firms by a significant margin. Tianjin appears to have the lowest
productivity, with Beijing and Chengdu immediately following, and the differences
between Beijing and Chengdu are quite small. Firms in Guangzhou have the second
highest level of productivity, not too far behind Shanghai. Plotting the relative
productivity levels on figure 3.12, the y-intercept is at the overall average level of
productivity (as TFP is an index, centered on zero). Thus, positive bars indicate above
average performance and negative bars indicate below average performance. Bringing
the investment climate indicators to the level of Shanghai’s would lead to substantial
74
productivity gains for Beijing and Tianjin, but the city that would experience by far the
largest gain would be Chengdu. Guangzhou, on the other hand, would experience
virtually no change in productivity as it is close to Shanghai in overall investment climate
(and in productivity). Thus the lagging of productivity of Guangzhou behind Shanghai is
largely explained by non-investment-climate factors such as industry composition.
Figure 3.13 Productivity gains with Shanghai’s IC
-0.1
0.1
0.2
International integrationEntry and exitLabor market flexibilityFinanceSkills and technologyPrivate sector participation
Beijing Chengdu Guangzhou Tianjin
0
Figure 3.13 sheds light on why the three cities trail Shanghai so far in productivity. For
Beijing, entry and exit barriers, integration, skill and technology, and finance are all
important. Overall, its productivity would increase almost 26 percent,14 with integration
and entry and exit each explaining increases of 8 percent.
For Chengdu, greater integration and the removal of entry barriers is impressive,
improving productivity each by roughly 20 percent. Labor market flexibility, finance,
14 That is, 123.0 −e
75
and skills and technology are important in similar magnitudes, each contributing another
3 percent to productivity gains. Private participation shows up as a negative in the
counterfactual because Chengdu has higher private participation than Shanghai to begin
with so that becoming more like Shanghai in this dimension is a negative. The total
expected gain in productivity could be 56 percent.
Guangzhou overall would not gain anything in terms of improved productivity by
being more like Shanghai. On the one hand, improvements would be observed with
Shanghai’s skills and technology and access to finance. On other hand, these gains are
offset because Guangzhou was found to be better than Shanghai in the important areas of
entry and exit barriers, labor market flexibility, and private sector participation.
The improvement in skills and technology would boost Tianjin’s productivity by
more than 10 percent. Integration is the second largest source of improvements, with
finance and entry and exit barriers the next most important sources. Overall, Tianjin
could improve productivity by 31 percent by reforms that brought its investment climate
to the level experienced in Shanghai.
3.4. Policy Implications
We have focused on three tasks: (1) constructing measures of the investment
climate; (2) demonstrating that the investment climate matters for sales growth,
investment rates, and productivity; (3) investigating the reasons for performance
differences among cities, the contribution of each category of the investment climate, and
the performance potential from improved investment climate indicators. What policy
implications can we draw from this investigation?
76
The first policy implication is that local government can improve regional growth
potential significantly. We have demonstrated that the five large cities differ greatly in
the three performance measures, and that the growth potential of improving the
investment climate could be huge. For instance, sales growth could increase up to ten
percentage points and productivity could increase by a half from improving the key
investment climate obstacles for cities such as Chengdu or Tianjin – and keep in mind
that these cities are likely among the better performers in the larger scheme of China’s
numerous cities. Another important implication from the regional variations is that
market segmentation in China is likely quite severe, otherwise free flow of resources
among regions would narrow down the differences.
Starting from a longer initial list, the empirical investigation found the following
categories of investment climate to be especially important: international integration,
private sector participation, entry and exit barriers, skills and technology, labor market
flexibility, and financial services.15 Within the category of labor market flexibility, we
find that it is particularly important to create conditions to allow for flexible labor force.
Another interesting finding is that cities have their distinct advantages and
disadvantages:
�� Shanghai shines as the most productive city and is clearly the center of higher
value added activities. The city is characterized by a strong degree of international
integration as viewed by the share of firms with foreign partners, although overall
15 Government efficiency was included in the analysis, but the significance of the effects were small enough that they were excluded from the counterfactual graphs and discussion. The lack of significant differences in performance on these measures across cities accounts for why this category is not particularly relevant in understanding differences within China – it does not imply that the topic is not important looking at China vis a vis other countries, or potentially if the regional coverage within China were extended.
77
foreign ownership and import penetration are lower than in Guangzhou. It also
has the strongest financial services, and has good entry and exit conditions and
labor market flexibility. Shanghai’s top issue for reform would be to improve its
domestic private sector participation. Secondary areas for reform would be to
encourage greater foreign ownership and import penetration to boost its sales and
investment, as well as greater flexibility in the use of temporary workers.
�� While Guangzhou does not produce as sophisticated products at Shanghai, it
nonetheless uses its advantages to claim the highest sales growth rate and investment
rate. It has the most flexible labor market, fluidity of entry and exit, government
efficiency, and private sector participation. Its international integration is also
reasonably strong. For Guangzhou, upgrading skills and finance would be the top
issues to consider for reform.
�� Beijing is largely in the middle of the pack, with no especially strong advantage or
disadvantage. It could benefit from some focus on greater labor market flexibility,
entry and exit, and international integration.
�� Tianjin is good in private sector participation, and in the middle of the pack in terms
of entry and exit fluidity and labor market flexibility. For Tianjin, reforms in skills
and technology should dominate the reform agenda, with improvements in
international integration and government efficiency as secondary areas of focus.
�� Chengdu, the only inland city we have surveyed, lags the farthest in most
performance measures as well as in investment climate indicators. However, it does
have a good level of private sector participation, with reasonable skills and especially
78
technology. For Chengdu, the top priorities for reform should be to foster greater
international integration and to lower entry and exit barriers.
While we have answered some of the questions posed earlier, it is important to
keep in mind some of the limitations associated with the survey work and the questions
that it can address. First of all, the results need to be treated with some caution. The
estimates should be seen as indicative of the relative importance of different dimensions
of the investment climate rather than exact predictors of how performance will change
should reforms be enacted. Still, the consistency in the regression results across the three
performance measures and that the levels considered in the counterfactual are based on
those actually achieved by the leading city, reinforces the credibility of this analysis.
Second, some dimensions of the investment climate did not receive much attention in this
study. This could be due to all cities having relatively strong performances on that
dimension or because there was little variation across cities for that measure. Given the
nature of the counterfactual, if all cities receive close to the same measure on an
indicator, the scope for improvement in the exercise is limited. Thus, physical
infrastructure does not get much attention here; all five have good indicators, certainly
against the rest of the country. Likewise, the government efficiency indicators do not
vary as much across cities, leaving little scope of its importance to be demonstrated in the
counterfactual analysis. The lack of attention on these issues here does not imply that
they are not potentially constraining factors for other areas within China or for explaining
China’s performance relative to other countries. Third, some important consequences of
the investment climate cannot be captured by survey data. For instance, the survey
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cannot address some issues surrounding entry and exit as firms that did not enter the
market or those firms that did exit could not be included in the sample. Fourth, there are
no doubt other important aspects that are left out in the categories of our investment
climate. One example is the effect of tax rates and special incentives – topics that are
certainly of interest but were deemed too difficult to get reliable responses on. Finally,
the current survey does not represent enough variation for inland cities. Future surveys
covering diverse inland locations are keenly needed, and currently under discussion
between the Enterprise Survey Organization and the World Bank team.
80
Technical Appendix
Data
The data on investment climate are based on two surveys that the World Bank
conducted with the Enterprise Survey Organization of Chinese National Bureau of
Statistics. The first survey was done in 2001, covering 300 firms in each of five cities:
Beijing, Tianjin, Shanghai, Guangzhou, and Chengdu, for a total of 1500 firms. The
survey collected detailed information on financial statements, and different aspects of
corporate governance, financing, firm-government relationship, innovation, technology,
labor, and so on. Most quantitative questions cover the period 1997 to 2000, and most
qualitative questions cover only the time of the survey.
The second survey covers the same set of firms, with a small percentage of firms
having disappeared between the first and the second survey. The questionnaire covers
the following aspects: investment climate constraints to the establishment, infrastructure
and services, finance, labor relations, sales and supplies, business-government relations,
conflict resolution and legal environment, crime, capacity, innovation and learning.
The sample firms consist of both manufacturing and service firms. The industries
covered include: clothing and leather products (14.1 percent); electronic and
communication equipment making (12.5 percent); electronic components (14.7 percent));
household electrical goods (11 percent); auto and auto parts (14.4 percent); information
technology services (8.9 percent); communication services (4.6 percent); accounting,
auditing and nonblank financial services (7.1 percent); advertising and marketing services
(5.8 percent); business logistics services (7 percent). Within the sample, firms vary
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substantially by size and by ownership type. The samples are randomly chosen given
pre-determined distribution by city and broad industry and size strata.
Construction of TFP
The total factor productivity is estimated using a production function as follows:
iti
J
jitjKitjLijtit eKLDV εααβ ++++= �
=10 )lnln(ln (A.1.)
where itV is value added for firm i and period t. itL and itK are the number of
employees and the capital stock, respectively. The capital stock is proxied by the original
value of fixed assets, the only time-varying measure we have for capital stock. ijtD is a
dummy variable that is one if firm i is affiliated with sector j. In total we have ten
industries as mentioned above. So equation (A.1.) essentially allows sector-specific
shares of labor and capital. The total factor productivity is then constructed as the
estimate of itie ε+ , the part of value added that is not explained by capital and labor.
Regressions framework
To examine how various elements of investment climate affect performance, we estimate
the following regressions:
itiit ICXY εβββ +++= 210 (A.2)
where Y could be sales growth rates, investment rate, or total factor productivity as
constructed above. X are a set of control variables, including industry dummies (to allow
the performance to have an industry-specific mean), year dummies (to capture macro
shocks, changes in macro policies, and technological changes over time), the logarithm of
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the number of employees, and the logarithm of initial sales. The last two measures are
intended to capture things such as economies of scale or any other aspects related to scale
(market power and so on). IC is a vector of indicators related to investment climate. The
results, along with some notes concerning the construction of some of the used measured,
are reported in Table A.1.
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Table A.1. The Impact of Investment Climate
(1) Sales growth rate (2) Investment rate (3) Total factor productivityForeign ownership 0.211 0.045 0.363 (0.045)*** (0.017)*** (0.102)*** Has a foreign partner 0.045 -0.017 0.369 (0.026)* (0.010)* (0.060)*** Import share for the most -0.077 -0.025 0.231 important product of the firm (0.071) (0.026) (0.156) Index of provincial price -0.109 -0.120 -0.630 segmentation (0.141) (0.053)** (0.324)* Market share of the most 0.146 0.048 0.264 important product of the firm (0.051)*** (0.019)** (0.117)** Excess capacity ( percent) -0.272 -0.029 -0.944 (0.053)*** (0.020) (0.120)*** Subcontracting (percent) 0.228 0.119 0.462 (0.105)** (0.039)*** (0.234)** Overmanning (percent) -0.025 -0.008 -0.163 (0.019) (0.007) (0.069)** Non-permanent workers (percent) 0.168 0.102 0.662 (0.041)*** (0.015)*** (0.093)*** Share of labor with formal 0.106 0.041 0.143 training (0.023)*** (0.009)*** (0.054)*** Quality of labor staff 0.075 0.020 0.315 (0.012)*** (0.004)*** (0.026)*** Index of RD intensity 0.003 0.019 0.093 (0.011) (0.004)*** (0.023)*** Managerial ownership 0.237 0.104 0.076 (0.080)*** (0.029)*** (0.176) Private individual 0.153 0.065 0.233 ownership (0.040)*** (0.015)*** (0.090)*** Index of corruption -4.167 0.644 -32.897 (2.931) (1.043) (7.029)*** Manager’s time on meeting (percent) -0.155 -0.000 0.021 regulation requirements (0.085)* (0.032) (0.197) Shipment costs lost due to theft, -0.152 -0.067 -0.456 breakage, and spoilage (percent) (0.180) (0.067) (0.415) Index of financial services 0.027 0.001 0.039 (0.009)*** (0.003) (0.018)** Log (number of employees) 0.067 0.005 (0.011)*** (0.004) log (initial sales) -0.083 -0.009 (0.008)*** (0.003)*** Year, industry indummies yes yes yes Observations 3128 3116 2818 R-squared 0.10 0.12 0.79
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Notes.
1. *, **, *** represent statistical significance in the 10, 5, and 1 percent levels. The
model specification is ordinary least squares.
2. Sales growth rate is winsorized at 5 and 95 percentiles to make sure that the results
are not driven by outlier: that is, replaced the lowest 5th percent observations with
the 5th percentile, and the 95th to 100th percentile with the 95th percentile values. The
sales growth rate is much more skewed than other variables such as investment rate.
For investment rate, we replaced negative number and number greater than 1 with 0
or 1; only fewer than 10 observations are affected. Similarly, total factor productivity
is winsorized at 1 and 99 percentiles.
3. The construction of some measures involved the following details:
1) Percent subcontracting: assumed to be zero if the answer is not applicable.
2) Excess capacity, not asked by service firms, and is assumed to be zero given the
relatively low excess capacity and the lower need for fixed assets investment.
3) The informal payment variable is cleaned as follows. Upon examining its
distribution, we find that there are 12 observations that are clearly outliers (i.e.,
those greater than 0.07), ranging from 0.49 to 28.57. The mean of this variable is
only 0.02 (including these outliers). In empirical implementation, we drop these
outliers.
85
4) The index of financial services is constructed as a principal component of the
following variables as follows:16
0.31 * share of input bought on trade credit + 0.44 * log(1+number of banks to do
business with) + 0.28 * share of loans denominated in foreign currencies + 0.50 *
the dummy variable of having overdraft facility or line of credit + 0.52 * the
dummy variable of having a bank loan + 0.004 * share of financing from parent
company or other partner companies + 0.13 * share of financing from trade credit
+ 0.13 * share of financing from “other sources” - 0.17 * share of financing from
retained earning or funds - 0.22 * share of financing from managerial families.
5) The index of staff quality is a principal component index of a number of
indicators of the human capital level of firm staff, constructed as 0.51 * share of
technical personnel + 0.36 * share of management and sales personnel + 0.54 *
average schooling of technical personnel + 0.57 * average schooling of
management and sales personnel. For graphing purposes, this variable is
renormalized by the addition of a constant, 0.50.
6) The index of RD intensity. A principal component of the following RD variables,
including log(1+ real RD expenditure per worker), percent of staff as RD staff, a
index of whether buying RD services outside. A constant of 0.50 is then re-
normalized into this index for graph presentation purposes.
Note that most of these variables are observed only for the year 2001. In our
empirical analysis we assume the prior years to have the same value.
16 For graphing purpose but without affecting any of our analyses, a constant of 1 is added to this variable.
86
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