resources, energy and tourism china review

Resources, Energy and Tourism China Review June 2013

Resources, Energy and Tourism China Review

June 2013

Resources, Energy and Tourism

China ReviewJune 2013

ii China Review • June 2013

© Commonwealth of Australia 2013

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ISSN (Print) 978-1-922106-07-0

ISSN (PDF) 978-1-922106-08-7

This publication was jointly undertaken by the Bureau of Resources and Energy Economics (BREE), Tourism Research Australia (TRA), and the Department of Resources, Energy and Tourism (RET).

Authors: Fast forward? China’s future and the implications for Australia: Roger Rose and Kate Penney; China iron ore and steel: prospects for the industry and implications for Australia: Kate Penney; The energy consumption, emissions and income inequalities of Chinese urban households: Jane Golley; Study tourism from China: opportunities and implications for Australia: Byron Keating and Amy Godfrey Other contributors: A number of colleagues at BREE and TRA have contributed to the preparation of this report as well as the statistical tables including: Tom Shael, Oliver Hough and Clare Stark.

Acknowledgements: Special thanks to Quentin Grafton and Leo Jago for their valuable guidance and contributions.

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Cover image: Paul Gunning

Postal address: Bureau of Resources and Energy Economics GPO Box 1564 Canberra ACT 2601 Australia

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China Review • June 2013 iii

ForewordOver the past three decades China has undergone a remarkable transformation to become the world’s second largest economy. This growth was in large part driven by liberalisation of economic policy, demographic conditions and access to technology and trade opportunities.

Some of the factors that facilitated China’s rapid growth, including a low-cost labour pool and massive capital investments, are receding. As recognised by the Chinese leadership, to maintain its current economic growth the Chinese economy will, over time, need to transition into a greater level of consumption, undertake further market liberalisation and increase the role of the services sector. While the scale of the challenges facing the Chinese economy is large, they are achievable, especially given the announced commitments to policy change by the new Chinese leadership.

Australia has been a major beneficiary of China’s growth over the past decade. China’s investment in the Australian economy, particularly in the resources sector, increased substantially over this period and China is now Australia’s largest merchandise trading partner, accounting for around 30 per cent of Australia’s total exports in 2011–12. China has also become a key market for Australia’s tourism exports, and in 2012 it became the second largest inbound market for visitor arrivals and the largest market for total expenditure and visitor nights.

Looking forward, changes in the Chinese economy will present challenges for Australia’s major export industries, but will also create new market opportunities. Some sectors that have the potential to benefit from opportunities in China include: agriculture, mining and energy technology and services, financial services, education and tourism.

The Chinese education market has been growing rapidly and now accounts for around 28 per cent of Australia’s international education exports. This has flow-on effects for the tourism sector because 22 per cent of Chinese students have visitors from home during their stay in Australia—an average of five visitors per student.

In this, the second issue of Resources, Energy and Tourism China Review, BREE and TRA provide a detailed discussion on some of the opportunities and challenges facing the Chinese economy over the next two decades and an overview of the implications for Australia’s major export industries. This release also includes a review of the prospects for China’s iron and steel markets; a detailed analysis of the energy consumption, emissions and income inequalities of Chinese urban households; and the opportunities and challenges for Australia stemming from Chinese study tourism.

As in the 2012 release, BREE and TRA have updated the Review’s unique collection of statistical tables, figures and charts about China and how China relates to Australia and the rest of the world.

Quentin GraftonExecutive Director/Chief EconomistBureau of Resources and Energy EconomicsJune 2013

Leo JagoChief Economist/General ManagerTourism Research AustraliaJune 2013

iv China Review • June 2013

ContentsForeword iii

Acronyms and abbreviations v

OverviewFast forward? China’s future and the implications for Australia 1

Reviews 41China iron ore and steel: prospects for the industry and implications for Australia 42

The energy consumption, emissions and income inequalities of Chinese urban households 63

Study tourism from China: opportunities and implications for Australia 76

Statistical tables and figures 101Part I: Chinese trends: economic and social indicators 108

Part II: Chinese trends: resources and energy activities 121

Part III: Chinese trends: tourism activities 131

Part IV: Australian trade with China 133

China Review • June 2013 v

Acronyms and abbreviationsAAGR annual average growth rate

ABS Australian Bureau of Statistics

ADS scheme Approved Destination Status scheme

BOF basic oxygen furnace

BREE Bureau of Resources and Energy Economics

cm cubic metres

DFAT Department of Foreign Affairs and Trade

EAF electric arc furnace

ELICOS English language intensive courses for overseas students

FDI foreign direct investment

FOB free on board

FYP Five Year Plan

GDP gross domestic product

GFC global financial crisis

ICT information and communications technology

IEA International Energy Agency

ILO International Labour Organization

IMF International Monetary Fund

IO input-output

IVS International Visitor Survey

kg kilogram

kgce kilogram of coal equivalent

koe kilogram of oil equivalent

kWh kilowatt hour

LGFV local government funding vehicles

LNG liquefied natural gas

LPG liquefied petroleum gas

MJ megajoules

MEP Ministry of Environmental Protection

MPE marginal propensity to emit

vi China Review • June 2013

Mt million tonnes

NBS National Bureau of Statistics of China

NDRC National Development and Reform Commission

NTAF National Tourism Accreditation Framework (also known as T-QUAL Accreditation)

OECD Organisation for Economic Co-operation and Development

PISA OECD Programme for International Student Assessment

PPP purchasing-power parity

R&D research and development

RET Department of Resources, Energy and Tourism

RMB Renminbi

SASAC State Owned Assets Supervision and Administration Committee

SCE standard coal equivalent

SOE State-owned Enterprise

TEQSA Tertiary Education Quality Standards Agency

TFC Tourism Forecasting Committee

TITE total inbound tourism expenditure

Tn tonne

T-QUAL tourism quality assured

TRA Tourism Research Australia

TVE town and village enterprises

UN United Nations

UNCTAD United Nations Conference on Trade and Development

UNESCO United Nations Educational, Scientific and Cultural Organization

VET vocational education and training

VFR visiting friends and relatives

WTO World Trade Organization

China Review • June 2013 1

Overview: Fast forward? China’s future and the implications for AustraliaRoger Rose and Kate Penney*

Introduction Since the beginning of its market-oriented reforms in 1978, China has undergone an extraordinary economic transformation. In little more than 30 years, the Chinese economy has been transformed to become the world’s second largest economy. Real gross domestic product (GDP) per capita increased at an annual rate of about 9 per cent over those three decades. As a consequence of that growth, the proportion of China’s population living in poverty declined from 65 per cent to less than 10 per cent.

Since 1978, China’s economy has evolved from a centrally planned and predominantly agricultural base to a largely market driven industrial economy. Its economic transformation has been closely tied to ongoing changes in economic policy, supported by a unique set of demographic conditions and access to technology and trade opportunities on world markets.

The future prospects for growth in China’s economy in relation to: markets; regulations; demography and skills; and technology are reviewed in the following sections. These issues are evaluated using the World Bank’s 2012 study and its projections of the Chinese economy to 2030. The 2030 projections are explicitly linked to the development and implementation of a broad program of policy changes, which largely relate to markets and regulations, but also include policies designed to improve China’s environmental performance, including those to manage CO₂ and related greenhouse gas emissions. The overview concludes with the implications of future growth and structural change in China’s economy for Australia’s major export industries.

China’s economic transitionChina’s transition started with the replacement of communal responsibility for meeting production quotas with the ‘household responsibility’ system in agriculture in 1978. Under household responsibility, producers were paid government prices for meeting their quota, but could sell any surplus at market prices. The consequence was a dramatic increase in agricultural productivity. This dual price system was subsequently expanded to other industries.

* The views expressed in this review are those of the authors alone and are not necessarily those of the Bureau of Resources and Energy Economics nor the Department of Resources, Energy and Tourism. The authors are grateful for the insights and assistance of Quentin Grafton in the preparation of this overview.

2 China Review • June 2013

The combination of improved incentives for industrial enterprises, and the freeing up of rural labour as productivity improved in agriculture, provided an opportunity for profitable expansion of manufacturing industries. Much of the initial industrial expansion was carried out by town and village enterprises (TVEs). Although many of the larger enterprises were communally operated, the majority of TVEs were private. With the explicit recognition of property rights, beginning in 1994, enterprises with corporate ownership and structure have become more dominant than TVEs.

From 1980, Special Economic Zones in coastal provinces were developed, giving enterprises in the Zones preferential access to international markets. The Zones served as centres for export-oriented production and as hubs for importation and adaptation of technology. Progressive trade reform through the 1990s and accession to the World Trade Organization (WTO) in 2001 further opened China’s economy to world markets.

China’s export industries have capitalised on low-cost labour, based on rural migrants (workers surplus to agriculture needs), and technology transfer from more advanced economies. A high level of investment funded by domestic savings and increasing levels of foreign direct investment also provided a growing capital base. Consequently, China’s trade has expanded rapidly, with trade (exports plus imports) in recent years being equivalent to 50–70 per cent of GDP.

China’s growth has been supported by a demographic structure where a high proportion of the population is of working age. Trade and foreign investment have also provided China’s developing industries with access to ideas, technology and markets on a scale that would not previously have been possible prior to its economic reforms.

The initial adoption of the dual price system in agriculture and other industries provided the impetus for growth, which has since been facilitated by the gradual transition to a largely market-based economy. Throughout the reform process there has been an experimental approach to policy development. Devolution of budgetary responsibility and policy to a local provincial level has allowed local testing of ideas with lessened national risk. This approach has overall been successful, but not without its challenges.

China’s pathway to relative prosperity and modernity has included significant dips, with the pace of economic growth falling abruptly three times since the early 1980s. Reform paused in 1988–89 and China’s economic growth fell below 3 per cent per year, the lowest since 1978. Not until 1992 did the reform process resume. The Asian Financial Crisis in 1997–98 cut China’s GDP growth and export performance even with an expansionary government response. The Global Financial Crisis (GFC), which began in 2008, also had an impact on China’s economy. Nevertheless, real GDP growth remained above 7 per cent throughout the GFC. Neither the Asian Financial Crisis nor the GFC appreciably affected the progress of policy reform in China.

The current structure of China’s economy is one in which, for most goods, market prices provide signals to industry about what to produce, when and where. However, there are serious regulatory challenges in markets for productive factors such as labour, capital and energy. Aspects of the system of local and provincial responsibility mean that there are rigidities in markets and transaction costs between regions that detract from market efficiency.


There are also questions about the appropriateness of structures and incentives for state owned enterprises (SOEs), which dominate banking, telecommunications and most heavy industries.

Some analysts, such as Das and N’Diaye (2012), Garnaut (2010) and Huang and Wang (2010), suggest that China has reached a turning point, either in terms of a need to rebalance the economy, or an end to the opportunity to rely on low-cost labour, or both. Whatever the future may hold, there is limited prospect of an ongoing era of abundant cheap labour. Wage rates have increased rapidly and growth in labour availability will decline as China’s population ages—a consequence of a low birth rate over the past 30 years—and limits workforce expansion. Ultimately, what may matter most in terms of future economic growth is the relationship between growth in the labour force and wages, and growth in productivity.

Questions about rebalancing the Chinese economy fall into one of two broad categories. The first includes issues such as the need for greater emphasis on consumption as a proportion of GDP, an expansion of the service sector and the need to manage the external balance and exchange rate. The second includes factor markets—including the reduction of impediments to rural-urban worker migration, the provision of health and social security services and the removal of distortions in banking and other industry sectors dominated by SOEs.

Looking forward, some of the factors that facilitated China’s growth may remain, but others will not. The comparative advantage of very low wages has passed; China is now clearly a middle income country (Figure 1). Further, an abundant supply of cheap labour may soon be in the past, if it is not already. Future growth will depend on the ability of both government and industry to adapt. The central government appears keen to pursue further policy change, but faces major challenges.

Figure 1: Cross country income distribution, 2011

1

2

3

4

5

6

USD per capita (ln scale)

Low income Middle income High income

United States Japan

India

Australia

China

Source: World Bank 2013b.


Key opportunitiesChina has developed an extensive network of transport and communication infrastructure. In the four years from 2007 to 2011, the total length of railway in operation was extended by 20 per cent and the total length of freeway by 58 per cent (Table 1). Over the same period, the capacity of mobile telephone exchanges doubled. While significant gaps in transport and telecommunications infrastructure, particularly in China’s west and rural areas remain, China’s current infrastructure will provide the base for a more integrated economy.

Table 1: China’s ICT and transport infrastructure

2007 2011% increase 2007–2011

Mobile subscribers (per 10 000 people) 54 731 98 625 80.2

Capacity of Mobile Telephone Exchanges (per 10 000 people) 85 496 171 636 100.8

Internet users (per 10 000 people) 21 000 51 310 144.3

Length of rail in operation (10 000 km) 7.8 9.3 19.6

Length of highways in operation (10 000 km) 358.4 410.6 14.6

Length of freeways in operation (10 000 km) 5.4 8.5 57.6

Length of petroleum and gas pipelines in operation (10 000 km) 5.4 8.3 53.0

Source: National Bureau of Statistics China 2012.

China has a much more educated workforce than before its economic reforms began. For example, of people aged 25–29, the percentage who had completed secondary studies rose progressively from 9.8 in 1980, to 47.5 in 1990 and to 75.5 in 2011. The share of that age group that have completed tertiary studies was 0.5, 1.5 and 8.8 per cent for 1980, 1990 and 2011, respectively (derived from World Bank 2013a).

With a larger private sector, particularly in export-oriented manufacturing, China has a set of entrepreneurial skills that should prove invaluable in making the adaptations necessary to adapt to changing domestic and international market conditions. These skills, along with a more educated workforce, will also provide opportunities to increase the domestic technology content of China’s exports.


Table 2: Opportunities and challenges facing China’s economy

1970–2012 2012–2030 2012–2030

outcome no policy change with policy change

Infrastructure x ✔ ✔

Human capital

basic education ✔ ✔ ✔

higher education x ✔ ✔

access to education – x ✔

Economic structure

export orientation ✔ x ✔

consumption – x ✔

savings ✔ x ✔

exchange rate – x ✔

SOEs – x ✔

Financial sector

ownership – x ✔

interest rates – x ✔

markets – x ✔

Factor prices ✔ x ✔

Labour market

migration rules – x ✔

demographics ✔ x x

Inequality – x ✔

Productivity

resource reallocation ✔ x –

imported technology ✔ – –

domestic technology – ✔ ✔

Environment – x ✔

Key: ✔opportunity x challenge – neutral


Key challenges in the absence of policy changeRapid economic growth does not come without challenges (Table 2). A driving force for China’s growth has been the sequential, and to some extent experimental, dismantling of centralist policy in favour of allowing market development. There is no guarantee, however, that the economic structure resulting from such a process will be balanced. In particular, there are evident imbalances in the current structure of China’s economy—consumption is low and has declined as a proportion of GDP (Figure 2). China’s service sector is relatively small and undeveloped, and its economy is heavily export dependent. During times of sluggish world economic growth, high export dependence may contribute to a less resilient economy.

Figure 2: China’s contribution to GDP, by source

20 40 60 80 100

2006–2011 2001–2006 1996–2001

%

Consumption Investment Net exports

Source: CEIC 2012.

China’s very high savings rate—at around 50 per cent of GDP—has allowed its extremely high investment to be largely domestically funded. Over an extended period, investment has been strongly oriented toward infrastructure and the heavy industries which provide essential inputs to infrastructure spending. Large investment in the manufacturing sector has allowed it to use abundant low-cost labour. As a result, production of manufactured goods has underwritten China’s burgeoning exports. China’s strong GDP performance has been supported by this domestic investment and foreign demand. Thus, with slowing investment and external demand, China will require stronger domestic consumption to sustain growth.

While China’s high savings rate supported high economic growth in the past, it is now a key hurdle in the transition to a consumption-led economy. A high savings rate is, typically, seen to be unfavourable to balanced economic growth because it reduces the demand for goods and services. Several factors contribute to China’s relatively high savings rate. One is the policy structure that promotes a high level of precautionary saving by much of the population (Figure 3). The dominance of SOEs in some industry sectors and the policy environment in which those enterprises operate supports both high levels of profit and rates of corporate saving by some of those enterprises. Further, a combination of interest rate controls and limits on overseas investment by Chinese residents oblige individual savers to subsidise industry and government at the expense of potential consumption.

China’s social services system and social safety net have many gaps relative to developed economies. Until reforms of SOEs were undertaken in the 1990s, many employees were provided with health and other insurance by their employers. Relieving SOEs of employee welfare obligations contributed to improved enterprise profitability, but left employees with a stronger incentive for saving as they could no longer rely on welfare assistance from their employers.


Currently, both employees and employers are typically required to contribute to employee pension funds, at least for urban permanent residents, although there is limited portability of pensions. Rural migrant workers mostly do not have access to these arrangements, nor do they generally have employer-sponsored health. Education expenses, at all levels, are at least partly privately funded, adding to the precautionary saving incentive.

China has a high rate of corporate saving. A major part of that corporate saving is by SOEs. The same set of reforms that transferred the costs of health care and, initially, pensions to employees encouraged increased profitability in those enterprises. SOEs also have potential sources of profits beyond the level that would persist in a competitive environment. The IMF (2011) notes that, while SOEs are notionally owned by the Chinese people, they have no obligation to pay dividends. Thus, income that might otherwise have gone to households and, at least in part, expanded consumption has become part of corporate saving. Banking and finance regulation further adds to incentives to save.

Figure 3: Gross national saving as a percentage of GDP

10

20

30

40

50

60

2002 2003 2004 2005 2006 2007 2008 2009

%

government

corporate

household

Source: CEIC 2012.

Largely as a consequence of strong export performance and high savings rate, China has maintained a very high external balance for an extended period (Figure 4). Since the GFC, there has been some moderation in China’s external balance stemming from weaker foreign demand, declining terms of trade and strong domestic investment, although it still remains high.

Some concerns have been raised about the sustainability of China’s present economic structure. The high current account balance, along with what is perceived to be an undervaluation of the Renminbi, has been the cause of considerable tension with China’s


trading partners. The long term viability of the export-oriented manufacturing industry which supports that balance is under threat. To date, China’s competitiveness in export markets has depended on its abundant cheap labour, an advantage that is diminishing. Most of China’s manufacturing exports have relatively low endogenous technology content, while the high-technology industry is relatively less efficient and is also reliant on imported components (Zao and Yang 2012). Maintaining competitiveness with less abundant labour will require an upgrade in China’s technological input which, in turn, will require a more skilled workforce.

Figure 4: China’s current account balance

-100

100

200

300

400

500

1982 1986 1990 1994 1998 2002 2006 2010

$USb

surplus

de�cit

Source: World Bank 2013b.

Perhaps the greatest set of challenges that China faces over the next two decades is related to an inevitable shift in the age and regional structure of its workforce. These changes will have implications for labour market policy and for policies more broadly, particularly those in relation to education and other aspects of local government finance. Over the past 20 years, China’s growth has been bolstered by a particularly favourable population structure. A combination of factors, including the flow-on effects of China’s one child policy, gave rise to a population with a proportionally large working age component and low dependency (Figure 5). Between 1980 and 2011, the proportion of China’s population aged between 16 and 65 rose from 59 to 73 per cent (World Bank 2013b). While China’s total population grew by 37 per cent over that period, its working age population grew by 67 per cent and supported faster economic growth. Wei and Hao (2012) estimate that since the 1990s, China’s demographics contributed to one-sixth of its economic growth, facilitated by increased market competition.


Figure 5: Ratio of working age to non-working age in China

1.5

2

2.5

3

1950 1960 1970 1980 1990 2000 2010 2020 2030

Ratio

of w

orki

ng a

ge to

non

w

orki

ng a

ge

Source: UN 2011.

The surge in the working age population in China is almost over. During the next two decades, population growth will stall and possibly reverse. Under the high population growth scenarios considered by the UN (2011), China’s population will still be growing in 2030, but only just. Under the low population growth scenario, China’s population will start to shrink by 2020. Regardless of the outcome for its total population, the age structure of the population will change dramatically over the next two decades (Figure 6). The change will be in a direction that may be much less conducive to economic growth without changes in labour markets and other policies. This is because the working age proportion of the population will begin to decline and, eventually, the absolute number of people of working age will begin to fall within the next two decades.


Figure 6: China’s population structure, 2010 vs 2030

Male Female

80 60 40 20 0 20 40 60 80

0-4 5-9

10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85-89 90-94 95-99 100+

millions

2010 2010

2030 2030

Source: UN 2011.

The impending changes in the age structure of the population, along with other changes in the labour market, raise the question: when will China reach a Lewis turning point at which there is no longer any flow of surplus labour from agriculture to other sectors? Garnaut (2010) suggests that, by 2009, there was limited or no excess labour. The basis for that assessment is an observation that wage rates are rising across the board and that rural residents face rising opportunity costs of migration. He observes that most rural residents are already employed locally, so have less reason to move than in the past. Li et al. (2012) examine evidence that broadly supports Garnaut’s assessment. They observe that real wage rates are increasing in all regions and across all skill levels (Figure 7). Further, they point out that wages have risen much faster than labour productivity. They estimate that China’s economy will reach a Lewis turning point somewhere between 2020 and 2025.

By contrast, Meng (2012) argues that regional shortages of labour are a direct effect of the hukou system and that there is a potentially vast pool of low-cost labour. The combination of restrictions that migrants face means that they currently spend only a very limited time in cities—about seven years on average. Meng observes that 62 per cent of migrants surveyed in the Rural-Urban Migration in China and Indonesia Project say they would move to the city permanently if given the option. In essence, she argues that easing discriminatory access to urban jobs and resolving social security and education problems would expand the number of migrants and the length of time they spend in urban areas.


Regardless of actions taken to resolve migration issues, the impending changes in the age structure of China’s population will have serious effects on China’s comparative advantage and, therefore, on the possible pattern of economic development. Das and N’Diaye (2012) estimate that China’s labour surplus is currently around 169 million, but will decline to 30 million by 2020. They estimate that China’s economy will reach a Lewis turning point somewhere between 2020 and 2025. Changes to labour supply conditions, such as modification of the hukou system, are calculated to change the timing of the turning point, but only by a few years.

Figure 7: Migrant wage growth in China

-5

5

10

15

20

25

30

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

%

migrant real wage

productivity in secondary and tertiary sectors

Source: OCED 2013.

Although market-oriented reforms have been underway for decades, China is not a complete market economy and has substantial government participation through its SOEs. As well as being dominant players in China, a number of SOEs are becoming more significant globally. While SOEs are, typically, highly profitable they are, typically, less efficient compared with their private counterparts. It is unlikely that full reform of these enterprises will occur while the government pursues ‘socialism with Chinese characteristics’ which, to date, has given prominent role to state ownership, particularly in strategic industries. The favourable operating conditions afforded to SOEs through policy and regulation have contributed to the slow pace of reforms in some industry sectors, such as banking and finance. These sectors remain heavily constrained and the Chinese stock and bond markets are far from fully developed.

China also faces emerging issues in terms of the distribution of income and opportunities, and also the treatment of unpriced environmental amenities. Rapid growth has resulted in rising prosperity in urban areas, however, rural residents still have restricted and inferior access to education and welfare, particularly those with rural hukou living in urban areas. One of the consequences of China’s pursuit of economic growth has been a widespread deterioration in the condition of natural resources, including land, water and air quality. Addressing these challenges may create some growth opportunities in the future, but remedial environmental action will have a cost.


Policy challenges that may create growth opportunitiesHuang and Wang (2010) suggest that it is difficult to directly link any single policy challenge to a particular factor. Thus, successful policy action to maintain China’s growth rate is likely to involve a package of reforms. Some of the key changes to redress existing economic imbalances include:

• improved competition in SOE dominated industries;

• labour market reform;

• improved provision of social services and safety net;

• liberalisation of the finance market; and

• reduction of input subsidies.

Reforming the labour market and improving the social services and safety net is unlikely without substantial change in the system of allocation of responsibilities to, and funding, of subnational governments.

While the scale of China’s challenge to sustain economic growth over the next two decades is large, it is not insurmountable. Policy change to address these issues will create opportunities for the expansion of the Chinese economy (Table 2). China has faced and overcome major challenges in the past, and has generally exceeded expectations. In this sense, the challenges facing the Chinese economy over the next few decades are not dissimilar. However, this time the adjustment is required in the context of increased global pressures and China’s more important role in the global economy. Enacting the required restructuring to maintain domestic growth, while taking on increased responsibility for global stability and governance, will not be straightforward and there is likely to be dips and troughs in its growth pattern. In any event, the outcome in China will have far-reaching global implications (Spence 2011).

China’s Leadership Transition

A once-in-a-decade leadership transition in China was formalised during the National People’s Congress and China’s People’s Political Consultative Conference in March 2013. Chinese President, Xi Jinping, and Premier, Li Keqiang, lead the seven-member Politburo Standing Committee that effectively governs China.

The newly-installed government have announced three key priorities for the government during their term. These include: (1) maintaining economic growth; (2) improving the well-being and livelihood of its citizens; and (3) safeguarding social justice.

Maintaining economic growth is considered to be the government’s most important task. Premier Li has stated that China needs to facilitate economic restructuring and foster new sources of growth by leveraging off domestic demand and innovation potential so as to improve the quality and efficiency of its economy, create jobs and income, and improve environmental outcomes.


The task of improving well-being will focus on increasing urban and rural incomes, in particular those living in poverty as well as expanding the middle-class. Premier Li has emphasised that, to promote social justice, the Chinese government will need to create a solid social security net that supports compulsory education, medical care, social insurance and housing.

In May 2013, the National Development and Reform Commission released plans for its reform agenda during 2013 which includes: changes to the financial and taxation systems, the promotion of private sector investment, accelerating urbanisation, and reducing inequality.

Competition and distributions in SOEsFrom the beginning of the reform process in 1978, there has been a development and expansion of private enterprise in product markets. Nevertheless, despite decades of reform, SOEs continue to dominate many strategic industry sectors in China, including finance, telecommunications, infrastructure construction, energy and significant raw material industries. SOE dominance of those sectors is supported by favourable regulation, including government-imposed entry barriers.

The protection provided to strategically placed SOEs has allowed the perverse result that such enterprises are highly profitable, but of low operating efficiency (Geng et al. 2009). In this context, Szamosszegi and Kyle (2011, p.53) cite McKinsey and OECD estimates that productivity of privately owned enterprises in China is about twice that of SOEs. Hong and Nong (2013) estimate the rate of return on equity in 2009 at about 8 per cent for SOEs, compared with around 16 per cent for non-SOEs. The low returns for SOEs occur despite the considerable subsidies on land, finance and other inputs received by many of these enterprises. Integrated with price controls over key inputs, such as water and energy, the SOE arrangements have also served to deliver significant support to export-oriented manufacturing and other industries.

The accumulation of profits within SOEs has important implications for the overall structure of the Chinese economy. SOEs account for about half of all production. Thus, retention of their profits makes a significant contribution to the relatively low rate of consumption in the economy. Retention of profits by SOEs also contributes to high levels of investment in the economy as a whole. In particular, Lee et al. (2012) analyse China’s investment using an optimal investment, cross country model. They find that effective subsidies to large corporations, through financial regulation, results in overinvestment and a transfer from households to businesses equivalent to around 4 per cent of GDP.


State Owned Enterprises in China

State Owned Enterprises (SOEs) are corporations run by the central or local (provincial, municipal and county) government. Typically, they are classified according to the nature of their assets—productive state-owned assets, administrative public institutions, and resource assets and other equity assets—or how they are managed by the government—central SOEs, local SOEs and under the supervision and administration of the Ministry of Finance (Hong and Nong 2013).

In 1949, a large proportion of industrial enterprises in China became centrally controlled, with production, prices, wages and employment primarily determined by the government. Since the late 1970s, reforms have facilitated a transition towards private enterprises and partnerships where the government continues to hold a majority interest. Consequently, the number of SOEs in China has been steadily declining over the past decade. The 12th Five-Year Plan outlines objectives of creating ‘National Champions’ and strategic industries, while also ‘grasping the large and letting go the small’. This will ensure the continued existence of large and powerful SOEs, but the total number may decline as enterprises are merged, privatised or restructured.

In 2011, SOEs accounted for around 5 per cent of the number of industrial enterprises with revenue over 20 million Renminbi (National Bureau of Statistics China 2012). However, the role SOEs play in the Chinese economy becomes more apparent when the proportion of total output value (26 per cent of total), profit (15 per cent), total assets (42 per cent) and employment (20 per cent) are considered. Typically, the average assets of SOEs (17 million Renminbi) are much larger than non-SOE funded enterprises (1 million Renminbi). Chinese government statistics for SOEs do not include collective-owned enterprises or majority-owned SOEs, indicating the contribution of SOEs to the economy are likely to be understated.

SOEs can ensure the reliable provision of essential services; improve coordination between industry and government for implementing policies; and contribute to higher employment. However, SOEs face different market conditions compared with private enterprises, leading to a clear comparative advantage, including: cheaper and easier access to financing, improved access to grants and tax breaks, and advantages in procurement processes and selection. There are also barriers to entry imposed on strategic or priority industries.

SOEs often have conflicting objectives—they are required to reach production targets and generate profits, but they are also tasked with implementing policy, generating employment and providing other social welfare functions. Because these enterprises are not purely working to the objective of profit maximisation, their efficiency can be poor. Further, public service restrictions may prevent the recruitment of the best managers (Grafton and Squires 2002). It has been estimated that the productivity of privately owned enterprises in China is about twice that of SOEs (Szamosszegi and Kyle 2011).

Liberalising the financial sectorThe efficiency of China’s financial sector is constrained in a number of ways including: interest rate controls and supporting capital account controls; state ownership of banks; restrictions on foreign direct investment (FDI) in the banking sector; regulations and reserve requirements, and security markets.


China’s banking sector is dominated by state-owned banks. Johansson (2012) calculates that, in 2009, state controlled banks owned 73 per cent of total bank assets. State ownership helps ensure that a large proportion of lending is directed to SOEs in other sectors. Hong and Nong (2013) observe considerable staff exchange between state banks and client SOEs that would facilitate loans to SOEs. In practice, state-owned banks, at least in part, serve as instruments to implement government priorities. As a direct consequence of state-owned banking structure and practice, lending may not be directed to the most profitable uses, and credit availability to individuals and private businesses is constrained. Perkins and Rawski (2008) argue that banking sector efficiency would be improved by promoting entry and removing the non-profit factors from credit allocation.

Interest rates in China are controlled by the imposition of maximum deposit rates and minimum lending rates. China’s real interest rates over recent years have been low, sometimes negative. A primary effect of maintaining low real interest rates has been to subsidise SOEs, the main borrowers. Low interest rates have also had a direct benefit to government and an indirect effect of making it cheaper to maintain an undervalued currency. Conversely, it has imposed a major cost to households, who are the primary lenders. The resulting reduction in household income contributes to a rate of household consumption lower than in many other countries.

The combination of banking arrangements and credit rationing that favour SOEs means that private businesses are, by comparison, credit constrained. Limits on foreign direct investment in China further limit growth of private businesses. Thus for some private businesses, the only option is to fund future operations from savings. At best, such credit pressure raises the cost of funds to private businesses.

China’s stock and bond markets are far from fully developed. In particular, severe limits on foreign involvement in China’s stock market restrict development. Supervision is under-resourced and there is a perception there may be market manipulation (Johansson 2012). The absence of well-developed and efficient stock and bond markets reduces options and raises costs for private sector businesses.

Removing price distortions for key inputs While most of China’s product markets are competitive, there are significant policy induced distortions in a number of key input markets. In many cases, these distortions are closely tied to the favoured position of SOEs in input markets and their ties with state-owned banks.

Rural and suburban land in China is collectively owned, except for some state-owned parcels. While farmers generally have 30 year use rights, governments have exclusive right to appropriate rural land and designate it for conversion to urban or industrial uses. One consequence of this arrangement is that leases for industrial purposes may be made available to industry at little or no cost (IMF 2011). Service delivery through SOEs and associated price controls in the markets for oil, gas and electricity mean that there are large effective subsidies, particularly to major industrial consumers. Recent changes in electricity tariffs have lessened the size of the subsidy to some major users and oil pricing arrangements now more closely link the domestic price to the world price. Nevertheless, Huang and Wang (2010) estimate the


total value of input subsidies, including SOE gains from interest rate controls, at 10 per cent of GDP. Two key effects of price regulation are to bias investment towards strategic industries and support manufacturing exports while constraining growth in the service sector.

Energy price reform

As part of its efforts to move towards a more market-based economy and improve environmental performance, the Chinese government announced new pricing arrangements for diesel and gasoline in March 2013. Under the new system, the price adjustment cycle has been reduced from 22 working days to ten working days so that the domestic oil price more closely reflects international market prices. The four per cent trigger band for domestic price changes has been removed and the types of crude used in the adjustment calculations have been altered. If international price changes are less than 50 Yuan over the adjustment cycle, the domestic price will not be changed. Similarly, the timing and size of price increases may be changed in some circumstances, such as at times of high domestic inflation or dramatic changes in world oil prices.

The previous pricing system encouraged distributors and consumers to stockpile oil products during periods of high international prices so that they could sell for a profit after the government price adjustment. The new system may disadvantage Chinese consumers should international oil prices increase suddenly, but will benefit refiners who have struggled to remain profitable amid price controls and had little incentive to improve fuel quality because they could not pass on higher costs.

The government has announced that it will promote price reform in 2013. Analysts believe that reforms in pricing for coal, gas and electricity are likely to make progress this year. This is particularly important for the gas market if China is to meet its goals of increasing the share of gas in the energy mix.

There is a growing divergence in the price of domestically produced and imported gas. This gap is expected to expand in the future as China imports more gas, especially in the form of LNG. End-use prices also tend to be kept low to avoid inflationary pressure, restricting the ability to pass on rising gas prices to final consumers (IEA 2012a).

Gas prices in China are currently based on three elements—the cost of gas, the cost of transport and the end-use. The National Development and Reform Commission (NDRC) have been piloting pricing reform in the Guangdong and Guangxi regions. Under the new system, gas prices in these regions are 60 per cent linked to fuel oil prices and 40 per cent linked to liquefied petroleum gas (LPG) prices. While this pricing mechanism reflects the competitors to gas in the industry and household sectors, respectively, it does not account for the competition from coal (IEA 2012a).

Removing labour market distortionsChina’s labour market is distorted by its household registration system, and the ties between that system and provision of social services. Under the hukou system, Chinese citizens are registered at their place of birth for access to education, health and other social services. Around 70 per cent of China’s population has rural hukou. People with rural hukou can migrate to urban areas, and it is estimated that there are around 145 million such migrants (Meng 2012). What is not currently possible, in most circumstances, is for those migrants to take with them


their rights to access social services. Generally, migrants do not have cover for health or work accident insurance or pensions, nor can they access public education for their children in their places of urban residence. Further, the urban job market is highly discriminatory. Migrants of any skill level are far more likely than workers with urban hukou to be placed in low skilled, low paid, jobs (Meng 2012).

There is a strong interaction between the hukou constraints and the rights to use agricultural land. Rural land is communally owned and access rights are managed at the village level. A migrant who is absent from the village for too long, or at the wrong time, may risk loss of access rights in a reallocation (De La Rupelle et al. 2008). Given the insecurity of urban employment and lack of safety net for most migrants, maintaining access to land in the home village can be an essential insurance.

A direct impact of the hukou regulations and their interaction with the land tenure system is that migrants’ stays in cities tend to be short. Chan (2010) argues that the hukou system has facilitated cheap access to young labour (under 30s) by the export-oriented manufacturing industry. However, short stays may mean that either worker skills are not developed or, when they are, are not fully utilised. The system effectively deprives urban businesses access to a large group of older workers—Chan (2010) puts the number of unemployed or underemployed rural workers aged 35 plus at 100 million.

Of particular importance over the next two decades will be the difference in age structure between those parts of the population with rural hukou and those with urban hukou. Meng (2012) observes that greater fertility in the rural population since the mid-1980s, and the fact that 70 per cent of China’s population have rural hukou, means that the vast majority of new entrants to the workforce will be rural. Consequently, failure to resolve the hukou issues will severely restrict the size and availability of China’s workforce.

Reform of the hukou system would have cost implications both for subnational governments and for enterprises employing migrant workers. In most cases, urban employers of migrants do not contribute to their pensions, health or other insurance. Huang and Wang (2010) estimate that to cover those services at the level provided for employees of urban hukou would add a 30–40 per cent loading to current migrant wage costs.

The choice to recognise migrants as permanent residents, or not, is made at a township, city, or provincial, government level. Assigning urban hukou to migrants would add to costs borne by those governments for education, housing and medical services and possibly add to some general infrastructure costs. Where governments do offer urban hukou to migrants, access is often rationed on the basis of some mix of factors such as: length of residence; educational qualification, and social security contributions. Many migrants will not meet the qualifications—for example, when Guangdong Province adopted a points system for urban hukou in 2010, 20 million migrants then working in the province, but with rural hukou from other provinces, were excluded (Tam 2010).


Both the World Bank (2012) and OECD (2013) point out that effective provision of social services is possible if there is reform of subnational government funding arrangements. The potential size of the migrant population, and thus the costs of additional services, would add pressure for reform if meaningful changes were to be made to the hukou rules.

Addressing environmental issuesOne of the consequences of China’s pursuit of economic growth has been a widespread deterioration in the condition of natural resources, including land, water and air quality. In effect, over much of the reform period, natural resources such as clean air and the waste assimilation capacity of waterways have been priced at, or close to, zero and, consequently, overused. That overuse has downstream effects including higher costs for industries using polluted water and health costs from urban air pollution. The need to address this issue is recognised in China’s 12th Five-Year Plan (FYP), which contains extensive targets for improving environmental performance.

The World Bank (2012) suggests a program of ‘green’ development for the future. The Bank couches its policy in terms of improving the quality of economic growth. Nevertheless, a key part of the policy recommendation is aimed at reaping gains from improved technology for cleaner industry and products. There are possibilities for improvements in measured national income from some forms of pollution reduction. For example, in the case where an upstream industry cuts water pollution, the savings to downstream users who now have access to cleaner water may exceed the cost of mitigation.

There may be potential income gains from developing cleaner technology. However, moving to a cleaner industry and environment will generally involve significant measured costs, often with benefits which do not appear in formal measures of national income. Many of the benefits of better environmental conditions, such as clean air and water, either do not enter national account measures or do so only indirectly and with long lags. Some of the costs of mitigation, however, are immediately evident1. Thus, while policies to address China’s environmental issues may improve the quality of life they may not contribute to measured growth in GDP.

1 For example, in the case of a reduction in urban air pollution, the increased amenity value of clean air is not measured, but improved health may be reflected in higher future income (less sick days) and lower future medical costs.


Air quality in China—implications and policy responses

In mid-January 2013, the air pollution index PM2.5, which measures the density of particulate matter with a diameter of less than 2.5 micrometres per cubic metre, increased to more than 900 in Beijing. The World Health Organization standard is 25. China has the highest PM2.5 density in the world (Figure 8). According to the Ministry of Environmental Protection (MEP), more than 600 million people across China have been affected by poor air quality since mid-January 2013. Several studies have assessed the health implications of elevated air pollution, which include increased death rates, increased incidence of lung cancer, increased blood pressure and a reduction in life expectancy (Deutsche Bank 2013).

Figure 8: Average PM2.5, 2001–2006

Source: NASA 2010.

The MEP has announced a target of reducing the national average PM2.5 to 35 by 2030, from an estimated 75 in 2010. A number of policies have been enacted to address rising pollution levels, but most of them tend to be short-term or inconsistent with other policy objectives. For example, a reduction in emissions from motor vehicles would require a decline in car ownership and use. However, China’s urbanisation strategy promotes the development of smaller cities which tend to rely less on mass public transportation options such as subways (Deutsche Bank 2013). Even if fuel standards in vehicles improve, it is unlikely to offset increases in ownership rates expected in 2030. The biggest concern for policy makers is that policies to control air pollution may have negative implications for economic growth.

To be able to reduce air pollution to safe levels, the Chinese government will need to institute a number of policy reforms related to energy, transportation and the environment. Modelling undertaken by Deutsche Bank (2013) demonstrates that for China to reach its PM2.5 target of 35 in 2030 it will need to sharply reduce its coal use, slow private motor vehicle growth and promote public transportation and increase investment in clean energy—gas, nuclear, hydro, wind and solar.


Moving on upThe point at which there is no cheap surplus labour in China is a matter of much debate. Among other factors, the timing of that turning point will depend on the degree to which the labour market is reformed. Lesser, or slower, reform will mean that the point at which urban industry faces labour shortages will come sooner. Regardless of the precise timing, much of China’s economic growth has been driven by rapid productivity growth (Zhu 2012, Perkins and Rawski 2008) and much of that productivity growth has been derived from reallocation of resources, including abundant labour. With the abundance of labour falling, new sources of productivity growth will need to be found for the pace of economic growth to be maintained.

In the context of rising real wages and future labour supply constraints, it is worth considering the path of development of some of the other middle income countries. The transition to high income is difficult and the growth momentum of many countries has stalled. Those middle income countries that have made the transition have done so by advancing from dependence on manufacturing exports based on relatively low technology inputs and cheap labour. Moving to the next stage requires some combination of two factors: (1) a more technologically sophisticated industry sector and (2) greater domestic consumption. A more technologically advanced industry is achievable only with a highly skilled workforce. Higher levels of consumption are supported by: (1) a reasonably equal distribution of income; (2) the presence of a relatively large middle class, and (3) a low workforce dependency. China faces challenges on all of these fronts.

Kharas (2010) calculates that China’s middle class currently accounts for 12 per cent of the population. That compares with 53 and 48 per cent for the Republic of Korea and Japan, respectively, at the time that each reached a middle income level. Both the Republic of Korea and Japan have since grown to high income levels. Conversely, Brazil’s middle class accounted for only 29 per cent when it reached middle income level. It has so far failed to grow to a high income level.

Zhang et al. (2012) observe that no country with a Gini coefficient2 greater than 0.40 at the time it reached the middle income level has grown to a high income level. The National Bureau of Statistics estimated China’s Gini coefficient was 0.48 in 2012, although other estimates are as high as 0.61 (Yao and Wang 2013). These findings suggest that China faces a significant challenge in its quest to overcome inequality. Further, the impending rise in the aged dependency rate as the population ages will be another constraint on future economic growth.

Other challenges exist for China in its transition to a high income level. Eichengreen et al. (2013), for instance, find a negative association between exceptionally high investment levels and undervalued exchange rates in the progression to a high income level. Both of these are currently features of China’s economy. Similarly, poor enforcement of property rights over intellectual capital detracts from incentives for endogenous development of technology (Agénor et al. 2012).

2 The Gini coefficient is a commonly used measure of inequality. Its value ranges between 0, which indicates complete equality, and 1, complete inequality. Calculation of the index requires accurate GDP and income data.


Endogenous development of technology appears to be a necessary feature of progression beyond dependence on manufactures based on cheap labour and borrowed technology. Agénor et al. (2012) suggest that China’s investment in high-end communications infrastructure is consistent with development of an advanced and efficient economy. Further, China’s 12th FYP includes recognition of the importance of technology development, with targets for significant increases in research expenditure and patents. Chu et al. (2011) indicate that as the potential benefits to domestic innovators from protection of intellectual property have increased, China’s government has tightened that protection. They demonstrate a consistency between the evolution of China’s intellectual property rights to date and a national welfare maximising progression. Nevertheless, the World Bank (2012) argues that a good deal more needs to be done to fund, coordinate and make effective use of research.

An educated workforceA key to advancing to greater technology use and a higher income economy is effective education and training. Two aspects of education appear to influence a country’s likelihood of growing to a high income level: (1) the breadth of access to education across the population (Figure 9) and (2) the percentage of the population who graduate at upper secondary and tertiary levels (Figure 10).

Zhang et al. (2012) compare the case of the Republic of Korea and Japan, both of which had universal access to education when they reached the middle income level, with Mexico, where access to education was effectively restricted to a small high-income group. They note that Mexico has not grown to a high income level. Eichengreen et al. (2013) also find that increasing the share of the population with secondary or tertiary training reduces the chance that a country’s growth will stall and that ‘high quality’ human capital is most important. They note that, in education terms, China is slightly ahead of the modal value for countries that have stagnated at a middle income level.


Figure 9: Average years of education for the age group 25–29, selected countries

2

4

6

8

10

12

14

16

Korea, Rep. o

f

Japan

United St

ates

Malays

ia

German

y

Russian

Federat

ion

Mexico

China

South

Afric

a

Thail

and

Brazil

Turke

y India

years

2000

2010

Source: OCED 2013.

In terms of overall participation in education, China has made substantial advances, as is illustrated by Figure 10. Despite these major improvements China still faces a fundamental problem in achieving broad access to high quality education if its current economic structure and policy settings remain in place. The level of public funding, and the quality, of education in China varies greatly between rural and urban areas, and also between regions. A significant part of a child’s education is often provided by the parents. Given China’s currently skewed income distribution, there is a risk that a large proportion of children will have less than desirable prospects of achieving a high level of education.

Zhang et al. (2012) estimate that up to 50 per cent of new entrants to China’s workforce over the next 20 years will come from rural poor areas3. If the current education access and funding arrangements were to remain in place, a large proportion of China’s new workers would have education and skills well below the level needed in an economy with rising skill requirements. In this context, Golley and Kong (2012) find that, while 80 per cent of children in large city school districts attend high school, only 30 per cent of those in rural areas do. At the next level of education, 54 per cent of urban children attend tier 1 or 2 colleges, but only 9 per cent from rural areas do so.

3 Estimates are that 20 per cent of new entrants will come from the 500+ counties officially defined as poor or that 50 per cent of new entrants will come from rural counties in western China.


The World Bank (2009) observes that the difference in education level is the largest reason for the difference in incomes. The World Bank suggests that the importance of private funding in education means that there is currently a high probability of a skills trap. In other words, those at the bottom of the income scale unable to afford education for their children will have uneducated offspring.

Figure 10: China’s education progression rates

40

60

80

100

1991 1993 1995 1997 1999 2001 2003 2005 2007 2009 2011 %

Primary school enrolment

Progressing to junior secondary school

Progressing to senior secondary school

Progressing to higher education

Source: National Bureau of Statistics China 2012.

Both Zhang et al. (2012) and the World Bank (2009) observe that health problems seriously detract from the learning of children in low-income households. Consequently, both sources contend that programs to ensure access to affordable health care, as well as education, are essential to ensure that poverty traps do not persist. Given that rural people will dominate new entries to the work force for some time, resolving rural health and education challenges will be important to robust and balanced economic growth.

Rebalancing government responsibilities with revenue instrumentsChange is needed if China is to resolve problems associated with segmentation of the labour market through the hukou system, inequality of access to education and provision of health and other social services. Martinez-Vazquez and Qiao (2011) suggest that there is a mismatch of capabilities and responsibilities for local (county/township) governments. Services such as health, social security and education often require a greater capacity for ‘pooling’ than is possible at local levels of government.

Currently, there is a mismatch of funding capability and expenditure need. Man (2011) estimates that in 2008 subnational governments raised 47 per cent of China’s total government revenue, but were responsible for 79 per cent of total expenditure. The regional relativities


in revenue base are even more skewed, with total per capita tax revenue for the lowest tax province (Tibet) only 6.3 per cent of that for the highest tax province (Shanghai). Those problems will increase with responsibility for greater service delivery.

The reliance of subnational governments on land taxes, especially land development taxes, is an additional distortion (Figure 11). The World Bank (2012) argues that dependence on land development taxes has also led to an inefficient pattern of urbanisation. The Bank suggests that moving to a land value tax would lead to some improvements in efficiency and security of funding, but would entail a significant adjustment period. Further, the Bank argues that uncertainty about land titles discourages efficient decisions in both agriculture and urban development.

Figure 11: Gross revenue from sale of land-use rights as percentage of GDP and of national tax and social security revenues

5

10

15

20

25

30

2

4

6

8

10

12

1999 2001 2003 2005 2007 2009 2011

% %

GDP (LHS)

government revenue (RHS)

Source: OECD 2013.


Emerging debt pressures in the Chinese economy

While the Chinese economy responded better to the global financial crisis (GFC) than most other countries, there have been some growing imbalances that present a risk to China’s growth prospects. In particular, there are concerns that China’s rising debt may result in overinvestment in infrastructure or a financial crunch that might require the government to bailout the banking sector.

China’s debt has surged since the GFC and large sums of money have been allocated to investments that are unlikely to generate sufficient returns to cover the loans used to fund them (Chancellor and Monnelly 2013). Some analysts are worried that China may follow the path of other nations that experienced economic downturns following a large build-up of credit. Fitch Ratings have estimated that China’s non-financial debt to GDP was more than 190 per cent in 2012, around 60 percentage points higher than in 2007. This is larger than the credit booms witnessed in Japan in the late 1980s and the United States prior to the GFC (Chancellor and Monnelly 2013).

A large proportion of China’s debt came from government stimulus, which helped maintain economic growth over the course of the crisis through infrastructure spending. This stimulus quickly fed-through to the property market, supported by incomplete financial market reform—low and sometimes negative real deposit rates, volatility in the equity market, expectations of an appreciation of the Renminbi and capital controls—which encouraged savings to be directed to property (Wang and Sun 2013). This resulted in elevated property prices and increased investment in new housing. Some believe that there has been overinvestment in China’s housing market. For example, there have been reports of underpopulated cities with over resourced infrastructure, such as Ordos in Inner Mongolia province, Chenggong in Yunnan province and Zhengdong in Henan province, where large volumes of new residential units remain unoccupied as investors struggle to find tenants that can afford the rent.

Further contributing to the increased debt has been ‘shadow’ banking which includes non-bank institutional lending, such as trusts and bank credit that is kept off official balance sheets, such as loans to local government infrastructure projects, policy bank debt and borrowings by asset management companies (Chancellor and Monnelly 2013). Many believe that this ‘sector’ is poorly regulated and not transparent and is a growing risk to financial stability. Standard and Poor’s Ratings have estimated that outstanding debt in the shadow banking sector was around US$3.7 trillion, or around 44 per cent of GDP, at the end of 2012 (Standard and Poor’s 2013).

Although high levels of debt are not necessarily a problem, concerns have been raised about the rate of growth of net debt and credit arrangements that increase the possibility of bad debts. Real estate collateral and inputs to housing construction—including commodities such as steel—underwrites most of China’s outstanding debt. Given the weakness in property markets and commodity prices, there is increased potential for default. For example, land is commonly used as collateral by property developers and local governments, the latter through local government funding vehicles (LGFVs). Local governments rely heavily on land sales as a source of revenue. If there were to be a sharp decline in land sales and/or land and property prices, the effect would quickly spread to the financial sector as the ability of LGFVs and property developers to repay outstanding loans would be diminished (Chancellor and Monnelly 2013). Analysts at Nomura estimate that local governments hold about 14 per cent and property developers some 6 per cent of outstanding bank loans (Silk 2013).

A number of China’s largest banks are state-owned. Thus, if they come under pressure from bad debts, the government will likely need to bailout the banking sector. To reduce building financial pressures, the Chinese government is trying to ensure banks and other lending institutions reduce credit.


A broad economic outlook for growth in China World Bank view to 2030The 2030 outlook provides a comprehensive analysis of the prospects and challenges for the Chinese economy, pinpointing what is required to maintain its growth trajectory. The underlying message is that China has the potential to sustain economic growth with little global, environmental and social disturbance over the period to 2030, but only if fundamental policy and institutional reforms are implemented.

Assuming the required policy changes occur, GDP growth is projected to decline gradually from an average annual rate of 8.5 per cent during 2011 to 2015, to around 5 per cent a year between 2026 and 2030 (Table 3). Over this time, China’s economy is expected to become more complex, market-driven, knowledge-centred and services-oriented. Further, China is expected to become even more integrated into the global economy as it increases its participation in world trade and financial markets. Its own financial market is also expected to mature, establishing the foundation for the acceptance of the Renminbi as an international reserve currency.

Although there are considerable opportunities for continued economic expansion, there are many emerging challenges that will likely slow economic growth. The extent to which these factors have a major effect on China’s economic progress will depend on the policy changes made over the coming years. The major challenge will be to support growth while avoiding sudden slowing of growth or major crises. Some required reforms will be easy to implement over the short to medium term while others will require fundamental, structural change.

Table 3: World Bank projected growth assuming steady reforms and no major shock

1995–2010 2011–2015 2016–20 2021–25 2026–30

GDP growth (% per year) 9.9 8.6 7.0 5.9 5.0

Labour growth 0.9 0.3 –0.2 –0.2 –0.4

Labour productivity growth 8.9 8.3 7.1 6.2 5.5

Structure of the economy (end of period %)

Investment/GDP ratio 46.4 42.0 38.0 36.0 34.0

Consumption/GDP ratio 48.6 56.0 60.0 63.0 66.0

Industry/GDP ratio 46.9 43.8 41.0 38.0 34.6

Services/GDP ratio 43.0 47.6 51.6 56.1 61.1

Share of employment in agriculture 38.1 30.0 23.7 18.2 12.5

Share of employment in service 34.1 42.0 47.6 52.9 59.0

Source: World Bank 2012.


The World Bank has outlined six strategic priorities that need to be addressed if China is to achieve its goal of becoming a “modern, harmonious and creative society by 2030”. These include:

• Changing the role of the government and private sector, such as the reform and reorganisation of SOEs, developing the private sector, promoting competition and continued reform of factor markets;

• Encouraging innovation through an “open” system linked to global research and development (R&D) networks that provides an enabling environment (through fiscal, financial and regulatory measures) to foster innovation efforts rather than targeted attempts at developing specific technologies;

• Encouraging green growth that takes advantage of the opportunities provided by environmental pressures by tapping into global markets and green technologies;

• Promotion of equality and social protection for all through reforms that expand opportunities and social security for everyone such as equal access to employment, finance, and education;

• Building a sustainable financial system that is resilient to macroeconomic shocks, accommodating of changing public expenditure demands and is transparent and responsive to policy change; and

• Developing mutually beneficial relationships with the rest of the world through continued integration into the world economy and participation in multilateral institutions and frameworks.

Some of these policy directions have been included in the 12th FYP, which focuses on achieving higher quality, inclusive growth. Key targets in China’s 12th FYP are outlined in Table 4. The 12th FYP aims to transform the economic development model towards the expansion of domestic consumption. There is also high priority given to improving the wellbeing of Chinese citizens, developing high-end manufacturing and improving environmental performance.

Achieving the 2030 viewThe World Bank presents its 2030 economic growth forecasts as ‘…assuming steady reforms and no major shock’. Implicitly, then, achievement of those growth rates is dependent on the proposed package of policy changes being realised. Many elements of the package can be viewed as long term propositions either in the sense that they will take time to implement or that benefits will flow regardless of the timing of change. For some other reforms, the timing and sequence of policy changes may be critical, particularly in terms of labour markets.

The faster China transitions to policies that provide greater equality of access to education, the higher is the potential for continued strong economic growth. Nevertheless, the full benefits of improved education access will not be realised for decades. A child beginning primary school under a new education regime in 2014, for example, will not be expected to graduate from senior high school until 2025. While it is possible for policy changes to influence the attendance and performance of children already at school, the evolution of policy and changes in the education system will take time. Further, successful reforms of the labour market and education funding will only be possible with significant changes to the allocation of responsibilities and finances for subnational governments.


Table 4: Selected key targets in China’s 12th FYP

Category Target (by 2015)

Economic

Average GDP growth 7%

Service sector (as % of GDP) 47%

Urbanisation 51.50%

R&D (as % of GDP) 2.20%

Patents per 10 000 people 3.3

Population

Rate of nine-year compulsory educational attainment 93%

Rate of high school enrolment 87%

New urban jobs created 45 million

Urban per capita disposable income >26 810 RMB

Rural per capita disposable income >8 310 RMB

Urban population with basic retirement insurance 357 million

Resources and Environment

Reduction in energy intensity per unit of GDP 16%

Reduction in carbon emissions per unit of GDP 17%

Non-fossil fuel as a % of primary energy consumption 11.40%

Source: Casey and Koleski 2011.

Finally, a more efficient banking and financial sector could underpin investment and productivity improvements across other sectors. As well, a move to market-based interest rates would most likely expand household income and, thus, consumption. For both these changes, speedy reform is required.

Few, if any, of the changes necessary to ensure continued rapid growth will be easy to make. In particular, changing the competitive environment of the banking and finance sector and SOEs more widely will undermine key interests. Nevertheless, all the changes suggested above are promised in some way or another in the 12th FYP.


Economic measurement in China

The compilation of economic indicators is difficult. This is especially true for China, because of the size of the economy and the speed with which it is changing. Given the limited resources devoted to national accounts in China, there is the potential for large margins of error in official estimates compared with many other countries (Xu and Ye 2000).

There is strong interest in developments in China because of its importance to the global economy and commodity markets. Concerns have been raised about the accuracy and reliability of Chinese economic indicators given they are used extensively for analysis and decision making.

Statistical reform has been a priority of the Chinese government over the past 30 years, and much has been achieved. International cooperation and the uptake of harmonised methods will expand the capabilities of Chinese statisticians and improve the reliability of economic data over time. Increased availability of alternative data sources, such as the HSBC purchasing managers’ index, will also provide more information on changes in the Chinese economy (Koch-Weser 2013).

Implications for Australia’s export industriesThe effect of China’s economic expansion on the Australian economy to date is well documented. The rapid increase in demand for energy and mineral resources since the mid-2000s prompted a period of structural adjustment to the strong terms of trade; exchange rate appreciation; increased resource investment; reallocation of productive factors and strong employment growth in the resources sector (Grafton and Liu 2012). The relatively smooth adjustment to the resources boom over the past few years bodes well for the ability of the Australian economy to react to future changes (Plumb et al 2012).

The structural change driven by the resources boom is most evident in investment and exports. China’s resource-intensive growth contributed to historically high commodity prices, which supported the expansion of Australia’s resource output. Given the capital-intensive nature of resource production, the growth in productive capacity has resulted in a large-scale increase in resource-related investment. New mining-related capital investment as a proportion of total new capital investment has reached new highs, accounting for 52 per cent in 2011–12 compared with 21 per cent a decade ago (ABS 2012a, Figure 12). Over the same period, China’s investment in the Australian economy, particularly in the resources sector, increased dramatically although it still remains a relatively small overall investor in Australia (ABS 2012b).


Figure 12: Australian mining investment expenditure by private enterprises

15

30

45

60

75

20

40

60

80

100

1987–88 1990–91 1993–94 1996–97 1999–00 2002–03 2005–06 2008–09 2011–12 %

2011–12 $b

new mining investment

share of total investment

Source: ABS 2012a.

There has also been a clear transition in the composition and direction of Australia’s trade, with the resources and energy sectors increasing the share of export earnings to 60 per cent in 2011–12 from 49 per cent a decade earlier (ABS 2012c, Figure 13). China is now Australia’s largest merchandise trading partner and resources trade has been reoriented to China. China accounted for 29 per cent of Australia’s total exports in 2011–12. The main exports were iron ore, coal, gold and crude oil. Australia sources 18 per cent of its total imports from China, mainly purchasing electronics and clothing. Australia is less important as a trading partner to China, accounting for only 4.7 per cent of their total imports (ranked fifth) and 1.8 per cent of outbound trade (ranked eleventh) (DFAT 2012).

Figure 13: Resources and energy share of total export earnings, Australia

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20

30

40

50

60

70

1975–76 1981–82 1987–88 1993–94 1999–00 2005–06 2011–12

%

Source: ABS 2012c.


The resource intensity of China’s future growth, particularly given plans to move to a consumption-led economic growth model, is uncertain. However, there are a number of factors that will support strong demand for commodities over the short to medium term. While the pace of growth may begin to decline, the scale of China’s growing demand still represents large volumes in absolute terms.

China’s urbanisation and rising household income have increased investment in new, higher quality housing. Residential construction has been a key contributor to strong demand growth over the past decade, particularly for steel, and is expected to remain important over the medium term (Figure 14). Construction activity is expected to wane over the longer term as the rate of urbanisation slows and the building stock improves, requiring fewer rebuilds. Infrastructure development, such as rail and electricity networks, will also contribute to commodity demand over the short to medium term. Further, the central and western regions are still largely undeveloped in terms of infrastructure and are targeted for expansion by the government.

Rising income has increased the demand for consumer durables, which are resource intensive in both production and use. The extent to which China demands materials for the production of these goods depends on the structure of its manufacturing sector. As China loses its competitive advantage in cheap labour, low-technology manufacturing based on scale economies will likely be shifted offshore, thereby changing the resource intensity and demand composition of its manufacturing sector.

Between 2014 and 2018, China’s steel consumption is projected to grow at an average rate of 3 per cent a year to total 822 million tonnes in 2018. China is expected to remain the main driver of consumption growth in base metals over the short to medium term. China’s aluminium consumption is projected to increase at an average annual rate of 8 per cent between 2013 and 2018, zinc by 8 per cent, copper by 7 per cent, and nickel by 3 per cent (BREE 2013).

Figure 14: Projected increase in built area from 2010 to 2020

40

80

120

160

200

City districts, 2010

Other urban, 2010

Needed for increased urban

population

Needed for more living space

billionunits

maximum allowable built area

Source: OCED 2013.


The composition of China’s energy consumption is expected to change considerably over the course of the next two decades, with the government focusing on energy conservation and the utilisation of clean energy sources. The 12th Five Year Plan on Energy Development, released in January 2013, outlines the major targets for energy development. Energy conservation is a major component of the plan with China’s energy consumption to be capped at 4 billion tonnes of coal equivalent and power use at 6.15 trillion kilowatt hours in 2015. Energy use per unit of GDP in 2015 is targeted to be reduced by 16 per cent compared with 2010; a broader energy efficiency improvement of 38 per cent has also been announced. In terms of energy security, the government plans to keep oil imports to no more than 61 per cent of total demand.

Greater utilisation of non-fossil energy is also expected over the period, with the share of non-fossil energy in primary energy consumption targeted to increase to 11.4 per cent. Natural gas is expected to account for 7.5 per cent of primary energy consumption by 2015. In order to achieve this goal, China will look to fast-track the development of its coal seam gas and shale gas resources over the next few years. The installed generating capacity of nuclear power is expected to reach 40 gigawatts electric by 2015.

Further reinforcing the clean energy targets in the energy development plan, China has announced its intentions to introduce a carbon tax. The government is also assessing the possibility of taxing energy-intensive products such as batteries. In 2010, the Ministry of Finance suggested implementing a price starting at 10 Yuan a tonne of carbon dioxide equivalent (around US$1.60) in 2012, increasing to 50 Yuan (around US$8) by 2020. Regional pilot programs are being developed and implemented. These are expected to transition to a national scheme in the future.

China is the world’s largest consumer of coal and it is the dominant source of energy, accounting for around 66 per cent of primary energy use in 2010. According to the IEA’s most recent medium term forecast (IEA 2012b), its coal consumption is projected to grow by 25 per cent over the period to 2017. This will be largely driven by the power sector, where consumption is expected to expand by one-third. Non-power demand (steel, coke, chemicals, cement and household use) is expected to ease over the same period as more modern energy sources are increasingly utilised and cement production slows (Cronshaw 2013). Given the efforts to reduce reliance on fossil fuels, China’s total coal demand can be expected to moderate over the longer term.

China’s energy consumption will be affected by developments in the transportation and industry sectors. For example, its energy profile is likely to be more oil-intensive if the transport sector develops to be more road-based than if it were based on mass public transportation systems like rail.

According to the IEA’s World Energy Outlook, China’s share of coal in the primary energy mix under the new policies scenario is projected to decline from 66 per cent in 2010 to 51 per cent in 2035 (Figure 15), representing the slowest growth among the fossil fuels. The strongest growth is expected to occur in the nuclear sector, albeit from a small base. The share of nuclear in primary energy consumption is projected to increase from 1 per cent in 2010 to 7 per cent in 2035. Gas use is projected to increase at an average rate of 7 per cent over the same period, to account for 12 per cent of total primary consumption in 2035 (IEA 2012c).


Figure 15: China’s primary energy consumption mix

10

20

30

40

50

60

70

Coal Oil Gas Nuclear Hydro Bioenergy Other Renewables

%

2010

2035

Source: IEA 2012c.

Australia’s role in meeting China’s resource demand will depend on (1) the volume and composition of China’s demand, (2) China’s ability to meet its own demand and (3) the ability of other countries to meet this demand.

China has vast reserves of minerals, but they can sometimes be insufficient to meet domestic requirements or, like the case of coal, be located far from regions where they are required. China aims to be as self-sufficient as possible in the production of resources, and some industries have been investing in overseas assets, including Australia, to ensure supply security.

Australian producers are not, typically, marginal producers, so will continue to supply commodities to the Chinese market despite an expected decline in commodity prices (Findlay 2011, BREE 2013). However, there will be increasing competition from abroad to provide resources to China. For example, the United States has the potential to rapidly expand liquefied natural gas (LNG) export capabilities based on its vast resources of shale gas. Australia’s ability to compete will continue to rely on the provision of a stable investment environment, control of capital and operating costs and improvements in productivity. The mining equipment, technology and services sector will play a key role in addressing these challenges, ensuring that Australian companies remain low-cost, efficient producers that capture a large proportion of global mining investment (Scott-Kemmis 2013).


Deal to trade Australian Dollar and Chinese Yuan

In April 2013, Australian-based banks Westpac and ANZ were granted the right to directly trade Australian dollars for Chinese Yuan in mainland China—i.e. granted ‘market maker’ status. The deal highlights the growing relationship between Australia and China, particularly trade ties that have increased the demand to directly convert the currencies. The Australian dollar is only the third major currency granted this right, after the US dollar and Japanese Yen.

While China introduced a Yuan-Australian dollar exchange rate in November 2011, trading has been conducted indirectly through the US dollar because of an absence of ‘market makers’. It is expected that the deal will make it easier, and cost less, to conduct business between the two countries as the need to convert to US dollars will be bypassed. The first trades occurred shortly after the deal was made.

The Chinese government is encouraging companies to invoice in Yuan rather than US dollars. However, according to The Executive Director of the Australian Financial Centre Task Force Geoff Weir, the shift to Yuan invoicing has been slow, particularly in the commodities sector where products are priced in US dollars. He believes that Australian companies have little incentive to accept payments in Yuan because they have limited exposure to liabilities denominated in Yuan (Winestock 2013).

The benefits accruing to Australia from China’s development over the medium to longer term are not guaranteed and will depend on China’s economic structure and progress as well as Australia’s ability to make the most of market opportunities. Despite strong economic growth in China since the 1980s, Australia has only realised benefits from that growth since the mid-2000s as commodity prices increased. There are varying views on whether China’s economic growth can be sustained, and the resource intensity of that growth. However, as economic growth and urbanisation slows, it is likely that the growth in demand for the current set of products Australia has a competitive advantage in supplying, such as iron ore and coal, will decline and the absolute demand for commodities may even peak and possibly decline by the 2030s.

If Australia is to continue to benefit from China’s economic expansion, it will need to seek new opportunities and develop the required capabilities, skills and experience today. These opportunities include developing a sound understanding of China’s culture, business practices, institutions and regulations; ongoing reforms to ensure open market access and broadening Australia’s social and economic relationship with China. Some sectors that have the potential to benefit from opportunities in China outside the resources and energy sectors include:

• Agriculture: As China’s population and incomes grow, more and different food products will be consumed. China does not have the capacity to be food self-sufficient, so will rely on imports to meet demand. Australia has a strong reputation in producing high-quality, safe grains for human consumption and meat products and would be well-placed to meet these needs. There are also opportunities in R&D and agribusiness that would allow Chinese producers to improve yields and manage water use and environmental impacts.

• Mining and energy technology and services: With planned expansions to China’s resources and energy output, along with the need for increasingly sophisticated extraction and processing techniques, there is the potential for increased collaboration and exports of mining and energy technology and services.


• Niche manufacturing: While some manufacturing industries will struggle to remain competitive, others will be able to capitalise on new market prospects or parts of the supply chain where Australia has an advantage. For example, there is the potential for exports of mining-related machinery, green energy technologies and pharmaceuticals.

• Financial services: As China becomes an increasingly large exporter of capital and reforms of its financial sector are undertaken, there are opportunities for Australian institutions to share its know-how in developing management skills, risk management, internal controls and technologies. Further, as China’s population ages, Australia’s experience in funds management and superannuation should be higher (KPMG 2012).

• Education: Rising incomes will contribute to an increase in the demand for more and better education services. While China is likely to invest heavily in improving the quality and accessibility of its education sector, it is doubtful that it will be able to fully meet this demand. Australia already has a good reputation in the international education market and there is the chance to expand service delivery in this sector, especially in terms of post-graduate education (see the article on education tourism in this volume).

• Health and aged care: As the Chinese population ages and disease patterns change, there is the potential for collaboration between research institutions and health systems for R&D and training purposes (KPMG 2012).

• Natural resource management: As the pressure on land, air and water resources places strains on the economy, there are opportunities for partnerships and collaboration on learning from Australia’s experience and “leapfrogging” developed economies on the path to sustainable growth (KPMG 2012).

• Tourism: With increasing disposable incomes, more Chinese people will be able to afford to travel. Tourism is already one of Australia’s largest export industries and there will be further opportunities to increase inbound tourism.

• Urban design and architectural services: With the process of urbanisation expected to continue into the foreseeable future, there are opportunities for urban planners and architects in the process of improving urban design and buildings.

Concluding remarksChina will soon have a lower proportion of its population of working age, a much higher dependency rate, and higher wages. The era of abundant cheap labour in China will soon be over. Beyond the next few years, maintaining a high growth rate will be possible only if productivity rises rapidly.

Productivity improvements from reallocation of resources are possible, with the greatest potential lying in improvements in competition in banking, finance, infrastructure, and heavy industry sectors dominated by SOEs. An increasing part of the productivity change will need to come in the form of endogenous development of technology, in combination with the skills of a more educated workforce. Despite the huge improvement in its level of education over the past three decades, China faces a significant challenge to ensure that future new entrants to its workforce are appropriately educated for a higher technology industrial structure.

The size of China’s market presents growth opportunities for Australia, especially in terms of energy exports. Nevertheless, a transition to a more consumer and service oriented economy


is likely to make China’s export demand less resource intensive over time. This suggests that the type of growth opportunities available in Australia will change as China’s economy moves to a lower proportional share of investment, higher consumption and a greater importance of the services sector.

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China ReviewReviews


China iron ore and steel: prospects for the industry and implications for AustraliaKate Penney*

IntroductionChina’s demand for raw materials since the late twentieth century has been underpinned by rapid economic and population growth; industrialisation; and urbanisation. Its output of iron ore and steel has been insufficient to meet its rapidly expanding requirements, even though it is a major producer of iron ore. As a result, China has relied heavily on iron ore imports to support its rapid growth in steel production.

China’s size and increasing integration into the world economy suggest that its consumption and production of steel will change over time and these will have global implications. Australia, as a large producer of raw materials, will be affected by China’s economic restructuring, especially in terms of resources and energy.

China’s iron ore and steel industriesIron oreChina is the world’s third largest producer of iron ore, accounting for around 17 per cent of iron ore output (in natural weight terms) in 2012 (Figure 1). Over the past decade, China’s iron ore production increased at an average annual rate of 11 per cent, driven by high prices that allowed some high-cost mines to operate. Chinese production was also supported by a recent substantial decline in Indian exports to China (OECD 2012). While China is a large producer in absolute terms, its iron ore reserves have a relatively low iron content compared with other major iron ore exporters. The implication for Chinese steel production is that low-grade iron ore requires additional processing which increases the cost of production, making imported iron ore relatively more attractive.

* The views expressed in this review are those of the author alone and are not necessarily those of the Bureau of Resources and Energy Economics nor the Department of Resources, Energy and Tourism. The author is grateful for the comments on this review provided by Tom Shael.


Figure 1: World iron ore production, by countrya, 1985–2012

500

1000

1500

2000

1985 1988

1991 1994

1997 2000

2003 2006

2009 2012

Mt

Australia Brazil China India Russia World

a China’s production has been converted to correspond with world average iron content.

Source: BREE 2013a.

China’s iron ore industry consists of many mines of various scales, with small and medium mines accounting for the bulk of production. These are geographically dispersed across the country but nearly 80 per cent of production is sourced from only five provinces—Hebei, Liaoning, Sichuan, Inner Mongolia and Shanxi (Map 1).


Map 1: Geographic location of China’s iron ore and steel production

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Most of China’s iron ore mines are run by state-owned enterprises, often the major steel companies, along with a few collectives and private companies. Collectives and privately-owned companies account for a large, but declining, share of production. Most of the state-owned firms operate under the framework established by the State Owned Assets Supervision and Administration Commission of the State Council (SASAC). The SASAC has emphasised consolidation of the industry, increased international competitiveness, improved technical efficiency and the need to respond to environmental concerns stemming from their activities as key priorities (OECD 2012).

China relies heavily on imports from Australia and Brazil. China overtook Japan as the world’s largest iron ore importer in 2003 and now accounts for more than 65 per cent of world imports. Unlike other major producers, China’s iron ore production is exclusively for domestic use.

SteelThe expansion in global steel production capacity over the past decade was driven by China, where crude steel capacity grew at an average annual rate of 20 per cent between 2001 and 2011. China is the world’s largest steel producer, accounting for around 47 per cent of world output in 2012 (Figure 2). Overcapacity is a key concern in China, with steel production estimated to have exceeded apparent consumption by around 31 per cent over the past decade (Ernst and Young 2013). China’s crude steel production is dispersed around the country, with the bulk of production co-located with iron ore mines in the north-east (Map 1).

Figure 2: World crude steel production, by region, 2001–2012

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Middle East South America

Africa

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Source: Bloomberg 2013.


Crude steel is transformed into finished end-products for final use, such as in automobiles and household appliances. Chinese production of finished products traditionally focused on ‘long’ products—bars, wires, tubes and sections—which are largely used in non-residential construction. More recently, there has been an expansion of high value, ‘flat’ products—steel sheets and strips—that are used in manufacturing (Holloway et al 2010). China’s finished steel production has increased at an annual average rate of 17 per cent since 2003, in line with rising steel demand and crude steel output.

China is the world’s largest consumer of finished steel products, accounting for almost half of world consumption in 2011 (Bloomberg 2013). China’s finished steel demand has increased at an average annual rate of 15 per cent since 2001, supported by strong construction activity and manufacturing for export. Finished steel is mainly used in construction (66 per cent), followed by machinery (21 per cent) and automobiles (6 per cent). Around 2 per cent of China’s finished steel is used in the production of household appliances. Within this category, steel is mostly used in refrigerators, washing machines and air conditioners (Figure 3).

Figure 3: China finished steel consumption, by end-use, 2011

Automobiles 6%

Shipbuilding 3%Machinery 21%

Rail 2%

Construction 66%Refrigerators 31%

Washing Machines 20%

Air conditioners 17%

Electric cookers 11% Electric ovens 9% Other 12%

Appliances 2%


Despite being a large steel producer and exporter, China still needs to import steel, particularly some of the higher quality, technology-intensive flat products such as steel strips and sheets.


China’s steel industry comprises of a few large, advanced producers and many small and medium sized producers making lower-value products. In 2011, there were 292 steel-making entities, with the ten largest producers accounting for around 50 per cent of production (CEIC 2012; Bloomberg 2013). The large producers tend to be state-owned companies, while most small producers are privately owned.

Sector outlookOver the coming decades, the evolution of the iron ore and steel sectors will depend on changes in commodity markets and government policies.

Drivers of consumption growthShort term

Over the short to medium term, support for growth in steel consumption in China will continue, but it will be increasingly influenced by Chinese economic policy. While consumption growth is expected to slow in conjunction with moderating economic growth, steel will remain a key input to achieve some of the measures announced under the 12th Five-Year Plan (FYP), particularly housing construction and high-end equipment manufacturing.

Construction is by far the largest component of China’s finished steel consumption (Figure 3). Steel is used throughout the entire construction process—with the most intense use in the foundation and core of the building. Accordingly, developments in this sector will have a large influence on China’s steel consumption.

In the 12th FYP, the Chinese Government has committed to the construction and renovation of 36 million apartments for low-income families in urban areas. Residential construction will also be supported by urban regeneration. Many urban residences are low-quality, old buildings which will be demolished and rebuilt (Credit Suisse 2012a). New housing is likely to be taller and consequently will be more steel intensive than the existing housing stock. As the height of a building increases, so too does its steel intensity. For example, a building with 16 to 35 floors uses around one-third more steel per square metre than a building with seven to 15 floors. Similarly, buildings with more than 35 floors are generally twice as steel intensive than buildings with seven to 15 floors (Credit Suisse 2012a). This trend of urban regeneration is expected to continue over the medium to long-term.

Additional steel consumption growth will come from the planned expansion of hard infrastructure (such as ports and rail), ship building, machinery and clean energy technologies (nuclear power plants, wind farms, hydropower developments and fuel efficient automobiles). For example, there are plans to develop new urban rail systems in 20 cities, expand the high-speed rail network; and construct 83 000 kilometres of new highway, 150 000 kilometres of oil and gas pipelines and eight new airports (Ernst and Young 2013). Many of these products will rely on specialty steel such as electrical (silicon) and stainless steels (KPMG 2011).


Medium to Longer term

The economic fundamentals that have contributed to the strong growth in China’s steel consumption will remain important drivers for growth over the medium to longer term. However, the relative importance of these traditional drivers is expected to diminish over the medium to long term.

Steel intensity

The steel intensity (or consumption per person) of the Chinese economy has increased rapidly over the past decade, consistent with its economic growth (Figure 4). China’s steel intensity already exceeds that of the United States and is similar to Japan’s steel intensity. There is the potential for China’s steel intensity to continue to increase as the economy develops.

Figure 4: Steel intensity of use in selected countries, 1980–2011

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Sources: World Steel Association (various years), IMF 2012.

It is unlikely that China will follow the very heavy steel-intensive development of the Republic of Korea and Chinese Taipei. The high consumption of steel per person in these countries is driven by a high export orientation and a comparative advantage in the production of capital-intensive goods. By contrast, China’s export orientation has been declining, a trend that is likely to continue given the focus on rebalancing the economy and expanding domestic consumption. Further, China’s current large infrastructure investment may reduce future investment which would contribute to reducing the steel intensity of the economy over time (Garnaut 2012).


McKay (2008) argues that China’s path will be unique, but it does exhibit some of the characteristics of the Japanese and United States’ experience. In particular, the large land mass of the United States and the rapid growth in world export share in Japan.

It is expected that China’s steel growth path will lie somewhere between the Republic of Korea and other industrialised countries. If Japan and the United States are used as benchmarks, per capita steel consumption peaked at around 800 kilograms and 600 kilograms, respectively for these two countries before declining. China’s per capita steel consumption is currently around 500 kilograms. Regardless, China’s future steel intensity, with its large population, even small increases in per person consumption will translate into large absolute increases in total steel use.

Economic growth and the expanding middle-class

Over the past three decades, China’s gross domestic product (GDP) growth has been underpinned by investment, which accounts for around 50 per cent of its GDP. After decades of growth driven by investment and trade, the Chinese government plans a transition to ‘sustainable’ economic growth that is underpinned by domestic consumption.

China’s economic growth is expected to slow, but remain robust over the medium to longer term. The World Bank (2012) projects economic growth to average 8.6 per cent a year between 2011 and 2015, before slowing to 7 per cent a year over the period 2016–20, 5.9 per cent in 2021–25 and 5 per cent in 2026–30, conditional on a series of reforms being implemented (discussed in the Overview).

The expectation of consumption-led economic growth should contribute to a strong increase in household consumption, particularly in urban areas. This will be further reinforced by China’s expanding middle class. Over the coming years, a large proportion of Chinese households will be in the middle income bracket and above. The IMF (2012) projects China’s per person GDP (in international purchasing power parity (PPP) terms) to be around $14 600 in 2017, equivalent to around one-quarter of the United States. Rising incomes are likely to contribute to greater spending on discretionary items such as transportation, communications, and household products. This has implications for steel consumption because some household appliances can contain up to 55 kilograms of steel (Figure 5). The extent to which China will consume steel in the production of these goods will depend on developments in its manufacturing sector.


Figure 5: Steel use in household appliances

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Electric Fan

Microwave Oven

Range Hood

Gas Water Heater

Gas Cooker

Electric Cooker

Electric Oven

Air Conditioner

Freezer

Washing Machine

Refrigerator

kg/unit


Over time, there is likely to be a gradual shift in the drivers of finished steel consumption, away from steel-intensive construction, towards consumer durables such as automobiles and household appliances. Nonetheless, the construction sector will remain an important component of China’s steel demand over the medium term.

Urbanisation

Residential construction is estimated to account for around 60 per cent of construction steel use (Berkelmans and Wang 2012). Accordingly, expectations for residential construction activity will be a key indicator of China’s future steel consumption.

China’s economic growth and the difference in wages between rural and urban areas have encouraged the transfer of labour into cities. The size of China’s urban population increased at an average annual rate of around 4 per cent between 1970 and 2010. This supported large-scale investment to build new housing, commercial facilities and infrastructure. The pace of urbanisation in China is projected to slow over the next 40 years, increasing by 1 per cent a year between 2010 and 2050. Nevertheless, almost 80 per cent of the Chinese population is expected to live in urban areas in 2050, up from 51 per cent in 2011 (Figure 6, UN 2011). While further residential construction is required to accommodate the expanding urban population, the pace of activity is likely to slow over the longer term as urban population growth slows and building quality improves such that it requires fewer and less frequent rebuilds.

Berkelmans and Wang (2012) project China’s urban residential construction activity to peak in 2017, before declining to below 2012 levels by 2030. A large proportion of the growth in steel use in residential construction is likely to stem from the increased steel intensity of buildings rather than increased floor space under construction (Credit Suisse 2012b). The use of steel in residential construction is projected to peak in 2023 at around 116 million tonnes, approximately 30 per cent higher than in 2011 (Berkelmans and Wang 2012).


Steel use in the construction of commercial buildings is expected to remain robust over the longer to medium term, supported by the expansion of the industrial and service sectors. Commercial buildings tend to be more steel intensive than residential buildings. While there has been extensive infrastructure development in larger cities, such as Beijing and Shanghai, the development of the western and central regions of China will require further infrastructure construction (Trench 2004).

Figure 6: Urbanisation in China

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Source: UN 2011.

Transportation sector

Vehicle ownership is expected to increase in line with rising household incomes. While China is one of the largest motor vehicle markets in the world, per person ownership is still low by world standards. The ownership of passenger vehicles in China is projected to increase from 40 per 1000 people in 2010 to 310 per 1000 people in 2035 (IEA 2012). Traffic congestion, regulation and high costs of ownership (such as registration) are likely to limit the rate of growth in vehicle ownership. As such, it is unlikely that car ownership and use will reach the average of OECD countries.


China’s land mass is more comparable to the United States than Japan or the Republic of Korea. Consequently, China will require a large transportation system to enable passenger and freight movement between cities. By contrast to the United States, China has a much higher population density and transportation systems will be more likely to be based on mass public transportation rather than automobiles (McKay 2008).

The Chinese Government has announced a number of measures to ensure that public transportation, such as buses, is developed as a priority, with the aim that public forms of road transport will account for 60 per cent of total automobile use. Between 2011 and 2015, public transportation will be exempt from consumption tax, receive favourable rates for vehicle and electricity charges and receive fuel and diesel subsidies (Xinhua Net 2013).

Peak steel consumption

There are numerous views on when China’s absolute steel consumption will peak. Assessing the exact timing is challenging, as the ability to compare China’s development with advanced economies has some limitations. While steel consumption growth will decline gradually over time, there are a number of factors that will prolong the timing of the peak over the short to medium term.

Steel consumption is closely linked to investment in developing economies, as it is used to develop a country’s stock of infrastructure, buildings and equipment. Over the past 50 years, China has accumulated around five billion tonnes of steel in its capital stock, with almost three-quarters of this total accumulated over the past decade (Credit Suisse 2012b). China’s steel consumption is unlikely to peak before the construction cycle matures and investment in infrastructure declines. China’s investment expenditure is likely to remain elevated until at least the early 2020s based on plans to expand transportation systems and energy infrastructure to accommodate the expanding urban population and avoid problems related to congestion and pollution. For example, there are 50 cities that meet the Chinese Government’s population and economic growth criteria to support subway construction (Credit Suisse 2012b).

Berkelmans and Wang (2012) expect Chinese residential construction to remain at high levels for another two decades and then decline slowly beyond that. A large proportion of current residential construction activity is directed at urban renewal, increasing the quality of the housing stock. It is estimated that China will need to build more floor space than already exists over the next 10 to 15 years to continue to improve living conditions (Credit Suisse 2012b). New builds are expected to be more steel intensive than present housing (Berkelmans and Wang (2012).

A consensus among analysts is that the peak in total Chinese steel consumption is likely to transpire in the mid to late 2020s. Berkelmans and Wang (2012) project a peak in residential construction, the largest end-use of steel, in 2023; while McKay (2008) projects the peak to occur in the early to mid-2020s, noting, however, that it was more likely to be later rather than sooner. Rio Tinto (2013), on the other hand, projects the peak to occur closer to 2030, supported by industrial demand for domestic and export markets, despite construction demand peaking around 2025 (Table 1).


Table 1: Comparison of peak steel projections

Forecasting organisation Year of projection Year of peak Peak volume

Rio Tinto 2013 2030 1 billion tonnes

BHP 2012 2025 1.1 billion tonnes

Credit Suisse 2012 2025 1.1 billion tonnes

McKay 2008 Early to mid-2020s N/A

Steel industry structure and capacityShort term

In order to eliminate overcapacity, industry fragmentation and pollution, the Chinese Government has introduced a number of policies aimed at promoting the strategic development of the sector since 2000. This has continued into the 12th FYP which details plans to further restructure China’s iron and steel sector. Over the period to 2015, there is expected to be further merger and acquisition activity to create several large and more efficient companies; restrictions on the expansion of steel capacity; the utilisation of better technology; a greater emphasis on the production of high-end steel products and the relocation of capacity to coastal areas. Following these changes, the rate of steel production growth is expected to decline (KPMG 2011).

Most of the capacity expansion restrictions are aimed at smaller steel producers that have been major contributors to the declining profitability of the sector. These producers typically use older technologies that create more pollution relative to output than larger facilities. Small producers will likely be forced to close or agree to a merger/acquisition under the 12th FYP. The criteria for closure of small steel producers are outlined in Table 2. It is envisioned that this will result in China’s top ten steel producers accounting for 60 per cent of China’s steel output by 2015, compared with 50 per cent in 2011. A longer-range target of 70 per cent of total production for the top ten steel producers by 2020 was set out in the Development Policies for the Iron and Steel Industry released by the NDRC in 2005 (KPMG 2011). This industry consolidation has been accelerated by state banks reducing lending rates to loss-making steel producers (Ernst and Young 2013).

Table 2: Cut-off for steel capacity closure

Blast Furnace < 400 cubic metres

Convertors < 30 tonnes

Electric Arc Furnace < 30 tonnes

Hot-rolled Strip < width of 1450 millimetres (a)

Hot-dipped Galvanised Coil < 300 000 tonnes a year

Colour-coated Sheet < 200 000 tonnes a year

a Excludes specialty steel.

Source: KPMG 2011.


The Chinese Government plans to relocate steel production facilities to coastal areas and interior waterways. Under the 12th FYP, a target of 40 per cent of production to be based in these regions by 2015 has been set in order to reduce seaborne logistics costs and environmental strain on current producing areas. Regions touted for steel industry development include Caofeidian Port in Hebei province, Zhanjiang in Guangdong Province and Fangcheng Port in the Guanxi Zhuang autonomous region (KPMG 2011). It is estimated that transportation costs currently account for around 11 per cent of the operating costs of Chinese steel companies (Ernst and Young 2013).

The 12th FYP has a strong focus on energy conservation and emissions reduction. In the iron and steel sector, support will be provided towards technical development in non-blast furnace iron making, clean steel production, integrated resources utilisation, energy management systems, high-temperature and high-pressure coke quenching, integrated residual heat utilisation and desulphurisation of sintering flue gas. To achieve this, it is expected that China will need to draw on foreign expertise particularly that of other large steel makers located in Japan and the Republic of Korea.

The penetration of specialty steel as a proportion of crude steel output is relatively low in China (5 to 10 per cent) compared with more industrialised countries (10 to 20 per cent). This sector is also being targeted for support under the 12th FYP (BOC 2012). As a result, high-end steel production is likely to grow despite forced consolidation throughout the rest of the industry.

Medium to long term

Over the medium to longer term, China will continue its efforts towards industry consolidation, improved efficiency and environmental standards and the creation of high-end products. The production of steel is expected to decline in line with declining steel demand.

The focus to date on the production of long products in the Chinese steel sector has supported the rapid expansion in construction activity over the past decade. The sector will need to continue the trend towards increasing the production of flat products such as plates and strip to service the manufacturing sector, particularly as construction activity begins to decline. If the industry does not make the transition as their requirements evolve, China will continue to rely heavily on the importation of flat products (Trench 2004).

Raw materialsChina has large iron ore resources, but they are a relatively low grade compared with other major iron ore producers. China’s iron ore grades have declined rapidly since the late 1990s. Accordingly, an increasing proportion of China’s iron ore demand has been met by imports (Figure 7). This trend is likely to persist if domestic iron ore grades continue to decline.


Figure 7: China’s iron ore grade and import dependency

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China’s mining policy has evolved over the past three decades from a focus on domestic resources towards international markets and foreign-sourced raw materials, driven by resource-intensive growth and limited domestic supply. Today, China’s iron ore policy strategy can be split into two broad themes—increasing domestic supply and reducing domestic consumption of raw materials (OECD 2012).

China will look to expand its iron ore supply through the development of large iron ore mines via industry consolidation and upgrades and acquiring interests in resources projects abroad. Under the 12th FYP, China has aimed for 45 per cent of iron ore to be sourced domestically by 2015 and a further 40 per cent from foreign assets. To date, most investment in foreign assets has been undertaken by state-owned companies, in contrast to domestic production which is largely driven by a few, large private companies. Whatever the intention, China’s strategy of investing in foreign assets may be constrained by political, economic, legal and financial factors (CBA 2012).

China is a high-cost producer of iron ore because of its low iron grades and energy intensive processing. These costs are expected to continue over the medium term and, with increasingly stringent environmental and safety laws and rising labour costs, make domestically sourced iron ore less commercially viable. Further development of iron ore mines in China will also be hampered by water and power availability, environmental regulation—especially at small low grade mines, lengthy approval processes of two to three years and at least 25 different taxes and fees adding to the cost of production (CBA 2012).


China’s steel consumption is expected to decline over the longer term as the factors that have been supporting rapid consumption growth, such as urbanisation and infrastructure development, begin to wane. Reinforcing these trends, the Chinese Government is attempting to further reduce steel consumption by changing steel-use standards that promote the use of high-strength, long-life products that require less frequent replacement (OECD 2012). Over time, China’s steel production is expected to decline in response to falling steel consumption. Accordingly, China’s iron ore requirements will be reduced.

Crude (unprocessed steel) can be produced directly using iron ore and coking coal with a Basic Oxygen Furnace (BOF) or from scrap steel and other inputs using an Electric Arc Furnace (EAF) (Holloway et al 2010). Although China is the world’s largest producer of steel using EAF, the process only accounts for around 11 per cent of its production capacity (CEIC 2012). This, in part, is because of the difficulties in accessing reliable electricity supply in some regions and low domestic scrap availability.

China’s scrap steel penetration is low, at around 14 per cent of production, compared with the United States where 60 per cent of production uses scrap (Holloway et al 2010; Yun 2012). Scrap utilisation reduces the reliance on raw material inputs, costs and energy use. Accordingly, the Chinese government has set a goal of 20 per cent scrap steel penetration by 2015 (Metal Bulletin 2012).

Scrap steel can be reclaimed from industrial equipment, buildings and household appliances that have reached the end of their useful-life or sourced from industrial returns and offcuts. China’s scrap steel stock is expected to increase over the medium to longer term. The construction sector currently accounts for a large proportion of China’s current steel use. Typically, it takes around 25 to 30 years before steel in construction applications are recycled. Given the surge in construction activity over the past few decades, the availability of scrap steel from this source is expected to expand rapidly. Further sources of scrap will come from machinery as technical improvements make equipment obsolete faster; an expanding vehicle population; and greater ownership and disposal of household appliances (Metal Bulletin 2012).

The increased availability of scrap material will encourage greater utilisation in steel production and displace some demand for iron ore. However, it will not totally displace the demand for iron ore as some steel cannot be recovered (Moolman 2012). BHP believes the use of scrap material in China will be an important consideration in their iron ore development plans post-2025 (Kloppers 2012). In addition, technical upgrades at steel producing facilities that improve efficiency will also reduce the growth in demand for iron ore (OECD 2012).


Implications for AustraliaAs a major iron producer and the world’s largest exporter of iron ore and metallurgical coal, developments in China’s iron ore and steel sectors have important implications for Australia’s trade and investment interactions with China.

The trade relationship between the two countries has grown rapidly over the past two decades and it is well recognised that China plays an important role in Australia’s economic prospects. China is now Australia’s largest two-way trading partner. In 2011–12, total trade (exports and imports) between the two countries was worth $120.2 billion. Australia’s largest exports to China were iron ore and concentrates, coal, gold and crude petroleum (DFAT 2012). China is the main export market for Australia’s iron ore (73 per cent of total iron ore exports in 2012), with Japan and the Republic of Korea importing most of the remainder (Figure 8a). In 2011–12, Australia exported 334 million tonnes of iron ore to China at a value of $44 billion (Figure 8b).

Figure 8: Australia’s iron ore exports (a) and (b) below

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Source: ABS 2012.

While China’s steel consumption growth is expected to moderate and eventually decline, it is expected to remain the major driver of global demand for Australian iron ore over the short to medium term. Given its lack of domestic resources, China will still rely on imports to meet requirements. The extent to which these imports will be sourced from Australia will depend on the expansion of output and the cost of production in other major iron ore producing countries. Increasingly, China will look to improve its bargaining position and secure low-cost, long-term supply. Australia will need to ensure that it remains a low-cost producer to remain competitive as new production is commissioned around the world and China’s demand begins to wane.

Brazil is the world’s second largest exporter of iron ore (after Australia). Its exports are expected to grow considerably over the period to 2025, underpinned by large, relatively low cost, high quality reserves. However, there is the potential for an increasing proportion of its steel production to be directed towards domestic markets if the Brazilian economy continues to grow rapidly (BREE 2012a). Australian iron ore is of a lower grade than is Brazil’s. Australia’s geographical proximity to China is its major advantage over Brazil. Low freight rates or the development of deeper ports in China, allowing for larger ships (such as the Valemax) will work to erode some of this advantage (Trench 2004).

India’s high quality iron ore is sought after by Chinese steel mills (BREE 2012a). However, over the period to 2025, India’s growing domestic demand for steel and government policies and regulations will limit export growth. The government has imposed mining bans in the key producing states of Odisha and Goa to eliminate illegal mining of iron and manganese ores. This will result in lower production and export of iron ore in India over the short term while the bans remain in place (BREE 2013a). Further, to ensure that an increasing proportion of production is dedicated to the domestic market, the Indian Government introduced a 5 per cent tax on iron ore exports in 2009, which was increased to 30 per cent in early 2012 (BREE 2012a).

There are also expected to be some iron ore projects developed in West Africa—Mauritania, Gabon, Cameroon and Guinea. It is anticipated that all production in these countries will be exported. While these countries have good potential, they still lack sufficient legislative frameworks, infrastructure, a skilled workforce and have sovereign risk issues that are likely to slow their export development (BREE 2012a).

China plans to further develop domestic resources and secure access to foreign supplies to ensure that future demand for bulk materials can be met. As a result, China has emerged as a major investor and developer of foreign resources. The need for more capital in the Australian resources sector to facilitate capacity expansion has increased the appeal of investment alliances with China (Drysdale and Findlay 2009). China’s total investment in Australia has increased at an average annual rate of 20 per cent over the past decade.

Commensurate with the increase in China’s demand for iron ore, investment in Australia’s iron ore productive capacity has increased considerably over the past few years. There is still a large pipeline of iron ore projects expected to be developed. As at April 2013, there were


eight iron ore projects with a combined value of $22 billion at the Committed Stage on BREE’s Major Mining Projects listing. Together, these projects could add around 157 million tonnes to Australia’s annual iron ore exports, representing a 19 per cent increase in volumes from 2012. Fortescue Metals Group’s Solomon Hub (60 million tonnes) is the largest project by output capacity, followed by BHP Billiton’s Jimblebar mine (35 million tonnes) and Rio Tinto’s Nammuldi expansion (26 million tonnes).

There are a number of other iron ore projects at less advanced stages of development, with a combined capacity of 687 million tonnes. If iron ore prices decline, resource companies will reassess expenditure on exploration and investment. Consequently, some projects may not proceed through to development, while exploration activity may be reduced and other expenditure curbed.

Figure 9: Australian exports vs proposed project capacity

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Figure 9 contains projections for Australia’s export capacity, derived using information in the Major Mining Projects listing released in May 2013. Based on the projections in the March quarter edition of BREE’s Resources and Energy Quarterly (BREE 2013a), the productive capacity at the planning and feasibility stage in Australia exceeds what it is likely to exported over the next five years.


Concluding remarksThere has been much debate about the expected long-term trends in China’s steel consumption, and when it is likely to peak. Over the short to medium term, consumption will be supported by continued urbanisation, combined with plans for infrastructure development announced under the 12th FYP. Over the longer term, the influence of the traditional drivers of demand will wane and the rate of consumption growth will decline and eventually contract. Most analysts have projected overall steel consumption to peak in the mid to late 2020s. Using Japan and the United States as benchmarks, China’s per capita steel consumption could peak between 600 kilograms and 800 kilograms from its current 500 kilograms.

China’s steel industry will likely consolidate and excess capacity based on obsolete technologies should be reduced or eliminated. The focus of Chinese steel production will trend towards specialty steel and be based on technology that is more efficient and environmentally friendly. While steel production expands in response to requirements over the short to medium term, China will need to secure access to raw materials. The Chinese government is aiming to achieve this transformation through expanding domestic production where possible and also by investing in overseas assets. Over the longer term, the increased utilisation of scrap material will reduce iron ore requirements and the absolute volume of steel production will decline.

Australia has been a major beneficiary of the rapid growth in China’s steel demand. The volume of Australian exports of iron ore to China increased almost five-fold over the past five years and investment from China has supported the expansion of production. Over the short to medium term, China will remain the key source of demand for Australia’s iron ore exports. Australia should have the productive capacity to meet increased demand from China. Australian iron ore export volumes are projected to increase by 71 per cent by 2018, but will face increasing competition from Brazil and Africa.

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By invitation: The energy consumption, emissions and income inequalities of Chinese urban householdsJane Golley, Australian Centre on China in the World, The Australian National University, Canberra*4

IntroductionChina’s recent rise to the unenviable position as the world’s largest emitter of carbon dioxide has coincided with a far more enviable economic growth record during the last three decades, albeit one that has generated significant income inequalities in a range of dimensions. Chinese leaders are challenged by the simultaneous needs to ‘build a resource efficient and environmentally-friendly society’ and to ensure that growth is more equitable, both of which are integral to ‘building a harmonious society’ as outlined in the Eleventh Five-Year Plan (2006–2010) and reiterated in the Twelfth Five-Year Plan (2011–2015).

It is far from obvious how best to tackle the combination of challenges from a policy perspective, even when narrowing the analysis down to a particular disadvantaged region, sector or group within the Chinese economy. Transferring income from rich to poor households, for example, would obviously reduce inter-household income inequality, but what would be the consequences for the aggregate carbon dioxide emissions of Chinese households, let alone of China at large? Policy decisions would be considerably easier to make if income redistribution turned out to be environmentally friendly as well. This report demonstrates that this may well be the case for China’s urban household sector.

4 This report is based on an article written by Jane Golley and Xin Meng entitled ‘Income inequality and carbon dioxide emissions: the case of Chinese urban households’, published in Energy Economics, 34:1864–72, 2012. Please see this article for further details on the technical aspects of the report.

* The views expressed in this review are those of the author alone and not the Department of Resources, Energy and Tourism (RET). ‘By Invitation’ provides an opportunity for scholars and experts to present their research findings on issues of relevance to the Bureau of Resources and Energy Economics (BREE) and/or Tourism Research Australia (TRA).


Direct and indirect energy consumption and emissionsCarbon dioxide emissions (henceforth emissions) are embodied in energy, which each household consumes directly in the form of coal, petroleum, natural gas and electricity, and indirectly via the energy inputs used in the production of all other goods and services that the household consumes. Each household’s direct energy consumption is relatively easy to calculate, as long as the physical quantity of consumption of each direct energy source can be observed. These physical quantities can be converted into net calorific values (expressed in joules) and summed across all sources. Each of these energy sources has a different emission factor, which is country and sector specific. Each household’s direct energy consumption can thus be converted into its direct emissions by multiplying the net calorific value of each energy source by its emission factor and summing across all sources.

‘Indirect’ energy consumption, and therefore indirect emissions, can be calculated in a number of ways. Process analysis assesses the emissions generated throughout the lifecycle of a product, from the commencement of production through to distribution, storage, transport, waste and recycling. This method is highly data intensive, and simply not possible given the Chinese data currently available. Less data-intensive methods rely on input-output (IO) analysis to identify the energy embodied in a unit value of production for each sector. The resulting ‘indirect’ energy intensities reflect not only the energy used as direct inputs into the production of each good, but also the energy used in the intermediate inputs that are used in the production of that good, and the energy used in the intermediate inputs of those intermediate inputs, and so on. These sector-level intensities can be combined with household expenditure on each sector to calculate the indirect energy consumption of each household, in what is known variously as the ‘IO plus household expenditure’ method, ‘environmental IO life-cycle analysis’ or ‘mixed monetary energetic approach’. This method is much more commonly used for practical reasons and is the one adopted here.

In particular, each household’s total energy consumption per capita is the sum of its direct energy consumption per capita and its indirect energy consumption per capita. In order to calculate the latter, we first calculate the direct energy intensities associated with each sector and then use the IO table to calculate the associated indirect energy intensities. Multiplying each of these intensities by the household expenditure per capita on each good and summing across all sectors gives each household’s indirect energy consumption per capita. A similar method is used to calculate direct and indirect emissions.

Our data is drawn from a variety of sources. China’s Urban Household Income and Expenditure Survey (UHIES) 2005 provides details of household-level expenditure on 131 goods and service items, from which we calculate per capita expenditures by dividing through by the number of household members. UHIES also provides household-level quantities of coal, petroleum, natural gas and electricity, which are converted into kilojoules using the conversion factors provided in Peters et al. (2006) and again divided by the number of household members to obtain per capita values. Emission factors for each of these energy sources in China’s urban sector are used to translate direct energy into direct emissions, and are also drawn from Peters et al. (2006). For the indirect energy and emissions, we aggregate the survey data into the sectors provided in China’s 42 sector 2005 IO table. This is combined with total energy and emissions data for these sectors, which are compiled by Peters et al. (2006), to calculate sector-level direct and indirect energy and emission intensities, from which the remaining calculations follow.


China’s energy and emission intensities by sectorTable 1 presents the direct and indirect energy and emission intensities for each sector that is consumed by households, expressed in megajoules (MJ) per Yuan and kilograms per Yuan, respectively. Two key points emerge. First, as expected, there are substantial differences in the direct energy and emission intensities across sectors, with the latter ranging from over a kilogram per Yuan in the electricity, steam and hot water sector to just two grams per Yuan in the electronic and telecommunications equipment sector. Second, differences between the direct and indirect intensities for each sector can be substantial. The construction sector, for example, ranks fourth last in direct emissions at seven grams per Yuan but eighth in terms of indirect emissions of 0.425 kilograms. The electronic and telecommunications equipment sector, the electric equipment and machinery sector and the instruments, meters, cultural and office equipment sector each have indirect emissions that are more than one hundred times greater than their direct emissions. These findings reflect the importance of using the input-output method to determine the relevant intensities attributed to household consumption of each good.


Table 1: Direct and Indirect Energy and Emission Intensities by Sector, 2005

Direct Energy

Intensity (MJ/yuan)

Indirect Energy

Intensity (MJ/yuan)

Direct Emission Intensity

(kg/yuan)

Indirect Emission Intensity

(kg/yuan)Manufacture of food products & tobacco processing 0.233 1.944 0.017 0.174

Textile goods 0.280 2.973 0.019 0.263

Wearing apparel, leather, furs & down 0.364 2.623 0.025 0.230

Sawmills and furniture 0.170 2.916 0.012 0.274

Paper & products, printing & record medium reproduction

0.408 3.278 0.029 0.297

Petroleum processing and coking 0.874 3.945 0.063 0.333

Chemicals 0.516 4.620 0.055 0.434

Metal products 0.151 4.230 0.009 0.506

Machinery and equipment 0.168 3.645 0.013 0.423

Transport equipment 0.136 3.312 0.010 0.375

Electric equipment and machinery 0.062 3.525 0.004 0.413

Electronic and telecommunication equipment 0.038 3.141 0.002 0.347

Instruments, meters, cultural and office machinery 0.037 3.121 0.002 0.347

Other manufacturing products 0.183 2.909 0.011 0.291

Electricity, steam & hot water production & supply 12.680 16.194 1.066 1.394

Gas production and supply 1.450 4.988 0.095 0.412

Water production and supply 0.233 5.034 0.007 0.437

Construction 0.096 3.497 0.007 0.425

Transports and storage 1.689 3.790 0.120 0.312

Post, Telecommunication and IT Services 0.152 2.263 0.010 0.223

Wholesale and retail trade 0.229 1.248 0.015 0.111

Eating and drinking places, and hotels 0.229 2.061 0.015 0.181

Finance and insurance 0.152 1.264 0.010 0.115

Real estate 0.152 0.819 0.010 0.078

Rentings and other commercial services 0.152 2.478 0.010 0.247

Residential and other services 0.152 1.907 0.010 0.176

Education 0.152 1.913 0.010 0.175

Health services and social welfare 0.152 3.208 0.010 0.302

Culture, sports and entertainments 0.152 1.901 0.010 0.174

Source: Own calculations using method and data described above


Per capita energy consumption and emissions of Chinese urban households Table 2 presents key summary statistics of urban households’ per capita energy consumption and emissions by income decile in 2005, where decile 10 represents the richest 10 per cent of the surveyed households. The table shows that urban Chinese individuals consumed an average of 27 050 MJ of energy in 2005, which in turn generated an average of 2.342 tonnes of emissions. Energy consumption and emissions are increasing throughout the income range, and are much higher for richer households than for poorer ones, with those of households in the richest decile being 4.5 and 5.1 times those in the poorest decile. This is to be expected, since people with more income are likely to spend more on both direct and indirect energy consumption. Less obvious is the finding that indirect energy and emissions dominate total energy (at 74 per cent) and emissions (81 per cent). This conforms with numerous recent studies that highlight the importance of indirect energy consumption, including Pachauri and Spreng (2002), who show that indirect energy requirements account for close to half of the total energy consumption of Indian households and Cohen et al. (2005), who show that 61 per cent of household energy is indirectly consumed in Brazil.

The variation in the shares of direct and indirect energy and emissions is also quite striking, with the share of direct emissions dropping from 39 per cent to 11 per cent across the income range. This reveals that indirect emissions become an increasingly important source of total emissions as income rises. Urban China is not alone in this, with a similar change in the ratio of direct and indirect also observed in urban Australia, for example (Lenzen et al., 2004).

Table 3 focuses on the sources of direct energy consumption and emissions across income deciles. The most striking difference in direct energy consumption is the reliance on coal, with individuals in the first income decile consuming an average of 3369 MJ of coal in 2005, more than five times the amount of coal consumed by individuals in the tenth decile. These large absolute discrepancies translate into large differences in the shares of alternative energy sources across income brackets, with coal accounting for 55 per cent of the first decile’s direct energy compared with just seven per cent for the tenth decile. Because coal is the most carbon-intensive energy source (i.e., with the highest emissions factor), the share of emissions associated with these coal shares is even higher, accounting for 60 per cent of the first decile’s direct emissions, for example. While the quantity of all other sources of energy and the emissions generated therein increase with income, the quantity of coal and its associated emissions are in fact decreasing with income.


Table 2: Household per capita energy consumption and emissions by income decile

Total Energy Direct Energy

Indirect Energy

Total Emissions Direct Emissions

Indirect Emissions

Decile (MJ) (MJ)(% of total) (MJ) (kg) (kg)

(% of total) (kg )

1 12 893 6 134 48 6 759 1 029 406 39 623

2 16 103 6 323 39 9 780 1 316 410 31 907

3 18 408 6 496 35 11 912 1 524 415 27 1 109

4 19 989 6 232 31 13 756 1 673 391 23 1 282

5 22 845 6 587 29 16 258 1 937 412 21 1 525

6 25 022 6 662 27 18 360 2 139 413 19 1 726

7 28 376 6 984 25 21 392 2 450 430 18 2 020

8 31 636 7 066 22 24 570 2 757 431 16 2 327

9 37 069 7 614 21 29 455 3 258 463 14 2 795

10 58 157 9 356 16 48 802 5 334 576 11 4 758

Total 27 050 6 945 26 20 104 2 342 435 19 1 907


Table 3: Per capita direct energy consumption and emissions by energy source

CoalCoal

EmissionsOil

EmissionsElectricity Emissions

Gas Emissions

Decile (MJ)(% of total)

(% of direct) (kg)

(% of total)

(% of direct) (kg) (kg) (kg)

1 3 369 26 55 244 24 60 23 51 87

2 2 792 17 44 202 15 49 33 62 112

3 2 431 13 37 176 12 42 41 71 126

4 1 835 9 29 133 8 34 42 80 136

5 1 798 8 27 130 7 32 49 87 146

6 1 459 6 22 106 5 26 57 95 156

7 1 292 5 19 94 4 22 62 103 170

8 1 060 3 15 77 3 18 62 113 179

9 904 2 12 66 2 14 81 124 193

10 625 1 7 45 1 8 163 158 210

Total 1 757 6 25 127 5 29 61 94 151


It is this fact that drives the decline in per capita total emission intensities over the income range, as shown in Figure 1 across income percentiles. That is, people in poorer households are more energy intensive and therefore more emission intensive in their total expenditure patterns. The figure shows that this decline is driven entirely by the decline in direct carbon


intensity, since indirect carbon intensity increases slightly over the same range. This is because poorer households spend a greater proportion of their income on direct energy and also because a substantial amount of their direct energy is in the form of coal, whereas richer households shift into gas, particularly for heating and cooking purposes.

This is not to say that the sources of indirect emissions are the same across income deciles, as illustrated in Table 4. Different levels of expenditure on each good, combined with different emission intensities for each sector, result in variations in the contributions of each sector to each decile’s indirect and total emissions. For example, food products and tobacco account for 22.9 per cent of the poorest decile’s indirect emissions, double the share for the richest decile, while 10.6 per cent of the richest decile’s indirect emissions stem from transport equipment, compared with less than one per cent for the poorest decile. In aggregate, these different consumption bundles translate into the slight increase in the indirect emission intensity as income rises (as seen in Figure 1), suggesting that poorer households are relatively ‘green’ when it comes to their indirect carbon generation.

Table 4: Sources of indirect and total emissions for the 1st, 5th and 10th Deciles (%)

Share of total emissions Share of indirect emissions

Indirect emissions from: 1st 5th 10th Total 1st 5th 10th

Manufacture of food products & tobacco processing 37.4 25.8 12.7 22.2 22.9 20.5 11.3

Textile goods 0.2 0.2 0.1 0.1 0.1 0.1 0.1

Wearing apparel, leather, furs & down 9.4 11.7 8.9 10.7 5.8 9.3 7.9

Sawmills and furniture 0.3 0.9 1.9 1.1 0.2 0.7 1.7

Paper & products, printing & record medium reproduction

2.6 2.5 2.4 2.5 1.6 2.0 2.2

Chemicals 12.1 11.9 10.3 11.8 7.4 9.4 9.2

Metal products 0.6 0.6 0.6 0.7 0.3 0.5 0.6

Transport equipment 0.9 2.0 11.8 4.4 0.5 1.6 10.6

Electric equipment and machinery 1.9 3.9 6.8 4.8 1.1 3.1 6.0

Electronic and telecommunication equipment 1.2 4.0 5.2 4.5 0.7 3.2 4.7

Instruments, meters, cultural and office machinery 0.0 0.2 0.5 0.3 0.0 0.1 0.5

Jewelry 2.7 2.8 3.1 3.0 1.7 2.2 2.7

Water production and supply 2.2 1.5 0.9 1.3 1.3 1.2 0.8

Construction 2.0 4.0 7.7 4.9 1.2 3.2 6.9

Transports and storage 2.3 3.0 3.5 3.2 1.4 2.4 3.1

Post, telecommunication and IT services 5.2 5.4 3.9 5.0 3.2 4.3 3.5

Eating and drinking places, and hotels 4.0 5.4 6.9 6.0 2.5 4.3 6.1

Finance and insurance 0.1 0.2 0.3 0.2 0.1 0.1 0.3

Rentings and other commercial services 1.2 1.0 1.1 1.0 0.8 0.8 1.0

Residential and other services 0.6 0.6 1.1 0.8 0.4 0.5 1.0

Education 7.3 6.0 3.5 5.1 4.5 4.8 3.2

Health services and social welfare 4.9 4.6 3.5 4.3 3.0 3.7 3.1

Culture, sports and entertainments 0.9 1.7 3.3 2.3 0.5 1.3 2.9



In what follows we are mainly interested in the relationship between emissions and income and what this implies about the impact of income redistribution from rich to poor households on aggregate household emissions. Figure 2 plots average per capita emissions by income percentile, revealing that the positive relationship between total emissions and income relationship is dominated by the indirect emissions-income relationship, while direct emissions vary little over the income range. This further stresses the point that indirect energy consumption is the major source of household-level energy consumption, and hence the major source of household-level emissions.

Figure 1: Per capita total, direct and indirect emission intensities across income percentiles

0.00

0.05

0.10

0.15

0.20

0.25

0.30

0.35

0.40

0 10 20 30 40 50 60 70 80 90 100

Emis

sion

inte

nsity

(kilo

gram

s pe

r yua

n)

Income percentile

total

direct

indirect

Source: Using method and data described in this section.

Figure 2: Total, direct and indirect emissions across income percentiles

2000

4000

6000

8000

10000

12000

0 10 20 30 40 50 60 70 80 90 100

Emis

sion

s (k

ilogr

ams)

Income Percentile

direct

indirect

total

Source: Using method and data described in this section.


Explaining household variations in per capita emissionsEconomic theory provides very little guidance to the specific functional form of the relationship between per capita emissions and per capita income. After exploring a range of different possibilities, we settled on the following log-level model specification:

lnTCk = β0 + β1yk + β2 y2k + β3 y

3k + β

4Vk+εk

where V is a vector of other variables that impact on total emissions, which include household size, the age and years of schooling of the household head, the percentages of children and elderly in the household, dwelling size and a dummy variable for each of the 15 provinces other than Beijing included in the survey data. In addition, we present results for the regressions with per capita direct emissions (DC) and per capita indirect emissions (IC) as the dependent variable respectively. All data are household-level per capita values calculated using the method and data described above.

The results are presented in Table 5. Column 1 shows a statistically significant cubic relationship between total emissions and income that implies two turning points in a generally upward sloping function: one downturn at approximately 57 000 Yuan and an upturn at around 115 000 Yuan. Columns 2 and 3 present the results for direct and indirect emissions respectively. As observed in Figure 2, the relationship between total emissions and income is driven almost entirely by the relationship between indirect emissions and income, as seen by the similarity of the coefficients in Columns 1 and 3. In contrast, the relationship between per capita direct emissions and income is virtually flat (with an insignificant coefficient on the cubic income term, a just significant coefficient on the squared term, and a significant coefficient on the linear term of just 0.022).

Larger households generate fewer per capita emissions on average, and this is true for both direct and indirect emissions. This implies that there are economies of scale in both direct and indirect energy consumption, which is quite intuitive. For example, cooking for five people does not require five times the energy used in cooking for one person, thereby reducing per capita direct emissions. Similarly, five people in the one household might use one or two televisions, but surely not five, thereby reducing the indirect emissions associated with television consumption (and the direct emissions associated with the electricity used to power them). The age and education level of the household head both have a significant positive impact on total emissions. Interestingly, while age impacts positively on direct emissions and negatively on indirect emissions, the reverse is true for years of schooling. At a stretch, this may suggest that more educated households are better informed about the negative (health and environmental) consequences of direct energy consumption, particularly in the form of coal, or that they are more environmentally conscious, and choose to adjust their direct energy consumption patterns accordingly. They are, however, perhaps unaware that their relatively ‘sophisticated’ consumption bundles are also relatively emission intensive. The positive coefficient on larger dwelling sizes in the total emissions regression is to be expected, and is driven by the positive impact of larger dwelling sizes on direct emissions.


The percentage of children in the household does not impact significantly on total emissions, although it does have a negative impact on direct emissions, while a higher percentage of elderly has a positive impact on all emissions. Like the age of the household head, this may indicate that older people are less aware of the health damages associated with direct energy consumption, but is more likely to reflect the longer time period that retirees spend at home. The positive coefficient on the percentage of elderly in the household for the indirect emissions suggests that either their consumption bundles are relatively carbon intensive or they spend a relatively higher percentage of their income on indirect rather than direct energy.

Table 5: Determinants of Household Per Capita Emissions

Dependent variable Log Per Capita Total Emissions

Log Per Capita Direct Emissions

Log Per Capita Indirect Emissions

Per capita income/103 0.093 0.022 0.116

[0.002]*** [0.002]*** [0.003]***

(Per capita income/103)2 -0.0012 -0.0001 -0.0017

[0.000]*** [0.000]* [0.000]***

(Per capita income/103)3 0.000004 0.0000002 0.000006

[0.000]*** [0.000] [0.000]***

Number of household members -0.069 -0.136 -0.043

[0.004]*** [0.007]*** [0.004]***

Household head age 0.001 0.010 -0.001

[0.0004]*** [0.001]*** [0.0004]***

Household head years of schooling 0.007 -0.008 0.014

[0.001]*** [0.002]*** [0.001]***

Household % children (age 0-15) 0.010 -0.111 0.030

[0.218] [0.040]*** [0.030]

Household % elderly (age>=65) 0.051 0.119 0.018

[0.016]*** [0.027]*** [0.016]***

Dwelling size (square meters/103) 0.0003 0.0016 -0.0001

[0.0001]*** [0.0002]*** [0.0001]

Constant 6.89 5.19 6.47

[0.012]*** [0.016]*** [0.035]***

Observations 33,358 33,115 33,358

R-squared 0.525 0.128 0.585

Source: Own regressions using data described in Section 2.

Note: *, **, *** significant at 10%, 5%, 1% respectively. Standard errors in brackets.

Provincial dummy results not reported for space reasons.


Income redistribution and emission reductionIf emission intensity (i.e., emissions per Yuan spent) is constant across income classes, then it is straightforward to show that any income redistribution will have zero impact on aggregate emissions (since if you take one Yuan from one person and give it to any other person, regardless of their income bracket, aggregate emissions won’t change). However, if emission intensity is decreasing in income (as it is here, as seen in Figure 1), the impact on aggregate emissions is unclear. Intuitively, this is because transferring money from a rich person with relatively low emission intensity to a poor person with relatively high emission intensity has four effects. For the poor person, higher income reduces the emission intensity on all pre-transfer income, which contributes to a reduction in aggregate emissions, which is offset by the fact that he/she now has more income to spend. For the rich person, the income reduction increases the intensity on all pre-transfer income, which is offset by the fact that they now have less money to spend. The overall impact on aggregate emissions depends on the relative magnitudes of these terms, which in turn relates to the marginal propensity to emit (MPE)—that is, to the slope of the total emissions-income relationship, or the change in total emissions resulting from a one Yuan increase in income. In particular, it is straightforward to show that inequality-reducing income redistribution will reduce aggregate emissions as long as the MPE is increasing in income.

We use the regression results to calculate point estimates of the MPE, the marginal propensity to directly emit (MPDE) and the marginal propensity to indirectly emit (MPIE) at the average level of income for each decile, as shown in Table 6. The results indicate an increasing MPE, which implies that taking one Yuan from someone in the richest decile and giving it to someone in the poorest decile will decrease aggregate emissions (by 0.082 kilograms = 0.180-0.098). The MPE and MPIE are both increasing in income evaluated at the decile means, close to doubling between the first and tenth deciles, while the MPDE rises marginally through to the ninth decile and then falls slightly in the tenth.

Note, however, that the implied magnitude of emissions reductions is small. Given average per capita emissions of 2.3 tonnes in 2005, our finding that the MPE of households in the richest decile only differs from that of households in the poorest decile by a magnitude of less than 100 grams suggests that the emissions-income relationship is in fact very close to linear over the relevant income range—i.e. that the MPE is very close to being constant.

This finding runs counter to a number of cross-country time-series analyses that have provided evidence of a diminishing MPE as income rises (Holtz-Eakin and Selden, 1995; Heil and Selden, 1999; Ravallion et al. 2000), and hence a trade-off between inequality-improving income redistributions and aggregate emissions (since a dollar taken from a rich person will reduce aggregate emissions by less than a dollar given to a poor person will increase it). However, these studies have failed to take into account the indirect emissions of consumers, generated through the indirect consumption of energy embodied in the goods and services they consume. By including indirect emissions into the analysis here, our results imply that for the case of Chinese urban households, redistribution may well be both egalitarian and green—a win-win case.


Table 6: Marginal propensities to emit at decile means (kg per Yuan)

Decile MPE MPDE MPIE

1 0.098 0.0073 0.082

2 0.108 0.0075 0.094

3 0.116 0.0075 0.103

4 0.124 0.0076 0.112

5 0.131 0.0077 0.121

6 0.140 0.0078 0.131

7 0.150 0.0079 0.143

8 0.162 0.0080 0.158

9 0.177 0.0081 0.178

10 0.180 0.0080 0.179

Average 0.147 0.0079 0.140

Source: Calculated by authors based on regression results.

Concluding remarksThis report has focused on just one of the many sources contributing to China’s new and unenviable position as the world’s largest emitter of carbon dioxide: urban household consumption. Using urban household survey data, we examined the variation in per capita energy consumption and emissions across households with different income levels. As expected, richer households emit more per capita both directly and indirectly. More interesting were the findings that poorer households are more emission intensive in their direct energy consumption because of their heavy reliance on coal, while richer households are more emission intensive in their indirect energy consumption. Our results indicated that 81 per cent of Chinese urban household emissions in 2005 were generated indirectly through the energy inputs used in the production of goods consumed by those households. This percentage rose steadily through the income range, peaking at 89 per cent for households in the richest decile, compared with just 61 per cent for the poorest households. This combination of facts gave rise to a positive relationship between per capita total emissions and per capita income, driven by the rise in indirect emissions over the income range. Given that the sole purpose of all production is ultimately consumption (as Adam Smith pointed out centuries ago), a deeper understanding of the relationship between consumer choice—both between and within direct and indirect energy demand—and the emissions generated as a consequence is called for. This report provides a small step in that direction.

The econometric analysis confirmed the positive relationship between total emissions and income, with an increasing marginal propensity to emit across income deciles, which was underpinned by an increasing marginal propensity to indirectly emit over the entire income range and a slightly increasing marginal propensity to emit directly over the first nine deciles. After controlling for income, households with larger dwellings and a higher percentage of elderly members had higher direct and indirect emissions, while households in Beijing—one of the country’s most developed urban areas—had higher indirect emissions than 14 of the 15 other provinces in the survey data.


As Chinese household incomes continue to rise and as China’s urbanisation gathers pace, consumer choices are likely to follow trends established in the most developed urban cities. In combination with a rapidly ageing population, evidence of an increasing marginal propensity to emit (even if only slight), and double-digit economic growth, it may be tempting to conclude that China’s carbon dioxide emissions are on unstoppable upward trend, since all of these factors point in that direction. However, such a conclusion would be unwise based on cross-sectional results, given the potential for changes in consumer choices and production techniques. The former could be altered by the introduction of a carbon tax or changing attitudes towards ‘green consumption’, for example. And there are a number of ways of improving the latter, including efforts to promote energy efficiency in the manufacturing sector, to strengthen international cooperation in low-carbon technologies, to reduce the emissions associated with upstream production sectors in the booming construction sector, and to conserve energy in the lighting, heating and air-conditioning at the household level (Guan et al., 2009). With all of these possibilities, the future path of the world’s top carbon dioxide emitter is very difficult to pin down—or up, as the case may be.

Instead, the final conclusion is less far-reaching and more optimistic. Household-level income redistribution is certainly not an appropriate policy tool for tackling China’s growing emissions—and nor did we set out to demonstrate that it was. What our results do allow us to conclude is that inequality-reducing income redistribution is unlikely to have a significantly detrimental impact on aggregate urban household carbon dioxide emissions. This is surely a positive finding for a country intent on building an environmentally friendly and harmonious society.

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Ravallion, Martin, Mark Heil and Jyotsna Jalan (2000), “Carbon emissions and income inequality”, Oxford Economic Papers 52:651–69.


Study tourism from China: opportunities and implications for AustraliaByron Keating5 and Amy Godfrey6

IntroductionAustralia, like most developed countries, has seen a significant shift towards a service-driven economy over the past five decades (ABS 2013). During this time, education and tourism have emerged as two of Australia’s largest service export industries. International education contributed $15.7 billion in export income to the Australian economy in 2010–11 (AEI 2012a). The direct contribution to gross domestic product (GDP) from tourism was approximately $34.6 billion for the same period (TRA 2012). When indirect contributions are taken into consideration, Tourism Research Australia (TRA) estimates that the total contribution is in the order of $73.3 billion, or 5.2 per cent of Australia’s GDP.

In this review we explore the nexus between education and tourism, termed study tourism, paying particular attention to understanding the nature and impact of China. China is recognised as Australia’s most important trading partner in terms of both international education and tourism, accounting for $4.3 billion (or 28 per cent) of Australia’s export income from international education and $3.5 billion (or 15 per cent) of Australia’s tourism exports (ABS 2013).

We begin by providing an overview of the strategic context for international education, including a summary of key policy initiatives that impact education and tourism (see Box). This initial discussion will provide a backdrop for examining the direct and indirect tourism impacts of China’s international education market. We conclude with a discussion about the implications of this analysis for industry and government.

Strategic contextTo unlock the potential of study tourism, it is necessary to recognise that overseas students must first choose Australia for their international education. Prior academic research has identified a range of key drivers of education destination choice (Bourke 2000; Briggs 2006; Chen and Zimitat 2006; Cubillo et al. 2006; Eusebio and Carneiro 2012; Kemp et al. 1998; Mazzarol and Soutar 2002; Shanka et al. 2006; Wang and Davidson 2008). The most highly cited

5 Professor Byron Keating is the director of the Centre for Tourism Research at the University of Canberra and the academic lead of the Emerging Markets Special Interest Group of the Council for Australasian University Tourism and Hospitality Education.

6 Amy Godfrey is a research analyst in the National Survey Team of Tourism Research Australia.

* The views expressed in this paper are those of the authors alone and not the Department of Resources, Energy and Tourism (RET).


of these researchers, Mazzarol and Soutar (2002), distinguish between push factors—those that influence a student’s decision to study overseas—and pull factors—those related to awareness and knowledge of a host destination. The most important pull factor for Chinese students has been to gain a better understanding of the West, followed by a perception that overseas education was of a higher quality than locally-offered equivalents. On the push side, international recognition of qualifications was the most important factor for Chinese students, followed by quality of education. Mazzarol and Soutar also highlight the importance of employment opportunities and access to an international community as important factors that can mitigate cost concerns.

The findings of this work are consistent with the above-cited academic research, which recognises, universally, the importance of quality, reputation, and cost as key drivers of destination choice. The remainder of this section will provide a general overview of current and future demand from China for international education, followed by consideration of Australia’s global competitiveness in terms of key push and pull factors.

Global demand from ChinaInternational education demand in Australia is dominated by Asian countries, with China the most significant source market. A recent report from the International Education Advisory Council reveals that of the 402 388 international students studying in Australia in 2012, 37 per cent, or almost 150 000 Chinese students, undertook study across different education categories, with higher education the largest contributor at 94 309 students (IEAC 2013). Table 1 provides a breakdown of enrolments for Australia’s top five source markets by education category.

Table 1: Australia’s top five source markets by education category enrolment

Rank Country Higher ed. VET Schools ELICOS Non-award Total1 China 94 309 15 821 8 367 21 157 6 104 149 758

2 India 12 671 40 061 93 1 366 205 54 396

3 Korea 8 289 9 143 2 202 7 435 650 27 719

4 Vietnam 11 071 4 717 1 908 4 432 423 22 551

5 Malaysia 16 308 3 171 569 924 615 21 587

Source: AEI International Student Data, 2012b; IEAC Australia – Educating Globally, 2013.

Australia only has a fraction of the total Chinese tertiary study market (around 0.3 per cent). According to the latest UNESCO Global Education Digest, only 1.8 per cent of Chinese tertiary students seek study opportunities outside of China (UNESCO 2012). And while Australia is a preferred destination for Chinese students, accounting for around 16 per cent of Chinese international enrolments, second only to the United States (23 per cent), it is unlikely that Australia’s relative share of this market will grow over coming years without significant investment in improving the capacity of Australian institutions, despite significant growth prospects out of China.


Table 2: International tertiary student flows for Australia’s top five source markets

Country OutboundMobility

ratioEnrolment

ratioShare of top destinations

Inbound total Net flow

Net flow ratio

total

China 562 889 1.8 0.5 US (22%) AU (16%) JP

(15%)

71 673 -491 216 -1.6

India 200 621 1 0.2 US (52%) UK (19%) AU

(10%)

.. .. ..

Korea 23 682* .. .. AU (35%) CAN (14%) FR (8%)

.. .. ..

Vietnam 47 979 2.4 0.5 US (27%) AU (20%) FR

(12%)

3 260 -44 719 -2.2

Malaysia 53 884 5.5 2.2 AU (36%) UK (23%) US

(11%)

57 824 3 166 0.3

Source: UNESCO Global Education Digest, 2012. AEI International Student Data, 2012b. *This figure represents an estimate based on Australian enrolment data and the UNESCO market share ratios.

A report on Australia’s international education industry by the Boston Consulting Group (BCG) suggests that growth in demand for international tertiary education from China will more than double between now and 2020 (see Figure 1), increasing by between 500 000 and 800 000 student placements (BCG 2013). This is in line with OECD forecasts of 7 per cent compound growth in the pool of international students through 2020. This growth in demand for high quality education will exceed China’s domestic supply, with increasingly wealthy populations willing and able to fund overseas education. However, competing host countries, specifically, the United States and United Kingdom, are positioned to aggressively expand capacity and represent a key challenge for Australia in the Chinese international education market.


Figure 1: Projections for Chinese higher education students studying abroad

200

400

600

800

1000

1200

1400

1600

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 '000

low

base

high

Source: EAC Australia – Educating Globally, 2013; BCG Analysis of International Education, 2013.

Australia’s global competitivenessOne possible implication of the growth in demand from China could be a reduction in demand for English-speaking higher education over time. Improved domestic higher education standards in China and growing demand for Mandarin-speaking education internationally, a key imperative of the China Ministry of Education, could represent a real ‘game changer’. Even if the ratio of demand for English to non-English speaking higher education remains constant over the next decade, smaller host countries such as Australia do not have the capacity to compete with the United States and United Kingdom. International enrolments in Australia currently represent 21.3 per cent of total tertiary enrolments, compared with 16 per cent in the United Kingdom, and just 3.5 per cent in the United States (OECD 2012). The United States has significant growth potential, coupled with strong education brands and a lower relative cost base. BCG predicts that the United States will move aggressively into the international education space (targeting China in particular), contributing to an over-supply of English-speaking tertiary education by 2020.

Australia’s competitiveness has been negatively influenced in recent years by the rising relative cost of education (combined fees and cost of living), particularly as a result of the appreciation of the Australian dollar after the Global Financial Crisis (GFC). Figure 2 shows that the relative average annual cost of studying and living in Australia has increased significantly in comparison to our two major competitors. The cost of international education in Australia has increased by 166 per cent in the last three years and was estimated at $44 000 per annum on average in 2011, compared to $37 000 in the United States and $30 000 in the United Kingdom.


Figure 2: Relative cost of higher education

10

20

30

40

50

2005 2006 2007 2008 2009 2010 2011 2012

'000 $US

Australia

United States

United Kingdom

Source: EAC Australia – Educating Globally, 2013; BCG Analysis of International Education, 2013.

Commencement data from Australian Education International reveal that despite a strong cumulative annual growth rate over the past decade of around 20 per cent, the growth of the Chinese higher education market in Australia has been flat post GFC. While this reflects the relative increase in the cost of Australian education, from Figure 3, we can see that the fallout from the GFC in the Chinese market was delayed and less pronounced compared to Australia’s other international education markets, which have fallen by more than 10 per cent.

Figure 3: Higher education commencements, 2002–12

10

20

30

40

50

60

70

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 '000

all other countries

China

Source: AEI International Student Data, 2012b; BCG Analysis of International Education, 2013.


One emergent concern for Australia’s international education exports relates to the relative quality of the Australian education product. OECD data reveal that while Australia is ahead of the United States and the United Kingdom in terms of reading, mathematics, and science performance on PISA international benchmarking, it compares far less impressively against emerging Asian economies, with China and Korea leading the way. Likewise, the improvement of Chinese universities in international rankings suggests that this trend is not limited to primary and secondary education.

China has rapidly improved its higher education system over the last 15 years. In particular, its investment in the building research capacity of its top nine flagship universities is already showing positive results, with three universities in the latest Times Higher Education’s top 50 rankings and four universities in the top 50 list published by QS World Rankings. This result compares favourably with Australia, which has four in each list. The relative improvement in the reputation of China’s domestic universities is likely to affect future demand for international education in Australia and, consequently, will impact direct and indirect educational tourism.

Online offerings will also test the brand strength and agility of Australian providers. The massive open online course (MOOC) phenomenon is already helping to increase the reach and credibility of well-regarded international education brands. However, if managed effectively, the movement to online and hybrid models could potentially extend Australia’s ties and influence in Asia.

Related Policy Initiatives

Some of the key policy-related initiatives undertaken in recent years in support of study tourism include:

Australia in the Asian Century White Paper

The release of the White Paper represents a significant re-positioning of Australia within its geographic footprint of Asia. Key to this agenda is recognition of the importance of education and cultural exchange. The White Paper argues for investment in programs that will support greater two-way people-to-people links between Asia and Australia. While the White Paper is not focused exclusively on China, it does, nevertheless, highlight that China will emerge as Australia’s key trading partner over the coming years.

Australia-Educating Globally

The Australian Government established the International Education Advisory Council to provide advice on the challenges and opportunities facing international education. A key milestone of the Council was the preparation of the “Australia: Educating Globally” report on trends in international education and on current policies affecting the sector. The report highlighted that demand for Australian education was dominated by students from Asian countries (particularly China), and that Australia needed to act to fortify its position in an increasingly competitive international education market.

Establishment of the Tertiary Education Quality Standards Agency (TEQSA)

The TEQSA was established following the Bradley Review of Higher Education in 2009. This review recommended, among other things, that Australia needed an independent national regulatory body to achieve a sustainable and responsible higher education system in a larger, more diverse, and demand-driven environment. In response to the Bradley Review in 2009, the Australian Government committed itself to renewed emphasis on student outcomes and the quality of the student experience.


Tourism 2020

Released in late 2011 as an extension of the National Long Term Tourism Strategy, Tourism 2020 is intended to respond to ongoing challenges and emerging opportunities for the Australian tourism industry. A key objective within the Tourism 2020 strategy was recognition of the importance of Asia, and in particular, China, to the future prospects of the Australian tourism industry. To reinforce the importance of China to the tourism industry, the Australian Government convened the inaugural Australia-China Tourism Summit in Cairns in 2011. A key outcome was a commitment to a memorandum of understanding on strengthening tourism cooperation between the two countries.

Tourism QualityThe Australian Government established the T-QUAL Accreditation and the T-QUAL Grants programs in 2010–11. The accreditation program is overseen by the Tourism Quality Council of Australia and aims to provide a symbol of quality to enable tourists to choose quality products and services. The grants program is administered by the Department of Resources, Energy, and Tourism and seeks to provide support for operators to address supply side challenges. A key initiative in relation to the Chinese market was the announcement of two strategic tourism investment grants. The first is focused on improving understanding of China’s market, and the second, announced in March 2013, is intended to improve capacity to serve.

Asia Marketing Fund

Funded from an increase to the Passenger Movement Charge, the Asian Marketing Fund will see the Australian Government invest $61 million over four years to support the promotion of Australia to growing Asian markets. The Fund is administered by Tourism Australia and seeks to encourage co-investment from the private sector and state and territorial governments.

Immigration and Visas

The Australian Department of Immigration and Citizenship has extended streamlined online visa processing for students from China (and other key markets). This was in direct response to criticism from the tertiary education sector about the impact of processing delays on the reputation and attractiveness of Australia’s education product. Other important initiatives relate to the relaxation of work conditions and the introduction of working holiday and post-study visas. Improvements to the Approved Destination Status (ADS) scheme, including the establishment of a new compliance taskforce, will also ensure a high quality experience for families and friends travelling to Australia on an ADS visa. Further proposed reforms include prioritising skilled migration opportunities for graduates of Australian education.

Tourism ImpactsThe study tourism market is an important market for the Australian tourism industry. Research undertaken by TRA in 2006, titled “Study Tourism Report: Profile of International Visitors who Studied in Australia,” provided a major positioning statement for the importance of the study tourism market to Australia. We use the analysis undertaken in this earlier report as a framework for investigating study tourism from China.

We first distinguish between a study tourist and a study visitor. A study tourist is someone who visited Australia to undertake study. A study visitor, on the other hand, is someone who came


to Australia for the purpose of visiting an international student studying in Australia. Study tourists can be further classified based on the nature of their study. Formal study tourists are defined as visitors aged 15 years and over who stated on their visitor arrival card that their main purpose for travelling to Australia was “education.” Informal study tourists were those who indicated a purpose for visiting other than education but still studied or took a course during their trip. Figure 4 provides a segmentation of the Chinese international visitor market on the basis of these classifications. While post-study tourism impacts are beyond the scope of the present research, we have included information on recent research that has sought to quantify the importance of Australian-educated alumni (see Box on alumni potential).

Figure 4: Segmenting the Chinese international visitor market by visitors, average stay in nights and average expenditure (excluding international airfares and packages)

All International 5.7 Million visitors Avg

stay 36 nights $3,316 avg expenditure

All China 592,169 visitors (10%)

Avg stay 47 nights (13%) $5,314 avg expenditure

(15%)

Other International 5.1 Million visitors (90%) Avg stay 35 nights (87%) $3,084 avg expenditure

(85%)

Study Visitors 23,153 visitors (4%)


(3%)

Study Tourists 96,236 visitors (16%)


(61%)

Other Visitors 472,780 visitors (80%)


(36%)

Formal Study 90,895 visitors (94%) Avg stay 165 nights

(99%) $21,062 avg expenditure

(99%)

Informal Study^ 5,341 visitors (6%)


(1%)

Source: Tourism Research Australia, 2013 (Unpublished Data). ^ Small sample size for informal study data - interpret with caution.

Note: Percentage share in brackets relates to total, not average.

We can see from Figure 4 that while study tourists represent just 16 per cent of the Chinese international visitor market, they account for 54 per cent of visitor nights and 61 per cent of expenditure from this market. With an average of 157 visitor nights and $20 017 per student, the study tourist from China stays more than three times as long and spends more than three times as much as the average Chinese visitor and stays almost five times as long and spends five times more than the average international visitor. The majority of this benefit, however, is attributable to formal study tourists, who account for 99 per cent of all study tourism nights and expenditures.


A demographic profile of each segment depicted in Figure 4 is presented below. Unsurprisingly, the study tourist market from China has a younger profile than the typical Chinese visitor and is more likely to be single. From Table 3, we can also see that the study tourist market is more likely to be female, particularly if undertaking an informal study visit. Interestingly, the majority of formal study tourists were repeat visitors (79 per cent), whereas informal study tourists were more likely to be first-time visitors. While this could be an artefact of the International Visitor Survey (IVS), which only captures data on the most recent 12 months, and many international students travel home at least once during their course of study, it could also allude to a pre-study market that visits to sample the Australian education system prior to commitment to a program of study. The profile of study visitors was comparable to the normal Chinese visitor population.

Table 3: Demographics by Chinese visitor classification

Gender Age Marital status Repeat-first

All int’l 54%, female 48%, 20-24 years 90%, single 79%, repeat

All China 52%, male 43%, 45 and over 58%, couple 63%, repeat

All study tourists 52%, female 44%, 45 and over 70%, couple 53%, first time

Formal study tourist 54%, female 48%, 20-24 years 90%, single 79%, repeat

Informal study tourist^ 66%, female 24%, 20-24 years 56%, couple 70%, first time

All study visitors 66%, female 71%, 45 and over 81%, couple 53%, first time


From Map 1, we can see that study tourism is dominated by China’s east coast with the majority of study tourists having originated from Shanghai (14 per cent), Jiangsu (13 per cent), and Guangdong (11 per cent). Other prominent source provinces include Beijing (8 per cent), Shandong (7 per cent), and Zhejiang (7 per cent).


Map 1: Source provinces within China

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AN

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NJI

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Num

ber o

f st

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tour

ists

Source: Tourism Research Australia, 2013 (Unpublished Data).


Figure 5 highlights the relatively younger profile of the formal study tourist group. The age profile of the study visitor group would seem to suggest that this group is likely to be parents or guardians of the study tourists. This assumption is also supported by additional IVS data, which show that 60 per cent of the study visitor segment from China travels as either an adult couple or as part of a family group. However, caution needs to be exercised when interpreting this due to small sample sizes for the travel group data.

Figure 5: Age distribution by visitor classification

5

48

24

12

12

71

4

24

44

43

10 20 30 40 50 60 70 80 90 100

Study visitor

Formal study

Informal study

All China

All international

%

15 to 19 20 to 24 * 25 to 29 30 to 34 35 to 44 45 and over *

Source: Tourism Research Australia, 2013 (Unpublished Data). Percentages relate to asterisk items in legend.

Direct impactsThis section of the report will provide a more detailed analysis of the direct impacts associated with the Chinese study markets. We can see from Figure 6 the impacts of the GFC and changes to Australian immigration policy. There has been a slowing of demand from Chinese study tourists with a corresponding reduction in the number of visitors and visitor nights. In 2012, Chinese students stayed, on average, eight fewer visitor nights in Australia than they did prior to 2009.


Figure 6: Study tourists from China

3

6

9

12

15

18

20

40

60

80

100

120

2006 2007 2008 2009 2010 2011 2012

million nights

'000 people

visitor nights (RHS)

visitors (LHS)


The data in Table 4 provide an indication of how the study tourism markets from China compare with Australia’s five most significant international education source markets. From these data, we can see that the size of the formal study market from China is significantly larger than the other markets. The data also reveal that the Chinese market had the highest average expenditures and the second highest length of stay (behind Korea). Malaysia had the largest number of visitors engaged in informal study, but overall, Korean and Indian students stayed longer and spent more on average than either the Malaysian or Chinese markets.


Table 4: Study tourists average length of stay and expenditure by main source markets, 2012

Formal study tourist Informal study tourist

Country Visitors Average Average Visitors Average Average

nights Expenditure ($) nights Expenditure ($)China^ 90 895 165 21 062 5 341 23 2 234

Malaysia^ 20 927 153 18 537 6 515 19 4 540

Japan 19 467 118 11 077 8 489 52 4 316

Singapore^ 19 330 128 20 703 4 236 23 4 375

USA^ 17 798 90 9 936 4 652 51 3 586

Korea 16 554 171 19 263 4 316 157 13 351

New Zealand^ 14 964 42 4 982 5 694 28 3 792

Indonesia^ 14 585 130 16 945 2 604 27 2 601

Hong Kong^ 13 509 159 17 894 2 309 74 6 796

India^ 12 654 161 15 397 1 796 122 7 839

All Int’l 358 641 142 16 107 72 036 61 5 327


Note: Vietnam not included in this table due to small sample size in the IVS.

Figure 7 provides a breakdown in expenditures for formal and informal study tourists from China. We can see that for formal study tourists, more than half of their investment was focused on education fees (46 per cent) and accommodations (16 per cent). For the informal study tourists, this represented only 15 per cent of their expenditures, with package tours representing the largest expenditure item (27 per cent) followed by airfares (21 per cent). However, as indicated above caution should be exercised as some of the sample sizes were small. Interestingly, the relative cost of education for the formal study segment has increased by 2 per cent since 2006, resulting in a commensurate reduction in shopping expenditures.


Figure 7: Chinese study tourist expenditure breakdown

6

21 11

23 16

6 12

15

12 8 11

14

3

16 10

5 46

9 23

12

0

27 16

10

10

20

30

40

50

60

70

80

90

100

Formal study Informal study All China All international %

Organised tours Domestic airfares

International airfares * Rental vehicles

Petrol and oil costs Taxi and local public transport

Long distance public transport Food, drink & accommodation

Accommodation * Food and drink *

Shopping to use in Aust Shopping to take home *

Gambling Entertainment

Motor vehicles Education fee *

Phone, fax & postage Other expenditure

Business events registration fees Package tour *


One of the challenges for the tourism market in general, and the China study tourism market in particular, relates to the limited dispersal of visitors. Figure 8 shows the dominant states and territories in terms of visitation were New South Wales, Victoria, and Queensland. In line with the TRA dispersal definition, Table 5 shows the percentage of each market that visited regions in Australia other than the capital cities, Gold Coast and Tropical North Queensland.

This pattern of visitation was consistent with the more general Chinese and international markets and seems to support the argument for limited dispersal. This argument is further


supported by IVS data on the regions visited, with the capital cities of Sydney, Melbourne, and Brisbane accounting for more than 65 per cent of visits. Other regions favoured by study tourists were the Gold Coast, Adelaide, Tropical North Queensland, Perth, and Canberra (in rank order). From Table 5, we see that only 14 per cent of formal study tourists and 25 per cent of informal study tourists’ excursion outside of the major metropolitan centres, with only 8 per cent of Chinese formal study tourists choosing a to study in a regional area.

Figure 8: Study tourist visitation by state

20

40

60

80

100

NSW VIC QLD SA WA TAS NT ACT %

Formal study Informal study All China All international

Source: Tourism Research Australia, 2013 (Unpublished Data)

Table 5: Percentage of Chinese study tourists and nights spent in regional Australia

Visitors Nights

Formal study 14% 7%

Informal study^ 25% 19%

All China 9% 7%

All International 27% 18%

Source: Tourism Research Australia, 2013 (Unpublished Data). ^ Small sample size for this data - interpret with caution. Note: Regional Australia excludes all capital cities, the Gold Coast and Tropical North Queensland.

Study tourists were also not particularly different from the typical Chinese or international traveller in terms of their activity preferences (see Figure 9), with social activities (28 per cent) the most popular followed by outdoor/nature activities (22 per cent) and local attractions (19 per cent). The informal study tourists were more interested in outdoor/nature activities (27 per cent) than either formal study tourists or the more general travellers.


Figure 9: Activities undertaken by study tourists

22

27

24

22

19

23

21

21

28

23

27

29

20 40 60 80 100

Formal study

Informal study

All China

All international

%

Outdoor / Nature * Active outdoor / sports Arts / Heritage

Indigenous culture activities Local attractions * Social / Other * Other activities


Figure 10 shows the proportion of study tourists that were either very satisfied or satisfied with a range of key factors associated with their trip. From these data, we can see that with the exception of visitor information centres (91 per cent) and customer service (81 per cent), formal study tourists were generally less satisfied with most aspects of their travel experience than either travellers from China or general international travellers. Informal study tourists were more satisfied in most dimensions. Telecommunications services were the most disappointing aspect for both formal (45 per cent) and informal study (44 per cent) tourists respectively.


Figure 10: Satisfaction of Chinese study tourists

20

40

60

80

100

Hotels/m

otels

Non hotel

Ground tr

ansp

ort

Air tran

sport

Shopping

Restauran

t/cafe

Value fo

r money

Visitor in

formati

on centre

s

Teleco

mm

unicatio

ns

Custom

er servi

ce

%

All Int'l Formal study Informal study All China

Source: Tourism Research Australia, 2013 (Unpublished Data). Note: data relates to proportion of respondents that indicated that they were satisfied or very satisfied.

Indirect impactsIn this section we provide a more detailed analysis of the indirect impacts associated with the Chinese study visitor market. Figure 11 shows that, when compared to Figure 6, there has been far more volatility in the study visitor market than the study tourism market. While there was a spike in 2010, this trend has flattened in the past 12 months as the Chinese economy has slowed, most notably in the reduction of visitor nights-to-visitor ratio in 2011–12.

Figure 11: Study visitors from China

5

10

15

20

25

200

400

600

800

1000

2006 2007 2008 2009 2010 2011 2012

'000 people

'000 nights

visitors (RHS)

visitor nights (LHS)



Compared to Australia’s five major international education markets, China had the greatest number of study visitors. While the Korean market does not have the volume of the Chinese markets, Koreans stayed longer and spent more on average than Chinese visitors. Another way to consider the study visitor market is in terms of flow-on impact to the study tourism market. From Table 6, we can see that there was, on average, 0.25 visitors per international student over the last 12 months, adding the equivalent of an additional 8 nights and $1115 per student. Data from the overseas student supplement to the IVS also reveals that 22 per cent of Chinese students will be visited during their course of study, contributing to an average of 5 visitors for every student.

Table 6: Flow-on impact of study visitors

Study Visitors Flow-on Impact

Country VisitorsAverage

nightsAverage

expenditure ($)Visitors per

student

Additional nights per

student

Additional expenditure per

student ($)China 23 153 31 4 379 0.25 8 1 115

Malaysia 14 614 16 5 025 0.7 11 3 509

Singapore 11 728 11 4 059 0.6 7 2 445

Indonesia 9 884 14 3 826 0.51 7 1 956

Hong Kong 6 206 11 2 452 0.35 4 855

Korea 5 604 47 4 637 0.34 16 1 570

Japan^ 5 467 7 1 359 0.37 3 497

USA^ 4 288 15 3 967 0.29 4 1 166

New Zealand^ 3 830 7 819 0.28 2 232

India^ 1 315 44 2 669 0.1 5 277

All Int’l 115 861 21 3 769 0.32 7 1 218

Source: Tourism Research Australia, 2013 (Unpublished Data). ^ Small sample size for this data - interpret with caution.

International airfares (20 per cent) were the main expenditure item for the study visitor market, followed by education fees (14 per cent), souvenirs (13 per cent), and food/drink (13 per cent). The high expenditures on education in Figure 12 could suggest that many parents were using their trip to settle their students’ financial affairs. In general, however, the breakdown in expenditures for study visitors was comparable to general visitation from China with one noticeable exception. The study visitor market was far less reliant on packaged travel, suggesting that their international study hosts had some degree of comfort in acting as a tour guide for their visitors.


Figure 12: Study visitor expenditure breakdown

20

11

23

12

12

15

13

11

14

13

10

5

14

23

12

1

16 10

10

20

30

40

50

60

70

80

90

100

Study visitor All China All international

%

Organised tours Domestic airfares

International airfares * Rental vehicles

Petrol and oil costs Taxi and local public transport

Long distance public transport Food, drink & accommodation

Accommodation * Food and drink *

Shopping to use in Aust Shopping to take home *

Gambling Entertainment

Motor vehicles Education fee *

Phone, fax & postage Other expenditure

Business events registration fees Package tour *

Source: Tourism Research Australia, 2013 (Unpublished Data) . Percentages relate to asterisk items in legend.


The travel patterns by state for study visitors from China was also reflective of the more general trends (see Figure 13), with only 10 per cent of visitors choosing to stay in cities beyond Australia’s major metropolitan centres (see Table 7). The strength of the Australian Capital Territory was most likely a reflection of the reputation of the Australian National University in Canberra as one of the country’s leading higher education providers. Another possible explanation of the limited dispersal for study visitors could relate to visa category, with ADS visas being particularly restrictive. And while the travel patterns of study visitors are consistent with ADS tourists, there was insufficient data to investigate this issue further.

Figure 13: Education stopover by State and territory for study visitors

10

20

30

40

50

60

70

80

NSW VIC QLD SA WA TAS NT ACT %

Study visitor All China All international

Source: Tourism Research Australia, 2013 (Unpublished Data). Note: Tasmania and NT are based on small sample sizes and data should be interpreted with caution.

Table 7: Percentage of Chinese study visitors and nights spent in regional Australia

Visitors Nights

Student visitors^ 10% 10%

All China 9% 7%

All International 27% 18%

Source: Tourism Research Australia, 2013 (Unpublished Data). ^ Small sample size for this data - interpret with caution. Note: Regional Australia excludes all capital cities, the Gold Coast and Tropical North Queensland

Notwithstanding the importance of outdoor/nature activities (25 per cent), which was consistent with the general brand positioning of Australia, the study visitors prioritised social activities (31 per cent) with their host international students (see Figure 14). The preference for social activities is also consistent with the accepted practice for friends and family to travel to host countries to participate in graduation-related activities. In all other respects, the activity preferences of study visitors were consistent with Chinese and international visitors.


Figure 14: Activities undertaken by study visitors

25

24

22

24

21

21

31

27

29

10 20 30 40 50 60 70 80 90 100

Study visitor

All China

All international

%

Outdoor / Nature * Active outdoor / sports Arts / Heritage

Indigenous culture activities Local attractions * Social / Other *

Other activities


Study visitors were far more satisfied with their travel experiences than study tourists and general Chinese travellers (see Figure 15). Study visitors were most satisfied with visitor information centres (99 per cent) followed by customer service (92 per cent). The one noticeable exception was satisfaction with telecommunications (46 per cent) which was considerably lower than the Chinese (51 per cent) and international (66 per cent) averages.

Figure 15: Satisfaction of Chinese study visitors

20

40

60

80

100

Hotels/m

otels

Non hotel

Ground tr

ansp

ort

Air tran

sport

Shopping

Restauran

t/cafe

Value fo

r money

Visitor in

formati

on

Teleco

mm

unicatio

ns

Custom

er servi

ce

%

All Int'l Study visitors All China

Source: Tourism Research Australia, 2013 (Unpublished Data). Note: data relates to proportion of respondents that indicated that they were satisfied or very satisfied.


Unlocking the alumni potential

Australia has a long history of educating Chinese students, and the relationship built during these formative years, it is argued, has the potential to provide future benefit to Australia’s tourism industry. Many graduates claim a deep-seeded desire to return to Australia at a later date. A large number of alumni also assume the role of brand ambassador upon return to China, sharing stories about their Australian experiences and encouraging friends and family to make Australia their destination of choice for education and travel.

This box presents the key findings of a survey of 1154 Chinese alumni of Australian universities. The survey was undertaken by Victoria University in partnership with the Central University of Finance and Economics in China and the Australia-China Alumni Association. Respondents included alumni in Beijing, Hangzhou, Shanghai, Hong Kong, and Hunan, with an equal mix of men and women. The majority were aged 35 years or younger (69 per cent) and were drawn from the fields of management, economics, and commerce. These qualifications were gained at 21 Australian education institutions.

Do Alumni travel back to Australia?• 64 per cent of respondents have travelled back to Australia in the last five years, with the majority

having travelled twice or more frequently. A large group (18 per cent) travelled back more than five times.

• Almost all (93 per cent) report that they intend to travel to Australia, with 21 per cent intending to travel within the next five years. During their most recent trip to Australia, the majority (53 per cent) travelled alone.

What do alumni do in Australia? • The average length of stay in Australia for alumni was more than two weeks, with 38 per cent

staying for more than four weeks. Very few alumni (16 per cent) have visited anywhere outside of the main Australian cities. The most popular cities were Sydney (85 per cent), Melbourne (83 per cent), Brisbane (58 per cent), and Canberra (51 per cent).

• The main forms of transport used in Australia were public transport (78 per cent), private transport with family and friends (56 per cent), air travel (45 per cent), and hired cars (45 per cent). Only 15 per cent stated that they travelled on packaged tours.

• Alumni combined many activities when returning to Australia, including going to the beach (72 per cent), shopping for pleasure (69 per cent), and, visiting friends and relatives (68 per cent). A large proportion was also involved in a business or professional activity (31 per cent) or an educational activity (43 per cent).

• The majority reported that they stayed with friends or family (72 per cent), with an average trip expenditure of around $2000 (14 per cent of respondents spent more than $10 000).


Why do alumni travel? • The findings show multiple reasons for return travel. For a large number, the main purpose is for

vacation and to go to places that they had not seen while studying in Australia. Most alumni, however, combine a number of activities. They come to visit friends and relatives, undertake further education or professional activities, conduct business, or to engage in a range of leisure activities such as shopping for pleasure and going to the beach.

• The majority of alumni enjoy Australia and appreciate it for its clean environment, natural beauty, and relaxed lifestyle. A clear theme in the comments was in relation to ‘friendly people’ and feeling comfortable because Australia is accepting of different cultures.

• Alumni value their Australian friendships very highly, and 80 per cent say that their friends in Australia are important or very important. They communicate often and a key reason for returning to Australia was to visit friends and family (68 per cent). A theme in the responses was visiting Australia ‘...is like a homecoming.’

What influence do alumni have?• Alumni influence others through word-of-mouth promotion of Australian education and tourism,

receiving visitors from Australia and through return travel. For example, the large majority (70 per cent) have or intend to recommend Australia as a place to study.

• Alumni maintain friendships and contacts in Australia and approximately 50 per cent said that they communicate via email, Skype, and other social media ‘more than several times a month.’ When travelling back to Australia, approximately 48 per cent travel with family members or friends.

• While studying in Australia, almost 50 per cent received visitors from China. The majority (74 per cent) also returned to China for a visit. A majority (60 per cent) have also played host to visitors from Australia and have ‘helped them out.’

Source: Pyke et al. (2013). The role and influence of China based Australian alumni on travel and tourism, Victoria University: Melbourne.

Concluding remarksThe review explores study tourism from China. The symbiotic relationship between tourism and international education suggests an opportunity for greater collaboration in order to maintain, and potentially increase, Australia’s relative share of China’s tertiary education market.

The analysis reveals that study tourists, particularly formal study tourists, stayed longer and spent more on average than other international travel segments. Our findings also indicate that the increased cost of Australian education has moderated demand and reduced expenditures on discretionary items such as leisure activities and souvenirs. The results indicate a limited regional dispersal of Chinese students beyond the major capital cities and a limited range of activities undertaken by students engaged in formal and informal study. The satisfaction data highlight a number of areas for improvement, particularly for formal study tourists, who were generally less satisfied than typical Chinese travellers across most areas of their trip, with particular concerns relating to telecommunications and value for money.

The results have implications for both industry and government. For instance, an opportunity exists for the tourism industry to respond with new products that encourage dispersal beyond the capital cities and to increase the breadth of activities and experiences of Chinese students. Consideration should also be given to the existing preference for socially-oriented activities,


with targeted products and related marketing highlighting the experiential and social opportunities for Chinese students and their family and friends.

There is an opportunity for greater collaboration between the tourism and education sectors. Tourism Australia and destination marketing organisations have demonstrated expertise in packaging the non-educational aspects of the Australian experience. This is a valuable resource that could benefit international education agents. One immediate opportunity exists around collaboration for the marketing and packaging of graduation-specific tourism product.

ReferencesABS (2013). International trade in goods and services (Cat. 5368.0), Australian Bureau of Statistics: Canberra, Australia.

AEI (2012a). Export income to Australia from international education activity in 2011–12, Australian Education International: Canberra, Australia.

AEI (2012b). International student enrolment data, Australian Education International: Canberra, Australia.

BCG (2013). Australia’s international education industry: Analysis of strategic trends, Boston Consulting Group: Boston, MA.

Bourke, A. (2000). A model of the determinants of international trade in higher education, The Service Industries Journal, 20:1, 110–138.

Briggs, S. (2006). An exploratory study of the factors influencing undergraduate student choice: The case of higher education in Scotland, Studies in Higher Education, 31:6, 705–722.

Chen, C-H. and Zimitat, C. (2006). Understanding Taiwanese students’ decision-making factors regarding Australian international higher education, International Journal of Educational Management , 20:2, 91–100.

Cubillo, J., Joaquı́ n Sa´nchez, J. and Cervin˜o, J. (2006). International students’ decision-making process, International Journal of Educational Management , 20:2, 101–115.

Davidson, M., Wilkins, H., King, B., Hobson, P., Craig-Smith, S. and Gardiner, S. (2010). International education visitation: Tourism opportunities, Sustainable Tourism CRC: Gold Coast, Australia.

Eusébio, C. and Carneiro, M. (2012). Determinants of tourist–host interactions: An analysis of the university student market, Journal of Quality Assurance in Hospitality & Tourism, 13:2, 123–151.

IEAC (2013). Australia – Educating globally, International Education Advisory Council: Canberra, Australia.


Kemp, S., Madden, G. and Simpson, M. (1998). Emerging Australian education markets: A discrete choice model of Taiwanese and Indonesian student intended study destination, Education Economics, 6:2, 159–169.

Mazzarol, T. and Soutar, G. (2002). Push-pull factors influencing international student destination choice, International Journal of Educational Management, 16:2, 82–90.

Pyke, J., Smith, E., Jiang, M., Li, G., Li, A. and DeLacy, T. (2013). The role and influence of China based Australian alumni on travel and tourism, Victoria University: Melbourne, Australia.

Shanka, T., Quintal, V. and Taylor, R. (2006). Factors influencing international students’ choice of an education destination: A correspondence analysis, Journal of Marketing for Higher Education, 15:2, 31–46.

TRA (2013). International visitor survey database, Tourism Research Australia: Canberra, Australia.

——(2012). Tourism industry facts & figures: At a glance, Tourism Research Australia: Canberra, Australia.

——(2006). Study tourism report: Profile of international visitors who studied in Australia, Tourism Research Australia: Canberra, Australia.

UNESCO (2012). Opportunities lost: The impact of grade repetition and early school leaving (Global Education Digest), United Nations Education, Scientific and Cultural Organisation: Montreal, Canada.

Wang, Y. and Davidson, M. (2008). Chinese student travel market to Australia: An exploratory assessment of destination perceptions, International Journal of Hospitality & Tourism Administration, 9:4, 405–426.


China ReviewStatistical tables

and figures


Statistical tables and figuresEconomic IndicatorsChina GDP in 2000 US$

1000

2000

3000

4000

1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011

2000 US$b/person

Source: World Bank World Development Indicators 2012.

China GDP per capita

500

1000

1500

2000

2500

3000

1961 1966 1971 1976 1981 1986 1991 1996 2001 2006 2011

2000 US$/ person

Source: World Bank World Development Indicators 2012.


Output per worker in selected countries

20

40

60

80

100

120

Cambodia

Viet Nam

India

Indonesia

Philippines

China

Thailan

d

Malaysi

a

Korea, Republic

of

Japan

Australi

a

Singap

ore

2012 US$'000

1992 2002 2012

Source: The Conference Board Total Economy Database™, January 2013, http://www.conference-board.org/data/economydatabase/

Population composition of China

20 000

40 000

60 000

80 000

100 000

120 000

140 000

160 000

1982

1987

1990

1995

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

‘0 000

aged 0–14 aged 15–64 aged 65 and over

Source: NBS China Statistical Yearbook 2012.


China’s major export destinations

Hong Kong

Hong Kong

Japan

Japan

Korea

Korea

Australia

Australia

European Union (27)

European Union (27)

United States

United States

100

200

300

400

500

600

2001 2011 2001 2011 2001 2011

Asia Europe N. America

US$b

Source: World Trade Organization 2012.

China’s energy production and consumption

500

1000

1500

2000

2500

3000

2011 1981 1984 1987 1990 1993 1996 1999 2002 2005 2008

kgce

Production Consumption

Source: NBS China Energy Statistical Yearbook 2012.


China commoditiesSteel balance

-100

100

200

300

400

500

600

700

800

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

Mt

Production Consumption Net imports

Source: World Steel Association 2012.

Iron ore balance

100

200

300

400

500

600

700

800

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

Mt


Source: UNCTAD 2012.


Metallurgical coal balance

-100

100

200

300

400

500

600 19

79

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

Mt


Source: IEA 2013.

Thermal coal balance

-500

500

1000

1500

2000

2500

3000

3500

1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

2007

2009

2011

Mt


Source: IEA 2013.


Australian tradeShare of exports destined for China, by volume

10

20

30

40

50

60

70

80

1989–90

1991–92

1993–94

1995–96

1997–98

1999–00

2001–02

2003–04

2005–06

2007–08

2009–10

2011–12 %

iron ore

thermal coal

metallurgical coal

Source: BREE

10

20

30

40

50

60

70

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 %

Aluminium

zinc

lead

copper

Source: BREE


Part I: Chinese trends: economic and social indicatorsTable 1: Gross domestic product, billion Yuan (current price), billion US$ (2000 prices), 1978–2011

Year

Gross domestic product

yuan

Primary1 industry

yuan

Secondary2 industry

yuanIndustry

yuanConstruction

yuan

Tertiary3 industry

yuan


2000 US$1978 365 103 175 161 14 87 158

1979 406 127 191 177 14 88 170

1980 455 137 219 200 20 98 183

1981 489 156 226 205 21 108 192

1982 532 178 238 216 22 116 210

1983 596 198 265 238 27 134 233

1984 721 232 311 279 32 179 268

1985 902 256 387 345 42 259 304

1986 1 028 279 449 397 53 299 331

1987 1 206 323 525 459 67 357 370

1988 1 504 387 659 578 81 459 411

1989 1 699 427 728 648 79 545 428

1990 1 867 506 772 686 86 589 445

1991 2 178 534 910 809 102 734 486

1992 2 692 587 1 170 1 028 142 936 554

1993 3 533 696 1 645 1 419 227 1 192 632

1994 4 820 957 2 245 1 948 296 1 618 715

1995 6 079 1 214 2 868 2 495 373 1 998 793

1996 7 118 1 402 3 383 2 945 439 2 333 872

1997 7 897 1 444 3 754 3 292 462 2 699 953

1998 8 440 1 482 3 900 3 402 499 3 058 1 028

1999 8 968 1 477 4 103 3 586 517 3 387 1 106

2000 9 921 1 494 4 556 4 003 552 3 871 1 198

2001 10 966 1 578 4 951 4 358 593 4 436 1 298

2002 12 033 1 654 5 390 4 743 647 4 990 1 416

2003 13 582 1 738 6 244 5 495 749 5 600 1 558

2004 15 988 2 141 7 390 6 521 869 6 456 1 715

2005 18 494 2 242 8 760 7 723 1 037 7 492 1 909

2006 21 631 2 404 10 372 9 131 1 241 8 855 2 151

2007 26 581 2 863 12 583 11 053 1 530 11 135 2 457

2008 31 405 3 370 14 900 13 026 1 874 13 134 2 693

2009 34 090 3 523 15 764 13 524 2 240 14 804 2 940


Year


yuan

Primary1 industry

yuan

Secondary2 industry

yuanIndustry

yuanConstruction

yuan

Tertiary3 industry

yuan


2000 US$2010 40 151 4 053 18 738 16 072 2 666 17 360 3 246

2011 47 288 4 749 22 041 18 847 3 194 20 498 3 548

Sources: NBS China Statistical Yearbook 2012, World Bank World Development Indicators 2013.

Note: In China, economic activities are categorised into three industry strata.

1 Primary industry refers to agriculture, forestry, animal husbandry and fishery, and services in support of these industries.

2 Secondary industry refers to mining and quarrying; manufacturing; the production and supply of electricity, water and gas; and construction. 3 Tertiary industry refers to all economic activities not included in primary or secondary industries.


Table 2: Gross domestic product composition (per cent), 1978–2011

Year Primary Secondary1 Tertiary

industry industry Industry2 Construction industry

1978 28 48 44 4 24

1979 31 47 44 4 22

1980 30 48 44 4 22

1981 32 46 42 4 22

1982 33 45 41 4 22

1983 33 44 40 5 22

1984 32 43 39 4 25

1985 28 43 38 5 29

1986 27 44 39 5 29

1987 27 44 38 6 30

1988 26 44 38 5 31

1989 25 43 38 5 32

1990 27 41 37 5 32

1991 25 42 37 5 34

1992 22 44 38 5 35

1993 20 47 40 6 34

1994 20 47 40 6 34

1995 20 47 41 6 33

1996 20 48 41 6 33

1997 18 48 42 6 34

1998 18 46 40 6 36

1999 17 46 40 6 38

2000 15 46 40 6 39

2001 14 45 40 5 41

2002 14 45 39 5 42

2003 13 46 41 6 41

2004 13 46 41 5 40

2005 12 47 42 6 41

2006 11 48 42 6 41

2007 11 47 42 6 42

2008 11 47 42 6 42

2009 10 46 40 7 43

2010 10 47 40 7 43

2011 10 47 40 7 43


1 Secondary industry is the sum of the industry and construction categories.

2 Industry refers to mining and quarrying; manufacturing; the production and supply of electricity, water and gas.


Table 3: Reference exchange rate of Renminbi (period average), RMB1 Yuan, 1981–2011

Year US$100 ¥100 HK$100 € 1001981 171 1 30 n.a.

1982 189 1 31 n.a.

1983 198 1 27 n.a.

1984 233 1 30 n.a.

1985 294 1 38 n.a.

1986 345 2 44 n.a.

1987 372 3 48 n.a.

1988 372 3 48 n.a.

1989 377 3 48 n.a.

1990 478 3 61 n.a.

1991 532 4 68 n.a.

1992 551 4 71 n.a.

1993 576 5 74 n.a.

1994 862 8 112 n.a.

1995 835 9 108 n.a.

1996 831 8 108 n.a.

1997 829 7 107 n.a.

1998 828 6 107 n.a.

1999 828 7 107 n.a.

2000 828 8 106 n.a.

2001 828 7 106 n.a.

2002 828 7 106 801

2003 828 7 106 936

2004 828 8 106 1029

2005 819 7 105 1020

2006 797 7 103 1002

2007 760 6 97 1042

2008 695 7 89 1022

2009 683 7 88 953

2010 677 8 87 897

2011 646 8 83 900


1 The Renminbi (RMB) is the official currency of China. The primary unit of the RMB is the Yuan.


Table 4: Fixed-base price indices (1990=100), 1990–2011

Consumer Price Urban Rural Retail Price

Year Index Household Household Index

1995 100 100 100 100

1996 108 109 108 106

1997 111 112 111 107

1998 110 111 110 104

1999 109 110 108 101

2000 109 111 108 100

2001 110 112 109 99

2002 109 111 108 97

2003 111 112 110 97

2004 115 115 115 100

2005 117 117 118 101

2006 119 119 119 102

2007 124 124 126 106

2008 132 131 134 112

2009 131 130 134 111

2010 135 134 138 114

2011 142 141 146 120



Table 5: Total value of imports and exports (US billion), 1978–20111

Year Imports Total Total Balance2

and exports exports imports1978 21 10 11 - 1

1980 38 18 20 - 2

1985 70 27 42 - 15

1990 115 62 53 9

1991 136 72 64 8

1992 166 85 81 4

1993 196 92 104 - 12

1994 237 121 116 5

1995 281 149 132 17

1996 290 151 139 12

1997 325 183 142 40

1998 324 184 140 43

1999 361 195 166 29

2000 474 249 225 24

2001 510 266 244 23

2002 621 326 295 30

2003 851 438 413 25

2004 1 155 593 561 32

2005 1 422 762 660 102

2006 1 760 969 791 178

2007 2 177 1 220 956 264

2008 2 563 1 431 1 133 298

2009 2 208 1 202 1 006 196

2010 2 974 1 578 1 396 182

2011 3 642 1 898 1 743 155


1 Data in 1978 were from the Ministry of Foreign Trade; and data since 1980 are from Customs statistics.

2 A negative balance indicates trade deficit. That is, imports surpassing exports.


Table 6: Sources of funds for investments (billion Yuan), 1981–2011

Year State1 Domestic2 Foreign3 Self-raised4,5 Total

budget loans investment funds and others1981 27 12 4 53 96

1982 28 18 6 71 123

1983 34 18 7 85 143

1984 42 26 7 108 183

1985 41 51 9 153 254

1986 46 66 14 187 312

1987 50 87 18 224 379

1988 43 98 28 297 465

1989 37 76 29 299 441

1990 39 89 28 295 452

1991 38 131 32 358 559

1992 35 221 47 505 808

1993 48 307 95 856 1 307

1994 53 400 177 1 153 1 783

1995 62 420 230 1 341 2 052

1996 63 457 275 1 541 2 336

1997 70 478 268 1 710 2 526

1998 120 554 262 1 936 2 872

1999 185 573 201 2 017 2 975

2000 211 673 170 2 258 3 3112001 255 724 173 2 647 3 799

2002 316 886 209 3 094 4 505

2003 269 1 204 260 4 128 5 862

2004 325 1 379 329 5 424 7 456

2005 415 1 632 398 7 014 9 459

2006 467 1 959 433 9 036 11 896

2007 586 2 304 513 11 677 15 080

2008 795 2 644 531 14 320 18 292

2009 1 269 3 930 462 19 362 25 023

2010 1 301 4 402 470 22 404 28 578

2011 1 484 4 634 506 27 973 34 598


1 Funds from the state budget consist of budgetary appropriation and loans.

2 ‘Domestic loans’ refers to loans of various forms from banks and non-bank financial institution during the reference period for the purpose of investment in fixed assets.

3 ‘Foreign investment’ refers to overseas funds received during the reference period for the construction and purchase of investment in fixed assets (covering equipment, materials and technology.

4 ‘Self-raised funds’ refers to extra-budgetary funds for investment in fixed assets received during the reference period by investing units from central government ministries, local governments, enterprises and institutions.

5 ‘Others’ refers to funds for investment in fixed assets received from sources other than those listed above, including capital raised by enterprises or financial institutions, funds raised from individuals and through donation, and funds transferred from other units.


Table 7: Composition of investment funds (per cent), 1981–2011

Year State Domestic Foreign Self-raisedbudget loans investment funds and others

1981 28 13 4 55

1982 23 14 5 58

1983 24 12 5 59

1984 23 14 4 59

1985 16 20 4 60

1986 15 21 4 60

1987 13 23 5 59

1988 9 21 6 64

1989 8 17 7 68

1990 9 20 6 65

1991 7 24 6 64

1992 4 27 6 62

1993 4 23 7 66

1994 3 22 10 65

1995 3 20 11 65

1996 3 20 12 66

1997 3 19 11 68

1998 4 19 9 67

1999 6 19 7 68

2000 6 20 5 68

2001 7 19 5 70

2002 7 20 5 69

2003 5 21 4 70

2004 4 18 4 73

2005 4 17 4 74

2006 4 16 4 76

2007 4 15 3 77

2008 4 14 3 78

2009 5 16 2 77

2010 5 15 2 78

2011 4 13 1 81



Table 8: Foreign capital investment utilised1 (US$ billion), 1979–2011

Year Total Foreign loans Direct foreign investments

Other foreign investments2

1979–1984 18 13 4 1

1985 5 3 2 0

1986 8 5 2 0

1987 8 6 2 0

1988 10 6 3 1

1989 10 6 3 0

1990 10 7 3 0

1991 12 7 4 0

1992 19 8 11 0

1993 39 11 28 0

1994 43 9 34 0

1995 48 10 38 0

1996 55 13 42 0

1997 64 12 45 7

1998 59 11 45 2

1999 53 10 40 2

2000 59 10 41 9

2001 50 0 47 3

2002 55 0 53 2

2003 56 0 54 3

2004 64 0 61 3

2005 64 0 60 3

2006 67 0 63 4

2007 78 0 75 4

2008 95 0 92 3

2009 92 0 90 2

2010 109 0 106 3

2011 118 0 116 2


1 Utilisation of foreign capital refers to remittance, equipment and technology financed from abroad by loans, foreign direct investment and other measures undertaken by Chinese governments at all levels, by various departments, enterprises and other economic units.

2 ‘Other foreign investments’ refers to all forms of foreign capital other than foreign borrowings and foreign direct investment. It includes the total value of shares in foreign currencies issued by enterprises at domestic or foreign stock exchanges; rent payable for equipment through international leasing arrangements; and the cost of imported equipment, technology and materials provided by foreign counterparts in compensation trade and in processing and assembly trade.


Table 9: Employment, total and composition by industry, 1978–2011

Year Total Employed Primary Secondary TertiaryPersons industry industry industry('0000) (%) (%) (%)

1978 40 152 71 17 12

1979 41 024 70 18 13

1980 42 361 69 18 13

1981 43 725 68 18 14

1982 45 295 68 18 14

1983 46 436 67 19 14

1984 48 197 64 20 16

1985 49 873 62 21 17

1986 51 282 61 22 17

1987 52 783 60 22 18

1988 54 334 59 22 18

1989 55 329 60 22 18

1990 64 749 60 21 19

1991 65 491 60 21 19

1992 66 152 59 22 20

1993 66 808 56 22 21

1994 67 455 54 23 23

1995 68 065 52 23 25

1996 68 950 51 24 26

1997 69 820 50 24 26

1998 70 637 50 24 27

1999 71 394 50 23 27

2000 72 085 50 23 28

2001 72 797 50 22 28

2002 73 280 50 21 29

2003 73 736 49 22 29

2004 74 264 47 23 31

2005 74 647 45 24 31

2006 74 978 43 25 32

2007 75 321 41 27 32

2008 75 564 40 27 33

2009 75 828 38 28 34

2010 76 105 37 29 35

2011 76 420 35 30 36



Table 10: Population and age composition, 1982–2011

YearTotal

population Population Population Population

(year-end) aged 0–14 Proportionaged

15–64 Proportionaged 65 and

over Proportion('0000) ('0000) (%) ('0000) (%) ('0000) (%)

1982 101 654 34 146 34 62 517 62 4 991 5

1987 109 300 31 347 29 71 985 66 5 968 5

1990 114 333 31 659 28 76 306 67 6 368 6

1995 121 121 32 218 27 81 393 67 7 510 6

1996 122 389 32 311 26 82 245 67 7 833 6

1997 123 626 32 093 26 83 448 68 8 085 7

1998 124 761 32 064 26 84 338 68 8 359 7

1999 125 786 31 950 25 85 157 68 8 679 7

2000 126 743 29 012 23 88 910 70 8 821 7

2001 127 627 28 716 23 89 849 70 9 062 7

2002 128 453 28 774 22 90 302 70 9 377 7

2003 129 227 28 559 22 90 976 70 9 692 8

2004 129 988 27 947 22 92 184 71 9 857 8

2005 130 756 26 504 20 94 197 72 10 055 8

2006 131 448 25 961 20 95 068 72 10 419 8

2007 132 129 25 660 19 95 833 73 10 636 8

2008 132 802 25 166 19 96 680 73 10 956 8

2009 133 450 24 659 19 97 484 73 11 307 9

2010 134 091 22 259 17 99 938 75 11 894 9

2011 134 735 22 164 17 100 283 74 12 288 9



Table 11: Dependency ratio, 1982–2011

Year Gross1 Children (0–14)2 Old (65 and over)3

dependency dependency dependencyratio ratio ratio

(%) (%) (%)1982 63 55 8

1987 52 44 8

1990 50 42 8

1995 49 40 9

1996 49 39 10

1997 48 39 10

1998 48 38 10

1999 48 38 10

2000 43 33 10

2001 42 32 10

2002 42 32 10

2003 42 31 11

2004 41 30 11

2005 39 28 11

2006 38 27 11

2007 38 27 11

2008 37 26 11

2009 37 25 12

2010 34 22 12

2011 34 22 12


1 ‘Gross dependency ratio’ refers to the ratio of the non-working age population (aged 0–14 and 65+) to the working-age population (aged 15–64), expressed as a percentage.

2 ‘Children dependency ratio’ refers to the ratio of the child population to the working-age population, expressed as a percentage.

3 ‘Old dependency ratio’ refers to the ratio of the elderly population to the working-age population, expressed as a percentage.


Table 12: Per capita annual income and Engel’s coefficient of urban and rural households, 1978–2011

Year

Annual disposable income of urban

households (yuan) Index

Annual net income1 of rural

households (yuan) Index

Engel's2 coefficient

of urban households (%)

Engel's coefficient

of rural households (%)

1978 343 100 134 100 58 68

1980 478 127 191 139 57 62

1985 739 160 398 269 53 58

1990 1 510 198 686 311 54 59

1991 1 701 212 709 317 54 58

1992 2 027 233 784 336 53 58

1993 2 577 255 922 347 50 58

1994 3 496 277 1 221 364 50 59

1995 4 283 290 1 578 384 50 59

1996 4 839 302 1 926 418 49 56

1997 5 160 312 2 090 437 47 55

1998 5 425 330 2 162 456 45 53

1999 5 854 361 2 210 474 42 53

2000 6 280 384 2 253 483 39 49

2001 6 860 416 2 366 504 38 48

2002 7 703 472 2 476 528 38 46

2003 8 472 515 2 622 551 37 46

2004 9 422 554 2 936 588 38 47

2005 10 493 607 3 255 625 37 46

2006 11 760 671 3 587 671 36 43

2007 13 786 753 4 140 734 36 43

2008 15 781 816 4 761 793 38 44

2009 17 175 895 5 153 861 37 41

2010 19 109 965 5 919 954 36 41

2011 21 810 1 046 6 977 1 063 36 40


1 Net income refers to the total income of households from all sources minus all corresponding expenses. It is mainly used as input for reinvestment in production and as consumption expenditure for the year, and also for savings and non-compulsory expenses of various forms.

2 Engel’s coefficient refers to the percentage of household expenditures on food as a proportion of total living expenses.


Part II: Chinese trends: resources and energy activitiesTable 13: Total energy production and composition, 1978–2011

Year

Total energy production (million

tons of SCE)1 Coal (%)Crude oil

(%)Natural gas

(%)Hydropower, nuclear

power, wind power (%)1978 628 70 24 3 3

1980 637 69 24 3 4

1985 855 73 21 2 4

1990 1039 74 19 2 5

1991 1048 74 19 2 5

1992 1073 74 19 2 5

1993 1111 74 19 2 5

1994 1187 75 18 2 6

1995 1290 75 17 2 6

1996 1330 75 17 2 6

1997 1335 74 17 2 7

1998 1298 73 18 2 7

1999 1319 74 17 3 6

2000 1350 73 17 3 7

2001 1439 73 16 3 8

2002 1507 74 16 3 8

2003 1719 76 14 3 7

2004 1966 77 13 3 7

2005 2162 78 12 3 7

2006 2322 78 11 3 8

2007 2473 78 11 4 8

2008 2606 77 11 4 9

2009 2746 77 10 4 9

2010 2969 77 10 4 9

2011 3180 78 9 4 9


1 The coefficient for converting electric power into SCE (standard coal equivalent) is calculated on the basis of average coal consumption in generating electric power.


Table 14: Total energy consumption and composition, 1978–2011

Year Total energy consumption (million

tons of SCE)1

Coal (%) Crude oil (%)

Natural gas (%)

Hydropower, nuclear power, wind power (%)

1978 571 71 23 3 3

1980 603 72 21 3 4

1985 767 76 17 2 5

1990 987 76 17 2 5

1991 1,038 76 17 2 5

1992 1,092 76 18 2 5

1993 1,160 75 18 2 5

1994 1,227 75 17 2 6

1995 1,312 75 18 2 6

1996 1,352 74 19 2 6

1997 1,359 71 20 2 6

1998 1,362 71 21 2 7

1999 1,406 71 22 2 6

2000 1,455 69 22 2 6

2001 1,504 68 22 2 8

2002 1,594 68 22 2 7

2003 1,838 70 21 3 7

2004 2,135 70 21 3 7

2005 2,360 71 20 3 7

2006 2,587 71 19 3 7

2007 2,805 71 19 3 7

2008 2,914 70 18 4 8

2009 3,066 70 18 4 8

2010 3,249 68 19 4 9

2011 3,480 68 19 5 8


1 The coefficient for converting electric power into SCE (standard coal equivalent) is calculated on the basis of average coal consumption in generating electric power.


Table 15: Energy production and consumption per capita1, 1980–2011

Year Production ConsumptionTotal energy Raw coal Crude oil Electricity Total energy Coal Oil Electricity

(kgce) (kg) (kg) (kWh) (kgce) (kg) (kg) (kWh)1980 650 632 108 306 614 622 89 306

1981 636 625 102 311 598 610 94 311

1982 662 661 101 325 615 636 81 325

1983 696 698 104 343 645 671 82 344

1984 751 761 111 364 684 723 83 364

1985 814 830 119 391 730 776 87 392

1986 826 838 123 421 758 806 91 422

1987 842 856 124 459 799 856 95 460

1988 870 889 124 495 844 902 101 496

1989 909 942 123 523 867 925 104 524

1990 915 951 122 547 869 930 101 549

1991 911 945 123 589 902 960 108 591

1992 921 958 122 647 937 979 115 651

1993 942 976 123 711 984 1026 125 715

1994 996 1040 123 779 1030 1078 125 777

1995 1071 1129 125 836 1089 1143 133 832

1996 1093 1147 129 887 1110 1150 145 884

1997 1085 1128 131 923 1105 1120 157 917

1998 1045 1073 130 939 1097 1087 160 934

1999 1053 1089 128 989 1122 1112 168 982

2000 1070 1096 129 1074 1153 1117 178 1067

2001 1131 1157 129 1164 1183 1136 180 1158

2002 1177 1211 130 1292 1245 1189 194 1286

2003 1334 1424 132 1483 1427 1402 211 1477

2004 1517 1638 136 1700 1647 1601 245 1695

2005 1658 1802 139 1918 1810 1778 250 1913

2006 1771 1929 141 2181 1973 1946 266 2181

2007 1876 2042 141 2482 2128 2070 278 2482

2008 1967 2115 144 2608 2200 2122 282 2608

2009 2063 2233 142 2782 2303 2222 288 2782

2010 2220 2418 152 3145 2429 2334 323 3135

2011 2366 2616 151 3506 2589 2551 338 3497


1 This table is calculated by annual average population.


Table 16: Residential energy consumption per capita, 1980–2011

Year Total average Coal Electricity LPG Natural gas Gas Urban Rural

(kgce) (kg) (kWh) (kg) (m3) (m3) (kgce) (kgce)1980 112 118 11 0 0 1 332 60

1981 101 122 12 0 0 1 290 55

1982 102 124 12 0 0 1 281 56

1983 107 128 13 1 0 1 283 59

1984 113 135 15 1 0 2 288 63

1985 127 149 21 1 0 1 307 72

1986 127 148 23 1 1 1 306 71

1987 132 152 26 1 1 2 300 76

1988 141 159 31 1 1 2 307 84

1989 139 152 35 1 2 2 297 84

1990 139 147 42 1 2 3 298 83

1991 139 143 47 2 2 3 292 83

1992 134 127 55 2 2 4 267 85

1993 133 123 63 3 1 5 258 86

1994 129 109 73 3 2 6 238 86

1995 131 112 83 4 2 5 242 86

1996 121 83 88 6 2 6 238 71

1997 119 77 99 6 2 9 226 71

1998 119 73 104 7 2 10 218 71

1999 122 70 109 7 2 9 213 75

2000 124 67 115 7 3 10 210 76

2001 127 66 127 7 3 9 207 80

2002 134 66 138 8 4 10 210 87

2003 153 70 160 9 4 10 232 102

2004 176 75 184 10 5 11 256 119

2005 194 77 221 10 6 11 279 132

2006 212 77 256 11 8 13 298 145

2007 234 74 308 12 11 20 320 163

2008 241 69 332 11 13 20 319 173

2009 254 69 366 11 13 23 325 190

2010 258 68 383 11 17 26 315 204

2011 278 69 418 12 20 11 327 228



Table 17: Imports of major energy products, 1991–2011

Year Coal Coke

Crude

oil

Gasoline

Diesel

oil

Kerosene Fuel

oil LPG

Other petroleum

products Natural

gas

Electricity

(104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (108 cu.m) (108 kWh)

1991 137 0 597 11 320 3 126 12 0 31

1992 123 0 1 136 33 501 16 169 2 11 0 50

1993 143 0 1 567 218 940 54 456 68 71 0 45

1994 121 0 235 105 624 27 398 97 139 0 18

1995 164 0 3 401 16 612 76 659 233 96 0 6

1996 322 0 2 262 8 465 66 943 355 107 0 1

1997 201 0 3 547 8 743 138 1 371 358 176 0 1

1998 159 0 2 732 1 311 129 1 627 477 191 0 0

1999 167 0 3 661 0 31 211 1 757 322 208 0 4

2000 212 0 7 027 0 26 255 1 480 482 161 0 15

2001 249 0 6 026 0 27 202 1 824 489 201 0 18

2002 1 081 0 6 941 0 48 215 1 660 626 384 0 23

2003 1 110 0 9 102 0 85 210 2 395 637 432 0 30

2004 1 861 1 12 272 0 275 282 3 059 641 384 0 34

2005 2 617 1 12 682 0 53 328 2 609 617 443 0 50

2006 3 811 0 14 517 6 71 561 2 799 536 443 10 54

2007 5 102 0 16 317 23 162 524 2 417 405 689 40 43

2008 4 034 0 17 889 199 624 648 2 186 259 666 46 38

2009 12 584 16 20 365 4 184 612 2 407 408 1 153 76 60

2010 16 310 11 23 768 0 180 487 2 299 327 1 731 165 56

2011 18 210 12 25 378 3 233 618 2 684 350 1 648 312 66



Table 18: Exports of major energy products, 1991–2011

Year

Coal Coke1

Crude

Oil

Gasoline Diesel

oil

Kerosene Fuel

oil LPG

Other petroleum

products

Natural

gas

Electricity

(104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (104 tn) (108 cu.m) (108 kWh)

1991 2 000 108 2 260 250 121 32 70 1 149 - 3

1992 1 966 135 2 151 270 148 18 63 1 66 - -

1993 1 981 261 1 943 185 129 7 32 1 108 - 1

1994 2 419 404 1 849 210 122 11 6 1 89 - 39

1995 2 862 886 1 823 186 131 37 28 7 131 - 60

1996 3 648 769 2 040 131 157 74 37 33 117 - 37

1997 3 073 1 058 1 983 178 232 72 52 39 156 - 72

1998 3 230 1 146 1 560 182 98 92 57 50 203 - 72

1999 3 744 997 717 414 60 125 25 8 221 - 91

2000 5 505 1 520 1 031 455 55 199 33 2 280 - 99

2001 9 012 1 385 755 572 26 182 44 2 325 - 102

2002 8 384 1 357 766 612 124 170 64 6 246 97

2003 9 403 1 472 813 754 224 202 76 2 262 103

2004 8 666 1 501 549 541 64 205 182 3 361 24 95

2005 7 172 1 276 807 560 148 269 230 3 473 30 112

2006 6 327 1 447 634 351 78 371 258 15 473 29 123

2007 5 317 1 530 389 464 66 448 380 34 416 26 146

2008 4 543 1 221 424 203 63 536 732 68 419 32 166

2009 2 240 54 507 492 451 594 862 85 305 32 174

2010 1 910 335 303 517 464 605 990 93 386 40 191

2011 1 466 330 252 406 202 653 1227 119 459 32 193


1 Includes semi-coke.


Table 19: Crude steel production, consumption, exports and imports, China vs rest of world (RoW), 1978–2011

Year Production Consumption1 Exports ImportsChina RoW China RoW China RoW China RoW

(Mt) (Mt) (Mt) (Mt) (Mt) (Mt) (Mt) (Mt)1978 32 685 40 677 0 139 9 131

1979 34 712 43 706 0 143 8 137

1980 37 678 42 675 0 140 5 137

1981 36 671 38 668 1 142 3 138

1982 37 608 40 606 1 134 4 132

1983 40 623 49 611 0 145 10 133

1984 43 667 57 653 0 159 13 145

1985 47 672 66 646 0 171 20 144

1986 52 662 69 642 0 162 17 142

1987 56 679 68 662 0 162 12 144

1988 59 721 67 710 1 170 9 160

1989 62 724 69 717 1 170 8 163

1990 66 704 68 698 3 168 4 163

1991 71 663 70 654 4 173 4 165

1992 81 639 85 619 4 192 8 172

1993 90 638 125 595 1 221 37 178

1994 93 632 116 605 3 236 26 208

1995 95 657 99 643 11 236 15 222

1996 101 649 111 625 7 238 16 215

1997 109 690 114 667 9 259 13 236

1998 115 663 122 642 5 264 13 243

1999 124 665 136 638 6 275 17 249

2000 129 720 138 704 11 295 21 278

2001 152 699 170 674 7 293 26 267

2002 182 722 206 704 7 312 29 284

2003 222 748 259 714 8 324 43 289

2004 273 788 287 773 20 346 33 329

2005 356 791 362 773 27 344 27 336

2006 421 828 393 844 52 366 19 391

2007 490 857 436 883 66 379 17 411

2008 512 829 465 855 56 380 16 410

2009 577 659 574 645 24 303 22 306

2010 639 793 612 788 42 347 17 364

2011 684 834 650 835 48 366 16 381

Source: Steel Statistical Yearbook 2012.

1 Crude steel equivalent.


Table 20: Iron ore production, consumption, exports and imports, China vs rest of world (RoW), 1978–2011

Year Production Consumption Exports ImportsChina RoW China RoW China RoW China RoW

(Mt) (Mt) (Mt) (Mt) (Mt) (Mt) (Mt) (Mt)1978 55 773 62 757 0 350 6 334

1979 56 828 62 814 0 397 6 383

1980 53 804 59 789 0 384 6 368

1981 49 788 51 764 0 372 2 349

1982 50 707 54 693 0 328 3 314

1983 53 664 57 641 0 314 4 291

1984 57 756 63 732 0 372 6 348

1985 65 778 75 755 0 376 10 353

1986 67 778 81 748 0 370 14 340

1987 72 778 84 749 0 368 12 339

1988 73 812 83 785 0 401 10 373

1989 76 830 89 795 0 424 13 389

1990 84 806 99 782 0 395 14 371

1991 82 767 101 733 0 397 19 364

1992 92 717 117 699 0 364 25 347

1993 111 706 144 667 0 396 33 357

1994 113 724 150 686 0 422 37 383

1995 124 773 165 724 0 459 41 409

1996 119 769 163 722 0 444 44 397

1997 125 798 181 742 0 482 55 426

1998 116 790 168 735 0 463 52 408

1999 111 773 167 713 0 446 55 387

2000 105 854 175 779 0 507 70 432

2001 102 832 194 729 0 504 92 401

2002 109 881 220 753 0 544 111 416

2003 208 956 356 794 0 595 148 432

2004 204 1040 412 841 0 648 208 449

2005 266 1113 541 843 0 719 275 448

2006 328 1221 654 899 0 767 326 445

2007 369 1303 752 927 0 829 383 453

2008 301 1394 745 956 0 890 444 452

2009 223 1345 852 697 0 961 630 314

2010 315 1521 934 876 0 1071 619 427

2011 322 1578 1009 880 0 1123 687 425

Source: UNCTAD 2012.


Table 21: Thermal coal production, consumption, exports and imports, China vs rest of world (RoW), 1978–2011


(Mt) (Mt) (Mt) (Mt) (Mt) (Mt) (Mt) (Mt)1978 565 1 538 565 1 543 3 84 2 84

1979 581 1 629 579 1 609 4 97 2 102

1980 552 1 706 559 1 681 5 114 2 114

1981 561 1 709 565 1 711 5 123 2 122

1982 604 1 791 599 1 755 5 124 4 130

1983 648 1 782 637 1 809 4 126 6 128

1984 717 1 847 703 1 857 5 148 7 150

1985 735 1 917 747 1 950 5 174 8 170

1986 754 1 977 777 1 959 7 176 8 174

1987 783 2 028 833 2 037 10 169 10 173

1988 829 2 040 896 2 074 12 183 11 185

1989 895 2 042 906 2 060 12 185 12 189

1990 920 1 964 979 1 975 14 281 11 312

1991 926 1 941 954 1 991 16 273 11 311

1992 949 1 932 989 1 951 20 262 11 295

1993 985 1 861 1 050 1 953 16 237 13 267

1994 1 065 1 920 1 117 1 971 19 235 10 279

1995 1 145 1 950 1 185 1 978 22 278 11 303

1996 1 198 1 977 1 261 2 046 29 294 10 314

1997 1 154 2 027 1 196 2 060 31 317 7 344

1998 1 124 2 054 1 164 2 050 27 340 9 357

1999 1 064 2 052 1 117 2 087 32 337 8 370

2000 1 055 2 076 1 101 2 199 49 384 8 434

2001 1 090 2 207 1 081 2 247 79 400 10 481

2002 1 195 2 188 1 186 2 268 71 410 20 485

2003 1 422 2 242 1 439 2 341 81 456 19 529

2004 1 642 2 352 1 672 2 457 81 488 22 562

2005 1 786 2 463 1 827 2 518 66 543 30 578

2006 1 880 2 606 1 977 2 583 59 630 45 625

2007 1 974 2 646 2 085 2 664 51 658 57 653

2008 2 230 2 715 2 307 2 712 42 654 45 671

2009 2 347 2 695 2 515 2 555 22 695 109 619

2010 2 537 2 727 2 630 2 692 18 771 139 663

2011 2 895 2 818 N.A. N.A. 11 851 165 706

Source: IEA database 2013.


Table 22: Metallurgical coal production, consumption, exports and imports, China vs rest of world (RoW), 1978–2011


(Mt) (Mt) (Mt) (Mt) (Mt) (Mt) (Mt) (Mt)1978 52.6 469.2 52.3 469.3 0.3 120.4 0.0 114.0

1979 54.4 504.1 53.7 496.4 0.7 140.1 0.0 133.8

1980 68.2 492.7 66.8 491.2 1.4 142.4 0.0 141.6

1981 60.6 488.3 59.1 483.9 1.5 147.7 0.0 142.8

1982 62.6 477.5 60.8 472.4 1.8 145.1 0.0 141.9

1983 66.2 455.2 63.9 452.1 2.3 142.9 0.0 136.3

1984 72.0 468.6 69.6 458.6 2.4 164.4 0.0 157.2

1985 68.4 471.6 62.9 469.7 2.5 169.4 0.2 166.8

1986 69.9 475.4 67.2 468.6 3.0 164.4 0.5 159.1

1987 72.8 477.5 70.1 464.9 3.6 171.5 0.2 164.0

1988 75.3 492.5 73.2 478.6 3.2 188.8 0.1 178.6

1989 81.3 489.9 77.4 477.2 2.9 189.9 0.3 177.2

1990 85.7 513.9 80.4 474.9 3.5 206.2 0.3 170.9

1991 87.2 472.8 83.7 439.1 3.8 198.7 0.4 168.7

1992 89.5 450.8 85.3 414.9 3.7 199.6 0.4 165.9

1993 96.6 421.8 91.8 402.0 4.3 181.2 0.0 163.7

1994 103.7 396.9 99.1 387.5 4.9 190.6 0.0 174.0

1995 147.8 398.7 140.5 394.3 6.7 188.4 0.0 179.6

1996 132.0 384.5 122.9 381.4 7.5 186.0 0.0 181.2

1997 135.4 390.9 130.1 378.6 4.6 192.4 0.4 183.0

1998 131.6 364.9 126.6 367.6 4.9 179.6 0.1 177.0

1999 123.0 358.6 118.8 360.5 5.2 173.9 0.3 168.2

2000 123.7 354.0 119.8 355.6 6.5 180.5 0.3 178.0

2001 128.8 347.2 118.8 337.0 11.4 183.6 0.3 171.4

2002 148.8 335.2 136.5 342.6 13.3 169.1 0.3 175.1

2003 165.8 343.7 154.2 346.4 13.1 172.4 2.6 173.5

2004 225.7 359.3 225.3 361.4 5.8 184.0 6.8 191.3

2005 280.6 364.3 282.4 344.0 5.3 202.1 7.2 186.9

2006 339.0 365.9 339.6 351.0 4.3 197.3 4.7 190.7

2007 379.1 383.4 381.1 362.0 2.5 213.9 6.2 200.9

2008 385.0 386.3 387.5 351.6 3.5 232.5 6.9 201.3

2009 416.5 365.0 438.6 321.3 0.6 210.9 34.4 167.1

2010 459.5 445.0 483.6 352.6 1.2 282.3 34.8 193.3

2011 524.3 463.7 N.A. N.A. 2.9 273.1 38.3 190.6

Source: IEA database 2013.


Part III: Chinese trends: tourism activitiesTable 23: Chinese outbound travel, by destination (‘000 people)

2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

AAGR2 - 10 years

2003–2012

Share of Total

Chinese departures,

2012

World1 13 801 19 445 20 816 23 560 25 605 26 704 27 259 34 453 40 637 47 092 14.6 100.0

Asia 11 158 16 073 17 059 18 929 20 714 21 757 22 454 28 601 32 973 37 727 14.5 80.1

South Asia 68 104 124 166 204 234 243 341 447 495 24.6 1.1

Southeast Asia 1 578 2 654 2 642 3 013 3 476 3 805 3 712 4 831 6 120 7 173 18.3 15.2

Northeast Asia 9 511 13 315 14 294 15 750 17 034 17 718 18 499 23 429 26 406 30 059 13.6 63.8

Oceania 231 318 352 392 452 443 442 557 674 669 12.6 1.4

Europe 1 945 2 460 2 647 3 262 3 261 3 119 2 966 3 493 4 660 5 690 12.7 12.1

Western Europe 1 156 1 497 1 662 2 026 2 160 1 944 1 881 2 348 3 307 4 059 15.0 8.6

Emerging Europe 789 962 985 1 236 1 101 1 175 1 085 1 145 1 353 1 631 8.4 3.5

Americas 274 356 452 549 638 761 778 1 097 1 468 1 981 24.6 4.2

South America 24 36 46 66 69 86 68 75 103 132 20.7 0.3

North America 234 304 388 465 550 653 686 997 1 333 1 811 25.5 3.8

Central America 9 6 7 5 4 7 7 10 12 14 4.5 0.0

Caribbean 7 9 11 12 15 15 17 16 20 24 15.2 0.1

Middle East 71 88 108 161 185 231 210 284 360 416 21.7 0.9

Africa 122 151 198 267 356 393 408 422 503 609 19.6 1.3

Sub-Saharan Africa 88 106 142 190 240 279 273 263 425 491 21.0 1.0

North Africa 34 44 56 77 115 114 135 159 78 118 14.8 0.3

Total out of region (Excludes NE Asia)

4 289 6 130 6 522 7 810 8 571 8 986 8 760 11 025 14 232 17 033 16.6 36.2

Source: Tourism Economics, Tourism Decision metrics 2013.

1 World includes overnight trips only.

2 AAGR – average annual growth rate.


Table 24: Top 20 destinations for Chinese tourists (‘000s)

2012 rank 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012

AAGR1 - 10

years 2003–

2012

Share of China

market, 2012

1 HONG KONG, SAR 5 693 7 794 8 030 8 434 9 093 9 380 9 664 11 678 13 600 15 612 11.9 33.2

2 MACAO, SAR 2 359 3 609 4 104 4 753 5 007 5 237 5 336 6 565 7 550 7 996 14.5 17.0

3 KOREA, REPUBLIC OF

513 627 710 897 1 069 1 168 1 342 1 875 2 185 2 690 20.2 5.7

4 TAIWAN 407 529 627 675 712 736 969 1 703 1 838 2 052 19.7 4.4

5 THAILAND 607 730 777 949 907 827 778 1 122 1 721 1 996 14.1 4.2

6 JAPAN 449 616 653 812 942 1 000 1 006 1 413 1 043 1 517 14.5 3.2

7 UNITED STATES 157 203 270 320 397 493 525 802 1 089 1 510 28.6 3.2

8 FRANCE 324 463 554 805 832 778 740 907 1 044 1 278 16.5 2.7

9 MALAYSIA 351 550 352 439 689 944 1 016 1 130 1 176 1 254 15.2 2.7

10 VIET NAM 74 534 492 354 394 441 356 621 978 1 205 36.3 2.6

11 SINGAPORE 430 682 662 790 844 810 706 905 1 001 1 146 11.5 2.4

12 GERMANY 268 387 418 441 462 421 385 511 933 1 132 17.4 2.4

13 RUSSIAN FEDERATION

647 763 749 702 668 706 627 646 671 767 1.9 1.6

14 INDONESIA 31 40 129 182 269 355 445 511 595 706 41.3 1.5

15 SWITZERLAND 63 83 110 133 146 129 187 286 453 575 28.0 1.2

16 AUSTRALIA 162 230 260 282 327 326 335 415 496 573 15.1 1.2

17 PHILIPPINES 32 40 107 134 158 164 155 187 243 320 29.2 0.7

18 AUSTRIA 141 172 177 177 171 156 155 182 260 320 9.5 0.7

19 CANADA 76 102 117 145 152 160 161 195 244 301 16.5 0.6

20 CAMBODIA 31 46 59 81 118 130 128 178 215 285 28.0 0.6

Source: Tourism Economics, Tourism Decision metrics 2013.



Part IV: Australian trade with ChinaTable 25: Australian exports to China and rest of world (RoW)

YearMineral

Resources1

Merchandised Goods2

Goods and Services3

China RoW China RoW Total1989–90 0.2 23.9 1.2 47.9 104.2

1990–91 0.3 27.9 1.3 51.1 115.9

1991–92 0.5 27.7 1.5 53.6 126.9

1992–93 0.8 29.3 2.3 58.4 136.3

1993–94 0.6 29.5 2.6 62.0 149.2

1994–95 0.7 29.7 3.0 64.1 155.8

1995–96 1.0 33.4 3.8 72.2 171.3

1996–97 1.2 33.0 3.6 75.3 189.9

1997–98 1.5 38.6 3.9 83.9 198.8

1998–99 1.6 37.2 3.9 82.0 202.6

1999–00 2.0 42.0 5.0 92.3 222.4

2000–01 2.8 53.3 6.8 112.7 240.6

2001–02 3.0 52.0 7.8 113.3 238.9

2002–03 3.6 49.4 8.8 106.7 239.4

2003–04 4.5 44.6 9.9 99.1 242.2

2004–05 6.8 57.1 13.0 113.8 250.6

2005–06 11.0 75.6 18.1 134.4 257.3

2006–07 13.2 86.8 22.8 145.3 267.6

2007–08 19.6 92.8 27.0 153.8 277.5

2008–09 33.2 126.4 39.3 191.5 281.6

2009–10 36.8 98.2 46.5 154.2 296.6

2010–11 49.9 121.7 64.9 180.9 297.3

2011–12 64.0 125.8 76.8 187.3 311.3

Sources: BREE, ABS cat no. 5302.0.

1 Not based on balance of payments.

2 FOB value.

3 Chain value.


Table 26: Australian exports of metallurgical coal, thermal coal and iron ore to China and rest of world (RoW)

Year Metallurgical coal1 Thermal coal Iron ore

China RoW China RoW China RoW

(Mt) (Mt) (Mt) (Mt) (Mt) (Mt)1989–90 0.5 42.6 0.0 43.9 5.5 93.0

1990–91 0.3 43.3 0.0 51.5 8.1 96.0

1991–92 0.3 47.4 0.0 58.2 14.6 91.9

1992–93 0.5 50.0 0.1 59.6 15.2 92.4

1993–94 0.5 47.7 0.0 59.1 16.7 97.7

1994–95 0.2 48.2 1.1 61.8 20.4 108.4

1995–96 0.1 49.7 1.4 59.7 23.3 102.9

1996–97 0.3 49.0 1.5 65.6 26.8 110.7

1997–98 0.3 56.7 1.5 77.0 29.9 112.3

1998–99 1.3 54.7 1.7 82.5 24.5 110.7

1999–00 1.4 61.4 0.9 78.1 30.4 119.0

2000–01 0.4 61.5 0.6 87.4 35.5 121.8

2001–02 0.0 65.4 2.9 89.1 39.1 117.0

2002–03 0.7 65.8 4.0 96.0 53.5 128.0

2003–04 3.1 64.5 2.5 104.2 66.1 128.7

2004–05 3.7 77.0 1.7 104.6 99.6 128.8

2005–06 2.2 75.3 4.0 106.8 123.5 115.9

2006–07 2.4 80.4 3.2 108.4 135.3 122.1

2007–08 1.4 82.3 1.5 113.6 167.6 126.7

2008–09 9.8 69.8 8.4 128.0 223.2 100.3

2009–10 15.5 82.2 13.9 121.1 265.6 124.3

2010–11 9.6 82.0 16.7 126.6 279.4 127.5

2011–12 9.8 81.7 28.5 130.0 333.9 136.2

Source: BREE.

1 High quality metallurgical coal.


Table 27: Australian exports of aluminium, copper, lead and zinc to China and rest of world1 (RoW)

Year Aluminium Copper Lead Zinc

China RoW China RoW China RoW China RoW

(Kt) (Kt) (Kt) (Kt) (Kt) (Kt) (Kt) (Kt)1990 2 934 7 226 0 72 0 1 255

1991 5 948 30 182 0 86 0 1 406

1992 25 905 41 230 0 106 0 1 490

1993 14 1 042 0 397 0 118 0 1 413

1994 2 946 52 383 0 88 26 1 359

1995 11 946 121 269 2 80 38 1 315

1996 12 1 056 191 597 19 65 136 1 352

1997 11 1 145 168 812 29 74 114 1 365

1998 5 1 305 317 917 26 205 32 1 523

1999 18 1 363 225 810 35 222 0 1 621

2000 19 1 383 285 730 70 215 9 1 693

2001 20 1 469 453 792 74 230 173 1 757

2002 46 1 480 371 784 42 222 129 1 785

2003 72 1 456 362 1 005 64 199 240 1 665

2004 75 1 458 216 966 83 181 281 1 600

2005 60 1 525 571 1 035 138 193 227 1 665

2006 37 1 581 540 1 019 127 153 238 1 593

2007 29 1 623 412 1 129 67 168 715 1 499

2008 16 1 663 602 1 204 60 162 809 1 437

2009 139 1 535 643 1 158 111 156 1 227 887

2010 40 1 652 564 1 313 166 135 1 047 1 235

2011 65 1 616 628 1 176 93 170 979 1 395

2012 99 1 551 647 1 313 n.a n.a 745 1 629

Source: BREE.

1 Export quantities are based on gross weight of ore and concentrates.


Table 28: Australian merchandise goods imports from top five sources and rest of world, $A billion

Year China US Japan Singapore Germany RoW1989–90 1.2 12.4 9.9 1.2 3.4 23.2

1990–91 1.5 11.5 8.8 1.3 3.1 22.7

1991–92 2.0 11.7 9.3 1.3 3.0 23.7

1992–93 2.6 13.0 11.1 1.5 3.4 28.0

1993–94 3.1 14.0 11.7 1.8 3.8 30.1

1994–95 3.6 16.0 12.8 2.2 4.9 35.0

1995–96 4.0 17.5 10.8 2.6 4.9 37.9

1996–97 4.2 17.6 10.2 2.6 4.6 39.7

1997–98 5.3 19.8 12.7 2.6 5.2 45.0

1998–99 6.1 20.9 13.6 2.9 6.1 48.0

1999–00 7.5 23.1 14.1 4.4 5.8 55.2

2000–01 9.9 22.4 15.4 3.9 6.2 60.6

2001–02 11.3 21.5 15.5 4.0 6.7 60.7

2002–03 13.8 22.5 16.3 4.4 8.0 68.2

2003–04 15.3 19.9 16.1 5.1 8.0 66.5

2004–05 19.8 21.3 17.2 7.2 8.6 75.3

2005–06 23.2 22.8 17.3 10.5 8.7 85.0

2006–07 27.1 24.9 17.4 10.1 9.3 92.0

2007–08 31.0 24.3 19.7 13.7 10.6 103.1

2008–09 37.0 25.3 17.8 13.4 11.1 114.7

2009–10 36.4 21.9 17.8 10.9 10.7 106.0

2010–11 41.1 23.2 16.7 11.4 10.2 111.4

2011–12 43.4 27.5 20.3 14.9 11.2 122.4

Source: ABS cat 5439.0.


Table 29: Chinese tourist numbers and characteristics

2008 2009 2010 2011 20125 year

AAGR1 (%)

VISITORS

Formal education - China 52 851 70 441 84 188 89 962 90 895 14.50

Informal education - China 6 937 4 364 5 764 4 786 5 341 -6.30

Visitors to Students 10 319 11 416 22 137 20 182 23 153 22.40

Total China 338 423 350 807 431 369 512 632 592 169 15.00

Total Visitors to Australia 5 166 843 5 174 744 5 440 894 5 439 255 5 691 791 2.40

VISITOR NIGHTS

Formal education - China 9 354 751 12 168 094 14 318 902 15 167 503 14 979 666 12.50



Total China 16 060 181 19 215 856 23 886 165 25 923 353 27 785 686 14.70

Total Visitors to Australia 166 785 442 177 385 291 186 074 749 194 997 941 206 275 542 5.50

AVERAGE STAY (NIGHTS)

Formal education - China 177 172.7 170.1 168.6 164.8 -1.80

Informal education - China 25.8 28.9 33.4 28.1 23.3 -2.50

Visitors to Students 27.1 21.4 38.7 35.7 31.2 3.50

Total China 47.5 54.8 55.4 50.6 46.9 -0.30

Total Visitors to Australia 32.3 34.3 34.2 35.9 36.2 2.90

TOTAL EXPENDITURE excluding airfare and package ($m)

Formal education - China 972.60 1 294.10 1 570.10 1 803.40 1 914.40 18.40

Informal education - China 23.50 13.20 34.90 35.00 11.90 -15.60

Visitors to Students 21.90 39.80 85.00 74.90 101.40 46.70

Total China 1 592.30 2 024.50 2 421.30 2 811.10 3 147.00 18.60

Total Visitors to Australia 15 933.30 16 789.20 17 343.70 18 189.90 18 876.60 4.30

Average Spend per trip ($)

Formal education - China 18 403 18 372 18 649 20 046 21 062 3.40



Total China 4 705 5 771 5 613 5 484 5 314 3.10

Total Visitors to Australia 3 084 3 244 3 188 3 344 3 316 1.80

Average Spend per night ($)

Formal education - China 104 106 110 119 128 5.30

Informal education - China 131 104 182 260 96 -7.50

Visitors to Students 78 163 99 104 140 15.70

Total China 99 105 101 108 113 3.40

Total Visitors to Australia 96 95 93 93 92 -1.10

Source: TRA.



Table 30: International visitor arrivals, China

Business VFR1 Holiday Other4 Total Total Total Share of

nights inNights

in TITE3 TITE

change nights HMGSA2 HMGSA Total per visitor

'000 '000 '000 '000 '000 (%) million per cent million $ million $

2000–01 39 18 57 23 143 n.a. 4.0 16.7 0.7 1 031 7 189

2001–02 36 19 70 31 172 20.1 5.2 14.9 0.8 1 258 7 300

2002–03 38 19 74 35 177 2.8 7.1 10.6 0.8 1 349 7 614

2003–04 51 24 91 41 217 22.4 9.1 10.4 0.9 1 542 7 109

2004–05 62 28 120 50 274 26.5 10.9 13.9 1.5 1 913 6 970

2005–06 67 34 132 58 292 6.5 11.9 13.7 1.6 1 875 6 414

2006–07 73 40 158 65 338 15.8 15.3 11.7 1.8 2 050 6 058

2007–08 71 46 177 78 375 10.9 15.9 13.0 2.1 2 493 6 645

2008–09 46 52 171 86 358 -4.6 17.7 8.3 1.5 2 901 8 102

2009–10 53 67 165 104 394 10.0 22.5 7.6 1.7 3 112 7 899

2010–11 66 82 226 120 500 26.9 25.8 8.3 2.1 3 610 7 223

2011–12 63 96 290 128 583 16.7 26.9 9.2 2.5 3 853 6 608

2012–13 70 114 351 136 676 15.9 31.0 9.1 2.8 4 487 6 637

2013–14 74 128 393 145 746 10.4 34.2 9.5 3.2 4 845 6 493

2014–15 79 139 420 156 801 7.3 37.2 9.3 3.5 5 228 6 528

2015–16 84 149 440 169 847 5.8 39.6 9.1 3.6 5 526 6 522

2016–17 87 158 458 181 890 5.0 42.7 8.8 3.8 5 925 6 658

2017–18 90 165 473 193 927 4.2 45.0 8.6 3.9 6 228 6 716

2018–19 93 172 489 205 965 4.1 47.5 8.4 4.0 6 553 6 788

2019–20 96 179 505 219 1 005 4.0 49.5 8.3 4.1 6 812 6 781

2020–21 99 186 521 232 1 044 4.0 52.8 8.1 4.3 7 263 6 953

2021–22 102 194 536 247 1 085 3.9 55.5 7.9 4.4 7 631 7 030

Compound annual growth rate (%)

01/02–06/07 14.9 15.8 17.6 16.2 14.5 23.9 -4.8 18.0 10.3 -3.7

06/07–11/12 -2.7 18.8 12.8 14.6 11.5 12.0 -4.7 6.8 13.5 1.8

11/12–16/17 6.6 10.6 9.6 7.2 8.8 9.7 -0.8 8.8 9.0 0.2

16/17–21/22 3.2 4.2 3.2 6.4 4.1 5.4 -2.2 3.1 5.2 1.1

01/02–11/12 5.7 17.3 15.2 15.4 13.0 17.8 -4.7 12.3 11.8 -1.0

11/12–21/22 4.9 7.3 6.4 6.8 6.4 7.5 -1.5 5.9 7.1 0.6

Source: Tourism Forecasting Committee

1 Visiting friends and relatives.

2 Hotels, motels, guesthouses, and serviced apartments.

3 Total Inbound Tourism Expenditure, real, base = Quarter 4 2012.

4 Other refers to education and employment visitors who stay in Australia for one year or less. On average, these visitors spend more and stay longer than the average tourist.

Resources, Energy and Tourism China Review June 2013

Resources, Energy and Tourism China Review

June 2013