Unravelling Modern China

Haico Ebbers

• Publisher: WSPC
• Year: 2019
• eBook ISBN: 9789813200296
• Topic: Economics
• Subtopic: Development Economics
• Index: Economics

This book provides a comprehensive and balanced view of the main transformations that are happening in the Chinese economy today. This view has developed from more than 200 interviews and numerous surveys (based on primary data), in addition to mainstream literature by academia and consultancy companies.

The general view of China is often either black or white. Global markets are generally guided by euphoria or fear. Academia are optimistic or pessimistic about China's longer-term growth potential. People believe or distrust Chinese data. These black and white pictures are, in many cases, easy to communicate (and even proved by anecdotic evidence), but are not correct.

Modern China is not the result of tradeoffs but ambiguities: market-driven AND government-driven, central government AND local government control, increasing brand loyalty AND extreme price sensitivity, fall of consumption as percentage of GDP AND strong increase in consumption, export as an important driver behind longer-term development AND yet hardly visible as a determinant of today's economic growth.

The aim of this book is to help readers understand the often conflicting nature of China, not only from an economic point of view, but also from political and social point of view. In this sense, it tries to give the reader an eclectic picture of China — the country of contradictions.

That is a difficult task because of the linkages between reforms and the fact that there are many preconceived ideas of China, its development and choices. It is interesting to note that the further from China people are, the more negative their views towards China. This book will make clear that this pessimism is overdone. In the longer term, the author is quite positive about China's transformations, believing that the rise of China is here to stay and that this is the major factor of change of this century.

Contents:

• Reliability of Chinese Data
• China's Integration in the World Economy
• Explaining Economic Growth
• The Need to Rebalance the Economy
• The Changing Role of the Government
• Social Impact of the Rebalancing
• The Emergence of the Chinese Middle Class
• The Success of Western Companies in China
• Chinese Companies Abroad

Readership: Readers who are interested to know where the Chinese economy is headed and how China will develop in the long term.China's Development;Rebalancing;Business in China;China's Integration in the World Economy;Middle Income Trap0 Key Features:

• A different (and better) interpretation of the mountain of data and information coming from China
• Linking the uncontrollable external environment in which international companies have to operate in China to their strategic choices
• Giving the newest view on new developments in China such as escaping the middle-income trap, the demographic dividend issue, the emergence of the middle class, the rebalancing towards domestic market away from export and the new relationship between the central government and Chinese companies going abroad

Part I

The Main Economic and Political Choices

In the first part of the book, we discuss the search of the Chinese policymakers for an optimal growth and modernisation strategy. China started to implement the traditional growth model in the early reform period of the late 1970s and early 1980s. The emphasis was on high savings and high investments, combined with government support to state-owned enterprises (SOEs) and keeping wages low. This was complemented by the opening up and the increasing competition after 1992, when the first special economic zones were established for foreign investors. Export was heavily stimulated, and we saw the marketisation of the SOEs.

However, there is an end-date to this type of policy. Severe imbalances became visible in the economy (and society). Think about rising income inequality and environmental degradation. There was a need to achieve “inclusive” growth: a policy that focuses on sharing the benefits of economic development with all inhabitants. Up to 2007, these imbalances could be counteracted by high economic growth, but now there is a sense of urgency. The “new normal” of GDP growth is around 6%, China is ageing, and the efficiency is low in many parts of the economy.

Easy reforms were implemented before 2007, but more was needed. The 11^th five-year plan of 2006 can be seen as the start of deepening structural reforms and modernising the economy: the process of rebalancing that focus on efficiency and innovation. This rebalancing is a search for the optimum combination of market forces and government intervention.

Chapter 1

Interpretation of China’s Data

Myth 1: Chinese data is unreliable and man-made

1.1Introduction

Generally, there are two views about the reliability of Chinese data. The first view is that Chinese data is untrustworthy. When I discuss Chinese issues with colleagues, journalists and politicians, in many cases, they indicate their reservations regarding the data. Probably because they believe China’s government to be secretive, controlling, corrupt and unpredictable in many political matters, they think the (economic) data must also be unreliable. We can argue that this is a specific case of the so-called Halo-effect — the overall impression of a government influences how we feel and think about its behaviour when talking about data. From this view, the whole attitude towards the Chinese government is negative. With respect to Chinese data, we can surmmarise (to quote one of my colleagues): “Whatever the Chinese say, don’t trust their data”.

On the other hand, there are people and institutions that believe most of the economic data is reliable. It is clear from my time spent in China that economic data on growth, consumption and investments is authentic. China’s economic success could not have happened if the government had relied on incorrect data. It also seems almost impossible to me that the party and state can steer the economy with all its transformations by relying on two sets of data — one fake and one genuine. Keeping two sets of data would have created such a complex governance structure that made this unworkable. Within this view, the problems of Chinese data are not the result of manipulating the figures, but the result of the complex way to get the statistics from such a large, fragmented and heterogeneous country. The collection becomes even more problematic if the economic structure is changing as rapidly as we have seen in China.

Despite this more optimistic view about data reliability, it is certainly the case that the Chinese authorities are secretive about the sources and methods of data collection. This makes it difficult for researchers to do independent cross-checks. The in-between view is that we need to accept a certain amount of data unreliability due to a combination of decentralised data-gathering, inconsistent methods and standards across the country, tax evasion by the private sector, and specific manipulation of data by the state, local government and SOEs. Essentially, it is a combination of deliberately publishing fake data and statistical obstacles. This was also mentioned by the International Monetary Fund (IMF).

The IMF noted in its first Financial Stability Assessment Program of China that a “full assessment of these various risks is, however, hampered by serious data gaps and access to confidential data” (IMF, 2011 & Nomura, 2011). It should be clear that many statistical problems are not only related to China, but also common for many developing countries and economies in transition. Getting correct figures “above the table” is also difficult in advanced economies with an extensive and sophisticated data-gathering process; it is particularly so with the service sector. We can argue that official statistics basically underestimate the service sector, even in a mature economy. Companies such as Lenovo, Hewlett Packard, Canon and Toyota are all classified as manufacturing companies. However, they also provide a lot of services and, in many cases, the “service part” in total revenues is even larger than from production. However, total revenues of these companies are counted as “manufacturing production”, not “service production”.

Most discussion is about the actual GDP level and growth, but the unreliability of data also applies to other aspects of economic and social life. Unemployment statistics is said to be underestimating the real unemployment due to problems in capturing the rural areas and the migrant workers in the cities. In addition, there are concerns about manipulating the figures. It is a puzzle how a stable official urban unemployment rate of around 4% between 2008 and 2015 is possible despite the economic crisis worldwide and fall in growth in China itself. Income distribution statistics are also questionable, based on a survey published by the National Bureau of Statistics (NBS), which sampled only 40,000 households, of which rural households were slightly under-represented. The statistics did not capture the very wealthy cohort of the population who did not participate in the survey. Moreover, the survey excluded property income and off-payroll income. In this respect, the migrant workers in the cities are difficult to capture in the statistics. Hence, the reliability of income inequality data is a significant issue.

There are also doubts about the real debt burden in China, particularly debt connected to local governments. National debt is difficult to measure due to financing vehicles (outside the books) of local governments. Moreover, the bad debt burden of the financial sector is uncertain due to “shadow” bank activities and the relationship between banks, government and SOEs. Furthermore, the bad debt is influenced heavily by the definition used. Another data issue relates to foreign direct investments (FDI). China’s outward- and inward-FDI increased spectacularly over the previous decade but the question is whether these flows are “real”. The statistics are heavily distorted arising from the use of Chinese tax heavens and round-tripping through Hong Kong and other tax heavens. An example makes this clear: if a Chinese company invests in the Virgin Islands, but that money is invested back in mainland China to receive preferential treatment given to foreign investors, both FDI outflow and inflow are increasing. The inflow of investments is considered as foreign, but is essentially from a Chinese entity. This round-tripping is strongly distorting the picture on capital flows, as we will see in Chapter 15.

The foregoing makes clear that we have reasons to question Chinese data. In this chapter, I will elaborate on the data issue, with specific focus on GDP. The chapter is structured as follows: Section 1.2 starts with a discussion of the arguments laid down by the cohort of people that do not trust Chinese data. They maintain that the GDP figures are “man-made”. This is followed by Section 1.3 which makes clear that Chinese data on economic growth and GDP are not as bad as may be expected. The essential argument is that we should see China as a tale of two economies. Finally, in Section 1.4, we will understand why, at the end of the day, Chinese data is good enough to be used in this book.

1.2A critical assessment of China’s GDP

There are several reasons why we may distrust GDP-related data. Firstly, China’s Statistical Bureau publishes official quarterly GDP data within weeks of the end of the reporting period, significantly faster than other statistics agencies. This, in itself, is not a problem, but the point is that large adjustments of the data are published afterwards (and in many cases, the adjustments are unexplained). Secondly, China is announcing its growth target beforehand. When a growth target is announced, it is logical to assume that certain man-made adjustments are done to ensure that the target is being reached. Thirdly, local or province officials may systematically exaggerate growth because reaching or overshooting the growth target will enhance their careers and result in faster promotion opportunities in the party, state or local government. Fourthly, economic growth is determined by the level of inflation; calculating inflation in China can be challenging. China’s Statistical Bureau may use the wrong level of inflation and, consequently, report the wrong real economic growth. Finally, the transformation from a production-based towards an expenditure-based method to calculate economic growth takes time and is a complex process.

Fast publication and large revisions afterwards

China is one of the first countries that publishes its GDP data, often within a few weeks after the reporting period has ended. Compared with countries that are smaller and collect data more efficiently, this is very fast. As indicated above, the problem is that large revisions of GDP are implemented afterwards based on the national economic census that takes place every five years. The first national economic census was done in 2005 (over the period 1993–2004) and added 17% to total GDP. It means that China’s GDP in 2004 was 17% higher than previously published. Put differently, real GDP growth in the years 1993–2004 was revised upwards by 0.5%-point per year (Holz, 2013; ECB, 2006). The argument behind this correction was that the data-gathering process was not able to take into account the fast-growing service sector. The second national census was done in early 2010 (over the period 2005–2009) and added another 4.4% to GDP over this five-year period (NBS website). To the western media, this was yet another indication of the unreliability of Chinese data.

Clearly, there is some truth in this for there was hardly any explanation as to why this revision was needed. At the same time, we can argue that there has been progress: although it is still a substantial adjustment over a five-year period, the correction is considerably lower than before. In 2015, we saw in the third national census (over the period 2010–2014) that again GDP was being corrected, now by 3.4% (NBS website). Again, the main argument of this adjustment was that the statistical authorities were not able to capture the structural changes that happened in the economy. For example, getting high-frequency data about e-commerce was a huge obstacle.

Growth target and man-made data

Distrust about the data quality is fuelled by the fact that China is one of the few countries that announces its annual GDP target beforehand. If the targets are announced beforehand, obviously some manipulation may be expected if the data is not in line with this target. That is certainly the case if the credibility of the party and state is at stake. Linked to this is the choice of the government authorities not to give quarterly GDP data. They publish annual data on a quarterly basis; so, the third-quarter performance of this year can be compared to the third-quarter performance of the previous year. We may argue that this creates more scope to “smoothen” growth rates. Another reason why experts are questioning the GDP data is the fact that the amplitude of the business cycle is so much smaller compared with other countries. Growth between 1980 and 2008 was in the range of 9–11%, which is rather remarkable for a huge country in transition. The volatility is considerably lower compared to other Asian emerging markets, and much lower than countries such as Japan and the US.

The reliability issue is also fuelled by the disconnection between GDP growth data and other economic data, such as electricity consumption and freight transport data. Indeed, it is difficult to understand why we see economic growth of 7% between 2010 and 2016 while, at the same time, electricity consumption and freight transport fell during this period. This unease about data has been intensified by the remark of then Premier Li Keqiang in 2007. He was party secretary of Liaoning province. According to him, GDP data is man-made and therefore unreliable (Reuters, 6 December 2010). To get a better picture about the state of the economy, he presented three indicators to make up the so-called Li Keqiang index — electricity consumption, rail cargo volume and bank lending. The Li Keqiang index is much more volatile than the official stable GDP development index and looks more connected to economic upturns and downturns. The Liaoning province incidence renewed scepticism in January 2017. It was obvious that the local officials deliberately inflated the production statistics for the last decade. After this incidence of faking economic data, the NBS investigated other provinces in the north of China and found that the metals and mining production data from provinces such as Hebei, Shanxi, Shaanxi and Inner Mongolia had also been inflated by local authorities.

Other indicators are also used to correct the official GDP growth, such as the floor area under construction and cargo traffic at ports. However, an important flaw when using these indicators is that they are focussing on the manufacturing sector — a sector which is falling in importance. In 2017, the share of manufacturing in GDP fell to 38% (World bank database). To take the more dynamic service sector into consideration, we should look at indicators such as retail sales, passenger car sales, tourism flows and e-commerce volume. These sectors show considerable growth which is in line with GDP growth.

Local versus national GDP figures

In 2014, Xinhua News Agency, the official press agency of the Chinese government, published The Enigma of China’s GDP Statistics. The conclusion of that publication was clear: the translation from local growth figures into nation-GDP is problematic. To the western media, this publication presented a picture of some growth-obsessed local officials who “have cooked the books”. As stated above, local officials are indeed eager to increase output in order to get promoted. Higher province or city GDP growth has been strongly correlated with promotions inside the party and state.

The Chinese media used the Xinhua-publication to explain how difficult data-gathering is in a highly fragmented environment. Many institutions are conducting their own surveys, hence coordination is missing; this may result in double-counting. Another type of double-counting relates to the value...

Table of contents

• Cover
• Halftitle
• Title
• Copyright
• Preface
• Contents
• Overview: Five Words That Characterise China
• Part I: The Main Economic and Political Choices
• Part II: The Main Challenges Ahead
• Part III: China’s Integration in the World Economy
• References
• Index