Trends And Cycles In China’s Macroeconomy – Analysis


China’s spectacular growth over the 2000s has slowed since 2013. The driving force behind the country’s growth was investment, so the key to understanding the slowdown lies in understanding what sustained investment in the past. This column shows how a preferential credit policy promoting heavy industrialisation explains the trends and cycles in China’s macroeconomy over the past two decades. This policy was not without negative consequences, particularly in terms of the distortions it introduced for business finance. Going forward, China needs to focus on creating the right incentives for banks to make loans to small productive businesses.

By Chun Chang, Kaiji Chen, Daniel Waggoner and Tao Zha*

Growth has been the hallmark of China. In recent years, however, China’s GDP growth has slowed down considerably while countercyclical government policy has taken centre stage. Never has this change been truer than after the 2008 Global Crisis, when the government injected RMB4 trillion into investment to combat the sharp fall of output growth. Issues related to both the trend and cycle are now on the minds of policymakers and economists.

The key issue for China today is the slowdown of GDP growth since 2013 (e.g. Economist 2009, Wildau et al. 2009).  What causes such a growth slowdown?  The data indicate that much of the slowdown comes from a slowdown of investment, which has been the driving force of China’s growth since 1997. To understand why investment in China has recently slowed, we must understand what has sustained investment growth in the past.

Explaining China’s growth

Song et al. (2011) explain China’s spectacular growth trend in the 2000s.  They construct a model economy with heterogeneous firms that differ in both productivity and access to the credit market to explain the observed coexistence of sustained returns to capital and growing foreign surpluses in China for most of the 2000s. Their model replicates the observed disinvestment of state-owned enterprises (SOEs) in the labour-intensive sector as private-owned enterprises (POEs) accumulate capital in the same sector.  In this two-sector model, they characterise two transition stages. In the first stage, both SOEs and POEs coexist in the labour-intensive sector, while capital-intensive goods are produced exclusively by SOEs. In the second stage, SOEs disappear from the labour-intensive sector and POEs become the sole producers in that productive sector.  Song et al. (2011) present a persuasive story about resource reallocations between SOEs and POEs within the productive labour-intensive sector, which is identified as the source of total factor productivity (TFP) growth since the late 1990s.

Although discussions about SOEs versus POEs have dominated the literature on China, the SOE-POE classification does not help explain the rising investment rate, the decline of labour income share, or the weak or negative cyclical co-movement between investment and consumption or between investment and labour income.  Figure 1 displays the recent trend patterns in China – investment as a share of GDP has steadily increased, while household consumption as a share of GDP and the labour income (as well as household disposable income) as a share of total value added have steadily declined.

Figure 1. China’s trend patterns in the last two decadeswaggoner-fig1-newAgainst a backdrop of these unbalanced trends is a stark picture of a structural break of the correlation between investment and consumption.  As shown in Figure 2, the strong positive correlation between investment and household consumption breaks down in the late 1990s, whether it is measured by annual growth rates or HP-filtered series.

Figure 2. Time series of correlations with the 10-year moving window.

Notes: The left-column graph represents the correlation of annual growth rates. The right-column graph reports the correlation of HP-filtered log annual values. ‘C’ stands for household consumption; ‘GFCF’ stands for gross fixed capital formation, which measures investment.
Notes: The left-column graph represents the correlation of annual growth rates. The right-column graph reports the correlation of HP-filtered log annual values. ‘C’ stands for household consumption; ‘GFCF’ stands for gross fixed capital formation, which measures investment.

According to Acemoglu and Guerrieri (2008), Fernald and Neiman (2011), and Chang and Hornstein (2015), a combination of two conditions may explain a rising investment rate and a declining share of labour income – the TFP in heavy industries must grow faster than in light industries, and the relative price of investment goods must decline.  For the Chinese economy, there is no evidence in support of these two conditions. In fact, since the late 1990s, the deepening of capital, not TFP growth, has become the major source of GDP growth in China.

Buera and Shin (2013) study the investment boom experienced by other fast growing economies (e.g. Korea, Taiwan, and Singapore).  In those economies, resources gradually move from unproductive firms to productive firms, so that the saving (investment) rate increases during the reallocation phase.  At the same time, the labour income share increased or remained stable during the investment boom period.  China is different. Much of the investment boom was at the cost of labour income growth and consumption growth.  Therefore, unless much of the investment income is channelled to households for their labour inputs, the investment boom is unsustainable in the long run.

Resource allocations

To address China’s key macroeconomic issues in one coherent and tractable framework, in a recent paper (Chun et al. 2015) we take a different perspective by shifting the emphasis to resource reallocations between the heavy and light sectors. The striking facts about both trends and cycles in China indicate that something fundamental has changed since the late 1990s. We argue that these changes began in March 1996, when the Eighth National People’s Congress passed a historic long-term plan to adjust the industrial structure for the next 15 years in favour of strengthening heavy industries.   Since March 1996, the government has been actively promoting so-called ‘heavy industries,’ which are largely composed of big, capital-intensive industries such as infrastructure, real estate, basic industries (metal products, autos, and high-tech machinery), and other heavy industries (petroleum and telecommunication). The promotion has been supported by medium- and long-term bank loans giving priority to the heavy sector. The other, more labour-intensive industries, or ‘light industries’, do not receive the same preferential treatment. Our approach is to build a two-sector model with a special emphasis on resource and credit reallocations between the heavy and light sectors and by introducing two new institutional ingredients into the model – a collateral constraint on producers in the heavy sector and a lending friction in the banking sector. With these new ingredients, the model can replicate both the trend patterns and the cyclical patterns displayed in Figures 1 and 2.

Problems with preferential policy

Our central policy message is that the spectacular economic growth in China is not an unalloyed progress as it begets the debt problem faced by the nation today.   We argue that preferential credit policy for promoting heavy industries accounts for the unusual cyclical patterns as well as the post-1990s economic transition represented by the persistently rising investment rate, the declining labour income share, and a growing foreign surplus.

Such a preferential policy, however, distorts business finance and entails negative consequences. Under the central government’s strategic plan of promoting heavy industries, local governments have made implicit guarantees of long-term bank loans to heavy industries, most of which are capital-intensive large firms and are less productive than the vibrant small businesses.  This is what we call ‘green banking.’ The result is fast growth, but the growth is unbalanced and at the cost of low consumption and low labour income.

The easy credit policy for promoting heavy industries crowds out short-term loans to productive small firms.  As a result, short-term loans are priced too high because they are not guaranteed by the government.  We call this short-term lending ‘yellow banking.’  Indeed, the Chinese data supports this crowding-out effect implied by the model.  Figure 3 shows that new medium-term and long-term loans move negatively with new short-term bank loans.  The average correlation between the two types of loans is -0.4.  This negative correlation is most conspicuous right after the 2008 financial crisis, when the government injected massive credits into medium- and long-term investment projects with a spike of new long-term loans to blunt the impact of the severe recession on the Chinese economy, while new short-term loans were left unchanged.  When this prodigious government credit expansion ceased in 2010, new short-term loans began to rise.

Figure 3. New bank loans to non-financial enterprises as a percent of GDP.

Note: The correlation between the two types of loans is -0.403 for 1992-2012 and -0.405 for 2000-2012.
Note: The correlation between the two types of loans is -0.403 for 1992-2012 and -0.405 for 2000-2012.

Going forward

Financial reforms in China should focus on ‘green banking’.  Only when the practice of green banking is properly reformed will commercial banks have incentives to make loans to small and productive businesses.  The stakes cannot be higher. The Eighteenth National People’s Congress, when discussing various policy goals in 2012, explicitly expressed concerns about low consumption growth and low labour share of income in China. In addition, a rapid ramping-up of China’s corporate debts and local government debts as a result of the preferential credit policy toward heavy industries has now reached a level that deems unsustainable.  Thus, China’s macroeconomy faces twin problems: (a) low consumption and income growth; and (b) overcapacity of heavy industries with rising debt risks.  How these problems are resolved might have profound policy implications.  Because both problems have stemmed from a preferential credit policy for promoting heavy industrialisation since the late 1990s, an effective policy would aim at reducing the preferential credit access given to large firms and especially those in heavy industries.   In short, financial reforms geared towards eliminating such a distortion would go a long way toward making both short-term and long-term loans function efficiently and put the economy on a more balanced path.

*About the authors:
Kaiji Chen
, Assistant Professor of Economics, Emory University

Daniel Waggoner, Research economist and policy adviser, Federal Reserve Bank of Atlanta

Tao Zha, Samuel Candler Dobbs Professor of Economics, Emory University; Executive Director of the Center for Quantitative Economic Research, Federal Reserve Bank of Atlanta

Acemoglu, D and V Guerrieri (2008) “Capital deepening and nonbalanced economic growth”, Journal of Political Economy, 116: 467–498.

Buera F J and Y Shin (2013) “Financial frictions and the persistence of history: A quantitative exploration”, Journal of Political Economy, 121: 221–272.

Chang, Y and A Hornstein (2015) “Transition dynamics in the neoclassical growth model: The case of South Korea,” The B.E. Journal of Macroeconomics, Forthcoming.

Chang, C, K Chen, D Waggoner, and T Zha (2015) “Trends and cycles in China’s macroeconomy,” 30th NBER Macroeconomics Annual, Forthcoming.

Fernald, J and B Neiman (2011) “Growth accounting with misallocation: Or, doing less with more in Singapore”, American Economic Journal: Macroeconomics, 3: 29–74.

Song, Z, K Storesletten, and F Zilibotti (2011) “Growing like China”, American Economic Review, 101: 196–233.

The Economist (2012) “Prudence without a purpose”, The Economist, 26 May.

Wildau, G, T Mitchell and J Anderlini (2009) “China growth lowest since 2009 as property and manufacturing drag”, Financial Times, 15 April. was a policy portal set up by the Centre for Economic Policy Research ( in conjunction with a consortium of national sites. Vox aims to promote research-based policy analysis and commentary by leading scholars. New content can be found at

Leave a Reply

Your email address will not be published. Required fields are marked *