Since 2000, China’s debt in terms of debt to GDP ratio has grown up to 280-290% (approximately), which exceeds the debt levels of highly-indebted developed countries, including the US (269%) and Germany (258%), and emerging countries like Brazil (160%) and India (135%). Over the last three decades, under China’s infrastructure-led public investment boom, the total aggregate debt has grown from $2.1 trillion to $28.2 trillion, which is greater than the combined GDP of the US, Germany and Japan over the same period.
While mainstream macroeconomics literature tends to largely focus on the government proportion of total debt, it is also important to note that other constituents like corporate debt, financial debt and household debt (in the Chinese context) tend to matter more in gauging a country’s overall indebtedness. In the Chinese case, government debt (marked at 55% of the GDP) remains low as compared to the other three constituents. Corporate debt and financial debt levels are marked at 125% and 65% of China’s GDP. But which economic factor has elicited such a vast volume of debt in China?
In a recent analysis on China’s public infrastructure-led investment model by some Oxford-based economists, it is shown how lower-quality, high cost ridden public infrastructure investments across China triggered a massive volume of overall debt, bringing the Chinese economy to the cliff of a national debt crisis.
On observing the investment and debt figures closely, one finds that the growth in China’s absolute debt is almost in equal proportion with the total capital investment; which between 2000 and 2014 was cumulatively $29.1 trillion. Scholars Steven Barnett and Ray Brooks support this further through their study, highlighting that the majority of investments China has made since 2000 remain debt-fuelled.
China’s Gross Fixed Capital Formation (blue bars) vs China’s government debt-GDP level (dotted line). Source: Trading Economics Database
China’s growing debt pile (debt-to-GDP, %). Source: McKinsey
The biggest increase in the accumulation of debt came in from the corporate and financial sector (dominated by the big four state-owned banks in China). Most of these companies (including the non-state owned private enterprises) borrowed extensively from financial markets to finance large scale infrastructure projects.
The infrastructure investment-led bubble
The traditional wisdom in macroeconomics on the utility of infrastructure investment, in recent times is built from studies by Paul Krugman (1991), David Aschauer (1989, 1993) who provided econometric evidence for the case of large-scale infrastructure projects (such as rail, roadways) that in lowering transport costs led to increasing returns (i.e. through greater output, more private investment, employment growth).
While the econometric evidence cited in these studies does present a strong policy case in pushing for greater large-scale public infrastructure investment, in the Chinese case there is scant bottom-up evidence in this regard. The actual outcomes of specific investment projects present massive costs incurred in the building process of these mega projects, particularly in emerging economies like China.
The study by Ansar, Flyvbjerg, Buzier and Lunn reports results on “95 road and rail transport infrastructure projects built in China from 1984 to 2008 and comparative results with a dataset of 806 transport projects built in ‘rich democracies’”. The economic value of a given infrastructural project is tested by the benefits to cost ratio level (BCR) which needs to be either equal to or greater than one (BCR > 1.0).
Average Schedule Overrun of Chinese Projects (in %). Source: Study by Ansar, Flyvbjerg, Buzier, Lunn
In their results, 75% of the 95 transport projects in China suffer a cost overrun (in local currency terms), while the actual costs incurred on these projects remain 30.6% higher than the original, estimated cost.
The figure above helps in giving an approximate idea on the average schedule overrun (in %). As projected by the analysts, the actual average construction time taken to complete infrastructure projects (4.3 years) remained less than the average time used by the richer democracies (6.9 years). At the same time, there aren’t any schedule overruns (only one in every two projects encountered a schedule delay in China, compared to seven out of ten in richer democracies). The problem, however, remained with the costs incurred and the quality and safety attached with actual outcomes delivered in the infrastructure projects completed.
In building infrastructure at an impressive speed, the Chinese corporate enterprises (state and non-state owned), financial markets traded off with quality, safety and the estimated cost of these projects. The combined effect of benefit shortfalls and cost overruns pushed the BMR below one.
While conventional macroeconomic theory may typically treat all infrastructure as part of an exogenous cost-reducing technological input into the economy, to drive growth, it is increasingly becoming evident that most models arguing for such investment, intuitively assume that more and better infrastructure reduces the cost of transporting goods and services.
The evidence cited from China lucidly suggests that poor project-level outcomes translate into “substantial macroeconomic risks”, like accumulating debt, higher percentage of non-performing assets, distortionary monetary expansion from central banks (involving printing of more local currency to finance high cost infrastructure investment) and so on.
Such a pattern clearly signals a warning sign for most emerging economies that seek to embark on a China-style public investment model in the quest of achieving higher economic growth. China’s case offers significant macroeconomic policy lessons where emphasis on deep institutional reforms along with the development of quality, sustainable physical infrastructure needs greater emphasis (both from the government and the private sector).
Countries like India, which are currently in process of homogenising large scale infrastructure projects across the country, need to be wary of the costs-returns attached with such projects. Robust project designing frameworks, periodic monitoring tools and better outcome-based impact assessment models are critical in the process of achieving consistent developmental growth.
Deepanshu Mohan is assistant professor of economics at Jindal School of International Affairs, O.P. Global Jindal University.