A Credit Creation Theory Perspective on China’s Real Estate Bubble & Local Government Debt - Part 4C: Lord vs King: All That Glitters Are Not Gold
“We come and go, but the land is always here. And the people who love it and understand it are the people who own it - for a little while” (My Antonia, Willa Cather)
This is the 3rd and final section of Part 4 of the blog series on China’s real estate bubble and local government debt. In the series, I will share my thoughts, from a credit creation perspective (credit creation theory is the idea that money is created by commercial banks through borrowing & lending.)
Part 4 focuses on:
In this section, let's explore some philosophical questions on why land financing and debt have thrived in China.
Links to the Rest of the Blog Series (Outline of the Blog Series)
This blog series is organized as following:
Outline
In this posting, I will take an indirect approach by first demonstrating the power of leverage with a couple examples.
Here is how this article is organized:
The Power of Leverage
Let’s look at a real-world example of leverage and a pure thought experiment.
Leveraging in IT Services: Europe, India, and US
Let’s take the IT services market for example. Here, IT services market includes IT, BPO/consulting, and engineering services (example: a large US bank hires a firm to develop and maintain a new core banking system - some of the codes are done here in the states but most will be done by programmers in India.)
Let’s pick three services pure plays: Accenture from the US, Capgemini from France, and TCS (Tata Consultancy Services) from India. Accenture is the biggest in the market, revenue is more than 2X as the other two. But all three offer a full range of services (with very little products). They are good representatives of the market.
Table 1. Accenture, Capgemini, and TCS Leverage Ratio and ROE Comparison
TCS’ has a lower cost structure, fatter margin, and faster organic growth (grew by nearly 10 times in the last 19 years.) It seldom makes large acquisitions despite its strong cash position (it acquires clients’ captive support service units, i.e., processing centers or IT departments, as part of large outsourcing deals).
By comparison, Accenture and Capgemini are more acquisitive. Accenture did more. Capgemini went for size (relatively to its own size.) The two strategic acquisitions that Capgemini made in the last decade were the iGate ($4B in 2015) and Altran ($3.6B in 2020) deals. They helped Capgemini:
The amount of goodwill on the balance sheet serves as a good proxy for M&A. When you acquire a company, goodwill is what you have paid ABOVE the asset value (market value less book value). In services, because targets tend to be other services firms, and services firms do not have much hard assets (you are buying talents and client relationships), you usually end up with a lot of goodwill. They are considered intangible assets, sitting on the assets side of the balance sheet (assets = liabilities + equity).
As we can see, both Accenture and Capgemini have more goodwill, especially Capgemini.
Here is how the three firms use debt financing:
Looking at their leverage ratios (debt to equity ratios), Capgemini took on bigger risks to fund strategic acquisitions (it had to finance billions of euros for the two acquisitions), while Accenture and TCS are less leveraged (most of TCS’ so called “debt” are not bank loans but leases related financing - leases are considered debt.)
Generally speaking, corporate behaviors across different countries/regions are different:
What do the investors think?
TCS is the no. 2 company on the BSE (Bombay Stock Exchange) by market cap. Its overall capitalization is still moderately smaller than Accenture’s, but it’s almost 5 times as large as Capgemini’s. (Different exchanges have different rates of returns.)
But here is a quick calculation of their stocks’ long-term returns:
Therefore, one way to look at it is this:
In recent years, there were few large Indian services vendors being taken private by private equity (PE) firms (PE firms leverage debts to acquire.) While cheap capitals from the QE (quantitative easing) year, Indian firms’ capital structures also made them attractive.
Thought Experiment: Firm Marcia vs Firm Maria
Now let’s do a simple thought experiment: Imagine that we have two entrepreneurs, Marcia and Maria. Both of their companies are in the solar power station development business; both are equally experienced and capable. Both of them have relationships with local utilities. A key difference between two is how they approach financing:
Both of them are trying to build power stations in new cities: Maria set her eyes in a city called “Big Bright,” and Marcia has her heart on “Open Sky.” While solar power stations are cheaper and quicker to build compared to traditional power plants, they are still significant investments, and the regulatory process can take up to 5 years. For this experiment, we assume the following:
See figures below for Marcia and Maria firms’ approaches.
Figure 1. Marcia’s Venture in Open Sky
Figure 2. Maria’s Venture in Big Bright
Marcia’s approach
Marcia funds the project with her firm’s profits from other projects; therefore, she can only afford to build one power station. She goes through the approval process. In the end, the project takes 3 years and costs her firm $10.3 million in cash (see Figure 1.)
Maria’s approach
Maria, on the other hand, scoped out 3 sites.
She put up $500K cash and secured a loan to purchase the land for all three sites, using the lands themselves as collateral.
Because Maria has the land rights in hands, city and state officials have more confidence in her proposal, which speeds up the process.
As she draws close to obtaining the city and state approvals, Maria re-appraises the land at a much higher value, which allows her to secure a much larger second loan - $30M - to pay off the first loan and fund the construction of all three power plants. (Her firm uses the future revenue as collateral for the second loan; when issuing debt, the same asset can be collateralized multiple times. For example, a company owned by a private equity (PE) fund can be collateralized, but the fund itself can also be collateralized for new loans because the fund’s future earnings are now served as collateral, even though those earnings are based on earnings of the companies that it owns. In PE, this is called NAV, or net asset value, financing.)
Then construction starts. Nine months later, all three sites are done and begin generating revenues.
A quick summary:
China’s Industrialization Dilemma
Let’s now return to the topic at hand.
The industrialization dilemma facing the global south in general is this:
In 1950, right after the PRC (Peoples’ Republic of China) was established, China’s manufacturing was pitiful. Its annual output of pig iron and crude steel were only 980 thousand tons and 610 thousand tons, respectively (pig iron is a basic form of iron used as a raw material for making other iron and steel.) To put this in perspective, its steel production was about 5% of Germany’s and 13% of Japan’s (at the time, Germany’s and Japan’s industrial capacities were largely wiped-out during WW2 already.)
China had neither the skilled laborers nor the capital needed to transform an agrarian economy to a manufacturing economy.
The education gap was easier to fix. By adopting the Soviet style compulsory education system, including mass literacy campaigns, the government raised the literacy rate rose from just 20% in 1950 (some even considered it to be even lower) to around 41% by 1964, and over 90% by the end of 1990. (Scientific and Cultural Organization (UNESCO)). STEM education (science, technology, engineering, mathematics) has also caught up quickly.
To have a viable manufacturing industry to keep the STEM graduates gainly employed, however, proved to be more daunting. China desperately needed investment. In the early days, the PRC tried foreign aid, small scale/low-end manufacturing, foreign direct investment/export led manufacturing.
Soviet Foreign Aid & Capital Accumulation through Agriculture
At first, there was the aid from the Soviets (I briefly discussed the Soviet’s aid to China in the 1950s in a previous article.) The program was called Project 156. It included $300M credits worth of equipment and materials and comprehensive technology transfers, including sending over thousands of Russian and Ukrainian experts. It helped to build the foundation of China’s heavy industries.
The government also relied on the Soviet playbook to “squeeze” value out of the farmlands and move into the cities (building factories):
This approach was organic, slow, and painful. It was also risky when pushed too hard. Before 1978’s reform, China was over-investing in manufacturing (around 50%) and under investing in agriculture (less than 10% of the accumulated capital) although the majority of the country’s population were still in agriculture. The country had gone through several major economic crises throughout the 50s to the 79s (this part of China’s history is often unknown to the west because mainstream economists usually only focused on China’s post reform development.)
For example, here is what the numbers tell us about the Great Leap Forward (1958 - 1958):
(Source: NBSC)
The Rise of Township and Village Enterprises (TVEs) - 1978 to 2000
"Township and Village Enterprises" (TVEs) refers to enterprises set up by townships and villages in China during the 80s and 90s in China. They were mostly factories. Some were small local SOEs offloaded by local governments to be restructured. Some were set up with local governments’ help. While they were still under the purview of the government, they were very different from the state-owned enterprises (SOEs) in the following ways:
Because the communities that owned the TVEs also owned the land (see previous post on collective land use right), TVEs had free (or virtually free) land. This helped cut down their startup costs.
TVEs quickly filled the gap left behind by large state-owned factories. During the 1980s and 1990s, they were a major growth engine for China. They employed more than 130 million people (or around 10% of China’s population then.)
After China entered the WTO in 2001, some TVEs adapted, transformed, and fully privatized, while others were absorbed by new firms (including foreign firms) or simply went away.
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Foreign Investments - 80s and after
After the reform started in 1978, foreign investments started to flow in from the West. Japanese and other Asian firms (from South Korea, Hong Kong, Taiwan, Singapore) started move in first, promptly followed by European, especially German firms, and then the Americans.
Be it manufacturing 2.0, 3.0 or 4.0, for developing countries playing “catchup”, good industrial policies need to manage foreign investments carefully: it’s less about how much investment or aid, but more about who will share their supply chains with you.
There are typically two types of foreign investments, FDI or portfolio investments:
The Chinese government favored FDI because it brought not just jobs and market access, but also technology and process know-how. The timing was also incredibly lucky: over the last 4 to 5 decades, foreign investments around the world have steadily shifted from FDI to portfolio investments, and China was able to ride the last tide FDI.
First, by the early 1980s, China was ready for the “PULL”: it had a massive sufficiently educated yet very cheap labor force and a poor but functioning industrial infrastructure. The industrialists and financiers in the west also had reasons to PUSH - the western economies were undergoing the great financialization, and de-industrialization:
The world was sloshing in new credits to make offshoring/outsourcing cheap and easy. Strong dollar and Yen, then followed euro, also meant that domestic manufacturing in Europe, Japan, and North America suddenly made less “sense” (profits).
Here is a quick snapshot of percentage of labor force in manufacturing in
(Source: data gathered by ChatGPT from Eurostat, Bureau of Statistics Japan, and US DoL BLS)
Japan and Germany were the two manufacturing powerhouses who started outsourcing/offshoring to China early on. They also provided China with machine beds and other tools that China needed to build its manufacturing industries. If you look at the current trade data between China and Germany, Japan, and the US, you will find that Germany’s and Japan’s supply chains are still more intertwined with China’s than the US (China-Germany and China-Japan trades have larger shares of intermediate goods vs final products, compared to the US; also, the two are still two top destination countries for dispatched workers from China, according to NBSC data.)
Throughout the 90s and early 2000s, FDI (foreign direct investments) in China were quite high, around $50 billion per year. Compared to China’s GDP back then, it was a big number. FDI as percentage of GDP was above 5% for consecutive years in the 90s. Local governments would often throw in free land (free for 10 to 30 years) and tax incentives (along with other “perk”, often at the expense of labor and the environment), to attract foreign companies.
But eventually FDI would level off because developed nations eventually ran out of new supply chains to offshore (or least what the countries deem acceptable to offshore.) Take Germany and Japan for example, Japan’s FDI to China has been around $4B a year for the past 3 decades or so (median). Germany’s FDI was around $1.4B a year. Both had periods of surges: 2018 and 2022 for Germany, and 2005, 2012, 2013 for Japan.) Germany’s FDI has been trending up slightly and is more cyclical, while Japan’s was down a bit in recent years, but the overall levels haven’t changed that much over the decades.
This is why as China’s economy grew, its FDI’s relative size to GDP steadily declined (it is the same trend that we observed in Japan and South Korea 20 and 30 years ago.) Therefore, to sustain further industrialization, a country needs to move beyond foreign capitals to “self-financial bootstrapping,” which means borrowing from oneself. Thus, enters land as the perfect anchor for domestic borrowing.
Land, Debt, & Industrialization
Land’s Use-Value vs. Financial Value
The crux of land financing is the duality of land’s value: use value and market value
A piece of land has a use value (or utility), which depends on how it is used. For example,
It is also a financial asset and has a market value, which is what you expect the next guy will be willing to pay for it.
Let’s look at this simple example:
Scenario A represents use value because the primary purpose is creating practical benefits to the community.
B, on the other hand, is primarily driven by financial value because the new school will increase the land value. The market value is largely derived from your belief in (or speculation of) what others (i.e., the community) will build.
The two are not necessarily congruent with each other, but they should be somewhat aligned; otherwise, the market value will be “distorted” by pure speculation and creates a bubble. For example, if a land is not going to be used for productive purposes ever (not generating real economic value), then its market value appreciation will be pure speculative.
In helping TVEs and attracting FDI, it was land’s use value at work - free or very cheap land directly subsidized the production process by lowering the land cost. Later developments, however, had everything to do with land’s market value.
China followed this formula:
China wasn’t the first to try this. The quote at the beginning of the article, “we come and go, but the land is always here. And the people who love it and understand it are the people who own it - for a little while.” was from Willa Cather’s 1918 novel, My Antonia, an American modernism classic about American frontiers. It epitomizes how much the American dream was anchored on land ownership. As America pushed westward in the 18th century, the vast expanse of “free land” (free for the settlers) transcended to more than just fertile loam. They became dreams of endless economic possibilities. Dreams bred confidence. Confidence drove leverage and leverage unleashed economic growth.
Real estate appreciation/speculation was the very reflection of “American Can-Do Optimism”. When it comes to land financing, the US government and industrialists in the 19th and 20s century wrote the book on it.
US Example: Building the 1st American Transcontinental Railway
Take the 1st US transcontinental railway for example, here is how the financing worked:
The US federal government spent only less than $200 million ($6.3B in today’s money) plus “free land” to build the railway. This was the full power of financialization of land. Granted that there were external costs:
It had winners and losers.
But in the end, it worked:
Land financing worked because the land’s use value (transporting people from the coasts to the Midwest) and its market value (more settlers -> more economic activities -> increasing property values) were aligned.
Iran Example: Sustaining Manufacturing Investments with Real Estate
When there are no alternative investment vehicles, the property and debt markets can work in tandem to serve as a reservoir to pool capital for industrialization: forgone consumption -> real estate -> debt market -> investments for industries.
This is observed even in highly isolated economies. Let’s take Iran as an example.
(source: IIEA Webinar on Iran's Manufacturing Industries and International Sanctions, June 8, 2022)
The result: Iran’s GDP per capita is currently less than $5,000 (only a small fraction of its other oil producing neighbors’). Yet it’s the only country in the Middle East, other than Israel, who can make cars, missiles, and computer chips (not to mention potential nuclear capabilities.)
Note that this is contingent upon few existing conditions, such as:
China’s Land Financing
Although the Chinese government did not have millions of acres of “free” land, it had access relatively “cheap and fast” land. It implemented rounds of reforms - taking land from landowners through violence. As discussed in Part 4B, most of the actual land use belong to villages collectively, and local governments had to acquire the land. But the local governments monopolized the acquisition process (one has to go through the local government to acquire land from the village collectives), which gave them the upper hand in negotiating.
Because the deals were negotiated at the community level, acquisitions were fast and large in scale (developing tens or hundreds of acres at a time.) Developing such projects required huge up-front financing.
Local governments secured big loans from the banks, with the “to be acquired” land as collateral. Initial investments from the government could be as low as just 10% (the rest from land transfer grants - what developers pay the government to use the land - and banks.) As one can imagine, the impact on the local economy is big and immediate. It soon became the favorite revenue source for local governments, especially after 2008.
During the great recession of 2008, the Chinese government announced a RMB 4 trillion (US$580 billion) stimulus spending package (around 12% of its GDP back then.) However, only 30% were paid directly by the central government (see link.) China’s sovereign debt only increased by around RMB 700 billion (~US$100B) a year in 2009 and 2010. The rest came from local governments and borrowing (borrowed by the local governments.)
The actual new credits injected in the system went way beyond the $580 billion, however. The 2008 stimulus plan came with the acquiescence from the central government to allow (even encourage) “borrow and build” at the local level. For example, the high-speed rails alone cost $600 billion. In a recent report, since 2008, in 290 studied municipalities, both collateralized land area and values have gone up significantly (Land System and China’s Development Model, China Industrial Economics, January 2022 Issue, Liu, Shouying, etal.)
To put it bluntly, the 2008 stimulus plan was de facto a RMB 2 billion (US$290 billion) down payment for a decade of borrowing spree.
So far, this has worked, because land’s use value (a place to live) and its market value (a place to invest) were aligned:
The challenge now is whether this will be sustainable going forward. There are few threats:
Summary
This post focuses on how land financing and debt helped drive China’s economic development. Specifically, I have covered the following:
Why are these important?
Here is a quote by China’s late leader, Deng Xiaoping, who initiated the economic reform, "It doesn't matter whether a cat is black or white, as long as it catches mice, it’s a good cat". It’s a metaphor for pragmatism over ideology. Back then, it worked out very well.
But times have changed. Pragmatism alone doesn’t cut it. For one thing, time for learning is over. Back then, Chinese leaders could look around, pick and choose different theories, learn from others’ historical lessons - both positive and negative (i.e., industrial policies from the US, Japan, and Germany, the collapse of the Soviet Union, etc.) That is coming to an end. Moving into the unknown is much harder and scarier.
Then there is size: being pragmatic and nimble worked 30-years and $17 trillion ago. The current Chinese administration doesn’t have the luxury to “try this and that to see which sticks.” Nor does the world economy have that luxury neither for that matter.
It’s not enough to just pointing out how many billions has China lifted out of poverty. China needs theorization of its economic experience. It must build a systematic and evidence-based economic framework that can both explain its past economic success, as well as the missteps, and help guide itself (and others) moving forward.
In short, it’s great to have “Amazon”, but you also need your “McKinsey.”
The mainstream textbook economics, namely neoclassical economic theories (Neoclassicism), is clearly coming up empty for this task. For one, it can’t predict any real-world events. Major Western financial publications (Business Week, Financial Times, Economists, etc.) have consistently predicted the collapse of the Chinese economy over the last 30+ years, and consistently missed the boat on the subprime housing crisis in 2008 or Japanese housing market collapse in the 90s. Overall, mainstream neoclassicism is consistently good at predicting things that will never happen and marginalizes people like Michael Burry (the protagonist in the movie, Big Short) and Richard Werner (a German economist and the author of Princes of Yen, who was a visiting researcher in Japan during the 90s and first prognosticated the market crash) who can actually spot real financial crisis.
Secondly, most of their tenets, such as rational behavior, marginalism (marginal productivity, marginal utility, etc.), utility maximation, perfect competition, efficient market/resource allocation, or general equilibrium theory, can’t be measured nor tested. Mounting evidence from recent works in the fields of micro-economics and behavior economics, where theories were actually TESTED in real world experiments, have suggested that these neoclassic macro-economic theories were more like self-perpetuating myths peddling on circular logic.
This begs the question: why is a school of thought that can neither explain the past (why the former Soviet states’ economic “therapy” failed, or why did the post 2008 quantitative easing/QE in the US or China’s land financed debt spending succeeded), nor predict the future, continuing to dominate the classrooms of the future generations of policy makers and financial leaders around the globe?
One reason is likely political/ideological: it was well aligned with Reaganomics (US) and Thatcherism (UK). With the rise of neoliberalism, it was mainstreamed and exported around the world.
But the main reason is that there are no clear alternatives. There has been a revival in recent years, thanks to the internet and the great recession of 2008, of classical economics (Simith, Ricardo, etc.), Marxism, and Keynesianism. The popularity of Thomas Piketty’s “Capital in the Twenty-First Century” in 2013 is a case in point.
While the classics are more eloquent, intellectually rigorous, and have a moral compass (most of the classical economists from the 19th and 20th centuries also studied philosophy, history, mathematics, morality, political theories, social and natural sciences), they have two major shortcomings:
For these reasons, neoclassicism still dominates. But there will emerge new schools of thought in economics with theories grounded in real world evidence that can explain why some economies industrialize and modernize faster, and how can other developing economies draw upon them to create & implement their own policies that works for THEM.