Reconciling Chinese Household Debt Statistics

So after my Bloomberg View piece came out citing a self generated statistic that Chinese household debt to household income was above 100%, I had a number of eagle eyed reader send me a piece from the South China Morning Post from the same day.  In the SCMP piece, they present a graph that shows Chinese household debt to household disposable income at just above 50%. Readers were wondering how could I explain the enormous discrepancy between my self generated number and the number that was cited in the SCMP.

This worry about household debt levels in China and the most common mistake is that people use per capita GDP rather than household income. For numerous reasons, there are enormous differences between per capita GDP and actual household income numbers.  Even this recent SCMP piece about the rapidly rising household GDP number mistakenly uses household debt to GDP rather than household income.

Before I explain the discrepancy, let me stress, I personally am quite accepting of differences in how to interpret the data and whether additional data changes our view. However, especially when focusing on China, presenting the most accurate data and knowing what it does and does not say, is something I take very seriously. So I was also personally intrigued by the discrepancy.

I cannot say with 100% accuracy how the SCMP figure was generated but I can come quite close.  The first data source cited is the Bank for International Settlements which generates a dataset with a figure for market value of household debt as a percentage of GDP. Though it does not specifically say, I would assume that GDP here is nominal.

There are a couple of points worth mentioning about this statistic.  First, the BIS figure on household debt as a percentage of GDP does not perfectly match the figure in the SCMP but it matches within at most 10%.  The BIS lists Chinese household debt as a percentage of GDP at 44.4%. The SCMP figure appears to be just a little bit above 50% and does not have a data label so I cannot say for certain. However, later in the article the writer claims that Chinese “household debt-to-GDP ratio is only 40 per cent” even though the BIS places it at 44.4%. Later the writes claims that Chinese “household debt-to-disposable income is 56 per cent” though again it is not entirely clear how this figure is arrived at.

What makes the authors figures even more suspect is the transformation into “household debt to disposable income by country” that he cites.  If we follow the sources used by the author, we are able to locate within the UN National Accounts data a gross household disposable income number which would appear to represent the number used by the author.

This is where the author appears to get the cited statistic and take amazing statistical liberties. The UN data indicates that in 2013 (the last available year in the UN data set) China had 35.7 trillion RMB of gross disposable household income (more about this specific number later). At the end of 2013, Chinese households had 19.7 trillion RMB of household debt. If we divide 19.7 trillion by 35.7 trillion we get a number of 55.1% which is very very close to the statistic used of 56%.

However, this number is grossly and intentionally misleading. The author never prominently notes that the data used on China, his primary subject, is from 2013. He only notes in the last note of the figure that “the rest are as of 2013”.  The author is writing about second half 2017 discussing current economic situation and never prominently mentions that the data he is basing his argument on is nearly 4 years old?  The authors intention was clearly to mislead readers rather than educate them as to what best available data tell us right now.

In fact, we have best available data right for the year ending 2016. If we take the PBOC data on Loans to Households we get a total of 33.4 trillion RMB in debt outstanding at the end of 2016 which is for all intents and purposes statistically identical to the BIS figure of 32.95 trillion. Now what we need to do is find recent data on the amount of disposable household income in China.  According to the National Bureau of Statistics China, per capita disposable income in China in 2016 was 23,821 RMB.  With an official 2016 population of 1.38 trillion, this gives us a total disposable income of 32.9 trillion RMB.  Next we take the total PBOC household debt number of 33.4 trillion and divide by the NBS number of total household income to arrive at a household debt to disposable income number of 101%.  If we extrapolate out through the first half based upon the rate of growth in disposable income through H1 and use the June 2017 household debt, this number comes in around 104-105%.

What is interesting is that even if we take the official Chinese data used to calculate household debt to household income ratio back in 2013, we get 79.7% not the 55.1%/56% number used by the author. So where did the SCMP and the author go wrong?

In addition to the misleading date, the author confuses a measure of GDP for household income.  The author uses a measure of household income with GDP measures that is based upon the estimated value of household consumption within GDP.  The reason this matters is that the NBS compiles other data on household income that shows relatively different numbers.  So far, I have been unable to locate the exact “gross disposable income” number in Chinese data that seems to be used within UN data.  This is used primarily in a form of GDP accounting that is not widely recognized from the expenditure approach.  I have however, been able to match the consumption number the UN uses to the NBS consumption expenditure within GDP data.  This

The NBS however, compiles survey data where they actually go out and conduct surveys on rural and household incomes rather than compiling it at a GDP level.  The UN data on gross disposable income collected via GDP overstates household income by roughly 43% according to the NBS survey data.  What is important is that this measure of income actually compiles data on income from all sources such as wages and salaries, transfers, and income from business and property.  Similarly the same data also compiles detailed data on the expenditure side with significant detail by category. This does not match identically but close enough the highly regarded China Household Finance Survey conducted by the Southwester University of Finance and Economics that we can take this survey data as much closer to reality than the 1993 methodology using headline GDP data from 2013.

The fundamental problem is that the author uses headline GDP data for household income rather than that survey data on what households actually make.  It should be noted though that the use of 2013 data is misleading.  In both fundamental data errors, there is significant laziness when significantly better quality and newer data sources exist.  The household debt levels for Chinese households is above 100% of household income.

The Year Ahead

Given the New Year and all that brings, I want to announce some changes I am going to be making to the blog and others things.

  1. Since I started this blog, I’ve tried to maintain a pretty narrow purview of things I would write about sticking pretty closely to data specific issues of the Chinese economy I felt were either not understood or discrepancies that needed attention.  Probably even more fundamentally, I try to focus on economic and financial issues that were poorly understood and educate people about what is happening in China.  When I first started writing this blog, people might have had suspicions about Chinese GDP, for instance, but they had little evidence or ways to compare where problems might be.  Now however, there is a much higher level not just among the technicians but even among more casual observers about these issues.
  2. Given the narrow range of issues I initially set out to tackle on this blog and how the conversation has changed, I am going to expand the range of things I am going to write about. Let me strongly emphasize this blog will still focus on China and primarily the economy and financial markets.  In fact, it will remain data focused just like what I have done before but I expand somewhat to include background on economic and financial issues that I think are poorly understood.  There will not be any blog posts about the Chinese writer Mo Yan or anything but expanding to cover nearby issues.
  3. One thing I plan to do is invite guest writers from time to time to make guest posts. This will hopefully mean Chinese economists as well as others that have unique Chinese expertise that I cannot provide.  The writing will follow a very similar style in the sense of trying to help people understand specific issues and providing background that will help provide perspective.  One thing that I hope to do with this is provide different viewpoints about various issues in China.  As someone who travels around China and meets with people who spend as much time as I do studying China, I get exposed to lots of smart people that have interesting ideas and viewpoints. I believe firmly in the exchange of ideas even I do not agree with it.  I expect to have some Chinese economists that may or may not attach their name to the post for fear of pushback, but will hopefully bring additional perspective.  Living in China, I get the privilege of hearing a range of very smart Chinese talk about many of these issues.  There is a real diversity of opinion among Chinese economists and hopefully I can bring you some of that.
  4. I am taking the blog in slightly new direction for a couple of reasons. First, I feel the level of conversation and knowledge about the Chinese economy is a lot higher than it used to be.  However, that bring different shortcomings in how people view the Chinese economy.  Second, to use a cliché, I want to stretch myself as an artist and not get type cast. Third, I think is a lot of additional detail about various issues here that need addressing that simply cannot be addressed by data forensics. Fourth, there are a lot more issues surrounding China and Chinese-US relations that cannot be studied with the more narrow type of data work I have typically focused on in the past.  Again, I will not be straying too far afield but rather expanding what I have done to encompass issues of importance.
  5. The other reason is that I am doing enough other things that I cannot dedicate the time I would like to writing for the blog but want to continue. I am privileged to be able to write for Bloomberg as well as other activities.
  6. I also plan to create a page which will have the blog in Chinese. Honestly, this will be done using Google Translate which has gotten to a really high level and then reviewed by an RA, but we will have the blog in Chinese.
  7. Most importantly, I am working on a big project that I will be unveiling in the next few months that is taking a not insignificant amount of time. I am really excited about this project and will unveil hopefully by March 1, but it is something I’m really excited about.

For the time being, all the best for a happy and healthy 2017.  I am really excited about the upcoming year.

Is Chinese Mortgage Data Waaaay To Low? (No, seriously)

So recently a lot of ink has been spilled on the rapid growth in Chinese mortgages.  On the face of it the increase is certainly worrying.  New mortgage lending in 2016 is up 111% and the total stock of mortgages is up 31%.  Even if we take a broader measure of household lending that likely captures a not insignificant amount of real estate related debt, medium and long term loans to households is up 31%.  The numbers on their face appear large with medium and long term loans to household registering 22 trillion RMB and personal mortgages clocking in at 16.5 trillion RMB.

These sound like big number and in some ways they are, but in reality these numbers are if anything suspiciously too low.  Most get caught up on the size of the numbers but never place these total numbers in any type of context.  In fact, if you place these numbers in context, these numbers are absurdly low.  Let me explain.

For conservatism, data, and simplicity sake, I am going to limit the analysis to urban housing units.  In other words, let us assume that all mortgage and medium to long term household debt is owed only by urban households.  This does not change the outcome in anyway and if anything make it much more conservative than it would be otherwise.

The primary thing we want to do is adjust for the number of households in urban China.  Without going into all the underlying calculations, which come from all official data, there are approximately 272 million urban households in China and according to official data, only a very small number of households do not own their housing.  Again, this is all relying and strictly using official data.

If we then estimate urban residential real estate wealth using the 100 City Index price per square meter as our high value and the Third Tier City Price per square meter as our low value, we have both a high and low value for our estimate of urban residential real estate wealth.  This gives us an estimated upper bound of 330 trillion RMB and a lower range of 189 trillion RMB.

Here is where it gets interesting.  If we translate this into a broad loan to value number, this means that urban China has an estimate loan to value ratio on its real estate holdings of 5-9%.  In other words, almost all of urban Chinese real estate is owned almost entirely free and clear according to official statistics.

If we apply this analysis backwards, the numbers are even more nonsensical.  In 2011, the urban loan to value ratio ranged from 3.3-4.5%.  If we use absolute numbers, the appear even more absurd.  When the average housing unit in 2011 cost 665,000 RMB using the third tier city price and 910,067 using the the 100 City National Index, mortgage debt totaled only 29,675 RMB per urban housing unit.

If we focus just on the new mortgages and new urban units, the numbers look decidedly problematic.  For instance, if we use the 100 City Index housing price, this would give us an implied equity share for new housing units from new mortgages of 71%.  In other words, if we assume that only newly constructed units are purchased with new mortgage debt, owners would be providing a down payment equal to about 71%.

Now while I use the slightly more restrictive mortgage debt, even if we include the broader label of medium and long term this would barely dent the number.  If we use the medium and long term household debt number instead which is only about 4-5 trillion RMB more, again using only urban households, this would still barely move the per unit or value debt number.   To bring Chinese urban housing wealth up to a 20% LTV, would require about a 41 trillion RMB increase in mortgage debt.  Put another way, outstanding mortgage debt would need to go from about 16.5 trillion RMB to 58 trillion RMB. Including the obvious candidates that some have nominated simply does not come close to making these numbers plausible.

We are left with a conundrum: either believe the data at these levels or find a better candidate when no good obvious source of debt under counting exists.  I’ll be honest in saying I’m not sure whether to accept them as vaguely reasonable representation or believe that they are not even close.

If we consider the possibility that these debt numbers are relatively accurate, while there are positives, there are also very real risks.  First, it raises the scope that Beijing could further increase urbanization and home ownership rates by loosening credit.  However, there is evidence that rural households migrating to urban areas are already debt budget constrained and that Beijing is uncomfortable with the level of debt even at these levels.  Additionally, this raises the possibility that real estate prices have a long way further to appreciate which seems implausible given already elevated price to income levels.

Second, this would imply that households have put very high level of savings into their homes and may have less liquidity available than understood.  By some recent estimates, Chinese households had 70% of their wealth in real estate.  Liquidity constraints may exacerbate any real estate or broader economic down turn placing additional pressure on prices.

Third, this would seem to place enormous pressure on public officials to maintain housing prices at elevated levels.  If Chinese households have placed the vast majority of their wealth into their home, though lack of leverage will not magnify the financial returns, it will place enormous pressure on the government to prevent price declines.

There is one possible scenario, though we do not have the data to say for sure this happening that would explain the discrepancies we see.  Given the mismatch of the mortgage data and required down payment this raises the possibility of the leverage upon leverage scenario.  For instance, a home is owned with no mortgage debt.  The owner then pledges the real estate as collateral to borrow money for the equity share and borrows money in the form of a mortgage to purchase additional real estate.  In this instance, only one mortgage appears outstanding where, if we assume the second property is financed with a 50/50 debt/equity split at the same value of the first property, then we have a mortgage per unit value of 25%.  However, in reality the risk level is much higher as both properties have debt against them and depend on stretched cash flow valuations or capital appreciation.

There are many possibilities but the only thing we can say for sure at the moment, once we break down mortgage data into per housing unit basis, the numbers seem implausibly low.

 

Brief Follow Up to GDP as Misleading Indicator

I want to do a brief follow up to my piece for Bloomberg Views on why GDP misleading indicator when looking at the Chinese economy.  As usual, start there and come back here for additional detail.

I know that there is a vigorous debate about whether Chinese data is legitimate or not and if you are reading this, you’re probably very well aware of my opinion.  To this day, I do not understand how anyone can look at the headline data and say it is a good faith accurate representation of statistical reality.  Even most people who defend Chinese data anymore set a much lower bar of something like “well the directionality is accurate.”  Talk about an absurdly low threshold.

However, one of the things that has generally escaped notice is that even if GDP is perfectly scientifically accurate, it is a stunningly poor indicator of how we our understanding of the Chinese economy.  In other words, let’s assume for our purposes right here that it is accurate.  If it is accurate, do we understand and frame the Chinese economy well?  The answer is a resounding no.

The fundamental reason is that GDP is a non-existent measurement for quantifying the ability to pay for things.  Whether it is consumer spending or debt coverage, no one can pay for anything in GDPs.  I would encourage you to walk into a bank sometime, apply for a loan, and when they ask you for repayment ability tell them your cash flow is weak but your GDP output is high.  Seriously, try it sometime.

We assume that GDP measures are correlated with measures of economic activity and cash flow but in China for a number of reasons, this assumption, while not necessarily wrong is much much weaker.

For one reason, corporate China, where most of the debt is, has been dealing with long term deflation.  Consequently, while liabilities have been increasing moderately to rapidly their total revenue and revenue per unit have been flat to declining.  In other words, even if GDP is completely accurate, the weak cash flow growth of firms is even worse than the GDP growth making firms ability to service their debt even worse than the GDP numbers make it appear.  This is the problem with deflation but that is what is happening.

We even see this mismatch when looking at per capita GDP which is sued for a variety of individual focused measures not match the cash flow people have to spend.  Household income is on average 45% of per capita GDP and in some major cities like Tianjin, significantly lower than that.  If they pay in GDP’s, then many consumer measures look maybe stretched or excessive but not wildly crazy.  However, if we change to measures of income, the measures look decidedly excessive.

Again, my purpose here is not to revisit whether or not to trust Chinese GDP, but much more fundamental how do we use GDP, even if it is perfectly accurate, to frame issues like risk and consumption.  I would say, not very well.

 

 

April Trade Data and Foreign Exchange Reserves

A lot of how you decide to view the Chinese April trade and foreign exchange report, depends on what exactly you measured.  April exports were higher than March exports but were down YoY and YTD YoY if measured in USD.  However, if measured in RMB exports YoY was actually up 4% but remains down YTD 2.3%.  In some ways, this data can be viewed positively or negatively, but I am going to try and help provide some personal perspective.

  1. While the month to month and year over year snapshots are important, I firmly believe that the YTD are much more important. MoM and YoY can induce a sense of noise or bias into analysis that skews our understanding.  YTD exports are down 8% from 2015 and imports YTD are down another 13%.  What makes the import growth some amazing is that full year import growth was down strongly in 2015 and flat in 2014.  It is difficult to see how these are positive signals for an economy as you stretch the time horizon out.
  2. While the trade surplus again remains strong this is a very deceptive measure for a couple of reasons. The trade surplus remains strong not because trade is increasing but because imports are shrinking much faster than exports.  Whether you look at it on a YoY or YTD YoY trend, it is clear that imports are shrinking faster than exports.  While some of this can be attributed to factors like commodity price drops, it is also clear that some of this needs to be attributed to weak Chinese demand.
  3. The other reason that the trade surplus is incredibly deceptive is that the actual surplus if measured by cash, which is really what matters, is much much smaller. Through March, Chinese Customs reported a surplus of $126 billion USD while banks reported a surplus in goods trade receipts of $23 billion.  This means there is a $103 billion discrepancy between the official trade surplus number and what cash is actually flowing into China.  Given the $46 billion surplus reported for April, we can probably expect that this resulted in a bank receipt surplus of $10-12 billion USD.
  4. Extrapolating this into the official amount of FX reserves is where things start to get a little debatable. To date, the only category in surplus on a cash basis in Chinese banks in goods trade and it is small at only $23 billion.  All others are in significant monthly and year to date deficit.  For instance, through Q1, YTD outflows are almost equal to Chinese net outflows through November in 2015 YTD.  Capital account receipts are plunging and outflows are up almost 40%.  This is a very consistent pattern in each month and summing across Q1.  If this patterns holds in April, this would imply a net outflow of at least $30 billion through official bank payment channels.    Despite talk of how USD valuation drove FX reserves up, the EUR was essentially unchanged against the USD in April.  The JPY which was up almost 5% against the USD but by most estimates comprises no more than 15% of PBOC reserves should not swing the portfolio that much.  If we assume the JPY has a 15% portfolio weighting and moved 5% in the PBOC’s favor, this should result in no more than a $24 billion boost.  This at least gets us closer to explaining the PBOC official data that reserves rose but as many have noted is an increasingly difficult number to reconcile to other data.  This would have to imply a much small outflow.
  5. The reason for the skepticism is that it is increasingly difficult to reconcile the ongoing outflows, even after accounting for valuation, with the stabilizing and actually increasing reserves. For example, in the past three months when FX reserves were stabilizing and then slightly increasing net outflows have actually gone up by most measures.  This is simply difficult to reconcile though I think it is fair to say that while there is suspicion and concern, there is as of yet no smoking gun or hard evidence of how they are making this number appear so rosy.
  6. Too many people focus on the level of FX reserves rather than the net outflow number. If you run a fixed exchange rate regime, you cannot sustain net outflows for an extended period of time.  Despite the rosy official trade surplus, underlying cash flows have if anything accelerated this year, though there may be some evidence that capital controls are starting to bite though it is too soon to tell if that is just Chinese New Year seasonal fluctuations.  Even if the FX numbers are perfectly accurate, the ongoing level of sustained outflows should absolutely be the bigger topic of discussion.

Economists and Danger: Welcome to Modern China

I do not typically write about individual news articles but I saw an article by the always excellent Lingling Wei (who in case you forgot also broke that the IMF was pushing the PBOC for more information about its derivatives portfolio) about Chinese authorities warning economists.  There are a couple of points worth mentioning and some of them are, warning you in advance are politically incorrect.

  1. Any China bull or anyone who still has any remote belief that Chinese data is anything other than art: you’re just embarrassing yourself. Assume the Chinese economy really is in good shape and economists are just misinterpreting data, why do you need to go around threatening people?  One thing that I get from certain non-Chinese economists (with one senior person at well known institution telling me “we have no reason to believe Chinese data is systematically manipulated”) is that I just don’t understand China or Chinese data.  It is widely accepted in China that Chinese data is heavily manipulated.  This is not some dastardly foreign plot but accepted wisdom in China.  I learned about this, as I have said many times, not from academic work but from my students who thought I was moron for believing it in the first place. If China known to censor the news do you really think they are choir boys on economic data and that the economy is humming along at 6.7%?
  2. Self censoring of economic and financial reporting in business community is wide spread. I was told point blank by a senior executive from a major financial institution that they no longer publish any report that is remotely critical of the Chinese economy or markets.  Of course this is not put in the employee handbook but that is unofficial policy.  We already know this is happening to Chinese reporters but his is increasingly happening to economists. To argue that Chinese doesn’t censor economic data is simply delusional.
  3. Politically incorrect warning (but something that should come as no surprise): I am personally only able to say what I say because I am white and American. Consider the race card played. If you have been following China at all, this should come as absolutely no revelation even if it is maybe somewhat politically incorrect to say straight up. Most all Chinese economists do not want to talk publicly about the economy, even those that are pro-Beijing for fear of saying something that will get them into trouble. In today’s China I cannot tell you how much respect I have for a Chinese economist who says anything publicly and even more so for those who do not perfectly conform to what Beijing says.  I know an economist, decidedly pro-Beijing, who gave an interview to local media but laughed when his comments aired as he mentioned they removed his suggestions and comments about how to reform. Mind you this was not a critical voice. This was in fact a very pro-Beijing voice but even he saw the irony.  I have never been approached to stop writing or saying what I am seeing in the Chinese economy, but if I was Chinese by passport or ethnically, I believe there is no chance I would be allowed to write what I write.
  4. The change in China has honestly given me pause to reconsider my own position for fear I might face retaliation in China. Despite my critiques of the Chinese economy and data on largely technical issues, I can say with hesitation I enjoy what I do, my job at Peking University, and the city of Shenzhen. My family enjoys living in Shenzhen, a very comfortable and pleasant city except for the stifling humidity, and my incredibly white kids speak native quality Chinese which has won me many a bet.  However, the entire environment in China is changing and changing rapidly and not just the economy.
  5. Some absolutely great comments by economists who realize how absurd the system is internally. Some of my favorites:
    1. “You can see they’re not happy when you tried to tell them foreign speculators are not your biggest problem,” said one of the officials who attended the meetings.
    2. “As a Chinese reporter, you can do anything but journalism these days,” said a senior editor at a state-owned media outlet.
    3. “I was told by regulators not to recommend shorting the renminbi,” Ms. Lin told the gathering, “so I’m just going to recommend buying the dollar.”
    4. the city’s propaganda department recently instructed a local think tank to stop researching a planned debt-for-equity swap program aimed at helping big state companies reduce debt, according to economists familiar with the matter. The reason, these economists said, is that officials don’t want the research to turn up unfavorable evidence after Premier Li Keqiang and others have endorsed the swaps.
    5. Despite recent signs of a rebound, Gao Shanwen, chief economist at brokerage Essence Securities Co., told investors that “a lot of the official data aren’t reliable” and the economy still faces “big problems,” according to people who attended the closed-door event. Words of those remarks crackled across social media. Two days later, Mr. Gao issued a clarification on his public account in the popular Chinese messaging app, WeChat, saying those remarks were “made up.” He then released a report on the economy shorn of critical commentary. Mr. Gao and representatives at his firm didn’t return requests for comment.

Just a Little More on Capital Outflows

So just a little more follow up to my most recent piece for Bloomberg Views on disguised capital flows from China.  As usual start there and finish here if you haven’t already.

  1. Here are some slides I prepared for the Foreign Correspondents Club in Beijing this week. You can clear see visually when the outflows really began and the direction they continue to go.  Hint: they are not reversing.
  2. You should not believe any of the official data on inflows or outflows. According to China, they had a pre-net errors and omissions balance of payment surplus of nearly $200 billion.  The NEO figure just brought the BOP into balance.  What country has large BOP surplus is bailing water  from the bowels of the Titanic to keep the RMB from dropping 25%?  This happens because BOP data is built on other faulty data like official trade surplus data.  So whenever someone cites the large trade surplus, they have proven to you that they do not know what they are talking about.
  3. All of the economic issues that people cite as attracting capital from China like the Fed and interest rates are simply compounding factors rather than driving factors. If China were actually enjoying large cash inflows from a $600 billion trade surplus, then the level of foreign debt repayment we are seeing would be completely and entirely irrelevant.  In fact, the PBOC would be forced to push down the RMB rather than prop it up.  However, that is not happening and that is why foreign debt repayment matters at all.  These are compounding factors but definitely not the driving factor.
  4. The Bank for International Settlements report a few months back was a classic piece of weak analysis without proper perspective. They cited foreign debt repayment as a primary factor for outflow but even by their own words, this analysis was extremely limited.  First, it only focused on the third quarter when the original devaluation took place. This omitted any look at a long time horizon.  Why does that matter? Between February 2014 and February 2016, foreign debt declined (drum roll please…..) by a grand total of $7 billion.  Second, by their own words, it only accounted for about a quarter of capital flows.  How does that count as the driving factor?  Given the magnitude of what we know about the gray market flow, foreign debt repayment is nothing more than a compounding factor and not remotely close to what should be considered a driving factor.
  5. I think there are three things that started this whole outflow process. First, China liberalized current account payments in 2012.  Consequently, if you wanted to buy a house in Sydney in 2012, you could either try and legally move it through the capital account, though with lots of difficulty.  You could also just import something from Sydney and enormously overpay so that money ended up in Australia so you could buy the house. Guess what people did? Second, economic activity peaked somewhere between late 2011 and early 2013 and has been on a downward trend ever since.  Given the vast over capacity and declining investment opportunities, this was likely Chinese seeing the declining opportunities taking some of their money off the table for better destinations.  Third, there was a political handover beginning in early 2013 that radically changed the atmosphere and likely well connected were hedging their bets well before it officially happened.  This is absolutely also a contributing factor.
  6. When I say that Chinese are moving their money abroad for additional security, I am using security in a very holistic sense. People are concerned about the cost of real estate, complete lack of the rule of law, the environment, getting caught up even tangentially in a corruption case, or so many other things.  No one in China views China as a secure destination, especially if you have any money.  Whether it is thoughts about where they want to send their children to school or comparing junk local Chinese government bond yields to high credit quality US corporate debt yields, for many reasons that bring greater security.
  7. This is not a short term process. Expect the capital outflows to continue. This is not going to turn around even if the economy does turn around for real.

Noise Vs. Trends or How to Look at the Chinese Economy

China has released a spate of good data which on the surface give a sense that the economy is turning around and everything will be fine.  However, if you look at the data in very straightforward ways, you can quickly see that the data is revealing significant underlying weakness.  Today rather than focusing on China, I am instead going to use China as the case study of how we need to analyze economies.

  1. What is the trend? Too many people will focus on a one month number and less about where does that number fall around the trend of previous months.  Economic data is noisy and most of the time simply bounces around a clear trend.  Just because it bounces above the trend in one month, does not mean the trend has reversed.  The trends with regards to China are obvious and need no revisiting but the key issue is that it is only normal that in some months, the data is above the trend line.  Take a simple example, if we believe the “rebalancing” story, which has more holes than a fisherman’s net, this absolute requires a long downward trend in roughly 50% of Chinese industry.  There may be short term data around that trend, but that trend is a long term structural shift and we would be advised not to read too much into month to month or quarter to quarter changes. Most every time people call some type of turnaround, plot the data and you can see that it is really just a bounce to slightly above the trend.
  2. What is the number measuring? Sounds a little simplistic but it is very important to make sure that the number being used is properly understood. As a simple example, joining forces with the previous point, many are rejoicing at the March trade data.  However, as China Beige Book so rightfully notes, the “bounce” was not a bounce at all after accounting for the previous years decline to the base and when considering the year to date numbers.  Year to date for the first quarter, Chinese trade numbers continue to decline.  As another example, the trade surplus measures the declared value of products at customs.  Officially China ran a nearly $600 billion goods trade surplus.  However, that measures the “declared value” not the cash transfer value.
  3. Put numbers in perspective. Many times people get excited over headline numbers and forget to put numbers in perspective.  Let me give you two examples. I think Chinese GDP data is completely unreliable, however, in most ways it doesn’t matter.  GDP is meaningless value to the man on street who pay their bills with cash.  Revenue across corporate China is essentially flat for quickly approaching about two years now while liabilities continue to grow significantly.  So for instance, while people say GDP is healthy, the key number of cash available to repay those debts is actually behaving very differently.  As another example, that thankfully many journalists and specialists picked up on is that Chinese bump in FX reserves was all about EUR strengthening against the USD not a decline in outflows.  Outflows remained right on trend.  Whenever you see a Chinese number, stop and think what is this number really telling me?

Sorry for the short post today been travelling in Beijing, Shanghai, and about to leave for Hangzhou before returning back to Shenzhen.  I’ll have some interesting slides to post in the next couple of days.

Good & Bad News: 3% Inflation Target Hit and Totally Unreliable

I don’t normally write two blog posts in one day but given the CPI data released today, I wanted to detail in brief why these numbers are so absurd because we can clearly tell these are absurd numbers with no basis in reality.  When I first saw the data on CPI increase to 2.3% I was stunned and when I saw that food was up 7.3% more than twice the change of any month in the past year my mouth hit the floor.  I never rule anything out in China but given the magnitude of the change only a few days after Beijing released a 3% inflation target, I thought it would be wise to just double check some numbers.

Before I explain why, let me give you a little background on China and CPI.  Numerous studies have found large problems with Chinese price data.  Emi Nakamura and Jon Steinsson (PDF) of Columbia found that official price data was much too smooth when compared to how household surveys indicated that households were spending money.  From my own work (PDF), the housing component of Chinese CPI shows that urban housing prices only increased 6% (let me emphasize that it total not annually and not asset price but rather how much more housing costs to obtain) from 2000-2011 and even if we added on 2012-2014 would only slightly raise that number.  There are many many problems with Chinese inflation and CPI data.

These problems have not gone away.  As Nakamura and Steinsson point out, as a country grows richer, they should spend less on food as a percentage of their income.  In simple terms, if you make $1,000 in a year, you might spend 40% of your income on food.  However, if you make $100,000 you would probably only spend say 5%.  This is important because since 2011, China has raised the weight of food in the CPI basket every year from 31.4% to 33.6%. You would be hard pressed to find another country in the world that experiences rapid growth and every year spends a higher percentage of its income on food.

All this is good background but also ties in directly to why we can tell today’s CPI data is nothing short of a fabrication.  With food comprising 33.6% of the CPI basket and food CPI running at 7.3%, this means that food inflation was responsible for 2.45% of the 2.3% CPI rate.  In other words, if you strip out food, inflation was actually -0.15%.

However, that’s not the worst of it.  It gets sooooo much better.  If you look beneath the hood of the CPI basket you will see that actually most food product prices were actually quite small.  Grains were up 0.6%, oils and fats 0.7%, aquatic products 3.5%, milk 0.1%, and beef 0.3%.  Mutton and eggs were down 7.8% and 3.6% respectively.

So what was up enough to account for the food CPI number?  Fresh vegetables and pork, registering increases of 30.6% and 25.4% respectively, were the only products with increases above the average.  At this point, it would be tempting to say that over the Chinese New Year holiday people celebrated with friends and bought the best food so makes sense.

There are only two problems with this theory.  First, do you want to tell me no other food prices went up? The only food people ate more to justify such a shift in prices was pork and fresh vegetables?  Skeptical that they would be such extreme outliers but let us set that aside for a moment. Second, the related data on pork and vegetables tell a radically different story.

Let stop a second and talk about ways to verify Chinese data. A key tenant of mine is to look for numbers that should come close to the number in question.  This does not mean we are looking for a perfect match but numbers that are I the ball park of each other.  Let me give you a simple example. If electricity production declines 10% but industrial consumption goes up 10%, you have to ask what is going on. If electricity production goes up 1% and consumption goes up 2.4%, that’s good enough for me and move on.  For almost any data point, there are many related data points that we can match up that will give us an idea what up and downstream things are doing.

What is interesting is that in reality, fresh vegetable and pork prices appeared to have gone up by roughly the amount indicated.  For instance, the Wholesale Price Index of Qianhai Agricultural Products of Vegetables from February 2015 to February 2016 was up 34%, only slightly more than the official CPI amount for fresh vegetables.  There are a wide variety of prices to choose from on that cover pork and pig prices from conception through to table and they are also roughly in line the 25% increase.

So what’s causing the discrepancy? Bad math.  If we take the official CPI weights for each category and plug them into the price increase of each product for the food category (remember food was responsible for more than 100% of the official CPI or 2.4% of the total 2.3% CPI) equals only 1.41%.  (By this I mean for instance, meat was up 15% and comprises 4.33% of the total CPI basket and repeat for other food categories.) What makes this even worse is that if we remove pork and fresh vegetables, food prices for which we have official basket weights and official inflation numbers shrank slightly at 0.06%.  Given that the CPI basket covers meat, grains, produce, dairy, flavoring and others and the food that we do not have official weights for was flat like the non-pork and fresh vegetable categories, it is very difficult to see where this supposed food inflation came from.  However, as the CPI contribution of pork and fresh vegetables only amount to 1.4%, this means we still need to find an additional 1% from the food category as the implication is, it does not come from the non-food basket.

What is so amazing about this is that inflation statistics in China do not add.  China says non-food inflation in February was 1% and food inflation was 7.3%.  Given a non-food weight of 66.39% and a food weight of 33.61%, this would sum to inflation of 3.12% or more than 0.8% more than the official rate.  In other words, Beijing tops in Communist efficiency has already met the 3% inflation target it set just last Saturday and they exceeded their target.  The only way you can have food inflation of 7.3% with a 34% food weight is to have deflation throughout the rest of the CPI.

However, even then, given the weights of the CPI basket and the price increases in those specific products, the numbers do not add to what Bejing says.  If we take Beijing numbers and assume that non-food need to deflate slightly and pork and fresh vegetables were the only food items that really increased in price, we still can only arrive at inflation around 1.4%.

There simply is no way for the numbers to reconcile. Let me emphasize in closing that everything here is official data and statistics.  The only math used was simple math done in an Excel spreadsheet.  All you have to do is try and do something as simple as add the numbers up to see that they do not add.

Update: I have been told by Alex Frangos of the Wall Street Journal Hong Kong that the NBS reduced the CPI weight of food by 3.4% by my calculation to 30.2% of the CPI basket.  I have not seen that and given that this would lower the combination of non-food and food inflation rates to 2.9%.  Given that I was working with 2016 component weights for products like meat or pork, this does not alter the other parts of the analysis.

Follow Up to Whether China has a Trade Surplus

I wanted to write a follow up to my previous post about whether China has a trade surplus because I received a number of very good questions and I felt there were some confusion about the implications of what I was trying to say.  Let me emphasize that in some areas here my thinking is still fluid and there are good arguments are both sides, so I won’t say that my thinking is final by any means.

  1. This is not misinvoicing. This is related to misinvoicing in that it achieves the same ultimate objective of disguising capital flows but it is not misinvoicing.  Misinvoicing is the process where a $100 export from Hong Kong to China turns into a customs reported $200 Chinese import from Hong Kong.  This is a mis-payment scheme.  In this case, Hong Kong reports a $100 export to China, China reports a $100 import from Hong Kong.  However, now when the Chinese importer goes to the bank to pay the Hong Kong exporter, the importer tells the bank to pay $200 rather than the $100 reported to Customs.  This may happen by the importer presenting forged Customs documentation to the bank or by bribing bank officials.  This may seem like a semantical difference but it is important to understand the difference and I will explain why the difference matters a little later.
  2. There has been some confusion about whether I am arguing whether this means China has a real trade surplus or whether imports are actually higher than reported. I think it is highly unlikely that that other countries are exporting to China $2.7 trillion worth of goods but Chinese customs is only reporting $1.7.  The reason is simple: that discrepancy would easily be caught by comparing Hong Kong/Australian/German/Japanese/US exports to China and Chinese imports of Hong Kong/Australian/German/Japanese/US products.  We do not see that discrepancy.  This means that that the value of physical goods imported in China is most likely $1.5-1.7 trillion.  I have dealt with Chinese data and nuances long enough to never rule anything out, however, it seems unlikely that China is actually importing $2.7 trillion worth of goods.
  3. However, we need to be careful about immediately jumping to the conclusion then that China has a real trade surplus. Though it may be fair that the market value of the goods trade would have resulted in a surplus, net exports for national accounting purposes are not based upon physical output or a market value but essentially on a cash basis.  For instance, if physical oil exports rise 10% from 100 to 110 but the price of oil drops from $100 to $50 then the cash value of exports drops from $10,000 to $5,500 for a 45% drop. The “real” increase in export shipments is irrelevant in some ways.  It helps inform our understanding of the whole but for national income accounting with regards to net exports (X-M) is irrelevant.  In real terms yes I think it is fair to say continues to have a trade surplus, but in very real ways this does not mean anything as cash is how trade balances are calculated and pass through to GDP growth.  In other words, people no longer trade seashells but cash and on a cash basis, China does not have a trade surplus.
  4. My thinking on what this means for GDP growth is more fluid and I would appreciate comments from someone who is a true national income accounting expert. I lean towards the argument that this has direct and negative pass through effect on the GDP growth and let me explain how.  In nominal terms, Chinese official data says GDP was 67.67 trillion RMB at the end of 2015 compared to 63.59 trillion RMB in 2014 for total nominal growth 4.08 trillion RMB.  Now the nominal RMB Customs reported trade surplus was 3.69 trillion RMB.  Now if reverse the Customs reported trade surplus and account for the trade balance on a cash basis including the service deficit, this turns into a trade in goods and services (emphasis not current account) deficit of 226 billion RMB.  This means that nominal growth when using the cash basis net export trade deficit turns into nominal growth of only 168 billion RMB or less than 0.3% in 2015.  I should strongly emphasize that I am implicitly assuming that China is counting net exports as equal to the trade balance reported at customs as part of the old equation Y = C + I + G + NX. Now here is the primary reason I believe this has a negative impact on growth and that growth should be reported, and again my thinking is fluid here.  Running a trade surplus implies that there is surplus cash flowing into the economy.  This cash is creating additional savings, investment, jobs, and demand throughout the economy.  However, because there is no surplus cash there is no additional savings, investment, jobs, and demand.  In fact, we see the impact pretty clearly.  When trade surpluses were high and the PBOC was sterilizing, China was awash with cash and investment was booming.  Now Customs reported trade surpluses are at record highs, but liquidity is tight and rather than sterilizing the PBOC is propping up the RMB.  Furthermore, as previous noted, because NX are always thought of on a cash/nominal basis, it seems that the impact on growth needs to be considered on a cash/nominal basis rather than a real basis.  Before I published my original post, I consulted a couple of very knowledgeable people about some of the implications like this and they all came back to me and said they really didn’t know and would have to think about it.  I say this definitely not to blame anyone I consulted as all errors are mine, but rather to note that this is a thorny issue about the implications and that this is what I currently think about the implications for growth but I am open to changing my mind and these are not deeply held convictions.
  5. This is also why capital controls would not work. For all the chatter about China imposing capital controls, it is obvious they simply wouldn’t work.  Let me explain.  Impose the most draconian capital controls you could imagine and money would still flood out of China via the free currency transactions via the current account.  I can already hear people saying, just tighten capital flows on the current account side.  The only way that could be achieved is by bringing goods and services flows into and out of China to a near standstill.  Think I am exaggerating?  Imagine customs inspectors having to count every physical unit into and out of China; establish an independent market price for every good and service into and out of China; verify the agreement between importer and exporter is at the independent market price; follow the importer exporter to the bank to verify that the payment or receipt perfectly matches the customs approved value.  In other words, at every possible step for every unit, everything would have to be verified and approved by the government.  This would necessitate bringing goods and services trade into and out of China to a complete standstill.
  6. Finally, I think there are a couple of things driving this shift in flows. First, China opened up the current account in 2012 to relatively free currency transactions and the data shows this discrepancy began growing rapidly in 2012.  That should not come as any surprise.  Second, in late 2012 and early 2013, China had a power hand over and it is likely that a not insignificant part of this outflow is driven by security concerns.  Chinese brokerages who survey their clients regularly find that high net worth individuals are concerned about a variety of issues with large numbers of them looking to leave China.  Third, investment returns in China have been declining for about 18 months.  For instance, 10 year local government Chinese debt is lower yielding than good quality US corporate debt.  Given the junk/near junk status of local government offerings, the risk return there is easily worth examining closer shall we say.  Fourth, I don’t think this is temporary in the least or about the stop or reverse.  This has been picking up speed since 2012 and shows no sign or reason to stop.  Outward FDI or official capital flows have no reason to use this channel.  This should be thought of as long term or permanent removal of capital from China.  Whether someone is moving from China to Canada or a small to medium size business is expanding elsewhere, most companies have no reason to use this channel.  This is not short term opportunism but rather long term to permanent capital expatriation.  Yet another reason, capital controls are very unlikely to work.
  7. I apologize if I missed any issues as I tried to cover them.