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.

Collection of Thoughts on Chinese Economy

  1. Simon Cox and others, I apologize as I don’t know the commenters only via email address, have raised some issues about my previous post about my posts on trade balance, payment flows, and growth. Scroll through the comments sections here and here. To briefly summarize, the basic objection is that the payment discrepancy does not change the “actual/true” trade surplus that China generates and as Simon points out this would still generate Chinese savings by holding assets abroad.  I am trying to faithfully represent their views as they are reasoned and logical so my apologies if that doesn’t accurately capture their views in one sentence.  I disagree with part of this and agree with part of this though with caveats.
  2. When a country runs a nominal trade surplus, especially one as large as China’s in 2015, there are certain things that happen. For instance, the surplus financial inflow creates additional liquidity, demand, wages are pushed up, the currency appreciates, and other spillover effects.  To be very kind absolutely none of these things are happening in China.  In fact, the exact opposite is happening.  If China was running a trade surplus, then the PBOC would have to be pushing the RMB down not keep it from dropping.  This brings us back to the difference between actual/true, real, and nominal growth.  China may have actual/true official growth of 6.9% if we consider the trade surplus actual/true.  However, based upon the financial flows that accompany a trade surplus and the spillover effects, we absolutely cannot say that China has a nominal/cash trade surplus and this has significant implications for what we see in the economy.  One way to think about this is   an accounting trick companies frequently use to boost their profits.  A common trick of companies the world over if they need a quarterly profit boost is write up the value of some of the assets on their books.  There has been no real change to the company other than an accounting trick.  That is essentially what is happening here.  The domestic cash flow, both for firms and surplus cash flow into China, simply is not present to associate with a trade surplus equal to 5.5% of GDP and the accompanying GDP growth.  What is happening is essentially an accounting trick. You can’t say growth exists but that none of the positive things that go with it do not.
  3. Simon raises the very real issue about the capital flight being savings, which whether it is kept in China or the around the world, boosts national wealth and income. From a national accounting perspective, he is totally correct.  If it is a simple matter of portfolio diversification, then the savings relationship in national income accounting still holds and growth goes up.  However, for many reasons I think the story is more complicated and not as positive.  The primary reason is that money leaving China is not a simple story of portfolio diversification.  Foreign assets owned by China from September 2014 to September 2015 are essentially unchanged.  In a year when nearly $1 trillion left China via fraudulent payments, official assets are unchanged.  This matters because the money leaving China is designed to stay off the grid, underground, out of sight, unknown to Chinese authorities.  Why does this matter? If it was a simple matter of portfolio diversification, like companies want to expand abroad, we would expect it to show up in official statistics even in China.  However, it is not a simple matter of portfolio diversification.  The intent behind this money, I strongly suspect and related data supports the idea, is permanent expatriation of capital out of China.  By that I mean, this money is leaving China and never coming back.  Wealth managers survey of clients for a number of years have found that wealthy clients are actively looking to leave China.  The number one sending country of immigrants into the United States is now China and it would not be surprising if other countries like Australia, New Zealand, Canada, and the UK (just to name a few) were not experiencing similar influxes.  The Chinese immigrants into these countries however are not the poor, hungry immigrants that arrived in Ellis Island but families buying businesses to obtain visas or attend graduate schools that lead to permanent residency.  They bring with them large amounts of capital that is coming from China.  According to some data, 90% of Chinese students that go to the United States for either college or graduate school, stay there never to come back except for vacation or to visit their parents.  Stories of cities seeing real estate prices sky rocket and Chinese become a primary language are common from Sydney to Vancouver and London but more importantly, the visas and residence permits that come with them.  Anecdotally, everyone in China above a certain income threshold has either plans to ultimately leave or contingency/fall back plans in case they need to leave.  Getting back to the point about how to interpret this financial flow, if it was pure portfolio diversification, there would be a case to incorporate some percentage of this outflow into national accounting based upon GDP.  However, based upon the illicit method of its departure, the accompanying asset purchases, and simultaneous emigration I do not think you can say this is standard portfolio diversification.  A major portion of the money leaving China that we are discussing here, the nearly $1 trillion in fraudulent payments, is not for domestic business expansion but rather permanent or quasi-permanent capital flight. Real portfolio diversification has no reason to use this channel so at the least this needs to be called a hedging strategy and much of it permanent capital flight.  The other thing is that despite people just waking up to this capital flight, this started in 2012 and has been growing every year.  It did not reach a critical mass until about 18 months ago, but this is not a new phenomenon.
  4. Capital outflows are a long term phenomenon. The one game winning streak put together in February is little more than a reprieve.  What reason does capital have to stay in China or flood in from abroad?  To everyone who hangs on what a 0.1% means in China, learn the concept of long term trend and statistical randomness around a trend.  The long term trend is clear and hasn’t changed.
  5. It is amazing how the conversation about China has changed. There almost is no such thing as a China bull anymore, there is only bulls trying say “it isn’t that bad”.  Their biggest argument now is that it isn’t as bad as Kyle Bass makes it sound, like that is a ringing endorsement.  The big key going forward is I simply don’t see what the signs for optimism are.  Fiscal stimulus? Great, more debt and things people aren’t going to use. Monetary easing? Great, stoke capital outflows, break the RMB peg, and deplete FX reserves. VC funds to drive entrepreneurship? Great, cause throwing vast sums of money with little oversight never created problems and definitely not like stimulus projects in China.  There are sectors growing in China and doing well but for the economy as a whole? No.  Rebalancing in China is a scam much like the rule of law or human rights.
  6. Everyone who essentially hangs their hopes for an improved Chinese economy on the policy making brilliance of Beijing: please up your meds. The problem is simple. It was easy to seem brilliant when you had an undervalued asset (fixed currency) and people bought into your story.  Now that people have wised up and are asking difficult questions, Beijing has no clue what to do or handle the questions.  Now that they actually have to make decisions and trade offs, the reality has come out.  Like they always say about managers, it is easy to seem brilliant during the good times, but you prove your worth in the bad times.  We are getting an answer about Beijing’s ability and they are not doing well.

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.

Why China Does Not Have a Trade Surplus

Life has few certainties except for death, taxes, and large Chinese trade surpluses.  The expected large Chinese trade surpluses are always referred to as both proof of the strength of the Chinese economy and its financial foundation as money continues to flow in.  In nominal RMB terms, the trade surplus amounted to 5.5% of GDP or 79% of total GDP growth.  In other words, in 2015 China is almost entirely dependent on maintaining a large trade balance to drive GDP growth.

However, what if the assumed trade balance did not actually exist?  In fact, how would it change our understanding of the Chinese economy and financial markets if the assumed trade surplus was actually a trade deficit?  Unfortunately, this is not a counterfactual but the reality.  China is running a small trade deficit.

The widely cited international trade data is provided by Chinese customs records.  The value of goods leaving and entering and China is recorded by the Customs Bureau.  According to Customs data, China imported $1.69 trillion (10.45 trillion RMB) and exported $2.27 trillion (14.14 trillion RMB) for a resulting trade balance of $593 billion (3.7 trillion RMB).  These often repeated numbers form the basis for why China is running a large trade surplus.

Before explaining why China has no trade surplus, it is important lay some related groundwork.  By now China watchers knows about the practice of trade misinvoicing.  This is the practice where, as originally executed, capital was either moved into or out of the country based upon fraudulently invoicing an import or export.  For instance, by over invoicing an export, capital can flow into China as the foreign counter party is over paying for the good and vice versa for imports.

To take one example, of trade between Mainland China and Hong Kong, there are significant discrepancies between the value reported to Chinese customs and Hong Kong customs.  Hong Kong reported imports from China worth $255 million USD but China reported exports to Hong Kong of $335 million USD.  The 31% difference in customs prices, or $79 million, is too large to be unintentional and acts as a capital inflow into China.  Conversely, China reports $12.8 billion USD of imports from Hong Kong but Hong Kong only reports $2.6 billion USD of exports to China.  The 385% difference is far in excess of the low mid to single digit invoicing discrepancies that are standard in global trade.  Consequently, the $10.1 billion USD in over invoiced Chinese “imports” acts as a capital outflow from China.

Misinvoicing contributes a not entirely insignificant share to unrecorded capital inflows and outflows.  However, Chinese authorities have become much more aware and concerned about these issues and  gone through various waves of cracking down over this issue.  Furthermore, the aggregate sums here are not enough to move the RMB and cause the currency pressures we are currently seeing.  In fact, misinvoicing is merely the beginning of the financial flow problems in trade with Chinese innovation taking it a step further.

China, as a country with strict currency controls, maintains records on international financial transactions sorted by a variety of categories.  For instance, there is data on payment or receipt of funds by current or capital account, goods or service trade, and direct or portfolio investment.  For our purposes, this allows us to compare in a relatively straightforward manner, how international payments are flowing compared to the customs reported flow of goods.

The differences in key data surrounding trade data is illustrative.  Chinese Customs data reports goods exports valued at $2.27 trillion, with SAFE reporting goods exports of $2.14 trillion but Chinese banks report receipts of $2.37 trillion.  In other words, funds received for exports of goods and services or about $100 billion higher than reported.  At 4-11% higher than the Customs and SAFE reported values this is slightly elevated, but given expected discrepancies in the mid-single digits, this number is slightly elevated but not extreme.

The differences between import and international payment data, however, is astounding. Whereas Chinese Customs reports $1.68 trillion and SAFE report $1.57 in goods imports into China, banks report paying $2.55 trillion for imports.  In other words, funds paid for imported goods and services was $870-980 billion or 52-62% higher than official Customs and SAFE trade data.  This level of discrepancy is extreme in both absolute and relative terms and cannot simply be called a rounding error but is nothing less than systemic fraud.

If we adjust the official trade in goods and services balance to reflect cash flows rather than official headline trade data as reported by both Customs and SAFE, the differences are even worse.    According to official Customs and SAFE data, China ran a goods trade surplus of $593 or $576 billion but according to bank payment and receipt data, China ran a goods trade surplus of only $128 billion.  If we include service trade, the picture worsens considerably.  China via SAFE trade data reports a $207 billion trade deficit in services trade.  Payment data reported via SAFE actually reports about $42 billion smaller deficit of $165 billion.  In other words, the supposed trade surplus of $600 billion has become a trade in goods and services deficit of $36 billion.  Expand to the current, through a significant primary income deficit, and the total current account deficit is now $124 billion.

There are two very important things to emphasize about these discrepancies.  First, the imports customs and payment discrepancy is responsible for essentially all of the discrepancy between payments and customs.  Neither goods exports or differences between service imports at customs and payments explain the difference.  In fact, service is underpaid according to payment and customs data.  Second, if there was a more benign explanation, we would expect to see symmetry between various categories.  Rather, we see most categories reconciling close enough and one channel, conveniently enough one that funnels capital out of China, enormously mis-stated.

This discrepancy between official reported trade data and bank payments is a relatively new phenomenon but has been growing rapidly and reveals important details about flows into and out of China.  For instance, since 2010 China has an aggregate trade in goods and services surplus based upon payments of 1.9 trillion RMB; however, since 2012 an aggregate deficit of 120 billion RMB. 2010 and 2011 were the only years where China ran a trade in goods and services surplus using payments data rather than customs data.  Expanding to consider the current account significantly worsens the outlook.  From 2010 to 2015, China has run a current account surplus of 462 billion RMB but from 2012 to 2015 ran a deficit of 1.44 trillion RMB.  The reason for the shift is simple.  In 2012, China freed international currency transactions made through the current account creating an enormous asymmetry.

There are a number of important conclusions and implications of the data presented here.  First, if we adjust the Chinese traded good surplus on a cash flow basis and include the trade deficit resulting in a net export deficit, Chinese GDP growth in 2015 grew only 0.3%.  If a positive trade balance in economic accounting directly adds to GDP growth then a deficit directly reduces it.  Consequently, swinging from a goods trade surplus of 5.5% of GDP to a goods and services trade deficit of negative 0.3% of GDP has an enormous impact on GDP growth rates.  There is a key distinction here that is important to note and that is on a cash flow basis.  Economic accounting holds that GDP grows because when running a trade surplus, additional cash flow is received than is expended.  This leads to higher investment through savings. In 2015, financial flows indicate this did not happen and there was not trade surplus on a cash flow basis due to the discrepancy between Customs and SAFE reported trade in goods and services values and what banks paid.

Second, the impact on real GDP and output is currently unknown.  There are numerous reasons to question the veracity of numerous aspects of the data which would change our understanding of the data.  For instance, there are examples of goods round tripping into and out of China designed solely to facilitate implicit capital transactions.  Given the enormity of the discrepancy we see in payments for imports, we cannot rule out that a not insignificant amount of trade was either round tripping or phantom trade.  As physical output of many products from industrial to consumer only increased in the low single digits, this would match closer the implied Chinese growth rate of 0.3%.

Third, this sheds new light on the state of Chinese finances and RMB outflows.  For instance, the differential between Customs and bank data reveals rising outflow discrepancies since 2012.  While many have begun to worry recently about rising pressure on the RMB, it is clear that outflows from China are long lasting, large, and completely domestically driven.  In 2015 the capital account maintained healthy levels with the outward direct investment balance in a small deficit of 28.3 billion RMB while the securities investment balance was in an even tinier deficit of 2.9 billion RMB.  Consequently, calls for “temporary capital controls” or attributing it to a recent increase in outward direct investment reveal a profound misunderstanding of what the problem is. There is nothing temporary, foreign, or speculative about RMB outflows.  In fact, quite the opposite.  It is domestically driven long term capital flight which should change the framework of what solutions are called for in managing RMB policy.

Fourth, the change in the current account deficit is a major driver in changes to PBOC foreign exchange reserves.  While these are disguised capital outflows, for accounting purposes it is showing up in the current account statements.  Consequently, while China shows only small capital account deficit of $75 billion and a cash flow current account deficit of $121 billion, this shift largely explains the currency pressures on the RMB.  If you look simply at the Customs reported trade surplus, it would understandably be puzzling why the RMB is under so much pressure when China continues to run a $593 billion trade surplus.  However, in reality official flows are negative to the tune of about $200 billion in 2015.  Add in official net errors and omissions outflows in 2015 of $132 billion and it becomes quite clear why the Chinese RMB is under pressure.

Fifth, regardless the impact on GDP, it is quite clear that cash flows within the Chinese economy are very tight.  The boost from surplus payments that is typically seen from a trade surplus is not present and firms are struggling to pay bills.  Payables and receivables continue to rise rapidly as liquidity deteriorates.  Again we cannot say for sure whether this is actual production being purchased or simply phantom production, though it is likely some blend of the two. What is important to note is that liquidity is much tighter within the Chinese economy than understood.

Sixth, the nature of capital flight from China cuts directly to the heart of why capital controls would be a poor remedy.  Capital is not leaving through the capital account.  Rather with a restricted capital account and a relatively free international transaction via the current account, enterprising Chinese are moving capital via the current account.  To arrest the flood of capital leaving this way, it would require China to bring goods and services trade in the world’s second largest economy to a complete standstill.  Every transaction would have to be verified for units, market price, agreement between importer and exporter, and accurate payment matching the invoice.  It is simply not feasible to impose currency controls that would arrest disguised capital outflows via international goods and services payment without bring international trade in China to a halt.

It is likely the PBOC is aware of the discrepancy between Customs and SAFE reported trade data and what the banks are paying via the current account.  In his interview with Caixin, PBOC Governor Zhou Xiaochuan was very careful to say that China ran a “surplus in the trade of goods” rather than current account, trade surplus, or payments and receipts for international trade.  Many foreign and Chinese agencies and analysts confuse these multiple categories referring to them as one category but they are not.  His mention indicates he likely understands how capital is leaving the country and why capital controls would be a poor remedy which is also indicated.

It is quite clear that the expected $600 billion trade surplus is not hitting the Chinese economy for reasons and some implications that are still unclear.  What we can say, is that this is negatively impacting GDP growth and liquidity.

Data Diving on Inflation

So now that we have had some new data releases and I am back from vacation, we get back to what I still consider the meat of this blog, focusing on the data of the Chinese economy.  I have developed a general rule of thumb that if you a read about a Chinese statistic in the headline of a news article, it is most likely heavily manipulated.  To rephrase this slightly, if it is top line data, it is heavily manipulated.   One of the problems for people who have not spent enormous time looking at the data is that, to give credit to Chinese artists, they are very skilled at manipulating the data in a variety of ways that can make it difficult to detect.  Many times, you can only detect the manipulation looking at much more granular data, which in all fairness, simply aren’t available to most people. However, in some cases, even just looking at granular data on the NBS website and comparing it to top line data that should be a summation of lower level data, one can see the discrepancies.

One of the biggest ways that Chinese officials manipulate real GDP growth is by manipulating the pricing indexes.  There has been recent skepticism about the unchanging nature of the PPI flattening at 5.9% over the past few months given the continuing price declines in a range of products.  However, for the moment, I want to focus on the CPI basket weighting.

When building inflation rates, one of the key questions is how to weight each and every product of the basket.  Ideally, you have lots of micro-level data that gives you a very clear idea of how to weight individual products and classes of products.  For instance, food prices should still comprise a major portion of the CPI and budgetary basket as despite Chinese economic development, it still comprises a significant portion of most people’s spending.  The CPI weight should closely resemble people’s spending habits.

There is one other thing that impacts how we want to approach the Chinese CPI basket, there is something called Engel Curve that should provide us a good basis of comparison about how people spend their money.  The idea is really pretty simple in that the more money a household or country makes, the less they will spend on food as a percentage of income.  It is really quite intuitive.  Assume you make $1,000 per year, you will probably spend a pretty high percentage of your income simply keeping yourself nourished.  Now assume you make $100,000 a year, you will probably  spend a higher amount of money in absolute terms, say $500 increased to $2,000, but you will spend a significantly lower percentage on food in absolute terms, going from say 50% to 2%.  As households and countries become wealthier, they will spend less as a percentage of their income on food.

Emi Nakamura and Jon Steinsson of Columbia, currently on leave at MIT, have actually written a paper studying the Engel Curve and Chinese households (PDF).  They write about recent Chinese inflation that “official inflation rose in the 2000’s, but our estimates indicate that true inflation was still higher and consumption growth was overstated over this period.”  If true inflation was higher this would mean that real GDP growth was in reality overstated.  In addition sound empirical and theory based research that inflation is significantly underestimated, we can again look inside the Chinese inflation data calculations.

China began releasing its CPI basket based upon food and non-food items, though in 2011 it released the weightings for the non-food sub items.  In 2011, the CPI food weighting was 31.39%.  This 2011 weighting had fallen from the 2006 number of 33.60% and was expected to keep falling and relatively rapidly.  History, intuition, and wealth of global economic data said that this number should pretty quickly fall beneath 30% of the budget.  Right? Wrong.

In 2012 the food weighting in the CPI basket jumped almost to 32.21% and has risen about 0.5% every year since.  For 2015, the food weighting of the CPI stands higher than the 2006 number at 33.61%.  This stands is such complete contradiction to everything we know about economics that is belies any credibility.

There are a couple of empirical points to look at here.  First, from 2011 to 2014, average urban wages officially grew 34.8%.  From 2006 to 2014, urban wages officially grew 170.2%.  Oddly though, during this period, the amount of money spent on food, according to official statistics, actually increased as a percentage of income.  In reality, this seems distinctly unlikely as it would spell morbid obesity with Chinese characteristics for most of the country.  It isn’t rising that fast.

Second, if we actually believe these numbers, from 2011 to 2014, the Chinese consumer will have seen wages go up 34.8% but food spending go up by 44.4%.  Put into absolute terms, they would have spent about an additional 2,880 RMB or 5.1% of their income on food than if the CPI weighting had dropped by a similar amount instead of going up.  That is not an insignificant amount of income.  I know of no other country that would plausibly claim to triple wages and have people spend the same percentage of income on food as before.

Third, I can’t honestly explain why the food weighting has gone up though I have some guesses.  Given that food inflation in China runs higher than non-food inflation, which given PPI deflation isn’t a surprise, it could be they are trying to obfuscate realized deflation.  Another possibility is that food inflation is actually higher than admitted but by allocating a higher percentage of the CPI weight they can obfuscate the true impact by allocating the same absolute expenditure amount but change the internal percentages.  I will be honest in saying, I’m not really sure why.

Fourth, the inflation basket is riddled with other problems but this is one good example.  For instance, the residence component is only 17.8% of the CPI basket.  Not only is that number incredibly low by really any standard, I think you would be hard pressed to find anyone in China who would say that food has risen as a percentage of their income while housing is only 17.8% of their income.  Until 2011, Chinese residents supposedly only spent 13% of their income on housing, an absurdly low number for any country but definitely one in the midst of one of the most rapid price increases in housing in modern history.  The point however, is that how a CPI basket is weighted internally can have a major impact on the final number depending on what you are trying to accomplish.

Whenever you read of a headline number in China, do NOT, I repeat do NOT just accept it as fact but try and go beneath and figure out what is going on.  There is tremendous and important detail lurking just beneath the surface.

Catching up to the Chinese Economy

So I haven’t been writing that much the past two weeks primarily because of a minor wrist surgery two weeks ago.  In addition to some forced time off, forced me to play a lot of catch up to my existing commitments.  Drove me nuts, because there are so many interesting things going on in the Chinese economy right now that I really wanted to write a lot more.  So for the moment, you’ll be stuck with a grab bag of thoughts.

  1. China released its 2016 economic plan yesterday and while I’ve only read the news reports at this point, it quite frankly sounds pretty well reasoned, like they read this blog (definitely joking but also probably somewhat true), but very unlikely to actually occur. One thing I always tell people trying to understand the Chinese economy is that you absolutely should not take press releases as fact.  If they announce a GDP figure of X, only believe it after you have verified it.  Same thing goes for the economic plan.  From everything I have read, it actually looks rather sensible.  However, I believe the likelihood of it happening is quite low.
  2. I don’t say this for pure skeptic reasons but a variety of reasons, not least of which is just pure mathematics. Let me give you one example.  The plan notes the importance of deleveraging. However, they simply cannot deleverage and maintain GDP growth of anywhere close to 6.5%.  Let me give you a slightly oversimplified model that will explain why.  (I should re-emphasize this model is using easy ratios in an oversimplified model but it will clearly convey the idea).  Let’s assume that that GDP growth is 6% and credit is growing at 12%.  If they only want to slow leverage build up, not even delever, and cut credit growth to 8%, in our simplified scenario that would cut GDP growth to 4%.  Now let’s add in another wrinkle, one recent report had (again using a nice round number) 50% of credit being used to pay of old debts.  Let’s now assume that 6% of credit growth goes to GDP growth and 6% to paying off old debts.  If they cut credit growth to 8% (leaving 4% to fall on the 6%/6% division), if the entire 4% reduction fell on credit growth to pay off old debts, that could easily trigger a wave of defaults.  Conversely, if the brunt of that credit cut fell on GDP expansion and new capacity expansion (already problematic), that could easily torpedo any growth targets for 2016.  Remember, this still assumes total leverage is rising, just slower than before.
  3. This is the key point: I see absolutely no evidence that the Chinese government is prepared to either accept or even recognize that those types of trade offs are necessary. Beijing wants to believe that markets move in one direction and do exactly what you want them to do and that just isn’t reality.  One of the most fundamental laws of economics is that man has unlimited wants and limited means.  There is a very small number of people, firms, or governments to whom this does not apply in the course of human events.  Tradeoffs have to be made and at this point, I see no evidence that Beijing is prepared to recognize that tradeoffs need to be made and then make difficult decisions to make them.
  4. I have a profound belief that when the government of China wants something to happen, they will make it happen. This is not universally true but mostly true.  If they really aren’t interested, they will nod and agree and ignore.  As the saying in China goes: in China there are a thousand ways to say no, including many where people say yes.  Don’t watch the press releases but look at the results.  That is the only way to judge what is going on.
  5. Beijing is going to face some battles on implementing these plans like deleveraging for a few reasons. First, I truly believe they don’t really know what is going on throughout the country.  Even banks don’t know what is going on in their branches throughout the country sitting at the home office in Beijing.  News reports of major GDP fraud in the north east is the tip of the iceberg.  Imagine how bad the data is at lower levels that receive less public or major official attention.  Second, Beijing has not fundamentally changed the promotion incentives so officials have an incentive to focus on the old line metrics.  Before I get a bunch of nasty emails saying otherwise, ask yourself if a city official would get credit for improving environmental welfare by shutting down a polluting low capacity coal plant and putting people out of work and restructuring the assets and recognizing some bad loans? Are you kidding?  Consequently, even if Beijing really wanted this (which I don’t think they do), they would face real problems pushing this plan.
  6. I don’t like to say told you so but this is one time I will say it: I told you so. A week or two ago, Beijing released details of how badly inflated north east Chinese provincial GDP. There are a couple of things to note about this situation.  First, if you believe this is limited to the north east provinces, please get stronger meds.  Second, China who has been a serial adjuster of GDP upwards, hasn’t made any indication they plan to revise the problematic GDP downwards.  That would be unharmonious.  Third, faced with overwhelming even self admitted evidence the new defense of Chinese cherry red kool-aid  GDP drinkers is that, “this was at the provincial level not at the national level. National level data is still good.”  There are two separate and enormous problems with this argument.  A) This assumes that government statisticians in Beijing are pure as the driven snow, as ethical and honest as Mother Theresa, and have the conscious of St. Augustine worrying over the proverbial pear tree.  I just have to ask: who are you kidding?  A friend of mine who used to teach in China, told me a story about a Chinese class he taught where Chinese high school students believed the same thing about government officials (stop and ponder smart people holding the same opinion as indoctrinated Chinese high schoolers for a minute). When he pointed out that central government officials came from provincial appointments, the students would argue that they were promoted because they were so pure and untainted, at which point he would stop arguing.  Again, if you believe that central government statisticians are pure as the driven snow….get help.  B) Potentially more problematic, this assumes that even if central government statisticians are pure as the driven snow they can calculate what the true level of GDP or other statistic should be.  In other words, if you are an honest Beijing statistician, how to do you adjust data you believe to be faulty to what it’s true number is?  This is harder than it sounds for many reasons.  A Chinese auditing report earlier this year found state owned (at the central and provincial level) falsified financial records, no surprise so far.  What was surprising was that some falsified them to look more positive and some to make them look worse.  They did this depending on whether they were trying to hide money or get money.  In short, just assigning a 3-5% downward adjustment, as a simple example, wouldn’t work.  Furthermore, if Beijing suspects that the data they are receiving is false but then the submitter would know that Beijing would know that, so they clearly wouldn’t submit false data.  In short, there is a lot more randomness and one would have to assume super natural power of clairvoyance if official data is accurately corrected.  That also for many more reasons, is an enormous stretch.

If I can’t write again before Christmas….Merry Christmas to everyone.

Brief Note on Retail Sales and Bad Math

Something I always tell people is just how bad the basic math on Chinese statistics and very rarely do people believe me until I start giving them examples.  Yesterday, I came across a perfect example in retail sales that I saw on WIND but is also apparent on the National Bureau of Statistics China website.

China announced that retail sales for China were up for October from October 2014 by 11% and up year to date compared to the first ten months of 2014 by 10.6%.  Here is the interesting part, if you actually calculate the percentage you arrive at very different numbers.  For October 2015, China lists 2.827 trillion RMB in retail sales. For October 2014, China lists 2.397 trillion RMB in retail sales.  That is an 18% YOY change for the month of October not the official 11% change.

The year to date numbers exhibit the same problem.  Through October this year, official Chinese statistics pegged retail sales at 24.435 trillion RMB compared to 21.312 trillion RMB in 2014.  The official change in retail sales is 10.6% but if calculate the change in those numbers it amounts to a change of 14.7%.  In other words, October and year to date official retail sales numbers differ from the announced percentage change by 7% and 4% respectively.

Honestly, I have no idea what explains the discrepancy.  There are two obvious suspects but neither would seem to be the culprit of the discrepancy. First, I thought maybe they are possibly deflating by a retail price inflation measure.  However, that wouldn’t be standard practice and would enormously overstate retail price inflation.  Second, I then suspected maybe this has something to do with online sales.  However, this seems problematic for numerous reasons.  If this number is only brick and mortar retail sales, this will obviously and grossly overstate retail sales.  Furthermore, there is no indication that consumer product output or total retail sales are growing at 15%.  Additionally, the amount would seem to significantly understate online retail sales.  In short, the two obvious suspects don’t seem to explain the discrepancy.

I keep saying, maybe the NSBC should get some of those Shanghai math students to double check their work.

Update: Capital Economics has raised the distinct possibility that the NBS is changing what they measure.  By that, we mean that there were sales that the NBS did not include sales for whatever reason in previous year.  The NBS prefers to say that they have increased the scope of the operations to count more.  This is a very distinct possibility but it must be noted and stressed that there is no specific announcement on methodological changes.  Consequently, while they publish the raw retail sales volume, they publish only the adjusted annual percentage growth.  Why? Who knows, it is a Chinese statistical agency.  There are numerous examples of this type of recalibration in statistical methodology, typically with no announcement or explanation about the change.  It bears worth emphasizing again that the 11% retail sales is contradicted by a large array of data some of it even published by the NBS so even if this is the explanation, it certainly does not make the data any more reliable.

A Modest Proposal for an Employment Measure in China

If there is one area where even the most battle hardened China analyst is left with nothing it is labor market data.  Even the most Beijing loving, data believing kool-aid drinkers refuse to defend the accuracy of Chinese labor market data.  Even if you believe the long term average is accurate, which in all fairness, I believe there is a reasonable probability that the long run average is somewhat accurate, it is beyond ludicrous to believe the complete lack of fluctuation.

The problem however, is that there is virtually nothing else that people can use for data to look at employment.  Even in the data I’ve been able to find, about three to four years ago, industries reported aggregate numbers of people employed and that was stopped.  There simply is no good data or even solid proxies for employment.  Whatever you think of the Li Keqiang Index and electricity production as a good proxy of GDP, there was very little that could even come close to providing useful insight on Chinese labor markets.

I would like to propose a proxy for measuring Chinese employment.  Before I tell you what it is, let me emphasize that that there a numerous shortcomings that I can think of and probably some that I have not, so please do not take this as a perfect measure that is authoritative.  However, I do believe it can provide us some useful information and insight that should track some dynamics of the Chinese labor market.

For the industrial sector, there is a dataset that covers nearly 400,000 firms that will achieve a projected 11-13 trillion RMB in sales revenue for 2015 and manages almost 20 trillion in assets.  This is a very comprehensive and large dataset of firms and key financial metrics.  One of the variables is expenditures on administrative costs.  I would propose that changes in administrative costs will be able to provide us some insight into changes in Chinese labor market dynamics.

Let me explain some of the positives and negatives of this measure.  First, administrative costs will be strongly linked to labor inputs.  While there are hard administrative costs like information technology, travel, or office space, labor costs dominate administrative costs and are the most variable when compared to the other primary input office space.  Second, the internal components of administrate costs will be highly correlated with each other.  For instance, if you hire more office workers, you will on average need more office space, computers, and travel budget.  This is important, because we are less likely to see negative correlation between the internal components of administrative costs that will result in a funny top line number.  By that I mean, if labor costs rise by 10% and the other costs fall by 10%, resulting in no change.  That is less of a risk in this specific scenario.

Third, the administrative cost measure does not tell us the initial employment level.  Consequently, while we can impute changes in labor market using some base, say 100 at whatever initial time period I choose, it will not tell us the number of people that have been employed or unemployed.  Fourth, we can however impute the level of employment, again with some base say 100, based upon estimated wage changes.  To take a simple example if, we estimate that wages have gone up by 10% and administrative costs have also gone up by 10%, we can essentially impute there has been no change in the volume of labor inputs.  I have never seen academic or popular research on administrative costs, labor, and the other cost components so for now we have to use intuition.

Fifth, administrative costs provides insight but into a narrow slice of the industrial sector.  I say this because at this point, I am loathe to project this onto the entire Chinese labor market.  I am not saying it isn’t related to other sectors but until I have done more research, I want to recognize it for what it is: administrative costs in the industrial sector.  In fact, I am not yet even entirely sure how this relates to workers directly related to product output.  For instance, if a coal mine is facing a decline, it is possible administrative personnel will be laid off sooner than miners.  At this point, I am simply reserving judgment until more work has been done. It is very unlikely however that the two are negatively correlated so there is most likely a positive correlation.

Sixth, I fully recognize that this is somewhat of a blunt measure.  By that I mean, it would be best if we knew how many people were employed and how much they made and didn’t have other cost items in our measure.  Even if all other cost measures are perfectly correlated with labor, their inclusion will blunt our understanding and require additional calculations to impute details we are really interested in.    However, just as we shouldn’t project the importance of this measure too much, we need to understand that similar to electricity production, this is a blunt proxy.

In the past year, administrative costs in the industrial sector have increased by 5.2%.  Now if we take the accepted wisdom that wage are still going up by 7-10% and use the midpoint of 8.5% this would imply declines in overall labor inputs.  Even in a best case scenario this would appear to indicate wage growth with no growth in labor input implying some degree of increasing unemployment.

If we venture out a little into applying this the larger industrial sector, we can propose some tentative analysis. First, it would seem likely that there is growing pressure on industrial employment levels but not major decline in levels.  Output in most industrial sectors is flat or seeing small declines.  The prices of inputs are declining and especially in capital intensive industries where labor will play a smaller role. Given declines in capital and product input will offset some to a significant degree of wage increases, though there is clearly not only significant pressure but some declines in industrial employment.  Consequently, it is probable the bigger impact on the labor market is overall declining/flat industrial output and falling prices.  This combination is placing a lot more pressure on wages and employment levels, but so far unlikely to cause widespread unemployment.

Second, it is very unlikely that formal service sector labor growth is offsetting changes in industrial employment levels.  Financial services, transportation, hotel, retail sales, and real estate (not real estate construction) are not experiencing hiring booms by any means.  In fact most have flat or low growth revenue and output.  Financial services the only service sector with strong revenue and output growth for numerous reasons, is not witnessing a hiring boom and definitely not enough to offset declines elsewhere.

I plan to flesh out some of these issues but for the moment, just wanted to put out some of these ideas.  I think this does provide some insight into the Chinese labor market, definitely far more than anything else out there but please note the caveats.

Follow Up To Bloomberg Views on Growth in Chinese Data

In case you missed it, I have now started writing occasionally for Bloomberg Views which are going to typically do explore some slightly different ideas from what I will continue to explore here.  Thanks very much to Bloomberg for asking me and it will take on some more popular issues concerning China and Asia.  I will leave the nerdier stuff here on the blog.  I wanted to expand on some of the ideas in the piece on how data in changing China.

  1. China is not nearly as data poor as people believe. It isn’t as data rich as other place for sure, but there is a lot of available data if you have what are generally industry standard data tools like Bloomberg, Wind, or CEIC.  I rarely refer to things like electricity, seriously look at the blog all searchable, primarily because there is so much other data to explore and present.  Even on the NBSC website, which is still relatively sparse, there is lots of data that allows us to cross check some of the headline data.
  2. There is a lot of laziness among a significant portion of China economic and financial analysts. A lot of people simply haven’t stopped and looked at anything beyond the Li Keqiang Index in quite some time.  I want to strongly emphasize two things though.  First, I see this relative laziness with regards to data in people/firms that I both agree with and disagree with.  There are people/firms that I agree with that I also believe are lazy in how they arrive at their conclusion and people/firms that I disagree with that I have a lot of respect for who push me to dig deeper prepare better.  I say all this only because I don’t think data laziness is limited to what you are ultimately saying.  Second, a lot of this laziness is simply path dependence.  By that I mean people started using the LKI and stopped pushing the envelope to figure out what was going on.  Just as the Chinese market is changing, data variety, quality, and volume is rapidly changing.  There have been interesting new data added just within the last year.  You can’t be a good China watcher talking about a rapidly changing economy, financial market, and consumer and not stay on top of the flood of data releases and changes.
  3. A lot of people, especially foreigners who don’t live in China but even some that do, paint suspicion about the data as some foreign conspiracy about the Chinese economy. What is so strange about this theory is that in China, there is almost zero trust in official data, though virtually no one will say so publicly.  When I arrive in China it never occurred to me that official data would be anything less than a good faith effort to gather data with the typical statistical errors that accompany any large data.  In fact, it was my Chinese students that first advised me not to believe official data.  As noted in the Bloomberg article, there are many examples of Chinese not believing official Chinese data and with good reason.  This is not some strange theory but accepted fact inside China.
  4. My primary beef with a lot of China analysts is that they simply don’t look at the data. Get away from top line official data and then tell me what you find.  It is no coincidence that the further you stray from top line official data like GDP and Retail Sales the more convinced you become that the economy is much weaker than is being portrayed.  Retail sales aren’t growing at 11% annually and GDP isn’t growing at 7%.  There are actually GDP estimates where they use they other major top line numbers and arrive at 7%.  Seriously, explore the data.
  5. It is no coincidence that the market has stepped into provide more data. Chinese investors and firms don’t trust the data and are generating ways to find more accurate tools to assess what is going on.  You simply can’t have a modern economy using such poor quality data and Beijing while Beijing is trying to make people you can have a modern, service sector, knowledge economy without accurate information or access to knowledge.  Think about that contradiction.

Official Data Doesn’t Reflect Any Underlying Data

As the slowdown is so widely acknowledged, perma-pandas now focus on service sector and consumption growth to meet the 7% growth target.  Given the relative lack of data covering the service sector, some have taken to using the non-manufacturing purchasing manager indexes produced by both the Chinese National Bureau of Statistics and the Caixin version for better information.

As with most Chinese data these days, there are increasing discrepancies between the official and unofficial measurements.  There is typically in recent months about a divergence of approximately 3 points between the official and unofficial measures.  There has however been no analysis as to what is causing the divergence.  The reason for the divergence after even a cursory review is readily apparent.

The official NBS non-manufacturing PMI is comprised of nine different components.  There are some rather unique characteristics that raise the question of political influence over the PMI but also how we can interpret it in light of the questionable construction.

First, of the nine individual components used to construct the official non-manufacturing PMI, only one component in the past year is ever above the monthly average.  It seems rather problematic as an accurate representation of the service sector that one measure would swing a multi-component by itself.  While he measure may provide useful information by itself, it seems to skew our understanding of the health of the service sector by relying so heavily on one component.

Second, not only was the Expected Business Activities Index an outlier, it was an extreme outlier.  The average of the Expected Business Activities Index was 59.9 over the past 12 months while the non-manufacturing PMI was only 53.8.  In other words, it was on average 6.1 points higher than the average.

Third, even given the extreme outlier nature of Expected Business Activity, it still required underlying statistical manipulation to meet the headline number.  This was accomplished by overweighting the one variable that was above the average even by so large an amount.  Though we can’t know exactly how they weighted all nine components, if we take a simple model where all other eight components are weighted identically and Expected Business Activity is overweighted, we can arrive at a plausible estimate.  Using this simple technique, I find that Expected Business Activity would receive a 36% weighting with all other components receiving an 8%.  In other words, Expected Business Activity is 4.5 times more important than any other variable.

Fourth, what makes this specific variable all the more unique in this context is that it does not measure actual business activity but rather the expectation of future business activity.  In fact, if we look at specific measures of business activity, the index tells a decidedly different though not depressing picture.  Over the past year, new orders, new export orders, and employment all hover right around 50.  The In Hand Orders Index is actually beneath that at 44.7 meaning there may be a difference between reported new orders, completion, and shipping to customers.

Given the problematic nature of the official service PMI index, I now turn to placing this in the larger context and what information this can provide us.  First, if we exclude the extreme outlier or use a straight average, the official PMI comes much closer to matching other data points.  For instance, it is much closer to the Caixin Services PMI of 50.5 compared to 49.3.  The difference is now -1.2 compared to 3.7.  Furthermore, it comes much closer to matching broad revenue growth in service sector industries which has been in the low single digits.  Despite the perma-panda argument that services are compensating for the decline in industry, a revised non-manufacturing PMI would actually match rather closely the revenue and consumption growth we are seeing in the tertiary sector.  In other words, if we correct for the official service PMI discrepancy, it comes much closer to matching other data points.

Second, I actually don’t want to rule out the very distinct possibility that the future expectations number is an accurate measurement.  It is such an outlier as to warrant some skepticism and the underlying weighting manipulation is undeniable, but the belief in future growth I think may be reasonable.  Unlike Americans near psychotic belief that everything will always improve with hard work, the version with Chinese characteristics is that people have become so accustomed to rapid growth that they don’t even entertain the possibility that any investment will yield less than 15%, sales won’t go up by at least double digits every year, and jobs will continue to increase.  That is not hope in the future but the undeniable birth right expectation that students and business owners have.  While this brings a host of other problems including risk management and the weight of expectations on political leaders, that is the state of belief.  Consequently, I do believe this could very well at least be close to an accurate measure.

Third, these PMI levels generally match what we know about  revenue growth of both listed and unlisted firms.  Revenue growth in broad and narrow sampling is flat to small declines on a year over year basis.  Despite outlandish and ill informed propositions that the 50 PMI only represents  “dividing line not between growth and recession, but between accelerating and slowing growth.”  50 does represent the dividing line between expansion and contraction as can clearly be seen on the Caixin releases and recognized the world over as the dividing line between expansion and contraction.  In short, these adjusted PMI levels come close to matching both other PMI measures and revenue growth.

Manipulating weightings or underlying data is actually a common technique to manipulate official data because most people do not actually verify the components or internal weightings.  Weighting problems manipulation are common in Chinese data.  In one notable instance, official data uses an 80/20 urban/rural weighting on CPI for China beginning no later than 2000 even though it was almost 70% rural at the time.

People who fail to actually study Chinese data remain convinced that the only variable Chinese data critics use is electricity consumption. As someone who works with Chinese data, the problem is that it is just too easy to point out the glaring manipulation of data.  It isn’t crazy techniques, other data, or conspiracy theories that reveal official Chinese data to be riddled with holes but Chinese data itself.

Note: The data used as always is transparent and available here. Next week I will do a more thorough analysis of GDP and just how manipulated it is.