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.

Deflationary Prospects for China

I want to follow up on my Bloomberg Views article about how loosening money is not the method to reverse the deflationary pressures in China.  For space and technical considerations, I can’t quite go into the level of detail that as an economist I might otherwise.  Let me expand on some of the ideas I presented there.

  1. Deflationary pressures are driven by enormous surplus capacity. We could go industry by industry but there has been plenty of research on the topic of enormous historical investment.  Businesses are fighting to stay alive and how they do this is by lowering the price of their products.  I think one of the absolute clearest economic events currently is that Chinese industry is experiencing very low capacity utilization.  Numerous IB’s have produced charts on the relationship between the output gap and deflation and it is very clear.
  2. One of the ideas which I am still working through in my head and exploring in the academic research is that monetary policy is typically designed to address demand driven shocks. By that I mean, maybe the global economy reduces demand for a countries exports or there is some domestic shock that lowers demand.  Prices fall to meet the new demand equilibrium.  However, that isn’t what is driving deflation in China.  Yes, export demand is essentially flat but there has no specific change in the domestic economy with many arguing that consumer demand is increasing, something I do not believe the data supports.  Furthermore, the deflation pre-dates any change in demand (Chinese economy ‘new normal’) by a number of years.  All signs to me point that this is not demand driven deflation but supply driven producer deflation.  I’m not entirely sure that monetary policy is well suited to manage supply driven deflation.
  3. I don’t think it is entirely misplaced to say that China is in a deflationary environment. Producer prices are declining significantly at 6% and appear to only be accelerating.  Non-food inflation in China is under 1% and even consumer food CPI is under 2%.  Retail prices are essentially flat actually registering small decline in October YOY.  Given the extremely low CPI, RPI, and PPI numbers, here is why I say we should probably consider China to be in deflation.  The primary concern over deflation is the link between prices and debt.  For instance, if a family purchases a home and borrows some money and then they start making 5% less every year, the real price of that debt increases.  However, in China the vast majority of debt is linked to corporations, SOE’s, and government.  Household debt as a percentage of the total pool of debt in China is minimal.  So even if CPI isn’t truly deflationary yet, given where the debt lies, this simply doesn’t matter that much.  If debt and prices is the key link when considering the impact of deflation, we need to consider China in deflation because PPI, where most of the debt is held, is clearly in a prolonged and serious deflationary spiral.  If you weight prices based upon the debt breakdown, I would suspect you would have deflation of at least 2%. We need to rethink what we consider deflation.  Just because Chinese CPI isn’t negative, doesn’t mean China isn’t in full fledged deflation.
  4. Due to the deflationary pressures, it is quite clear what is happening in the Chinese economy is that loose money is being used to both continue to expand capacity (furthering deflationary pressures) and keep struggling firms alive (even further adding to the deflationary pressures).  In this environment, short of taking the monetary policy to grossly excessive stimulus levels and essentially inflating away the debt, it is very difficult to see how a stimulatory money policy pushing demand growth is going to prompt an increased price level.
  5. My thoughts are still somewhat fluid but I am beginning to be swayed that the deflationary period facing China is going to be quite prolonged and painful. This likely holds true for not just China but for the global economy from spillover effects in a variety of markets.  The enormous investment in the past decade that is still ongoing essentially time shifted large amounts of investment.  If China even returns to some type of normal for investment, this would have large implications.  For instance, this would signal a sustained downward shift in demand for investment inputs.  Given that 50% of Chinese GDP is still linked to investment, this would have an enormous impact on GDP.  Furthermore, given the enormous increase and overhang this implies many years of working through the overhang.  Even if China was to just stop building new things, it would take time to work through the surplus capacity through the trend increase in demand and retirement of depleted capital.  Conversely, if China attempts to keep growth rates high by maintaining incredibly high investment rates, we can expect greater deflationary pressures as more capacity comes on line.  Thinking even longer term, if you take an even longer term view and assume that China works through these deflationary pressures by 2020, at that point, China will be facing even greater population pressures.  Working age population has been falling since about 2012 maybe even 2011, so let’s say by 2020 the capacity issues are resolved, at that point China will have ten years of falling population furthering deflationary pressure. In short, I don’t believe there is any reason to believe that this is just a minor period that will quickly be reversed and prompt higher inflation.
  6. Ultimately, what do to is a purely political question. The PBOC is not independent and does not pretend to be.  Given the complete lack of real economic leadership or imagination in policy making and the necessity of political expedience, I believe you can fully expect investment to remain elevated and deflationary pressures to remain enormous.  This implies that not only will deflation be prolonged but there is little chance of it reversing and policies will quite probably exacerbate this.

Chinese New Year News

Apparently, I am not the only one coming up with better estimates for the reality of Chinese data.  One Chinese academic says that if a more representative methodology is used to record home prices in China it may increase “housing market appreciation by more than 100%!”  It is also worth noting this is from the China Daily not a foreign publication.  These data discrepancies have caused one research firm to estimate Chinese GDP at 6.1% in the 4th quarter rather than the officially report 7.7%. More some other time on why China needs to maintain such rapid growth but it is interesting just how many people are pointing out the Dragon Emperor has no clothes.

From departing Fitch Chinese shadow banking expert Charlene Chu comes this beautiful tidbit regarding asset management and bad loans:

The fundamental question with these asset-management companies is where are they getting the money to do their business. We can see on the asset-management-company balance sheets that much of their funding is coming from banks, so they are borrowing from banks to buy bad debt from banks. In that scenario, there isn’t any true risk transfer the way there was in the previous bank bailout when the financing for the nonperforming loan carve-outs came from the government. Instead, what we have is bad loans moving from banks’ loan portfolios into their interbank portfolios as a claim on an asset-management company. Over the short term, this disguises the bad debt situation. But over the longer term, if asset-management companies can’t repay their borrowing from banks, then bank capital is still at risk of loss….Fundamentally there needs to be a deeper recognition that most of the challenges facing the financial sector, including the liquidity issues we see at the moment, are related to asset quality problems. That’s regardless of what the nonperforming loan data say. The market recognizes that; that’s why the banks are trading at such low valuations.”

While credit problems loom in China, there are also larger underlying pressures to the real economy.  One of the biggest is wage pressures.  According to this Financial Times article Chinese “factories made clothes at half the cost of its facilities in Malaysia and Thailand but that gap has since disappeared.”

China wants to start policy think tanks which invites the obvious question: don’t you need to be able to think to have a think tank?  Jailing professors for pushing the government to require officials to disclose their personal wealth isn’t radical stuff, unless you have something to hide.

Update:  According to Goldman Sachs the Chinese banking regulator has issued a warning on all loans made to coal miners.  Remember, it is a Shaanxi coal miner that triggered the first wealth management product that defaulted which is currently under negotiations with investors.


The Audacity of Chinese Inflation Data

It is frequently difficult to grasp for many people just how invented most Chinese economic and financial data actually is.  In my paper, How Badly Flawed is Chinese Economic Data? The Opening Bid is $1 Trillion I present some of the many ways.  Let me give you one example in the bar graph below.

Each year represents the amount that food price inflation contributed to the overall consumer price index.  For example, in 2003 if we use the official weight for food prices, food price inflation would have been responsible for 100% of consumer price inflation.

In the 9 years presented, there are only two years where food price inflation represents less than 70% of total inflation.  If you add this up over the years, between 2003 and 2011, food price inflation was responsible for 99% of all inflation in China.  Another way to think about this is that the Chinese government is claiming that no other prices rose in China between 2003 and 2011!  In other words, prices in China except for food have not changed in a decade.

You be the judge.


Why Does Anyone Still Believe Chinese Data?

It baffles me with everything that we know about Chinese economic and financial data that people, and even smart people who should know better, continue to believe the Communist Party Propaganda press releases put out by Beijing.  The Reuters team writes:

“The slowdown in the rate of deflation was taken as further evidence of a possible stabilisation of the economy, with analysts looking to data later in the day on investment and industrial output for more signs of a bottoming out in activity.”

When you simply make economic data up, of course the numbers are always going to look good.  For about ten years, Chinese unemployment has bounced between 4.1-4.3%.  Now even accepting that Chinese unemployment has remained quite low throughout this entire time period, which in itself a dubious proposition, we expect more random variation than that.

Let’s take another example from my recent working paper How Badly Flawed is Chinese Economic Data? The Opening Bid is $1 Trillion, on how the National Bureau of Statistics in China (NBSC) calculates consumer price inflation and how they should calculate consumer price inflation (CPI).

CPI should be calculated based upon what the average consumer buys.  To take a simple example, if Honda sells a million cars a year in the United States and their prices go up by 2% annually, that should count a lot more than the 10,000 Bentley’s a year that go up in price by 5% annually.

Despite having the highest scoring high school math students in the world, it is apparent that none of these technically proficient students work for the NBSC.  Below is a table with the official raw data on price change in private housing with a break down by urban and rural residents where the previous year is equal to 100.  This pricing data is used to build the Chinese CPI.

Looking at the raw data from the NBSC, it is apparent there is some skewing of the total change to urban residents.  When you calculate the total price change with the implied weighting between the urban and rural population, the NBSC is significantly overweighting the urban population.  The NBSC between 2000 and 2011 gives an 80% weighting to the urban population with a 20% weighting to the rural population.  In 10 out of the 12 years, if utilize a straight 80/20 urban rural, the implied total number is within 1 one thousandth of a percent of the official number.

However, this 80/20 urban/rural weighting is not remotely representative of the Chinese population.  In 2000, China was nearly two-thirds rural and 2010 reached a fifty-fifty urban rural split.  In other words, the NBSC was mis-weighting the   rural population by nearly 50 percentage points.  This results in a not insignificant accumulated difference over time.  The already bogus data price data gets reduced even more in the price basket by overweighting the population with the lower price increase: urban private housing residents.  If we weight based upon the actual population weight rather than the Alice in Wonderland 80/20 urban/rural weighting, this raises the price of housing by approximately ½ of one percent annually of more than 5% cumulative difference.

While this total does not drastically alter the final Chinese CPI number, it definitely adds to it.  More importantly, it shows just how absolutely fraudulent the Chinese data is and how many layers the employ to manipulate the data.  It is not just manipulating the price data, which they do, but also how to weight that data and who it applies to.

Furthermore, you continue to add up all these little ways that the NBSC is fraudulently manipulating the data and you arrive at some pretty big numbers.  As the saying goes, a trillion here and a trillion there, and pretty soon, you are talking some serious money.

My New Working Paper on Bogus Chinese Economic Data

So after getting a bunch of questions about a blog post I did about bogus Chinese economic data, some challenging what I wrote and some just wanting to know more, I decided to give it a bit more formal treatment.  I put together a working paper entitled How Badly Flawed is Chinese Economic Data? The Opening Bid is $1 Trillion available here.

I plan on covering some of the major findings periodically over the next couple of weeks but Chinese is so fraudulently manipulated as to be Alice in Wonderland absurd.  Let me give you one simple example below in this table.

According to the official National Bureau of Statistics China (NBSC), the price of private housing in urban areas between 2000 and 2011 rose by a grand total of 6% with rural area prices grew slightly faster registering a 20% increase.  It needs to be emphasized that these are not annual numbers but rather the total increase in China in 12 years.  To anyone who is alive and has heard of China, these numbers are not simply questionable but downright comical and fraudulent.

It is also worth noting that according to the NBSC, approximately 70% of Chinese households are considered “private housing” occupants.  This means that the NBSC is saying about 70% of Chinese households have faced housing price inflation of between 6-20%.  More about this break down in a future post which is very interesting in itself.

The primary point of the paper is not simply to reveal more discrepancies in the Chinese economic data, which it does, but also to measure the impact of these fraudulent statistics on real economic activity.

If you don’t want to read the paper or hit the highlights, don’t worry I will be posting the greatest hits here over the next couple of weeks.

Enjoy and cross your fingers.