It was suggested to me that charting intermodal and total carload freight doesn’t give a good enough picture of what is occurring. Below are charts of the 18 categories that the Association of American Railroads report. I don’t believe that smoothing is necessary for this data. For example it is quite clear that changes occur in some categories over memorial day, July 4, labor day, thanksgiving, and Christmas/New year. I don’t see the need to try and smooth these drops in activity away. In the charts below the color code is 2007 — black; 2008 — orange; 2009 — green; 2010 — blue.

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rail freight

Rail freight data for week 7 of 2010 was released today and at this stage there still doesn’t seem to be any signs of a recovery or “green shoots.” The drop in carloads in week 7 was attributed to a sharp drop in coal loadings. Cumulative carloads to date in 2010 are down 17.2 percent from 2008. I’m not sure how people can account for the state of rail freight when they spin about “green shoots” or “V shaped” recoveries.

(charts made with Mathematica)

rail freight

Subtitle: “Evidence that Deutsche Bank analysts don’t know calculus”

A recent article in the Wall Street Journal titled “Some Good News on Jobs: Tax Withholding Improving” seems to have installed some confidence in bulls and left bears scratching their heads. The article contained a figure showing year-on-year tax receipts. Here it is:

The brief article contains this quote:

“The tax data, which are reported daily by the US Treasury, are particularly valuable to us because they are not subject to revision. Over the past 3-4 months, the plunge in tax receipts has reversed sharply. While still down in year-on-year terms (-2.5%), the lengthening recovery in tax receipts strongly supports our view that net positive hiring is very near—probably not in the February figures (due to weather), but increasingly likely when the March jobs data are reported on April 2.”

What everyone, including Deutsche Bank, are ignoring is that this is a difference curve, in this case year-on-year difference. Year-on-year comparisons make the most sense presumably because of seasonality in tax payments to the IRS. A difference curve is basically a coarse grained derivative,i.e. large steps instead of infinitesimally small steps. For those who didn’t do calculus at high school a derivative gives you the rate of change of something, basically the change of something with respect to the change of something else. The key thing to know about derivatives is that when things become negative at a slower rate this is manifested by an upturn in the derivative plot. This is best illustrated in the figure below where on the left some quantity is dropping and eventually levels out — but at a level much lower than it started. On the right is the derivative of that declining plot. Looks kind of “V” shaped doesn’t it.

The chart shows why difference plots can give a false sense of what is occurring. In the example above the “V” shaped recovery is really only saying that things have stopped getting worse.

Here is a chart of employment numbers from the Bureau of Labor Statistics [BLS].

It doesn’t look good does it. No “V” shaped up-turn in employment numbers. Hmmm, hang on, what does the year-on-year change look like?

That’s better! Signs of a “V” shaped recovery!

Tax receipts should be correlated with employment. Everyone agrees on this, right? In the next two charts I’ve overlayed the YOY employment data with the YOY tax data in the Deutsche Bank chart. I did two plots with varying opacity so that the correlation is clear to all (this is actually easy to do using Mathematica).

So the YOY employment numbers are actually pretty well correlated with the YOY tax receipts. Tax receipts appear to lag 2-4 weeks as you would expect. The thing is we know that the actual employment situation is bad yet YOY employment numbers are correlated to YOY tax receipts. The answer of course is that employment numbers seems to have stopped dropping, in other words it has stopped getting worse (for now). The same goes for the tax receipts in the Deutsche Bank chart. This isn’t a “V” shaped sign. All it means is that tax receipts have almost stopped falling.

To return to the quotes at the start of the article

“…the plunge in tax receipts has reversed sharply…”

Well if you want to put it that way. Actually all that has happened is it has stopped getting worse.

“…the lengthening recovery in tax receipts…”

Sorry, tax receipts haven’t recovered. You are confusing a slowdown in the decline with a recovery.

So bears can breath a sigh of relief, bulls can return to the search for signs of a recovery, and economists can continue to plot difference curves and tout them as “V” shaped recovery signs!

——————-

As a postscript here are charts of real and nominal social security and medicare taxes and the YOY changes of those taxes. Note that tax receipts jump sharply in January.

calculus · debunking · Deutsche Bank · employment · taxes · Wall Street Journal

Here is a figure is taken from an ABARE quarterly report.

The bars are the spread, in US dollars per metric ton, between copper prices on the London Metal Exchange (LME) and the Shanghai Futures Exchange (SHFE). The orange line shows China refined copper imports in kilo tonnes. This chart was originally created to show that when arbitrage opportunities exist between the LME and the SHFE, China increases its imports of refined copper. Note that trade on the SHFE is restricted to Chinese firms and commodities held on mainland China.

I wanted to combine that data with some more recent data I had, and that presented a problem — how can I get this data out of the chart. Last year when I read this blog post I thought that what was presented could be modified to created a plot digitizer. Since I didn’t have any plots to digitize I didn’t give it any further thought — until now. After a little bit of trial and error I came up with the function below which has been designed solely for measuring in the y axis only: (more…)

BarChart · copper · LME prices · mathematica

Another great article from Matt Taibbi: Wall Street’s Bailout Hustle .

“Goldman Sachs and other big banks aren’t just pocketing the trillions we gave them to rescue the economy – they’re re-creating the conditions for another crash“

fraud · Matt Taibbi

Paul Solman from PBS Newshour interviews with William Black.

Links to an interview in early 2009 with William Black: video and transcript. He is the author of The Best Way to Rob a Bank Is to Own One: How Corporate Executives and Politicians Looted the S&L Industry.

banks · fraud · Paul Solman · PBS · william black

The figure below shows the recovery in world trade since the global financial crisis. What seems to be occurring is that rather than a “V” shaped recovery in which trade returns to levels prior to the crash at the same, or similar, rates as the rate of decline, trade has resumed the same growth trajectory prior as to the crash. The failure of a “V” shaped rebound to occur is presumably a function of the amount of de-leveraging taking place and a general indication that a full recovery will be slow.

trade

On Friday the US Census Bureau announced the advance estimates of US retail and food services sales for January. The headline numbers quoted in the media was a 4.7% year-on-year rise. This is a seasonally adjusted number and I’ll discuss seasonal adjusting later in the article. Firstly I want to focus on the non-seasonal raw data. ZeroHedge were understandably skeptical of the upbeat number referring to it as “yet another economic data fabrication.” I view things slightly differently, more along the lines of an”economic headline fabrication”, i.e. issue a press release with a good number knowing that the media merely regurgitate the press release rather than analyzing the underlying data I’ve shown in a previous article that the raw, i.e. non-seasonally adjusted, data from this survey correlates well with sales tax data so I am comfortable about the raw numbers. The table below shows the situation in terms of raw data (sales revenue is in US$ millions):

Note that in these tables the columns run from Jan 09 to Jan 10, Jan 08 to Jan 09 and Jan 07 to Jan 08. So we’re still well down on pre-global financial crisis (GFC) metrics, however the numbers understate the decline because had a GFC not occurred nominal retail sales would have continued to grow through 2008 and 2009as we can see in the chart below:

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Consumption · retail sales

Paul Solman from PBS Newshour interviews with former Regan budget director David Stockman.

David Stockman is the author of Triumph of Politics: Why the Reagan Revolution Failed.

David Stockman · Too big to fail

In a previous post I mentioned downloading 1000 pages of data from the National Bureau of Statistics of China. So what should I do with that. What I actually wanted was data of freight and energy consumption but decided it was easier to get all that was available. The reason I wanted freight and energy was to get some idea of how general the growth in China is — given that there is skepticism in some circles about the actual numbers coming out of China. Of course there is just as much skepticism in similar circles about numbers provided by the US government. However uncertainty about the numbers doesn’t always point to blatant manipulation. For example the US GDP number gets revised as more and/or better quality information is received — curious that the revision recently seem to be on the downside though. In China the chief economist of the Hong Kong Chamber of Commerce recently suggested that the margin of error in the Chinese GDP number was 20%.

We know that China is apparently growing at a rate much greater than their 8% target. In response to the global financial crisis China went on a spending splurge that dwarfed the US stimulus, in terms of a % of GDP. Whereas the US spending packages were targeted as banks, home buyers and car makers China seemingly focused on infrastructure. Whether or not the infrastructure was needed is a separate debate.

Here is the chart of China’s freight movements over the last 5 years:

In this chart we see the steady growth in freight volumes prior to the global financial crisis — note the rise in December each year, the “blip” as the global financial crisis hit, and then the recovery in freight volumes during 2009. The recovery and growth in freight volumes in 2009 is consistent with infrastructure and construction stimulus.

The US went into recession during the global financial crisis but the government tells us we have had two successive quarters of positive GDP growth. The last quarter of 2009 was a sizzling 5.7% annualized growth according to US government number crunchers. I don’t have data on road transport but below is a chart of US rail freight from 2007, firstly intermodal freight:

…and carload freight:

The Bureau of Transportation Statistics says that

“… carload traffic is comprised mostly of bulk commodities, such as coal (46% of rail tonnage in 2001), agricultural products, and nonmetallic minerals and products, while rail intermodal transports a huge range of goods—from bicycles to automotive parts, lawnmowers to glassware, greeting cards to bottled water, and toys to computers.“

While China has a spike in freight each December, the US has a large dip at Christmas and smaller dips for July 4 and Thanksgiving. It is a bit early to call the rail freight trend for 2010 but it is clear that freight traffic has not recovered/bounced/grown to the same extent as GDP (or stock markets). In order to compare rail to rail here is the chart of China’s rail freight:

So what we have here is a story in which the pattern of freight volumes is consistent with the GDP story coming out of China, but as yet it is inconsistent with the GDP recovery story coming out of the USA. Of course data used here is supplied by the Chinese government and those who suspect manipulation of data, by either government, would point out that data such as freight traffic can be manipulated in China to be consistent with GDP growth whereas in the USA it cannot.

China · freight · rail freight