The United States has what is called a consumer driven economy; in other words spending by consumers provides a significant component of GDP. In America’s case consumer spending accounts for over 70% of GDP and here is a problem: if people aren’t working they aren’t spending. Unemployment in America remains at record highs while job creation lags overall, in some sectors such as manufacturing the rate is effectively zero.
The chart above shows total non farm job openings (JTSJOR, black line, % change year on year, measured quarterly reported annually) for the period January, 2002 through Q1 2013. The period was chosen to include two recessions. As the economy recovered from the Early 2000s recession (which ended November 1st, 2001) we can see jobs creation increased steadily, peaking out in July, 2004. From this point jobs creation steadily declined until the US economy entered The Great Recession in December 2007. After the Great Recession ended in June, 2009 once again the economy created jobs steadily, hitting a peak in July, 2010. And from there jobs creation has trended steadily down, is recession far off?
While the media continues an incessant stream of happy news reiterating the mantra “things are getting better”, I try to look at a broad range of indicators to get a true idea of the state of economy. So you think “things are getting better” do you? Enough to quit your job? Perhaps without another lined up? After all, if things are truly getting better, you might be inclined to take some time off, then start your job hunt. Well, the data shows otherwise.
The chart above shows a metric called “Quits”, (JTS1000QUR, black line, measured monthly) from January 2000 to March 2013, with the vertical grey bars indicating recession. We can see between the Early 2000s recession and The Great Recession voluntary separations (aka “quits”) averaged 2.3% of the unemployed. After The Great Recession quits averaged 1.7%, telling us that voluntary separations have dropped some 26%.
Moral of the story? Folks just aren’t quitting their jobs at the same frequency as they did before The Great Recession. Maybe its because they were frightened by the intensity and duration of the recession, perhaps its because they’ve recently found employment after being out of work for a protracted period of time.
Or maybe things aren’t really “getting better”?
The chart above shows US Gross Domestic Product for the period 1973 to 2013 (GDP, thick black line), with recessions indicated by vertical gray bars. For each period of economic expansion I’ve added a flat trend line, essentially identifying the level of US GDP as if the recession had never happened. You’ll notice that with the exception of the most recent (rightmost) recession, GDP quickly recovers.
But its a curious thing about The Great Recession, which ended in June, 2009 – almost four years later, US GDP is way off track. In fact, US GDP is roughly $1T lower than it should be, if GDP has recovered as quickly as it had during previous recessions.
What’s the difference? We have never intervened in the financial markets like we’re doing now. We have never run such large deficits like we’re doing now. With each round of stimulus The United States is not only running out of financial rope, the increase in GDP is weaker than the one before.
Sure, the stock market is booming, but not the economy. Does stimulus really work?
Most of the happy news about GDP looks at quarterly changes, but a broader perspective reveals a different story. The chart above shows real1 GDP from January, 1947 to the present. I’ve calculated the average GDP for the period of economic expansion in the table below. The present period of expansion is the second weakest on record, surpassing only the early 1980s recovery, which itself was hampered by relatively high energy prices after the 1979 energy crisis, as well as record high interest rates under then Federal Reserve Chairman, Paul Volker.
So what is the cause of the current anaemic economic performance? Of course nobody is totally sure, but the major difference between this and other periods of economic expansion is, of course, the US Government’s interference in the markets and excessively high deficits.
This will not end well.
 GDPC1, real GDP, average during period of economic expansion, 1947 to 2013
1 Inflation adjusted.
I’ve previously written about America’s mythical manufacturing revival so here is the latest installment off the back of Friday’s job numbers.
How many jobs were created in the manufacturing sector in April?
Precisely ZERO.
Seems like the sector is driving increases in productivity over increases in employment.
Unemployment is a notoriously controversial topic and The Bureau of Labor Statistics, BLS (unintentionally) complicates matters by publishing no fewer than six instead of one single metric. The media widely publishes U3, or the total unemployed plus “discouraged workers” but ignores broader measures such as U6, which reports all unemployed, as well as those “marginally attached to the labour force” (i.e., temporary jobs) plus those who are working part time but can’t find full time employment.
Another problem – unemployment numbers month to month are volatile but BLS publishes a series I like to look at that addresses this problem – four month moving averages of US Unemployment, broken down to the state level.
The two charts above present U3 and U6 for all states, tracked as a four month moving averages across the period Q2, 2012 to Q1, 2013. For each chart I’ve baselined the vertical axis at the lowest rate observed, and sorted the remaining states in ascending order. Finally, I’ve identified the US national four month unemployment rate.
Click to expand each image. Regardless of how today’s unemployment number shakes out, remember the underlying data is volatile so sometimes its better to look at a moving average rather a single snapshot result.
A combination of the latest US GDP numbers failing to inspire and The Fed’s waffling on further stimulus (seriously, if the economy were on track they should be talking about decreasing further debt purchases) has led people to begin to question the current policy of relentlessly increasing debt.
Just to clarify things I thought I’d take a look back at overall US borrowings and growth. The chart above shows two series: first, Real Gross Domestic Product (GDPC1, black line) compared with the Debt/GDP ratio coincident with GDP (GFDEGDQ188S, red line), measured quarterly for the period 1966 to 2013. Periods of recession are indicated with vertical grey bars. For each period of growth I’ve presented two numbers – real GDP and the overall percentage of Federal Debt to US GDP.
Wrong. The Fed is buying. But let’s look deeper: the latest news on US housing was promising, with prices gaining some 9.3% YOY in 20 cities. An old expression claims as housing goes so goes the US economy so what’s not to like about this picture?
Unfortunately, much of this growth is being driven by direct intervention of the US Federal Reserve in the private mortgage market, specifically by purchases of mortgage backed securities. Last week alone The Fed purchased $13.1B of MBS’, and has been using cash flow generated by these securities to purchase additional MBS’. These interventions have the effect of artificially lowering mortgage rates thus artificially increasing demand. Do these lower rates reflect the true risk / reward profile that lending institutions strive for when offering mortgages? I don’t think so and the bank’s themselves DON’T HAVE TO WORRY, as they have a ready guarantor – The Federal Reserve – who purchases some $40B a month of the all the MBS’ they can create. The chart above shows the scale of The Fed’s intervention meddling. The black line, MBST, shows the dollar value of the securities held by The Fed. From $0 before 2009 they’ve added over $1T of MBS’ in a very short period of time. And even more worrying – since November 2011 after beginning to wind down their positions they once again started adding. Why? You’ve got to wonder.
So yes, its no wonder housing is booming. To the point that some folks are openly speculating about another US housing bubble.
Almost anytime governments interfere in the markets we end up with imbalances.
So where’s the inflation?
As documented in this blog and elsewhere, as one of the policy responses to The Great Recession the United States sharply increased it’s money supply. Generally, as the the supply of money increases so does possibility of inflation. However official metrics of inflation show historically low measures, leading some to suspect governments of manipulating or otherwise suppressing the truth. While manipulation of single indices calculated by government or private organisations is, of course, a possibilityreality (*cough* the LIBOR scandal), controlling prices across entire global markets is something completely different, I would suggest to the point of impossibility.
The term “soft commodities “ refers to agricultural commodities, compared to other commodities such as metals. The chart above shows the year to date returns of six soft commodities, specifically sugar, wheat, coffee, corn, soybeans and cocoa. Clearly with the exception of cocoa all soft commodity prices are declining to a greater or lesser extent. Sugar, for example, is showing a year to date change of -10.26%, or an annualised rate of roughly -53%, while soybeans are falling at an annualised rate of roughly -0.61%. Cocoa is the only commodity series that is increasing at roughly 16% annualised but that is explained away by a forecasted shortage.
Evidence of deflation? We’ll have to see how pronounced these declines are going forward, but they are hardly supportive of inflation.
Obama has proposed making fundamental changes to the way that various government benefits such as Social Security are adjusted for inflation. Specifically, its been proposed that the existing metric, the Consumer Price Index (CPI) be replaced with a different metric known as “Chained CPI”. What’s the difference?
The chart above shows two series: the Consumer Price Index (CPIAUCSL, black line) and Chained Consumer Price Index (aka, “chained CPI”, SUUR0000SA0, blue line), monthly for the period 2003 to 2013. To make the differences easier to understand I’ve based line each series at 100 in 2003. The vertical grey bar identifies the period of The Great Recession, which ended in June, 2009.
Some observations: across the period in question, CPI averaged about 1.32% higher than Chained CPI. The largest difference, 2.74%, was observed in December of 2012. Over the past year the difference between CPI and Chained CPI averaged 2.16%.
A visual inspection of the graph seems indicate the gap between CPI and Chained CPI is widening and this is supposed by looking at the numbers: before The Great Recession the difference between CPI and Chained CPI averaged 0.75%, while after The Great Recession the difference between the two series averaged 1.96%. Since July of 2012 the difference has been greater than 2%. Further,
in 57 of the 121 months during the period in question the difference was greater than 1%, and it exceeded 2% for 23 of the months.
Clearly by switching to Chained CPI the government will save money, both on a monthly basis but also in terms of the compounding effects of the reduced payments over time. I’m not totally sure why the difference between the two series is widening so I’ll dig deep into this as time permits.
Switching to Chained CPI isn’t a new idea; the switchover was first identified in 1996 by The Boskin Commission. The fundamental idea underlying Chained CPI is that as prices change people switch the goods they acquire, but these qualitative substitutions aren’t properly modeled.
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Who am I? 
As you might have guessed, my name is Dave Coker. I'm an ex-expatriate New Yorker who has lived in London since 1997.
I've worked in Investment Banking since the early 1980's, starting my career in New York with Dow Jones . I next moved to Deutsche Bank, where I spent the bulk of my career as Vice President of Global Risk Management. While at Moody's I was responsible for Professional Services in Europe, The Middle East and Africa, and was responsible globally for resources. While at ABN AMRO I was Global Programme Manager Risk Management Technology. Needless to say, I've seen Investment Banking and financial services from a wide variety of perspectives.
I take a long view towards finance and economics. I believe past events - the study of economic history - can help us understand current market events.
Internationally educated, I'm completing a PhD in Finance (Zurich), currently hold an MSc in Quantitative Finance (London), an MBA (London), studied Mathematics & Computer Science at the Undergraduate level (New York), and, most importantly, I've been a lifelong Student of the Markets.
I currently write and sell market commentary to several banks and hedge funds, consult on Credit Risk to a Global Tier 1 Investment Bank, and teach finance as a Visiting Lecturer at Universities in England, France and Austria.
I'm a polished and effective public speaker, sometimes presenting on finance as many as six or eight times a week. I've also made several media appearances over the past two years, once again on the subject of finance.
I enjoy discussing pretty much anything in the Capital Markets space. If you'd like to chat click here to drop me a line!
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