One of the major reasons I expects sluggish growth and weak earnings is the secular decline in the growth of real net fixed nonresidential investment. The dominant factor driving productivity growth is workers being provided additional capital equipment to assist them. It is the old simple story of getting a ditch dug. Would you rather have a dozen men with shovels or one guy with a back-hoe to do the job? It is important to look at net, not gross investment, because more and more business capital spending is on high technology equipment. But high tech has a much shorter life span than traditional capital goods. Consequently, more and more of gross investment is just to replace obsolete equipment. We are having to run faster and faster just to stay even. The growth of net nonresidential capital equipment averaged 3.3% from 1950 to 1980 and 2.5% from 1980 to 2008. Over the past five years its’ average growth was 1.1%, or 0.0% growth on a per employee basis. No wonder productivity growth is so weak and is most likely to remain so..
Even with the rebound in second quarter growth, first half growth was still under 2%. Moreover, newly revised real GDP data reports even slower growth over the past few years. For some five years the consensus has forecast stronger growth right around the corner, despite the fact that it has consistently been too optimistic. This has clearly been the weakest economic expansion on record. On the other hand, the expansion is now 73 months old, which ties it with the early 2000s expansion as the fourth longest on record. The longer ones were the 1960s expansion of 106 months; the 1980s one of 92 months and the 1990s one of 119 months.
In recent weeks there has been much discussion about the seasonal adjustment factors for GDP understating growth. The evidence seems pretty strong and BEA says they are working on an adjustment.
But remember, the seasonal adjustment factor have to sum to one (1.00). If you change the seasonal adjustment factors to add two percentage points to first quarter growth you must also subtract two percentage points from the other quarters. Changing the seasonal adjustment factors will not change the annual value of GDP. If annual growth was reported to be 2.5% before the correction it will still be 2.5% after the seasonals are changed. This also means that the annual values for other economic data, like productivity will not change either.
Maybe the good thing that could come out of the issue is that people will give less weight to the volatile monthly and quarterly economic reports and more weight to the longer run growth rates.
Remember, the game of estimating monthly and quarterly data releases was originally started by the brokerage houses to increase volume — their profits are extremely sensitive to market volume.
Jeff Jacoby had an interesting article in the Boston Globe on Sunday where he argue that if the demand for something doubled the price must increase—it is basic introductory economics. What price is too high for a miracle drug?
His argument is so typical of how so many columnist and/or bloggers demonstrate that a little knowledge is a dangerous thing.
In basic theory many economist draw supply and demand curve that show if demand doubles the price will increase. But most are aware that this is actually a special case where all the assumptions of the perfect competition model hold. But, practical economists realize that this is a special case and that there are many exceptions to this theory.
Specifically, Jacoby writes that a doubling of a demand for a medical drug must lead to a price increase.
But the drug industry is a clear case where introductory economic analysis does not work because the drug industry is one of those industries where much of the cost of bring a new product to market is sunk or fixed cost. The specific sunk or fixed cost in the drug industry is the fortunes spent on research, development and testing before a new drug can be brought to market. These expenses are capitalized and incorporated into the price of a drug. The rough and ready rule of thumb is that these sunk or fixed cost account for about half of the price of a new drug. Exactly how much of this sunk cost is incorporated depends heavily on the estimate of how large the market for the drug will be. For example, if a drug firm has $1 billion in these sunk cost and they expect to sell two billion units of the drug they can assign $0.50 to the price of each pill for the sunk cost and another $0.50 for other costs of manufacturing, distribution, advertising, profits, etc., etc., so the final price is $1.00 per pill. But if the demand suddenly doubles, as Jacoby writes, the price does not have to increase. Rather the $1billion in fixed or sunk cost can now be spread over four billion units rather than original two billion units so the cost per unit falls from $.50 to $0.25. Consequently, the drug firm can cut the price of the drug from $1.00 per pill to $0.75 per unit and still make more profits than they did when the price was $1.00.
Jacoby’s analysis is a classic example that if so many bloggers or public pundits knew half as much as they though they knew, they would be geniuses. But the real problem is that the Globe editorial staff allows such shoddy analysis to gain the credibility it gets from being published in a highly regarded paper like the Boston Globe.
Jacoby claims that the doubling of demand for the drug Maloxone completely justifies the more than doubling of the price from $19.56 to $41.43 and that state officials should not investigate that increase. But maybe, just maybe, the state officials know something that Jacoby does not know.
The Census Bureau had a press release this morning announcing that nominal retail sales fell -0.6% in February, the third consecutive fall.
Wall Street economists,analysts, strategists and managers have been watching these weak retail sales reports and speculating on why the drop in oil prices has not lead to the boost in consumer spending that virtually everyone expected.
The problem is that the nominal data can be misleading. Few know that the Bureau of Economic Analysis (BEA) as part of its GDP calculation also creates an unpublished series on retail sales that will be available later this month. The BEA also estimates deflators for the various components of retail sales and an estimate of monthly real retail sales by category.
The BEA data is much better than the series of nominal sales deflated by the CPI available in FRED ( the St. Louis Fed. public data base).
Over the previous three months –November, December and January –both Census and BEA estimated that nominal retail sales fell 1.3%.
But the BEA data also showed that over these three months the retail deflator fell -3.34%. Consequently, the -1.3% drop in nominal sales
is actually a 2.15%increase in real retail sales, or almost 9% at an annual rate.
I expect when the BEA deflator becomes available the – 0.6% drop in February nominal sales will actually be a real increase.
The sharp decline in the retail deflator is not just oil. Almost every segment of retail sales except food stores and restaurants is showing a sharp drop in prices. In 2013 and 2014 the change in the retail deflator bounced around zero. But as of January the year over year change in retail sales prices fell to -3.3%. While the Fed is worrying about inflation and the Cassandras who have seen inflation right around the corner for years continue to forecast a massive inflationary surge, the data implies that deflation may be much more likely.
and gasoline was under $1/ gal.
The opponents of Obama-care just will not give up. Just because all of their claims of disaster over the last few years have been proven wrong they continue to repeat every claims that they think does not make them look foolish.
The latest example is John R. Graham of the Independent Institute who claims that Obama-care is hurting employment because of rising part time employment.
But I would suggest he really ought to look at the data. Part time employment has a very strong cyclical pattern.
It’s share of employment rises sharply in recession and declines in recoveries.
A major part of this cyclical swing is driven by changes in employment in different sectors. For example, the average workweek in retail is 30.1 hours, almost exactly where it has been for decades. In leisure and hospitality it is 25.2 hours and in education it is 32.0 hours, where they have been for decades. But in manufacturing the average workweek is 42.1 versus 39.7 at the recession bottom. In construction it is now 39.6 hours as compared to 38.8 hours at the recession bottom. So when the cyclical downturn causes employment in the strongly cyclical like manufacturing and construction while employment in the industries that traditionally use a lot of part time employes remains relatively stable the share of part time employees in total employment rises sharply. This is why the chart shows that part time employment’s share of total employment rose sharply in the Reagan and Bush recessions. It is also why part time employment share of total employment has fallen under Obama — it is a perfectly normal cyclical economic pattern.
(chart below the fold)
I keep seeing references to the 1970′s stagnation that reflect a consensus belief that real GDP growth in the 1970s was significantly lower in the 1970s than in the 1980s.
But this is contrary to the data:
REAL GDP GROWTH( % )
Yes, the 1970s had a serious problem with inflation, but that does not negate the fact that real GDP growth was actually higher in the 1970s than in the 1980s. We need a different term to correctly describe the 1970s rather than stagnation.
So why do knowledgeable economist like Krugman not recognize that applying the stagnation term to the 1970s creates a false impression about our economic history.
I can not believe the nerve of Greg Mankiw posting a blog about the Veterans Administration having problems.
He suggests giving Vets a voucher.
I suggest that he should apologize to all the Vets for the War and Tax cuts policies that were implemented while he was at the White House that created the problem he is referring to.
But I guess Republicans do not believe they ever have to take the blame for the problems they create.
The Bureau of Economic Analysis has been working on creating state and metro cost of living indices for several years and they have just published a new set of them that can be used to create real per capita income comparisons between states.
In their press release they show a map comparing real growth in 2012 that ranged from plus 12.7% in North Dakota and minus -2.3% in South Dakota.
But I found the ranking of the states real per capita income much more interesting.