Archive for December, 2013

Digging in the Wrong Place

Tuesday, December 17th, 2013

[Raiders of the Lost Ark]

… The old wise man reveals writing on the back of the medallion for the Staff of Ra, which states that part of the staff must be removed before using it to locate the Lost Ark …

Indiana: Belloq’s medallion only had writing on one side? You sure about that?

Sallah: Positive!

Indiana: Belloq’s staff is too long.

IndianaSallah: They’re digging in the wrong place!


It seems to me that today’s Economics profession is “digging in the wrong place” – misreading the data and pursuing the wrong solutions.

Rather than print credit and deficit spend, what if we just enforced the laws governing competition a bit more strongly?

The Sherman Antitrust Act and related pro-competition laws need to be better enforced across large sections of the U.S. economy.  While there appears to this author to be enough price competition among the various international auto manufacturers (at least for the U.S. market), and also in computers/electronics, the same is not true of the majority of the economy. For many other major durable goods, for telecom services, for a wide variety of nondurable products and services (including TV, Radio and paper-based news!) there are really only a few corporate providers in any given market. (Did you know that just 3 companies control 9/10 of the market in soft drinks? That only 4 Pet Store chains have nearly 2/3 of the market share? And don’t even get me started on healthcare…)  Utilities are already regulated as local monopolies — but is the regulation truly pro-consumer?

A closer look is needed at consumer products, particularly in foods, and even including restaurant chains. A relatively small number of corporations are hiding behind myriad brand names. When one pulls back the veil of brand-name marketing and takes a close look at the corporate ownership and cross-linkages, the true picture is pretty grim. (My kids have earned my respect as good consumers by carefully reading the labels on the packages in the fridge, and saying words to the effect of “Oh no, it’s Kraft again!”) Furthermore, it’s clear from price trends (despite 5 years of very difficult economic conditions) that pricing power is being exploited. There’s also a lot of evidence of corporate titans buying up young upstarts, ostensibly to acquire new capabilities, but also having the net effect of suppressing new competition. Moreover, in the dynamic landscape of corporate maneuvers, there’s a noticeable trend in various industries, such as SEO services, where corporate titans are strategically acquiring young upstarts, ostensibly to gain new capabilities but also with the underlying impact of suppressing emerging competition. In addressing these issues, it is imperative to consider the implementation of effective Chicago SEO Scholar strategies to enhance visibility and competitiveness.

So perhaps economists should reconsider the idea that the U.S. economy might be suffering from a “shortage of competition”, with too many sectors dominated by “pricing cartels”. That idea has tremendous explanatory power to describe the overall economic situation.

Even without explicit cartel or monopoly power, it’s possible for corporations to act cooperatively against the national or consumer interest. (One can look at their industry-based lobbying outfits in Washington for more examples…) When corporations in less-than-competitive industries all push for higher prices (and lower wage expenses) and the result is maximum profits industry-wide, the consequence is that fewer goods (and services) are produced and sold. Supply is constrained by the high prices, and demand constrained by low wages, particularly when large swathes of the economy are affected.

This “high-price/low-demand equilibrium” has many observable consequences. With supply and demand both constrained, total output is below capacity, which means fewer workers are needed and unemployment stays elevated while median income lags. Corporate profits are at record highs as a share of GDP, yet household incomes are not improving. The same economic power which produces high prices and record profits/GDP also produces favorable tax laws for the corporations. With corporations and the very wealthy avoiding taxes, and households earning less federal tax receipts are reduced. The non-rich, suffering from declining standards of living, demand help. So the government deficit-spends to provide that help, and also to bridge the demand and employment gaps. All of these consequences are observed today.

If this is right, then the cure for the economy as a whole is not to be found in monetary or fiscal policy, but simply in nonfinancial policies aimed at increasing competition!

Increasing competition leads to lower cartel profits in the short term, but leads to increased employment and a healthier, more prosperous economy overall. When more companies compete to provide goods and services in a given market, they must provide the goods at lower cost and higher quality. With prices being lower, sales rise, and to produce the increased quantities being sold, more people must be employed. The workers can then afford to purchase more, creating a virtuous loop which results in much greater output and in fact much greater profits in the long run. Those would be Sustainable Gains!

This sort of argument is well-known from classical economics. There is a good explanation (in a historical context) in one of J.K. Galbraith’s books or essays, although I don’t recall which one. The concept goes back at least to Adam Smith, according to the treatment on Wikipedia. It is unfortunate that modern economists appear to neglect the issue. Do they think there is no need for economic policymakers to deliberately foster ample competition among producers?  Or do they simply assume that corporations will find ways to compete effectively without government intervention?  The evidence suggests that corporations, left to their own devices, concentrate more pricing power than is in the national interest.

Systematic Bias in Weekly Unemployment Claims Data

Friday, December 13th, 2013

The systematic bias in the weekly unemployment claims data has been increasing in recent years. Every week the BLS reports weekly claims to great fanfare, and at the same time the BLS quietly revises the previous week’s claims. The “preliminary” new data is compared against the revised “older” data to advertise any directional change. However, the data show that the revisions are almost always upwards, which is statistically impossible if the original claims estimate is done honestly.  In practice the result is that the media receive a report which compares the current lowball number with last week’s upwardly-revised number, and dutifully report “unemployment claims drop”. However, a large part of the time this simply isn’t true; the initial number is just wrong and claims are simply bouncing around.

I’ve done these types of analyses myself several times in the past several years and always found the systematic bias maddening. See my Oct 2012 comments on Economist’s View (reposted below).

The situation reminds me of how sometimes a store will raise prices (say by 20%), then mark the product as “On Sale” (say “10% off”) and fooling the buyer into thinking they’re getting a good deal.

I can understand the value of this sort of behavior in a competitive retail market, but we should expect more from our economic statistics. And from our news sources. Any workers in a discipline that claims to be a science (e.g. econometrics) or to be objective and factual (e.g. serious journalists) need to be really aware of these sorts of errors, and work to eliminate them.

I’m glad to see this issue is getting more attention.


Reprint of comment from October 2012 on Economist’s View (during the brouhaha surrounding the allegedly fraudulent pre-election employment situation report):

The BLS would have far more credibility if they did not frequently report misleading headlines that “weekly unemployment claims decrease”. Their practice of comparing current-week preliminary (lower) claims against prior-week revised (increased) claims invariably fails to mention the amount of the upward revision.

The weekly claims series has flatlined for essentially all of 2012, but not at a level consistent with strong employment growth. See CalculatedRisk for the plot:

Every single week, the prior week’s preliminary estimate is revised upward. See the table below. This makes the current week’s number look better in comparison, since the current week’s number has not _yet_ been revised upward. This is not simply a statistical outlier, but a systematic error which acts as a propaganda tool.

It is not uncommon for this fraudulent comparison to cause errors in the reported _direction_ of the change from the prior week. There are weeks when the claims are increasing (on an apples-to-apples basis), but they are reported as decreases because the comparison is made against the revised data. For instance, the report for the week of March 24 claimed a “decrease” in claims from March 17, but in fact the claims had increased. Again, see the table below.

Under the general premise that “there is never just one cockroach”, the presence of this statistically indefensible data series leads all reasonable observers to be skeptical of everything else put out by the same organization.

Date Initial Revised Increase(+) or Decrease(-)? ** = Flagrantly Wrong Headline
12/31/2011: 372,000 375,000 +
1/7/2012: 399,000 402,000 + large “jump up” due to seasonal adjustment error?
1/14/2012: 352,000 356,000 + large “drop down” due to seasonal adjustment error?
1/21 377,000 379,000 +
1/28 367,000 373,000 +
2/4 358,000 361,000 +
2/11 348,000 351,000 +
2/18 351,000 353,000 + ** increase made to look unchanged
2/25 351,000 354,000 + ** unchanged made to appear as decrease
3/3 362,000 365,000 +
3/10 351,000 353,000 +
3/17 348,000 364,000 + Anomalously large upward revision makes subsequent data look better
3/24 359,000 363,000 + ** increase made to appear as decrease
3/31 357,000 367,000 + Anomalously large upward revision makes subsequent data look better
4/7 380,000 388,000 + large “jump up” due to seasonal adjustment error?
4/14 386,000 389,000 + ** increase made to appear as decrease
4/21 388,000 392,000 + ** increase made to appear as decrease
4/28 365,000 368,000 + large “drop down” due to seasonal adjustment error?
5/5 367,000 370,000 + ** increase made to appear as decrease
5/12 370,000 372,000 + ** increase made to appear as unchanged
5/19 370,000 373,000 + ** unchanged made to appear as decrease
5/26 383,000 389,000 +
6/2 377,000 380,000 +
6/9 386,000 389,000 +
6/16 387,000 392,000 + ** increase made to appear as decrease
6/23 386,000 388,000 +
6/30 374,000 376,000 +
7/7 350,000 352,000 + large “drop down” due to seasonal adjustment error?
7/14 386,000 388,000 + large “jump up” due to seasonal adjustment error?
7/21 353,000 357,000 +
7/28 365,000 367,000 +
8/4 361,000 364,000 +
8/11 366,000 368,000 +
8/18 372,000 374,000 +
8/25 374,000 377,000 + ** increase made to appear as unchanged
9/1 365,000 367,000 +
9/8 382,000 385,000 +
9/15 382,000 385,000 + ** unchanged made to appear as decrease
9/22 359,000 363,000 + large “drop down” due to seasonal adjustment error?
9/29 367,000

P.S. It is most interesting that the “preliminary” data upon which the headlines are based is not tabulated with the revised data. One must read each press release and copy the numbers to see this effect. Sorry if my tabulation is not as clean as it could be.