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I
have been speaking with Rick Davis at the Consumer Metrics
Institute about leading economic indicators. Davis
claims his data leads the GDP by about 17 weeks while noting that other
so-called "leading indicators" are merely a reflection on the stock
market and yield curve.
Davis captures his data solely from online transactions of real consumers, in
real time.
Here are a four charts. The first chart shows the Consumer Conference Board
LEI, not the Consumer Metrics Index.
Consumer Conference Board LEI vs. S&P 500
Davis writes:
Is the conference board LEI really leading anything or is it merely a
reflection of the stock market? A look at the actual values of the LEI and
the S&P 500 over the last four years confirms the indicator is really a
coincident indicator for the equity markets, published once a month, three
weeks in arrears.
Weighted Composite Index (WCI) vs. S&P 500
The above chart shows the Consumer Metrics Weighted Composite Index (WCI) vs.
the S&P 500 Index. Watch what happens when the above data is offset by 5
months.
WCI vs. S&P 500 Shifted 5 Months
The Consumer Metrics website shows most of the WCI components advancing.
However, housing and consumer spending account for roughly 60% of the index
and those are contracting.
It is hard to make a case on the basis of so little data, but at least since
2006 we see evidence of actual leading.
However, the stock market does not always follow the economy nor is the stock
market a leading indicator of the economy.
Please see Is the Stock Market
a Leading Indicator? for a discussion.
Thus, as interesting as the above chart may be, I would not recommend using
Consumer Metrics Data to project stock market movements. However, when a
stock market is as lofty as this one, and a recovery is priced in that is not
likely to happen, I would expect the stock market to decline if the economy
tanks.
Daily Growth Index (DGI) vs. BEA GDP
The above chart shows Consumer Metrics Daily Growth Index (DGI) plotted
against GDP.
According to Davis the DGI is 91-Day moving average of the WCI that
corresponds to a trailing 'quarter', and is translated from a 100-base number
into a +/- percentage. For example 99 on the WCI would roughly correspond to
-1% on the DGI.
Rick Davis writes:
Hi
Mish
I wanted to provide you with an update on our measurements of the consumer
economy, which have continued to weaken since we spoke two weeks ago. On
February 13th our "Growth Index" (which we use as a demand-side
proxy or analog for a real-time "GDP" index) had dropped to an
annualized contraction rate of 1.25%, down nearly a half-percent since we
last spoke.
Since the most recent official GDP data from the BEA were running about 17
weeks behind our Growth Index, I assume they will continue to lag that far
behind for the next two quarterly GDP updates.
If so, I have the following predictions.
Prediction 1: On April 30th the BEA will announce that the 1st Quarter 2010
U.S. GDP grew at about a 2.5% rate. This approximates our growth index's
value on November 30th, 2009 - 17 weeks prior to the 1st quarter's end.
Prediction 2: On July 30th the BEA will announce that the 2nd Quarter 2010
U.S. GDP contracted at about a 1% rate. This is a projection of where our
Growth Index will be on February 28th, 17 weeks before the end of the 2nd
quarter.
Methodology
Discussion
Consumer Metrics data comes solely from online transactions. As such it has
many obvious biases that Davis points out in a follow-up Email.
Hello
Mish
I will not disclose proprietary methods as to exactly how we capture data but
I am willing to say that we are monitoring only U.S. consumers who are transacting
in English on the internet. As you know, this causes some demographic
sampling biases, but it has many advantages as well.
Sampling Biases
A) Our consumers may be educationally, economically and socially skewed
relative to the entire U.S. population and economy.
B) We are tracking only discretionary durable goods ordered, purchased, or
financed via the internet. This means that we are not capturing many
significant sources of spending: groceries, non-discretionary medical
services, some utilities, gasoline, non-reserved entertainment or dining,
items ordered by phone or mail, bills paid by conventional check, etc.
However, in spite of some sampling biases, we have many advantages.
For example, consider the problem of inventory measurement in cyberspace vs.
a few decades ago. In 1960 someone might take a clipboard and measure music
industry inventory by going to the local record shop and counting Doris Day
45's in various bins. Shipment of those 45's may have been captured some
weeks earlier in a rail car loadings report.
Today we have a different question. How do you count the inventory at the
iTunes store? How many of the units sold by iTunes were captured in any rail
car loadings report? Sticking with the rail car loadings for a moment: How many
books sold at Amazon will be captured at any stage past pulp and dyes? How
about the Kindle downloads? Are we expected to dismiss iTunes and Amazon as
irrelevant to the economy?
Our long term vision is nothing short of a complete revolution in the way
economic data is collected and reported. To that end we are working on a
number of initiatives that expand the scope of our indicators.
We are also looking at modern real-time analogs for inventories and
supply/demand pressures. Clearly eBay is a text-book model for the real-time
supply/demand processes in the economy, where an abundant number of standard
products can be placed in many different standard 'shopping carts' to monitor
pricing dynamics on a daily basis.
The internet is replete with potential sources of real-time inventory data,
from job postings on Monster to social inquiries on Craigslist. Mainstream
economists have not started thinking about ways to capture shadow inventories
or the underground economy.
Note that our Weighted Composite Index leads the S&P by about 140 days,
with a standard deviation of about a quarter of that (35 days). In contrast,
the conference board LEI is at best a coincident indicator.
However, the causative chain between consumer activities and subsequent
equity market movements is torturous and prone to many random and perilous
perturbations. Thus, historical time lags are not necessarily indications of
similar future lags.
Rosenberg
on the Consumer Conference Board LEI
Here is an interesting snip from Breakfast with Dave
on February 19.
LEADING
INDICATOR A GIANT HEADFAKE
The Conference Board’s leading economic index (LEI) rose 0.3 points in
January, to 107.4 — a new high on the level. But the good news started
and ended with the headline because the data beneath the surface were not so
constructive. The diffusion index collapsed to 55 from 100 — the
weakest breadth since March 2009. In fact, if not for the continued vital
contribution from the shape of the yield curve — it only has to stay
positively sloped to add to the index; it doesn't have to move — the
LEI would have actually dipped 0.1% last month.
While
the LEI is making new highs, there is little reason to believe it.
Rick Davis on the LEI
Rick Davis writes:
I
wonder how many people actually take the time to read the Conference Board
LEI Report and look at the data in it? The full
report itself is a mere 9 pages.
There are several things worth noting in the report:
1) Seven of the components were actually measured and three were statistical
"imputations". According to the release:
"To address the problem of lags in available data, those leading,
coincident and lagging indicators that are not available at the time of
publication are estimated using statistical imputation. An autoregressive
model is used to estimate each unavailable component."
2) The largest positive contribution to the index in January was the yield
curve, which has been providing a positive contribution continuously
throughout the entire recession.
Anyone buying the LEI at face value is buying into the proposition that a
favorable yield curve is sufficient to stimulate the economy.
3) The S&P 500 is among the five components
showing statistically significant increases during January. Table 2 of the
report, the LEI shows the S&P 500 rallied in January from 1110.38 to
1123.58.
Meanwhile, in the real world, the January price
movement for the S&P 500 was actually -3.70% (1,115.10 on 12/31 to
1,073.87 on 1/29).
The S&P 500 for January was the third largest
contributor to the LEI as noted in the February 18th release.
Timely,
Accurate Information Not
Inquiring minds interested in the above discrepancy found a description of
the lag problem in a Conference Board document written in 2002 called A More Timely and Useful Index of Leading
Indicators. Here are a few pertinent paragraphs
describing various problems.
"Most of the macroeconomic data for the United States require
considerable time to collect, process, and release. Lags of one month are
common for principal monthly indicators. For the quarterly data, including
the national income and product accounts (NIPA), the lags
are longer. Moreover, many of these indicators are subject to sizable revisions that are only realized over
long time intervals. The data revisions
presumably reduce measurement errors but
they add to uncertainty and forecasting errors, as do gaps and lags in the
availability of the data."
The paper went on to point out:
"At the same time, the publication lags and revision schedules vary
greatly and some indicators are everywhere available promptly. In particular,
financial market price and yield data are available electronically in real
time during each trading day. The U.S. leading index includes stock prices
and interest rate spreads that have no significant data lags and relatively
few, if any, revisions. The financial market indicators convey a great deal
of information with predictive value, yet, until recently, they were
represented in the leading index, not by their most recent monthly values,
but by their values in the preceding month for which data for other
indicators were also available."
According to the 2002 paper The Conference Board corrected that problem in
2001:
"In the old procedure, the index released during the current month (t)
referred to the month (t-2). In the new procedure, implemented by The
Conference Board since January 2001, the index released in the same month (t)
refers to the month (t-1) ... In our example, the old index would be
calculated in the first week of March (t) for January (t-2), the month with a
complete set of components. The new index would be calculated in the third
week of March for February (t-1), the month for which 70 percent of the
components are available and 30 percent are forecast."
Major
LEI Problems
·
Lags
in Availability of Data
·
Sizable
Revisions
·
Gaps
·
Measurement
Errors
·
Belief
the S&P 500 leads
With so many lags and gaps, even if the LEI indicators did lead, what good is
it if the indicators are going be revised away later and the components are
either a month old, fictional, or imputed to start?
Real World Indicators
With the consumer confidence present conditions index crashing to a low last
seen in February 1983 (see Is Consumer
Confidence a Contrarian Indicator? for details),
there is no good reason to believe consumers will be doing a lot of heavy
lifting.
Unemployed consumers typically do not spend a lot of money and Weekly Unemployment
Claims Spiked To 496,000.
Couple that with the fact that New Home Sales
Unexpectedly Plunge to Record Low it should not be
too hard to envision a flat to negative GDP decline in the second or third
quarter unless things turn around right now.
Finally, in light of the fact that economists are an amazingly optimistic
these days (save a small group of notables like Dave Rosenberg, Steve Keen,
and Nouriel Roubini) expect any economic surprises to be to the downside.
Throw away that V-shaped party hat. A stalled recovery or an outright
economic relapse is likely just around the corner.
Mish
GlobalEconomicAnalysis.blogspot.com
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