FOR WIRE TRANSMISSION: 9:30 A.M. EDT, THURSDAY,
JULY 27, 2000
GERMANY COMPOSITE INDEXES OF
LEADING AND COINCIDENT INDICATORS:
The leading index decreased 0.1 percent in June, and the coincident index
increased 0.1 percent. Taken together, the two composite indexes and their
components point towards a continuation of the expansion in Germany.
- The coincident indicators show that the economy
continued to expand through June, extending the strong growth pattern
exhibited over the past year.
- With the slight decline in June, the growth in the leading indicators
continued to slow, but the index remains well above levels from one year
LEADING INDICATORS. Five of the nine
indicators that make up the leading index increased in June. The most
significant increases—in order from the largest positive contributor to
the smallest—are applications for unemployment compensation, new orders
for investment goods industries and consumer confidence. The most
significant negative contributors to the leading index in June—in order
from the largest negative contributor to the smallest—are change in
inventories and the yield spread. Stock prices and the six-month smoothed
growth rate of CPI services remained steady in June. (For details see data
availability section and tables).
With the decrease of 0.1 percent in June, the leading index
now stands at 107.5 (1990=100). Based on revised data, this index increased
0.1 percent in May and decreased 0.3 percent in April. During the six-month
span through June, the leading index rose 1.0 percent, and five of the nine
components advanced (diffusion index, six-month span equals 55.6 percent).
COINCIDENT INDICATORS. Two
of the five components of the coincident index increased in June. The most
significant increases in order from largest to smallest are gross domestic
product and industrial production. Manufacturing sales, retail trade, and
unemployment rate remained steady in June. (For details see data
availability section and tables).
With the increase of 0.1 percent in June, the coincident
index stands at 107.7 (1990=100). Based on revised data, this index
increased 0.4 percent in May, and 0.5 percent in April. During the
six-month period through June, the coincident index increased 1.6 percent,
with all five series making positive contributions (diffusion index,
six-month span equals 100 percent).
DATA AVAILABILITY. The data series used to compute
the two composite indexes reported in the tables in this release are those
available "as of" 10 A.M. MET (Germany) on July 22, 2000. At the
time of the release, recent data for several of the series are based on
estimates. In the leading index, new orders for investment goods
industries, applications for unemployment compensation, yield spread,
consumer confidence index, change in inventories, new residential
construction orders and gross enterprises and properties income are based
on estimates. In the coincident index, recent data for gross domestic
product, industrial production, manufacturing sales and retail trade are
also based on estimates.
The schedule for the Germany Leading Economic Indicators news release in 2000:
|July data ...
||Tuesday August 29, 2000|
|August data ...
||Thursday September 28, 2000|
|September data ...
||Thursday October 26, 2000
All releases are at 9:30 A.M. EDT
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|Bart Van Ark
THE CYCLICAL INDICATOR APPROACH.
The composite indexes are the key elements in an analytic system designed
to signal peaks and troughs in the business cycle. The leading and
coincident indexes are essentially composite averages of between five and
eight individual leading or coincident indicators. (See below for details.)
They are constructed to summarize and reveal common turning point patterns
in economic data in a clearer and more convincing manner than any
individual component—primarily because they smooth out some of the
volatility of individual components.
Historically, the cyclical turning points in
the leading index have occurred before those in aggregate economic
activity, while the cyclical turning points in the coincident index have
occurred at about the same time as those in aggregate economic activity.
A change in direction in a composite index
does not signal a cyclical turning point unless the movement is of
significant size, duration, and scope. Historical analysis with U.S. data
shows recession warnings are best determined by looking for negative growth
of at least 1 percent, coupled with declines in at least half of the
components over a six-month span. Further explanations of the cyclical
indicator approach and the composite index methodology appear in The
Conference Board’s Business Cycle Indicators page:
Methodology and Revisions.
Germany Composite Indexes:
Components and Standardization Factors
||New Orders, Investment
||Yield Spread, 10 Year
minus 3 month
||Change in Inventories
||Gross Enterprise and
||Growth Rate for
Consumer Price index for Services
||Gross Domestic Product
The component factors are inversely related to the standard deviation of the
month-to-month changes in each component. They are used to equalize the
volatility of the contribution from each component and are
"normalized" to sum to 1. These factors were last revised effective
with the June 27, 2000 release, and all historical values for the two composite
indexes were revised at that time to reflect the changes. (Under normal
circumstances, updates to the leading and coincident indexes only incorporate
revisions to data over the past six months.)
factors above were calculated using 1973-1998 as the sample period
for measuring volatility for the leading index, and 1991-1998 as the
sample period for the coincident index. There are additional sample
periods as the result of different starting dates for the component data.
When one or more components is missing, the other factors are adjusted
proportionately to ensure that the total continues to sum to 1. For
additional information on the standardization factors and the index
methodology visit the following web page: Methodology and Revisions.
address the problem of lags in available data, those leading and
coincident indicators that are not available at the time of publication
are estimated using statistical imputation. An autoregressive model is
used to estimate each component. The resulting indexes are constructed
using real and estimated data, and will be revised as the data unavailable
at the time of publication become available. Such revisions are part of
the monthly data revisions, now a regular part of the U.S. Business Cycle
Indicators program. The main advantage of this procedure is to utilize in
the leading index the data, such as stock prices, that are available
sooner than other data on real aspects of the economy, such as and new
orders and changes in inventory. Empirical research by The Conference
Board suggests there are real gains in adopting this procedure to make all
the indicator series as up-to-date as possible.