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August 2000

The leading index decreased 0.3 percent in August, and the coincident index increased 0.1 percent. Taken together, the composite indexes and their components still indicate a potential weakening trend in the German economy.

  • The consistency and breadth of the declines in the leading indicators caution that continuing strength in the German economy may be at risk, but the small magnitude of the decline over the past six months reduces concern.
  • Despite this weakness in the leading indicators, the growth in the coincident index remains strong.

LEADING INDICATORS.  Six of the nine indicators that make up the leading index decreased in August. The most significant decreases—in order from the largest negative contributor to the smallest—are CPI for services, yield spread, change in inventories, and new residential construction orders. The most significant positive contributors to the leading index in August—in order from the largest positive contributor to the smallest—are applications for unemployment insurance and new orders for investment goods industries. (For details see data availability section and tables). 

With the decrease of 0.3 percent in August, the leading index now stands at 106.1 (1990=100). Based on revised data, this index decreased 0.8 percent in July and decreased 0.3 percent in June. During the six-month span through August, the leading index declined 1.8 percent, and four of the nine components declined (diffusion index, six-month span equals 44.4 percent).

COINCIDENT INDICATORS.  Two of the five components of the coincident index increased in August. The most significant increases—in order from the largest negative contributor to the smallest—are gross domestic product and industrial production. Unemployment rate and retail trade remained steady in August. (For details see data availability section and tables).

With the increase of 0.1 percent in August, the coincident index stands at 108.5 (1990=100). Based on revised data, this index increased 0.4 percent in July, and 0.1 percent in June. During the six-month period through August, the coincident index increased 1.9 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 September 27, 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:
September data ... Thursday October 26, 2000

All releases are at 9:30 A.M. EDT

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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

Leading Index Factor
1. New Orders, Investment Goods .0604
2. Applications for Unemployment Compensation .0287
3. Yield Spread, 10 Year minus 3 month .3352
4. Change in Inventories .0999
5. Gross Enterprise and Property Income .0828
6. Stock Prices .0311
7. New Orders, Residential Construction .0415
8. Growth Rate for Consumer Price index for Services .2079
9. Consumer Confidence Index .1125


Coincident Index Factor
1. Manufacturing Sales .0605
2. Gross Domestic Product .3519
3. Industrial Production .0898
4. Retail Sales .0879
5 Unemployment Rate .4099

Notes:  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.)

The 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.

To 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.