AIER has developed a system for forecasting changes in business cycles and publishes the results in the first Research Report of each month. This four- part web series, which will run on consecutive Fridays, describes this system and is adapted for the web from a March 2007 Economic Education Bulletin.
Many techniques have been developed for predicting changes in economic activity. We have found the analysis of selected statistical series to be useful in forecasting reversals in business cycles just prior to or shortly after their occurrence and in forecasting continuations of trends.
The method behind using statistical indicators is to find economic series that consistently lead, coincide, or lag turns in business activity. The leading indicators can be used to forecast turning points in the cycle. The coincident indicators define the turning points; the lagging indicators confirm cyclical turns in business activity.
A change in the trend of business activity is more difficult to forecast than a continuation of trends. The economy is always changing, and the past is not a sure guide to the future. Moreover, the statistical indicators would provide little or no warning of a sudden economic collapse precipitated by, say, a natural catastrophe or financial shock. Nor does the statistical indicator approach provide a basis for forecasting magnitudes of changes in any aspect of economic activity.
To qualify as a useful indicator, a statistical series must have economic relevance, and its data must be collected and processed in a statistically acceptable way. The data should be fresh and not subject to frequent revision. The series must move reliably with general business activity and exhibit a consistent pattern over time as a leading, coincident, or lagging indicator.
We have chosen 24 series—12 leading, 6 roughly coincident, and 6 lagging indicators. Most reflect activity in the goods-producing sector. Goods-producing industries are more cyclically sensitive than service-producing industries and are more apt to signal turning points in the business cycle.
In this posting, we describe AIER’s leading indicators. Although the leading indicators are useful for forecasting turns, advance warning may be short. As the late Geoffrey H. Moore, renowned business-cycle economist, said, “The leaders often tell you where you’re going only about the time you get there.”
Leading Indicators (All dollar-denominated series are adjusted for price inflation.)
M1 money supply. An estimate of money balances (primarily currency and demand deposits). When M1 does not keep pace with inflation, bank lending may contract, and hence economic activity.
Yield Curve Index. The cumulative total of the monthly spread between the 10-year Treasury note and the effective federal funds rate. When the yield on the 10-year note is lower than the effective federal funds rate, the index will turn downward (i.e., the yield curve inverts), a signal that interest rates and the economy are headed even lower in the future.
Index of manufacturers’ supply prices. The percentage of purchasing agents who report paying higher prices in the current month compared with the preceding month. A higher index indicates stronger demand for business inputs relative to their supply.
New orders for consumer goods and materials. All new orders for goods and materials used primarily by consumers (less food and energy). The placing of such orders tends to precede production of consumer goods.
New orders for core capital goods. The value of new orders received by manufacturers of nondefense and non-aircraft capital goods. The placing of such orders tends to lead machinery production and production of the goods that machinery later produces.
New housing permits. Tends to lead construction expenditures.
Ratio of manufacturing and trade sales to inventories. The balance between sales and inventories. Faster inventory growth relative to sales suggests a structural imbalance within the manufacturing sector.
Vendor performance. The percentage of purchasing agents who experience slower deliveries in the current month compared with the preceding month. Slower deliveries indicate a higher volume of business activity.
Index of common stock prices. Uses monthly averages of daily indexes of closing prices from Standard & Poor’s 500 stock composite index. Changes in stocks prices reflect changes in investors’ opinions of profit prospects. Index is adjusted for price inflation.
Average workweek in manufacturing. The total of paid labor-hours of manufacturing production workers divided by the number of such workers. Employers tend to reduce the workweek of their labor force before they reduce the size of their workforce.
Initial claims for unemployment insurance. Inverted for analysis. Measures the average number of persons who file first-time claims for unemployment compensation each week in a given month. A decline in general business activity leads to layoffs.
Change in consumer debt. Percent change in the amount of consumer debt outstanding during the month from the amount three months earlier. Consumer debt includes auto loans and credit card debt, but not home mortgages or home equity loans. Borrowing is a source of consumer purchasing power.
In Part Two
, we will describe the lagging and coincident indicators.