Academic journal article NBER Reporter

Experimental Indexes of Leading and Coincident Economic Indicators

Academic journal article NBER Reporter

Experimental Indexes of Leading and Coincident Economic Indicators

Article excerpt

Annual Research Conference--I:

Experimental Indexes of Leading and Coincident Economic Indicators

The index of coincident economic indicators is a weighted average of several broad monthly indicators of current economic conditions. The index of leading economic indicators is a weighted average of a set of series that signal future changes in overall economic activity. My NBER research project with Mark W. Watson of Northwestern University takes a fresh look at these two indexes and develops new alternatives to the present Department of Commerce (DOC) indicators.

Although coincident and leading indicators currently are produced by the DOC, this is a fitting research project for the NBER. Indeed, the genesis of these indexes was a report written 52 years ago by Wesley Clair Mitchell and his research Associate Arthur F. Burns. That report developed the system of coincident, leading, and lagging indicators that has led to the indexes currently produced by the DOC.

Watson and I started this project with two broad questions: first, how should we construct indexes that provide a timely and interpretable forecast of the state of the economy over the next six months? This question is motivated by the practical problem of using the DOC index of leading indicators to forecast a recession. For example, the rule of thumb that forecasts a recession if there are three consecutive declines in the DOC's monthly leading index is neither timely nor precise. Thus we focused on producing direct forecasts of short-term overall economic growth and of the probability of a recession.

Second, we asked which series to include in constructing these indexes. At a deeper level, how should we decide which series to include and which to exclude? The traditional approach to selecting series for the leading index basically has been bivariate; that is, comparing series one at a time to movements in the coincident index. In contrast, our approach to variable selection is multivariate. It focuses on picking series that have important predictive content on the margin: that is, that have predictive content given the other series in the index.

Three New Experimental Indexes

Our project has resulted in three new indexes. To distinguish them from the indexes produced by the DOC, and to emphasize that this is an ongoing research project, we refer to these as "experimental" indexes. The first of these indexes is the experimental index of coincident indicators (XCI). Like the coincident index produced by the DOC, the XCI is designed to measure --on a monthly basis--the current level of overall economic activity. The second index, the experimental leading index (XLI), forecasts the growth of the XCI over the next six months, scaled to provide annual rates. This index is computed using a revised set of leading variables. The third index, the experimental recession index (XRI), represents a new concept in the context of coincident and leading economic indicators. This index estimates the probability that the economy will be in a recession in six months. Because it is a probability, the index can range from 0 to 100 percent.

Experimental Index of Coincident Indicators (XCI)

The XCI is plotted in Figure 1. Cyclical peaks and troughs, as determined by the NBER's Business Cycle Dating Committee, are indicated by vertical lines. Our XCI is quantitatively similar to the coincident index produced by the DOC. Like the DOC series, ours is a weighted average of four broad measures of economic activity: industrial production; real personal income (less transfers); real manufacturing and trade sales; and employee-hours at nonagricultural establishments. The index is scaled to equal 100 in 1967.

The two main differences between our XCI and the DOC coincident index are, first, that we use employee-hours rather than the number of employees and, second, that we put some weight on lagged values of these series. …

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