An economic indicator whose peaks and troughs in the business cycle are thought to lead subsequent turning points in the general economy or some other economic series. But do they really? Here is what William J. Bennett, former U.S. Secretary for Education, said about the U.S. Census Bureau’s Index of Leading Economic Indicators in the Wall Street Journal on 15 March 1993: "These 11 measurements, taken together, represent the best means we now have of . . . predicting future economic trends." This appears to be a common viewpoint on leading economic indicators. Research on leading economic indicators began in the late 1930s. In 1950, an index of eight leading indicators was developed using data from as far back as 1870. Use of the method spread to at least 22 countries by the end of the century. By the time the U.S. Commerce Department turned the indicators over to the Conference Board in the early 1990s, there had been seven revisions to improve the data. There has long been criticism of leading indicators. Koopmans (1947), in his review of Burns and Mitchell’s early work, decried the lack of theory. Few validation studies have been conducted. Auerbach (1982), in a small-scale test involving three-month-ahead ex-ante forecasts of unemployment, found that the use of leading indicators reduced the RMSE slightly in tests covering about 24 years. Diebold and Rudebusch (1991) examined whether the addition of information from the Composite Leading Index (CLI) can improve upon extrapolations of industrial production. They first based the extrapolations on regressions against prior observations of industrial production and developed four models. Using monthly data from 1950 through 1988, they then prepared ex ante forecasts for one, four, eight, and twelve periods ahead using successive updating The extrapolations yielded a total of 231 forecasts for each model for each forecast horizon. The results confirmed prior research showing that ex post forecasts are improved by use of the CLI. However, inclusion of CLI information reduced ex ante forecast accuracy, especially for short-term forecasts (one to four months ahead). Their findings are weak as they come from a single series. In general then, while leading indicators are useful for showing where things are now, we have only weak evidence to support their use as a forecasting tool. For more on leading indicators, see Lahiri and Moore (1991).