Leading Economic Indicators

According to an article in World Almanac Book of Facts, 2003, leading economic indicators are those that lend to rise or fall in advance of the rest of the economy. The index of leading economic indicators is a composite of eleven economic measurements developed to help forecast likely changes in the economy as a whole. The conventional is as follows: Typically, three consecutive monthly leading economic indicator changes in the same direction suggest a turning point in the economy. The components are:

Building permits, durable order backlog,

The M2 money supply which includes all coins, currency held by the public, travelers checks, checking account balances, automatic transfer service accounts, and balances on deposit in credit unions, in addition to savings and small time deposits, overnight Repos at commercial banks, and non-institutional money market accounts.

Index of consumer expectations and consumer confidence, which is based on survey of several thousand households ("Index of Leading Economic Indicators", 2003, 107).

The index of leading economic indicators is intended to forecast or foretell economic activity six to nine months in the future. For this reason, the use of leading economic indicators to forecast eco

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accuracy where these leading economic indicators will be in eighteen months using traditional forecasting methods. Historically, when forced to create a model to forecast individual economic indicators eighteen months or further into the future, individuals performed linear regression analysis. Linear regression is a statistical technique for fitting a straight line to a set of data points. By using historical data, it would be possible to create a line that best fit each of the historical data points for the leading economic indicators through a technique that involves minimizing the sum of the squares of deviations between the points and the line. Once this was accomplished, the best fit lines could be extended eighteen months ahead and forecasts could be made. Ideally, one would incorporate sufficient data points to improve the accuracy of the analysis, and since authoritative six-month forecasts are available, there would be no reason not to use them in this regression analysis. Jagric explains that recent developments in nonlinear time series analysis have caused economists to examine the forecasting properties of nonlinear models in forecasting changes in leading economic indicators. He adds that present research sugg

Category: Economics - L