This article throws light upon the top six theories of business forecasting. The theories are: 1. Theory of Economic Rhythm 2. Action and Reaction Approach 3. Sequence Method or Time Lag Method 4. Specific Historical Analogy 5. Cross-Cut Analysis 6. Model Building Approach.

Theories of Business Forecasting:

  1. Theory of Economic Rhythm
  2. Action and Reaction Approach
  3. Sequence Method or Time Lag Method
  4. Specific Historical Analogy
  5. Cross-Cut Analysis
  6. Model Building Approach

Business Forecasting: Theory # 1.

Theory of Economic Rhythm:

This theory propounds that the economic phenomena behave in a rhythmic manner and cycles of nearly the same intensity and duration tend to recur. According to this theory, the available historical data have to be analysed into their components, i.e. trend, seasonal, cyclical and irregular variations.


The secular trend obtained from the historical data is projected a number of years into the future on a graph or with the help of mathematical trend equations. If the phenomena is cyclical in behaviour, the trend should be adjusted for cyclical movements.

When the forecast for a year is to be split into months or quarters then the forecaster should adjust the projected figures for seasonal variations also with the help of seasonal indices.

It becomes difficult to predict irregular variations and hence, rhythm method should be used along with other methods to avoid inaccuracy in forecasts. However, it must be remembered that business cycles may not be strictly periodic and the very assumptions of this theory may not be true as history may not repeat.

Business Forecasting: Theory # 2.

Action and Reaction Approach:


This theory is based on the Newton’s ‘Third Law of Motion’, i.e., for every action there is an equal and opposite reaction. When we apply this law to business, it implies that it there if depression in a particular field of business, there is bound to be boom in it sooner or later. It reminds us of the business, cycle which has four phases, i.e., prosperity, decline, depression and prosperity.

This theory regards a certain level of business activity as normal and the forecaster has to estimate the normal level carefully. According to this theory, if the price of commodity goes beyond the normal level, it must come down also below the normal level because of the increased production and supply of that commodity.

Business Forecasting: Theory # 3.

Sequence Method or Time Lag Method:

This theory is based on the behaviour of different businesses which show similar movements occurring successively but not simultaneously. As such, this method takes into account time lag based on the theory of lead-lag relationship which holds good in most cases.


The series that usually change earlier serve as forecast for other related series. However, the accuracy of forecasts under this method depends upon the accuracy with which time lag is estimated.

Business Forecasting: Theory # 4.

Specific Historical Analogy:

This theory is based on the assumption that history repeats itself. It simply implies that whatever happened in the past under a set of circumstances is likely to happen in future under the same set of conditions.

Thus, a forecaster has to analyse the past data to select such period whose conditions are similar to the period of forecasting. Further, while predicting for the future, some adjustments may be made for the special circumstances which prevail at the time of making the forecasts.

Business Forecasting: Theory # 5.


Cross-Cut Analysis:

In this method of business forecasting, the combined effect of various factors is not studied, but the effect of each factor, that has a bearing on the forecast, is studied independently. This theory is similar to the Analysis of Time Series under the statistical methods.

Business Forecasting: Theory # 6.

Model Building Approach:

This approach makes use of mathematical equations for drawing economic models. These models depict the inter-relationships amongst the various factors affecting the economy or business. The expected values for dependent variables are then ascertained by putting the values of known variables in the model. This approach is highly mechanical and this can be rarely employed in business conditions.